Development of autonomous eating mechanism for biomimetic robots
NASA Astrophysics Data System (ADS)
Jeong, Kil-Woong; Cho, Ik-Jin; Lee, Yun-Jung
2005-12-01
Most of the recently developed robots are human friendly robots which imitate animals or humans such as entertainment robot, bio-mimetic robot and humanoid robot. Interest for these robots are being increased because the social trend is focused on health, welfare, and graying. Autonomous eating functionality is most unique and inherent behavior of pets and animals. Most of entertainment robots and pet robots make use of internal-type battery. Entertainment robots and pet robots with internal-type battery are not able to operate during charging the battery. Therefore, if a robot has an autonomous function for eating battery as its feeds, the robot is not only able to operate during recharging energy but also become more human friendly like pets. Here, a new autonomous eating mechanism was introduced for a biomimetic robot, called ELIRO-II(Eating LIzard RObot version 2). The ELIRO-II is able to find a food (a small battery), eat and evacuate by itself. This work describe sub-parts of the developed mechanism such as head-part, mouth-part, and stomach-part. In addition, control system of autonomous eating mechanism is described.
2014-07-16
Limbed robot RoboSimian was developed at NASA Jet Propulsion Laboratory, seen here with Brett Kennedy, supervisor of the JPL Robotic Vehicles and Manipulators Group, and Chuck Bergh, a senior engineer in JPL Robotic Hardware Systems Group.
PaR-PaR Laboratory Automation Platform
DOE Office of Scientific and Technical Information (OSTI.GOV)
Linshiz, G; Stawski, N; Poust, S
2013-05-01
Labor-intensive multistep biological tasks, such as the construction and cloning of DNA molecules, are prime candidates for laboratory automation. Flexible and biology-friendly operation of robotic equipment is key to its successful integration in biological laboratories, and the efforts required to operate a robot must be much smaller than the alternative manual lab work. To achieve these goals, a simple high-level biology-friendly robot programming language is needed. We have developed and experimentally validated such a language: Programming a Robot (PaR-PaR). The syntax and compiler for the language are based on computer science principles and a deep understanding of biological workflows. PaR-PaRmore » allows researchers to use liquid-handling robots effectively, enabling experiments that would not have been considered previously. After minimal training, a biologist can independently write complicated protocols for a robot within an hour. Adoption of PaR-PaR as a standard cross-platform language would enable hand-written or software-generated robotic protocols to be shared across laboratories.« less
PaR-PaR laboratory automation platform.
Linshiz, Gregory; Stawski, Nina; Poust, Sean; Bi, Changhao; Keasling, Jay D; Hillson, Nathan J
2013-05-17
Labor-intensive multistep biological tasks, such as the construction and cloning of DNA molecules, are prime candidates for laboratory automation. Flexible and biology-friendly operation of robotic equipment is key to its successful integration in biological laboratories, and the efforts required to operate a robot must be much smaller than the alternative manual lab work. To achieve these goals, a simple high-level biology-friendly robot programming language is needed. We have developed and experimentally validated such a language: Programming a Robot (PaR-PaR). The syntax and compiler for the language are based on computer science principles and a deep understanding of biological workflows. PaR-PaR allows researchers to use liquid-handling robots effectively, enabling experiments that would not have been considered previously. After minimal training, a biologist can independently write complicated protocols for a robot within an hour. Adoption of PaR-PaR as a standard cross-platform language would enable hand-written or software-generated robotic protocols to be shared across laboratories.
Robot-friendly connector. [space truss structures
NASA Technical Reports Server (NTRS)
Parma, George F. (Inventor); Vandeberghe, Mark H. (Inventor); Ruiz, Steve C. (Inventor)
1993-01-01
Robot friendly connectors, which, in one aspect, are truss joints with two parts, a receptacle and a joint, are presented. The joints have a head which is loosely inserted into the receptacle and is then tightened and aligned. In one aspect, the head is a rounded hammerhead which initially is enclosed in the receptacle with sloppy fit provided by the shape, size, and configuration of surfaces on the head and on the receptacle.
2009-07-19
MoonFest: From Apollo to LCROSS and Beyond public event at NASA'S Ames Researc Center, Moffett Field, Calif. The day included scientific talks, model rocket launches on the flight line, musical performances, family-friendly activities and more. Robot '971 Spartan Robotics' from the FIRST Robotic competition, demo their abilities.
Friends with Faces: How Social Networks Can Enhance Face Recognition and Vice Versa
NASA Astrophysics Data System (ADS)
Mavridis, Nikolaos; Kazmi, Wajahat; Toulis, Panos
The "friendship" relation, a social relation among individuals, is one of the primary relations modeled in some of the world's largest online social networking sites, such as "FaceBook." On the other hand, the "co-occurrence" relation, as a relation among faces appearing in pictures, is one that is easily detectable using modern face detection techniques. These two relations, though appearing in different realms (social vs. visual sensory), have a strong correlation: faces that co-occur in photos often belong to individuals who are friends. Using real-world data gathered from "Facebook," which were gathered as part of the "FaceBots" project, the world's first physical face-recognizing and conversing robot that can utilize and publish information on "Facebook" was established. We present here methods as well as results for utilizing this correlation in both directions. Both algorithms for utilizing knowledge of the social context for faster and better face recognition are given, as well as algorithms for estimating the friendship network of a number of individuals given photos containing their faces. The results are quite encouraging. In the primary example, doubling of the recognition accuracy as well as a sixfold improvement in speed is demonstrated. Various improvements, interesting statistics, as well as an empirical investigation leading to predictions of scalability to much bigger data sets are discussed.
The magic glove: a gesture-based remote controller for intelligent mobile robots
NASA Astrophysics Data System (ADS)
Luo, Chaomin; Chen, Yue; Krishnan, Mohan; Paulik, Mark
2012-01-01
This paper describes the design of a gesture-based Human Robot Interface (HRI) for an autonomous mobile robot entered in the 2010 Intelligent Ground Vehicle Competition (IGVC). While the robot is meant to operate autonomously in the various Challenges of the competition, an HRI is useful in moving the robot to the starting position and after run termination. In this paper, a user-friendly gesture-based embedded system called the Magic Glove is developed for remote control of a robot. The system consists of a microcontroller and sensors that is worn by the operator as a glove and is capable of recognizing hand signals. These are then transmitted through wireless communication to the robot. The design of the Magic Glove included contributions on two fronts: hardware configuration and algorithm development. A triple axis accelerometer used to detect hand orientation passes the information to a microcontroller, which interprets the corresponding vehicle control command. A Bluetooth device interfaced to the microcontroller then transmits the information to the vehicle, which acts accordingly. The user-friendly Magic Glove was successfully demonstrated first in a Player/Stage simulation environment. The gesture-based functionality was then also successfully verified on an actual robot and demonstrated to judges at the 2010 IGVC.
Xie, Chen; Tang, Xiaofeng; Berlinghof, Marvin; Langner, Stefan; Chen, Shi; Späth, Andreas; Li, Ning; Fink, Rainer H; Unruh, Tobias; Brabec, Christoph J
2018-06-27
Development of high-quality organic nanoparticle inks is a significant scientific challenge for the industrial production of solution-processed organic photovoltaics (OPVs) with eco-friendly processing methods. In this work, we demonstrate a novel, robot-based, high-throughput procedure performing automatic poly(3-hexylthio-phene-2,5-diyl) and indene-C 60 bisadduct nanoparticle ink synthesis in nontoxic alcohols. A novel methodology to prepare particle dispersions for fully functional OPVs by manipulating the particle size and solvent system was studied in detail. The ethanol dispersion with a particle diameter of around 80-100 nm exhibits reduced degradation, yielding a power conversion efficiency of 4.52%, which is the highest performance reported so far for water/alcohol-processed OPV devices. By successfully deploying the high-throughput robot-based approach for an organic nanoparticle ink preparation, we believe that the findings demonstrated in this work will trigger more research interest and effort on eco-friendly industrial production of OPVs.
Decentralized sensor fusion for Ubiquitous Networking Robotics in Urban Areas.
Sanfeliu, Alberto; Andrade-Cetto, Juan; Barbosa, Marco; Bowden, Richard; Capitán, Jesús; Corominas, Andreu; Gilbert, Andrew; Illingworth, John; Merino, Luis; Mirats, Josep M; Moreno, Plínio; Ollero, Aníbal; Sequeira, João; Spaan, Matthijs T J
2010-01-01
In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking Robotics in Urban Sites), a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted.
Energy optimization in mobile sensor networks
NASA Astrophysics Data System (ADS)
Yu, Shengwei
Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while consuming negligible amount of energy for mobility cost. For the second problem, the problem is extended to accommodate mobile robotic nodes with energy harvesting capability, which makes it a non-convex optimization problem. The non-convexity issue is tackled by using the existing sequential convex approximation method, based on which we propose a novel procedure of modified sequential convex approximation that has fast convergence speed. For the third problem, the proposed procedure is used to solve another challenging non-convex problem, which results in utilizing mobility and routing simultaneously in mobile robotic sensor networks to prolong the network lifetime. The results indicate that joint design of mobility and routing has an edge over other methods in prolonging network lifetime, which is also the justification for the use of mobility in mobile sensor networks for energy efficiency purpose. For the fourth problem, we include the dynamics of the robotic nodes in the problem by modeling the networked robotic system using hybrid systems theory. A novel distributed method for the networked hybrid system is used to solve the optimal moving trajectories for robotic nodes and optimal network links, which are not answered by previous approaches. Finally, the fact that mobility is more effective in prolonging network lifetime for a data-intensive network leads us to apply our methods to study mobile visual sensor networks, which are useful in many applications. We investigate the joint design of mobility, data routing, and encoding power to help improving the video quality while maximizing the network lifetime. This study leads to a better understanding of the role mobility can play in data-intensive surveillance sensor networks.
Decentralized Sensor Fusion for Ubiquitous Networking Robotics in Urban Areas
Sanfeliu, Alberto; Andrade-Cetto, Juan; Barbosa, Marco; Bowden, Richard; Capitán, Jesús; Corominas, Andreu; Gilbert, Andrew; Illingworth, John; Merino, Luis; Mirats, Josep M.; Moreno, Plínio; Ollero, Aníbal; Sequeira, João; Spaan, Matthijs T.J.
2010-01-01
In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking Robotics in Urban Sites), a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted. PMID:22294927
Using Empathy to Improve Human-Robot Relationships
NASA Astrophysics Data System (ADS)
Pereira, André; Leite, Iolanda; Mascarenhas, Samuel; Martinho, Carlos; Paiva, Ana
For robots to become our personal companions in the future, they need to know how to socially interact with us. One defining characteristic of human social behaviour is empathy. In this paper, we present a robot that acts as a social companion expressing different kinds of empathic behaviours through its facial expressions and utterances. The robot comments the moves of two subjects playing a chess game against each other, being empathic to one of them and neutral towards the other. The results of a pilot study suggest that users to whom the robot was empathic perceived the robot more as a friend.
Control of autonomous robot using neural networks
NASA Astrophysics Data System (ADS)
Barton, Adam; Volna, Eva
2017-07-01
The aim of the article is to design a method of control of an autonomous robot using artificial neural networks. The introductory part describes control issues from the perspective of autonomous robot navigation and the current mobile robots controlled by neural networks. The core of the article is the design of the controlling neural network, and generation and filtration of the training set using ART1 (Adaptive Resonance Theory). The outcome of the practical part is an assembled Lego Mindstorms EV3 robot solving the problem of avoiding obstacles in space. To verify models of an autonomous robot behavior, a set of experiments was created as well as evaluation criteria. The speed of each motor was adjusted by the controlling neural network with respect to the situation in which the robot was found.
NASA Astrophysics Data System (ADS)
Zheng, Taixiong
2005-12-01
A neuro-fuzzy network based approach for robot motion in an unknown environment was proposed. In order to control the robot motion in an unknown environment, the behavior of the robot was classified into moving to the goal and avoiding obstacles. Then, according to the dynamics of the robot and the behavior character of the robot in an unknown environment, fuzzy control rules were introduced to control the robot motion. At last, a 6-layer neuro-fuzzy network was designed to merge from what the robot sensed to robot motion control. After being trained, the network may be used for robot motion control. Simulation results show that the proposed approach is effective for robot motion control in unknown environment.
Prototyping and Simulation of Robot Group Intelligence using Kohonen Networks.
Wang, Zhijun; Mirdamadi, Reza; Wang, Qing
2016-01-01
Intelligent agents such as robots can form ad hoc networks and replace human being in many dangerous scenarios such as a complicated disaster relief site. This project prototypes and builds a computer simulator to simulate robot kinetics, unsupervised learning using Kohonen networks, as well as group intelligence when an ad hoc network is formed. Each robot is modeled using an object with a simple set of attributes and methods that define its internal states and possible actions it may take under certain circumstances. As the result, simple, reliable, and affordable robots can be deployed to form the network. The simulator simulates a group of robots as an unsupervised learning unit and tests the learning results under scenarios with different complexities. The simulation results show that a group of robots could demonstrate highly collaborative behavior on a complex terrain. This study could potentially provide a software simulation platform for testing individual and group capability of robots before the design process and manufacturing of robots. Therefore, results of the project have the potential to reduce the cost and improve the efficiency of robot design and building.
Prototyping and Simulation of Robot Group Intelligence using Kohonen Networks
Wang, Zhijun; Mirdamadi, Reza; Wang, Qing
2016-01-01
Intelligent agents such as robots can form ad hoc networks and replace human being in many dangerous scenarios such as a complicated disaster relief site. This project prototypes and builds a computer simulator to simulate robot kinetics, unsupervised learning using Kohonen networks, as well as group intelligence when an ad hoc network is formed. Each robot is modeled using an object with a simple set of attributes and methods that define its internal states and possible actions it may take under certain circumstances. As the result, simple, reliable, and affordable robots can be deployed to form the network. The simulator simulates a group of robots as an unsupervised learning unit and tests the learning results under scenarios with different complexities. The simulation results show that a group of robots could demonstrate highly collaborative behavior on a complex terrain. This study could potentially provide a software simulation platform for testing individual and group capability of robots before the design process and manufacturing of robots. Therefore, results of the project have the potential to reduce the cost and improve the efficiency of robot design and building. PMID:28540284
Light Robots: Bridging the Gap between Microrobotics and Photomechanics in Soft Materials.
Zeng, Hao; Wasylczyk, Piotr; Wiersma, Diederik S; Priimagi, Arri
2018-06-01
For decades, roboticists have focused their efforts on rigid systems that enable programmable, automated action, and sophisticated control with maximal movement precision and speed. Meanwhile, material scientists have sought compounds and fabrication strategies to devise polymeric actuators that are small, soft, adaptive, and stimuli-responsive. Merging these two fields has given birth to a new class of devices-soft microrobots that, by combining concepts from microrobotics and stimuli-responsive materials research, provide several advantages in a miniature form: external, remotely controllable power supply, adaptive motion, and human-friendly interaction, with device design and action often inspired by biological systems. Herein, recent progress in soft microrobotics is highlighted based on light-responsive liquid-crystal elastomers and polymer networks, focusing on photomobile devices such as walkers, swimmers, and mechanical oscillators, which may ultimately lead to flying microrobots. Finally, self-regulated actuation is proposed as a new pathway toward fully autonomous, intelligent light robots of the future. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Wave-variable framework for networked robotic systems with time delays and packet losses
NASA Astrophysics Data System (ADS)
Puah, Seng-Ming; Liu, Yen-Chen
2017-05-01
This paper investigates the problem of networked control system for nonlinear robotic manipulators under time delays and packet loss by using passivity technique. With the utilisation of wave variables and a passive remote controller, the networked robotic system is demonstrated to be stable with guaranteed position regulation. For the input/output signals of robotic systems, a discretisation block is exploited to convert continuous-time signals to discrete-time signals, and vice versa. Subsequently, we propose a packet management, called wave-variable modulation, to cope with the proposed networked robotic system under time delays and packet losses. Numerical examples and experimental results are presented to demonstrate the performance of the proposed wave-variable-based networked robotic systems.
Robopedia: Leveraging Sensorpedia for Web-Enabled Robot Control
DOE Office of Scientific and Technical Information (OSTI.GOV)
Resseguie, David R
There is a growing interest in building Internetscale sensor networks that integrate sensors from around the world into a single unified system. In contrast, robotics application development has primarily focused on building specialized systems. These specialized systems take scalability and reliability into consideration, but generally neglect exploring the key components required to build a large scale system. Integrating robotic applications with Internet-scale sensor networks will unify specialized robotics applications and provide answers to large scale implementation concerns. We focus on utilizing Internet-scale sensor network technology to construct a framework for unifying robotic systems. Our framework web-enables a surveillance robot smore » sensor observations and provides a webinterface to the robot s actuators. This lets robots seamlessly integrate into web applications. In addition, the framework eliminates most prerequisite robotics knowledge, allowing for the creation of general web-based robotics applications. The framework also provides mechanisms to create applications that can interface with any robot. Frameworks such as this one are key to solving large scale mobile robotics implementation problems. We provide an overview of previous Internetscale sensor networks, Sensorpedia (an ad-hoc Internet-scale sensor network), our framework for integrating robots with Sensorpedia, two applications which illustrate our frameworks ability to support general web-based robotic control, and offer experimental results that illustrate our framework s scalability, feasibility, and resource requirements.« less
Neural net target-tracking system using structured laser patterns
NASA Astrophysics Data System (ADS)
Cho, Jae-Wan; Lee, Yong-Bum; Lee, Nam-Ho; Park, Soon-Yong; Lee, Jongmin; Choi, Gapchu; Baek, Sunghyun; Park, Dong-Sun
1996-06-01
In this paper, we describe a robot endeffector tracking system using sensory information from recently-announced structured pattern laser diodes, which can generate images with several different types of structured pattern. The neural network approach is employed to recognize the robot endeffector covering the situation of three types of motion: translation, scaling and rotation. Features for the neural network to detect the position of the endeffector are extracted from the preprocessed images. Artificial neural networks are used to store models and to match with unknown input features recognizing the position of the robot endeffector. Since a minimal number of samples are used for different directions of the robot endeffector in the system, an artificial neural network with the generalization capability can be utilized for unknown input features. A feedforward neural network with the generalization capability can be utilized for unknown input features. A feedforward neural network trained with the back propagation learning is used to detect the position of the robot endeffector. Another feedforward neural network module is used to estimate the motion from a sequence of images and to control movements of the robot endeffector. COmbining the tow neural networks for recognizing the robot endeffector and estimating the motion with the preprocessing stage, the whole system keeps tracking of the robot endeffector effectively.
Should We Turn the Robots Loose?
2010-05-02
interference. Potential sources of electromagnetic interference include everyday signals such as cell phones and Wifi , intentional friendly jamming of IED...might even attempt to hack or hijack our robotic warriors. Our current enemies have proven to be very adaptable and have developed simple counters to our...demonstrates the ease with which robot command and control might be hacked . It is reasonable to suspect that a future threat with a more robust
Rachinger, Jens; Bumm, Klaus; Wurm, Jochen; Bohr, Christopher; Nissen, Urs; Dannenmann, Tim; Buchfelder, Michael; Iro, Heinrich; Nimsky, Christopher
2007-01-01
To introduce a new robotic system to the field of neurosurgery and report on a preliminary assessment of accuracy as well as on envisioned application concepts. Based on experience with another system (Evolution 1, URS Inc., Schwerin, Germany), technical advancements are discussed. The basic module is an industrial 6 degrees of freedom robotic arm with a modified control element. The system combines frameless stereotaxy, robotics, and endoscopy. The robotic reproducibility error and the overall error were evaluated. For accuracy testing CT markers were placed on a cadaveric head and pinpointed with the robot's tool tip, both fully automated and telemanipulatory. Applicability in a clinical setting, user friendliness, safety and flexibility were assessed. The new system is suitable for use in the neurosurgical operating theatre. Hard- and software are user-friendly and flexible. The mean reproducibility error was 0.052-0.062 mm, the mean overall error was 0.816 mm. The system is less cumbersome and much easier to use than the Evolution 1. With its user-friendly interface and reliable safety features, its high application accuracy and flexibility, the new system is a versatile robotic platform for various neurosurgical applications. Adaptations for different applications are currently being realized. Copyright (c) 2007 S. Karger AG, Basel.
Towards Human-Friendly Efficient Control of Multi-Robot Teams
NASA Technical Reports Server (NTRS)
Stoica, Adrian; Theodoridis, Theodoros; Barrero, David F.; Hu, Huosheng; McDonald-Maiers, Klaus
2013-01-01
This paper explores means to increase efficiency in performing tasks with multi-robot teams, in the context of natural Human-Multi-Robot Interfaces (HMRI) for command and control. The motivating scenario is an emergency evacuation by a transport convoy of unmanned ground vehicles (UGVs) that have to traverse, in shortest time, an unknown terrain. In the experiments the operator commands, in minimal time, a group of rovers through a maze. The efficiency of performing such tasks depends on both, the levels of robots' autonomy, and the ability of the operator to command and control the team. The paper extends the classic framework of levels of autonomy (LOA), to levels/hierarchy of autonomy characteristic of Groups (G-LOA), and uses it to determine new strategies for control. An UGVoriented command language (UGVL) is defined, and a mapping is performed from the human-friendly gesture-based HMRI into the UGVL. The UGVL is used to control a team of 3 robots, exploring the efficiency of different G-LOA; specifically, by (a) controlling each robot individually through the maze, (b) controlling a leader and cloning its controls to followers, and (c) controlling the entire group. Not surprisingly, commands at increased G-LOA lead to a faster traverse, yet a number of aspects are worth discussing in this context.
Friend suggestion in social network based on user log
NASA Astrophysics Data System (ADS)
Kaviya, R.; Vanitha, M.; Sumaiya Thaseen, I.; Mangaiyarkarasi, R.
2017-11-01
Simple friend recommendation algorithms such as similarity, popularity and social aspects is the basic requirement to be explored to methodically form high-performance social friend recommendation. Suggestion of friends is followed. No tags of character were followed. In the proposed system, we use an algorithm for network correlation-based social friend recommendation (NC-based SFR).It includes user activities like where one lives and works. A new friend recommendation method, based on network correlation, by considering the effect of different social roles. To model the correlation between different networks, we develop a method that aligns these networks through important feature selection. We consider by preserving the network structure for a more better recommendations so that it significantly improves the accuracy for better friend-recommendation.
Toward controlling perturbations in robotic sensor networks
NASA Astrophysics Data System (ADS)
Banerjee, Ashis G.; Majumder, Saikat R.
2014-06-01
Robotic sensor networks (RSNs), which consist of networks of sensors placed on mobile robots, are being increasingly used for environment monitoring applications. In particular, a lot of work has been done on simultaneous localization and mapping of the robots, and optimal sensor placement for environment state estimation1. The deployment of RSNs, however, remains challenging in harsh environments where the RSNs have to deal with significant perturbations in the forms of wind gusts, turbulent water flows, sand storms, or blizzards that disrupt inter-robot communication and individual robot stability. Hence, there is a need to be able to control such perturbations and bring the networks to desirable states with stable nodes (robots) and minimal operational performance (environment sensing). Recent work has demonstrated the feasibility of controlling the non-linear dynamics in other communication networks like emergency management systems and power grids by introducing compensatory perturbations to restore network stability and operation2. In this paper, we develop a computational framework to investigate the usefulness of this approach for RSNs in marine environments. Preliminary analysis shows promising performance and identifies bounds on the original perturbations within which it is possible to control the networks.
Deep Gate Recurrent Neural Network
2016-11-22
Schmidhuber. A system for robotic heart surgery that learns to tie knots using recurrent neural networks. In IEEE International Conference on...tasks, such as Machine Translation (Bahdanau et al. (2015)) or Robot Reinforcement Learning (Bakker (2001)). The main idea behind these networks is to...and J. Peters. Reinforcement learning in robotics : A survey. The International Journal of Robotics Research, 32:1238–1274, 2013. ISSN 0278-3649. doi
Biologically Inspired SNN for Robot Control.
Nichols, Eric; McDaid, Liam J; Siddique, Nazmul
2013-02-01
This paper proposes a spiking-neural-network-based robot controller inspired by the control structures of biological systems. Information is routed through the network using facilitating dynamic synapses with short-term plasticity. Learning occurs through long-term synaptic plasticity which is implemented using the temporal difference learning rule to enable the robot to learn to associate the correct movement with the appropriate input conditions. The network self-organizes to provide memories of environments that the robot encounters. A Pioneer robot simulator with laser and sonar proximity sensors is used to verify the performance of the network with a wall-following task, and the results are presented.
So Long, Robot Reader! A Superhero Intervention Plan for Improving Fluency
ERIC Educational Resources Information Center
Marcell, Barclay; Ferraro, Christine
2013-01-01
This article presents an engaging means for turning disfluent readers into prosody superstars. Each week students align with Poetry Power Man and his superhero friends to battle the evil Robot Reader and his sidekicks. The Fluency Foursome helps students adhere to the multidimensional aspects of fluency where expression and comprehension are…
Robot Tracer with Visual Camera
NASA Astrophysics Data System (ADS)
Jabbar Lubis, Abdul; Dwi Lestari, Yuyun; Dafitri, Haida; Azanuddin
2017-12-01
Robot is a versatile tool that can function replace human work function. The robot is a device that can be reprogrammed according to user needs. The use of wireless networks for remote monitoring needs can be utilized to build a robot that can be monitored movement and can be monitored using blueprints and he can track the path chosen robot. This process is sent using a wireless network. For visual robot using high resolution cameras to facilitate the operator to control the robot and see the surrounding circumstances.
Method for neural network control of motion using real-time environmental feedback
NASA Technical Reports Server (NTRS)
Buckley, Theresa M. (Inventor)
1997-01-01
A method of motion control for robotics and other automatically controlled machinery using a neural network controller with real-time environmental feedback. The method is illustrated with a two-finger robotic hand having proximity sensors and force sensors that provide environmental feedback signals. The neural network controller is taught to control the robotic hand through training sets using back- propagation methods. The training sets are created by recording the control signals and the feedback signal as the robotic hand or a simulation of the robotic hand is moved through a representative grasping motion. The data recorded is divided into discrete increments of time and the feedback data is shifted out of phase with the control signal data so that the feedback signal data lag one time increment behind the control signal data. The modified data is presented to the neural network controller as a training set. The time lag introduced into the data allows the neural network controller to account for the temporal component of the robotic motion. Thus trained, the neural network controlled robotic hand is able to grasp a wide variety of different objects by generalizing from the training sets.
Development of a telepresence robot for medical consultation
NASA Astrophysics Data System (ADS)
Bugtai, Nilo T.; Ong, Aira Patrice R.; Angeles, Patrick Bryan C.; Cervera, John Keen P.; Ganzon, Rachel Ann E.; Villanueva, Carlos A. G.; Maniquis, Samuel Nazirite F.
2017-02-01
There are numerous efforts to add value for telehealth applications in the country. In this study, the design of a telepresence doctor to facilitate remote medical consultations in the wards of Philippine General Hospital is proposed. This includes the design of a robot capable of performing a medical consultation with clear audio and video information for both ends. It also provides the operating doctor full control of the telepresence robot and gives a user-friendly interface for the controlling doctor. The results have shown that it provides a stable and reliable mobile medical service through the use of the telepresence robot.
Maintaining Limited-Range Connectivity Among Second-Order Agents
2016-07-07
we consider ad-hoc networks of robotic agents with double integrator dynamics. For such networks, the connectivity maintenance problems are: (i) do...hoc networks of mobile autonomous agents. This loose ter- minology refers to groups of robotic agents with limited mobility and communica- tion...connectivity can be preserved. 3.1. Networks of robotic agents with second-order dynamics and the connectivity maintenance problem. We begin by
High level functions for the intuitive use of an assistive robot.
Lebec, Olivier; Ben Ghezala, Mohamed Walid; Leynart, Violaine; Laffont, Isabelle; Fattal, Charles; Devilliers, Laurence; Chastagnol, Clement; Martin, Jean-Claude; Mezouar, Youcef; Korrapatti, Hermanth; Dupourqué, Vincent; Leroux, Christophe
2013-06-01
This document presents the research project ARMEN (Assistive Robotics to Maintain Elderly People in a Natural environment), aimed at the development of a user friendly robot with advanced functions for assistance to elderly or disabled persons at home. Focus is given to the robot SAM (Smart Autonomous Majordomo) and its new features of navigation, manipulation, object recognition, and knowledge representation developed for the intuitive supervision of the robot. The results of the technical evaluations show the value and potential of these functions for practical applications. The paper also documents the details of the clinical evaluations carried out with elderly and disabled persons in a therapeutic setting to validate the project.
A New Paradigm for Robotic Rovers
NASA Astrophysics Data System (ADS)
Clark, P. E.; Curtis, S. A.; Rilee, M. L.
We are in the process of developing rovers with extreme mobility needed to explore remote, rugged terrain. We call these systems Tetrahedral Explorer Technologies (TETs). Architecture is based on conformable tetrahedra, the simplest space-filling form, as building blocks, single or networked, where apices act as nodes from which struts reversibly deploy. The tetrahedral framework acts as a simple skeletal muscular structure. We have already prototyped a simple robotic walker from a single reconfigurable tetrahedron capable of tumbling and a more evolved 12Tetrahedral Walker, the Autonomous Landed Investigator (ALI), which has interior nodes for payload, more continuous motion, and is commandable through a user friendly interface. ALI is an EMS level mission concept which would allow autonomous in situ exploration of the lunar poles within the next decade. ALI would consist of one or more 12tetrahedral walkers capable of rapid locomotion with the many degrees of freedom and equipped for navigation in the unilluminated, inaccessible and thus largely unexplored rugged terrains where lunar resources are likely to be found: the Polar Regions. ALI walkers would act as roving reconnaissance teams for unexplored regions, analyzing samples along the way.
SWARMs Ontology: A Common Information Model for the Cooperation of Underwater Robots.
Li, Xin; Bilbao, Sonia; Martín-Wanton, Tamara; Bastos, Joaquim; Rodriguez, Jonathan
2017-03-11
In order to facilitate cooperation between underwater robots, it is a must for robots to exchange information with unambiguous meaning. However, heterogeneity, existing in information pertaining to different robots, is a major obstruction. Therefore, this paper presents a networked ontology, named the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) ontology, to address information heterogeneity and enable robots to have the same understanding of exchanged information. The SWARMs ontology uses a core ontology to interrelate a set of domain-specific ontologies, including the mission and planning, the robotic vehicle, the communication and networking, and the environment recognition and sensing ontology. In addition, the SWARMs ontology utilizes ontology constructs defined in the PR-OWL ontology to annotate context uncertainty based on the Multi-Entity Bayesian Network (MEBN) theory. Thus, the SWARMs ontology can provide both a formal specification for information that is necessarily exchanged between robots and a command and control entity, and also support for uncertainty reasoning. A scenario on chemical pollution monitoring is described and used to showcase how the SWARMs ontology can be instantiated, be extended, represent context uncertainty, and support uncertainty reasoning.
A motion sensing-based framework for robotic manipulation.
Deng, Hao; Xia, Zeyang; Weng, Shaokui; Gan, Yangzhou; Fang, Peng; Xiong, Jing
2016-01-01
To data, outside of the controlled environments, robots normally perform manipulation tasks operating with human. This pattern requires the robot operators with high technical skills training for varied teach-pendant operating system. Motion sensing technology, which enables human-machine interaction in a novel and natural interface using gestures, has crucially inspired us to adopt this user-friendly and straightforward operation mode on robotic manipulation. Thus, in this paper, we presented a motion sensing-based framework for robotic manipulation, which recognizes gesture commands captured from motion sensing input device and drives the action of robots. For compatibility, a general hardware interface layer was also developed in the framework. Simulation and physical experiments have been conducted for preliminary validation. The results have shown that the proposed framework is an effective approach for general robotic manipulation with motion sensing control.
Advanced wireless mobile collaborative sensing network for tactical and strategic missions
NASA Astrophysics Data System (ADS)
Xu, Hao
2017-05-01
In this paper, an advanced wireless mobile collaborative sensing network will be developed. Through properly combining wireless sensor network, emerging mobile robots and multi-antenna sensing/communication techniques, we could demonstrate superiority of developed sensing network. To be concrete, heterogeneous mobile robots including unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) are equipped with multi-model sensors and wireless transceiver antennas. Through real-time collaborative formation control, multiple mobile robots can team the best formation that can provide most accurate sensing results. Also, formatting multiple mobile robots can also construct a multiple-input multiple-output (MIMO) communication system that can provide a reliable and high performance communication network.
Feasibility of a Friendship Network-Based Pediatric Obesity Intervention.
Giannini, Courtney M; Irby, Megan B; Skelton, Joseph A; Gesell, Sabina B
2017-02-01
There is growing evidence supporting social network-based interventions for adolescents with obesity. This study's aim was to determine the feasibility of a social network-based intervention by assessing adolescents' friendship networks, willingness to involve friends in treatment, and how these factors influence enjoyment. Adolescents (N = 42) were recruited from a tertiary care obesity clinic. Participants gave a list of closest friends, friendship characteristics, and which of their friends they would involve in treatment. A subset (N = 14) participated in group treatment, were encouraged to bring friends, and invited to a second interview. Participants nominated a mean of 4.0 (standard deviation [SD] = 1.6) friends and were more likely to nominate closer friends (p = 0.003). Friends who attended group sessions were more likely to have multiple friendships in common with the participant's own network (p = 0.04). Involving friends in treatment is feasible and desired by adolescents and may be a novel approach for augmenting obesity treatment outcomes.
Collaboration of Miniature Multi-Modal Mobile Smart Robots over a Network
2015-08-14
theoretical research on mathematics of failures in sensor-network-based miniature multimodal mobile robots and electromechanical systems. The views...theoretical research on mathematics of failures in sensor-network-based miniature multimodal mobile robots and electromechanical systems. The...independently evolving research directions based on physics-based models of mechanical, electromechanical and electronic devices, operational constraints
An Intelligent Agent Approach for Teaching Neural Networks Using LEGO[R] Handy Board Robots
ERIC Educational Resources Information Center
Imberman, Susan P.
2004-01-01
In this article we describe a project for an undergraduate artificial intelligence class. The project teaches neural networks using LEGO[R] handy board robots. Students construct robots with two motors and two photosensors. Photosensors provide readings that act as inputs for the neural network. Output values power the motors and maintain the…
General visual robot controller networks via artificial evolution
NASA Astrophysics Data System (ADS)
Cliff, David; Harvey, Inman; Husbands, Philip
1993-08-01
We discuss recent results from our ongoing research concerning the application of artificial evolution techniques (i.e., an extended form of genetic algorithm) to the problem of developing `neural' network controllers for visually guided robots. The robot is a small autonomous vehicle with extremely low-resolution vision, employing visual sensors which could readily be constructed from discrete analog components. In addition to visual sensing, the robot is equipped with a small number of mechanical tactile sensors. Activity from the sensors is fed to a recurrent dynamical artificial `neural' network, which acts as the robot controller, providing signals to motors governing the robot's motion. Prior to presentation of new results, this paper summarizes our rationale and past work, which has demonstrated that visually guided control networks can arise without any explicit specification that visual processing should be employed: the evolutionary process opportunistically makes use of visual information if it is available.
NASA Technical Reports Server (NTRS)
Rodriguez, Guillermo (Editor)
1990-01-01
Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.
A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242)
Dülger, L. Canan; Kapucu, Sadettin
2016-01-01
This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot's joint angles. PMID:27610129
Almusawi, Ahmed R J; Dülger, L Canan; Kapucu, Sadettin
2016-01-01
This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot's joint angles.
Portable control device for networked mobile robots
Feddema, John T.; Byrne, Raymond H.; Bryan, Jon R.; Harrington, John J.; Gladwell, T. Scott
2002-01-01
A handheld control device provides a way for controlling one or multiple mobile robotic vehicles by incorporating a handheld computer with a radio board. The device and software use a personal data organizer as the handheld computer with an additional microprocessor and communication device on a radio board for use in controlling one robot or multiple networked robots.
Rumor Diffusion in an Interests-Based Dynamic Social Network
Mao, Xinjun; Guessoum, Zahia; Zhou, Huiping
2013-01-01
To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1) positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2) with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3) a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4) a network with a smaller clustering coefficient has a larger efficiency. PMID:24453911
Rumor diffusion in an interests-based dynamic social network.
Tang, Mingsheng; Mao, Xinjun; Guessoum, Zahia; Zhou, Huiping
2013-01-01
To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1) positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2) with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3) a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4) a network with a smaller clustering coefficient has a larger efficiency.
Intelligent manipulation technique for multi-branch robotic systems
NASA Technical Reports Server (NTRS)
Chen, Alexander Y. K.; Chen, Eugene Y. S.
1990-01-01
New analytical development in kinematics planning is reported. The INtelligent KInematics Planner (INKIP) consists of the kinematics spline theory and the adaptive logic annealing process. Also, a novel framework of robot learning mechanism is introduced. The FUzzy LOgic Self Organized Neural Networks (FULOSONN) integrates fuzzy logic in commands, control, searching, and reasoning, the embedded expert system for nominal robotics knowledge implementation, and the self organized neural networks for the dynamic knowledge evolutionary process. Progress on the mechanical construction of SRA Advanced Robotic System (SRAARS) and the real time robot vision system is also reported. A decision was made to incorporate the Local Area Network (LAN) technology in the overall communication system.
Lee, Woo Jin; Lee, Won Kyung
2016-01-01
Because of the remarkable developments in robotics in recent years, technological convergence has been active in this area. We focused on finding patterns of convergence within robot technology using network analysis of patents in both the USPTO and KIPO. To identify the variables that affect convergence, we used quadratic assignment procedures (QAP). From our analysis, we observed the patent network ecology related to convergence and found technologies that have great potential to converge with other robotics technologies. The results of our study are expected to contribute to setting up convergence based R&D policies for robotics, which can lead new innovation. PMID:27764196
Design guidelines for robotically serviceable hardware
NASA Technical Reports Server (NTRS)
Gordon, Scott A.
1988-01-01
Research being conducted at the Goddard Space Flight Center into the development of guidelines for the design of robotically serviceable spaceflight hardware is described. A mock-up was built based on an existing spaceflight system demonstrating how these guidelines can be applied to actual hardware. The report examines the basic servicing philosophy being studied and how this philosophy is reflected in the formulation of design guidelines for robotic servicing. A description of the mock-up is presented with emphasis on the design features that make it robot friendly. Three robotic servicing schemes fulfilling the design guidelines were developed for the mock-up. These servicing schemes are examined as to how their implementation was affected by the constraints of the spacecraft system on which the mock-up is based.
SWARMs Ontology: A Common Information Model for the Cooperation of Underwater Robots
Li, Xin; Bilbao, Sonia; Martín-Wanton, Tamara; Bastos, Joaquim; Rodriguez, Jonathan
2017-01-01
In order to facilitate cooperation between underwater robots, it is a must for robots to exchange information with unambiguous meaning. However, heterogeneity, existing in information pertaining to different robots, is a major obstruction. Therefore, this paper presents a networked ontology, named the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) ontology, to address information heterogeneity and enable robots to have the same understanding of exchanged information. The SWARMs ontology uses a core ontology to interrelate a set of domain-specific ontologies, including the mission and planning, the robotic vehicle, the communication and networking, and the environment recognition and sensing ontology. In addition, the SWARMs ontology utilizes ontology constructs defined in the PR-OWL ontology to annotate context uncertainty based on the Multi-Entity Bayesian Network (MEBN) theory. Thus, the SWARMs ontology can provide both a formal specification for information that is necessarily exchanged between robots and a command and control entity, and also support for uncertainty reasoning. A scenario on chemical pollution monitoring is described and used to showcase how the SWARMs ontology can be instantiated, be extended, represent context uncertainty, and support uncertainty reasoning. PMID:28287468
Li, Yongcheng; Sun, Rong; Wang, Yuechao; Li, Hongyi; Zheng, Xiongfei
2016-01-01
We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning). Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle) to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot's performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks.
Reward-Modulated Hebbian Plasticity as Leverage for Partially Embodied Control in Compliant Robotics
Burms, Jeroen; Caluwaerts, Ken; Dambre, Joni
2015-01-01
In embodied computation (or morphological computation), part of the complexity of motor control is offloaded to the body dynamics. We demonstrate that a simple Hebbian-like learning rule can be used to train systems with (partial) embodiment, and can be extended outside of the scope of traditional neural networks. To this end, we apply the learning rule to optimize the connection weights of recurrent neural networks with different topologies and for various tasks. We then apply this learning rule to a simulated compliant tensegrity robot by optimizing static feedback controllers that directly exploit the dynamics of the robot body. This leads to partially embodied controllers, i.e., hybrid controllers that naturally integrate the computations that are performed by the robot body into a neural network architecture. Our results demonstrate the universal applicability of reward-modulated Hebbian learning. Furthermore, they demonstrate the robustness of systems trained with the learning rule. This study strengthens our belief that compliant robots should or can be seen as computational units, instead of dumb hardware that needs a complex controller. This link between compliant robotics and neural networks is also the main reason for our search for simple universal learning rules for both neural networks and robotics. PMID:26347645
Path optimisation of a mobile robot using an artificial neural network controller
NASA Astrophysics Data System (ADS)
Singh, M. K.; Parhi, D. R.
2011-01-01
This article proposed a novel approach for design of an intelligent controller for an autonomous mobile robot using a multilayer feed forward neural network, which enables the robot to navigate in a real world dynamic environment. The inputs to the proposed neural controller consist of left, right and front obstacle distance with respect to its position and target angle. The output of the neural network is steering angle. A four layer neural network has been designed to solve the path and time optimisation problem of mobile robots, which deals with the cognitive tasks such as learning, adaptation, generalisation and optimisation. A back propagation algorithm is used to train the network. This article also analyses the kinematic design of mobile robots for dynamic movements. The simulation results are compared with experimental results, which are satisfactory and show very good agreement. The training of the neural nets and the control performance analysis has been done in a real experimental setup.
Tele-rehabilitation using in-house wearable ankle rehabilitation robot.
Jamwal, Prashant K; Hussain, Shahid; Mir-Nasiri, Nazim; Ghayesh, Mergen H; Xie, Sheng Q
2018-01-01
This article explores wide-ranging potential of the wearable ankle robot for in-house rehabilitation. The presented robot has been conceptualized following a brief analysis of the existing technologies, systems, and solutions for in-house physical ankle rehabilitation. Configuration design analysis and component selection for ankle robot have been discussed as part of the conceptual design. The complexities of human robot interaction are closely encountered while maneuvering a rehabilitation robot. We present a fuzzy logic-based controller to perform the required robot-assisted ankle rehabilitation treatment. Designs of visual haptic interfaces have also been discussed, which will make the treatment interesting, and the subject will be motivated to exert more and regain lost functions rapidly. The complex nature of web-based communication between user and remotely sitting physiotherapy staff has also been discussed. A high-level software architecture appended with robot ensures user-friendly operations. This software is made up of three important components: patient-related database, graphical user interface (GUI), and a library of exercises creating virtual reality-specifically developed for ankle rehabilitation.
Adaptive categorization of ART networks in robot behavior learning using game-theoretic formulation.
Fung, Wai-keung; Liu, Yun-hui
2003-12-01
Adaptive Resonance Theory (ART) networks are employed in robot behavior learning. Two of the difficulties in online robot behavior learning, namely, (1) exponential memory increases with time, (2) difficulty for operators to specify learning tasks accuracy and control learning attention before learning. In order to remedy the aforementioned difficulties, an adaptive categorization mechanism is introduced in ART networks for perceptual and action patterns categorization in this paper. A game-theoretic formulation of adaptive categorization for ART networks is proposed for vigilance parameter adaptation for category size control on the categories formed. The proposed vigilance parameter update rule can help improving categorization performance in the aspect of category number stability and solve the problem of selecting initial vigilance parameter prior to pattern categorization in traditional ART networks. Behavior learning using physical robot is conducted to demonstrate the effectiveness of the proposed adaptive categorization mechanism in ART networks.
USAR Robot Communication Using ZigBee Technology
NASA Astrophysics Data System (ADS)
Tsui, Charles; Carnegie, Dale; Pan, Qing Wei
This paper reports the successful development of an automatic routing wireless network for USAR (urban search and rescue) robots in an artificial rubble environment. The wireless network was formed using ZigBee modules and each module was attached to a micro-controller in order to model a wireless USAR robot. Proof of concept experiments were carried out by deploying the networked robots into artificial rubble. The rubble was simulated by connecting holes and trenches that were dug in 50 cm deep soil. The simulated robots were placed in the bottom of the holes. The holes and trenches were then covered up by various building materials and soil to simulate a real rubble environment. Experiments demonstrated that a monitoring computer placed 10 meters outside the rubble can establish proper communication with all robots inside the artificial rubble environment.
Challenges of In Space Robotic Servicing
NASA Technical Reports Server (NTRS)
Roberts, Brian John
2015-01-01
As future space missions extend beyond the friendly confines of low earth orbit, robots are becoming an increasingly vital component on flight manifests. While the main focus to-date has been on satellite servicing due to its high commercial potential, robots are also being considered for orbital debris removal, space construction, and asteroid sample retrieval. The robotic technologies and automation required to carry out these missions represent a significant advancement beyond the manipulation technology used previously on the Space Shuttle, the International Space Station, and planetary rovers. While higher demands are being driven by the more ambitious nature of the tasks, the handling of uncooperative targets such as satellites and asteroids, present a greater challenge.
A new neural net approach to robot 3D perception and visuo-motor coordination
NASA Technical Reports Server (NTRS)
Lee, Sukhan
1992-01-01
A novel neural network approach to robot hand-eye coordination is presented. The approach provides a true sense of visual error servoing, redundant arm configuration control for collision avoidance, and invariant visuo-motor learning under gazing control. A 3-D perception network is introduced to represent the robot internal 3-D metric space in which visual error servoing and arm configuration control are performed. The arm kinematic network performs the bidirectional association between 3-D space arm configurations and joint angles, and enforces the legitimate arm configurations. The arm kinematic net is structured by a radial-based competitive and cooperative network with hierarchical self-organizing learning. The main goal of the present work is to demonstrate that the neural net representation of the robot 3-D perception net serves as an important intermediate functional block connecting robot eyes and arms.
Le, Duc Van; Oh, Hoon; Yoon, Seokhoon
2013-07-05
In a practical deployment, mobile sensor network (MSN) suffers from a low performance due to high node mobility, time-varying wireless channel properties, and obstacles between communicating nodes. In order to tackle the problem of low network performance and provide a desired end-to-end data transfer quality, in this paper we propose a novel ad hoc routing and relaying architecture, namely RoCoMAR (Robots' Controllable Mobility Aided Routing) that uses robotic nodes' controllable mobility. RoCoMAR repeatedly performs link reinforcement process with the objective of maximizing the network throughput, in which the link with the lowest quality on the path is identified and replaced with high quality links by placing a robotic node as a relay at an optimal position. The robotic node resigns as a relay if the objective is achieved or no more gain can be obtained with a new relay. Once placed as a relay, the robotic node performs adaptive link maintenance by adjusting its position according to the movements of regular nodes. The simulation results show that RoCoMAR outperforms existing ad hoc routing protocols for MSN in terms of network throughput and end-to-end delay.
Van Le, Duc; Oh, Hoon; Yoon, Seokhoon
2013-01-01
In a practical deployment, mobile sensor network (MSN) suffers from a low performance due to high node mobility, time-varying wireless channel properties, and obstacles between communicating nodes. In order to tackle the problem of low network performance and provide a desired end-to-end data transfer quality, in this paper we propose a novel ad hoc routing and relaying architecture, namely RoCoMAR (Robots' Controllable Mobility Aided Routing) that uses robotic nodes' controllable mobility. RoCoMAR repeatedly performs link reinforcement process with the objective of maximizing the network throughput, in which the link with the lowest quality on the path is identified and replaced with high quality links by placing a robotic node as a relay at an optimal position. The robotic node resigns as a relay if the objective is achieved or no more gain can be obtained with a new relay. Once placed as a relay, the robotic node performs adaptive link maintenance by adjusting its position according to the movements of regular nodes. The simulation results show that RoCoMAR outperforms existing ad hoc routing protocols for MSN in terms of network throughput and end-to-end delay. PMID:23881134
The European Hands-On Universe project
NASA Astrophysics Data System (ADS)
Ferlet, Roger
2012-07-01
The EU-HOU project is a wide collaboration of teachers and scientists with the purpose of creating a way for pupils to get excited by science, primarily through the use of astronomy. EU-HOU gives pupils the chance to use real astronomical data to investigate research questions such as how to detect an extrasolar planet, identify the black hole at the center of the Milky Way, or discover the existence of dark matter. EU-HOU provides also the opportunity of real time sky observations through networks of robotic optical and radio telescopes via the Internet, together with pupil-friendly software to analyse the data. EU-HOU offers teachers incentives and advice through class-ready resources directly inspired from modern research, which can engage students in the wonder of scientific discovery and develop their creative thinking.
Neural network-based landmark detection for mobile robot
NASA Astrophysics Data System (ADS)
Sekiguchi, Minoru; Okada, Hiroyuki; Watanabe, Nobuo
1996-03-01
The mobile robot can essentially have only the relative position data for the real world. However, there are many cases that the robot has to know where it is located. In those cases, the useful method is to detect landmarks in the real world and adjust its position using detected landmarks. In this point of view, it is essential to develop a mobile robot that can accomplish the path plan successfully using natural or artificial landmarks. However, artificial landmarks are often difficult to construct and natural landmarks are very complicated to detect. In this paper, the method of acquiring landmarks by using the sensor data from the mobile robot necessary for planning the path is described. The landmark we discuss here is the natural one and is composed of the compression of sensor data from the robot. The sensor data is compressed and memorized by using five layered neural network that is called a sand glass model. The input and output data that neural network should learn is the sensor data of the robot that are exactly the same. Using the intermediate output data of the network, a compressed data is obtained, which expresses a landmark data. If the sensor data is ambiguous or enormous, it is easy to detect the landmark because the data is compressed and classified by the neural network. Using the backward three layers, the compressed landmark data is expanded to original data at some level. The studied neural network categorizes the detected sensor data to the known landmark.
Eddie, David; Kelly, John F
2017-06-01
Having high-risk, substance-using friends is associated with young adult substance use disorder (SUD) relapse. It is unclear, however, whether it is the total number of high-risk friends, or the amount of time spent with high-risk friends that leads to relapse. Unclear also, is to what extent low-risk friends buffer risk. This study examined the influence of number of high-risk and low-risk friends, and the amount time spent with these friends on post-treatment percent days abstinent (PDA). Young adult inpatients (N=302) were assessed at intake, and 3, 6, and 12 months on social network measures and PDA. Mixed models tested for effects of number of high- and low-risk friends, and time spent with these friends on PDA, and for net-risk friend effects to test whether low-risk friends offset risk. Within and across assessments, number of, and time spent with high-risk friends was negatively associated with PDA, while the inverse was true for low-risk friends. Early post-treatment, time spent with friends more strongly predicted PDA than number of friends. Participants were more deleteriously affected by time with high-risk friends the longer they were out of treatment, while contemporaneously protection conferred by low-risk friends increased. This interaction effect, however, was not observed with number of high- or low-risk friends, or number of friends net-risk. Young adult SUD patients struggling to break ties with high-risk friends should be encouraged to minimize time with them. Clinicians should also encourage patients to grow their social network of low-risk friends. Copyright © 2017 Elsevier B.V. All rights reserved.
Social Balance on Networks: The Dynamics of Friendship and Hatred
NASA Astrophysics Data System (ADS)
Redner, Sidney
2006-03-01
We study the evolution of social networks that contain both friendly and unfriendly pairwise links between individual nodes. The network is endowed with dynamics in which the sense of a link in an imbalanced triad---a triangular loop with 1 or 3 unfriendly links---is reversed to make the triad balanced. Thus an imbalanced triad is analogous to a frustrated plaquette in a random magnet, while a balanced triad fulfills the adage: ``a friend of my friend is my friend; an enemy of my friend is my enemy; a friend of my enemy is my enemy; an enemy of my enemy is my friend.'' With this frustration-reducing dynamics, an infinite network undergoes a dynamic phase transition from a steady state to ``paradise''---all links are friendly---as the propensity for friendly links to be created in an update event passes through 1/2. On the other hand, a finite network always falls into a socially-balanced absorbing state where no imbalanced triads remain. A prominent example of the achievement of social balance is the evolution of pacts and treaties between various European countries during the late 1800's and early 1900's. Here social balance gave rise to the two major alliances that comprised the protagonists of World War I.
Raacke, John; Bonds-Raacke, Jennifer
2008-04-01
The increased use of the Internet as a new tool in communication has changed the way people interact. This fact is even more evident in the recent development and use of friend-networking sites. However, no research has evaluated these sites and their impact on college students. Therefore, the present study was conducted to evaluate: (a) why people use these friend-networking sites, (b) what the characteristics are of the typical college user, and (c) what uses and gratifications are met by using these sites. Results indicated that the vast majority of college students are using these friend-networking sites for a significant portion of their day for reasons such as making new friends and locating old friends. Additionally, both men and women of traditional college age are equally engaging in this form of online communication with this result holding true for nearly all ethnic groups. Finally, results showed that many uses and gratifications are met by users (e.g., "keeping in touch with friends"). Results are discussed in light of the impact that friend-networking sites have on communication and social needs of college students.
Guaranteeing Spoof-Resilient Multi-Robot Networks
2015-05-12
particularly challenging attack on this assumption is the so-called “Sybil attack.” In a Sybil attack a malicious agent can generate (or spoof) a large...cybersecurity in general multi-node networks (e.g. a wired LAN), the same is not true for multi- robot networks [14, 28], leaving them largely vulnerable...key passing or cryptographic authen- tication is difficult to maintain due to the highly dynamic and distributed nature of multi-robot teams where
Park, N S; Jang, Y; Lee, B S; Chiriboga, D A; Chang, S; Kim, S Y
2018-05-01
The objectives of this study were to (1) develop an empirical typology of social networks in older Koreans; and (2) examine its effect on physical and mental health. A sample of 6900 community-dwelling older adults in South Korea was drawn from the 2014 Korean National Elderly Survey. Latent profile analysis (LPA) was conducted to derive social network types using eight common social network characteristics (marital status, living arrangement, the number and frequency of contact with close family/relatives, the number and frequency of contact with close friends, frequency of participation in social activities, and frequency of having visitors at home). The identified typologies were then regressed on self-rated health and depressive symptoms to explore the health risks posed by the group membership. The LPA identified a model with five types of social network as being most optimal (BIC = 153,848.34, entropy = .90). The groups were named diverse/family (enriched networks with more engagement with family), diverse/friend (enriched networks with more engagement with friends), friend-focused (high engagement with friends), distant (structurally disengaged), and restricted (structurally engaged but disengaged in family/friends networks). A series of regression analyses showed that membership in the restricted type was associated with more health and mental health risks than all types of social networks except the distant type. Findings demonstrate the importance of family and friends as a source of social network and call attention to not only structural but also non-structural aspects of social isolation. Findings and implications are discussed in cultural contexts.
The Unified Behavior Framework for the Simulation of Autonomous Agents
2015-03-01
1980s, researchers have designed a variety of robot control architectures intending to imbue robots with some degree of autonomy. A recently developed ...Identification Friend or Foe viii THE UNIFIED BEHAVIOR FRAMEWORK FOR THE SIMULATION OF AUTONOMOUS AGENTS I. Introduction The development of autonomy has...room for research by utilizing methods like simulation and modeling that consume less time and fewer monetary resources. A recently developed reactive
High-Repeatability, Robot Friendly, ORU Interface
NASA Technical Reports Server (NTRS)
Voellmer, George M. (Inventor)
1992-01-01
A robot-friendly coupling device for an Orbital Replacement Unit (ORU). The invention will provide a coupling that is detached and attached remotely by a robot. The design of the coupling must allow for slight misalignments, over torque protection, and precision placement. This is accomplished by using of a triangular interface having three components. A base plate assembly is located on an attachment surface, such as a satellite. The base plate assembly has a cup member, a slotted member, and a post member. The ORU that the robot attaches to the base plate assembly has an ORU plate assembly with two cone members and a post member which mate to the base plate assembly. As the two plates approach one another, one cone member of the ORU plate assembly only has to be placed accurately enough to fall into the cup member of the base plate assembly. The cup forces alignment until a second cone falls into a slotted member which provides final alignment. A single bolt is used to attach the two plates. Two deflecting plates are attached to the backs of the plates. When pressure is applied to the center of the deflecting plates, the force is distributed preventing the ORU & base plates from deflecting. This accounts for precision in the placement of the article.
Diverse Friendship Networks and Heterogeneous Peer Effects on Adolescent Misbehaviors
ERIC Educational Resources Information Center
Xu, Yilan; Fan, Linlin
2018-01-01
This study estimates peer effects in diverse friendship networks by friend types. Evidence from friendship networks for 57,351 U.S. high school adolescents demonstrates that adolescents are more likely to make friends with someone of the same immigrant status or ethnicity ('similar friends') than those with different backgrounds ('dissimilar…
Framework and Method for Controlling a Robotic System Using a Distributed Computer Network
NASA Technical Reports Server (NTRS)
Sanders, Adam M. (Inventor); Strawser, Philip A. (Inventor); Barajas, Leandro G. (Inventor); Permenter, Frank Noble (Inventor)
2015-01-01
A robotic system for performing an autonomous task includes a humanoid robot having a plurality of compliant robotic joints, actuators, and other integrated system devices that are controllable in response to control data from various control points, and having sensors for measuring feedback data at the control points. The system includes a multi-level distributed control framework (DCF) for controlling the integrated system components over multiple high-speed communication networks. The DCF has a plurality of first controllers each embedded in a respective one of the integrated system components, e.g., the robotic joints, a second controller coordinating the components via the first controllers, and a third controller for transmitting a signal commanding performance of the autonomous task to the second controller. The DCF virtually centralizes all of the control data and the feedback data in a single location to facilitate control of the robot across the multiple communication networks.
Seelye, Adriana M; Wild, Katherine V; Larimer, Nicole; Maxwell, Shoshana; Kearns, Peter; Kaye, Jeffrey A
2012-12-01
Remote telepresence provided by tele-operated robotics represents a new means for obtaining important health information, improving older adults' social and daily functioning and providing peace of mind to family members and caregivers who live remotely. In this study we tested the feasibility of use and acceptance of a remotely controlled robot with video-communication capability in independently living, cognitively intact older adults. A mobile remotely controlled robot with video-communication ability was placed in the homes of eight seniors. The attitudes and preferences of these volunteers and those of family or friends who communicated with them remotely via the device were assessed through survey instruments. Overall experiences were consistently positive, with the exception of one user who subsequently progressed to a diagnosis of mild cognitive impairment. Responses from our participants indicated that in general they appreciated the potential of this technology to enhance their physical health and well-being, social connectedness, and ability to live independently at home. Remote users, who were friends or adult children of the participants, were more likely to test the mobility features and had several suggestions for additional useful applications. Results from the present study showed that a small sample of independently living, cognitively intact older adults and their remote collaterals responded positively to a remote controlled robot with video-communication capabilities. Research is needed to further explore the feasibility and acceptance of this type of technology with a variety of patients and their care contacts.
Wang, Yuechao; Li, Hongyi; Zheng, Xiongfei
2016-01-01
We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning). Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle) to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot’s performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks. PMID:27806074
Reinterpretaion of the friendship paradox
NASA Astrophysics Data System (ADS)
Fu, Jingcheng; Wu, Jianliang
The friendship paradox (FP) is a sociological phenomenon stating that most people have fewer friends than their friends do. It is to say that in a social network, the number of friends that most individuals have is smaller than the average number of friends of friends. This has been verified by Feld. We call this interpreting method mean value version. But is it the best choice to portray the paradox? In this paper, we propose a probability method to reinterpret this paradox, and we illustrate that the explanation using our method is more persuasive. An individual satisfies the FP if his (her) randomly chosen friend has more friends than him (her) with probability not less than 1/2. Comparing the ratios of nodes satisfying the FP in networks, rp, we can see that the probability version is stronger than the mean value version in real networks both online and offline. We also show some results about the effects of several parameters on rp in random network models. Most importantly, rp is a quadratic polynomial of the power law exponent γ in Price model, and rp is higher when the average clustering coefficient is between 0.4 and 0.5 in Petter-Beom (PB) model. The introduction of the probability method to FP can shed light on understanding the network structure in complex networks especially in social networks.
Robustness of a distributed neural network controller for locomotion in a hexapod robot
NASA Technical Reports Server (NTRS)
Chiel, Hillel J.; Beer, Randall D.; Quinn, Roger D.; Espenschied, Kenneth S.
1992-01-01
A distributed neural-network controller for locomotion, based on insect neurobiology, has been used to control a hexapod robot. How robust is this controller? Disabling any single sensor, effector, or central component did not prevent the robot from walking. Furthermore, statically stable gaits could be established using either sensor input or central connections. Thus, a complex interplay between central neural elements and sensor inputs is responsible for the robustness of the controller and its ability to generate a continuous range of gaits. These results suggest that biologically inspired neural-network controllers may be a robust method for robotic control.
Ethnic Differences among Friend Networks Later in Life
ERIC Educational Resources Information Center
Kang, Hyunsook; Hebert, Corie
2014-01-01
This study seeks to broaden the understanding of friend relationships in older adults and the differences in those friend relationships among various ethnic groups. Secondary data from the National Social Life, Health and Aging Project (NSHAP) was analyzed to test the hypothesis that Caucasian older adults have stronger friend networks than older…
Cellular-level surgery using nano robots.
Song, Bo; Yang, Ruiguo; Xi, Ning; Patterson, Kevin Charles; Qu, Chengeng; Lai, King Wai Chiu
2012-12-01
The atomic force microscope (AFM) is a popular instrument for studying the nano world. AFM is naturally suitable for imaging living samples and measuring mechanical properties. In this article, we propose a new concept of an AFM-based nano robot that can be applied for cellular-level surgery on living samples. The nano robot has multiple functions of imaging, manipulation, characterizing mechanical properties, and tracking. In addition, the technique of tip functionalization allows the nano robot the ability for precisely delivering a drug locally. Therefore, the nano robot can be used for conducting complicated nano surgery on living samples, such as cells and bacteria. Moreover, to provide a user-friendly interface, the software in this nano robot provides a "videolized" visual feedback for monitoring the dynamic changes on the sample surface. Both the operation of nano surgery and observation of the surgery results can be simultaneously achieved. This nano robot can be easily integrated with extra modules that have the potential applications of characterizing other properties of samples such as local conductance and capacitance.
The mechanical design of a humanoid robot with flexible skin sensor for use in psychiatric therapy
NASA Astrophysics Data System (ADS)
Burns, Alec; Tadesse, Yonas
2014-03-01
In this paper, a humanoid robot is presented for ultimate use in the rehabilitation of children with mental disorders, such as autism. Creating affordable and efficient humanoids could assist the therapy in psychiatric disability by offering multimodal communication between the humanoid and humans. Yet, the humanoid development needs a seamless integration of artificial muscles, sensors, controllers and structures. We have designed a human-like robot that has 15 DOF, 580 mm tall and 925 mm arm span using a rapid prototyping system. The robot has a human-like appearance and movement. Flexible sensors around the arm and hands for safe human-robot interactions, and a two-wheel mobile platform for maneuverability are incorporated in the design. The robot has facial features for illustrating human-friendly behavior. The mechanical design of the robot and the characterization of the flexible sensors are presented. Comprehensive study on the upper body design, mobile base, actuators selection, electronics, and performance evaluation are included in this paper.
MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers
Allot, Alexis; Chennen, Kirsley; Nevers, Yannis; Poidevin, Laetitia; Kress, Arnaud; Ripp, Raymond; Thompson, Julie Dawn; Poch, Olivier
2017-01-01
Background The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.0 and particularly social networks, which are at the forefront of big data exploration and human-data interaction. Objective MyGeneFriends is a Web platform inspired by social networks, devoted to genetic disease analysis, and organized around three types of proactive agents: genes, humans, and genetic diseases. The aim of this study was to improve exploration and exploitation of biological, postgenomic era big data. Methods MyGeneFriends leverages conventions popularized by top social networks (Facebook, LinkedIn, etc), such as networks of friends, profile pages, friendship recommendations, affinity scores, news feeds, content recommendation, and data visualization. Results MyGeneFriends provides simple and intuitive interactions with data through evaluation and visualization of connections (friendships) between genes, humans, and diseases. The platform suggests new friends and publications and allows agents to follow the activity of their friends. It dynamically personalizes information depending on the user’s specific interests and provides an efficient way to share information with collaborators. Furthermore, the user’s behavior itself generates new information that constitutes an added value integrated in the network, which can be used to discover new connections between biological agents. Conclusions We have developed MyGeneFriends, a Web platform leveraging conventions from popular social networks to redefine the relationship between humans and biological big data and improve human processing of biomedical data. MyGeneFriends is available at lbgi.fr/mygenefriends. PMID:28623182
Addressing the Movement of a Freescale Robotic Car Using Neural Network
NASA Astrophysics Data System (ADS)
Horváth, Dušan; Cuninka, Peter
2016-12-01
This article deals with the management of a Freescale small robotic car along the predefined guide line. Controlling of the direction of movement of the robot is performed by neural networks, and scales (memory) of neurons are calculated by Hebbian learning from the truth tables as learning with a teacher. Reflexive infrared sensors serves as inputs. The results are experiments, which are used to compare two methods of mobile robot control - tracking lines.
Dynamical network interactions in distributed control of robots
NASA Astrophysics Data System (ADS)
Buscarino, Arturo; Fortuna, Luigi; Frasca, Mattia; Rizzo, Alessandro
2006-03-01
In this paper the dynamical network model of the interactions within a group of mobile robots is investigated and proposed as a possible strategy for controlling the robots without central coordination. Motivated by the results of the analysis of our simple model, we show that the system performance in the presence of noise can be improved by including long-range connections between the robots. Finally, a suitable strategy based on this model to control exploration and transport is introduced.
Technology demonstration of space intravehicular automation and robotics
NASA Technical Reports Server (NTRS)
Morris, A. Terry; Barker, L. Keith
1994-01-01
Automation and robotic technologies are being developed and capabilities demonstrated which would increase the productivity of microgravity science and materials processing in the space station laboratory module, especially when the crew is not present. The Automation Technology Branch at NASA Langley has been working in the area of intravehicular automation and robotics (IVAR) to provide a user-friendly development facility, to determine customer requirements for automated laboratory systems, and to improve the quality and efficiency of commercial production and scientific experimentation in space. This paper will describe the IVAR facility and present the results of a demonstration using a simulated protein crystal growth experiment inside a full-scale mockup of the space station laboratory module using a unique seven-degree-of-freedom robot.
Social Network Types and Mental Health Among LGBT Older Adults
Kim, Hyun-Jun; Fredriksen-Goldsen, Karen I.; Bryan, Amanda E. B.; Muraco, Anna
2017-01-01
Purpose of the Study: This study was designed to identify social network types among lesbian, gay, bisexual, and transgender (LGBT) older adults and examine the relationship between social network type and mental health. Design and Methods: We analyzed the 2014 survey data of LGBT adults aged 50 and older (N = 2,450) from Aging with Pride: National Health, Aging, and Sexuality/Gender Study. Latent profile analyses were conducted to identify clusters of social network ties based on 11 indicators. Multiple regression analysis was performed to examine the association between social network types and mental health. Results: We found five social network types. Ordered from greatest to least access to family, friend, and other non-family network ties, they were diverse, diverse/no children, immediate family-focused, friend-centered/restricted, and fully restricted. The friend-centered/restricted (33%) and diverse/no children network types (31%) were the most prevalent. Among individuals with the friend-centered/restricted type, access to social networks was limited to friends, and across both types children were not present. The least prevalent type was the fully restricted network type (6%). Social network type was significantly associated with mental health, after controlling for background characteristics and total social network size; those with the fully restricted type showed the poorest mental health. Implications: Unique social network types (diverse/no children and friend-centered/restricted) emerge among LGBT older adults. Moreover, individuals with fully restricted social networks are at particular risk due to heightened health needs and limited social resources. This study highlights the importance of understanding heterogeneous social relations and developing tailored interventions to promote social connectedness and mental health in LGBT older adults. PMID:28087798
Social Network Types and Mental Health Among LGBT Older Adults.
Kim, Hyun-Jun; Fredriksen-Goldsen, Karen I; Bryan, Amanda E B; Muraco, Anna
2017-02-01
This study was designed to identify social network types among lesbian, gay, bisexual, and transgender (LGBT) older adults and examine the relationship between social network type and mental health. We analyzed the 2014 survey data of LGBT adults aged 50 and older (N = 2,450) from Aging with Pride: National Health, Aging, and Sexuality/Gender Study. Latent profile analyses were conducted to identify clusters of social network ties based on 11 indicators. Multiple regression analysis was performed to examine the association between social network types and mental health. We found five social network types. Ordered from greatest to least access to family, friend, and other non-family network ties, they were diverse, diverse/no children, immediate family-focused, friend-centered/restricted, and fully restricted. The friend-centered/restricted (33%) and diverse/no children network types (31%) were the most prevalent. Among individuals with the friend-centered/restricted type, access to social networks was limited to friends, and across both types children were not present. The least prevalent type was the fully restricted network type (6%). Social network type was significantly associated with mental health, after controlling for background characteristics and total social network size; those with the fully restricted type showed the poorest mental health. Unique social network types (diverse/no children and friend-centered/restricted) emerge among LGBT older adults. Moreover, individuals with fully restricted social networks are at particular risk due to heightened health needs and limited social resources. This study highlights the importance of understanding heterogeneous social relations and developing tailored interventions to promote social connectedness and mental health in LGBT older adults. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Dual adaptive dynamic control of mobile robots using neural networks.
Bugeja, Marvin K; Fabri, Simon G; Camilleri, Liberato
2009-02-01
This paper proposes two novel dual adaptive neural control schemes for the dynamic control of nonholonomic mobile robots. The two schemes are developed in discrete time, and the robot's nonlinear dynamic functions are assumed to be unknown. Gaussian radial basis function and sigmoidal multilayer perceptron neural networks are used for function approximation. In each scheme, the unknown network parameters are estimated stochastically in real time, and no preliminary offline neural network training is used. In contrast to other adaptive techniques hitherto proposed in the literature on mobile robots, the dual control laws presented in this paper do not rely on the heuristic certainty equivalence property but account for the uncertainty in the estimates. This results in a major improvement in tracking performance, despite the plant uncertainty and unmodeled dynamics. Monte Carlo simulation and statistical hypothesis testing are used to illustrate the effectiveness of the two proposed stochastic controllers as applied to the trajectory-tracking problem of a differentially driven wheeled mobile robot.
PIMS sequencing extension: a laboratory information management system for DNA sequencing facilities.
Troshin, Peter V; Postis, Vincent Lg; Ashworth, Denise; Baldwin, Stephen A; McPherson, Michael J; Barton, Geoffrey J
2011-03-07
Facilities that provide a service for DNA sequencing typically support large numbers of users and experiment types. The cost of services is often reduced by the use of liquid handling robots but the efficiency of such facilities is hampered because the software for such robots does not usually integrate well with the systems that run the sequencing machines. Accordingly, there is a need for software systems capable of integrating different robotic systems and managing sample information for DNA sequencing services. In this paper, we describe an extension to the Protein Information Management System (PIMS) that is designed for DNA sequencing facilities. The new version of PIMS has a user-friendly web interface and integrates all aspects of the sequencing process, including sample submission, handling and tracking, together with capture and management of the data. The PIMS sequencing extension has been in production since July 2009 at the University of Leeds DNA Sequencing Facility. It has completely replaced manual data handling and simplified the tasks of data management and user communication. Samples from 45 groups have been processed with an average throughput of 10000 samples per month. The current version of the PIMS sequencing extension works with Applied Biosystems 3130XL 96-well plate sequencer and MWG 4204 or Aviso Theonyx liquid handling robots, but is readily adaptable for use with other combinations of robots. PIMS has been extended to provide a user-friendly and integrated data management solution for DNA sequencing facilities that is accessed through a normal web browser and allows simultaneous access by multiple users as well as facility managers. The system integrates sequencing and liquid handling robots, manages the data flow, and provides remote access to the sequencing results. The software is freely available, for academic users, from http://www.pims-lims.org/.
Perspectives of construction robots
NASA Astrophysics Data System (ADS)
Stepanov, M. A.; Gridchin, A. M.
2018-03-01
This article is an overview of construction robots features, based on formulating the list of requirements for different types of construction robots in relation to different types of construction works.. It describes a variety of construction works and ways to construct new or to adapt existing robot designs for a construction process. Also, it shows the prospects of AI-controlled machines, implementation of automated control systems and networks on construction sites. In the end, different ways to develop and improve, including ecological aspect, the construction process through the wide robotization, creating of data communication networks and, in perspective, establishing of fully AI-controlled construction complex are formulated.
Proactive recruitment of cancer patients’ social networks into a smoking cessation trial
Bastian, Lori A.; Fish, Laura J.; Peterson, Bercedis L.; Biddle, Andrea K.; Garst, Jennifer; Lyna, Pauline; Molner, Stephanie; Bepler, Gerold; Kelley, Mike; Keefe, Francis J.; McBride, Colleen M.
2011-01-01
Background This report describes the characteristics associated with successful enrollment of smokers in the social networks (i.e., family and close friends) of patients with lung cancer into a smoking cessation intervention. Methods Lung cancer patients from four clinical sites were asked to complete a survey enumerating their family members and close friends who smoke, and provide permission to contact these potential participants. Family members and close friends identified as smokers were interviewed and offered participation in a smoking cessation intervention. Repeated measures logistic regression model examined characteristics associated with enrollment. Results A total of 1,062 eligible lung cancer patients were identified and 516 patients consented and completed the survey. These patients identified 1,325 potentially eligible family and close friends. Of these, 496 consented and enrolled in the smoking cessation program. Network enrollment was highest among patients who were white and had late-stage disease. Social network members enrolled were most likely to be female, a birth family, immediate family, or close friend, and live in close geographic proximity to the patient. Conclusions Proactive recruitment of smokers in the social networks of lung cancer patients is challenging. In this study, the majority of family members and friends declined to participate. Enlisting immediate female family members and friends, who live close to the patient as agents to proactively recruit other network members into smoking cessation trials could be used to extend reach of cessation interventions to patients’ social networks. Moreover, further consideration should be given to the appropriate timing of approaching network smokers to consider cessation. PMID:21382509
Dynamic Routing and Coordination in Multi-Agent Networks
2016-06-10
SECURITY CLASSIFICATION OF: Supported by this project, we designed innovative routing, planning and coordination strategies for robotic networks and...tasks partitioned among robots , in what order are they to be performed, and along which deterministic routes or according to which stochastic rules do...individual robots move. The fundamental novelties and our recent breakthroughs supported by this project are manifold: (1) the application 1
Fused smart sensor network for multi-axis forward kinematics estimation in industrial robots.
Rodriguez-Donate, Carlos; Osornio-Rios, Roque Alfredo; Rivera-Guillen, Jesus Rooney; Romero-Troncoso, Rene de Jesus
2011-01-01
Flexible manipulator robots have a wide industrial application. Robot performance requires sensing its position and orientation adequately, known as forward kinematics. Commercially available, motion controllers use high-resolution optical encoders to sense the position of each joint which cannot detect some mechanical deformations that decrease the accuracy of the robot position and orientation. To overcome those problems, several sensor fusion methods have been proposed but at expenses of high-computational load, which avoids the online measurement of the joint's angular position and the online forward kinematics estimation. The contribution of this work is to propose a fused smart sensor network to estimate the forward kinematics of an industrial robot. The developed smart processor uses Kalman filters to filter and to fuse the information of the sensor network. Two primary sensors are used: an optical encoder, and a 3-axis accelerometer. In order to obtain the position and orientation of each joint online a field-programmable gate array (FPGA) is used in the hardware implementation taking advantage of the parallel computation capabilities and reconfigurability of this device. With the aim of evaluating the smart sensor network performance, three real-operation-oriented paths are executed and monitored in a 6-degree of freedom robot.
Peer-to-peer model for the area coverage and cooperative control of mobile sensor networks
NASA Astrophysics Data System (ADS)
Tan, Jindong; Xi, Ning
2004-09-01
This paper presents a novel model and distributed algorithms for the cooperation and redeployment of mobile sensor networks. A mobile sensor network composes of a collection of wireless connected mobile robots equipped with a variety of sensors. In such a sensor network, each mobile node has sensing, computation, communication, and locomotion capabilities. The locomotion ability enhances the autonomous deployment of the system. The system can be rapidly deployed to hostile environment, inaccessible terrains or disaster relief operations. The mobile sensor network is essentially a cooperative multiple robot system. This paper first presents a peer-to-peer model to define the relationship between neighboring communicating robots. Delaunay Triangulation and Voronoi diagrams are used to define the geometrical relationship between sensor nodes. This distributed model allows formal analysis for the fusion of spatio-temporal sensory information of the network. Based on the distributed model, this paper discusses a fault tolerant algorithm for autonomous self-deployment of the mobile robots. The algorithm considers the environment constraints, the presence of obstacles and the nonholonomic constraints of the robots. The distributed algorithm enables the system to reconfigure itself such that the area covered by the system can be enlarged. Simulation results have shown the effectiveness of the distributed model and deployment algorithms.
Cohort Differences in Received Social Support in Later Life: The Role of Network Type.
Suanet, Bianca; Antonucci, Toni C
2017-07-01
The objective is to assess cohort differences in received emotional and instrumental support in relation to network types. The main guiding hypothesis is that due to increased salience of non-kin with recent social change, those in friend-focused and diverse network types receive more support in later birth cohorts than earlier birth cohorts. Data from the Longitudinal Aging Study Amsterdam are employed. We investigate cohort differences in total received emotional and instrumental support in a series of linear regression models comparing birth cohorts aged 55-64, 65-74, 75-84, and 85-94 across three time periods (1992, 2002, and 2012). Four network types (friend, family, restricted, and diverse) are identified. Friend-focused networks are more common in later birth cohorts, restrictive networks less common. Those in friend-focused networks in later cohorts report receiving more emotional and instrumental support. No differences in received support are evident upon diverse networks. The increased salience of non-kin is reflected in an increase in received emotional and instrumental support in friend-focused networks in later birth cohorts. The preponderance of non-kin in networks should not be perceived as a deficit model for social relationships as restrictive networks are declining across birth cohorts. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
2004-03-12
KENNEDY SPACE CENTER, FLA. - While at the 2004 Florida Regional FIRST competition, held at the University of Central Florida, Center Director Jim Kennedy talks to participants in the FIRST LEGO™ League (FLL). Considered the "little league" of the FIRST (For Inspiration and Recognition of Science and Technology) Robotics Competition, FLL is the result of a partnership between FIRST and the LEGO™ Company. FLL extends the FIRST concept of inspiring and celebrating science and technology to children aged 9 through 14, using real-world context and hands-on experimentation. Young participants can build a robot and compete in a friendly, FIRST-style robotics event specially designed for their age group.
2004-03-12
KENNEDY SPACE CENTER, FLA. - While at the 2004 Florida Regional FIRST competition, held at the University of Central Florida, Center Director Jim Kennedy talks to participants in the FIRST LEGO™ League (FLL). Considered the "little league" of the FIRST (For Inspiration and Recognition of Science and Technology) Robotics Competition, FLL is the result of a partnership between FIRST and the LEGO™ Company. FLL extends the FIRST concept of inspiring and celebrating science and technology to children aged 9 through 14, using real-world context and hands-on experimentation. Young participants can build a robot and compete in a friendly, FIRST-style robotics event specially designed for their age group.
2004-03-12
KENNEDY SPACE CENTER, FLA. - During a break at the 2004 Florida Regional FIRST competition, held at the University of Central Florida, Florida Gov. Jeb Bush joins participants in the FIRST LEGO™ League (FLL). Considered the "little league" of the FIRST (For Inspiration and Recognition of Science and Technology) Robotics Competition, FLL is the result of a partnership between FIRST and the LEGO™ Company. FLL extends the FIRST concept of inspiring and celebrating science and technology to children aged 9 through 14, using real-world context and hands-on experimentation. Young participants can build a robot and compete in a friendly, FIRST-style robotics event specially designed for their age group.
NASA Technical Reports Server (NTRS)
2004-01-01
KENNEDY SPACE CENTER, FLA. While at the 2004 Florida Regional FIRST competition, held at the University of Central Florida, Center Director Jim Kennedy talks to participants in the FIRST LEGO League (FLL). Considered the 'little league' of the FIRST (For Inspiration and Recognition of Science and Technology) Robotics Competition, FLL is the result of a partnership between FIRST and the LEGO Company. FLL extends the FIRST concept of inspiring and celebrating science and technology to children aged 9 through 14, using real-world context and hands-on experimentation. Young participants can build a robot and compete in a friendly, FIRST-style robotics event specially designed for their age group.
NASA Technical Reports Server (NTRS)
2004-01-01
KENNEDY SPACE CENTER, FLA. While at the 2004 Florida Regional FIRST competition, held at the University of Central Florida, Center Director Jim Kennedy talks to participants in the FIRST LEGO League (FLL). Considered the 'little league' of the FIRST (For Inspiration and Recognition of Science and Technology) Robotics Competition, FLL is the result of a partnership between FIRST and the LEGO Company. FLL extends the FIRST concept of inspiring and celebrating science and technology to children aged 9 through 14, using real-world context and hands-on experimentation. Young participants can build a robot and compete in a friendly, FIRST-style robotics event specially designed for their age group.
NASA Technical Reports Server (NTRS)
2004-01-01
KENNEDY SPACE CENTER, FLA. During a break at the 2004 Florida Regional FIRST competition, held at the University of Central Florida, Florida Gov. Jeb Bush joins participants in the FIRST LEGO League (FLL). Considered the 'little league' of the FIRST (For Inspiration and Recognition of Science and Technology) Robotics Competition, FLL is the result of a partnership between FIRST and the LEGO Company. FLL extends the FIRST concept of inspiring and celebrating science and technology to children aged 9 through 14, using real-world context and hands-on experimentation. Young participants can build a robot and compete in a friendly, FIRST-style robotics event specially designed for their age group.
Path planning in GPS-denied environments via collective intelligence of distributed sensor networks
NASA Astrophysics Data System (ADS)
Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok
2016-05-01
This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.
NASA Technical Reports Server (NTRS)
2005-01-01
KENNEDY SPACE CENTER, FLA. Pink T-shirt-clad friends and family cheer for the Space Coast FIRST Robotics Team, known as the Pink Team, at the 2005 FIRST Robotics Regional Competition held at the University of Central Florida March 10-12. The NASA-sponsored Roccobots took first place in the competition as part of a three- team alliance and advances to the Championship in Atlanta in April. The Pink Team comprises students from Rockledge High School and Cocoa Beach Junior/Senior High School.
Metaphors to Drive By: Exploring New Ways to Guide Human-Robot Interaction
DOE Office of Scientific and Technical Information (OSTI.GOV)
David J. Bruemmer; David I. Gertman; Curtis W. Nielsen
2007-08-01
Autonomous behaviors created by the research and development community are not being extensively utilized within energy, defense, security, or industrial contexts. This paper provides evidence that the interaction methods used alongside these behaviors may not provide a mental model that can be easily adopted or used by operators. Although autonomy has the potential to reduce overall workload, the use of robot behaviors often increased the complexity of the underlying interaction metaphor. This paper reports our development of new metaphors that support increased robot complexity without passing the complexity of the interaction onto the operator. Furthermore, we illustrate how recognition ofmore » problems in human-robot interactions can drive the creation of new metaphors for design and how human factors lessons in usability, human performance, and our social contract with technology have the potential for enormous payoff in terms of establishing effective, user-friendly robot systems when appropriate metaphors are used.« less
Application of da Vinci(®) Robot in simple or radical hysterectomy: Tips and tricks.
Iavazzo, Christos; Gkegkes, Ioannis D
2016-01-01
The first robotic simple hysterectomy was performed more than 10 years ago. These days, robotic-assisted hysterectomy is accepted as an alternative surgical approach and is applied both in benign and malignant surgical entities. The two important points that should be taken into account to optimize postoperative outcomes in the early period of a surgeon's training are how to achieve optimal oncological and functional results. Overcoming any technical challenge, as with any innovative surgical method, leads to an improved surgical operation timewise as well as for patients' safety. The standardization of the technique and recognition of critical anatomical landmarks are essential for optimal oncological and clinical outcomes on both simple and radical robotic-assisted hysterectomy. Based on our experience, our intention is to present user-friendly tips and tricks to optimize the application of a da Vinci® robot in simple or radical hysterectomies.
Health Promotion via Deaf-Friendly Ministries
Branz, Patricia; Fager, Matthew; Seegers, Sharon; Shimasaki, Suzuho
2013-01-01
Deaf community members face many barriers to accessing health information. This paper discusses the feasibility of creating a nationwide network of Deaf-friendly ministries to help disseminate cancer information in American Sign Language (ASL) to the Deaf community. Deaf-friendly ministries (N=403), identified through Internet searches and one-on-one referrals, were sent up to three mailed invitations to join the network. Over half of the ministries responded, with 191 (47.4 %) of the ministries joining the network, completing a baseline survey and receiving ASL cancer education videos to share with members of their congregation and community. Fifteen (3.7 %) responded that they were not interested or no longer had a Deaf-friendly ministry; the rest did not respond or their invitations were returned as undeliverable. As the program progressed, an additional 238 Deaf-friendly ministries were identified. To date, 61 (25.6 %) agreed to participate after the single invitation that was mailed. This network of Deaf-friendly ministries offers a promising dissemination partner. PMID:22941763
Seelye, Adriana M.; Larimer, Nicole; Maxwell, Shoshana; Kearns, Peter; Kaye, Jeffrey A.
2012-01-01
Abstract Objective: Remote telepresence provided by tele-operated robotics represents a new means for obtaining important health information, improving older adults' social and daily functioning and providing peace of mind to family members and caregivers who live remotely. In this study we tested the feasibility of use and acceptance of a remotely controlled robot with video-communication capability in independently living, cognitively intact older adults. Materials and Methods: A mobile remotely controlled robot with video-communication ability was placed in the homes of eight seniors. The attitudes and preferences of these volunteers and those of family or friends who communicated with them remotely via the device were assessed through survey instruments. Results: Overall experiences were consistently positive, with the exception of one user who subsequently progressed to a diagnosis of mild cognitive impairment. Responses from our participants indicated that in general they appreciated the potential of this technology to enhance their physical health and well-being, social connectedness, and ability to live independently at home. Remote users, who were friends or adult children of the participants, were more likely to test the mobility features and had several suggestions for additional useful applications. Conclusions: Results from the present study showed that a small sample of independently living, cognitively intact older adults and their remote collaterals responded positively to a remote controlled robot with video-communication capabilities. Research is needed to further explore the feasibility and acceptance of this type of technology with a variety of patients and their care contacts. PMID:23082794
Automated platform for designing multiple robot work cells
NASA Astrophysics Data System (ADS)
Osman, N. S.; Rahman, M. A. A.; Rahman, A. A. Abdul; Kamsani, S. H.; Bali Mohamad, B. M.; Mohamad, E.; Zaini, Z. A.; Rahman, M. F. Ab; Mohamad Hatta, M. N. H.
2017-06-01
Designing the multiple robot work cells is very knowledge-intensive, intricate, and time-consuming process. This paper elaborates the development process of a computer-aided design program for generating the multiple robot work cells which offer a user-friendly interface. The primary purpose of this work is to provide a fast and easy platform for less cost and human involvement with minimum trial and errors adjustments. The automated platform is constructed based on the variant-shaped configuration concept with its mathematical model. A robot work cell layout, system components, and construction procedure of the automated platform are discussed in this paper where integration of these items will be able to automatically provide the optimum robot work cell design according to the information set by the user. This system is implemented on top of CATIA V5 software and utilises its Part Design, Assembly Design, and Macro tool. The current outcomes of this work provide a basis for future investigation in developing a flexible configuration system for the multiple robot work cells.
Federal Register 2010, 2011, 2012, 2013, 2014
2010-06-25
... SECURITIES AND EXCHANGE COMMISSION [File No. 500-1] Channel America Television Network, Inc., EquiMed, Inc., Kore Holdings, Inc., Robotic Vision Systems, Inc. (n/k/a Acuity Cimatrix, Inc.), Security... information concerning the securities of Channel America Television Network, Inc. because it has not filed any...
Embedded diagnostic, prognostic, and health management system and method for a humanoid robot
NASA Technical Reports Server (NTRS)
Barajas, Leandro G. (Inventor); Strawser, Philip A (Inventor); Sanders, Adam M (Inventor); Reiland, Matthew J (Inventor)
2013-01-01
A robotic system includes a humanoid robot with multiple compliant joints, each moveable using one or more of the actuators, and having sensors for measuring control and feedback data. A distributed controller controls the joints and other integrated system components over multiple high-speed communication networks. Diagnostic, prognostic, and health management (DPHM) modules are embedded within the robot at the various control levels. Each DPHM module measures, controls, and records DPHM data for the respective control level/connected device in a location that is accessible over the networks or via an external device. A method of controlling the robot includes embedding a plurality of the DPHM modules within multiple control levels of the distributed controller, using the DPHM modules to measure DPHM data within each of the control levels, and recording the DPHM data in a location that is accessible over at least one of the high-speed communication networks.
MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers.
Allot, Alexis; Chennen, Kirsley; Nevers, Yannis; Poidevin, Laetitia; Kress, Arnaud; Ripp, Raymond; Thompson, Julie Dawn; Poch, Olivier; Lecompte, Odile
2017-06-16
The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.0 and particularly social networks, which are at the forefront of big data exploration and human-data interaction. MyGeneFriends is a Web platform inspired by social networks, devoted to genetic disease analysis, and organized around three types of proactive agents: genes, humans, and genetic diseases. The aim of this study was to improve exploration and exploitation of biological, postgenomic era big data. MyGeneFriends leverages conventions popularized by top social networks (Facebook, LinkedIn, etc), such as networks of friends, profile pages, friendship recommendations, affinity scores, news feeds, content recommendation, and data visualization. MyGeneFriends provides simple and intuitive interactions with data through evaluation and visualization of connections (friendships) between genes, humans, and diseases. The platform suggests new friends and publications and allows agents to follow the activity of their friends. It dynamically personalizes information depending on the user's specific interests and provides an efficient way to share information with collaborators. Furthermore, the user's behavior itself generates new information that constitutes an added value integrated in the network, which can be used to discover new connections between biological agents. We have developed MyGeneFriends, a Web platform leveraging conventions from popular social networks to redefine the relationship between humans and biological big data and improve human processing of biomedical data. MyGeneFriends is available at lbgi.fr/mygenefriends. ©Alexis Allot, Kirsley Chennen, Yannis Nevers, Laetitia Poidevin, Arnaud Kress, Raymond Ripp, Julie Dawn Thompson, Olivier Poch, Odile Lecompte. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.06.2017.
Systems and Algorithms for Automated Collaborative Observation Using Networked Robotic Cameras
ERIC Educational Resources Information Center
Xu, Yiliang
2011-01-01
The development of telerobotic systems has evolved from Single Operator Single Robot (SOSR) systems to Multiple Operator Multiple Robot (MOMR) systems. The relationship between human operators and robots follows the master-slave control architecture and the requests for controlling robot actuation are completely generated by human operators. …
Adaptive artificial neural network for autonomous robot control
NASA Technical Reports Server (NTRS)
Arras, Michael K.; Protzel, Peter W.; Palumbo, Daniel L.
1992-01-01
The topics are presented in viewgraph form and include: neural network controller for robot arm positioning with visual feedback; initial training of the arm; automatic recovery from cumulative fault scenarios; and error reduction by iterative fine movements.
Training a Network of Electronic Neurons for Control of a Mobile Robot
NASA Astrophysics Data System (ADS)
Vromen, T. G. M.; Steur, E.; Nijmeijer, H.
An adaptive training procedure is developed for a network of electronic neurons, which controls a mobile robot driving around in an unknown environment while avoiding obstacles. The neuronal network controls the angular velocity of the wheels of the robot based on the sensor readings. The nodes in the neuronal network controller are clusters of neurons rather than single neurons. The adaptive training procedure ensures that the input-output behavior of the clusters is identical, even though the constituting neurons are nonidentical and have, in isolation, nonidentical responses to the same input. In particular, we let the neurons interact via a diffusive coupling, and the proposed training procedure modifies the diffusion interaction weights such that the neurons behave synchronously with a predefined response. The working principle of the training procedure is experimentally validated and results of an experiment with a mobile robot that is completely autonomously driving in an unknown environment with obstacles are presented.
Formation Control over Delayed Communication Network
NASA Astrophysics Data System (ADS)
Secchi, Cristian; Fantuzzi, Cesare
In this Chapter we address the problem of formation control of a group of robots that exchange information over a communication network characterized by a non negligible delay. We consider the Virtual Body Artificial Potential approach for stabilizing a group of robots at a desired formation. We show that it is possible to model the controlled group of robots as a port-Hamiltonian system and we exploit the scattering framework to achieve a passive behavior of the controlled system and to stabilize the robots in the desired formation independently of any communication delay.
Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment.
Yao, Yao; Storme, Veronique; Marchal, Kathleen; Van de Peer, Yves
2016-01-01
We developed a bio-inspired robot controller combining an artificial genome with an agent-based control system. The genome encodes a gene regulatory network (GRN) that is switched on by environmental cues and, following the rules of transcriptional regulation, provides output signals to actuators. Whereas the genome represents the full encoding of the transcriptional network, the agent-based system mimics the active regulatory network and signal transduction system also present in naturally occurring biological systems. Using such a design that separates the static from the conditionally active part of the gene regulatory network contributes to a better general adaptive behaviour. Here, we have explored the potential of our platform with respect to the evolution of adaptive behaviour, such as preying when food becomes scarce, in a complex and changing environment and show through simulations of swarm robots in an A-life environment that evolution of collective behaviour likely can be attributed to bio-inspired evolutionary processes acting at different levels, from the gene and the genome to the individual robot and robot population.
Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment
Yao, Yao; Storme, Veronique; Marchal, Kathleen
2016-01-01
We developed a bio-inspired robot controller combining an artificial genome with an agent-based control system. The genome encodes a gene regulatory network (GRN) that is switched on by environmental cues and, following the rules of transcriptional regulation, provides output signals to actuators. Whereas the genome represents the full encoding of the transcriptional network, the agent-based system mimics the active regulatory network and signal transduction system also present in naturally occurring biological systems. Using such a design that separates the static from the conditionally active part of the gene regulatory network contributes to a better general adaptive behaviour. Here, we have explored the potential of our platform with respect to the evolution of adaptive behaviour, such as preying when food becomes scarce, in a complex and changing environment and show through simulations of swarm robots in an A-life environment that evolution of collective behaviour likely can be attributed to bio-inspired evolutionary processes acting at different levels, from the gene and the genome to the individual robot and robot population. PMID:28028477
The power of (Mis)perception: Rethinking suicide contagion in youth friendship networks.
Zimmerman, Gregory M; Rees, Carter; Posick, Chad; Zimmerman, Lori A
2016-05-01
Suicide is a leading cause of death among youth. In the wake of peer suicide, youth are vulnerable to suicide contagion. But, questions remain about the mechanisms through which suicide spreads and the accuracy of youths' estimates of friends' suicidal behaviors. This study addresses these questions within school-aged youths' friendship networks. Social network data were drawn from two schools in the National Longitudinal Study of Adolescent to Adult Health, from which 2180 youth in grades 7-12 nominated up to ten friends. A measure of "perceived" friends' attempted suicide was constructed based on respondents' reports of their friends' attempted suicide. This measure was broader than a "true" measure of friends' attempted suicide, constructed from self-reports of nominated friends who attended respondents' schools. Sociograms graphically represented the accuracy with which suicide attempters estimated friends' suicide attempts. Results from cross-tabulation with Chi-square analysis indicated that approximately 4% of youth (88/2180) attempted suicide, and these youth disproportionately misperceived (predominantly overestimated) friends' suicidal behaviors, compared to non-suicide-attempters. Penalized logistic regression models indicated that friends' self-reported attempted suicide was unrelated to respondent attempted suicide. But, the odds of respondent attempted suicide were 2.54 times higher (95% CI, 1.06-6.10) among youth who accurately perceived friends' attempted suicide, and 5.40 times higher (95% CI, 3.34-8.77) among youth who overestimated friends' attempted suicide. The results suggest that at-risk youth overestimate their friends' suicidal behaviors, which exacerbates their own risk of suicidal behavior. Methodologically, this suggests that a continued collaboration among network scientists, suicide researchers, and medical providers is necessary to further examine the mechanisms surrounding this phenomenon. Practically, it is important to screen at-risk youth for exposure to peer suicide and to use the social environment created by adolescent friendship networks to empower and support youth who are susceptible to suicidal thoughts and behaviors. Copyright © 2016 Elsevier Ltd. All rights reserved.
Taylor, Robert Joseph; Mouzon, Dawne M; Nguyen, Ann W; Chatters, Linda M
2016-12-01
This study examined reciprocal support networks involving extended family, friends and church members among African Americans. Our analysis examined specific patterns of reciprocal support (i.e., received only, gave only, both gave and received, neither gave or received), as well as network characteristics (i.e., contact and subjective closeness) as correlates of reciprocal support. The analysis is based on the African American sub-sample of the National Survey of American Life (NSAL). Overall, our findings indicate that African Americans are very involved in reciprocal support networks with their extended family, friends and church members. Respondents were most extensively involved in reciprocal supports with extended family members, followed closely by friends and church networks. Network characteristics (i.e., contact and subjective closeness) were significantly and consistently associated with involvement with reciprocal support exchanges for all three networks. These and other findings are discussed in detail. This study complements previous work on the complementary roles of family, friend and congregational support networks, as well as studies of racial differences in informal support networks.
Yakoubi, Rachid; Autorino, Riccardo; Laydner, Humberto; Guillotreau, Julien; White, Michael A; Hillyer, Shahab; Spana, Gregory; Khanna, Rakesh; Isaac, Wahib; Haber, Georges-Pascal; Stein, Robert J; Kaouk, Jihad H
2012-06-01
The aim of this study was to evaluate a novel ultrasound probe specifically developed for robotic surgery by determining its efficiency in identifying renal tumors. The study was carried out using the Da Vinci™ surgical system in one female pig. Renal tumor targets were created by percutaneous injection of a tumor mimic mixture. Single-port and standard robotic partial nephrectomy were performed. Intraoperative ultrasound was performed using both standard laparoscopic probe and the new ProART™ Robotic probe. Probe maneuverability and ease of handling for tumor localization were recorded. The standard laparoscopic probe was guided by the assistant. Significant clashing with robotic arms was noted during the single-port procedure. The novel robotic probe was easily introduced through the assistant trocar, and held by the console surgeon using the robotic Prograsp™ with no registered clashing in the external operative field. The average time for grasping the new robotic probe was less than 10 s. Once inserted and grasped, no limitation was found in terms of instrument clashing during the single-port procedure. This novel ultrasound probe developed for robotic surgery was noted to be user-friendly when performing porcine standard and especially single-port robotic partial nephrectomy. Copyright © 2011 John Wiley & Sons, Ltd.
Sawka, Keri Jo; McCormack, Gavin R; Nettel-Aguirre, Alberto; Swanson, Kenda
2015-08-01
To gather and synthesize current evidence on the associations between aspects of friendship networks (e.g., friends' dietary behavior, popularity) and an individual's dietary behavior among children and adolescents. A systematic search of six scientific online databases was conducted in August 2013. Eligible studies included child or adolescent participants (aged 6 to 18years), a measure of each participant's friendship network, and a measure of habitual dietary behavior for both the participant and the participant's nominated friend(s). Data on study design, participant characteristics, friendship networks, dietary behavior, and study outcomes were abstracted. From a total of 9041 articles retrieved, seven studies were included in this review. Overall, friends' unhealthy food consumption was associated with an individual's unhealthy food consumption, and this association appeared to be stronger for boys compared with girls. More popular adolescents also tended to consume more unhealthy foods. Best friends' total energy intake was correlated with an individual's total energy intake. Similarities among friends' healthy food consumption, as well as daily breakfast consumption, were inconclusive. Longitudinal evidence showed that an individual's unhealthy food consumption tended to become similar to friends' unhealthy food consumption over time. Social network analysis in the adolescent dietary behavior literature is beginning to emerge. Results highlight friends' particular influence on unhealthy food consumption among adolescents. Focus on modeling healthy dietary behaviors among adolescent friendship group may help reduce unhealthy dietary behaviors and promote healthy weight status among youth. Copyright © 2015 Elsevier Ltd. All rights reserved.
Decomposing the components of friendship and friends' influence on adolescent drinking and smoking.
Fujimoto, Kayo; Valente, Thomas W
2012-08-01
Friendship networks are an important source of peer influence. However, existing network studies vary in terms of how they operationalize friendship and friend's influence on adolescent substance use. This study uses social network analysis to characterize three types of friendship relations: (1) mutual or reciprocated, (2) directional, and (3) intimate friends. We then examine the relative effects of each friendship type on adolescent drinking and smoking behavior. Using a saturated sample from the Add Health data, a nationally representative sample of high school adolescents (N = 2,533 nested in 12 schools), we computed the level of exposure to drinking and smoking of friends using a network exposure model, and their association with individual drinking and smoking using fixed effect models. Results indicated that the influence from mutual or reciprocated type of friendship relations is stronger on adolescent substance use than directional, especially for smoking. Regarding the directionality of directional type of friendship relations, adolescents are equally influenced by both nominating and nominated friends on their drinking and smoking behavior. Results for intimate friends friendship relations indicated that the influence from "best friends" was weaker than the one from non-"best friends," which indicates that the order of friend nomination may not matter as much as nomination reciprocation. This study demonstrates that considering different features of friendship relationships is important in evaluating friends' influence on adolescent substance use. Related policy implications are discussed. Copyright © 2012 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
Fused Smart Sensor Network for Multi-Axis Forward Kinematics Estimation in Industrial Robots
Rodriguez-Donate, Carlos; Osornio-Rios, Roque Alfredo; Rivera-Guillen, Jesus Rooney; de Jesus Romero-Troncoso, Rene
2011-01-01
Flexible manipulator robots have a wide industrial application. Robot performance requires sensing its position and orientation adequately, known as forward kinematics. Commercially available, motion controllers use high-resolution optical encoders to sense the position of each joint which cannot detect some mechanical deformations that decrease the accuracy of the robot position and orientation. To overcome those problems, several sensor fusion methods have been proposed but at expenses of high-computational load, which avoids the online measurement of the joint’s angular position and the online forward kinematics estimation. The contribution of this work is to propose a fused smart sensor network to estimate the forward kinematics of an industrial robot. The developed smart processor uses Kalman filters to filter and to fuse the information of the sensor network. Two primary sensors are used: an optical encoder, and a 3-axis accelerometer. In order to obtain the position and orientation of each joint online a field-programmable gate array (FPGA) is used in the hardware implementation taking advantage of the parallel computation capabilities and reconfigurability of this device. With the aim of evaluating the smart sensor network performance, three real-operation-oriented paths are executed and monitored in a 6-degree of freedom robot. PMID:22163850
2014-09-01
college student alongside you, little sis! To Jes- xix sika Miller, Lauren Garcia and Caity White , my closest friends and confidants of ten years, who...arena corresponding coverage to the GUI is outlined in white 2.1.3 Challenges in the Model There are inherent challenges with any model that implements...source middleware originally maintained by Willow Garage [36] and now managed by the Open Source Robotics Foundation [37]. It provides a framework for
The influence of personal networks on the use and abuse of alcohol and drugs.
Calafat, Amador; Cajal, Berta; Juan, Montse; Mendes, Fernando; Kokkevi, Anna; Blay, Nicole; Palmer, Alfonso; Duch, Maria Angels
2010-01-01
Party networks of young people are very important for socialization, but can also influence their involvement in risk behaviours or they can be protective. The influence of nightlife network of friends in using alcohol/ drugs is investigated through a survey. We explore the individual-centred networks (7.360 friends) of 1.363 recreational nightlife users in 9 European cities in 2006, through 22 friend characteristics. Statistical analysis utilised factorial analysis with varimax rotation and analysis of variance. The 69% of the sample had been drunk during the last month and more than half of them had used illicit drugs. Most of the respondents use to have a stable group of friends with whom to go out. Networks main characteristics were being more or less deviant and/or prosocial. Having not network or a less prosocial network is related to be low consumers. Having a non deviant, but prosocial network is related to being a person who gets drunk without using illegal drugs. Users of illegal drugs have a deviant and prosocial network. Finally ex users have less deviant networks, but at the same time a helper and prosocial network. Males drug use patterns appear to be less affected by the characteristics of their networks. Some preventive consequences coming from these results are already known as the importance of having less deviant friends. But some other issues are less known: to enhance certain prosocial skills may have counter preventive effects among recreational users and to influence the network for preventative purposes may be more effective among females.
Cloud-based robot remote control system for smart factory
NASA Astrophysics Data System (ADS)
Wu, Zhiming; Li, Lianzhong; Xu, Yang; Zhai, Jingmei
2015-12-01
With the development of internet technologies and the wide application of robots, there is a prospect (trend/tendency) of integration between network and robots. A cloud-based robot remote control system over networks for smart factory is proposed, which enables remote users to control robots and then realize intelligent production. To achieve it, a three-layer system architecture is designed including user layer, service layer and physical layer. Remote control applications running on the cloud server is developed on Microsoft Azure. Moreover, DIV+ CSS technologies are used to design human-machine interface to lower maintenance cost and improve development efficiency. Finally, an experiment is implemented to verify the feasibility of the program.
Yap, Hwa Jen; Taha, Zahari; Md Dawal, Siti Zawiah; Chang, Siow-Wee
2014-01-01
Traditional robotic work cell design and programming are considered inefficient and outdated in current industrial and market demands. In this research, virtual reality (VR) technology is used to improve human-robot interface, whereby complicated commands or programming knowledge is not required. The proposed solution, known as VR-based Programming of a Robotic Work Cell (VR-Rocell), consists of two sub-programmes, which are VR-Robotic Work Cell Layout (VR-RoWL) and VR-based Robot Teaching System (VR-RoT). VR-RoWL is developed to assign the layout design for an industrial robotic work cell, whereby VR-RoT is developed to overcome safety issues and lack of trained personnel in robot programming. Simple and user-friendly interfaces are designed for inexperienced users to generate robot commands without damaging the robot or interrupting the production line. The user is able to attempt numerous times to attain an optimum solution. A case study is conducted in the Robotics Laboratory to assemble an electronics casing and it is found that the output models are compatible with commercial software without loss of information. Furthermore, the generated KUKA commands are workable when loaded into a commercial simulator. The operation of the actual robotic work cell shows that the errors may be due to the dynamics of the KUKA robot rather than the accuracy of the generated programme. Therefore, it is concluded that the virtual reality based solution approach can be implemented in an industrial robotic work cell. PMID:25360663
Yap, Hwa Jen; Taha, Zahari; Dawal, Siti Zawiah Md; Chang, Siow-Wee
2014-01-01
Traditional robotic work cell design and programming are considered inefficient and outdated in current industrial and market demands. In this research, virtual reality (VR) technology is used to improve human-robot interface, whereby complicated commands or programming knowledge is not required. The proposed solution, known as VR-based Programming of a Robotic Work Cell (VR-Rocell), consists of two sub-programmes, which are VR-Robotic Work Cell Layout (VR-RoWL) and VR-based Robot Teaching System (VR-RoT). VR-RoWL is developed to assign the layout design for an industrial robotic work cell, whereby VR-RoT is developed to overcome safety issues and lack of trained personnel in robot programming. Simple and user-friendly interfaces are designed for inexperienced users to generate robot commands without damaging the robot or interrupting the production line. The user is able to attempt numerous times to attain an optimum solution. A case study is conducted in the Robotics Laboratory to assemble an electronics casing and it is found that the output models are compatible with commercial software without loss of information. Furthermore, the generated KUKA commands are workable when loaded into a commercial simulator. The operation of the actual robotic work cell shows that the errors may be due to the dynamics of the KUKA robot rather than the accuracy of the generated programme. Therefore, it is concluded that the virtual reality based solution approach can be implemented in an industrial robotic work cell.
Indirect iterative learning control for a discrete visual servo without a camera-robot model.
Jiang, Ping; Bamforth, Leon C A; Feng, Zuren; Baruch, John E F; Chen, YangQuan
2007-08-01
This paper presents a discrete learning controller for vision-guided robot trajectory imitation with no prior knowledge of the camera-robot model. A teacher demonstrates a desired movement in front of a camera, and then, the robot is tasked to replay it by repetitive tracking. The imitation procedure is considered as a discrete tracking control problem in the image plane, with an unknown and time-varying image Jacobian matrix. Instead of updating the control signal directly, as is usually done in iterative learning control (ILC), a series of neural networks are used to approximate the unknown Jacobian matrix around every sample point in the demonstrated trajectory, and the time-varying weights of local neural networks are identified through repetitive tracking, i.e., indirect ILC. This makes repetitive segmented training possible, and a segmented training strategy is presented to retain the training trajectories solely within the effective region for neural network approximation. However, a singularity problem may occur if an unmodified neural-network-based Jacobian estimation is used to calculate the robot end-effector velocity. A new weight modification algorithm is proposed which ensures invertibility of the estimation, thus circumventing the problem. Stability is further discussed, and the relationship between the approximation capability of the neural network and the tracking accuracy is obtained. Simulations and experiments are carried out to illustrate the validity of the proposed controller for trajectory imitation of robot manipulators with unknown time-varying Jacobian matrices.
Automation, Miniature Robotics and Sensors for Nondestructive Testing and Evaluation, Volume 4
NASA Technical Reports Server (NTRS)
Bar-Cohen, Y.; Baumgartner, E.; Backes, P.; Sherrit, S.; Bao, X.; Leary, S.; Kennedy, B.; Mavroidis, C.; Pfeiffer, C.; Culbert, C.;
1999-01-01
The development of NDE techniques has always been driven by the ongoing need for low-cost, rapid, user-friendly, reliable and efficient methods of detecting and characterizing flaws as well as determining material properties.
Crookes, Danielle M; Shelton, Rachel C; Tehranifar, Parisa; Aycinena, Corina; Gaffney, Ann Ogden; Koch, Pam; Contento, Isobel R; Greenlee, Heather
2016-04-01
Little is known about Latina breast cancer survivors' social networks or their perceived social support to achieve and maintain a healthy diet. This paper describes the social networks and perceived support for healthy eating in a sample of breast cancer survivors of predominantly Dominican descent living in New York City. Spanish-speaking Latina breast cancer survivors enrolled in a randomized controlled trial of a culturally tailored dietary intervention. Social networks were assessed using Cohen's Social Network Index and a modified General Social Survey Social Networks Module that included assessments of shared health promoting behaviors. Perceived social support from family and friends for healthy, food-related behaviors was assessed. Participants' networks consisted predominantly of family and friends. Family members were more likely than other individuals to be identified as close network members. Participants were more likely to share food-related activities than exercise activities with close network members. Perceived social support for healthy eating was high, although perceived support from spouses and children was higher than support from friends. Despite high levels of perceived support, family was also identified as a barrier to eating healthy foods by nearly half of women. Although friends are part of Latina breast cancer survivors' social networks, spouses and children may provide greater support for healthy eating than friends. Involving family members in dietary interventions for Latina breast cancer survivors may tap into positive sources of support for women, which could facilitate uptake and maintenance of healthy eating behaviors.
"Friending" Professors, Parents and Bosses: A Facebook Connection Conundrum
ERIC Educational Resources Information Center
Karl, Katherine A.; Peluchette, Joy V.
2011-01-01
The ever-growing popularity of Facebook has led some educators to ponder what role social networking might have in education. The authors examined student reactions to friend requests from people outside their regular network of friends including professors, parents, and employers. We found students have the most positive reactions to friend…
Inverse kinematics problem in robotics using neural networks
NASA Technical Reports Server (NTRS)
Choi, Benjamin B.; Lawrence, Charles
1992-01-01
In this paper, Multilayer Feedforward Networks are applied to the robot inverse kinematic problem. The networks are trained with endeffector position and joint angles. After training, performance is measured by having the network generate joint angles for arbitrary endeffector trajectories. A 3-degree-of-freedom (DOF) spatial manipulator is used for the study. It is found that neural networks provide a simple and effective way to both model the manipulator inverse kinematics and circumvent the problems associated with algorithmic solution methods.
Analysis hierarchical model for discrete event systems
NASA Astrophysics Data System (ADS)
Ciortea, E. M.
2015-11-01
The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.
Computer graphics testbed to simulate and test vision systems for space applications
NASA Technical Reports Server (NTRS)
Cheatham, John B.
1991-01-01
Artificial intelligence concepts are applied to robotics. Artificial neural networks, expert systems and laser imaging techniques for autonomous space robots are being studied. A computer graphics laser range finder simulator developed by Wu has been used by Weiland and Norwood to study use of artificial neural networks for path planning and obstacle avoidance. Interest is expressed in applications of CLIPS, NETS, and Fuzzy Control. These applications are applied to robot navigation.
Wlodarski, Rafael; Dunbar, Robin I M
2016-12-01
The aim of this study was to examine differences in the neural processing of social information about kin and friends at different levels of closeness and social network level. Twenty-five female participants engaged in a cognitive social task involving different individuals in their social network while undergoing functional magnetic resonance imaging scanning to detect BOLD (Blood Oxygen Level Dependent) signals changes. Greater levels of activation occurred in several regions of the brain previously associated with social cognition when thinking about friends than when thinking about kin, including the posterior cingulate cortex (PCC) and the ventral medial prefrontal cortex (vMPFC). Linear parametric analyses across network layers further showed that, when it came to thinking about friends, activation increased in the vMPFC, lingual gyrus, and sensorimotor cortex as individuals thought about friends at closer layers of the network. These findings suggest that maintaining friendships may be more cognitively exacting than maintaining kin relationships. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Marks, Jennifer; de la Haye, Kayla; Barnett, Lisa M; Allender, Steven
2015-01-01
There is limited understanding of the association between peer social networks and physical activity (PA), sedentary and screen-related behaviors. This study reports on associations between personal network characteristics and these important health behaviors for early adolescents. Participants were 310 students, aged 11-13 years, from fifteen randomly selected Victorian primary schools (43% response rate). PA and sedentary behaviors were collected via accelerometer and self-report questionnaire, and anthropometric measures via trained researchers. Participants nominated up to fifteen friends, and described the frequency of interaction and perceived activity intensity of these friends. Personal network predictors were examined using regression modelling for PA and sedentary/screen behavior. Perceived activity levels of friends, and friendships with very frequent interaction were associated with outside-of-school PA and/or sedentary/screen time. Differences according to sex were also observed in the association between network characteristics and PA and sedentary time. A higher number of friends and greater proportion of same sex friends were associated with boys engaging in more moderate-to-vigorous PA outside of school hours. PA intensity during school-day breaks was positively associated with having a greater proportion of friends who played sports for girls, and a greater proportion of male friends for boys. Friendship network characteristics are associated with PA and sedentary/screen time in late childhood/early adolescence, and these associations differ by sex. The positive influence of very active peers may be a promising avenue to strengthen traditional interventions for the promotion of PA and reduction in screen time.
Marks, Jennifer; de la Haye, Kayla; Barnett, Lisa M; Allender, Steven
2015-01-01
Introduction There is limited understanding of the association between peer social networks and physical activity (PA), sedentary and screen-related behaviors. This study reports on associations between personal network characteristics and these important health behaviors for early adolescents. Methods Participants were 310 students, aged 11–13 years, from fifteen randomly selected Victorian primary schools (43% response rate). PA and sedentary behaviors were collected via accelerometer and self-report questionnaire, and anthropometric measures via trained researchers. Participants nominated up to fifteen friends, and described the frequency of interaction and perceived activity intensity of these friends. Personal network predictors were examined using regression modelling for PA and sedentary/screen behavior. Results Perceived activity levels of friends, and friendships with very frequent interaction were associated with outside-of-school PA and/or sedentary/screen time. Differences according to sex were also observed in the association between network characteristics and PA and sedentary time. A higher number of friends and greater proportion of same sex friends were associated with boys engaging in more moderate-to-vigorous PA outside of school hours. PA intensity during school-day breaks was positively associated with having a greater proportion of friends who played sports for girls, and a greater proportion of male friends for boys. Conclusion Friendship network characteristics are associated with PA and sedentary/screen time in late childhood/early adolescence, and these associations differ by sex. The positive influence of very active peers may be a promising avenue to strengthen traditional interventions for the promotion of PA and reduction in screen time. PMID:26709924
Friends First? The Peer Network Origins of Adolescent Dating
Kreager, Derek A.; Molloy, Lauren E.; Moody, James; Feinberg, Mark E.
2015-01-01
The proximity of dating partners in peer friendship networks has important implications for the diffusion of health-risk behaviors and adolescent social development. We derive two competing hypotheses for the friendship-romance association. The first predicts that daters are proximally positioned in friendship networks prior to dating and that opposite-gender friends are likely to transition to dating. The second predicts that dating typically crosses group boundaries and opposite-gender friends are unlikely to later date. We test these hypotheses with longitudinal friendship data for 626 9th grade PROSPER heterosexual dating couples. Results primarily support the second hypothesis: romantic partners are unlikely to be friends in the previous year or share the same cohesive subgroup, and opposite-gender friends are unlikely to transition into dating. PMID:27134511
Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya
2016-01-01
To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language-behavior relationships and the temporal patterns of interaction. Here, "internal dynamics" refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language-behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language-behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.
An architectural approach to create self organizing control systems for practical autonomous robots
NASA Technical Reports Server (NTRS)
Greiner, Helen
1991-01-01
For practical industrial applications, the development of trainable robots is an important and immediate objective. Therefore, the developing of flexible intelligence directly applicable to training is emphasized. It is generally agreed upon by the AI community that the fusion of expert systems, neural networks, and conventionally programmed modules (e.g., a trajectory generator) is promising in the quest for autonomous robotic intelligence. Autonomous robot development is hindered by integration and architectural problems. Some obstacles towards the construction of more general robot control systems are as follows: (1) Growth problem; (2) Software generation; (3) Interaction with environment; (4) Reliability; and (5) Resource limitation. Neural networks can be successfully applied to some of these problems. However, current implementations of neural networks are hampered by the resource limitation problem and must be trained extensively to produce computationally accurate output. A generalization of conventional neural nets is proposed, and an architecture is offered in an attempt to address the above problems.
Sang, Hongqiang; Yang, Chenghao; Liu, Fen; Yun, Jintian; Jin, Guoguang
2016-12-01
It is very important for robotically assisted minimally invasive surgery to achieve a high-precision and smooth motion control. However, the surgical instrument tip will exhibit vibration caused by nonlinear friction and unmodeled dynamics, especially when the surgical robot system is attempting low-speed, fine motion. A fuzzy neural network sliding mode controller (FNNSMC) is proposed to suppress vibration of the surgical robotic system. Nonlinear friction and modeling uncertainties are compensated by a Stribeck model, a radial basis function (RBF) neural network and a fuzzy system, respectively. Simulations and experiments were performed on a 3 degree-of-freedom (DOF) minimally invasive surgical robot. The results demonstrate that the FNNSMC is effective and can suppress vibrations at the surgical instrument tip. The proposed FNNSMC can provide a robust performance and suppress the vibrations at the surgical instrument tip, which can enhance the quality and security of surgical procedures. Copyright © 2016 John Wiley & Sons, Ltd.
High Reliability Robot Friendly ORU Interface
NASA Technical Reports Server (NTRS)
Voellmer, George M. (Inventor)
1991-01-01
Presented here is a robot friendly coupling device for an orbital replacement unit (ORU). The invention will provide a coupling that is detached and attached remotely by a robot. The design of the coupling must allow for slight misalignments, over-torque protection, and precision placement. This is accomplished by means of a triangular interface comprising three components. A base plate assembly is located on an attachment surface, such as a satellite. The base plate assembly has a cup member, a slotted member, and a post member. The ORU that the robot attaches to the base plate assembly has an ORU plate assembly with two cone members and a post member which mate to the base plate assembly. As the two plates approach one another, one cone member of the ORU plate assembly has to be placed accurately enough to fall into the cup member of the base plate assembly. The cup member forces alignment until a second cone falls into a slotted member which provides final alignment. A single bolt is used to attach the two plates. Two deflecting plates are attached to the backs of the plates. When pressure is applied to the center of the deflecting plates, the force is distributed preventing the ORU and base plates from deflecting. This accounts for precision in the placement of the article. The novelty is believed to reside in using deflecting plates in conjunction with kinematic mounts to provide distributed forces to the two members.
Designing a social and assistive robot for seniors.
Eftring, H; Frennert, S
2016-06-01
The development of social assistive robots is an approach with the intention of preventing and detecting falls among seniors. There is a need for a relatively low-cost mobile robot with an arm and a gripper which is small enough to navigate through private homes. User requirements of a social assistive robot were collected using workshops, a questionnaire and interviews. Two prototype versions of a robot were designed, developed and tested by senior citizens (n = 49) in laboratory trials for 2 h each and in the private homes of elderly persons (n = 18) for 3 weeks each. The user requirement analysis resulted in a specification of tasks the robot should be able to do to prevent and detect falls. It was a challenge but possible to design and develop a robot where both the senior and the robot arm could reach the necessary interaction points of the robot. The seniors experienced the robot as happy and friendly. They wanted the robot to be narrower so it could pass through narrow passages in the home and they also wanted it to be able to pass over thresholds without using ramps and to drive over carpets. User trials in seniors' homes are very important to acquire relevant knowledge for developing robots that can handle real life situations in the domestic environment. Very high reliability of a robot is needed to get feedback about how seniors experience the overall behavior of the robot and to find out if the robot could reduce falls and improve the feeling of security for seniors living alone.
Fujimoto, Kayo; Valente, Thomas W.
2012-01-01
This study investigates two contagion mechanisms of peer influence based on direct communication (cohesion) versus comparison through peers who occupy similar network positions (structural equivalence) in the context of adolescents' drinking alcohol and smoking. To date, the two contagion mechanisms have been considered observationally inseparable, but this study attempts to disentangle structural equivalence from cohesion as a contagion mechanism by examining the extent to which the transmission of drinking and smoking behaviors attenuates as a function of social distance (i.e., from immediate friends to indirectly connected peers). Using the U.S. Add Health data consisting of a nationally representative sample of American adolescents (Grades 7-12), this study measured peer risk-taking up to four steps away from the adolescent (friends of friends of friends of friends) using a network exposure model. Peer influence was tested using a logistic regression model of alcohol drinking and cigarette smoking. Results indicate that influence based on structural equivalence tended to be stronger than influence based on cohesion in general, and that the magnitude of the effect decreased up to three steps away from the adolescent (friends of friends of friends). Further analysis indicated that structural equivalence acted as a mechanism of contagion for drinking and cohesion acted as one for smoking. These results indicate that the two transmission mechanisms with differing network proximities can differentially affect drinking and smoking behaviors in American adolescents. PMID:22475405
NASA Astrophysics Data System (ADS)
Massimiliano Capisani, Luca; Facchinetti, Tullio; Ferrara, Antonella
2010-08-01
This article presents the networked control of a robotic anthropomorphic manipulator based on a second-order sliding mode technique, where the control objective is to track a desired trajectory for the manipulator. The adopted control scheme allows an easy and effective distribution of the control algorithm over two networked machines. While the predictability of real-time tasks execution is achieved by the Soft Hard Real-Time Kernel (S.Ha.R.K.) real-time operating system, the communication is established via a standard Ethernet network. The performances of the control system are evaluated under different experimental system configurations using, to perform the experiments, a COMAU SMART3-S2 industrial robot, and the results are analysed to put into evidence the robustness of the proposed approach against possible network delays, packet losses and unmodelled effects.
Cyber-physical approach to the network-centric robotics control task
NASA Astrophysics Data System (ADS)
Muliukha, Vladimir; Ilyashenko, Alexander; Zaborovsky, Vladimir; Lukashin, Alexey
2016-10-01
Complex engineering tasks concerning control for groups of mobile robots are developed poorly. In our work for their formalization we use cyber-physical approach, which extends the range of engineering and physical methods for a design of complex technical objects by researching the informational aspects of communication and interaction between objects and with an external environment [1]. The paper analyzes network-centric methods for control of cyber-physical objects. Robots or cyber-physical objects interact with each other by transmitting information via computer networks using preemptive queueing system and randomized push-out mechanism [2],[3]. The main field of application for the results of our work is space robotics. The selection of cyber-physical systems as a special class of designed objects is due to the necessity of integrating various components responsible for computing, communications and control processes. Network-centric solutions allow using universal means for the organization of information exchange to integrate different technologies for the control system.
SVR versus neural-fuzzy network controllers for the sagittal balance of a biped robot.
Ferreira, João P; Crisóstomo, Manuel M; Coimbra, A Paulo
2009-12-01
The real-time balance control of an eight-link biped robot using a zero moment point (ZMP) dynamic model is difficult due to the processing time of the corresponding equations. To overcome this limitation, two alternative intelligent computing control techniques were compared: one based on support vector regression (SVR) and another based on a first-order Takagi-Sugeno-Kang (TSK)-type neural-fuzzy (NF) network. Both methods use the ZMP error and its variation as inputs and the output is the correction of the robot's torso necessary for its sagittal balance. The SVR and the NF were trained based on simulation data and their performance was verified with a real biped robot. Two performance indexes are proposed to evaluate and compare the online performance of the two control methods. The ZMP is calculated by reading four force sensors placed under each robot's foot. The gait implemented in this biped is similar to a human gait that was acquired and adapted to the robot's size. Some experiments are presented and the results show that the implemented gait combined either with the SVR controller or with the TSK NF network controller can be used to control this biped robot. The SVR and the NF controllers exhibit similar stability, but the SVR controller runs about 50 times faster.
PIMS sequencing extension: a laboratory information management system for DNA sequencing facilities
2011-01-01
Background Facilities that provide a service for DNA sequencing typically support large numbers of users and experiment types. The cost of services is often reduced by the use of liquid handling robots but the efficiency of such facilities is hampered because the software for such robots does not usually integrate well with the systems that run the sequencing machines. Accordingly, there is a need for software systems capable of integrating different robotic systems and managing sample information for DNA sequencing services. In this paper, we describe an extension to the Protein Information Management System (PIMS) that is designed for DNA sequencing facilities. The new version of PIMS has a user-friendly web interface and integrates all aspects of the sequencing process, including sample submission, handling and tracking, together with capture and management of the data. Results The PIMS sequencing extension has been in production since July 2009 at the University of Leeds DNA Sequencing Facility. It has completely replaced manual data handling and simplified the tasks of data management and user communication. Samples from 45 groups have been processed with an average throughput of 10000 samples per month. The current version of the PIMS sequencing extension works with Applied Biosystems 3130XL 96-well plate sequencer and MWG 4204 or Aviso Theonyx liquid handling robots, but is readily adaptable for use with other combinations of robots. Conclusions PIMS has been extended to provide a user-friendly and integrated data management solution for DNA sequencing facilities that is accessed through a normal web browser and allows simultaneous access by multiple users as well as facility managers. The system integrates sequencing and liquid handling robots, manages the data flow, and provides remote access to the sequencing results. The software is freely available, for academic users, from http://www.pims-lims.org/. PMID:21385349
Motor modules in robot-aided walking
2012-01-01
Background It is hypothesized that locomotion is achieved by means of rhythm generating networks (central pattern generators) and muscle activation generating networks. This modular organization can be partly identified from the analysis of the muscular activity by means of factorization algorithms. The activity of rhythm generating networks is described by activation signals whilst the muscle intervention generating network is represented by motor modules (muscle synergies). In this study, we extend the analysis of modular organization of walking to the case of robot-aided locomotion, at varying speed and body weight support level. Methods Non Negative Matrix Factorization was applied on surface electromyographic signals of 8 lower limb muscles of healthy subjects walking in gait robotic trainer at different walking velocities (1 to 3km/h) and levels of body weight support (0 to 30%). Results The muscular activity of volunteers could be described by low dimensionality (4 modules), as for overground walking. Moreover, the activation signals during robot-aided walking were bursts of activation timed at specific phases of the gait cycle, underlying an impulsive controller, as also observed in overground walking. This modular organization was consistent across the investigated speeds, body weight support level, and subjects. Conclusions These results indicate that walking in a Lokomat robotic trainer is achieved by similar motor modules and activation signals as overground walking and thus supports the use of robotic training for re-establishing natural walking patterns. PMID:23043818
Planning in subsumption architectures
NASA Technical Reports Server (NTRS)
Chalfant, Eugene C.
1994-01-01
A subsumption planner using a parallel distributed computational paradigm based on the subsumption architecture for control of real-world capable robots is described. Virtual sensor state space is used as a planning tool to visualize the robot's anticipated effect on its environment. Decision sequences are generated based on the environmental situation expected at the time the robot must commit to a decision. Between decision points, the robot performs in a preprogrammed manner. A rudimentary, domain-specific partial world model contains enough information to extrapolate the end results of the rote behavior between decision points. A collective network of predictors operates in parallel with the reactive network forming a recurrrent network which generates plans as a hierarchy. Details of a plan segment are generated only when its execution is imminent. The use of the subsumption planner is demonstrated by a simple maze navigation problem.
Cooperative Autonomous Robots for Reconnaissance
2009-03-06
REPORT Cooperative Autonomous Robots for Reconnaissance 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: Collaborating mobile robots equipped with WiFi ...Cooperative Autonomous Robots for Reconnaissance Report Title ABSTRACT Collaborating mobile robots equipped with WiFi transceivers are configured as a mobile...equipped with WiFi transceivers are configured as a mobile ad-hoc network. Algorithms are developed to take advantage of the distributed processing
An integrated design and fabrication strategy for entirely soft, autonomous robots.
Wehner, Michael; Truby, Ryan L; Fitzgerald, Daniel J; Mosadegh, Bobak; Whitesides, George M; Lewis, Jennifer A; Wood, Robert J
2016-08-25
Soft robots possess many attributes that are difficult, if not impossible, to achieve with conventional robots composed of rigid materials. Yet, despite recent advances, soft robots must still be tethered to hard robotic control systems and power sources. New strategies for creating completely soft robots, including soft analogues of these crucial components, are needed to realize their full potential. Here we report the untethered operation of a robot composed solely of soft materials. The robot is controlled with microfluidic logic that autonomously regulates fluid flow and, hence, catalytic decomposition of an on-board monopropellant fuel supply. Gas generated from the fuel decomposition inflates fluidic networks downstream of the reaction sites, resulting in actuation. The body and microfluidic logic of the robot are fabricated using moulding and soft lithography, respectively, and the pneumatic actuator networks, on-board fuel reservoirs and catalytic reaction chambers needed for movement are patterned within the body via a multi-material, embedded 3D printing technique. The fluidic and elastomeric architectures required for function span several orders of magnitude from the microscale to the macroscale. Our integrated design and rapid fabrication approach enables the programmable assembly of multiple materials within this architecture, laying the foundation for completely soft, autonomous robots.
Jin, Long; Liao, Bolin; Liu, Mei; Xiao, Lin; Guo, Dongsheng; Yan, Xiaogang
2017-01-01
By incorporating the physical constraints in joint space, a different-level simultaneous minimization scheme, which takes both the robot kinematics and robot dynamics into account, is presented and investigated for fault-tolerant motion planning of redundant manipulator in this paper. The scheme is reformulated as a quadratic program (QP) with equality and bound constraints, which is then solved by a discrete-time recurrent neural network. Simulative verifications based on a six-link planar redundant robot manipulator substantiate the efficacy and accuracy of the presented acceleration fault-tolerant scheme, the resultant QP and the corresponding discrete-time recurrent neural network. PMID:28955217
Development of wrist rehabilitation robot and interface system.
Yamamoto, Ikuo; Matsui, Miki; Inagawa, Naohiro; Hachisuka, Kenji; Wada, Futoshi; Hachisuka, Akiko; Saeki, Satoru
2015-01-01
The authors have developed a practical wrist rehabilitation robot for hemiplegic patients. It consists of a mechanical rotation unit, sensor, grip, and computer system. A myoelectric sensor is used to monitor the extensor carpi radialis longus/brevis muscle and flexor carpi radialis muscle activity during training. The training robot can provoke training through myoelectric sensors, a biological signal detector and processor in advance, so that patients can undergo effective training of extention and flexion in an excited condition. In addition, both-wrist system has been developed for mirror effect training, which is the most effective function of the system, so that autonomous training using both wrists is possible. Furthermore, a user-friendly screen interface with easily recognizable touch panels has been developed to give effective training for patients. The developed robot is small size and easy to carry. The developed aspiring interface system is effective to motivate the training of patients. The effectiveness of the robot system has been verified in hospital trails.
Crookes, Danielle M.; Shelton, Rachel C.; Tehranifar, Parisa; Aycinena, Corina; Gaffney, Ann Ogden; Koch, Pam; Contento, Isobel R.; Greenlee, Heather
2015-01-01
Purpose Little is known about Latina breast cancer survivors' social networks or their perceived social support to achieve and maintain a healthy diet. This paper describes the social networks and perceived support for healthy eating in a sample of breast cancer survivors of predominantly Dominican descent living in New York City. Methods Spanish-speaking Latina breast cancer survivors enrolled in a randomized controlled trial of a culturally-tailored dietary intervention. Social networks were assessed using Cohen's Social Network Index and a modified General Social Survey Social Networks Module that included assessments of shared health promoting behaviors. Perceived social support from family and friends for healthy, food-related behaviors was assessed. Results Participants' networks consisted predominantly of family and friends. Family members were more likely than other individuals to be identified as close network members. Participants were more likely to share food-related activities than exercise activities with close network members. Perceived social support for healthy eating was high, although perceived support from spouses and children was higher than support from friends. Despite high levels of perceived support, family was also identified as a barrier to eating healthy foods by nearly half of women. Conclusions Although friends are part of Latina breast cancer survivors' social networks, spouses and children may provide greater support for healthy eating than friends. Implications for Cancer Survivors Involving family members in dietary interventions for Latina breast cancer survivors may tap into positive sources of support for women, which could facilitate uptake and maintenance of healthy eating behaviors. PMID:26202538
ERIC Educational Resources Information Center
Doty, Keith L.
1999-01-01
Research on neural networks and hippocampal function demonstrating how mammals construct mental maps and develop navigation strategies is being used to create Intelligent Autonomous Mobile Robots (IAMRs). Such robots are able to recognize landmarks and navigate without "vision." (SK)
How Friendship Network Characteristics Influence Subjective Well-Being
ERIC Educational Resources Information Center
van der Horst, Mariska; Coffe, Hilde
2012-01-01
This article explores how friendship network characteristics influence subjective well-being (SWB). Using data from the 2003 General Social Survey of Canada, three components of the friendship network are differentiated: number of friends, frequency of contact, and heterogeneity of friends. We argue that these characteristics shape SWB through the…
Deus ex machina or e-slave? Public perception of healthcare robotics in the German print media.
Laryionava, Katsiaryna; Gross, Dominik
2012-07-01
The news media plays a central role in providing information regarding new medical technologies and exerts an influence on their social perception, understanding, and assessments. This study, therefore, analyzes how healthcare robotics are portrayed in the German print news media. It examines whether the risks and opportunities of new medical technologies are presented in a balanced manner and investigates whether or not print media coverage of these technologies is affected by science-fiction discourse, in which robots appear mostly as a threat to humans. Ten years of German print media coverage (2000-2010) have been studied by means of systematic, standardized content analysis. Reporting focuses predominantly on beneficial advancements in medical practice and the advantages of robotics for patients, medical staff, and society. The results show that the dominant relationship between robots and humans that is transmitted in print media in medical contexts is positive, with robots mostly portrayed as assistants, colleagues, or even friends. Only a small number of articles report ethical questions and risks. In contrast to science-fiction discourse, the German print media provides a positive picture of robotics to the lay public.
A neural-network approach to robotic control
NASA Technical Reports Server (NTRS)
Graham, D. P. W.; Deleuterio, G. M. T.
1993-01-01
An artificial neural-network paradigm for the control of robotic systems is presented. The approach is based on the Cerebellar Model Articulation Controller created by James Albus and incorporates several extensions. First, recognizing the essential structure of multibody equations of motion, two parallel modules are used that directly reflect the dynamical characteristics of multibody systems. Second, the architecture of the proposed network is imbued with a self-organizational capability which improves efficiency and accuracy. Also, the networks can be arranged in hierarchical fashion with each subsequent network providing finer and finer resolution.
Friend networking sites and their relationship to adolescents' well-being and social self-esteem.
Valkenburg, Patti M; Peter, Jochen; Schouten, Alexander P
2006-10-01
The aim of this study was to investigate the consequences of friend networking sites (e.g., Friendster, MySpace) for adolescents' self-esteem and well-being. We conducted a survey among 881 adolescents (10-19-year-olds) who had an online profile on a Dutch friend networking site. Using structural equation modeling, we found that the frequency with which adolescents used the site had an indirect effect on their social self-esteem and well-being. The use of the friend networking site stimulated the number of relationships formed on the site, the frequency with which adolescents received feedback on their profiles, and the tone (i.e., positive vs. negative) of this feedback. Positive feedback on the profiles enhanced adolescents' social self-esteem and well-being, whereas negative feedback decreased their self-esteem and well-being.
Intelligent Surveillance Robot with Obstacle Avoidance Capabilities Using Neural Network
2015-01-01
For specific purpose, vision-based surveillance robot that can be run autonomously and able to acquire images from its dynamic environment is very important, for example, in rescuing disaster victims in Indonesia. In this paper, we propose architecture for intelligent surveillance robot that is able to avoid obstacles using 3 ultrasonic distance sensors based on backpropagation neural network and a camera for face recognition. 2.4 GHz transmitter for transmitting video is used by the operator/user to direct the robot to the desired area. Results show the effectiveness of our method and we evaluate the performance of the system. PMID:26089863
Future Autonomous Robotic Systems in the Pacific Theater
2015-05-06
areas to inform the friendly units behind of what potential threats lurk within. Once secure supply routes are established, driverless vehicles can...developing new ARS, from driverless vehicles to handheld medical devices that dispense personal diagnoses, tailored to that individual’s medical
Deutsch, Arielle R; Steinley, Douglas; Slutske, Wendy S
2014-09-01
Although socializing effects of friends' drinking on adolescent drinking behavior have been firmly established in previous literature, study results on the importance of gender, as well as the specific role that gender may play in peer socialization, are very mixed. Given the increasing importance of gender in friendships (particularly opposite-sex friendships) during adolescence, it is necessary to better understand the nuanced roles that gender can play in peer socialization effects on alcohol use. In addition, previous studies focusing on the interplay between individual gender and friends' gender have been largely dyadic; less is known about potential gendered effects of broader social networks. The current study sought to further investigate potential effects of gender on friends' influence on adolescent drinking behavior with particular emphasis on the number of same-sex and opposite-sex friends within one's friendship network, as well as closeness to these friends. Using Waves I and II of the saturated sample of the National Longitudinal Study of Adolescent Health (Add Health), adolescent friendship networks were used to calculate the mean drinking behaviors of adolescent friends. Multi-level models estimated the effects of individual drinking behaviors, friend drinking behaviors, and school-level drinking behaviors on adolescent drinking 1 year later, as well as moderating effects of gender composition of friendship groups and male and female friend closeness on the relationship between friends' drinking behaviors and adolescent drinking behavior. Results documented that gender composition of friendship groups did not influence the effect of friends' drinking on individual drinking 1 year later. However, closeness to friends did influence this relationship. As closeness to male friends decreased, the influence of their drinking behavior increased, for both boys and girls. A similar effect was found for female friends, but only for boys. Female friend closeness did not affect the relationship between peer alcohol socialization and girls' alcohol use. The findings indicate that the role of gender on alcohol socialization may be more complex than previously thought, particularly when examining the potential role that alcohol use may play as a mechanism for social bonding within opposite-sex friendships and same-sex male friendships.
A Face Attention Technique for a Robot Able to Interpret Facial Expressions
NASA Astrophysics Data System (ADS)
Simplício, Carlos; Prado, José; Dias, Jorge
Automatic facial expressions recognition using vision is an important subject towards human-robot interaction. Here is proposed a human face focus of attention technique and a facial expressions classifier (a Dynamic Bayesian Network) to incorporate in an autonomous mobile agent whose hardware is composed by a robotic platform and a robotic head. The focus of attention technique is based on the symmetry presented by human faces. By using the output of this module the autonomous agent keeps always targeting the human face frontally. In order to accomplish this, the robot platform performs an arc centered at the human; thus the robotic head, when necessary, moves synchronized. In the proposed probabilistic classifier the information is propagated, from the previous instant, in a lower level of the network, to the current instant. Moreover, to recognize facial expressions are used not only positive evidences but also negative.
Robot Task Commander with Extensible Programming Environment
NASA Technical Reports Server (NTRS)
Hart, Stephen W (Inventor); Wightman, Brian J (Inventor); Dinh, Duy Paul (Inventor); Yamokoski, John D. (Inventor); Gooding, Dustin R (Inventor)
2014-01-01
A system for developing distributed robot application-level software includes a robot having an associated control module which controls motion of the robot in response to a commanded task, and a robot task commander (RTC) in networked communication with the control module over a network transport layer (NTL). The RTC includes a script engine(s) and a GUI, with a processor and a centralized library of library blocks constructed from an interpretive computer programming code and having input and output connections. The GUI provides access to a Visual Programming Language (VPL) environment and a text editor. In executing a method, the VPL is opened, a task for the robot is built from the code library blocks, and data is assigned to input and output connections identifying input and output data for each block. A task sequence(s) is sent to the control module(s) over the NTL to command execution of the task.
Huisman, Chip
2014-05-01
Using stochastic actor-based models for longitudinal network analysis, this study examines the role of friends' smoking attitudes and behavior for Dutch adolescents' smoking behavior in four secondary schools (N = 875). The data were collected in two waves in two small suburban towns under second graders in 2008 to 2009 by means of a standardized questionnaire. Stochastic actor-based models for longitudinal network analysis can control for friendship selection while examining the effect of friends' attitudes and smoking behavior on the smoking behavior of a student. The findings suggest that friends tend to select each other on similar smoking behavior. Influence of friends' smoking behavior seems to play no role. In one school, an effect of friends' attitudes towards smoking on the smoking behavior is found. The implications for future research are to consider attitudes when examining the influence of friendship network on smoking behavior. The main limitation of this study lies in the limited sample, which makes generalizations to the general population difficult.
Reactive navigation for autonomous guided vehicle using neuro-fuzzy techniques
NASA Astrophysics Data System (ADS)
Cao, Jin; Liao, Xiaoqun; Hall, Ernest L.
1999-08-01
A Neuro-fuzzy control method for navigation of an Autonomous Guided Vehicle robot is described. Robot navigation is defined as the guiding of a mobile robot to a desired destination or along a desired path in an environment characterized by as terrain and a set of distinct objects, such as obstacles and landmarks. The autonomous navigate ability and road following precision are mainly influenced by its control strategy and real-time control performance. Neural network and fuzzy logic control techniques can improve real-time control performance for mobile robot due to its high robustness and error-tolerance ability. For a mobile robot to navigate automatically and rapidly, an important factor is to identify and classify mobile robots' currently perceptual environment. In this paper, a new approach of the current perceptual environment feature identification and classification, which are based on the analysis of the classifying neural network and the Neuro- fuzzy algorithm, is presented. The significance of this work lies in the development of a new method for mobile robot navigation.
Gender, Friendship Networks, and Delinquency: A Dynamic Network Approach.
Haynie, Dana L; Doogan, Nathan J; Soller, Brian
2014-11-01
Researchers have examined selection and influence processes in shaping delinquency similarity among friends, but little is known about the role of gender in moderating these relationships. Our objective is to examine differences between adolescent boys and girls regarding delinquency-based selection and influence processes. Using longitudinal network data from adolescents attending two large schools in AddHealth ( N = 1,857) and stochastic actor-oriented models, we evaluate whether girls are influenced to a greater degree by friends' violence or delinquency than boys (influence hypothesis) and whether girls are more likely to select friends based on violent or delinquent behavior than boys (selection hypothesis). The results indicate that girls are more likely than boys to be influenced by their friends' involvement in violence. Although a similar pattern emerges for nonviolent delinquency, the gender differences are not significant. Some evidence shows that boys are influenced toward increasing their violence or delinquency when exposed to more delinquent or violent friends but are immune to reducing their violence or delinquency when associating with less violent or delinquent friends. In terms of selection dynamics, although both boys and girls have a tendency to select friends based on friends' behavior, girls have a stronger tendency to do so, suggesting that among girls, friends' involvement in violence or delinquency is an especially decisive factor for determining friendship ties.
Mobile robotic sensors for perimeter detection and tracking.
Clark, Justin; Fierro, Rafael
2007-02-01
Mobile robot/sensor networks have emerged as tools for environmental monitoring, search and rescue, exploration and mapping, evaluation of civil infrastructure, and military operations. These networks consist of many sensors each equipped with embedded processors, wireless communication, and motion capabilities. This paper describes a cooperative mobile robot network capable of detecting and tracking a perimeter defined by a certain substance (e.g., a chemical spill) in the environment. Specifically, the contributions of this paper are twofold: (i) a library of simple reactive motion control algorithms and (ii) a coordination mechanism for effectively carrying out perimeter-sensing missions. The decentralized nature of the methodology implemented could potentially allow the network to scale to many sensors and to reconfigure when adding/deleting sensors. Extensive simulation results and experiments verify the validity of the proposed cooperative control scheme.
Advanced mechanisms for robotics
NASA Technical Reports Server (NTRS)
Vranish, John M.
1992-01-01
An overview of applied research and development at NASA-Goddard (GSFC) on mechanisms and the collision avoidance skin for robots is presented. First the work on robot end effectors is outlined, followed by a brief discussion on robot-friendly payload latching mechanisms and compliant joints. This, in turn, is followed by the collision avoidance/management skin and the GSFC research on magnetostrictive direct drive motors. Finally, a new project, the artificial muscle, is introduced. Each of the devices is described in sufficient detail to permit a basic understanding of its purpose, fundamental principles of operation, and capabilities. In addition, the development status of each is reported along with descriptions of breadboards and prototypes and their test results. In each case, the implications of the research for commercialization is discussed. The chronology of the presentation will give a clear idea of both the evolution of the R&D in recent years and its likely direction in the future.
Intelligent mobility for robotic vehicles in the army after next
NASA Astrophysics Data System (ADS)
Gerhart, Grant R.; Goetz, Richard C.; Gorsich, David J.
1999-07-01
The TARDEC Intelligent Mobility program addresses several essential technologies necessary to support the army after next (AAN) concept. Ground forces in the AAN time frame will deploy robotic unmanned ground vehicles (UGVs) in high-risk missions to avoid exposing soldiers to both friendly and unfriendly fire. Prospective robotic systems will include RSTA/scout vehicles, combat engineering/mine clearing vehicles, indirect fire artillery and missile launch platforms. The AAN concept requires high on-road and off-road mobility, survivability, transportability/deployability and low logistics burden. TARDEC is developing a robotic vehicle systems integration laboratory (SIL) to evaluate technologies and their integration into future UGV systems. Example technologies include the following: in-hub electric drive, omni-directional wheel and steering configurations, off-road tires, adaptive tire inflation, articulated vehicles, active suspension, mine blast protection, detection avoidance and evasive maneuver. This paper will describe current developments in these areas relative to the TARDEC intelligent mobility program.
McCormack, Gavin R.; Nettel-Aguirre, Alberto; Blackstaffe, Anita; Perry, Rosemary; Hawe, Penelope
2014-01-01
Background. Adolescent friendships have been linked to physical activity levels; however, network characteristics have not been broadly examined. Method. In a cross-sectional analysis of 1061 adolescents (11–15 years), achieving 60 minutes/day of moderate-to-vigorous physical activity (MVPA) and participating in over 2 hours/day of sedentary behaviour were determined based on friendship network characteristics (density; proportion of active/sedentary friends; betweenness centrality; popularity; clique membership) and perceived social support. Results. Adolescents with no friendship nominations participated in less MVPA. For boys and girls, a ten percent point increase in active friends was positively associated with achievement of 60 minutes/day of MVPA (OR 1.11; 95% CI 1.02–1.21, OR 1.14; 95% CI 1.02–1.27, resp.). For boys, higher social support from friends was negatively associated with achieving 60 minutes/day of MVPA (OR 0.63; 95% CI 0.42–0.96). Compared with low density networks, boys in higher density networks were more likely to participate in over 2 hours/day of sedentary behaviour (OR 2.93; 95% CI 1.32–6.49). Social support from friends also modified associations between network characteristics and MVPA and sedentary behaviour. Conclusion. Different network characteristics appeared to have different consequences. The proportion of active close friends was associated with MVPA, while network density was associated with sedentary behaviour. This poses challenges for intervention design. PMID:25328690
A Novel Friendly Jamming Scheme in Industrial Crowdsensing Networks against Eavesdropping Attack.
Li, Xuran; Wang, Qiu; Dai, Hong-Ning; Wang, Hao
2018-06-14
Eavesdropping attack is one of the most serious threats in industrial crowdsensing networks. In this paper, we propose a novel anti-eavesdropping scheme by introducing friendly jammers to an industrial crowdsensing network. In particular, we establish a theoretical framework considering both the probability of eavesdropping attacks and the probability of successful transmission to evaluate the effectiveness of our scheme. Our framework takes into account various channel conditions such as path loss, Rayleigh fading, and the antenna type of friendly jammers. Our results show that using jammers in industrial crowdsensing networks can effectively reduce the eavesdropping risk while having no significant influence on legitimate communications.
A Gradient Optimization Approach to Adaptive Multi-Robot Control
2009-09-01
implemented for deploying a group of three flying robots with downward facing cameras to monitor an environment on the ground. Thirdly, the multi-robot...theoretically proven, and implemented on multi-robot platforms. Thesis Supervisor: Daniela Rus Title: Professor of Electrical Engineering and Computer...often nonlinear, and they are coupled through a network which changes over time. Thirdly, implementing multi-robot controllers requires maintaining mul
Robotic platform for traveling on vertical piping network
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nance, Thomas A; Vrettos, Nick J; Krementz, Daniel
This invention relates generally to robotic systems and is specifically designed for a robotic system that can navigate vertical pipes within a waste tank or similar environment. The robotic system allows a process for sampling, cleaning, inspecting and removing waste around vertical pipes by supplying a robotic platform that uses the vertical pipes to support and navigate the platform above waste material contained in the tank.
Integrated Network Architecture for Sustained Human and Robotic Exploration
NASA Technical Reports Server (NTRS)
Noreen, Gary; Cesarone, Robert; Deutsch, Leslie; Edwards, Charles; Soloff, Jason; Ely, Todd; Cook, Brian; Morabito, David; Hemmati, Hamid; Piazolla, Sabino;
2005-01-01
The National Aeronautics and Space Administration (NASA) Exploration Systems Enterprise is planning a series of human and robotic missions to the Earth's moon and to Mars. These missions will require communication and navigation services. This paper1 sets forth presumed requirements for such services and concepts for lunar and Mars telecommunications network architectures to satisfy the presumed requirements. The paper suggests that an inexpensive ground network would suffice for missions to the near-side of the moon. A constellation of three Lunar Telecommunications Orbiters connected to an inexpensive ground network could provide continuous redundant links to a polar lunar base and its vicinity. For human and robotic missions to Mars, a pair of areostationary satellites could provide continuous redundant links between Earth and a mid-latitude Mars base in conjunction with the Deep Space Network augmented by large arrays of 12-m antennas on Earth.
Bio-Inspired Genetic Algorithms with Formalized Crossover Operators for Robotic Applications.
Zhang, Jie; Kang, Man; Li, Xiaojuan; Liu, Geng-Yang
2017-01-01
Genetic algorithms are widely adopted to solve optimization problems in robotic applications. In such safety-critical systems, it is vitally important to formally prove the correctness when genetic algorithms are applied. This paper focuses on formal modeling of crossover operations that are one of most important operations in genetic algorithms. Specially, we for the first time formalize crossover operations with higher-order logic based on HOL4 that is easy to be deployed with its user-friendly programing environment. With correctness-guaranteed formalized crossover operations, we can safely apply them in robotic applications. We implement our technique to solve a path planning problem using a genetic algorithm with our formalized crossover operations, and the results show the effectiveness of our technique.
Applications of artificial intelligence in safe human-robot interactions.
Najmaei, Nima; Kermani, Mehrdad R
2011-04-01
The integration of industrial robots into the human workspace presents a set of unique challenges. This paper introduces a new sensory system for modeling, tracking, and predicting human motions within a robot workspace. A reactive control scheme to modify a robot's operations for accommodating the presence of the human within the robot workspace is also presented. To this end, a special class of artificial neural networks, namely, self-organizing maps (SOMs), is employed for obtaining a superquadric-based model of the human. The SOM network receives information of the human's footprints from the sensory system and infers necessary data for rendering the human model. The model is then used in order to assess the danger of the robot operations based on the measured as well as predicted human motions. This is followed by the introduction of a new reactive control scheme that results in the least interferences between the human and robot operations. The approach enables the robot to foresee an upcoming danger and take preventive actions before the danger becomes imminent. Simulation and experimental results are presented in order to validate the effectiveness of the proposed method.
From embodied mind to embodied robotics: humanities and system theoretical aspects.
Mainzer, Klaus
2009-01-01
After an introduction (1) the article analyzes the evolution of the embodied mind (2), the innovation of embodied robotics (3), and finally discusses conclusions of embodied robotics for human responsibility (4). Considering the evolution of the embodied mind (2), we start with an introduction of complex systems and nonlinear dynamics (2.1), apply this approach to neural self-organization (2.2), distinguish degrees of complexity of the brain (2.3), explain the emergence of cognitive states by complex systems dynamics (2.4), and discuss criteria for modeling the brain as complex nonlinear system (2.5). The innovation of embodied robotics (3) is a challenge of future technology. We start with the distinction of symbolic and embodied AI (3.1) and explain embodied robots as dynamical systems (3.2). Self-organization needs self-control of technical systems (3.3). Cellular neural networks (CNN) are an example of self-organizing technical systems offering new avenues for neurobionics (3.4). In general, technical neural networks support different kinds of learning robots (3.5). Finally, embodied robotics aim at the development of cognitive and conscious robots (3.6).
Friendship networks and physical activity and sedentary behavior among youth: a systematized review.
Sawka, Keri Jo; McCormack, Gavin R; Nettel-Aguirre, Alberto; Hawe, Penelope; Doyle-Baker, Patricia K
2013-12-01
Low levels of physical activity and increased participation in sedentary leisure-time activities are two important obesity-risk behaviors that impact the health of today's youth. Friend's health behaviors have been shown to influence individual health behaviors; however, current evidence on the specific role of friendship networks in relation to levels of physical activity and sedentary behavior is limited. The purpose of this review was to summarize evidence on friendship networks and both physical activity and sedentary behavior among children and adolescents. After a search of seven scientific databases and reference scans, a total of thirteen articles were eligible for inclusion. All assessed the association between friendship networks and physical activity, while three also assessed sedentary behavior. Overall, higher levels of physical activity among friends are associated with higher levels of physical activity of the individual. Longitudinal studies reveal that an individual's level of physical activity changes to reflect his/her friends' higher level of physical activity. Boys tend to be influenced by their friendship network to a greater extent than girls. There is mixed evidence surrounding a friend's sedentary behavior and individual sedentary behavior. Friends' physical activity level appears to have a significant influence on individual's physical activity level. Evidence surrounding sedentary behavior is limited and mixed. Results from this review could inform effective public health interventions that harness the influence of friends to increase physical activity levels among children and adolescents.
NASA Astrophysics Data System (ADS)
Son, Yurak; Kamano, Takuya; Yasuno, Takashi; Suzuki, Takayuki; Harada, Hironobu
This paper describes the generation of adaptive gait patterns using new Central Pattern Generators (CPGs) including motor dynamic models for a quadruped robot under various environment. The CPGs act as the flexible oscillators of the joints and make the desired angle of the joints. The CPGs are mutually connected each other, and the sets of their coupling parameters are adjusted by genetic algorithm so that the quadruped robot can realize the stable and adequate gait patterns. As a result of generation, the suitable CPG networks for not only a walking straight gait pattern but also rotation gait patterns are obtained. Experimental results demonstrate that the proposed CPG networks are effective to automatically adjust the adaptive gait patterns for the tested quadruped robot under various environment. Furthermore, the target tracking control based on image processing is achieved by combining the generated gait patterns.
Model of a Soft Robotic Actuator with Embedded Fluidic Network
NASA Astrophysics Data System (ADS)
Gamus, Benny; Or, Yizhar; Gat, Amir
2017-11-01
Soft robotics is an emerging bio-inspired concept of actuation, with promising applications for robotic locomotion and manipulation. Focusing on actuation by pressurized embedded fluidic networks, we present analytic formulation and closed-form solutions of an elastic actuator with pressurized fluidic networks. In this work we account for the effects of solid inertia and elasticity, as well as fluid viscosity, which allows modelling the system's step-response and frequency response as well as suggesting mode elimination and isolation techniques. We also present and model the application of viscous-peeling as an actuation mechanism, simplifying the fabrication process by eliminating the need for internal cavities. The theoretical results describing the viscous-elastic-inertial dynamics of the actuator are illustrated by experiments. The approach presented in this work may pave the way for the design and implementation of soft robotic legged locomotion that exploits dynamic effects.
Takeuchi, Ryohei; Harada, Hiroshi; Masuda, Kohji; Ota, Gen-ichiro; Yokoi, Masaki; Teramura, Nobuyasu; Saito, Tomoyuki
2008-06-01
We report the testing of a mobile Robotic Tele-echo system that was placed in an ambulance and successfully transmitted clear real time echo imaging of a patient's abdomen to the destination hospital from where this device was being remotely operated. Two-way communication between the paramedics in this vehicle and a doctor standing by at the hospital was undertaken. The robot was equipped with an ultrasound probe which was remotely controlled by the clinician at the hospital and ultrasound images of the patient were transmitted wirelessly. The quality of the ultrasound images that were transmitted over the public mobile telephone networks and those transmitted over the Multimedia Wireless Access Network (a private networks) were compared. The transmission rate over the public networks and the private networks was approximately 256 Kbps, 3 Mbps respectively. Our results indicate that ultrasound images of far higher definition could be obtained through the private networks.
A Novel Cloud-Based Service Robotics Application to Data Center Environmental Monitoring
Russo, Ludovico Orlando; Rosa, Stefano; Maggiora, Marcello; Bona, Basilio
2016-01-01
This work presents a robotic application aimed at performing environmental monitoring in data centers. Due to the high energy density managed in data centers, environmental monitoring is crucial for controlling air temperature and humidity throughout the whole environment, in order to improve power efficiency, avoid hardware failures and maximize the life cycle of IT devices. State of the art solutions for data center monitoring are nowadays based on environmental sensor networks, which continuously collect temperature and humidity data. These solutions are still expensive and do not scale well in large environments. This paper presents an alternative to environmental sensor networks that relies on autonomous mobile robots equipped with environmental sensors. The robots are controlled by a centralized cloud robotics platform that enables autonomous navigation and provides a remote client user interface for system management. From the user point of view, our solution simulates an environmental sensor network. The system can easily be reconfigured in order to adapt to management requirements and changes in the layout of the data center. For this reason, it is called the virtual sensor network. This paper discusses the implementation choices with regards to the particular requirements of the application and presents and discusses data collected during a long-term experiment in a real scenario. PMID:27509505
Li, Zhijun; Ge, Shuzhi Sam; Liu, Sibang
2014-08-01
This paper investigates optimal feet forces' distribution and control of quadruped robots under external disturbance forces. First, we formulate a constrained dynamics of quadruped robots and derive a reduced-order dynamical model of motion/force. Consider an external wrench on quadruped robots; the distribution of required forces and moments on the supporting legs of a quadruped robot is handled as a tip-point force distribution and used to equilibrate the external wrench. Then, a gradient neural network is adopted to deal with the optimized objective function formulated as to minimize this quadratic objective function subjected to linear equality and inequality constraints. For the obtained optimized tip-point force and the motion of legs, we propose the hybrid motion/force control based on an adaptive neural network to compensate for the perturbations in the environment and approximate feedforward force and impedance of the leg joints. The proposed control can confront the uncertainties including approximation error and external perturbation. The verification of the proposed control is conducted using a simulation.
Leonard, Rosemary; Horsfall, Debbie; Rosenberg, John; Noonan, Kerrie
2015-04-01
Although there is ample evidence of the risk to carers from the burden of caring, there is also evidence that a caring network can relieve the burden on the principal carer, strengthen community relationships, and increase 'Death Literacy' in the community. There is often an assumption that, in caring networks, family and service providers are central and friends and community are marginal. We examined whether this is the case in practice using SNA. To identify the relative positioning of family, friends, community, and service providers in caring networks. In interviews with carers (N = 23) and focus groups with caring networks (N = 13) participants were asked to list the people in the caring network and rate the strength of their relationships to them (0 no relationship to 3 strong relationship). SNA in UCInet was used to map the networks, examine density (number and strength of relationships) across time (when caring began to the present) and across relationship types (family, friends, community, and service providers) supplemented by qualitative data. The analysis revealed significant increases in the density of the networks over time. The density of relationships with friends was similar to that other family. Community and service providers had significantly lower density. Qualitative analysis revealed that often service providers were not seen as part of the networks. To avoid carer burnout, it is important not to make assumptions about where carers obtain support but work with each carer to mobilise any support that is available. © 2015, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Neural networks for satellite remote sensing and robotic sensor interpretation
NASA Astrophysics Data System (ADS)
Martens, Siegfried
Remote sensing of forests and robotic sensor fusion can be viewed, in part, as supervised learning problems, mapping from sensory input to perceptual output. This dissertation develops ARTMAP neural networks for real-time category learning, pattern recognition, and prediction tailored to remote sensing and robotics applications. Three studies are presented. The first two use ARTMAP to create maps from remotely sensed data, while the third uses an ARTMAP system for sensor fusion on a mobile robot. The first study uses ARTMAP to predict vegetation mixtures in the Plumas National Forest based on spectral data from the Landsat Thematic Mapper satellite. While most previous ARTMAP systems have predicted discrete output classes, this project develops new capabilities for multi-valued prediction. On the mixture prediction task, the new network is shown to perform better than maximum likelihood and linear mixture models. The second remote sensing study uses an ARTMAP classification system to evaluate the relative importance of spectral and terrain data for map-making. This project has produced a large-scale map of remotely sensed vegetation in the Sierra National Forest. Network predictions are validated with ground truth data, and maps produced using the ARTMAP system are compared to a map produced by human experts. The ARTMAP Sierra map was generated in an afternoon, while the labor intensive expert method required nearly a year to perform the same task. The robotics research uses an ARTMAP system to integrate visual information and ultrasonic sensory information on a B14 mobile robot. The goal is to produce a more accurate measure of distance than is provided by the raw sensors. ARTMAP effectively combines sensory sources both within and between modalities. The improved distance percept is used to produce occupancy grid visualizations of the robot's environment. The maps produced point to specific problems of raw sensory information processing and demonstrate the benefits of using a neural network system for sensor fusion.
NASA Astrophysics Data System (ADS)
Patkin, M. L.; Rogachev, G. N.
2018-02-01
A method for constructing a multi-agent control system for mobile robots based on training with reinforcement using deep neural networks is considered. Synthesis of the management system is proposed to be carried out with reinforcement training and the modified Actor-Critic method, in which the Actor module is divided into Action Actor and Communication Actor in order to simultaneously manage mobile robots and communicate with partners. Communication is carried out by sending partners at each step a vector of real numbers that are added to the observation vector and affect the behaviour. Functions of Actors and Critic are approximated by deep neural networks. The Critics value function is trained by using the TD-error method and the Actor’s function by using DDPG. The Communication Actor’s neural network is trained through gradients received from partner agents. An environment in which a cooperative multi-agent interaction is present was developed, computer simulation of the application of this method in the control problem of two robots pursuing two goals was carried out.
Mobile robots exploration through cnn-based reinforcement learning.
Tai, Lei; Liu, Ming
2016-01-01
Exploration in an unknown environment is an elemental application for mobile robots. In this paper, we outlined a reinforcement learning method aiming for solving the exploration problem in a corridor environment. The learning model took the depth image from an RGB-D sensor as the only input. The feature representation of the depth image was extracted through a pre-trained convolutional-neural-networks model. Based on the recent success of deep Q-network on artificial intelligence, the robot controller achieved the exploration and obstacle avoidance abilities in several different simulated environments. It is the first time that the reinforcement learning is used to build an exploration strategy for mobile robots through raw sensor information.
Neural-Network Control Of Prosthetic And Robotic Hands
NASA Technical Reports Server (NTRS)
Buckley, Theresa M.
1991-01-01
Electronic neural networks proposed for use in controlling robotic and prosthetic hands and exoskeletal or glovelike electromechanical devices aiding intact but nonfunctional hands. Specific to patient, who activates grasping motion by voice command, by mechanical switch, or by myoelectric impulse. Patient retains higher-level control, while lower-level control provided by neural network analogous to that of miniature brain. During training, patient teaches miniature brain to perform specialized, anthropomorphic movements unique to himself or herself.
Analyzing Cyber-Physical Threats on Robotic Platforms.
Ahmad Yousef, Khalil M; AlMajali, Anas; Ghalyon, Salah Abu; Dweik, Waleed; Mohd, Bassam J
2018-05-21
Robots are increasingly involved in our daily lives. Fundamental to robots are the communication link (or stream) and the applications that connect the robots to their clients or users. Such communication link and applications are usually supported through client/server network connection. This networking system is amenable of being attacked and vulnerable to the security threats. Ensuring security and privacy for robotic platforms is thus critical, as failures and attacks could have devastating consequences. In this paper, we examine several cyber-physical security threats that are unique to the robotic platforms; specifically the communication link and the applications. Threats target integrity, availability and confidential security requirements of the robotic platforms, which use MobileEyes/arnlServer client/server applications. A robot attack tool (RAT) was developed to perform specific security attacks. An impact-oriented approach was adopted to analyze the assessment results of the attacks. Tests and experiments of attacks were conducted in simulation environment and physically on the robot. The simulation environment was based on MobileSim; a software tool for simulating, debugging and experimenting on MobileRobots/ActivMedia platforms and their environments. The robot platform PeopleBot TM was used for physical experiments. The analysis and testing results show that certain attacks were successful at breaching the robot security. Integrity attacks modified commands and manipulated the robot behavior. Availability attacks were able to cause Denial-of-Service (DoS) and the robot was not responsive to MobileEyes commands. Integrity and availability attacks caused sensitive information on the robot to be hijacked. To mitigate security threats, we provide possible mitigation techniques and suggestions to raise awareness of threats on the robotic platforms, especially when the robots are involved in critical missions or applications.
Analyzing Cyber-Physical Threats on Robotic Platforms †
2018-01-01
Robots are increasingly involved in our daily lives. Fundamental to robots are the communication link (or stream) and the applications that connect the robots to their clients or users. Such communication link and applications are usually supported through client/server network connection. This networking system is amenable of being attacked and vulnerable to the security threats. Ensuring security and privacy for robotic platforms is thus critical, as failures and attacks could have devastating consequences. In this paper, we examine several cyber-physical security threats that are unique to the robotic platforms; specifically the communication link and the applications. Threats target integrity, availability and confidential security requirements of the robotic platforms, which use MobileEyes/arnlServer client/server applications. A robot attack tool (RAT) was developed to perform specific security attacks. An impact-oriented approach was adopted to analyze the assessment results of the attacks. Tests and experiments of attacks were conducted in simulation environment and physically on the robot. The simulation environment was based on MobileSim; a software tool for simulating, debugging and experimenting on MobileRobots/ActivMedia platforms and their environments. The robot platform PeopleBotTM was used for physical experiments. The analysis and testing results show that certain attacks were successful at breaching the robot security. Integrity attacks modified commands and manipulated the robot behavior. Availability attacks were able to cause Denial-of-Service (DoS) and the robot was not responsive to MobileEyes commands. Integrity and availability attacks caused sensitive information on the robot to be hijacked. To mitigate security threats, we provide possible mitigation techniques and suggestions to raise awareness of threats on the robotic platforms, especially when the robots are involved in critical missions or applications. PMID:29883403
A Tree Based Self-routing Scheme for Mobility Support in Wireless Sensor Networks
NASA Astrophysics Data System (ADS)
Kim, Young-Duk; Yang, Yeon-Mo; Kang, Won-Seok; Kim, Jin-Wook; An, Jinung
Recently, WSNs (Wireless Sensor Networks) with mobile robot is a growing technology that offer efficient communication services for anytime and anywhere applications. However, the tiny sensor node has very limited network resources due to its low battery power, low data rate, node mobility, and channel interference constraint between neighbors. Thus, in this paper, we proposed a tree based self-routing protocol for autonomous mobile robots based on beacon mode and implemented in real test-bed environments. The proposed scheme offers beacon based real-time scheduling for reliable association process between parent and child nodes. In addition, it supports smooth handover procedure by reducing flooding overhead of control packets. Throughout the performance evaluation by using a real test-bed system and simulation, we illustrate that our proposed scheme demonstrates promising performance for wireless sensor networks with mobile robots.
Evolutionary Space Communications Architectures for Human/Robotic Exploration and Science Missions
NASA Technical Reports Server (NTRS)
Bhasin, Kul; Hayden, Jeffrey L.
2004-01-01
NASA enterprises have growing needs for an advanced, integrated, communications infrastructure that will satisfy the capabilities needed for multiple human, robotic and scientific missions beyond 2015. Furthermore, the reliable, multipoint infrastructure is required to provide continuous, maximum coverage of areas of concentrated activities, such as around Earth and in the vicinity of the Moon or Mars, with access made available on demand of the human or robotic user. As a first step, the definitions of NASA's future space communications and networking architectures are underway. Architectures that describe the communications and networking needed between the nodal regions consisting of Earth, Moon, Lagrange points, Mars, and the places of interest within the inner and outer solar system have been laid out. These architectures will need the modular flexibility that must be included in the communication and networking technologies to enable the infrastructure to grow in capability with time and to transform from supporting robotic missions in the solar system to supporting human ventures to Mars, Jupiter, Jupiter's moons, and beyond. The protocol-based networking capability seamlessly connects the backbone, access, inter-spacecraft and proximity network elements of the architectures employed in the infrastructure. In this paper, we present the summary of NASA's near and long term needs and capability requirements that were gathered by participative methods. We describe an integrated architecture concept and model that will enable communications for evolutionary robotic and human science missions. We then define the communication nodes, their requirements, and various options to connect them.
Evolutionary Space Communications Architectures for Human/Robotic Exploration and Science Missions
NASA Astrophysics Data System (ADS)
Bhasin, Kul; Hayden, Jeffrey L.
2004-02-01
NASA enterprises have growing needs for an advanced, integrated, communications infrastructure that will satisfy the capabilities needed for multiple human, robotic and scientific missions beyond 2015. Furthermore, the reliable, multipoint infrastructure is required to provide continuous, maximum coverage of areas of concentrated activities, such as around Earth and in the vicinity of the Moon or Mars, with access made available on demand of the human or robotic user. As a first step, the definitions of NASA's future space communications and networking architectures are underway. Architectures that describe the communications and networking needed between the nodal regions consisting of Earth, Moon, Lagrange points, Mars, and the places of interest within the inner and outer solar system have been laid out. These architectures will need the modular flexibility that must be included in the communication and networking technologies to enable the infrastructure to grow in capability with time and to transform from supporting robotic missions in the solar system to supporting human ventures to Mars, Jupiter, Jupiter's moons, and beyond. The protocol-based networking capability seamlessly connects the backbone, access, inter-spacecraft and proximity network elements of the architectures employed in the infrastructure. In this paper, we present the summary of NASA's near and long term needs and capability requirements that were gathered by participative methods. We describe an integrated architecture concept and model that will enable communications for evolutionary robotic and human science missions. We then define the communication nodes, their requirements, and various options to connect them.
Higher-order neural network software for distortion invariant object recognition
NASA Technical Reports Server (NTRS)
Reid, Max B.; Spirkovska, Lilly
1991-01-01
The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.
Negriff, Sonya; Valente, Thomas W
2018-02-07
Maltreated youth are at risk for exposure to online sexual content and high-risk sexual behavior, yet characteristics of their online social networks have not been examined as a potential source of vulnerability. The aims of the current study were: 1) to test indicators of size (number of friends) and fragmentation (number of connections between friends) of maltreated young adults' online networks as predictors of intentional and unintentional exposure to sexual content and offline high-risk sexual behavior and 2) to test maltreatment as a moderator of these associations. Participants were selected from a longitudinal study on the effects of child maltreatment (n = 152; Mean age 21.84 years). Data downloaded from Facebook were used to calculate network variables of size (number of friends), density (connections between friends), average degree (average number of connections for each friend), and percent isolates (those not connected to others in the network). Self-reports of intentional and unintentional exposure to online sexual content and offline high-risk sexual behavior were the outcome variables. Multiple-group path modeling showed that only for the maltreated group having a higher percent of isolates in the network predicted intentional exposure to online sexual content and offline high-risk sexual behavior. An implication of this finding is that the composition of the Facebook network may be used as a risk indicator for individuals with child-welfare documented maltreatment experiences. Copyright © 2018. Published by Elsevier Ltd.
Robot computer problem solving system
NASA Technical Reports Server (NTRS)
Becker, J. D.; Merriam, E. W.
1974-01-01
The conceptual, experimental, and practical phases of developing a robot computer problem solving system are outlined. Robot intelligence, conversion of the programming language SAIL to run under the THNEX monitor, and the use of the network to run several cooperating jobs at different sites are discussed.
Fujimoto, Kayo; Valente, Thomas W
2015-01-01
Adolescents interact with their peers in multiple social settings and form various types of peer relationships that affect drinking behavior. Friendship and popularity perceptions constitute critical relationships during adolescence. These two relations are commonly measured by asking students to name their friends, and this network is used to construct drinking exposure and peer status variables. This study takes a multiplex network approach by examining the congruity between friendships and popularity as correlates of adolescent drinking. Using data on friendship and popularity nominations among high school adolescents in Los Angeles, California (N = 1707; five schools), we examined the associations between an adolescent's drinking and drinking by (a) their friends only; (b) multiplexed friendships, friends also perceived as popular; and (c) congruent, multiplexed-friends, close friends perceived as popular. Logistic regression results indicated that friend-only drinking, but not multiplexed-friend drinking, was significantly associated with self-drinking (AOR = 3.51, p < 0.05). However, congruent, multiplexed-friend drinking also was associated with self-drinking (AOR = 3.10, p < 0.05). This study provides insight into how adolescent health behavior is predicated on the multiplexed nature of peer relationships. The results have implications for the design of health promotion interventions for adolescent drinking. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.
Fujimoto, Kayo; Valente, Thomas W.
2014-01-01
Adolescents interact with their peers in multiple social settings and form various types of peer relationships that affect drinking behavior. Friendship and popularity perceptions constitute critical relationships during adolescence. These two relations are commonly measured by asking students to name their friends, and this network is used to construct drinking exposure and peer status variables. This study takes a multiplex network approach by examining the congruity between friendships and popularity as correlates of adolescent drinking. Using data on friendship and popularity nominations among high school adolescents in Los Angeles, California (N = 1707; five schools), we examined the associations between an adolescent's drinking and drinking by (a) their friends only; (b) multiplexed friendships, friends also perceived as popular; and (c) congruent, multiplexed-friends, close friends perceived as popular. Logistic regression results indicated that friend-only drinking, but not multiplexed-friend drinking, was significantly associated with self-drinking (AOR = 3.51, p < 0.05). However, congruent, multiplexed-friend drinking also was associated with self-drinking (AOR = 3.10, p < 0.05). This study provides insight into how adolescent health behavior is predicated on the multiplexed nature of peer relationships. The results have implications for the design of health promotion interventions for adolescent drinking. PMID:24913275
Social Networks as a Critical Pathway for Public Education in IYA2009
NASA Astrophysics Data System (ADS)
Plait, P.; Gay, P. L.
2008-11-01
Social networks are websites (or software that distributes media over the Internet) where users can share content to either a list of friends on that site or to anyone who surfs onto their page, and where those friends can interact and discuss the content. By linking to friends online, the users' personal content (pictures, songs, favorite movies, diaries, websites, and so on) is dynamically distributed, and can ``become viral,'' that is, get spread rapidly as more people see it and spread it themselves. Social networks are immensely popular around the planet, especially with teens, and by tapping into these networks IYA can excite and inspire a younger audience. IYA already has a small but growing presence on several of the larger social networks, and more are planned.
Gender, Friendship Networks, and Delinquency: A Dynamic Network Approach**
Haynie, Dana L.; Doogan, Nathan J.; Soller, Brian
2014-01-01
Researchers have examined selection and influence processes in shaping delinquency similarity among friends, but little is known about the role of gender in moderating these relationships. Our objective is to examine differences between adolescent boys and girls regarding delinquency-based selection and influence processes. Using longitudinal network data from adolescents attending two large schools in AddHealth (N = 1,857) and stochastic actor-oriented models, we evaluate whether girls are influenced to a greater degree by friends' violence or delinquency than boys (influence hypothesis) and whether girls are more likely to select friends based on violent or delinquent behavior than boys (selection hypothesis). The results indicate that girls are more likely than boys to be influenced by their friends' involvement in violence. Although a similar pattern emerges for nonviolent delinquency, the gender differences are not significant. Some evidence shows that boys are influenced toward increasing their violence or delinquency when exposed to more delinquent or violent friends but are immune to reducing their violence or delinquency when associating with less violent or delinquent friends. In terms of selection dynamics, although both boys and girls have a tendency to select friends based on friends' behavior, girls have a stronger tendency to do so, suggesting that among girls, friends' involvement in violence or delinquency is an especially decisive factor for determining friendship ties. PMID:26097241
NASA Technical Reports Server (NTRS)
Marzwell, Neville I.; Chen, Alexander Y. K.
1991-01-01
Dexterous coordination of manipulators based on the use of redundant degrees of freedom, multiple sensors, and built-in robot intelligence represents a critical breakthrough in development of advanced manufacturing technology. A cost-effective approach for achieving this new generation of robotics has been made possible by the unprecedented growth of the latest microcomputer and network systems. The resulting flexible automation offers the opportunity to improve the product quality, increase the reliability of the manufacturing process, and augment the production procedures for optimizing the utilization of the robotic system. Moreover, the Advanced Robotic System (ARS) is modular in design and can be upgraded by closely following technological advancements as they occur in various fields. This approach to manufacturing automation enhances the financial justification and ensures the long-term profitability and most efficient implementation of robotic technology. The new system also addresses a broad spectrum of manufacturing demand and has the potential to address both complex jobs as well as highly labor-intensive tasks. The ARS prototype employs the decomposed optimization technique in spatial planning. This technique is implemented to the framework of the sensor-actuator network to establish the general-purpose geometric reasoning system. The development computer system is a multiple microcomputer network system, which provides the architecture for executing the modular network computing algorithms. The knowledge-based approach used in both the robot vision subsystem and the manipulation control subsystems results in the real-time image processing vision-based capability. The vision-based task environment analysis capability and the responsive motion capability are under the command of the local intelligence centers. An array of ultrasonic, proximity, and optoelectronic sensors is used for path planning. The ARS currently has 18 degrees of freedom made up by two articulated arms, one movable robot head, and two charged coupled device (CCD) cameras for producing the stereoscopic views, and articulated cylindrical-type lower body, and an optional mobile base. A functional prototype is demonstrated.
Evolutionary Dynamics of Collective Action in Structured Populations
NASA Astrophysics Data System (ADS)
Santos, Marta Daniela de Almeida
The pervasiveness of cooperation in Nature is not easily explained. If evolution is characterized by competition and survival of the fittest, why should selfish individuals cooperate with each other? Evolutionary Game Theory (EGT) provides a suitable mathematical framework to study this problem, central to many areas of science. Conventionally, interactions between individuals are modeled in terms of one-shot, symmetric 2-Person Dilemmas of Cooperation, but many real-life situations involve decisions within groups with more than 2 individuals, which are best-dealt in the framework of N-Person games. In this Thesis, we investigate the evolutionary dynamics of two paradigmatic collective social dilemmas - the N-Person Prisoner's Dilemma (NPD) and the N-Person Snowdrift Game (NSG) on structured populations, modeled by networks with diverse topological properties. Cooperative strategies are just one example of the many traits that can be transmitted on social networks. Several recent studies based on empirical evidence from a medical database have suggested the existence of a 3 degrees of influence rule, according to which not only our "friends", but also our friends' friends, and our friends' friends' friends, have a non-trivial influence on our decisions. We investigate the degree of peer influence that emerges from the spread of cooperative strategies, opinions and diseases on populations with distinct underlying networks of contacts. Our results show that networks naturally entangle individuals into interactions of many-body nature and that for each network class considered different processes lead to identical degrees of influence. None
Zunzunegui, M V; Koné, A; Johri, M; Béland, F; Wolfson, C; Bergman, H
2004-05-01
The objective was to evaluate the associations between older persons' health status and their social integration and social networks (family, children, friends and community), in two French-speaking, Canadian community dwelling populations aged 65 years and over, using the conceptual framework proposed by Berkman and Thomas. Data were taken from two 1995 surveys conducted in the city of Moncton (n = 1518) and the Montreal neighbourhood of Hochelaga-Maisonneuve (n = 1500). Social engagement (a cumulative index of social activities), networks consisting of friends, family and children and social support were measured using validated scales. Multiple logistic regressions based on structured inclusion of potentially mediating variables were fitted to estimate the associations between health status and social networks. Self-rated health was better for those with a high level of social integration and a strong network of friends in both locations. In addition, in Hochelaga-Maisonneuve family and children networks were positively associated with good health, though the effect of friend networks was attenuated in the presence of disability, good social support from children was associated with good health. Age, sex and education were included as antecedent variables; smoking, alcohol consumption, exercise, locus of control and depressive symptoms were considered intermediary variables between social networks and health. In conclusion, social networks, integration and support demonstrated unique positive associations with health. The nature of these associations may vary between populations and cultures.
A neural network-based exploratory learning and motor planning system for co-robots
Galbraith, Byron V.; Guenther, Frank H.; Versace, Massimiliano
2015-01-01
Collaborative robots, or co-robots, are semi-autonomous robotic agents designed to work alongside humans in shared workspaces. To be effective, co-robots require the ability to respond and adapt to dynamic scenarios encountered in natural environments. One way to achieve this is through exploratory learning, or “learning by doing,” an unsupervised method in which co-robots are able to build an internal model for motor planning and coordination based on real-time sensory inputs. In this paper, we present an adaptive neural network-based system for co-robot control that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. To validate this system we used the 11-degrees-of-freedom RoPro Calliope mobile robot. Through motor babbling of its wheels and arm, the Calliope learned how to relate visual and proprioceptive information to achieve hand-eye-body coordination. By continually evaluating sensory inputs and externally provided goal directives, the Calliope was then able to autonomously select the appropriate wheel and joint velocities needed to perform its assigned task, such as following a moving target or retrieving an indicated object. PMID:26257640
A neural network-based exploratory learning and motor planning system for co-robots.
Galbraith, Byron V; Guenther, Frank H; Versace, Massimiliano
2015-01-01
Collaborative robots, or co-robots, are semi-autonomous robotic agents designed to work alongside humans in shared workspaces. To be effective, co-robots require the ability to respond and adapt to dynamic scenarios encountered in natural environments. One way to achieve this is through exploratory learning, or "learning by doing," an unsupervised method in which co-robots are able to build an internal model for motor planning and coordination based on real-time sensory inputs. In this paper, we present an adaptive neural network-based system for co-robot control that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. To validate this system we used the 11-degrees-of-freedom RoPro Calliope mobile robot. Through motor babbling of its wheels and arm, the Calliope learned how to relate visual and proprioceptive information to achieve hand-eye-body coordination. By continually evaluating sensory inputs and externally provided goal directives, the Calliope was then able to autonomously select the appropriate wheel and joint velocities needed to perform its assigned task, such as following a moving target or retrieving an indicated object.
Robotic Lunar Landers For Science And Exploration
NASA Technical Reports Server (NTRS)
Cohen, B. A.; Bassler, J. A.; Morse, B. J.; Reed, C. L. B.
2010-01-01
NASA Marshall Space Flight Center and The Johns Hopkins University Applied Physics Laboratory have been conducting mission studies and performing risk reduction activities for NASA s robotic lunar lander flight projects. In 2005, the Robotic Lunar Exploration Program Mission #2 (RLEP-2) was selected as an ESMD precursor robotic lander mission to demonstrate precision landing and determine if there was water ice at the lunar poles; however, this project was canceled. Since 2008, the team has been supporting SMD designing small lunar robotic landers for science missions, primarily to establish anchor nodes of the International Lunar Network (ILN), a network of lunar geophysical nodes. Additional mission studies have been conducted to support other objectives of the lunar science community. This paper describes the current status of the MSFC/APL robotic lunar mission studies and risk reduction efforts including high pressure propulsion system testing, structure and mechanism development and testing, long cycle time battery testing, combined GN&C and avionics testing, and two autonomous lander test articles.
Quadrupedal Robot Locomotion: A Biologically Inspired Approach and Its Hardware Implementation
Espinal, A.; Rostro-Gonzalez, H.; Carpio, M.; Guerra-Hernandez, E. I.; Ornelas-Rodriguez, M.; Puga-Soberanes, H. J.; Sotelo-Figueroa, M. A.; Melin, P.
2016-01-01
A bioinspired locomotion system for a quadruped robot is presented. Locomotion is achieved by a spiking neural network (SNN) that acts as a Central Pattern Generator (CPG) producing different locomotion patterns represented by their raster plots. To generate these patterns, the SNN is configured with specific parameters (synaptic weights and topologies), which were estimated by a metaheuristic method based on Christiansen Grammar Evolution (CGE). The system has been implemented and validated on two robot platforms; firstly, we tested our system on a quadruped robot and, secondly, on a hexapod one. In this last one, we simulated the case where two legs of the hexapod were amputated and its locomotion mechanism has been changed. For the quadruped robot, the control is performed by the spiking neural network implemented on an Arduino board with 35% of resource usage. In the hexapod robot, we used Spartan 6 FPGA board with only 3% of resource usage. Numerical results show the effectiveness of the proposed system in both cases. PMID:27436997
Quadrupedal Robot Locomotion: A Biologically Inspired Approach and Its Hardware Implementation.
Espinal, A; Rostro-Gonzalez, H; Carpio, M; Guerra-Hernandez, E I; Ornelas-Rodriguez, M; Puga-Soberanes, H J; Sotelo-Figueroa, M A; Melin, P
2016-01-01
A bioinspired locomotion system for a quadruped robot is presented. Locomotion is achieved by a spiking neural network (SNN) that acts as a Central Pattern Generator (CPG) producing different locomotion patterns represented by their raster plots. To generate these patterns, the SNN is configured with specific parameters (synaptic weights and topologies), which were estimated by a metaheuristic method based on Christiansen Grammar Evolution (CGE). The system has been implemented and validated on two robot platforms; firstly, we tested our system on a quadruped robot and, secondly, on a hexapod one. In this last one, we simulated the case where two legs of the hexapod were amputated and its locomotion mechanism has been changed. For the quadruped robot, the control is performed by the spiking neural network implemented on an Arduino board with 35% of resource usage. In the hexapod robot, we used Spartan 6 FPGA board with only 3% of resource usage. Numerical results show the effectiveness of the proposed system in both cases.
Center for Neural Engineering: applications of pulse-coupled neural networks
NASA Astrophysics Data System (ADS)
Malkani, Mohan; Bodruzzaman, Mohammad; Johnson, John L.; Davis, Joel
1999-03-01
Pulsed-Coupled Neural Network (PCNN) is an oscillatory model neural network where grouping of cells and grouping among the groups that form the output time series (number of cells that fires in each input presentation also called `icon'). This is based on the synchronicity of oscillations. Recent work by Johnson and others demonstrated the functional capabilities of networks containing such elements for invariant feature extraction using intensity maps. PCNN thus presents itself as a more biologically plausible model with solid functional potential. This paper will present the summary of several projects and their results where we successfully applied PCNN. In project one, the PCNN was applied for object recognition and classification through a robotic vision system. The features (icons) generated by the PCNN were then fed into a feedforward neural network for classification. In project two, we developed techniques for sensory data fusion. The PCNN algorithm was implemented and tested on a B14 mobile robot. The PCNN-based features were extracted from the images taken from the robot vision system and used in conjunction with the map generated by data fusion of the sonar and wheel encoder data for the navigation of the mobile robot. In our third project, we applied the PCNN for speaker recognition. The spectrogram image of speech signals are fed into the PCNN to produce invariant feature icons which are then fed into a feedforward neural network for speaker identification.
Modular architecture for robotics and teleoperation
Anderson, Robert J.
1996-12-03
Systems and methods for modularization and discretization of real-time robot, telerobot and teleoperation systems using passive, network based control laws. Modules consist of network one-ports and two-ports. Wave variables and position information are passed between modules. The behavior of each module is decomposed into uncoupled linear-time-invariant, and coupled, nonlinear memoryless elements and then are separately discretized.
Integrated network architecture for sustained human and robotic exploration
NASA Technical Reports Server (NTRS)
Noreen, Gary K.; Cesarone, Robert; Deutsch, Leslie; Edwards, Charlie; Soloff, Jason; Ely, Todd; Cook, Brian; Morabito, David; Hemmati, Hamid; Piazzolla, Sabino;
2005-01-01
The National Aeronautics and Space Administration (NASA) Exploration Systems Mission Directorate is planning a series of human and robotic missions to the Earth's moon and to Mars. These missions will require telecommunication and navigation services. This paper sets forth presumed requirements for such services and presents strawman lunar and Mars telecommunications network architectures to satisfy the presumed requirements.
Video-based convolutional neural networks for activity recognition from robot-centric videos
NASA Astrophysics Data System (ADS)
Ryoo, M. S.; Matthies, Larry
2016-05-01
In this evaluation paper, we discuss convolutional neural network (CNN)-based approaches for human activity recognition. In particular, we investigate CNN architectures designed to capture temporal information in videos and their applications to the human activity recognition problem. There have been multiple previous works to use CNN-features for videos. These include CNNs using 3-D XYT convolutional filters, CNNs using pooling operations on top of per-frame image-based CNN descriptors, and recurrent neural networks to learn temporal changes in per-frame CNN descriptors. We experimentally compare some of these different representatives CNNs while using first-person human activity videos. We especially focus on videos from a robots viewpoint, captured during its operations and human-robot interactions.
Friends, Depressive Symptoms, and Life Satisfaction Among Older Korean Americans.
Roh, Soonhee; Lee, Yeon-Shim; Lee, Kyoung Hag; Shibusawa, Tazuko; Yoo, Grace J
2015-08-01
This study examined the interactive effects of social network support and depressive symptoms on life satisfaction among older Korean Americans (KAs). Using data from a sample of 200 elders in a large metropolitan area (M age = 72.50, SD = 5.15), hierarchical regression analysis was used to examine the interaction between social network support and depressive symptoms on life satisfaction among older KAs. After controlling for demographic variables, both social network support and depressive symptoms were identified as predictors for life satisfaction. Interaction effects indicated strong associations between higher social network support specifically from friends and lower depressive symptoms with higher levels of life satisfaction. Findings highlight the important role that friends play in terms of social network support for the mental health of older KAs, and the need for geriatric practitioners to monitor and assess the quality of social network support-including friendships-when working with older KAs.
Bridging the gap between motor imagery and motor execution with a brain-robot interface.
Bauer, Robert; Fels, Meike; Vukelić, Mathias; Ziemann, Ulf; Gharabaghi, Alireza
2015-03-01
According to electrophysiological studies motor imagery and motor execution are associated with perturbations of brain oscillations over spatially similar cortical areas. By contrast, neuroimaging and lesion studies suggest that at least partially distinct cortical networks are involved in motor imagery and execution. We sought to further disentangle this relationship by studying the role of brain-robot interfaces in the context of motor imagery and motor execution networks. Twenty right-handed subjects performed several behavioral tasks as indicators for imagery and execution of movements of the left hand, i.e. kinesthetic imagery, visual imagery, visuomotor integration and tonic contraction. In addition, subjects performed motor imagery supported by haptic/proprioceptive feedback from a brain-robot-interface. Principal component analysis was applied to assess the relationship of these indicators. The respective cortical resting state networks in the α-range were investigated by electroencephalography using the phase slope index. We detected two distinct abilities and cortical networks underlying motor control: a motor imagery network connecting the left parietal and motor areas with the right prefrontal cortex and a motor execution network characterized by transmission from the left to right motor areas. We found that a brain-robot-interface might offer a way to bridge the gap between these networks, opening thereby a backdoor to the motor execution system. This knowledge might promote patient screening and may lead to novel treatment strategies, e.g. for the rehabilitation of hemiparesis after stroke. Copyright © 2014 Elsevier Inc. All rights reserved.
ERIC Educational Resources Information Center
Zula, Ken; Yarrish, Karen K.; Pawelzik, Walter
2011-01-01
Social networking sites such as Facebook, LinkedIn, and Twitter are widely regarded as an exciting opportunity to communicate with friends, especially for college students. The overall response to social networking tends to be one of trust regarding a generation that, supposedly has many friends but little sense of privacy. Employers use social…
Singh, Lucky; Singh, Prashant Kumar; Arokiasamy, Perianayagam
2016-06-01
The rapid growth of the older population in India draws attention to the factors that contribute to their changing health realities. However, there has hardly been any study in India that has looked at the effects of specific social networks with children, relatives, friends and confidant on depression among older adults. The objective of the study is to investigate the association between social network and depression among the rural elderly. The study population comprised over 630 older adults (aged 60 and above) from the rural areas of Varanasi, Uttar Pradesh. We adopted Berkman's theoretical model of the impact of social relations on depression among the elderly in the Indian context. Results of the Confirmatory Factor Analysis (CFA) demonstrated that the four specific social network types: children, relatives, friends and confidant were tenable. The results showed that a better social network with 'friends/neighbours' was protective against depression among the rural elderly. This clearly points to the need for more social network centres for older adults, so that they can interact with friends within the community or between communities and participate in group activities.
Leveraging Large-Scale Semantic Networks for Adaptive Robot Task Learning and Execution.
Boteanu, Adrian; St Clair, Aaron; Mohseni-Kabir, Anahita; Saldanha, Carl; Chernova, Sonia
2016-12-01
This work seeks to leverage semantic networks containing millions of entries encoding assertions of commonsense knowledge to enable improvements in robot task execution and learning. The specific application we explore in this project is object substitution in the context of task adaptation. Humans easily adapt their plans to compensate for missing items in day-to-day tasks, substituting a wrap for bread when making a sandwich, or stirring pasta with a fork when out of spoons. Robot plan execution, however, is far less robust, with missing objects typically leading to failure if the robot is not aware of alternatives. In this article, we contribute a context-aware algorithm that leverages the linguistic information embedded in the task description to identify candidate substitution objects without reliance on explicit object affordance information. Specifically, we show that the task context provided by the task labels within the action structure of a task plan can be leveraged to disambiguate information within a noisy large-scale semantic network containing hundreds of potential object candidates to identify successful object substitutions with high accuracy. We present two extensive evaluations of our work on both abstract and real-world robot tasks, showing that the substitutions made by our system are valid, accepted by users, and lead to a statistically significant reduction in robot learning time. In addition, we report the outcomes of testing our approach with a large number of crowd workers interacting with a robot in real time.
Fire Extinguisher Robot Using Ultrasonic Camera and Wi-Fi Network Controlled with Android Smartphone
NASA Astrophysics Data System (ADS)
Siregar, B.; Purba, H. A.; Efendi, S.; Fahmi, F.
2017-03-01
Fire disasters can occur anytime and result in high losses. It is often that fire fighters cannot access the source of fire due to the damage of building and very high temperature, or even due to the presence of explosive materials. With such constraints and high risk in the handling of the fire, a technological breakthrough that can help fighting the fire is necessary. Our paper proposed the use of robots to extinguish the fire that can be controlled from a specified distance in order to reduce the risk. A fire extinguisher robot was assembled with the intention to extinguish the fire by using a water pump as actuators. The robot movement was controlled using Android smartphones via Wi-fi networks utilizing Wi-fi module contained in the robot. User commands were sent to the microcontroller on the robot and then translated into robotic movement. We used ATMega8 as main microcontroller in the robot. The robot was equipped with cameras and ultrasonic sensors. The camera played role in giving feedback to user and in finding the source of fire. Ultrasonic sensors were used to avoid collisions during movement. Feedback provided by camera on the robot displayed on a screen of smartphone. In lab, testing environment the robot can move following the user command such as turn right, turn left, forward and backward. The ultrasonic sensors worked well that the robot can be stopped at a distance of less than 15 cm. In the fire test, the robot can perform the task properly to extinguish the fire.
Social Support Systems and Social Network Characteristics of Older Adults with HIV.
Brennan-Ing, Mark; Seidel, Liz; Karpiak, Stephen E
Social networks of older adults with HIV have been characterized as fragile, with a greater reliance on friends as compared to family. However, we know little about the subgroup differences in the social network constellations of this population, how such characteristics are related to social support resources, and their relationship with psychosocial well-being. We developed a typology of social networks of older HIV-positive adults and examined if they would be related to receipt of informal assistance, perceptions of support sufficiency, and psychosocial well-being. Data were obtained from Research on Older Adults with HIV (n = 914). Participants were 50 years and older, HIV positive, and diverse in terms of race/ethnicity, gender, and sexual orientation. Cluster analysis identified Isolated, Friend-centered, and Integrated social network types. The Isolated reported significantly lower levels of assistance, lower perceptions of support availability and adequacy, greater stigma and psychological distress, and lower well-being compared to their peers. While friends dominate many social networks in this population, a more nuanced interpretation is needed; many have no friends and a substantial proportion receive significant family support. Those with Isolated network types will likely need to access a high volume of community-based services as they age as they lack informal support resources. © 2017 S. Karger AG, Basel.
Yoo, Sung Jin; Park, Jin Bae; Choi, Yoon Ho
2006-12-01
A new method for the robust control of flexible-joint (FJ) robots with model uncertainties in both robot dynamics and actuator dynamics is proposed. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self-recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides the ability to overcome the "explosion of complexity" problem in backstepping controllers. The SRWNNs are used to observe the arbitrary model uncertainties of FJ robots, and all their weights are trained online. From the Lyapunov stability analysis, their adaptation laws are induced, and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a three-link FJ robot are utilized to validate the good position tracking performance and robustness against payload uncertainties and external disturbances of the proposed control system.
Tomini, Florian; Tomini, Sonila M; Groot, Wim
2016-12-01
Networks of family and friends are a source of support and are generally associated with higher life satisfaction values among older adults. On the other hand, older adults who are satisfied with their life may be more able to develop and maintain a wider social network. For this reason, the causal link between size and composition of the social networks and satisfaction with life is yet to be explored. This paper investigates the effect of the 'size', (number of family and friends, and network) and the 'composition' (the proportion of friends over total number of persons) of the social network on life satisfaction among older adults (50+). Moreover, we also investigate the patterns of this relation between different European countries. Data from the 4 th wave of Survey of Health, Ageing and Retirement in Europe and an instrumental variable approach are used to estimate the extent of the relation between life satisfaction and size and composition of social networks. Respondents in Western and Northern European (WNE) countries report larger networks than respondents in Eastern and Southern European (ESE) countries. However, the positive relationship between network size and life satisfaction is consistent across countries. On the other hand, the share of friends in the network appears to be generally negatively related to satisfaction with life, though results are not statistically significant for all countries. Apparently, a larger personal network is important for older adults (50+) to be more satisfied with life. Our results suggest that this relation is particularly positive if the network is comprised of family members.
Jung, Jun-Young; Heo, Wonho; Yang, Hyundae; Park, Hyunsub
2015-01-01
An exact classification of different gait phases is essential to enable the control of exoskeleton robots and detect the intentions of users. We propose a gait phase classification method based on neural networks using sensor signals from lower limb exoskeleton robots. In such robots, foot sensors with force sensing registers are commonly used to classify gait phases. We describe classifiers that use the orientation of each lower limb segment and the angular velocities of the joints to output the current gait phase. Experiments to obtain the input signals and desired outputs for the learning and validation process are conducted, and two neural network methods (a multilayer perceptron and nonlinear autoregressive with external inputs (NARX)) are used to develop an optimal classifier. Offline and online evaluations using four criteria are used to compare the performance of the classifiers. The proposed NARX-based method exhibits sufficiently good performance to replace foot sensors as a means of classifying gait phases. PMID:26528986
Jung, Jun-Young; Heo, Wonho; Yang, Hyundae; Park, Hyunsub
2015-10-30
An exact classification of different gait phases is essential to enable the control of exoskeleton robots and detect the intentions of users. We propose a gait phase classification method based on neural networks using sensor signals from lower limb exoskeleton robots. In such robots, foot sensors with force sensing registers are commonly used to classify gait phases. We describe classifiers that use the orientation of each lower limb segment and the angular velocities of the joints to output the current gait phase. Experiments to obtain the input signals and desired outputs for the learning and validation process are conducted, and two neural network methods (a multilayer perceptron and nonlinear autoregressive with external inputs (NARX)) are used to develop an optimal classifier. Offline and online evaluations using four criteria are used to compare the performance of the classifiers. The proposed NARX-based method exhibits sufficiently good performance to replace foot sensors as a means of classifying gait phases.
Child-Robot Interactions for Second Language Tutoring to Preschool Children
Vogt, Paul; de Haas, Mirjam; de Jong, Chiara; Baxter, Peta; Krahmer, Emiel
2017-01-01
In this digital age social robots will increasingly be used for educational purposes, such as second language tutoring. In this perspective article, we propose a number of design features to develop a child-friendly social robot that can effectively support children in second language learning, and we discuss some technical challenges for developing these. The features we propose include choices to develop the robot such that it can act as a peer to motivate the child during second language learning and build trust at the same time, while still being more knowledgeable than the child and scaffolding that knowledge in adult-like manner. We also believe that the first impressions children have about robots are crucial for them to build trust and common ground, which would support child-robot interactions in the long term. We therefore propose a strategy to introduce the robot in a safe way to toddlers. Other features relate to the ability to adapt to individual children’s language proficiency, respond contingently, both temporally and semantically, establish joint attention, use meaningful gestures, provide effective feedback and monitor children’s learning progress. Technical challenges we observe include automatic speech recognition (ASR) for children, reliable object recognition to facilitate semantic contingency and establishing joint attention, and developing human-like gestures with a robot that does not have the same morphology humans have. We briefly discuss an experiment in which we investigate how children respond to different forms of feedback the robot can give. PMID:28303094
Child-Robot Interactions for Second Language Tutoring to Preschool Children.
Vogt, Paul; de Haas, Mirjam; de Jong, Chiara; Baxter, Peta; Krahmer, Emiel
2017-01-01
In this digital age social robots will increasingly be used for educational purposes, such as second language tutoring. In this perspective article, we propose a number of design features to develop a child-friendly social robot that can effectively support children in second language learning, and we discuss some technical challenges for developing these. The features we propose include choices to develop the robot such that it can act as a peer to motivate the child during second language learning and build trust at the same time, while still being more knowledgeable than the child and scaffolding that knowledge in adult-like manner. We also believe that the first impressions children have about robots are crucial for them to build trust and common ground, which would support child-robot interactions in the long term. We therefore propose a strategy to introduce the robot in a safe way to toddlers. Other features relate to the ability to adapt to individual children's language proficiency, respond contingently, both temporally and semantically, establish joint attention, use meaningful gestures, provide effective feedback and monitor children's learning progress. Technical challenges we observe include automatic speech recognition (ASR) for children, reliable object recognition to facilitate semantic contingency and establishing joint attention, and developing human-like gestures with a robot that does not have the same morphology humans have. We briefly discuss an experiment in which we investigate how children respond to different forms of feedback the robot can give.
Sarikaya, Duygu; Corso, Jason J; Guru, Khurshid A
2017-07-01
Video understanding of robot-assisted surgery (RAS) videos is an active research area. Modeling the gestures and skill level of surgeons presents an interesting problem. The insights drawn may be applied in effective skill acquisition, objective skill assessment, real-time feedback, and human-robot collaborative surgeries. We propose a solution to the tool detection and localization open problem in RAS video understanding, using a strictly computer vision approach and the recent advances of deep learning. We propose an architecture using multimodal convolutional neural networks for fast detection and localization of tools in RAS videos. To the best of our knowledge, this approach will be the first to incorporate deep neural networks for tool detection and localization in RAS videos. Our architecture applies a region proposal network (RPN) and a multimodal two stream convolutional network for object detection to jointly predict objectness and localization on a fusion of image and temporal motion cues. Our results with an average precision of 91% and a mean computation time of 0.1 s per test frame detection indicate that our study is superior to conventionally used methods for medical imaging while also emphasizing the benefits of using RPN for precision and efficiency. We also introduce a new data set, ATLAS Dione, for RAS video understanding. Our data set provides video data of ten surgeons from Roswell Park Cancer Institute, Buffalo, NY, USA, performing six different surgical tasks on the daVinci Surgical System (dVSS) with annotations of robotic tools per frame.
Cheng, Sheung-Tak; Leung, Edward M F; Chan, Trista Wai Sze
2014-06-01
This study examined the associations between social network types and peak expiratory flow (PEF), and whether these associations were mediated by social and physical activities and mood. Nine hundred twenty-four community-dwelling Chinese older adults, who were classified into five network types (diverse, friend-focused, family-focused, distant family, and restricted), provided data on demographics, social and physical activities, mood, smoking, chronic diseases, and instrumental activities of daily living. PEF and biological covariates, including blood lipids and glucose, blood pressure, and height and weight, were assessed. Two measures of PEF were analyzed: the raw reading in L/min and the reading expressed as percentage of predicted normal value on the basis of age, sex, and height. Diverse, friend-focused, and distant family networks were hypothesized to have better PEF values compared with restricted networks, through higher physical and/or social activities. No relative advantage was predicted for family-focused networks because such networks tend to be associated with lower physical activity. Older adults with diverse, friend-focused, and distant family networks had significantly better PEF measures than those with restricted networks. The associations between diverse network and PEF measures were partially mediated by physical exercise and socializing activity. The associations between friend-focused network and PEF measures were partially mediated by socializing activity. No significant PEF differences between family-focused and restricted networks were found. Findings suggest that social network types are associated with PEF in older adults, and that network-type differences in physical and socializing activity is partly responsible for this relationship. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Educational Robotics: Open Questions and New Challenges
ERIC Educational Resources Information Center
Alimisis, Dimitris
2013-01-01
This paper investigates the current situation in the field of educational robotics and identifies new challenges and trends focusing on the use of robotic technologies as a tool that will support creativity and other 21st-century learning skills. Finally, conclusions and proposals are presented for promoting cooperation and networking of…
Milde, Moritz B.; Blum, Hermann; Dietmüller, Alexander; Sumislawska, Dora; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia
2017-01-01
Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware. PMID:28747883
Intelligent, self-contained robotic hand
Krutik, Vitaliy; Doo, Burt; Townsend, William T.; Hauptman, Traveler; Crowell, Adam; Zenowich, Brian; Lawson, John
2007-01-30
A robotic device has a base and at least one finger having at least two links that are connected in series on rotary joints with at least two degrees of freedom. A brushless motor and an associated controller are located at each joint to produce a rotational movement of a link. Wires for electrical power and communication serially connect the controllers in a distributed control network. A network operating controller coordinates the operation of the network, including power distribution. At least one, but more typically two to five, wires interconnect all the controllers through one or more joints. Motor sensors and external world sensors monitor operating parameters of the robotic hand. The electrical signal output of the sensors can be input anywhere on the distributed control network. V-grooves on the robotic hand locate objects precisely and assist in gripping. The hand is sealed, immersible and has electrical connections through the rotary joints for anodizing in a single dunk without masking. In various forms, this intelligent, self-contained, dexterous hand, or combinations of such hands, can perform a wide variety of object gripping and manipulating tasks, as well as locomotion and combinations of locomotion and gripping.
Process for anodizing a robotic device
Townsend, William T [Weston, MA
2011-11-08
A robotic device has a base and at least one finger having at least two links that are connected in series on rotary joints with at least two degrees of freedom. A brushless motor and an associated controller are located at each joint to produce a rotational movement of a link. Wires for electrical power and communication serially connect the controllers in a distributed control network. A network operating controller coordinates the operation of the network, including power distribution. At least one, but more typically two to five, wires interconnect all the controllers through one or more joints. Motor sensors and external world sensors monitor operating parameters of the robotic hand. The electrical signal output of the sensors can be input anywhere on the distributed control network. V-grooves on the robotic hand locate objects precisely and assist in gripping. The hand is sealed, immersible and has electrical connections through the rotary joints for anodizing in a single dunk without masking. In various forms, this intelligent, self-contained, dexterous hand, or combinations of such hands, can perform a wide variety of object gripping and manipulating tasks, as well as locomotion and combinations of locomotion and gripping.
Milde, Moritz B; Blum, Hermann; Dietmüller, Alexander; Sumislawska, Dora; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia
2017-01-01
Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware.
The Contagious Spread of Violence Among US Adolescents Through Social Networks.
Bond, Robert M; Bushman, Brad J
2017-02-01
To test the hypothesis that violence among US adolescents spreads like a contagious disease through social networks. Participants were a nationally representative sample of 90 118 US students aged 12 to 18 years who were involved in the National Longitudinal Study of Adolescent Health. Violence was assessed by having participants report the number of times in the preceding 12 months they had been involved in a serious physical fight, had hurt someone badly, and had pulled a weapon on someone. Participants were 48% more likely to have been involved in a serious fight, 183% more likely to have hurt someone badly, and 140% more likely to have pulled a weapon on someone if a friend had engaged in the same behavior. The influence spread up to 4 degrees of separation (i.e., friend of friend of friend of friend) for serious fights, 2 degrees for hurting someone badly, and 3 degrees for pulling a weapon on someone. Adolescents were more likely to engage in violent behavior if their friends did the same, and contagion of violence extended beyond immediate friends to friends of friends.
Peer influences on moral disengagement in late childhood and early adolescence.
Caravita, Simona C S; Sijtsema, Jelle J; Rambaran, J Ashwin; Gini, Gianluca
2014-02-01
Moral disengagement processes are cognitive self-justification processes of transgressive actions that have been hypothesized to be learned and socialized within social contexts. The current study aimed at investigating socialization of moral disengagement by friends in two developmentally different age groups, namely late childhood (age: 9-10 years; n = 133, 42.9% girls) and early adolescence (age: 11-14 years; n = 236, 40.6% girls) over a 1-year period. Specifically, the current study examined whether similarity in moral disengagement between friends was the result of friends' influence or friend selection. Moreover, gender (42% girls), individual bullying behavior, and perceived popularity status were examined as potential moderators of socialization for moral disengagement within friendship networks. Self-report measures were used to assess moral disengagement, sociometric questions and a peer-nomination scale for friendship networks and bullying behavior, respectively. Longitudinal social network analysis (RSiena) was used to study change of moral disengagement in friendship networks during a 1-year interval. In early adolescence, friends were more likely to be similar to each other over time and this was explained only by influence processes and not by selection processes. Gender, bullying, and perceived popularity did not moderate the friends' influence on moral disengagement over time. Results indicate that self-justification processes change over time already in late childhood, but only in early adolescence this change is likely to be dependent upon peers' moral disengagement.
Nabi, Robin L; Prestin, Abby; So, Jiyeon
2013-10-01
There is clear evidence that interpersonal social support impacts stress levels and, in turn, degree of physical illness and psychological well-being. This study examines whether mediated social networks serve the same palliative function. A survey of 401 undergraduate Facebook users revealed that, as predicted, number of Facebook friends associated with stronger perceptions of social support, which in turn associated with reduced stress, and in turn less physical illness and greater well-being. This effect was minimized when interpersonal network size was taken into consideration. However, for those who have experienced many objective life stressors, the number of Facebook friends emerged as the stronger predictor of perceived social support. The "more-friends-the-better" heuristic is proposed as the most likely explanation for these findings.
Garnier, Simon; Combe, Maud; Jost, Christian; Theraulaz, Guy
2013-01-01
Interactions between individuals and the structure of their environment play a crucial role in shaping self-organized collective behaviors. Recent studies have shown that ants crossing asymmetrical bifurcations in a network of galleries tend to follow the branch that deviates the least from their incoming direction. At the collective level, the combination of this tendency and the pheromone-based recruitment results in a greater likelihood of selecting the shortest path between the colony's nest and a food source in a network containing asymmetrical bifurcations. It was not clear however what the origin of this behavioral bias is. Here we propose that it results from a simple interaction between the behavior of the ants and the geometry of the network, and that it does not require the ability to measure the angle of the bifurcation. We tested this hypothesis using groups of ant-like robots whose perceptual and cognitive abilities can be fully specified. We programmed them only to lay down and follow light trails, avoid obstacles and move according to a correlated random walk, but not to use more sophisticated orientation methods. We recorded the behavior of the robots in networks of galleries presenting either only symmetrical bifurcations or a combination of symmetrical and asymmetrical bifurcations. Individual robots displayed the same pattern of branch choice as individual ants when crossing a bifurcation, suggesting that ants do not actually measure the geometry of the bifurcations when travelling along a pheromone trail. Finally at the collective level, the group of robots was more likely to select one of the possible shorter paths between two designated areas when moving in an asymmetrical network, as observed in ants. This study reveals the importance of the shape of trail networks for foraging in ants and emphasizes the underestimated role of the geometrical properties of transportation networks in general. PMID:23555202
Telerobotic management system: coordinating multiple human operators with multiple robots
NASA Astrophysics Data System (ADS)
King, Jamie W.; Pretty, Raymond; Brothers, Brendan; Gosine, Raymond G.
2003-09-01
This paper describes an application called the Tele-robotic management system (TMS) for coordinating multiple operators with multiple robots for applications such as underground mining. TMS utilizes several graphical interfaces to allow the user to define a partially ordered plan for multiple robots. This plan is then converted to a Petri net for execution and monitoring. TMS uses a distributed framework to allow robots and operators to easily integrate with the applications. This framework allows robots and operators to join the network and advertise their capabilities through services. TMS then decides whether tasks should be dispatched to a robot or a remote operator based on the services offered by the robots and operators.
Estimation of Visual Maps with a Robot Network Equipped with Vision Sensors
Gil, Arturo; Reinoso, Óscar; Ballesta, Mónica; Juliá, Miguel; Payá, Luis
2010-01-01
In this paper we present an approach to the Simultaneous Localization and Mapping (SLAM) problem using a team of autonomous vehicles equipped with vision sensors. The SLAM problem considers the case in which a mobile robot is equipped with a particular sensor, moves along the environment, obtains measurements with its sensors and uses them to construct a model of the space where it evolves. In this paper we focus on the case where several robots, each equipped with its own sensor, are distributed in a network and view the space from different vantage points. In particular, each robot is equipped with a stereo camera that allow the robots to extract visual landmarks and obtain relative measurements to them. We propose an algorithm that uses the measurements obtained by the robots to build a single accurate map of the environment. The map is represented by the three-dimensional position of the visual landmarks. In addition, we consider that each landmark is accompanied by a visual descriptor that encodes its visual appearance. The solution is based on a Rao-Blackwellized particle filter that estimates the paths of the robots and the position of the visual landmarks. The validity of our proposal is demonstrated by means of experiments with a team of real robots in a office-like indoor environment. PMID:22399930
Estimation of visual maps with a robot network equipped with vision sensors.
Gil, Arturo; Reinoso, Óscar; Ballesta, Mónica; Juliá, Miguel; Payá, Luis
2010-01-01
In this paper we present an approach to the Simultaneous Localization and Mapping (SLAM) problem using a team of autonomous vehicles equipped with vision sensors. The SLAM problem considers the case in which a mobile robot is equipped with a particular sensor, moves along the environment, obtains measurements with its sensors and uses them to construct a model of the space where it evolves. In this paper we focus on the case where several robots, each equipped with its own sensor, are distributed in a network and view the space from different vantage points. In particular, each robot is equipped with a stereo camera that allow the robots to extract visual landmarks and obtain relative measurements to them. We propose an algorithm that uses the measurements obtained by the robots to build a single accurate map of the environment. The map is represented by the three-dimensional position of the visual landmarks. In addition, we consider that each landmark is accompanied by a visual descriptor that encodes its visual appearance. The solution is based on a Rao-Blackwellized particle filter that estimates the paths of the robots and the position of the visual landmarks. The validity of our proposal is demonstrated by means of experiments with a team of real robots in a office-like indoor environment.
Origin of Peer Influence in Social Networks
NASA Astrophysics Data System (ADS)
Pinheiro, Flávio L.; Santos, Marta D.; Santos, Francisco C.; Pacheco, Jorge M.
2014-03-01
Social networks pervade our everyday lives: we interact, influence, and are influenced by our friends and acquaintances. With the advent of the World Wide Web, large amounts of data on social networks have become available, allowing the quantitative analysis of the distribution of information on them, including behavioral traits and fads. Recent studies of correlations among members of a social network, who exhibit the same trait, have shown that individuals influence not only their direct contacts but also friends' friends, up to a network distance extending beyond their closest peers. Here, we show how such patterns of correlations between peers emerge in networked populations. We use standard models (yet reflecting intrinsically different mechanisms) of information spreading to argue that empirically observed patterns of correlation among peers emerge naturally from a wide range of dynamics, being essentially independent of the type of information, on how it spreads, and even on the class of underlying network that interconnects individuals. Finally, we show that the sparser and clustered the network, the more far reaching the influence of each individual will be.
Social network modulation of reward-related signals
Fareri, Dominic S.; Niznikiewicz, Michael A.; Lee, Victoria K.; Delgado, Mauricio R.
2012-01-01
Everyday goals and experiences are often shared with others who may hold different places within our social networks. We investigated whether the experience of sharing a reward differs with respect to social network. Twenty human participants played a card guessing game for shared monetary outcomes with three partners: a computer, a confederate (out-of-network), and a friend (in-network). Participants subjectively rated the experience of sharing a reward more positively with their friend than the other partners. Neuroimaging results support participants’ subjective reports, as ventral striatal BOLD responses were more robust when sharing monetary gains with a friend, as compared to with the confederate or computer, suggesting a higher value for sharing with an in-network partner. Interestingly, ratings of social closeness co-varied with this activity, resulting in a significant partner × closeness interaction: exploratory analysis showed that only participants reporting higher levels of closeness demonstrated partner-related differences in striatal BOLD response. These results suggest that reward valuation in social contexts is sensitive to distinctions of social network, such that sharing positive experiences with in-network others may carry higher value. PMID:22745503
To friend or not to friend? Social networking and faculty perceptions of online professionalism.
Chretien, Katherine C; Farnan, Jeanne M; Greysen, S Ryan; Kind, Terry
2011-12-01
To assess faculty perceptions of professional boundaries and trainee-posted content on social networking sites (SNS). In June 2010, the Clerkship Directors in Internal Medicine conducted its annual survey of U.S. and Canadian member institutions. The survey included sections on demographics and social networking. The authors used descriptive statistics and tests of association to analyze the Likert scale responses and qualitatively analyzed the free-text responses. Of 110 institutional members, 82 (75%) responded to the survey. Of the 40 respondents who reported current or past SNS use, 21 (53%) reported receiving a "friend request" from a current student and 25 (63%) from a current resident. Of these, 4 (19%) accepted the student request and 12 (48%) accepted the resident request. Sixty-three of 80 (79%) felt it was inappropriate to send a friend request to a current student, 61 (76%) to accept a current student's request, 42 (53%) to become friends with a current resident, and 61 (81%) to become friends with a current patient. Becoming friends with a former student, former resident, or colleague was perceived as more appropriate. Younger respondents were less likely to deem specific student behaviors inappropriate (odds ratio [OR] 0.18-0.79; adjusted OR 0.12-0.86, controlling for respondents' sex, rank, and SNS use), although none reached statistical significance. Some internal medicine educators are using SNSs and interacting with trainees online. Their perceptions on the appropriateness of social networking behaviors provide some consensus for professional boundaries between faculty and trainees in the digital world.
Selfhout, Maarten; Burk, William; Branje, Susan; Denissen, Jaap; van Aken, Marcel; Meeus, Wim
2010-04-01
The current study focuses on the emergence of friendship networks among just-acquainted individuals, investigating the effects of Big Five personality traits on friendship selection processes. Sociometric nominations and self-ratings on personality traits were gathered from 205 late adolescents (mean age=19 years) at 5 time points during the first year of university. SIENA, a novel multilevel statistical procedure for social network analysis, was used to examine effects of Big Five traits on friendship selection. Results indicated that friendship networks between just-acquainted individuals became increasingly more cohesive within the first 3 months and then stabilized. Whereas individuals high on Extraversion tended to select more friends than those low on this trait, individuals high on Agreeableness tended to be selected more as friends. In addition, individuals tended to select friends with similar levels of Agreeableness, Extraversion, and Openness.
Urbanism, Neighborhood Context, and Social Networks.
Cornwell, Erin York; Behler, Rachel L
2015-09-01
Theories of urbanism suggest that the urban context erodes individuals' strong social ties with friends and family. Recent research has narrowed focus to the neighborhood context, emphasizing how localized structural disadvantage affects community-level cohesion and social capital. In this paper, we argue that neighborhood context also shapes social ties with friends and family- particularly for community-dwelling seniors. We hypothesize that neighborhood disadvantage, residential instability, and disorder restrict residents' abilities to cultivate close relationships with neighbors and non-neighbor friends and family. Using data from the National Social Life, Health, and Aging Project (NSHAP), we find that older adults who live in disadvantaged neighborhoods have smaller social networks. Neighborhood disadvantage is also associated with less close network ties and less frequent interaction - but only among men. Furthermore, residents of disordered neighborhoods have smaller networks and weaker ties. We urge scholars to pay greater attention to how neighborhood context contributes to disparities in network-based access to resources.
Urbanism, Neighborhood Context, and Social Networks
Cornwell, Erin York; Behler, Rachel L.
2017-01-01
Theories of urbanism suggest that the urban context erodes individuals’ strong social ties with friends and family. Recent research has narrowed focus to the neighborhood context, emphasizing how localized structural disadvantage affects community-level cohesion and social capital. In this paper, we argue that neighborhood context also shapes social ties with friends and family– particularly for community-dwelling seniors. We hypothesize that neighborhood disadvantage, residential instability, and disorder restrict residents’ abilities to cultivate close relationships with neighbors and non-neighbor friends and family. Using data from the National Social Life, Health, and Aging Project (NSHAP), we find that older adults who live in disadvantaged neighborhoods have smaller social networks. Neighborhood disadvantage is also associated with less close network ties and less frequent interaction – but only among men. Furthermore, residents of disordered neighborhoods have smaller networks and weaker ties. We urge scholars to pay greater attention to how neighborhood context contributes to disparities in network-based access to resources. PMID:28819338
Is a healthy city also an age-friendly city?
Jackisch, Josephine; Zamaro, Gianna; Green, Geoff; Huber, Manfred
2015-06-01
Healthy Ageing is an important focus of the European Healthy Cities Network and has been supported by WHO since 2003 as a key strategic topic, since 2010 in cooperation with the Global Network of Age-friendly Cities and Communities. Based on the methodology of realist evaluation, this article synthesizes qualitative evidence from 33 structured case studies (CS) from 32 WHO European Healthy Cities, 72 annual reports from Network cities and 71 quantitative responses to a General Evaluation Questionnaire. City cases are assigned to three clusters containing the eight domains of an age-friendly city proposed by WHO's Global Age-friendly City Guide published in 2007. The analysis of city's practice and efforts in this article takes stock of how cities have developed the institutional prerequisites and processes necessary for implementing age-friendly strategies, programmes and projects. A content analysis of the CS maps activities across age-friendly domains and illustrates how cities contribute to improving the social and physical environments of older people and enhance the health and social services provided by municipalities and their partners. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Hussain, Irfan; Santarnecchi, Emiliano; Leo, Andrea; Ricciardi, Emiliano; Rossi, Simone; Prattichizzo, Domenico
2017-07-01
The Supernumerary robotic limbs are a recently introduced class of wearable robots that, differently from traditional prostheses and exoskeletons, aim at adding extra effectors (i.e., arms, legs, or fingers) to the human user, rather than substituting or enhancing the natural ones. However, it is still undefined whether the use of supernumerary robotic limbs could specifically lead to neural modifications in brain dynamics. The illusion of owning the part of body has been already proven in many experimental observations, such as those relying on multisensory integration (e.g., rubber hand illusion), prosthesis and even on virtual reality. In this paper we present a description of a novel magnetic compatible supernumerary robotic finger together with preliminary observations from two functional magnetic resonance imaging (fMRI) experiments, in which brain activity was measured before and after a period of training with the robotic device, and during the use of the novel MRI-compatible version of the supernumerary robotic finger. Results showed that the usage of the MR-compatible robotic finger is safe and does not produce artifacts on MRI images. Moreover, the training with the supernumerary robotic finger recruits a network of motor-related cortical regions (i.e. primary and supplementary motor areas), hence the same motor network of a fully physiological voluntary motor gestures.
An evaluation of the distribution of sexual references among "Top 8" MySpace friends.
Moreno, Megan A; Brockman, Libby; Rogers, Cara B; Christakis, Dimitri A
2010-10-01
To evaluate whether online friends of adolescents who display sexual references on a social networking site also display references. The method used was content analysis. The result of this study was that adolescents who displayed explicit sexual references were more likely to have online friends who displayed references. Thus, social networking sites present new opportunities to investigate adolescent sexual behavior. Copyright © 2010 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
Social network, recovery attitudes and internal stigma among those with serious mental illness.
Cullen, Bernadette Am; Mojtabai, Ramin; Bordbar, Elahe; Everett, Anita; Nugent, Katie L; Eaton, William W
2017-08-01
Social network size and strength is an important determinant of overall health. This study describes the extent and strength of the social network among a sample of individuals with serious mental illness (SMI) and explores the relationship between an individual's social network and their experience of internal stigma and recovery attitudes. Over a 2-year period, consecutive new patients with SMI attending two community mental health clinics were recruited and interviewed using a comprehensive battery of assessments including assessment of internalized stigma, recovery attitudes and symptom severity. Among the 271 patients interviewed, social network size was small across all diagnostic categories. In adjusted results, the number of friends and support from relatives and friends was significantly related to the personal confidence and hope recovery attitude ( p < .05). The number of relatives and friends and support from relatives was significantly related to internalized stigma ( p < .05). Frequency of contact with relatives or friends was not related to either recovery factors or internalized stigma. There is a significant positive relationship between the size and perceived strength of an individual's social network and internalized stigma and some recovery attitudes. Clinical programs that address any of these factors could potentially improve outcomes for this population.
Effects of Social Support Network Size on Mortality Risk: Considerations by Diabetes Status.
Loprinzi, Paul D; Ford, M Allison
2018-05-01
Previous work demonstrates that social support is inversely associated with mortality risk. Less research, however, has examined the effects of the size of the social support network on mortality risk among those with and without diabetes, which was the purpose of this study. Data from the 1999-2008 National Health and Nutrition Examination Survey were used, with participants followed through 2011. This study included 1,412 older adults (≥60 years of age) with diabetes and 5,872 older adults without diabetes. The size of the social support network was assessed via self-report and reported as the number of participants' close friends. Among those without diabetes, various levels of social support network size were inversely associated with mortality risk. However, among those with diabetes, only those with a high social support network size (i.e., at least six close friends) had a reduced risk of all-cause mortality. That is, compared to those with zero close friends, those with diabetes who had six or more close friends had a 49% reduced risk of all-cause mortality (hazard ratio 0.51, 95% CI 0.27-0.94). To mitigate mortality risk, a greater social support network size may be needed for those with diabetes.
Teen Alcohol Use and Social Networks: The Contributions of Friend Influence and Friendship Selection
Cheadle, Jacob E; Walsemann, Katrina M; Goosby, Bridget J
2015-01-01
Background We evaluated the contributions of teen alcohol use to the formation and continuation of new and existing friendships while in turn estimating the influence of friend drinking on individuals’ regular use and heavy drinking. Method Longitudinal network analysis was used to assess the mutual influences between teen drinking and social networks among adolescents in two large Add Health schools where full network data was collected three times. Friendship processes were disaggregated into the formation of new friendships and the continuation of existing friendships in a joint model isolating friendship selection and friend influences. Results Friends have a modest influence on one another when selection is controlled. Selection is more complicated than prior studies suggest, and is only related to new friendships and not their duration in the largest school. Alcohol use predicts decreasing popularity in some cases, and popularity does not predict alcohol consumption. Conclusion Intervention efforts should continue pursuing strategies that mitigate negative peer influences. The development of socializing opportunities that facilitate relationship opportunities to select on healthy behaviors also appears promising. Future work preventing teen substance use should incorporate longitudinal network assessments to determine whether programs promote protective peer relationships in addition to how treatment effects diffuse through social networks. PMID:26692436
Cavallo, F; Aquilano, M; Bonaccorsi, M; Mannari, I; Carrozza, M C; Dario, P
2011-01-01
This paper aims to show the effectiveness of a (inter / multi)disciplinary team, based on the technology developers, elderly care organizations, and designers, in developing the ASTRO robotic system for domiciliary assistance to elderly people. The main issues presented in this work concern the improvement of robot's behavior by means of a smart sensor network able to share information with the robot for localization and navigation, and the design of the robot's appearance and functionalities by means of a substantial analysis of users' requirements and attitude to robotic technology to improve acceptability and usability.
Design and implementation of a software package to control a network of robotic observatories
NASA Astrophysics Data System (ADS)
Tuparev, G.; Nicolova, I.; Zlatanov, B.; Mihova, D.; Popova, I.; Hessman, F. V.
2006-09-01
We present a description of a reusable software package able to control a large, heterogeneous network of fully and semi-robotic observatories initially developed to run the MONET network of two 1.2 m telescopes. Special attention is given to the design of a robust, long-term observation scheduler which also allows the trading of observation time and facilities within various networks. The handling of the ``Phase I&II" project-development process, the time-accounting between complex organizational structures, and usability issues for making the package accessible not only to professional astronomers, but also to amateurs and high-school students is discussed. A simple RTML-based solution to link multiple networks is demonstrated.
Representation Learning of Logic Words by an RNN: From Word Sequences to Robot Actions
Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya
2017-01-01
An important characteristic of human language is compositionality. We can efficiently express a wide variety of real-world situations, events, and behaviors by compositionally constructing the meaning of a complex expression from a finite number of elements. Previous studies have analyzed how machine-learning models, particularly neural networks, can learn from experience to represent compositional relationships between language and robot actions with the aim of understanding the symbol grounding structure and achieving intelligent communicative agents. Such studies have mainly dealt with the words (nouns, adjectives, and verbs) that directly refer to real-world matters. In addition to these words, the current study deals with logic words, such as “not,” “and,” and “or” simultaneously. These words are not directly referring to the real world, but are logical operators that contribute to the construction of meaning in sentences. In human–robot communication, these words may be used often. The current study builds a recurrent neural network model with long short-term memory units and trains it to learn to translate sentences including logic words into robot actions. We investigate what kind of compositional representations, which mediate sentences and robot actions, emerge as the network's internal states via the learning process. Analysis after learning shows that referential words are merged with visual information and the robot's own current state, and the logical words are represented by the model in accordance with their functions as logical operators. Words such as “true,” “false,” and “not” work as non-linear transformations to encode orthogonal phrases into the same area in a memory cell state space. The word “and,” which required a robot to lift up both its hands, worked as if it was a universal quantifier. The word “or,” which required action generation that looked apparently random, was represented as an unstable space of the network's dynamical system. PMID:29311891
Representation Learning of Logic Words by an RNN: From Word Sequences to Robot Actions.
Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya
2017-01-01
An important characteristic of human language is compositionality. We can efficiently express a wide variety of real-world situations, events, and behaviors by compositionally constructing the meaning of a complex expression from a finite number of elements. Previous studies have analyzed how machine-learning models, particularly neural networks, can learn from experience to represent compositional relationships between language and robot actions with the aim of understanding the symbol grounding structure and achieving intelligent communicative agents. Such studies have mainly dealt with the words (nouns, adjectives, and verbs) that directly refer to real-world matters. In addition to these words, the current study deals with logic words, such as "not," "and," and "or" simultaneously. These words are not directly referring to the real world, but are logical operators that contribute to the construction of meaning in sentences. In human-robot communication, these words may be used often. The current study builds a recurrent neural network model with long short-term memory units and trains it to learn to translate sentences including logic words into robot actions. We investigate what kind of compositional representations, which mediate sentences and robot actions, emerge as the network's internal states via the learning process. Analysis after learning shows that referential words are merged with visual information and the robot's own current state, and the logical words are represented by the model in accordance with their functions as logical operators. Words such as "true," "false," and "not" work as non-linear transformations to encode orthogonal phrases into the same area in a memory cell state space. The word "and," which required a robot to lift up both its hands, worked as if it was a universal quantifier. The word "or," which required action generation that looked apparently random, was represented as an unstable space of the network's dynamical system.
ROS-IGTL-Bridge: an open network interface for image-guided therapy using the ROS environment.
Frank, Tobias; Krieger, Axel; Leonard, Simon; Patel, Niravkumar A; Tokuda, Junichi
2017-08-01
With the growing interest in advanced image-guidance for surgical robot systems, rapid integration and testing of robotic devices and medical image computing software are becoming essential in the research and development. Maximizing the use of existing engineering resources built on widely accepted platforms in different fields, such as robot operating system (ROS) in robotics and 3D Slicer in medical image computing could simplify these tasks. We propose a new open network bridge interface integrated in ROS to ensure seamless cross-platform data sharing. A ROS node named ROS-IGTL-Bridge was implemented. It establishes a TCP/IP network connection between the ROS environment and external medical image computing software using the OpenIGTLink protocol. The node exports ROS messages to the external software over the network and vice versa simultaneously, allowing seamless and transparent data sharing between the ROS-based devices and the medical image computing platforms. Performance tests demonstrated that the bridge could stream transforms, strings, points, and images at 30 fps in both directions successfully. The data transfer latency was <1.2 ms for transforms, strings and points, and 25.2 ms for color VGA images. A separate test also demonstrated that the bridge could achieve 900 fps for transforms. Additionally, the bridge was demonstrated in two representative systems: a mock image-guided surgical robot setup consisting of 3D slicer, and Lego Mindstorms with ROS as a prototyping and educational platform for IGT research; and the smart tissue autonomous robot surgical setup with 3D Slicer. The study demonstrated that the bridge enabled cross-platform data sharing between ROS and medical image computing software. This will allow rapid and seamless integration of advanced image-based planning/navigation offered by the medical image computing software such as 3D Slicer into ROS-based surgical robot systems.
Adaptive Control Parameters for Dispersal of Multi-Agent Mobile Ad Hoc Network (MANET) Swarms
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kurt Derr; Milos Manic
A mobile ad hoc network is a collection of independent nodes that communicate wirelessly with one another. This paper investigates nodes that are swarm robots with communications and sensing capabilities. Each robot in the swarm may operate in a distributed and decentralized manner to achieve some goal. This paper presents a novel approach to dynamically adapting control parameters to achieve mesh configuration stability. The presented approach to robot interaction is based on spring force laws (attraction and repulsion laws) to create near-optimal mesh like configurations. In prior work, we presented the extended virtual spring mesh (EVSM) algorithm for the dispersionmore » of robot swarms. This paper extends the EVSM framework by providing the first known study on the effects of adaptive versus static control parameters on robot swarm stability. The EVSM algorithm provides the following novelties: 1) improved performance with adaptive control parameters and 2) accelerated convergence with high formation effectiveness. Simulation results show that 120 robots reach convergence using adaptive control parameters more than twice as fast as with static control parameters in a multiple obstacle environment.« less
Yoo, Sung Jin; Park, Jin Bae; Choi, Yoon Ho
2008-10-01
In this paper, we propose a new robust output feedback control approach for flexible-joint electrically driven (FJED) robots via the observer dynamic surface design technique. The proposed method only requires position measurements of the FJED robots. To estimate the link and actuator velocity information of the FJED robots with model uncertainties, we develop an adaptive observer using self-recurrent wavelet neural networks (SRWNNs). The SRWNNs are used to approximate model uncertainties in both robot (link) dynamics and actuator dynamics, and all their weights are trained online. Based on the designed observer, the link position tracking controller using the estimated states is induced from the dynamic surface design procedure. Therefore, the proposed controller can be designed more simply than the observer backstepping controller. From the Lyapunov stability analysis, it is shown that all signals in a closed-loop adaptive system are uniformly ultimately bounded. Finally, the simulation results on a three-link FJED robot are presented to validate the good position tracking performance and robustness of the proposed control system against payload uncertainties and external disturbances.
Evolutionary Design of a Robotic Material Defect Detection System
NASA Technical Reports Server (NTRS)
Ballard, Gary; Howsman, Tom; Craft, Mike; ONeil, Daniel; Steincamp, Jim; Howell, Joe T. (Technical Monitor)
2002-01-01
During the post-flight inspection of SSME engines, several inaccessible regions must be disassembled to inspect for defects such as cracks, scratches, gouges, etc. An improvement to the inspection process would be the design and development of very small robots capable of penetrating these inaccessible regions and detecting the defects. The goal of this research was to utilize an evolutionary design approach for the robotic detection of these types of defects. A simulation and visualization tool was developed prior to receiving the hardware as a development test bed. A small, commercial off-the-shelf (COTS) robot was selected from several candidates as the proof of concept robot. The basic approach to detect the defects was to utilize Cadmium Sulfide (CdS) sensors to detect changes in contrast of an illuminated surface. A neural network, optimally designed utilizing a genetic algorithm, was employed to detect the presence of the defects (cracks). By utilization of the COTS robot and US sensors, the research successfully demonstrated that an evolutionarily designed neural network can detect the presence of surface defects.
Zhong, Xungao; Zhong, Xunyu; Peng, Xiafu
2013-10-08
In this paper, a global-state-space visual servoing scheme is proposed for uncalibrated model-independent robotic manipulation. The scheme is based on robust Kalman filtering (KF), in conjunction with Elman neural network (ENN) learning techniques. The global map relationship between the vision space and the robotic workspace is learned using an ENN. This learned mapping is shown to be an approximate estimate of the Jacobian in global space. In the testing phase, the desired Jacobian is arrived at using a robust KF to improve the ENN learning result so as to achieve robotic precise convergence of the desired pose. Meanwhile, the ENN weights are updated (re-trained) using a new input-output data pair vector (obtained from the KF cycle) to ensure robot global stability manipulation. Thus, our method, without requiring either camera or model parameters, avoids the corrupted performances caused by camera calibration and modeling errors. To demonstrate the proposed scheme's performance, various simulation and experimental results have been presented using a six-degree-of-freedom robotic manipulator with eye-in-hand configurations.
NASA Astrophysics Data System (ADS)
Serbu, Sabina; Rivière, Étienne; Felber, Pascal
The emergence of large-scale distributed applications based on many-to-many communication models, e.g., broadcast and decentralized group communication, has an important impact on the underlying layers, notably the Internet routing infrastructure. To make an effective use of network resources, protocols should both limit the stress (amount of messages) on each infrastructure entity like routers and links, and balance as much as possible the load in the network. Most protocols use application-level metrics such as delays to improve efficiency of content dissemination or routing, but the extend to which such application-centric optimizations help reduce and balance the load imposed to the infrastructure is unclear. In this paper, we elaborate on the design of such network-friendly protocols and associated metrics. More specifically, we investigate random-based gossip dissemination. We propose and evaluate different ways of making this representative protocol network-friendly while keeping its desirable properties (robustness and low delays). Simulations of the proposed methods using synthetic and real network topologies convey and compare their abilities to reduce and balance the load while keeping good performance.
Milot, Marie-Helene; Hamel, Mathieu; Provost, Philippe-Olivier; Bernier-Ouellet, Julien; Dupuis, Maxime; Letourneau, Dominic; Briere, Simon; Michaud, Francois
2016-08-01
Stroke is one of the leading causes of disability worldwide. Consequently, many stroke survivors exhibit difficulties undergoing voluntary movement in their affected upper limb, compromising their functional performance and level of independence. To minimize the negative impact of stroke disabilities, exercises are recognized as a key element in post-stroke rehabilitation. In order to provide the practice of exercises in a uniform and controlled manner as well as increasing the efficiency of therapists' interventions, robotic training has been found, and continues to prove itself, as an innovative intervention for post-stroke rehabilitation. However, the complexity as well as the limited degrees of freedom and workspace of currently commercially available robots can limit their use in clinical settings. Up to now, user-friendly robots covering a sufficiently large workspace for training of the upper limb in its full range of motion are lacking. This paper presents the design and implementation of ERA, an upper-limb 3-DOF force-controlled exerciser robot, which presents a workspace covering the entire range of motion of the upper limb. The ERA robot provides 3D reaching movements in a haptic virtual environment. A description of the hardware and software components of the ERA robot is also presented along with a demonstration of its capabilities in one of the three operational modes that were developed.
Soft Robotic Manipulator for Improving Dexterity in Minimally Invasive Surgery.
Diodato, Alessandro; Brancadoro, Margherita; De Rossi, Giacomo; Abidi, Haider; Dall'Alba, Diego; Muradore, Riccardo; Ciuti, Gastone; Fiorini, Paolo; Menciassi, Arianna; Cianchetti, Matteo
2018-02-01
Combining the strengths of surgical robotics and minimally invasive surgery (MIS) holds the potential to revolutionize surgical interventions. The MIS advantages for the patients are obvious, but the use of instrumentation suitable for MIS often translates in limiting the surgeon capabilities (eg, reduction of dexterity and maneuverability and demanding navigation around organs). To overcome these shortcomings, the application of soft robotics technologies and approaches can be beneficial. The use of devices based on soft materials is already demonstrating several advantages in all the exploitation areas where dexterity and safe interaction are needed. In this article, the authors demonstrate that soft robotics can be synergistically used with traditional rigid tools to improve the robotic system capabilities and without affecting the usability of the robotic platform. A bioinspired soft manipulator equipped with a miniaturized camera has been integrated with the Endoscopic Camera Manipulator arm of the da Vinci Research Kit both from hardware and software viewpoints. Usability of the integrated system has been evaluated with nonexpert users through a standard protocol to highlight difficulties in controlling the soft manipulator. This is the first time that an endoscopic tool based on soft materials has been integrated into a surgical robot. The soft endoscopic camera can be easily operated through the da Vinci Research Kit master console, thus increasing the workspace and the dexterity, and without limiting intuitive and friendly use.
Tobis, Sławomir; Cylkowska-Nowak, Mirosława; Wieczorowska-Tobis, Katarzyna; Pawlaczyk, Mariola; Suwalska, Aleksandra
2017-01-01
The question arises how recent developments in robotics can contribute to the care for older people. The study is part of the EU-funded ENRICHME project. The aim of the study was to investigate opinions of occupational therapy students (OTS), as future professional caregivers, on the use of robots in care for older people. It included 26 OTS from Poznan University of Medical Sciences. To collect data, the Users' Needs, Requirements, and Abilities Questionnaire (UNRAQ) was developed. OTS perceived the robot as "a useful device" and "an assistant" rather than "a companion" ( p < 0.01). In their opinion, the most important functions of the robot were related to health aspects (emergency alarms, health parameters monitoring, physical activity and memory training, and reminders about medication, drinks, etc.), scored positively by 23-26 OTS. Functions such as mood detection, encouraging to contact with friends, and monitoring of food consumption were accepted by 16-17 OTS. Two statements concerning social functions (accompanying in everyday activities and decreasing the sense of loneliness) were rated positively by less the than half of the participants. A module concerning technology use, including robotics, should constitute an important part of the curricula of both academic and continuous education of OTS.
Mobile Robot Navigation and Obstacle Avoidance in Unstructured Outdoor Environments
2017-12-01
to pull information from the network, it subscribes to a specific topic and is able to receive the messages that are published to that topic. In order...total artificial potential field is characterized “as the sum of an attractive potential pulling the robot toward the goal…and a repulsive potential...of robot laser_max = 20; % robot laser view horizon goaldist = 0.5; % distance metric for reaching goal goali = 1
Cooperative system and method using mobile robots for testing a cooperative search controller
Byrne, Raymond H.; Harrington, John J.; Eskridge, Steven E.; Hurtado, John E.
2002-01-01
A test system for testing a controller provides a way to use large numbers of miniature mobile robots to test a cooperative search controller in a test area, where each mobile robot has a sensor, a communication device, a processor, and a memory. A method of using a test system provides a way for testing a cooperative search controller using multiple robots sharing information and communicating over a communication network.
MONET: a MOnitoring NEtwork of Telescopes
NASA Astrophysics Data System (ADS)
Hessman, F. V.; Beuermann, K.
2002-01-01
MONET is a planned network of two 1m-class robotic telescopes which will be used for various photometric monitoring projects -- variable stars, planet searches, AGN's, GRB's -- as well as by school children in Germany and over the world. The two host partners, the Univ. of Texas' McDonald Observatory and the South African Astronomical Observatory, will operate the telescopes in exchange for observing time on the network. MONET will be one of the first robotic telescope networks offering 1-m class telescopes, complete coverage of the sky, good longitude coverage for long observing sequences on objects near the celestial equator, and a heavy educational emphasis.
Biologically inspired computation and learning in Sensorimotor Systems
NASA Astrophysics Data System (ADS)
Lee, Daniel D.; Seung, H. S.
2001-11-01
Networking systems presently lack the ability to intelligently process the rich multimedia content of the data traffic they carry. Endowing artificial systems with the ability to adapt to changing conditions requires algorithms that can rapidly learn from examples. We demonstrate the application of such learning algorithms on an inexpensive quadruped robot constructed to perform simple sensorimotor tasks. The robot learns to track a particular object by discovering the salient visual and auditory cues unique to that object. The system uses a convolutional neural network that automatically combines color, luminance, motion, and auditory information. The weights of the networks are adjusted using feedback from a teacher to reflect the reliability of the various input channels in the surrounding environment. Additionally, the robot is able to compensate for its own motion by adapting the parameters of a vestibular ocular reflex system.
NASA Astrophysics Data System (ADS)
Liu, Xiaolin; Li, Lanfei; Sun, Hanxu
2017-12-01
Spherical flying robot can perform various tasks in the complex and varied environment to reduce labor costs. However, it is difficult to guarantee the stability of the spherical flying robot in the case of strong coupling and time-varying disturbance. In this paper, an artificial neural network controller (ANNC) based on MPSO-BFGS hybrid optimization algorithm is proposed. The MPSO algorithm is used to optimize the initial weights of the controller to avoid the local optimal solution. The BFGS algorithm is introduced to improve the convergence ability of the network. We use Lyapunov method to analyze the stability of ANNC. The controller is simulated under the condition of nonlinear coupling disturbance. The experimental results show that the proposed controller can obtain the expected value in shoter time compared with the other considered methods.
Arash: A social robot buddy to support children with cancer in a hospital environment.
Meghdari, Ali; Shariati, Azadeh; Alemi, Minoo; Vossoughi, Gholamreza R; Eydi, Abdollah; Ahmadi, Ehsan; Mozafari, Behrad; Amoozandeh Nobaveh, Ali; Tahami, Reza
2018-06-01
This article presents the thorough design procedure, specifications, and performance of a mobile social robot friend Arash for educational and therapeutic involvement of children with cancer based on their interests and needs. Our research focuses on employing Arash in a pediatric hospital environment to entertain, assist, and educate children with cancer who suffer from physical pain caused by both the disease and its treatment process. Since cancer treatment causes emotional distress, which can reduce the efficiency of medications, using social robots to interact with children with cancer in a hospital environment could decrease this distress, thereby improving the effectiveness of their treatment. Arash is a 15 degree-of-freedom low-cost humanoid mobile robot buddy, carefully designed with appropriate measures and developed to interact with children ages 5-12 years old. The robot has five physical subsystems: the head, arms, torso, waist, and mobile-platform. The robot's final appearance is a significant novel concept; since it was selected based on a survey taken from 50 children with chronic diseases at three pediatric hospitals in Tehran, Iran. Founded on these measures and desires, Arash was designed, built, improved, and enhanced to operate successfully in pediatric cancer hospitals. Two experiments were devised to evaluate the children's level of acceptance and involvement with the robot, assess their feelings about it, and measure how much the robot was similar to the favored conceptual sketch. Both experiments were conducted in the form of storytelling and appearance/performance evaluations. The obtained results confirm high engagement and interest of pediatric cancer patients with the constructed robot.
Rare Neural Correlations Implement Robotic Conditioning with Delayed Rewards and Disturbances
Soltoggio, Andrea; Lemme, Andre; Reinhart, Felix; Steil, Jochen J.
2013-01-01
Neural conditioning associates cues and actions with following rewards. The environments in which robots operate, however, are pervaded by a variety of disturbing stimuli and uncertain timing. In particular, variable reward delays make it difficult to reconstruct which previous actions are responsible for following rewards. Such an uncertainty is handled by biological neural networks, but represents a challenge for computational models, suggesting the lack of a satisfactory theory for robotic neural conditioning. The present study demonstrates the use of rare neural correlations in making correct associations between rewards and previous cues or actions. Rare correlations are functional in selecting sparse synapses to be eligible for later weight updates if a reward occurs. The repetition of this process singles out the associating and reward-triggering pathways, and thereby copes with distal rewards. The neural network displays macro-level classical and operant conditioning, which is demonstrated in an interactive real-life human-robot interaction. The proposed mechanism models realistic conditioning in humans and animals and implements similar behaviors in neuro-robotic platforms. PMID:23565092
Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi
2015-01-01
Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.
Zhang, Bin; Wang, Yuechao; Li, Hongyi
2015-01-01
Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579
ERIC Educational Resources Information Center
Lonardo, Robert A.; Giordano, Peggy C.; Longmore, Monica A.; Manning, Wendy D.
2009-01-01
Adolescent networks include parents, friends, and romantic partners, but research on the social learning mechanisms related to delinquency has not typically examined the characteristics of all three domains simultaneously. Analyses draw on data from the Toledo Adolescent Relationships Study (n = 957), and our analytic sample contains 51% male and…
Peer Network Overlap in Twin, Sibling, and Friend Dyads
ERIC Educational Resources Information Center
McGuire, Shirley; Segal, Nancy L.
2013-01-01
Research suggests that sibling–peer connections are important for understanding adolescent problem behaviors. Using a novel behavioral genetic design, the current study investigated peer network overlap in 300 child–child pairs (aged 7-13 years) in 5 dyad types: monozygotic (MZ), dizygotic twins, full siblings (FSs), friend pairs, and virtual…
A Decentralized Framework for Multi-Agent Robotic Systems
2018-01-01
Over the past few years, decentralization of multi-agent robotic systems has become an important research area. These systems do not depend on a central control unit, which enables the control and assignment of distributed, asynchronous and robust tasks. However, in some cases, the network communication process between robotic agents is overlooked, and this creates a dependency for each agent to maintain a permanent link with nearby units to be able to fulfill its goals. This article describes a communication framework, where each agent in the system can leave the network or accept new connections, sending its information based on the transfer history of all nodes in the network. To this end, each agent needs to comply with four processes to participate in the system, plus a fifth process for data transfer to the nearest nodes that is based on Received Signal Strength Indicator (RSSI) and data history. To validate this framework, we use differential robotic agents and a monitoring agent to generate a topological map of an environment with the presence of obstacles. PMID:29389849
Lonardo, Robert A; Giordano, Peggy C; Longmore, Monica A; Manning, Wendy D
2009-03-01
Adolescent networks include parents, friends, and romantic partners, but research on the social learning mechanisms related to delinquency has not typically examined the characteristics of all three domains simultaneously. Analyses draw on data from the Toledo Adolescent Relationships Study (n = 957), and our analytic sample contains 51% male and 49% female as well as 69% white, 24% African-American, and 7% Latino respondents. Parents,' peers,' and partners' deviance are each related to respondents' delinquency, and affiliation with a greater number of deviant networks is associated with higher self-reported involvement. Analyses that consider enmeshment type indicate that those with both above average romantic partner and friend delinquency report especially high levels of self-reported involvement. In all comparisons, adolescents with deviant romantic partners are more delinquent than those youths with more prosocial partners, regardless of friends' and parents' behavior. Findings highlight the importance of capturing the adolescent's entire network of affiliations, rather than viewing these in isolation, and suggest the need for additional research on romantic partner influences on delinquent behavior and other adolescent outcomes.
[Digital imaging and robotics in endoscopic surgery].
Go, P M
1998-05-23
The introduction of endoscopical surgery has among other things influenced technical developments in surgery. Owing to digitalisation, major progress will be made in imaging and in the sophisticated technology sometimes called robotics. Digital storage makes the results of imaging diagnostics (e.g. the results of radiological examination) suitable for transmission via video conference systems for telediagnostic purposes. The availability of digital video technique renders possible the processing, storage and retrieval of moving images as well. During endoscopical operations use may be made of a robot arm which replaces the camera man. The arm does not grow tired and provides a stable image. The surgeon himself can operate or address the arm and it can remember fixed image positions to which it can return if ordered to do so. The next step is to carry out surgical manipulations via a robot arm. This may make operations more patient-friendly. A robot arm can also have remote control: telerobotics. At the Internet site of this journal a number of supplements to this article can be found, for instance three-dimensional (3D) illustrations (which is the purpose of the 3D spectacles enclosed with this issue) and a quiz (http:@appendix.niwi. knaw.nl).
Comparison Analysis among Large Amount of SNS Sites
NASA Astrophysics Data System (ADS)
Toriumi, Fujio; Yamamoto, Hitoshi; Suwa, Hirohiko; Okada, Isamu; Izumi, Kiyoshi; Hashimoto, Yasuhiro
In recent years, application of Social Networking Services (SNS) and Blogs are growing as new communication tools on the Internet. Several large-scale SNS sites are prospering; meanwhile, many sites with relatively small scale are offering services. Such small-scale SNSs realize small-group isolated type of communication while neither mixi nor MySpace can do that. However, the studies on SNS are almost about particular large-scale SNSs and cannot analyze whether their results apply for general features or for special characteristics on the SNSs. From the point of view of comparison analysis on SNS, comparison with just several types of those cannot reach a statistically significant level. We analyze many SNS sites with the aim of classifying them by using some approaches. Our paper classifies 50,000 sites for small-scale SNSs and gives their features from the points of network structure, patterns of communication, and growth rate of SNS. The result of analysis for network structure shows that many SNS sites have small-world attribute with short path lengths and high coefficients of their cluster. Distribution of degrees of the SNS sites is close to power law. This result indicates the small-scale SNS sites raise the percentage of users with many friends than mixi. According to the analysis of their coefficients of assortativity, those SNS sites have negative values of assortativity, and that means users with high degree tend to connect users with small degree. Next, we analyze the patterns of user communication. A friend network of SNS is explicit while users' communication behaviors are defined as an implicit network. What kind of relationships do these networks have? To address this question, we obtain some characteristics of users' communication structure and activation patterns of users on the SNS sites. By using new indexes, friend aggregation rate and friend coverage rate, we show that SNS sites with high value of friend coverage rate activate diary postings and their comments. Besides, they become activated when hub users with high degree do not behave actively on the sites with high value of friend aggregation rate and high value of friend coverage rate. On the other hand, activation emerges when hub users behave actively on the sites with low value of friend aggregation rate and high value of friend coverage rate. Finally, we observe SNS sites which are increasing the number of users considerably, from the viewpoint of network structure, and extract characteristics of high growth SNS sites. As a result of discrimination on the basis of the decision tree analysis, we can recognize the high growth SNS sites with a high degree of accuracy. Besides, this approach suggests mixi and the other small-scale SNS sites have different character trait.
RTML: remote telescope markup language and you
NASA Astrophysics Data System (ADS)
Hessman, F. V.
2001-12-01
In order to coordinate the use of robotic and remotely operated telescopes in networks -- like Göttingen's MOnitoring NEtwork of Telescopes (MONET) -- a standard format for the exchange of observing requests and reports is needed. I describe the benefits of Remote Telescope Markup Language (RTML), an XML-based protocol originally developed by the Hands-On Universe Project, which is being used and further developed by several robotic telescope projects and firms.
Integration of Hierarchical Goal Network Planning and Autonomous Path Planning
2016-03-01
Conference on Robotics and Automation (ICRA); 2010 May 3– 7; Anchorage, AK. p. 2902–2908. 4. Ayan NF, Kuter U, Yaman F, Goldman RP. Hotride...DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release; distribution unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT Automated planning has...world robotic systems. This report documents work to integrate a hierarchical goal network planning algorithm with low-level path planning. The system
Zaharakis, Nikola; Mason, Michael J; Mennis, Jeremy; Light, John; Rusby, Julie C; Westling, Erika; Crewe, Stephanie; Flay, Brian R; Way, Thomas
2018-02-01
The school environment is extremely salient in young adolescents' lives. Adolescents who have unfavorable attitudes toward school and teachers are at elevated risk for dropping out of school and engaging in behavioral health risks. Peer network health-a summation of the positive and negative behaviors in which one's close friend group engages-may be one way by which attitudes toward school exert influence on youth substance use. Utilizing a sample of 248 primarily African-American young urban adolescents, we tested a moderated mediation model to determine if the indirect effect of attitude to school on cannabis involvement through peer network health was conditioned on gender. Attitude toward school measured at baseline was the predictor (X), peer network health measured at 6 months was the mediator (M), cannabis involvement (including use, offers to use, and refusals to use) measured at 24 months was the outcome (Y), and gender was the moderator (W). Results indicated that negative attitudes toward school were indirectly associated with increased cannabis involvement through peer network health. This relationship was not moderated by gender. Adolescents in our sample with negative attitudes toward school were more likely to receive more offers to use cannabis and to use cannabis more frequently through the perceived health behaviors of their close friends. Implications from these results point to opportunities to leverage the dynamic associations among school experiences, friends, and cannabis involvement, such as offers and use.
NASA Astrophysics Data System (ADS)
Rahman, Md. Mozasser; Ikeura, Ryojun; Mizutani, Kazuki
In the near future many aspects of our lives will be encompassed by tasks performed in cooperation with robots. The application of robots in home automation, agricultural production and medical operations etc. will be indispensable. As a result robots need to be made human-friendly and to execute tasks in cooperation with humans. Control systems for such robots should be designed to work imitating human characteristics. In this study, we have tried to achieve these goals by means of controlling a simple one degree-of-freedom cooperative robot. Firstly, the impedance characteristic of the human arm in a cooperative task is investigated. Then, this characteristic is implemented to control a robot in order to perform cooperative task with humans. A human followed the motion of an object, which is moved through desired trajectories. The motion is actuated by the linear motor of the one degree-of-freedom robot system. Trajectories used in the experiments of this method were minimum jerk (the rate of change of acceleration) trajectory, which was found during human and human cooperative task and optimum for muscle movement. As the muscle is mechanically analogous to a spring-damper system, a simple second-order equation is used as models for the arm dynamics. In the model, we considered mass, stiffness and damping factor. Impedance parameter is calculated from the position and force data obtained from the experiments and based on the “Estimation of Parametric Model”. Investigated impedance characteristic of human arm is then implemented to control a robot, which performed cooperative task with human. It is observed that the proposed control methodology has given human like movements to the robot for cooperating with human.
Autonomous caregiver following robotic wheelchair
NASA Astrophysics Data System (ADS)
Ratnam, E. Venkata; Sivaramalingam, Sethurajan; Vignesh, A. Sri; Vasanth, Elanthendral; Joans, S. Mary
2011-12-01
In the last decade, a variety of robotic/intelligent wheelchairs have been proposed to meet the need in aging society. Their main research topics are autonomous functions such as moving toward some goals while avoiding obstacles, or user-friendly interfaces. Although it is desirable for wheelchair users to go out alone, caregivers often accompany them. Therefore we have to consider not only autonomous functions and user interfaces but also how to reduce caregivers' load and support their activities in a communication aspect. From this point of view, we have proposed a robotic wheelchair moving with a caregiver side by side based on the MATLAB process. In this project we discussing about robotic wheel chair to follow a caregiver by using a microcontroller, Ultrasonic sensor, keypad, Motor drivers to operate robot. Using camera interfaced with the DM6437 (Davinci Code Processor) image is captured. The captured image are then processed by using image processing technique, the processed image are then converted into voltage levels through MAX 232 level converter and given it to the microcontroller unit serially and ultrasonic sensor to detect the obstacle in front of robot. In this robot we have mode selection switch Automatic and Manual control of robot, we use ultrasonic sensor in automatic mode to find obstacle, in Manual mode to use the keypad to operate wheel chair. In the microcontroller unit, c language coding is predefined, according to this coding the robot which connected to it was controlled. Robot which has several motors is activated by using the motor drivers. Motor drivers are nothing but a switch which ON/OFF the motor according to the control given by the microcontroller unit.
NASA Astrophysics Data System (ADS)
Choo, Seongho; Li, Vitaly; Choi, Dong Hee; Jung, Gi Deck; Park, Hong Seong; Ryuh, Youngsun
2005-12-01
On developing the personal robot system presently, the internal architecture is every module those occupy separated functions are connected through heterogeneous network system. This module-based architecture supports specialization and division of labor at not only designing but also implementation, as an effect of this architecture, it can reduce developing times and costs for modules. Furthermore, because every module is connected among other modules through network systems, we can get easy integrations and synergy effect to apply advanced mutual functions by co-working some modules. In this architecture, one of the most important technologies is the network middleware that takes charge communications among each modules connected through heterogeneous networks systems. The network middleware acts as the human nerve system inside of personal robot system; it relays, transmits, and translates information appropriately between modules that are similar to human organizations. The network middleware supports various hardware platform, heterogeneous network systems (Ethernet, Wireless LAN, USB, IEEE 1394, CAN, CDMA-SMS, RS-232C). This paper discussed some mechanisms about our network middleware to intercommunication and routing among modules, methods for real-time data communication and fault-tolerant network service. There have designed and implemented a layered network middleware scheme, distributed routing management, network monitoring/notification technology on heterogeneous networks for these goals. The main theme is how to make routing information in our network middleware. Additionally, with this routing information table, we appended some features. Now we are designing, making a new version network middleware (we call 'OO M/W') that can support object-oriented operation, also are updating program sources itself for object-oriented architecture. It is lighter, faster, and can support more operation systems and heterogeneous network systems, but other general purposed middlewares like CORBA, UPnP, etc. can support only one network protocol or operating system.
Bohnert, Amy S B; German, Danielle; Knowlton, Amy R; Latkin, Carl A
2010-03-01
Social support is a multi-dimensional construct that is important to drug use cessation. The present study identified types of supportive friends among the social network members in a community-based sample and examined the relationship of supporter-type classes with supporter, recipient, and supporter-recipient relationship characteristics. We hypothesized that the most supportive network members and their support recipients would be less likely to be current heroin/cocaine users. Participants (n=1453) were recruited from low-income neighborhoods with a high prevalence of drug use. Participants identified their friends via a network inventory, and all nominated friends were included in a latent class analysis and grouped based on their probability of providing seven types of support. These latent classes were included as the dependent variable in a multi-level regression of supporter drug use, recipient drug use, and other characteristics. The best-fitting latent class model identified five support patterns: friends who provided Little/No Support, Low/Moderate Support, High Support, Socialization Support, and Financial Support. In bivariate models, friends in the High, Low/Moderate, and Financial Support were less likely to use heroin or cocaine and had less conflict with and were more trusted by the support recipient than friends in the Low/No Support class. Individuals with supporters in those same support classes compared to the Low/No Support class were less likely to use heroin or cocaine, or to be homeless or female. Multivariable models suggested similar trends. Those with current heroin/cocaine use were less likely to provide or receive comprehensive support from friends. Published by Elsevier Ireland Ltd.
Moriarty, John; McVicar, Duncan; Higgins, Kathryn
2016-08-01
Peer effects in adolescent cannabis are difficult to estimate, due in part to the lack of appropriate data on behaviour and social ties. This paper exploits survey data that have many desirable properties and have not previously been used for this purpose. The data set, collected from teenagers in three annual waves from 2002 to 2004 contains longitudinal information about friendship networks within schools (N = 5020). We exploit these data on network structure to estimate peer effects on adolescents from their nominated friends within school using two alternative approaches to identification. First, we present a cross-sectional instrumental variable (IV) estimate of peer effects that exploits network structure at the second degree, i.e. using information on friends of friends who are not themselves ego's friends to instrument for the cannabis use of friends. Second, we present an individual fixed effects estimate of peer effects using the full longitudinal structure of the data. Both innovations allow a greater degree of control for correlated effects than is commonly the case in the substance-use peer effects literature, improving our chances of obtaining estimates of peer effects than can be plausibly interpreted as causal. Both estimates suggest positive peer effects of non-trivial magnitude, although the IV estimate is imprecise. Furthermore, when we specify identical models with behaviour and characteristics of randomly selected school peers in place of friends', we find effectively zero effect from these 'placebo' peers, lending credence to our main estimates. We conclude that cross-sectional data can be used to estimate plausible positive peer effects on cannabis use where network structure information is available and appropriately exploited. Copyright © 2016 Elsevier Ltd. All rights reserved.
A mobile robots experimental environment with event-based wireless communication.
Guinaldo, María; Fábregas, Ernesto; Farias, Gonzalo; Dormido-Canto, Sebastián; Chaos, Dictino; Sánchez, José; Dormido, Sebastián
2013-07-22
An experimental platform to communicate between a set of mobile robots through a wireless network has been developed. The mobile robots get their position through a camera which performs as sensor. The video images are processed in a PC and a Waspmote card sends the corresponding position to each robot using the ZigBee standard. A distributed control algorithm based on event-triggered communications has been designed and implemented to bring the robots into the desired formation. Each robot communicates to its neighbors only at event times. Furthermore, a simulation tool has been developed to design and perform experiments with the system. An example of usage is presented.
Neural joint control for Space Shuttle Remote Manipulator System
NASA Technical Reports Server (NTRS)
Atkins, Mark A.; Cox, Chadwick J.; Lothers, Michael D.; Pap, Robert M.; Thomas, Charles R.
1992-01-01
Neural networks are being used to control a robot arm in a telerobotic operation. The concept uses neural networks for both joint and inverse kinematics in a robotic control application. An upper level neural network is trained to learn inverse kinematic mappings. The output, a trajectory, is then fed to the Decentralized Adaptive Joint Controllers. This neural network implementation has shown that the controlled arm recovers from unexpected payload changes while following the reference trajectory. The neural network-based decentralized joint controller is faster, more robust and efficient than conventional approaches. Implementations of this architecture are discussed that would relax assumptions about dynamics, obstacles, and heavy loads. This system is being developed to use with the Space Shuttle Remote Manipulator System.
Rulison, Kelly L.; Gest, Scott D.; Loken, Eric
2013-01-01
We examined three interrelated questions: (1) Who selects physically aggressive friends?; (2) Are physically aggressive adolescents influential?; and (3) Who is susceptible to influence from these friends? Using stochastic actor-based modeling, we tested our hypotheses using a sample of 480 adolescents (ages 11–13) who were followed across four assessments (fall and spring of 6th and 7th grade). After controlling for other factors that drive network and behavioral dynamics, we found that physically aggressive adolescents were attractive as friends, physically aggressive adolescents and girls were more likely to select physically aggressive friends, and peer-rejected adolescents were less likely to select physically aggressive friends. There was an overall peer influence effect, but gender and social status were not significant moderators of influence. PMID:24068860
Social network profiles as information sources for adolescents' offline relations.
Courtois, Cédric; All, Anissa; Vanwynsberghe, Hadewijch
2012-06-01
This article presents the results of a study concerning the use of online profile pages by adolescents to know more about "offline" friends and acquaintances. Previous research has indicated that social networking sites (SNSs) are used to gather information on new online contacts. However, several studies have demonstrated a substantial overlap between offline and online social networks. Hence, we question whether online connections are meaningful in gathering information on offline friends and acquaintances. First, the results indicate that a combination of passive uncertainty reduction (monitoring a target's profile) and interactive uncertainty reduction (communication through the target's profile) explains a considerable amount of variance in the level of uncertainty about both friends and acquaintances. More specifically, adolescents generally get to know much more about their acquaintances. Second, the results of online uncertainty reduction positively affect the degree of self-disclosure, which is imperative in building a solid friend relation. Further, we find that uncertainty reduction strategies positively mediate the effect of social anxiety on the level of certainty about friends. This implies that socially anxious teenagers benefit from SNSs by getting the conditions right to build a more solid relation with their friends. Hence, we conclude that SNSs play a substantial role in today's adolescents' everyday interpersonal communication.
PR-PR: Cross-Platform Laboratory Automation System
DOE Office of Scientific and Technical Information (OSTI.GOV)
Linshiz, G; Stawski, N; Goyal, G
To enable protocol standardization, sharing, and efficient implementation across laboratory automation platforms, we have further developed the PR-PR open-source high-level biology-friendly robot programming language as a cross-platform laboratory automation system. Beyond liquid-handling robotics, PR-PR now supports microfluidic and microscopy platforms, as well as protocol translation into human languages, such as English. While the same set of basic PR-PR commands and features are available for each supported platform, the underlying optimization and translation modules vary from platform to platform. Here, we describe these further developments to PR-PR, and demonstrate the experimental implementation and validation of PR-PR protocols for combinatorial modified Goldenmore » Gate DNA assembly across liquid-handling robotic, microfluidic, and manual platforms. To further test PR-PR cross-platform performance, we then implement and assess PR-PR protocols for Kunkel DNA mutagenesis and hierarchical Gibson DNA assembly for microfluidic and manual platforms.« less
PR-PR: cross-platform laboratory automation system.
Linshiz, Gregory; Stawski, Nina; Goyal, Garima; Bi, Changhao; Poust, Sean; Sharma, Monica; Mutalik, Vivek; Keasling, Jay D; Hillson, Nathan J
2014-08-15
To enable protocol standardization, sharing, and efficient implementation across laboratory automation platforms, we have further developed the PR-PR open-source high-level biology-friendly robot programming language as a cross-platform laboratory automation system. Beyond liquid-handling robotics, PR-PR now supports microfluidic and microscopy platforms, as well as protocol translation into human languages, such as English. While the same set of basic PR-PR commands and features are available for each supported platform, the underlying optimization and translation modules vary from platform to platform. Here, we describe these further developments to PR-PR, and demonstrate the experimental implementation and validation of PR-PR protocols for combinatorial modified Golden Gate DNA assembly across liquid-handling robotic, microfluidic, and manual platforms. To further test PR-PR cross-platform performance, we then implement and assess PR-PR protocols for Kunkel DNA mutagenesis and hierarchical Gibson DNA assembly for microfluidic and manual platforms.
ERIC Educational Resources Information Center
Kvenild, Cassandra; Shepherd, Craig E.; Smith, Shannon M.; Thielk, Emma
2017-01-01
In a climate of increased interest in science, technology, engineering, and math (STEM), school libraries have unique opportunities to grow collections and cultivate partnerships in the sciences. At the federal level and in many states, STEM initiatives encourage hands-on exposure to technologies and open the door for student-led discovery of…
Karakasiliotis, K; Thandiackal, R; Melo, K; Horvat, T; Mahabadi, N K; Tsitkov, S; Cabelguen, J M; Ijspeert, A J
2016-06-01
Robots are increasingly used as scientific tools to investigate animal locomotion. However, designing a robot that properly emulates the kinematic and dynamic properties of an animal is difficult because of the complexity of musculoskeletal systems and the limitations of current robotics technology. Here, we propose a design process that combines high-speed cineradiography, optimization, dynamic scaling, three-dimensional printing, high-end servomotors and a tailored dry-suit to construct Pleurobot: a salamander-like robot that closely mimics its biological counterpart, Pleurodeles waltl Our previous robots helped us test and confirm hypotheses on the interaction between the locomotor neuronal networks of the limbs and the spine to generate basic swimming and walking gaits. With Pleurobot, we demonstrate a design process that will enable studies of richer motor skills in salamanders. In particular, we are interested in how these richer motor skills can be obtained by extending our spinal cord models with the addition of more descending pathways and more detailed limb central pattern generator networks. Pleurobot is a dynamically scaled amphibious salamander robot with a large number of actuated degrees of freedom (DOFs: 27 in total). Because of our design process, the robot can capture most of the animal's DOFs and range of motion, especially at the limbs. We demonstrate the robot's abilities by imposing raw kinematic data, extracted from X-ray videos, to the robot's joints for basic locomotor behaviours in water and on land. The robot closely matches the behaviour of the animal in terms of relative forward speeds and lateral displacements. Ground reaction forces during walking also resemble those of the animal. Based on our results, we anticipate that future studies on richer motor skills in salamanders will highly benefit from Pleurobot's design. © 2016 The Author(s).
Karakasiliotis, K.; Thandiackal, R.; Melo, K.; Horvat, T.; Mahabadi, N. K.; Tsitkov, S.; Cabelguen, J. M.; Ijspeert, A. J.
2016-01-01
Robots are increasingly used as scientific tools to investigate animal locomotion. However, designing a robot that properly emulates the kinematic and dynamic properties of an animal is difficult because of the complexity of musculoskeletal systems and the limitations of current robotics technology. Here, we propose a design process that combines high-speed cineradiography, optimization, dynamic scaling, three-dimensional printing, high-end servomotors and a tailored dry-suit to construct Pleurobot: a salamander-like robot that closely mimics its biological counterpart, Pleurodeles waltl. Our previous robots helped us test and confirm hypotheses on the interaction between the locomotor neuronal networks of the limbs and the spine to generate basic swimming and walking gaits. With Pleurobot, we demonstrate a design process that will enable studies of richer motor skills in salamanders. In particular, we are interested in how these richer motor skills can be obtained by extending our spinal cord models with the addition of more descending pathways and more detailed limb central pattern generator networks. Pleurobot is a dynamically scaled amphibious salamander robot with a large number of actuated degrees of freedom (DOFs: 27 in total). Because of our design process, the robot can capture most of the animal's DOFs and range of motion, especially at the limbs. We demonstrate the robot's abilities by imposing raw kinematic data, extracted from X-ray videos, to the robot's joints for basic locomotor behaviours in water and on land. The robot closely matches the behaviour of the animal in terms of relative forward speeds and lateral displacements. Ground reaction forces during walking also resemble those of the animal. Based on our results, we anticipate that future studies on richer motor skills in salamanders will highly benefit from Pleurobot's design. PMID:27358276
Social Network Sensors for Early Detection of Contagious Outbreaks
Christakis, Nicholas A.; Fowler, James H.
2010-01-01
Current methods for the detection of contagious outbreaks give contemporaneous information about the course of an epidemic at best. It is known that individuals near the center of a social network are likely to be infected sooner during the course of an outbreak, on average, than those at the periphery. Unfortunately, mapping a whole network to identify central individuals who might be monitored for infection is typically very difficult. We propose an alternative strategy that does not require ascertainment of global network structure, namely, simply monitoring the friends of randomly selected individuals. Such individuals are known to be more central. To evaluate whether such a friend group could indeed provide early detection, we studied a flu outbreak at Harvard College in late 2009. We followed 744 students who were either members of a group of randomly chosen individuals or a group of their friends. Based on clinical diagnoses, the progression of the epidemic in the friend group occurred 13.9 days (95% C.I. 9.9–16.6) in advance of the randomly chosen group (i.e., the population as a whole). The friend group also showed a significant lead time (p<0.05) on day 16 of the epidemic, a full 46 days before the peak in daily incidence in the population as a whole. This sensor method could provide significant additional time to react to epidemics in small or large populations under surveillance. The amount of lead time will depend on features of the outbreak and the network at hand. The method could in principle be generalized to other biological, psychological, informational, or behavioral contagions that spread in networks. PMID:20856792
Cheng, Long; Hou, Zeng-Guang; Tan, Min; Zhang, W J
2012-10-01
The trajectory tracking problem of a closed-chain five-bar robot is studied in this paper. Based on an error transformation function and the backstepping technique, an approximation-based tracking algorithm is proposed, which can guarantee the control performance of the robotic system in both the stable and transient phases. In particular, the overshoot, settling time, and final tracking error of the robotic system can be all adjusted by properly setting the parameters in the error transformation function. The radial basis function neural network (RBFNN) is used to compensate the complicated nonlinear terms in the closed-loop dynamics of the robotic system. The approximation error of the RBFNN is only required to be bounded, which simplifies the initial "trail-and-error" configuration of the neural network. Illustrative examples are given to verify the theoretical analysis and illustrate the effectiveness of the proposed algorithm. Finally, it is also shown that the proposed approximation-based controller can be simplified by a smart mechanical design of the closed-chain robot, which demonstrates the promise of the integrated design and control philosophy.
Popularity and adolescent friendship networks: selection and influence dynamics.
Dijkstra, Jan Kornelis; Cillessen, Antonius H N; Borch, Casey
2013-07-01
This study examined the dynamics of popularity in adolescent friendship networks across 3 years in middle school. Longitudinal social network modeling was used to identify selection and influence in the similarity of popularity among friends. It was argued that lower status adolescents strive to enhance their status through befriending higher status adolescents, whereas higher status adolescents strive to maintain their status by keeping lower status adolescents at a distance. The results largely supported these expectations. Selection partially accounted for similarity in popularity among friends; adolescents preferred to affiliate with similar-status or higher status peers, reinforcing the attractiveness of popular adolescents and explaining stability of popularity at the individual level. Influence processes also accounted for similarity in popularity over time, showing that peers increase in popularity and become more similar to their friends. The results showed how selection and influence processes account for popularity dynamics in adolescent networks over time.
A neuro-collision avoidance strategy for robot manipulators
NASA Technical Reports Server (NTRS)
Onema, Joel P.; Maclaunchlan, Robert A.
1992-01-01
The area of collision avoidance and path planning in robotics has received much attention in the research community. Our study centers on a combination of an artificial neural network paradigm with a motion planning strategy that insures safe motion of the Articulated Two-Link Arm with Scissor Hand System relative to an object. Whenever an obstacle is encountered, the arm attempts to slide along the obstacle surface, thereby avoiding collision by means of the local tangent strategy and its artificial neural network implementation. This combination compensates the inverse kinematics of a robot manipulator. Simulation results indicate that a neuro-collision avoidance strategy can be achieved by means of a learning local tangent method.
Mamdani Fuzzy System for Indoor Autonomous Mobile Robot
NASA Astrophysics Data System (ADS)
Khan, M. K. A. Ahamed; Rashid, Razif; Elamvazuthi, I.
2011-06-01
Several control algorithms for autonomous mobile robot navigation have been proposed in the literature. Recently, the employment of non-analytical methods of computing such as fuzzy logic, evolutionary computation, and neural networks has demonstrated the utility and potential of these paradigms for intelligent control of mobile robot navigation. In this paper, Mamdani fuzzy system for an autonomous mobile robot is developed. The paper begins with the discussion on the conventional controller and then followed by the description of fuzzy logic controller in detail.
Symbolic dynamic filtering and language measure for behavior identification of mobile robots.
Mallapragada, Goutham; Ray, Asok; Jin, Xin
2012-06-01
This paper presents a procedure for behavior identification of mobile robots, which requires limited or no domain knowledge of the underlying process. While the features of robot behavior are extracted by symbolic dynamic filtering of the observed time series, the behavior patterns are classified based on language measure theory. The behavior identification procedure has been experimentally validated on a networked robotic test bed by comparison with commonly used tools, namely, principal component analysis for feature extraction and Bayesian risk analysis for pattern classification.
Determining Locations by Use of Networks of Passive Beacons
NASA Technical Reports Server (NTRS)
Okino, Clayton; Gray, Andrew; Jennings, Esther
2009-01-01
Networks of passive radio beacons spanning moderate-sized terrain areas have been proposed to aid navigation of small robotic aircraft that would be used to explore Saturn s moon Titan. Such networks could also be used on Earth to aid navigation of robotic aircraft, land vehicles, or vessels engaged in exploration or reconnaissance in situations or locations (e.g., underwater locations) in which Global Positioning System (GPS) signals are unreliable or unavailable. Prior to use, it would be necessary to pre-position the beacons at known locations that would be determined by use of one or more precise independent global navigation system(s). Thereafter, while navigating over the area spanned by a given network of passive beacons, an exploratory robot would use the beacons to determine its position precisely relative to the known beacon positions (see figure). If it were necessary for the robot to explore multiple, separated terrain areas spanned by different networks of beacons, the robot could use a long-haul, relatively coarse global navigation system for the lower-precision position determination needed during transit between such areas. The proposed method of precise determination of position of an exploratory robot relative to the positions of passive radio beacons is based partly on the principles of radar and partly on the principles of radio-frequency identification (RFID) tags. The robot would transmit radar-like signals that would be modified and reflected by the passive beacons. The distance to each beacon would be determined from the roundtrip propagation time and/or round-trip phase shift of the signal returning from that beacon. Signals returned from different beacons could be distinguished by means of their RFID characteristics. Alternatively or in addition, the antenna of each beacon could be designed to radiate in a unique pattern that could be identified by the navigation system. Also, alternatively or in addition, sets of identical beacons could be deployed in unique configurations such that the navigation system could identify their unique combinations of radio-frequency reflections as an alternative to leveraging the uniqueness of the RFID tags. The degree of dimensional accuracy would depend not only on the locations of the beacons but also on the number of beacon signals received, the number of samples of each signal, the motion of the robot, and the time intervals between samples. At one extreme, a single sample of the return signal from a single beacon could be used to determine the distance from that beacon and hence to determine that the robot is located somewhere on a sphere, the radius of which equals that distance and the center of which lies at the beacon. In a less extreme example, the three-dimensional position of the robot could be determined with fair precision from a single sample of the signal from each of three beacons. In intermediate cases, position estimates could be refined and/or position ambiguities could be resolved by use of supplementary readings of an altimeter and other instruments aboard the robot.
Decomposing the Components of Friendship and Friends’ Influence on Adolescent Drinking and Smoking
Fujimoto, Kayo; Valente, Thomas W
2012-01-01
Purpose Friendship networks are an important source of peer influence. However, existing network studies vary in terms of how they operationalize friendship and friend’s influence on adolescent substance use. This study uses social network analysis to characterize three types of friendship relations: (1) mutual or reciprocated, (2) directional, and (3) intimate friends. We then examine the relative effects of each friendship type on adolescent drinking and smoking behavior. Methods Using a saturated sample from the Add Health data, a nationally representative sample of high-school adolescents (N=2,533 nested in 12 schools), we computed the level of exposure to drinking and smoking of friends using a network exposure model, and their association with individual drinking and smoking using fixed effect models. Results Results indicated that the influence from (1) is stronger on adolescent substance use than (2), especially for smoking. Regarding the directionality of (2), adolescents are equally influenced by both nominating and nominated friends on their drinking and smoking behavior. Results for (3) indicated that the influence from “best friends” was weaker than the one from non-“best friends,” which indicates that the order of friend nomination may not matter as much as nomination reciprocation. Conclusions This study demonstrates that considering different features of friendship relationships is important in evaluating friends’ influence on adolescent substance use. Related policy implications are discussed. PMID:22824443
Sajjadi, Homeira; Jorjoran Shushtari, Zahra; Shati, Mohsen; Salimi, Yahya; Dejman, Masoomeh; Vameghi, Meroe; Karimi, Salahedin; Mahmoodi, Zohreh
2018-01-01
Network scale-up is one of the most important indirect methods of estimating the size of clandestine populations and people with high-risk behaviors. The present study is an indirect estimation of the population size of students with high-risk behaviors in select universities of medical sciences. A total of 801 students from two University of Medical Sciences at Tehran and Alborz University of Medical Sciences were selected through convenience sampling. Six subgroups of high-risk behaviors were examined in the study, including Tramadol use, cannabis use, opium use, alcohol consumption, extramarital heterosexual intercourse, and heterosexual intercourse in return for money. To estimate the social network size in the study population, each participant was asked to name their close student friends from the two select universities. Data were collected using a checklist designed for this purpose. The participants' mean number of close friends from the selected medical universities was C = 8.14 (CI: 7.54-8.75). Within these social networks, friends with extramarital heterosexual intercourse (5.53%) and friends who consumed alcohol (4.92%) had the highest frequency, and friends who used opium (0.33%) had the lowest frequency. The variables of age, gender, marital status, type of residence and academic degree were significantly related to the likelihood of having close friends with certain high-risk behaviors (P<0.001). According to the results obtained, alcohol consumption and extramarital heterosexual intercourse are very common among students. Special HIV prevention programs are therefore necessary for this age group.
Social networks and mental health in post-conflict Mitrovica, Kosova.
Nakayama, Risa; Koyanagi, Ai; Stickley, Andrew; Kondo, Tetsuo; Gilmour, Stuart; Arenliu, Aliriza; Shibuya, Kenji
2014-11-17
To investigate the relation between social networks and mental health in the post-conflict municipality of Mitrovica, Kosovo. Using a three-stage stratified sampling method, 1239 respondents aged 16 years or above were recruited in the Greater Mitrovica region. Social network depth was measured by the frequency of contacts with friends, relatives and strangers. Depression and anxiety were measured using the Hospital Anxiety and Depression Scale (HADS). Multivariate logistic regression was used to examine the association between social network depth and mental health. The analytical sample consisted of 993 respondents. The prevalence of depression (54.3%) and anxiety (64.4%) were extremely high. In multiple regression analysis, a lower depth of social network (contact with friends) was associated with higher levels of both depression and anxiety. This study has shown that only one variety of social network--contact with friends--was important in terms of mental health outcomes in a population living in an area heavily affected by conflict. This suggests that the relation between social networks and mental health may be complex in that the effects of different forms of social network on mental health are not uniform and may depend on the way social networks are operationalised and the particular context in which the relationship is examined.
Lee, Aaron; Carrico, Catherine; Bourassa, Katelynn; Slosser, Andrea
2016-01-01
Purpose. Health status and social networks are associated with resilience among older adults. Each of these factors may be important to the ability of adults to remain in rural and remote communities as they age. We examined the association of health status and social networks and resilience among older adults dwelling in a rural and remote county in the Western United States. Methods. We selected a random sample of 198 registered voters aged 65 years or older from a frontier Wyoming county. Hierarchical linear regression was used to examine the association of health status as well as social networks and resilience. We also examined health status as a moderator of the relationship between social networks and resilience. Results. Family networks (p = 0.024) and mental health status (p < 0.001) significantly predicted resilience. Mental health status moderated the relationship of family (p = 0.004) and friend (p = 0.021) networks with resilience. Smaller family and friend networks were associated with greater resilience when mental health status was low, but not when it was high. Conclusion. Efforts to increase mental health status may improve resilience among older adults in rural environments, particularly for those with smaller family and friends networks. PMID:27478639
Steinley, Douglas; Slutske, Wendy S.
2014-01-01
Although socializing effects of friends’ drinking on adolescent drinking behavior have been firmly established in previous literature, study results on the importance of gender, as well as the specific role that gender may play in peer socialization, are very mixed. Given the increasing importance of gender in friendships (particularly opposite-sex friendships) during adolescence, it is necessary to better understand the nuanced roles that gender can play in peer socialization effects on alcohol use. In addition, previous studies focusing on the interplay between individual gender and friends’ gender have been largely dyadic; less is known about potential gendered effects of broader social networks. The current study sought to further investigate potential effects of gender on friends’ influence on adolescent drinking behavior with particular emphasis on the number of same-sex and opposite-sex friends within one’s friendship network, as well as closeness to these friends. Using Waves I and II of the saturated sample of the National Longitudinal Study of Adolescent Health (Add Health), adolescent friendship networks were used to calculate the mean drinking behaviors of adolescent friends. Multi-level models estimated the effects of individual drinking behaviors, friend drinking behaviors, and school-level drinking behaviors on adolescent drinking 1 year later, as well as moderating effects of gender composition of friendship groups and male and female friend closeness on the relationship between friends’ drinking behaviors and adolescent drinking behavior. Results documented that gender composition of friendship groups did not influence the effect of friends’ drinking on individual drinking 1 year later. However, closeness to friends did influence this relationship. As closeness to male friends decreased, the influence of their drinking behavior increased, for both boys and girls. A similar effect was found for female friends, but only for boys. Female friend closeness did not affect the relationship between peer alcohol socialization and girls’ alcohol use. The findings indicate that the role of gender on alcohol socialization may be more complex than previously thought, particularly when examining the potential role that alcohol use may play as a mechanism for social bonding within opposite-sex friendships and same-sex male friendships. PMID:24170437
Friendship Concept and Community Network Structure among Elementary School and University Students.
Hernández-Hernández, Ana María; Viga-de Alva, Dolores; Huerta-Quintanilla, Rodrigo; Canto-Lugo, Efrain; Laviada-Molina, Hugo; Molina-Segui, Fernanda
2016-01-01
We use complex network theory to study the differences between the friendship concepts in elementary school and university students. Four friendship networks were identified from surveys. Three of these networks are from elementary schools; two are located in the rural area of Yucatán and the other is in the urban area of Mérida, Yucatán. We analyzed the structure and the communities of these friendship networks and found significant differences among those at the elementary schools compared with those at the university. In elementary schools, the students make friends mainly in the same classroom, but there are also links among different classrooms because of the presence of siblings and relatives in the schools. These kinds of links (sibling-friend or relative-friend) are called, in this work, "mixed links". The classification of the communities is based on their similarity with the classroom composition. If the community is composed principally of students in different classrooms, the community is classified as heterogeneous. These kinds of communities appear in the elementary school friendship networks mainly because of the presence of relatives and siblings. Once the links between siblings and relatives are removed, the communities resembled the classroom composition. On the other hand, the university students are more selective in choosing friends and therefore, even when they have friends in the same classroom, those communities are quite different to the classroom composition. Also, in the university network, we found heterogeneous communities even when the presence of sibling and relatives is negligible. These differences made up a topological structure quite different at different academic levels. We also found differences in the network characteristics. Once these differences are understood, the topological structure of the friendship network and the communities shaped in an elementary school could be predicted if we know the total number of students and the ties between siblings and relatives. However, at the university, we cannot do the same. This discovery implies that friendship is a dynamic concept that produces several changes in the friendship network structure and the way that people make groups of friends; it provides the opportunity to give analytic support to observational studies. Communities were also studied by gender and we found that when the links among relatives and siblings were removed, the number of communities formed by one gender alone increased. At the university, many communities formed by students of the same gender were also found.
Friends of friends: are indirect connections in social networks important to animal behaviour?
Brent, Lauren J N
2015-05-01
Friend of a friend relationships, or the indirect connections between people, influence our health, well-being, financial success and reproductive output. As with humans, social behaviours in other animals often occur within a broad interconnected network of social ties. Yet studies of animal social behaviour tend to focus on associations between pairs of individuals. With the increase in popularity of social network analysis, researchers have started to look beyond the dyad to examine the role of indirect connections in animal societies. Here, I provide an overview of the new knowledge that has been uncovered by these studies. I focus on research that has addressed both the causes of social behaviours, i.e. the cognitive and genetic basis of indirect connections, as well as their consequences, i.e. the impact of indirect connections on social cohesion, information transfer, cultural practices and fitness. From these studies, it is apparent that indirect connections play an important role in animal behaviour, although future research is needed to clarify their contribution.
Friends of friends: are indirect connections in social networks important to animal behaviour?
Brent, Lauren J. N.
2015-01-01
Friend of a friend relationships, or the indirect connections between people, influence our health, well-being, financial success and reproductive output. As with humans, social behaviours in other animals often occur within a broad interconnected network of social ties. Yet studies of animal social behaviour tend to focus on associations between pairs of individuals. With the increase in popularity of social network analysis, researchers have started to look beyond the dyad to examine the role of indirect connections in animal societies. Here, I provide an overview of the new knowledge that has been uncovered by these studies. I focus on research that has addressed both the causes of social behaviours, i.e. the cognitive and genetic basis of indirect connections, as well as their consequences, i.e. the impact of indirect connections on social cohesion, information transfer, cultural practices and fitness. From these studies, it is apparent that indirect connections play an important role in animal behaviour, although future research is needed to clarify their contribution. PMID:25937639
A Mobile Robots Experimental Environment with Event-Based Wireless Communication
Guinaldo, María; Fábregas, Ernesto; Farias, Gonzalo; Dormido-Canto, Sebastián; Chaos, Dictino; Sánchez, José; Dormido, Sebastián
2013-01-01
An experimental platform to communicate between a set of mobile robots through a wireless network has been developed. The mobile robots get their position through a camera which performs as sensor. The video images are processed in a PC and a Waspmote card sends the corresponding position to each robot using the ZigBee standard. A distributed control algorithm based on event-triggered communications has been designed and implemented to bring the robots into the desired formation. Each robot communicates to its neighbors only at event times. Furthermore, a simulation tool has been developed to design and perform experiments with the system. An example of usage is presented. PMID:23881139
Pilkington, Pamela D; Windsor, Tim D; Crisp, Dimity A
2012-03-01
This study examined the extent to which associations between volunteering and subjective well-being (SWB) could be related to volunteers having more supportive social networks relative to nonvolunteers. The sample consisted of 561 midlife and older adults (aged 55-94 years) from the TRAnsitions In Later Life study. Multiple mediation analyses examined associations between hours spent volunteering per week; availability of social support from friends, relatives, and neighbors; positive and negative social exchanges; and SWB. The results indicated that the higher life satisfaction and positive affect reported by those who volunteer at moderate levels (up to 7 hr per week) are related to their higher levels of positive social exchanges and greater availability of social support from friends and family, relative to nonvolunteers. Those who volunteer at higher levels (7 hr or more per week) also reported greater levels of positive affect in comparison to nonvolunteers, and this was related to their greater availability of social support from friends. Availability of support from friends accounted for the greatest proportion of the volunteering-SWB associations. The findings suggest that the positive SWB associated with volunteering is related to volunteers' more extensive friend and family networks.
Cylkowska-Nowak, Mirosława; Pawlaczyk, Mariola
2017-01-01
Background The question arises how recent developments in robotics can contribute to the care for older people. The study is part of the EU-funded ENRICHME project. Objectives of Study The aim of the study was to investigate opinions of occupational therapy students (OTS), as future professional caregivers, on the use of robots in care for older people. Methods It included 26 OTS from Poznan University of Medical Sciences. To collect data, the Users' Needs, Requirements, and Abilities Questionnaire (UNRAQ) was developed. Findings OTS perceived the robot as “a useful device” and “an assistant” rather than “a companion” (p < 0.01). In their opinion, the most important functions of the robot were related to health aspects (emergency alarms, health parameters monitoring, physical activity and memory training, and reminders about medication, drinks, etc.), scored positively by 23–26 OTS. Functions such as mood detection, encouraging to contact with friends, and monitoring of food consumption were accepted by 16-17 OTS. Two statements concerning social functions (accompanying in everyday activities and decreasing the sense of loneliness) were rated positively by less the than half of the participants. Limitations and Recommendations for Further Research A module concerning technology use, including robotics, should constitute an important part of the curricula of both academic and continuous education of OTS. PMID:29097983
Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate
2015-01-01
Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world.
Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate
2015-01-01
Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world. PMID:26528176
Robotic Joints Support Horses and Humans
NASA Technical Reports Server (NTRS)
2008-01-01
A rehabilitative device first featured in Spinoff 2003 is not only helping human patients regain the ability to walk, but is now helping our four-legged friends as well. The late James Kerley, a prominent Goddard Space Flight Center researcher, developed cable-compliant mechanisms in the 1980s to enable sounding rocket assemblies and robots to grip or join objects. In cable-compliant joints (CCJs), short segments of cable connect structural elements, allowing for six directions of movement, twisting, alignment, and energy damping. Kerley later worked with Goddard s Wayne Eklund and Allen Crane to incorporate the cable-compliant mechanisms into a walker for human patients to support the pelvis and imitate hip joint movement.
Huang, Grace C; Soto, Daniel; Fujimoto, Kayo; Valente, Thomas W
2014-08-01
We examined the coevolution of adolescent friendships and peer influences with respect to their risk behaviors and social networking site use. Investigators of the Social Network Study collected longitudinal data during fall 2010 and spring 2011 from 10th-grade students in 5 Southern California high schools (n = 1434). We used meta-analyses of stochastic actor-based models to estimate changes in friendship ties and risk behaviors and the effects of Facebook and MySpace use. Significant shifts in adolescent smoking and drinking occurred despite little change in overall prevalence rates. Students with higher levels of alcohol use were more likely to send and receive friendship nominations and become friends with other drinkers. They were also more likely to increase alcohol use if their friends drank more. Adolescents selected friends with similar Facebook and MySpace use habits. Exposure to friends' risky online pictures increased smoking behaviors but had no significant effects on alcohol use. Our findings support a greater focus on friendship selection mechanisms in school-based alcohol use interventions. Social media platforms may help identify at-risk adolescent groups and foster positive norms about risk behaviors.
Comparing the Happiness Effects of Real and On-Line Friends
Helliwell, John F.; Huang, Haifang
2013-01-01
A recent large Canadian survey permits us to compare face-to-face (‘real-life’) and on-line social networks as sources of subjective well-being. The sample of 5,000 is drawn randomly from an on-line pool of respondents, a group well placed to have and value on-line friendships. We find three key results. First, the number of real-life friends is positively correlated with subjective well-being (SWB) even after controlling for income, demographic variables and personality differences. Doubling the number of friends in real life has an equivalent effect on well-being as a 50% increase in income. Second, the size of online networks is largely uncorrelated with subjective well-being. Third, we find that real-life friends are much more important for people who are single, divorced, separated or widowed than they are for people who are married or living with a partner. Findings from large international surveys (the European Social Surveys 2002–2008) are used to confirm the importance of real-life social networks to SWB; they also indicate a significantly smaller value of social networks to married or partnered couples. PMID:24019875
Cerebellum-inspired neural network solution of the inverse kinematics problem.
Asadi-Eydivand, Mitra; Ebadzadeh, Mohammad Mehdi; Solati-Hashjin, Mehran; Darlot, Christian; Abu Osman, Noor Azuan
2015-12-01
The demand today for more complex robots that have manipulators with higher degrees of freedom is increasing because of technological advances. Obtaining the precise movement for a desired trajectory or a sequence of arm and positions requires the computation of the inverse kinematic (IK) function, which is a major problem in robotics. The solution of the IK problem leads robots to the precise position and orientation of their end-effector. We developed a bioinspired solution comparable with the cerebellar anatomy and function to solve the said problem. The proposed model is stable under all conditions merely by parameter determination, in contrast to recursive model-based solutions, which remain stable only under certain conditions. We modified the proposed model for the simple two-segmented arm to prove the feasibility of the model under a basic condition. A fuzzy neural network through its learning method was used to compute the parameters of the system. Simulation results show the practical feasibility and efficiency of the proposed model in robotics. The main advantage of the proposed model is its generalizability and potential use in any robot.
Zwier, Sandra; Araujo, Theo; Boukes, Mark; Willemsen, Lotte
2011-10-01
This study aims to contribute to an emerging literature that seeks to understand how identity markers on social networking sites (SNSs) shape interpersonal impressions, and particularly the boundaries that SNSs present for articulating unconstrained "hoped-for possible selves." An experiment employing mock-up Facebook profiles was conducted, showing that appearing with friends on a Facebook profile picture as well as increasingly higher number of Facebook friends strengthened perceptions of a profiler's hoped-for level of social connectedness. Excessive numbers of friends, however, weakened perceptions of a profiler's real-level social connectedness, particularly among participants with smaller social networks on Facebook themselves. The discussion focuses on when people come to find that reasonable boundaries of self-generated information on an SNS have been exceeded.
Simpkins, Sandra D.; Schaefer, David R.; Price, Chara D.; Vest, Andrea E.
2012-01-01
Bioecological theory suggests that adolescents’ health is a result of selection and socialization processes occurring between adolescents and their microsettings. This study examines the association between adolescents’ friends and health using a social network model and data from the National Longitudinal Study of Adolescent Health (N = 1,896, mean age = 15.97 years). Results indicated evidence of friend influence on BMI and physical activity. Friendships were more likely among adolescents who engaged in greater physical activity and who were similar to one another in BMI and physical activity. These effects emerged after controlling for alternative friend selection factors, such as endogenous social network processes and propinquity through courses and activities. Some selection effects were moderated by gender, popularity, and reciprocity. PMID:24222971
Investigating Ground Swarm Robotics Using Agent Based Simulation
2006-12-01
Incorporation of virtual pheromones as a shared memory map is modeled as an additional capability that is found to enhance the robustness and reliability of the...virtual pheromones as a shared memory map is modeled as an additional capability that is found to enhance the robustness and reliability of the swarm... PHEROMONES .......................................... 42 1. Repel Friends under Inorganic SA.................................................. 45 2. Max
Dr. Janie Merkel is interviewed by Ryan Blum and Janice Friend.
Merkel, Janie
2007-12-01
Dr. Janie Merkel is the director of Yale's Chemical Genomics Screening Facility, a high-throughput screening laboratory that is part of the Yale University Center for Genomics and Proteomics. The Screening Facility connects Yale researchers with industry-quality robotic machinery and a diverse group of compound libraries, which have been used successfully to link therapeutic targets with potential therapies.
Candidate change agent identification among men at risk for HIV infection
Schneider, John A.; McFadden, Rachel B.; Laumann, Edward O.; Kumar, SG Prem; Gandham, Sabitha R.; Oruganti, Ganesh
2012-01-01
Despite limited HIV prevention potency, peer-based programs have become one of the most often used HIV prevention approaches internationally. These programs demonstrate a need for greater specificity in peer change agent (PCA) recruitment and social network evaluation. In the present three-phase study based in India (2009–2010), we first explored the nature of friendship among truck-drivers, a group of men at high risk for HIV infection, in order to develop a thorough understanding of the social forces that contribute to and maintain their personal networks. This was accomplished in the first two study phases, through a combination of focus group discussions (n=5 groups), in-depth qualitative interviews (n=20), and personal network analyses (n=25) of truck-drivers to define friendship and deepen our understanding of friendship across geographic spaces. Measures collected in phases I and II included friend typologies, discussion topics, social network influences, advice-giving, and risk reduction. Outcomes were assessed through an iterative process of qualitative textual analysis and social network analysis. The networks of truck-drivers were found to comprise three typologies: close friends, parking lot friends, and other friends. From these data, we developed an algorithmic approach to the identification of a candidate PCA within a high-risk man’s personal network. In stage III we piloted field-use of this approach to identify and recruit PCAs, and further evaluated their potential for intervention through preliminary analysis of the PCA’s own personal networks. An instrument was developed to translate what social network theory and analysis has taught us about egocentric network dynamics into a real-world methodology for identifying intervention-appropriate peers within an individual’s personal network. Our approach can be tailored to the specifications of any high-risk population, and may serve to enhance current peer-based HIV interventions. PMID:22762951
Dynamics of social balance on networks
NASA Astrophysics Data System (ADS)
Antal, T.; Krapivsky, P. L.; Redner, S.
2005-09-01
We study the evolution of social networks that contain both friendly and unfriendly pairwise links between individual nodes. The network is endowed with dynamics in which the sense of a link in an imbalanced triad—a triangular loop with one or three unfriendly links—is reversed to make the triad balanced. With this dynamics, an infinite network undergoes a dynamic phase transition from a steady state to “paradise”—all links are friendly—as the propensity p for friendly links in an update event passes through 1/2 . A finite network always falls into a socially balanced absorbing state where no imbalanced triads remain. If the additional constraint that the number of imbalanced triads in the network not increase in an update is imposed, then the network quickly reaches a balanced final state.
Biblio-MetReS: A bibliometric network reconstruction application and server
2011-01-01
Background Reconstruction of genes and/or protein networks from automated analysis of the literature is one of the current targets of text mining in biomedical research. Some user-friendly tools already perform this analysis on precompiled databases of abstracts of scientific papers. Other tools allow expert users to elaborate and analyze the full content of a corpus of scientific documents. However, to our knowledge, no user friendly tool that simultaneously analyzes the latest set of scientific documents available on line and reconstructs the set of genes referenced in those documents is available. Results This article presents such a tool, Biblio-MetReS, and compares its functioning and results to those of other user-friendly applications (iHOP, STRING) that are widely used. Under similar conditions, Biblio-MetReS creates networks that are comparable to those of other user friendly tools. Furthermore, analysis of full text documents provides more complete reconstructions than those that result from using only the abstract of the document. Conclusions Literature-based automated network reconstruction is still far from providing complete reconstructions of molecular networks. However, its value as an auxiliary tool is high and it will increase as standards for reporting biological entities and relationships become more widely accepted and enforced. Biblio-MetReS is an application that can be downloaded from http://metres.udl.cat/. It provides an easy to use environment for researchers to reconstruct their networks of interest from an always up to date set of scientific documents. PMID:21975133
Relational Diversity Promotes Cooperation in Prisoner’s Dilemma Games
Xu, Bo; Wang, Jianwei; Deng, Ruipu; Li, Miao
2014-01-01
Relational diversity can be characterized by heterogeneous distributions of tie strengths in social networks and this diversity is present not only among humans, but throughout the animal world. We account for this observation by analyzing two network datasets from Facebook. We measure the strength of a tie by calculating the extent of overlap of friends between the two individuals. Based on the previous findings in human experiments, we argue that it is very unlikely that players will allocate their investments equally to their neighbors. There is a tendency that players prefer to donate more to their intimate friends. We find that if players preferentially allocate their investments to their good friends, cooperation will be promoted in PDG. We proved that the facilitation of the cooperative strategy relies mostly on the cooperative allies between best friends, resulting in the formation of cooperative clusters which are able to prevail against the defectors even when there is a large cost to cooperate. Moreover, we discover that the effect of relational diversity cannot be analyzed by adopting classical complex networks models, because neither of the artificial networks is able to produce networks with diverse distributions of tie strengths. It is of vital importance to introduce real social networks to study the influence of diverse relations especially when it comes to humans. This research proposes a brand new perspective to understand the influence of social relations on the emergence of cooperation in evolutionary prisoner’s dilemma games. PMID:25474354
Relational diversity promotes cooperation in prisoner's dilemma games.
Xu, Bo; Wang, Jianwei; Deng, Ruipu; Li, Miao
2014-01-01
Relational diversity can be characterized by heterogeneous distributions of tie strengths in social networks and this diversity is present not only among humans, but throughout the animal world. We account for this observation by analyzing two network datasets from Facebook. We measure the strength of a tie by calculating the extent of overlap of friends between the two individuals. Based on the previous findings in human experiments, we argue that it is very unlikely that players will allocate their investments equally to their neighbors. There is a tendency that players prefer to donate more to their intimate friends. We find that if players preferentially allocate their investments to their good friends, cooperation will be promoted in PDG. We proved that the facilitation of the cooperative strategy relies mostly on the cooperative allies between best friends, resulting in the formation of cooperative clusters which are able to prevail against the defectors even when there is a large cost to cooperate. Moreover, we discover that the effect of relational diversity cannot be analyzed by adopting classical complex networks models, because neither of the artificial networks is able to produce networks with diverse distributions of tie strengths. It is of vital importance to introduce real social networks to study the influence of diverse relations especially when it comes to humans. This research proposes a brand new perspective to understand the influence of social relations on the emergence of cooperation in evolutionary prisoner's dilemma games.
Hinaut, Xavier; Petit, Maxime; Pointeau, Gregoire; Dominey, Peter Ford
2014-01-01
One of the principal functions of human language is to allow people to coordinate joint action. This includes the description of events, requests for action, and their organization in time. A crucial component of language acquisition is learning the grammatical structures that allow the expression of such complex meaning related to physical events. The current research investigates the learning of grammatical constructions and their temporal organization in the context of human-robot physical interaction with the embodied sensorimotor humanoid platform, the iCub. We demonstrate three noteworthy phenomena. First, a recurrent network model is used in conjunction with this robotic platform to learn the mappings between grammatical forms and predicate-argument representations of meanings related to events, and the robot's execution of these events in time. Second, this learning mechanism functions in the inverse sense, i.e., in a language production mode, where rather than executing commanded actions, the robot will describe the results of human generated actions. Finally, we collect data from naïve subjects who interact with the robot via spoken language, and demonstrate significant learning and generalization results. This allows us to conclude that such a neural language learning system not only helps to characterize and understand some aspects of human language acquisition, but also that it can be useful in adaptive human-robot interaction.
A networked modular hardware and software system for MRI-guided robotic prostate interventions
NASA Astrophysics Data System (ADS)
Su, Hao; Shang, Weijian; Harrington, Kevin; Camilo, Alex; Cole, Gregory; Tokuda, Junichi; Hata, Nobuhiko; Tempany, Clare; Fischer, Gregory S.
2012-02-01
Magnetic resonance imaging (MRI) provides high resolution multi-parametric imaging, large soft tissue contrast, and interactive image updates making it an ideal modality for diagnosing prostate cancer and guiding surgical tools. Despite a substantial armamentarium of apparatuses and systems has been developed to assist surgical diagnosis and therapy for MRI-guided procedures over last decade, the unified method to develop high fidelity robotic systems in terms of accuracy, dynamic performance, size, robustness and modularity, to work inside close-bore MRI scanner still remains a challenge. In this work, we develop and evaluate an integrated modular hardware and software system to support the surgical workflow of intra-operative MRI, with percutaneous prostate intervention as an illustrative case. Specifically, the distinct apparatuses and methods include: 1) a robot controller system for precision closed loop control of piezoelectric motors, 2) a robot control interface software that connects the 3D Slicer navigation software and the robot controller to exchange robot commands and coordinates using the OpenIGTLink open network communication protocol, and 3) MRI scan plane alignment to the planned path and imaging of the needle as it is inserted into the target location. A preliminary experiment with ex-vivo phantom validates the system workflow, MRI-compatibility and shows that the robotic system has a better than 0.01mm positioning accuracy.
Hinaut, Xavier; Petit, Maxime; Pointeau, Gregoire; Dominey, Peter Ford
2014-01-01
One of the principal functions of human language is to allow people to coordinate joint action. This includes the description of events, requests for action, and their organization in time. A crucial component of language acquisition is learning the grammatical structures that allow the expression of such complex meaning related to physical events. The current research investigates the learning of grammatical constructions and their temporal organization in the context of human-robot physical interaction with the embodied sensorimotor humanoid platform, the iCub. We demonstrate three noteworthy phenomena. First, a recurrent network model is used in conjunction with this robotic platform to learn the mappings between grammatical forms and predicate-argument representations of meanings related to events, and the robot's execution of these events in time. Second, this learning mechanism functions in the inverse sense, i.e., in a language production mode, where rather than executing commanded actions, the robot will describe the results of human generated actions. Finally, we collect data from naïve subjects who interact with the robot via spoken language, and demonstrate significant learning and generalization results. This allows us to conclude that such a neural language learning system not only helps to characterize and understand some aspects of human language acquisition, but also that it can be useful in adaptive human-robot interaction. PMID:24834050
Three Degrees of Inclusion: the Gossip-Effect in Human Networks
NASA Astrophysics Data System (ADS)
Szekfu˝, Balázs; Szvetelszky, Zsuzsanna
2005-06-01
Using the scientific definition of gossip, an ancient and ubiquitous phenomenon of the social networks, we present our preliminary study and its results on how to measure the networks based on dissemination of connections and information. We try to accurately calculate the gossip-effects in networks with our hypothesis of "three degrees of inclusion". Our preliminary study on the subject of "three degrees of inclusion" gives latency to a very important property of social networks. Observing the human communication of closely knit social groups we came to the conclusion that the human networks are based on not more than three degrees of links. Taking the strong human ties into account our research indicates that whoever is on the fourth degree rarely counts as an in-group member. Our close friend's close friend's close friend — that is about the farthest — three steps — our network can reach out when it comes to telling a story or asking for a favor. Up to now no investigations have been performed to see whether the effects of gossip lead to the phase transition of the content of network's self-organizing communication. Our conclusion is that the gossip-effect must be considered as the prefactor of the news and opinions diffusion and dynamics at the social level.
Mercken, Liesbeth; Snijders, Tom A B; Steglich, Christian; Vertiainen, Erkki; de Vries, Hein
2010-07-01
The main goal of this study was to examine differences between adolescent male and female friendship networks regarding smoking-based selection and influence processes using newly developed social network analysis methods that allow the current state of continuously changing friendship networks to act as a dynamic constraint for changes in smoking behaviour, while allowing current smoking behaviour to be simultaneously a dynamic constraint for changes in friendship networks. Longitudinal design with four measurements. Nine junior high schools in Finland. A total of 1163 adolescents (mean age = 13.6 years) who participated in the control group of the ESFA (European Smoking prevention Framework Approach) study, including 605 males and 558 females. Smoking behaviour of adolescents, parents, siblings and friendship ties. Smoking-based selection of friends was found in male as well as female networks. However, support for influence among friends was found only in female networks. Furthermore, females and males were both influenced by parental smoking behaviour. In Finnish adolescents, both male and female smokers tend to select other smokers as friends but it appears that only females are influenced to smoke by their peer group. This suggests that prevention campaigns targeting resisting peer pressure may be more effective in adolescent girls than boys.
Tweeting it off: characteristics of adults who tweet about a weight loss attempt
Pagoto, Sherry; Schneider, Kristin L; Evans, Martinus; Waring, Molly E; Appelhans, Brad; Busch, Andrew M; Whited, Matthew C; Thind, Herpreet; Ziedonis, Michelle
2014-01-01
Objective The purpose of this study was to describe adults who use Twitter during a weight loss attempt and to compare the positive and negative social influences they experience from their offline friends, online friends, and family members. Materials and methods Participants (N=100, 80% female, mean age=37.65, SD=8.42) were recruited from Twitter. They completed a brief survey about their experiences discussing their weight loss attempt with their online and offline friends and provided responses to open-ended questions on the benefits and drawbacks of discussing weight on Twitter, Facebook, and weight-specific social networks. Results Participants rated their connections on Twitter and weight loss-specific social networks to be significantly greater sources of positive social influence for their weight loss (F(3)=3.47; p<0.001) and significantly lesser sources of negative social influence (F(3)=40.39 and F(3)=33.68 (both p<0.001)) than their offline friends, family, and Facebook friends. Greater positive social influence from Twitter and Facebook friends was associated with greater weight loss in participants’ most recent weight loss attempt (r=0.30, r=0.32; p<0.01). The most commonly reported benefits of tweeting about weight loss include social support, information, and accountability. The most common drawbacks reported are that interactions were too brief and lacked personal connection. Discussion People who discuss their weight loss on Twitter report more social support and less negativity from their Twitter friends than their Facebook friends and in-person relationships. Conclusions Online social networks should be explored as a tool for connecting patients who lack weight loss social support from their in-person relationships. PMID:24928175
Carter, Stacey C; Chiang, Alexander; Shah, Galaxy; Kwan, Lorna; Montgomery, Jeffrey S; Karam, Amer; Tarnay, Christopher; Guru, Khurshid A; Hu, Jim C
2015-05-01
To examine the feasibility and outcomes of video-based peer feedback through social networking to facilitate robotic surgical skill acquisition. The acquisition of surgical skills may be challenging for novel techniques and/or those with prolonged learning curves. Randomized controlled trial involving 41 resident physicians performing the Tubes (Da Vinci Intuitive Surgical, Sunnyvale, CA) simulator exercise with versus without peer feedback of video-recorded performance through a social networking Web page. Data collected included simulator exercise score, time to completion, and comfort and satisfaction with robotic surgery simulation. There were no baseline differences between the intervention group (n = 20) and controls (n = 21). The intervention group showed improvement in mean scores from session 1 to sessions 2 and 3 (60.7 vs 75.5, P < 0.001, and 60.7 vs 80.1, P < 0.001, respectively). The intervention group scored significantly higher than controls at sessions 2 and 3 (75.5 vs 59.6, P = 0.009, and 80.1 vs 65.9, P = 0.019, respectively). The mean time (seconds) to complete the task was shorter for the intervention group than for controls during sessions 2 and 3 (217.4 vs 279.0, P = 0.004, and 201.4 vs 261.9, P = 0.006, respectively). At the study conclusion, feedback subjects were more comfortable with robotic surgery than controls (90% vs 62%, P = 0.021) and expressed greater satisfaction with the learning experience (100% vs 67%, P = 0.014). Of the intervention subjects, 85% found that peer feedback was useful and 100% found it effective. Video-based peer feedback through social networking appears to be an effective paradigm for surgical education and accelerates the robotic surgery learning curve during simulation.
Socially assistive robotics for stroke and mild TBI rehabilitation.
Matarić, Maja; Tapus, Adriana; Winstein, Carolee; Eriksson, Jon
2009-01-01
This paper describes an interdisciplinary research project aimed at developing and evaluating effective and user-friendly non-contact robot-assisted therapy, aimed at in-home use. The approach stems from the emerging field of social cognitive neuroscience that seeks to understand phenomena in terms of interactions between the social, cognitive, and neural levels of analysis. This technology-assisted therapy is designed to be safe and affordable, and relies on novel human-robot interaction methods for accelerated recovery of upper-extremity function after lesion-induced hemiparesis. The work is based on the combined expertise in the science and technology of non-contact socially assistive robotics and the clinical science of neurorehabilitation and motor learning, brought together to study how to best enhance recovery after stroke and mild traumatic brain injury. Our approach is original and promising in that it combines several ingredients that individually have been shown to be important for learning and long-term efficacy in motor neurorehabilitation: (1) intensity of task specific training and (2) engagement and self-management of goal-directed actions. These principles motivate and guide the strategies used to develop novel user activity sensing and provide the rationale for development of socially assistive robotics therapy for monitoring and coaching users toward personalized and optimal rehabilitation programs.
Intermediate peer contexts and educational outcomes: Do the friends of students' friends matter?
Carbonaro, William; Workman, Joseph
2016-07-01
Sociologists of education have long been interested in the effects of peer relations on educational outcomes. Recent theory and research on adolescence suggest that peers on the boundaries of students' friendship networks may play an important role in shaping behaviors and educational outcomes. In this study, we examine the importance of a key "intermediate peer context" for students' outcomes: the friends of a student's friends. Our findings indicate both friends' and friends' friends' characteristics independently predict students' college expectations and their risk of dropping out of high school (although only friends' characteristics predict GPA). Our models suggest the magnitude of students' friends-of-friends' characteristics are at least as large their friends' characteristics. Together, the association between the peer context and students outcomes is considerably larger when accounting for both the characteristics of students' friends and the friends of their friends. Copyright © 2016 Elsevier Inc. All rights reserved.
Motion planning with complete knowledge using a colored SOM.
Vleugels, J; Kok, J N; Overmars, M
1997-01-01
The motion planning problem requires that a collision-free path be determined for a robot moving amidst a fixed set of obstacles. Most neural network approaches to this problem are for the situation in which only local knowledge about the configuration space is available. The main goal of the paper is to show that neural networks are also suitable tools in situations with complete knowledge of the configuration space. In this paper we present an approach that combines a neural network and deterministic techniques. We define a colored version of Kohonen's self-organizing map that consists of two different classes of nodes. The network is presented with random configurations of the robot and, from this information, it constructs a road map of possible motions in the work space. The map is a growing network, and different nodes are used to approximate boundaries of obstacles and the Voronoi diagram of the obstacles, respectively. In a second phase, the positions of the two kinds of nodes are combined to obtain the road map. In this way a number of typical problems with small obstacles and passages are avoided, and the required number of nodes for a given accuracy is within reasonable limits. This road map is searched to find a motion connecting the given source and goal configurations of the robot. The algorithm is simple and general; the only specific computation that is required is a check for intersection of two polygons. We implemented the algorithm for planar robots allowing both translation and rotation and experiments show that compared to conventional techniques it performs well, even for difficult motion planning scenes.
Adaptive control strategies for flexible robotic arm
NASA Technical Reports Server (NTRS)
Bialasiewicz, Jan T.
1993-01-01
The motivation of this research came about when a neural network direct adaptive control scheme was applied to control the tip position of a flexible robotic arm. Satisfactory control performance was not attainable due to the inherent non-minimum phase characteristics of the flexible robotic arm tip. Most of the existing neural network control algorithms are based on the direct method and exhibit very high sensitivity if not unstable closed-loop behavior. Therefore a neural self-tuning control (NSTC) algorithm is developed and applied to this problem and showed promising results. Simulation results of the NSTC scheme and the conventional self-tuning (STR) control scheme are used to examine performance factors such as control tracking mean square error, estimation mean square error, transient response, and steady state response.
Aerial robot intelligent control method based on back-stepping
NASA Astrophysics Data System (ADS)
Zhou, Jian; Xue, Qian
2018-05-01
The aerial robot is characterized as strong nonlinearity, high coupling and parameter uncertainty, a self-adaptive back-stepping control method based on neural network is proposed in this paper. The uncertain part of the aerial robot model is compensated online by the neural network of Cerebellum Model Articulation Controller and robust control items are designed to overcome the uncertainty error of the system during online learning. At the same time, particle swarm algorithm is used to optimize and fix parameters so as to improve the dynamic performance, and control law is obtained by the recursion of back-stepping regression. Simulation results show that the designed control law has desired attitude tracking performance and good robustness in case of uncertainties and large errors in the model parameters.
A Green Robotic Observatory for Astronomy Education
NASA Astrophysics Data System (ADS)
Reddy, Vishnu; Archer, K.
2008-09-01
With the development of robotic telescopes and stable remote observing software, it is currently possible for a small institution to have an affordable astronomical facility for astronomy education. However, a faculty member has to deal with the light pollution (observatory location on campus), its nightly operations and regular maintenance apart from his day time teaching and research responsibilities. While building an observatory at a remote location is a solution, the cost of constructing and operating such a facility, not to mention the environmental impact, are beyond the reach of most institutions. In an effort to resolve these issues we have developed a robotic remote observatory that can be operated via the internet from anywhere in the world, has a zero operating carbon footprint and minimum impact on the local environment. The prototype observatory is a clam-shell design that houses an 8-inch telescope with a SBIG ST-10 CCD detector. The brain of the observatory is a low draw 12-volt harsh duty computer that runs the dome, telescope, CCD camera, focuser, and weather monitoring. All equipment runs of a 12-volt AGM-style battery that has low lead content and hence more environmental-friendly to dispose. The total power of 12-14 amp/hrs is generated from a set of solar panels that are large enough to maintain a full battery charge for several cloudy days. This completely eliminates the need for a local power grid for operations. Internet access is accomplished via a high-speed cell phone broadband connection or satellite link eliminating the need for a phone network. An independent observatory monitoring system interfaces with the observatory computer during operation. The observatory converts to a trailer for transportation to the site and is converted to a semi-permanent building without wheels and towing equipment. This ensures minimal disturbance to local environment.
ERIC Educational Resources Information Center
Walther, Joseph B.; Van Der Heide, Brandon; Kim, Sang-Yeon; Westerman, David; Tong, Stephanie Tom
2008-01-01
This research explores how cues deposited by social partners onto one's online networking profile affect observers' impressions of the profile owner. An experiment tested the relationships between both (a) what one's associates say about a person on a social network site via "wall postings," where friends leave public messages, and (b) the…
ERIC Educational Resources Information Center
Hughes, Mikayla; Morrison, Kelly; Asada, Kelli Jean K.
2005-01-01
Friends with benefits relationships (FWBRs) are defined as relationships between cross-sex friends in which the friends engage in sexual activity but do not define their relationship as romantic. Relationship scholars have only recently begun to examine these relationships, despite their mention in the popular media (e.g., HBO's 'Sex in the City,'…
Family and Friends: Which Types of Personal Relationships Go Together in a Network?
Rözer, Jesper; Mollenhorst, Gerald; Poortman, Anne-Rigt
We examine the link between family and personal networks. Using arguments about meeting opportunities, competition and social influence, we hypothesise how the presence of specific types of family members (i.e., a partner, children, parents and siblings) and non-family members (i.e., friends, neighbours and colleagues) in the network mutually affect one another. In addition, we propose that-beyond their mere presence-the active role of family members in the network strongly affects the presence of non-family members in the network. Data from the third wave of the Survey on the Social Networks of the Dutch, collected in 2012 and 2013, show that active involvement is of key importance; more than merely having family members present in one's personal network, the active involvement of specific types of family members in the personal network is associated with having disproportionally more other family members and having somewhat fewer non-family members in the network.
Modeling cascading failures with the crisis of trust in social networks
NASA Astrophysics Data System (ADS)
Yi, Chengqi; Bao, Yuanyuan; Jiang, Jingchi; Xue, Yibo
2015-10-01
In social networks, some friends often post or disseminate malicious information, such as advertising messages, informal overseas purchasing messages, illegal messages, or rumors. Too much malicious information may cause a feeling of intense annoyance. When the feeling exceeds a certain threshold, it will lead social network users to distrust these friends, which we call the crisis of trust. The crisis of trust in social networks has already become a universal concern and an urgent unsolved problem. As a result of the crisis of trust, users will cut off their relationships with some of their untrustworthy friends. Once a few of these relationships are made unavailable, it is likely that other friends will decline trust, and a large portion of the social network will be influenced. The phenomenon in which the unavailability of a few relationships will trigger the failure of successive relationships is known as cascading failure dynamics. To our best knowledge, no one has formally proposed cascading failures dynamics with the crisis of trust in social networks. In this paper, we address this potential issue, quantify the trust between two users based on user similarity, and model the minimum tolerance with a nonlinear equation. Furthermore, we construct the processes of cascading failures dynamics by considering the unique features of social networks. Based on real social network datasets (Sina Weibo, Facebook and Twitter), we adopt two attack strategies (the highest trust attack (HT) and the lowest trust attack (LT)) to evaluate the proposed dynamics and to further analyze the changes of the topology, connectivity, cascading time and cascade effect under the above attacks. We numerically find that the sparse and inhomogeneous network structure in our cascading model can better improve the robustness of social networks than the dense and homogeneous structure. However, the network structure that seems like ripples is more vulnerable than the other two network structures. Our findings will be useful in further guiding the construction of social networks to effectively avoid the cascading propagation with the crisis of trust. Some research results can help social network service providers to avoid severe cascading failures.
Gamma--Ray burst afterglows with the Watcher robotic telescope
NASA Astrophysics Data System (ADS)
Topinka, M.; Hanlon, L.; Meehan, S.; Tisdall, P.; Jelínek, M.; Kubánek, P.; van Heerden, H.; Meintjes, P.
2014-12-01
The main scientific goal of the Watcher robotic telescope is the rapid follow-up observation of gamma--ray burst afterglows. Some examples of recent observations, including GRB 120327A and GRB 130606A, at a redshift of 5.9, are presented. The telescope has recently been successfully integrated into the GLORIA global robotic telescope network, which allows users to use the array for their own scientific projects.
A stability-based mechanism for hysteresis in the walk–trot transition in quadruped locomotion
Aoi, Shinya; Katayama, Daiki; Fujiki, Soichiro; Tomita, Nozomi; Funato, Tetsuro; Yamashita, Tsuyoshi; Senda, Kei; Tsuchiya, Kazuo
2013-01-01
Quadrupeds vary their gaits in accordance with their locomotion speed. Such gait transitions exhibit hysteresis. However, the underlying mechanism for this hysteresis remains largely unclear. It has been suggested that gaits correspond to attractors in their dynamics and that gait transitions are non-equilibrium phase transitions that are accompanied by a loss in stability. In the present study, we used a robotic platform to investigate the dynamic stability of gaits and to clarify the hysteresis mechanism in the walk–trot transition of quadrupeds. Specifically, we used a quadruped robot as the body mechanical model and an oscillator network for the nervous system model to emulate dynamic locomotion of a quadruped. Experiments using this robot revealed that dynamic interactions among the robot mechanical system, the oscillator network, and the environment generate walk and trot gaits depending on the locomotion speed. In addition, a walk–trot transition that exhibited hysteresis was observed when the locomotion speed was changed. We evaluated the gait changes of the robot by measuring the locomotion of dogs. Furthermore, we investigated the stability structure during the gait transition of the robot by constructing a potential function from the return map of the relative phase of the legs and clarified the physical characteristics inherent to the gait transition in terms of the dynamics. PMID:23389894
Neural network-based multiple robot simultaneous localization and mapping.
Saeedi, Sajad; Paull, Liam; Trentini, Michael; Li, Howard
2011-12-01
In this paper, a decentralized platform for simultaneous localization and mapping (SLAM) with multiple robots is developed. Each robot performs single robot view-based SLAM using an extended Kalman filter to fuse data from two encoders and a laser ranger. To extend this approach to multiple robot SLAM, a novel occupancy grid map fusion algorithm is proposed. Map fusion is achieved through a multistep process that includes image preprocessing, map learning (clustering) using neural networks, relative orientation extraction using norm histogram cross correlation and a Radon transform, relative translation extraction using matching norm vectors, and then verification of the results. The proposed map learning method is a process based on the self-organizing map. In the learning phase, the obstacles of the map are learned by clustering the occupied cells of the map into clusters. The learning is an unsupervised process which can be done on the fly without any need to have output training patterns. The clusters represent the spatial form of the map and make further analyses of the map easier and faster. Also, clusters can be interpreted as features extracted from the occupancy grid map so the map fusion problem becomes a task of matching features. Results of the experiments from tests performed on a real environment with multiple robots prove the effectiveness of the proposed solution.
A stability-based mechanism for hysteresis in the walk-trot transition in quadruped locomotion.
Aoi, Shinya; Katayama, Daiki; Fujiki, Soichiro; Tomita, Nozomi; Funato, Tetsuro; Yamashita, Tsuyoshi; Senda, Kei; Tsuchiya, Kazuo
2013-04-06
Quadrupeds vary their gaits in accordance with their locomotion speed. Such gait transitions exhibit hysteresis. However, the underlying mechanism for this hysteresis remains largely unclear. It has been suggested that gaits correspond to attractors in their dynamics and that gait transitions are non-equilibrium phase transitions that are accompanied by a loss in stability. In the present study, we used a robotic platform to investigate the dynamic stability of gaits and to clarify the hysteresis mechanism in the walk-trot transition of quadrupeds. Specifically, we used a quadruped robot as the body mechanical model and an oscillator network for the nervous system model to emulate dynamic locomotion of a quadruped. Experiments using this robot revealed that dynamic interactions among the robot mechanical system, the oscillator network, and the environment generate walk and trot gaits depending on the locomotion speed. In addition, a walk-trot transition that exhibited hysteresis was observed when the locomotion speed was changed. We evaluated the gait changes of the robot by measuring the locomotion of dogs. Furthermore, we investigated the stability structure during the gait transition of the robot by constructing a potential function from the return map of the relative phase of the legs and clarified the physical characteristics inherent to the gait transition in terms of the dynamics.
The most common friend first immunization
NASA Astrophysics Data System (ADS)
Nian, Fu-Zhong; Hu, Cha-Sheng
2016-12-01
In this paper, a standard susceptible-infected-recovered-susceptible(SIRS) epidemic model based on the Watts-Strogatz (WS) small-world network model and the Barabsi-Albert (BA) scale-free network model is established, and a new immunization scheme — “the most common friend first immunization” is proposed, in which the most common friend’s node is described as being the first immune on the second layer protection of complex networks. The propagation situations of three different immunization schemes — random immunization, high-risk immunization, and the most common friend first immunization are studied. At the same time, the dynamic behaviors are also studied on the WS small-world and the BA scale-free network. Moreover, the analytic and simulated results indicate that the immune effect of the most common friend first immunization is better than random immunization, but slightly worse than high-risk immunization. However, high-risk immunization still has some limitations. For example, it is difficult to accurately define who a direct neighbor in the life is. Compared with the traditional immunization strategies having some shortcomings, the most common friend first immunization is effective, and it is nicely consistent with the actual situation. Project supported by the National Natural Science Foundation of China (Grant No. 61263019), the Program for International Science and Technology Cooperation Projects of Gansu Province, China (Grant No. 144WCGA166), and the Program for Longyuan Young Innovation Talents and the Doctoral Foundation of Lanzhou University of Technology, China.
Service Oriented Robotic Architecture for Space Robotics: Design, Testing, and Lessons Learned
NASA Technical Reports Server (NTRS)
Fluckiger, Lorenzo Jean Marc E; Utz, Hans Heinrich
2013-01-01
This paper presents the lessons learned from six years of experiments with planetary rover prototypes running the Service Oriented Robotic Architecture (SORA) developed by the Intelligent Robotics Group (IRG) at the NASA Ames Research Center. SORA relies on proven software engineering methods and technologies applied to space robotics. Based on a Service Oriented Architecture and robust middleware, SORA encompasses on-board robot control and a full suite of software tools necessary for remotely operated exploration missions. SORA has been eld tested in numerous scenarios of robotic lunar and planetary exploration. The experiments conducted by IRG with SORA exercise a large set of the constraints encountered in space applications: remote robotic assets, ight relevant science instruments, distributed operations, high network latencies and unreliable or intermittent communication links. In this paper, we present the results of these eld tests in regard to the developed architecture, and discuss its bene ts and limitations.
NASA Astrophysics Data System (ADS)
Billard, Aude
2000-10-01
This paper summarizes a number of experiments in biologically inspired robotics. The common feature to all experiments is the use of artificial neural networks as the building blocks for the controllers. The experiments speak in favor of using a connectionist approach for designing adaptive and flexible robot controllers, and for modeling neurological processes. I present 1) DRAMA, a novel connectionist architecture, which has general property for learning time series and extracting spatio-temporal regularities in multi-modal and highly noisy data; 2) Robota, a doll-shaped robot, which imitates and learns a proto-language; 3) an experiment in collective robotics, where a group of 4 to 15 Khepera robots learn dynamically the topography of an environment whose features change frequently; 4) an abstract, computational model of primate ability to learn by imitation; 5) a model for the control of locomotor gaits in a quadruped legged robot.
Social networks of patients with psychosis: a systematic review.
Palumbo, Claudia; Volpe, Umberto; Matanov, Aleksandra; Priebe, Stefan; Giacco, Domenico
2015-10-12
Social networks are important for mental health outcomes as they can mobilise resources and help individuals to cope with social stressors. Individuals with psychosis may have specific difficulties in establishing and maintaining social relationships which impacts on their well-being and quality of life. There has been a growing interest in developing social network interventions for patients with psychotic disorders. A systematic literature review was conducted to investigate the size of social networks of patients with psychotic disorders, as well as their friendship networks. A systematic electronic search was carried out in MEDLINE, EMBASE and PsychINFO databases using a combination of search terms relating to 'social network', 'friendship' and 'psychotic disorder'. The search identified 23 relevant papers. Out of them, 20 reported patient social network size. Four papers reported the mean number of friends in addition to whole network size, while three further papers focused exclusively on the number of friends. Findings varied substantially across the studies, with a weighted mean size of 11.7 individuals for whole social networks and 3.4 individuals for friendship networks. On average, 43.1 % of the whole social network was composed of family members, while friends accounted for 26.5 %. Studies assessing whole social network size and friendship networks of people with psychosis are difficult to compare as different concepts and methods of assessment were applied. The extent of the overlap between different social roles assessed in the networks was not always clear. Greater conceptual and methodological clarity is needed in order to help the development of effective strategies to increase social resources of patients with psychosis.
Support and Conflict in Ethnically Diverse Young Adults' Relationships with Parents and Friends
ERIC Educational Resources Information Center
Moilanen, Kristin L.; Raffaelli, Marcela
2010-01-01
We examined support and conflict with parents and close friends in a sample of ethnically diverse young adults (European-, Asian-, Cuban-, Latin-, and Mexican Americans). College students (N = 495) completed six subscales from the Network of Relationships Inventory (NRI; Furman & Buhrmester, 1985). Friends were rated higher than parents on…
NASA Astrophysics Data System (ADS)
Plait, Philip
2008-05-01
Social networks are websites (or software that distributes media online) where users can distribute content to either a list of friends on that site or to anyone who surfs onto their page, and where those friends can interact and discuss the content. By linking to friends online, the users’ personal content (pictures, songs, favorite movies, diaries, websites, and so on) is dynamically distributed, and can "become viral", that is, get spread rapidly as more people see it and spread it themselves. Social networks are immensely popular around the planet, especially with younger users. The biggest social networks are Facebook and MySpace; an IYA2009 user already exists on Facebook, and one will be created for MySpace (in fact, several NASA satellites such as GLAST and Swift already have successful MySpace pages). Twitter is another network where data distribution is more limited; it is more like a mini-blog, but is very popular. IYA2009 already has a Twitter page, and will be updated more often with relevant information. In this talk I will review the existing social networks, show people how and why they are useful, and give them the tools they need to contribute meaningfully to IYA's online reach.
Bakkum, Douglas J.; Gamblen, Philip M.; Ben-Ary, Guy; Chao, Zenas C.; Potter, Steve M.
2007-01-01
Here, we and others describe an unusual neurorobotic project, a merging of art and science called MEART, the semi-living artist. We built a pneumatically actuated robotic arm to create drawings, as controlled by a living network of neurons from rat cortex grown on a multi-electrode array (MEA). Such embodied cultured networks formed a real-time closed-loop system which could now behave and receive electrical stimulation as feedback on its behavior. We used MEART and simulated embodiments, or animats, to study the network mechanisms that produce adaptive, goal-directed behavior. This approach to neural interfacing will help instruct the design of other hybrid neural-robotic systems we call hybrots. The interfacing technologies and algorithms developed have potential applications in responsive deep brain stimulation systems and for motor prosthetics using sensory components. In a broader context, MEART educates the public about neuroscience, neural interfaces, and robotics. It has paved the way for critical discussions on the future of bio-art and of biotechnology. PMID:18958276
Three degrees of inclusion: the emergence of self-organizing social beliefs
NASA Astrophysics Data System (ADS)
Szvetelszky, Zsuzsanna; Szekfu˝, Balázs
2005-07-01
Using the scientific definition of gossip, an ancient and ubiquitous phenomenon of the social networks, we present our preliminary study and its results on how to measure the networks based on dissemination of connections and information. We try to accurately calculate the gossip-effects in networks with our hypothesis of "three degrees of inclusion". Our preliminary study on the subject of "three degrees of inclusion" gives latency to a very important property of social networks. Observing the human communication of closely knit social groups we came to the conclusion that the human networks are based on not more than three degrees of links. Taking the strong human ties into account our research indicates that whoever is on the fourth degree rarely counts as an in-group member. Our close friend's close friend's close friend — that is about the farthest — three steps — our network can reach out when it comes to telling a story or asking for a favor. Up to now no investigations have been performed to see whether the effects of gossip lead to the phase transition of the content of network's self-organizing communication. Our conclusion is that the gossip-effect must be considered as the prefactor of the news and opinions diffusion and dynamics at the social level.
Kim, Jun Won; Kim, Bung-Nyun; Kim, Johanna Inhyang; Lee, Young Sik; Min, Kyung Joon; Kim, Hyun-Jin; Lee, Jaewon
2015-01-01
Social network analysis has emerged as a promising tool in modern social psychology. This method can be used to examine friend-based social relationships in terms of network theory, with nodes representing individual students and ties representing relationships between students (e.g., friendships and kinships). Using social network analysis, we investigated whether greater severity of ADHD symptoms is correlated with weaker peer relationships among elementary school students. A total of 562 sixth-graders from two elementary schools (300 males) provided the names of their best friends (maximum 10 names). Their teachers rated each student's ADHD symptoms using an ADHD rating scale. The results showed that 10.2% of the students were at high risk for ADHD. Significant group differences were observed between the high-risk students and other students in two of the three network parameters (degree, centrality and closeness) used to assess friendship quality, with the high-risk group showing significantly lower values of degree and closeness compared to the other students. Moreover, negative correlations were found between the ADHD rating and two social network analysis parameters. Our findings suggest that the severity of ADHD symptoms is strongly correlated with the quality of social and interpersonal relationships in students with ADHD symptoms.
Kim, Jun Won; Kim, Bung-Nyun; Kim, Johanna Inhyang; Lee, Young Sik; Min, Kyung Joon; Kim, Hyun-Jin; Lee, Jaewon
2015-01-01
Introduction Social network analysis has emerged as a promising tool in modern social psychology. This method can be used to examine friend-based social relationships in terms of network theory, with nodes representing individual students and ties representing relationships between students (e.g., friendships and kinships). Using social network analysis, we investigated whether greater severity of ADHD symptoms is correlated with weaker peer relationships among elementary school students. Methods A total of 562 sixth-graders from two elementary schools (300 males) provided the names of their best friends (maximum 10 names). Their teachers rated each student’s ADHD symptoms using an ADHD rating scale. Results The results showed that 10.2% of the students were at high risk for ADHD. Significant group differences were observed between the high-risk students and other students in two of the three network parameters (degree, centrality and closeness) used to assess friendship quality, with the high-risk group showing significantly lower values of degree and closeness compared to the other students. Moreover, negative correlations were found between the ADHD rating and two social network analysis parameters. Conclusion Our findings suggest that the severity of ADHD symptoms is strongly correlated with the quality of social and interpersonal relationships in students with ADHD symptoms. PMID:26562777
Improvement of the insertion axis for cochlear implantation with a robot-based system.
Torres, Renato; Kazmitcheff, Guillaume; De Seta, Daniele; Ferrary, Evelyne; Sterkers, Olivier; Nguyen, Yann
2017-02-01
It has previously reported that alignment of the insertion axis along the basal turn of the cochlea was depending on surgeon' experience. In this experimental study, we assessed technological assistances, such as navigation or a robot-based system, to improve the insertion axis during cochlear implantation. A preoperative cone beam CT and a mastoidectomy with a posterior tympanotomy were performed on four temporal bones. The optimal insertion axis was defined as the closest axis to the scala tympani centerline avoiding the facial nerve. A neuronavigation system, a robot assistance prototype, and software allowing a semi-automated alignment of the robot were used to align an insertion tool with an optimal insertion axis. Four procedures were performed and repeated three times in each temporal bone: manual, manual navigation-assisted, robot-based navigation-assisted, and robot-based semi-automated. The angle between the optimal and the insertion tool axis was measured in the four procedures. The error was 8.3° ± 2.82° for the manual procedure (n = 24), 8.6° ± 2.83° for the manual navigation-assisted procedure (n = 24), 5.4° ± 3.91° for the robot-based navigation-assisted procedure (n = 24), and 3.4° ± 1.56° for the robot-based semi-automated procedure (n = 12). A higher accuracy was observed with the semi-automated robot-based technique than manual and manual navigation-assisted (p < 0.01). Combination of a navigation system and a manual insertion does not improve the alignment accuracy due to the lack of friendly user interface. On the contrary, a semi-automated robot-based system reduces both the error and the variability of the alignment with a defined optimal axis.
NASA Astrophysics Data System (ADS)
Aviles, Angelica I.; Alsaleh, Samar; Sobrevilla, Pilar; Casals, Alicia
2016-03-01
Robotic-Assisted Surgery approach overcomes the limitations of the traditional laparoscopic and open surgeries. However, one of its major limitations is the lack of force feedback. Since there is no direct interaction between the surgeon and the tissue, there is no way of knowing how much force the surgeon is applying which can result in irreversible injuries. The use of force sensors is not practical since they impose different constraints. Thus, we make use of a neuro-visual approach to estimate the applied forces, in which the 3D shape recovery together with the geometry of motion are used as input to a deep network based on LSTM-RNN architecture. When deep networks are used in real time, pre-processing of data is a key factor to reduce complexity and improve the network performance. A common pre-processing step is dimensionality reduction which attempts to eliminate redundant and insignificant information by selecting a subset of relevant features to use in model construction. In this work, we show the effects of dimensionality reduction in a real-time application: estimating the applied force in Robotic-Assisted Surgeries. According to the results, we demonstrated positive effects of doing dimensionality reduction on deep networks including: faster training, improved network performance, and overfitting prevention. We also show a significant accuracy improvement, ranging from about 33% to 86%, over existing approaches related to force estimation.
Santos, Carlos; Espinosa, Felipe; Santiso, Enrique; Mazo, Manuel
2015-05-27
One of the main challenges in wireless cyber-physical systems is to reduce the load of the communication channel while preserving the control performance. In this way, communication resources are liberated for other applications sharing the channel bandwidth. The main contribution of this work is the design of a remote control solution based on an aperiodic and adaptive triggering mechanism considering the current network delay of multiple robotics units. Working with the actual network delay instead of the maximum one leads to abandoning this conservative assumption, since the triggering condition is fixed depending on the current state of the network. This way, the controller manages the usage of the wireless channel in order to reduce the channel delay and to improve the availability of the communication resources. The communication standard under study is the widespread IEEE 802.11g, whose channel delay is clearly uncertain. First, the adaptive self-triggered control is validated through the TrueTime simulation tool configured for the mentioned WiFi standard. Implementation results applying the aperiodic linear control laws on four P3-DX robots are also included. Both of them demonstrate the advantage of this solution in terms of network accessing and control performance with respect to periodic and non-adaptive self-triggered alternatives.
Hitchman, Sara C.; Fong, Geoffrey T.; Zanna, Mark P.; Thrasher, James F.; Chung-Hall, Janet; Siahpush, Mohammad
2014-01-01
Background Smoking rates are higher among low socioeconomic (SES) groups, and there is evidence that inequalities in smoking are widening over time in many countries. Low SES smokers may be more likely to smoke and less likely to quit because smoking is heavily concentrated in their social contexts. This study investigated whether low SES smokers (1) have more smoking friends, and (2) are more likely to gain and less likely to lose smoking friends over time. Correlates of having more smoking friends and gaining or losing smoking friends were also considered. Method Respondents included 6,321 adult current smokers (at recruitment) from Wave 1 (2002) and Wave 2 (2003) of the International Tobacco Control Project (ITC) Four Country Survey, a nationally representative longitudinal cohort survey of smokers in Australia, Canada, UK, and US. Results Low SES smokers reported more smoking friends than moderate and high SES smokers. Low SES smokers were also more likely to gain smoking friends over time compared with high SES smokers. Smokers who were male, younger, and lived with other smokers reported more smoking friends, and were also more likely to gain and less likely to lose smoking friends. Smoking behaviours, such as higher nicotine dependence were related to reporting more smoking friends, but not to losing or gain smoking friends. Conclusions Smoking is highly concentrated in the social networks of lower SES smokers and this concentration may be increasing over time. Cessation interventions should consider how the structure of low SES smokers’ social networks affects quitting. PMID:25156228
The relationships among family, friends, and psychological well-being for Thai elderly.
Thanakwang, Kattika; Ingersoll-Dayton, Berit; Soonthorndhada, Kusol
2012-01-01
The extent to which family and friends contribute to psychological well-being (PWB) may be subject to cultural variability. This study examines the mechanisms by which relationships with family and friends contribute to PWB among Thai elders. Interviews were conducted with 469 men and women aged 60 and older in Nan Province, Thailand. The data were analyzed using structural equation modeling, controlling for age, gender, education, income, marital status, and health status. Family and friendship networks have a significant direct effect on family and friendship support. However, family and friendship networks do not have a significant direct effect on PWB, but rather an indirect effect via social support. Similarly, friendship support mediates the relationship between friendship networks and family support. Both family support and friendship support are significantly related to PWB but family support is the stronger predictor. Using an adapting theoretical framework developed by Berkman, Glass, Brissette, & Seeman (2000) allows researchers to map the various pathways by which relationships with family and friends may contribute to PWB among older Thai adults.
First Annual Workshop on Space Operations Automation and Robotics (SOAR 87)
NASA Technical Reports Server (NTRS)
Griffin, Sandy (Editor)
1987-01-01
Several topics relative to automation and robotics technology are discussed. Automation of checkout, ground support, and logistics; automated software development; man-machine interfaces; neural networks; systems engineering and distributed/parallel processing architectures; and artificial intelligence/expert systems are among the topics covered.
Weidel, Philipp; Djurfeldt, Mikael; Duarte, Renato C; Morrison, Abigail
2016-01-01
In order to properly assess the function and computational properties of simulated neural systems, it is necessary to account for the nature of the stimuli that drive the system. However, providing stimuli that are rich and yet both reproducible and amenable to experimental manipulations is technically challenging, and even more so if a closed-loop scenario is required. In this work, we present a novel approach to solve this problem, connecting robotics and neural network simulators. We implement a middleware solution that bridges the Robotic Operating System (ROS) to the Multi-Simulator Coordinator (MUSIC). This enables any robotic and neural simulators that implement the corresponding interfaces to be efficiently coupled, allowing real-time performance for a wide range of configurations. This work extends the toolset available for researchers in both neurorobotics and computational neuroscience, and creates the opportunity to perform closed-loop experiments of arbitrary complexity to address questions in multiple areas, including embodiment, agency, and reinforcement learning.
Weidel, Philipp; Djurfeldt, Mikael; Duarte, Renato C.; Morrison, Abigail
2016-01-01
In order to properly assess the function and computational properties of simulated neural systems, it is necessary to account for the nature of the stimuli that drive the system. However, providing stimuli that are rich and yet both reproducible and amenable to experimental manipulations is technically challenging, and even more so if a closed-loop scenario is required. In this work, we present a novel approach to solve this problem, connecting robotics and neural network simulators. We implement a middleware solution that bridges the Robotic Operating System (ROS) to the Multi-Simulator Coordinator (MUSIC). This enables any robotic and neural simulators that implement the corresponding interfaces to be efficiently coupled, allowing real-time performance for a wide range of configurations. This work extends the toolset available for researchers in both neurorobotics and computational neuroscience, and creates the opportunity to perform closed-loop experiments of arbitrary complexity to address questions in multiple areas, including embodiment, agency, and reinforcement learning. PMID:27536234
ERIC Educational Resources Information Center
French, Doran C.; Purwono, Urip; Rodkin, Philip
2014-01-01
The objectives of this longitudinal study were to predict the tobacco and alcohol use of Indonesian Muslim adolescents from their religiosity and the substance use of friends and network affiliates. At Year 1, there were 996 participants from eighth grade (n = 507, age = 13.4 years) and 10th grade (n = 489, age = 15.4); 875 were followed into the…
NASA Astrophysics Data System (ADS)
Zhang, Yachu; Zhao, Yuejin; Liu, Ming; Dong, Liquan; Kong, Lingqin; Liu, Lingling
2017-09-01
In contrast to humans, who use only visual information for navigation, many mobile robots use laser scanners and ultrasonic sensors along with vision cameras to navigate. This work proposes a vision-based robot control algorithm based on deep convolutional neural networks. We create a large 15-layer convolutional neural network learning system and achieve the advanced recognition performance. Our system is trained from end to end to map raw input images to direction in supervised mode. The images of data sets are collected in a wide variety of weather conditions and lighting conditions. Besides, the data sets are augmented by adding Gaussian noise and Salt-and-pepper noise to avoid overfitting. The algorithm is verified by two experiments, which are line tracking and obstacle avoidance. The line tracking experiment is proceeded in order to track the desired path which is composed of straight and curved lines. The goal of obstacle avoidance experiment is to avoid the obstacles indoor. Finally, we get 3.29% error rate on the training set and 5.1% error rate on the test set in the line tracking experiment, 1.8% error rate on the training set and less than 5% error rate on the test set in the obstacle avoidance experiment. During the actual test, the robot can follow the runway centerline outdoor and avoid the obstacle in the room accurately. The result confirms the effectiveness of the algorithm and our improvement in the network structure and train parameters
The Infantry Squad: Decisive Force Now and in the Future
2012-01-01
robotic improvements. ●A design that includes the human dimension as a foundation. In the Near Future The vignette that follows describes how the...view the …the truth is, the network needs to be available at the individual soldier level. Robots such as TALON allow warfighters to clear routes...quickly without having to wait for explosive ordnance dis- posal teams. Here a TALON robot inspects a suspected improvised explosive device. (P ho
Cater, Dan; Vyas, Arpita; Vyas, Dinesh
2015-01-01
Colorectal cancer is the second leading cause of mortality in men and women in the United States. While there is a definite advantage regarding the use of colonoscopies in screening, there is still a lack of widespread acceptance of colonoscopy use in the general public. This is evident by the fact that up to 75% of patients diagnosed with colorectal cancer present with locally advanced disease. In order to make colonoscopy and in turn colorectal cancer screening a patient friendly and a comfortable test some changes in tool are necessary. The conventional colonoscope has not changed much since its development. There are several new advances in colorectal screening practices. One of the most promising new advances is the advent of robotic endoscopic techniques. PMID:26380845
Robotic Lunar Landers for Science and Exploration
NASA Technical Reports Server (NTRS)
Cohen, B. A.; Hill, L. A.; Bassler, J. A.; Chavers, D. G.; Hammond, M. S.; Harris, D. W.; Kirby, K. W.; Morse, B. J.; Mulac, B. D.; Reed, C. L. B.
2010-01-01
NASA Marshall Space Flight Center and The Johns Hopkins University Applied Physics Laboratory has been conducting mission studies and performing risk reduction activities for NASA s robotic lunar lander flight projects. In 2005, the Robotic Lunar Exploration Program Mission #2 (RLEP-2) was selected as a Exploration Systems Mission Directorate precursor robotic lunar lander mission to demonstrate precision landing and definitively determine if there was water ice at the lunar poles; however, this project was canceled. Since 2008, the team has been supporting NASA s Science Mission Directorate designing small lunar robotic landers for diverse science missions. The primary emphasis has been to establish anchor nodes of the International Lunar Network (ILN), a network of lunar science stations envisioned to be emplaced by multiple nations. This network would consist of multiple landers carrying instruments to address the geophysical characteristics and evolution of the moon. Additional mission studies have been conducted to support other objectives of the lunar science community and extensive risk reduction design and testing has been performed to advance the design of the lander system and reduce development risk for flight projects. This paper describes the current status of the robotic lunar mission studies that have been conducted by the MSFC/APL Robotic Lunar Lander Development team, including the ILN Anchor Nodes mission. In addition, the results to date of the lunar lander development risk reduction efforts including high pressure propulsion system testing, structure and mechanism development and testing, long cycle time battery testing and combined GN&C and avionics testing will be addressed. The most visible elements of the risk reduction program are two autonomous lander test articles: a compressed air system with limited flight durations and a second version using hydrogen peroxide propellant to achieve significantly longer flight times and the ability to more fully exercise flight sensors and algorithms. Robotic Lunar Lander design and development will have significant feed-forward to other missions to the Moon and, indeed, to other airless bodies such as Mercury, asteroids, and Europa, to which similar science and exploration objectives are applicable.
Ohta, Hidetoshi; Kawashima, Makoto
2014-01-01
A few types of steerable capsule endoscopes have been proposed but disappointingly their systems were not applicable to common endoscopic treatment or pathological diagnosis. This study validates the possibility of treatment and biopsy by using an internet-linked (wireless control via the internet) robotic capsule endoscope (iRoboCap). iRoboCap consisted of three parts: an imaging unit, a movement control unit and a therapeutic tool unit. Two types of iRoboCaps were designed, one was a submarine type (iRoboCap-S) and the other was an amphibious type (iRoboCap-A). They were remotely and wirelessly steered by a portable tablet device using Bluetooth and via the internet. The success rates of biopsy or clipping were evaluated in a phantom. Although the two prototypes have various problems that need improving, we hope that our robotic and wireless innovations have opened the door to new endoscopic procedures and will pioneer various new applications in medicine.
Robot friendly probe and socket assembly
NASA Technical Reports Server (NTRS)
Nyberg, Karen L. (Inventor)
1994-01-01
A probe and socket assembly for serving as a mechanical interface between structures is presented. The assembly comprises a socket having a housing adapted for connection to a first supporting structure and a probe which is readily connectable to a second structure and is designed to be easily grappled and manipulated by a robotic device for insertion and coupling with the socket. Cooperable automatic locking means are provided on the probe shaft and socket housing for automatically locking the probe in the socket when the probe is inserted a predetermined distance. A second cooperable locking means on the probe shaft and housing are adapted for actuation after the probe has been inserted the predetermined distance. Actuation means mounted on the probe and responsive to the grip of the probe handle by a gripping device, such as a robot for conditioning the probe for insertion and are also responsive to release of the grip of the probe handle to actuate the second locking means to provide a hard lock of the probe in the socket.
Navigation of robotic system using cricket motes
NASA Astrophysics Data System (ADS)
Patil, Yogendra J.; Baine, Nicholas A.; Rattan, Kuldip S.
2011-06-01
This paper presents a novel algorithm for self-mapping of the cricket motes that can be used for indoor navigation of autonomous robotic systems. The cricket system is a wireless sensor network that can provide indoor localization service to its user via acoustic ranging techniques. The behavior of the ultrasonic transducer on the cricket mote is studied and the regions where satisfactorily distance measurements can be obtained are recorded. Placing the motes in these regions results fine-grain mapping of the cricket motes. Trilateration is used to obtain a rigid coordinate system, but is insufficient if the network is to be used for navigation. A modified SLAM algorithm is applied to overcome the shortcomings of trilateration. Finally, the self-mapped cricket motes can be used for navigation of autonomous robotic systems in an indoor location.
Parisi, Domenico
2010-01-01
Trying to understand human language by constructing robots that have language necessarily implies an embodied view of language, where the meaning of linguistic expressions is derived from the physical interactions of the organism with the environment. The paper describes a neural model of language according to which the robot's behaviour is controlled by a neural network composed of two sub-networks, one dedicated to the non-linguistic interactions of the robot with the environment and the other one to processing linguistic input and producing linguistic output. We present the results of a number of simulations using the model and we suggest how the model can be used to account for various language-related phenomena such as disambiguation, the metaphorical use of words, the pervasive idiomaticity of multi-word expressions, and mental life as talking to oneself. The model implies a view of the meaning of words and multi-word expressions as a temporal process that takes place in the entire brain and has no clearly defined boundaries. The model can also be extended to emotional words if we assume that an embodied view of language includes not only the interactions of the robot's brain with the external environment but also the interactions of the brain with what is inside the body.
A Typology to Explain Changing Social Networks Post Stroke.
Northcott, Sarah; Hirani, Shashivadan P; Hilari, Katerina
2018-05-08
Social network typologies have been used to classify the general population but have not previously been applied to the stroke population. This study investigated whether social network types remain stable following a stroke, and if not, why some people shift network type. We used a mixed methods design. Participants were recruited from two acute stroke units. They completed the Stroke Social Network Scale (SSNS) two weeks and six months post stroke and in-depth interviews 8-15 months following the stroke. Qualitative data was analysed using Framework Analysis; k-means cluster analysis was applied to the six-month data set. Eighty-seven participants were recruited, 71 were followed up at six months, and 29 completed in-depth interviews. It was possible to classify all 29 participants into one of the following network types both prestroke and post stroke: diverse; friends-based; family-based; restricted-supported; restricted-unsupported. The main shift that took place post stroke was participants moving out of a diverse network into a family-based one. The friends-based network type was relatively stable. Two network types became more populated post stroke: restricted-unsupported and family-based. Triangulatory evidence was provided by k-means cluster analysis, which produced a cluster solution (for n = 71) with comparable characteristics to the network types derived from qualitative analysis. Following a stroke, a person's social network is vulnerable to change. Explanatory factors for shifting network type included the physical and also psychological impact of having a stroke, as well as the tendency to lose contact with friends rather than family.
A Mobile Sensor Network System for Monitoring of Unfriendly Environments.
Song, Guangming; Zhou, Yaoxin; Ding, Fei; Song, Aiguo
2008-11-14
Observing microclimate changes is one of the most popular applications of wireless sensor networks. However, some target environments are often too dangerous or inaccessible to humans or large robots and there are many challenges for deploying and maintaining wireless sensor networks in those unfriendly environments. This paper presents a mobile sensor network system for solving this problem. The system architecture, the mobile node design, the basic behaviors and advanced network capabilities have been investigated respectively. A wheel-based robotic node architecture is proposed here that can add controlled mobility to wireless sensor networks. A testbed including some prototype nodes has also been created for validating the basic functions of the proposed mobile sensor network system. Motion performance tests have been done to get the positioning errors and power consumption model of the mobile nodes. Results of the autonomous deployment experiment show that the mobile nodes can be distributed evenly into the previously unknown environments. It provides powerful support for network deployment and maintenance and can ensure that the sensor network will work properly in unfriendly environments.
Intelligent navigation and accurate positioning of an assist robot in indoor environments
NASA Astrophysics Data System (ADS)
Hua, Bin; Rama, Endri; Capi, Genci; Jindai, Mitsuru; Tsuri, Yosuke
2017-12-01
Intact robot's navigation and accurate positioning in indoor environments are still challenging tasks. Especially in robot applications, assisting disabled and/or elderly people in museums/art gallery environments. In this paper, we present a human-like navigation method, where the neural networks control the wheelchair robot to reach the goal location safely, by imitating the supervisor's motions, and positioning in the intended location. In a museum similar environment, the mobile robot starts navigation from various positions, and uses a low-cost camera to track the target picture, and a laser range finder to make a safe navigation. Results show that the neural controller with the Conjugate Gradient Backpropagation training algorithm gives a robust response to guide the mobile robot accurately to the goal position.
Computer graphics testbed to simulate and test vision systems for space applications
NASA Technical Reports Server (NTRS)
Cheatham, John B.
1991-01-01
Research activity has shifted from computer graphics and vision systems to the broader scope of applying concepts of artificial intelligence to robotics. Specifically, the research is directed toward developing Artificial Neural Networks, Expert Systems, and Laser Imaging Techniques for Autonomous Space Robots.
Parametric motion control of robotic arms: A biologically based approach using neural networks
NASA Technical Reports Server (NTRS)
Bock, O.; D'Eleuterio, G. M. T.; Lipitkas, J.; Grodski, J. J.
1993-01-01
A neural network based system is presented which is able to generate point-to-point movements of robotic manipulators. The foundation of this approach is the use of prototypical control torque signals which are defined by a set of parameters. The parameter set is used for scaling and shaping of these prototypical torque signals to effect a desired outcome of the system. This approach is based on neurophysiological findings that the central nervous system stores generalized cognitive representations of movements called synergies, schemas, or motor programs. It has been proposed that these motor programs may be stored as torque-time functions in central pattern generators which can be scaled with appropriate time and magnitude parameters. The central pattern generators use these parameters to generate stereotypical torque-time profiles, which are then sent to the joint actuators. Hence, only a small number of parameters need to be determined for each point-to-point movement instead of the entire torque-time trajectory. This same principle is implemented for controlling the joint torques of robotic manipulators where a neural network is used to identify the relationship between the task requirements and the torque parameters. Movements are specified by the initial robot position in joint coordinates and the desired final end-effector position in Cartesian coordinates. This information is provided to the neural network which calculates six torque parameters for a two-link system. The prototypical torque profiles (one per joint) are then scaled by those parameters. After appropriate training of the network, our parametric control design allowed the reproduction of a trained set of movements with relatively high accuracy, and the production of previously untrained movements with comparable accuracy. We conclude that our approach was successful in discriminating between trained movements and in generalizing to untrained movements.
Robot Competence Development by Constructive Learning
NASA Astrophysics Data System (ADS)
Meng, Q.; Lee, M. H.; Hinde, C. J.
This paper presents a constructive learning approach for developing sensor-motor mapping in autonomous systems. The system’s adaptation to environment changes is discussed and three methods are proposed to deal with long term and short term changes. The proposed constructive learning allows autonomous systems to develop network topology and adjust network parameters. The approach is supported by findings from psychology and neuroscience especially during infants cognitive development at early stages. A growing radial basis function network is introduced as a computational substrate for sensory-motor mapping learning. Experiments are conducted on a robot eye/hand coordination testbed and results show the incremental development of sensory-motor mapping and its adaptation to changes such as in tool-use.
Robot Competence Development by Constructive Learning
NASA Astrophysics Data System (ADS)
Meng, Q.; Lee, M. H.; Hinde, C. J.
This paper presents a constructive learning approach for developing sensor-motor mapping in autonomous systems. The system's adaptation to environment changes is discussed and three methods are proposed to deal with long term and short term changes. The proposed constructive learning allows autonomous systems to develop network topology and adjust network parameters. The approach is supported by findings from psychology and neuroscience especially during infants cognitive development at early stages. A growing radial basis function network is introduced as a computational substrate for sensory-motor mapping learning. Experiments are conducted on a robot eye/hand coordination testbed and results show the incremental development of sensory-motor mapping and its adaptation to changes such as in tool-use.
NASA Technical Reports Server (NTRS)
Tawel, Raoul (Inventor)
1994-01-01
A method for the rapid learning of nonlinear mappings and topological transformations using a dynamically reconfigurable artificial neural network is presented. This fully-recurrent Adaptive Neuron Model (ANM) network was applied to the highly degenerate inverse kinematics problem in robotics, and its performance evaluation is bench-marked. Once trained, the resulting neuromorphic architecture was implemented in custom analog neural network hardware and the parameters capturing the functional transformation downloaded onto the system. This neuroprocessor, capable of 10(exp 9) ops/sec, was interfaced directly to a three degree of freedom Heathkit robotic manipulator. Calculation of the hardware feed-forward pass for this mapping was benchmarked at approximately 10 microsec.
Multi-function robots with speech interaction and emotion feedback
NASA Astrophysics Data System (ADS)
Wang, Hongyu; Lou, Guanting; Ma, Mengchao
2018-03-01
Nowadays, the service robots have been applied in many public circumstances; however, most of them still don’t have the function of speech interaction, especially the function of speech-emotion interaction feedback. To make the robot more humanoid, Arduino microcontroller was used in this study for the speech recognition module and servo motor control module to achieve the functions of the robot’s speech interaction and emotion feedback. In addition, W5100 was adopted for network connection to achieve information transmission via Internet, providing broad application prospects for the robot in the area of Internet of Things (IoT).
Entangling mobility and interactions in social media.
Grabowicz, Przemyslaw A; Ramasco, José J; Gonçalves, Bruno; Eguíluz, Víctor M
2014-01-01
Daily interactions naturally define social circles. Individuals tend to be friends with the people they spend time with and they choose to spend time with their friends, inextricably entangling physical location and social relationships. As a result, it is possible to predict not only someone's location from their friends' locations but also friendship from spatial and temporal co-occurrence. While several models have been developed to separately describe mobility and the evolution of social networks, there is a lack of studies coupling social interactions and mobility. In this work, we introduce a model that bridges this gap by explicitly considering the feedback of mobility on the formation of social ties. Data coming from three online social networks (Twitter, Gowalla and Brightkite) is used for validation. Our model reproduces various topological and physical properties of the networks not captured by models uncoupling mobility and social interactions such as: i) the total size of the connected components, ii) the distance distribution between connected users, iii) the dependence of the reciprocity on the distance, iv) the variation of the social overlap and the clustering with the distance. Besides numerical simulations, a mean-field approach is also used to study analytically the main statistical features of the networks generated by a simplified version of our model. The robustness of the results to changes in the model parameters is explored, finding that a balance between friend visits and long-range random connections is essential to reproduce the geographical features of the empirical networks.
Olfaction and Hearing Based Mobile Robot Navigation for Odor/Sound Source Search
Song, Kai; Liu, Qi; Wang, Qi
2011-01-01
Bionic technology provides a new elicitation for mobile robot navigation since it explores the way to imitate biological senses. In the present study, the challenging problem was how to fuse different biological senses and guide distributed robots to cooperate with each other for target searching. This paper integrates smell, hearing and touch to design an odor/sound tracking multi-robot system. The olfactory robot tracks the chemical odor plume step by step through information fusion from gas sensors and airflow sensors, while two hearing robots localize the sound source by time delay estimation (TDE) and the geometrical position of microphone array. Furthermore, this paper presents a heading direction based mobile robot navigation algorithm, by which the robot can automatically and stably adjust its velocity and direction according to the deviation between the current heading direction measured by magnetoresistive sensor and the expected heading direction acquired through the odor/sound localization strategies. Simultaneously, one robot can communicate with the other robots via a wireless sensor network (WSN). Experimental results show that the olfactory robot can pinpoint the odor source within the distance of 2 m, while two hearing robots can quickly localize and track the olfactory robot in 2 min. The devised multi-robot system can achieve target search with a considerable success ratio and high stability. PMID:22319401
Jones, Raya A
2017-08-01
Rhetorical moves that construct humanoid robots as social agents disclose tensions at the intersection of science and technology studies (STS) and social robotics. The discourse of robotics often constructs robots that are like us (and therefore unlike dumb artefacts). In the discourse of STS, descriptions of how people assimilate robots into their activities are presented directly or indirectly against the backdrop of actor-network theory, which prompts attributing agency to mundane artefacts. In contradistinction to both social robotics and STS, it is suggested here that to view a capacity to partake in dialogical action (to have a 'voice') is necessary for regarding an artefact as authentically social. The theme is explored partly through a critical reinterpretation of an episode that Morana Alač reported and analysed towards demonstrating her bodies-in-interaction concept. This paper turns to 'body' with particular reference to Gibsonian affordances theory so as to identify the level of analysis at which dialogicality enters social interactions.
The other half of the embodied mind.
Parisi, Domenico
2011-01-01
Embodied theories of mind tend to be theories of the cognitive half of the mind and to ignore its emotional half while a complete theory of the mind should account for both halves. Robots are a new way of expressing theories of the mind which are less ambiguous and more capable to generate specific and non-controversial predictions than verbally expressed theories. We outline a simple robotic model of emotional states as states of a sub-part of the neural network controlling the robot's behavior which has specific properties and which allows the robot to make faster and more correct motivational decisions, and we describe possible extensions of the model to account for social emotional states and for the expression of emotions that, unlike those of current "emotional" robots, are really "felt" by the robot in that they play a well-identified functional role in the robot's behavior.
The Other Half of the Embodied Mind
Parisi, Domenico
2011-01-01
Embodied theories of mind tend to be theories of the cognitive half of the mind and to ignore its emotional half while a complete theory of the mind should account for both halves. Robots are a new way of expressing theories of the mind which are less ambiguous and more capable to generate specific and non-controversial predictions than verbally expressed theories. We outline a simple robotic model of emotional states as states of a sub-part of the neural network controlling the robot's behavior which has specific properties and which allows the robot to make faster and more correct motivational decisions, and we describe possible extensions of the model to account for social emotional states and for the expression of emotions that, unlike those of current “emotional” robots, are really “felt” by the robot in that they play a well-identified functional role in the robot's behavior. PMID:21687441
Huang, Grace C; Unger, Jennifer B; Soto, Daniel; Fujimoto, Kayo; Pentz, Mary Ann; Jordan-Marsh, Maryalice; Valente, Thomas W
2014-05-01
Online social networking sites (SNSs) have become a popular mode of communication among adolescents. However, little is known about the effects of social online activity on health behaviors. The authors examined the use of SNSs among friends and the degree to which SNS activities relate to face-to-face peer influences and adolescent risk behaviors. Longitudinal egocentric friendship network data along with adolescent social media use and risk behaviors were collected from 1,563 10th-grade students across five Southern California high schools. Measures of online and offline peer influences were computed and assessed using fixed-effects models. The frequency of adolescent SNS use and the number of their closest friends on the same SNSs were not significantly associated with risk behaviors. However, exposure to friends' online pictures of partying or drinking was significantly associated with both smoking (β = .11, p < .001) and alcohol use (β = .06, p < .05). Whereas adolescents with drinking friends had higher risk levels for drinking, adolescents without drinking friends were more likely to be affected by higher exposure to risky online pictures (β = -.10, p < .05). Myspace and Facebook had demographically distinct user characteristics and differential effects on risk behaviors. Exposure to risky online content had a direct impact on adolescents' risk behaviors and significantly interacted with risk behaviors of their friends. These results provide evidence that friends' online behaviors should be considered a viable source of peer influence and that increased efforts should focus on educating adolescents on the negative effects of risky online displays. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
Intelligent control of robotic arm/hand systems for the NASA EVA retriever using neural networks
NASA Technical Reports Server (NTRS)
Mclauchlan, Robert A.
1989-01-01
Adaptive/general learning algorithms using varying neural network models are considered for the intelligent control of robotic arm plus dextrous hand/manipulator systems. Results are summarized and discussed for the use of the Barto/Sutton/Anderson neuronlike, unsupervised learning controller as applied to the stabilization of an inverted pendulum on a cart system. Recommendations are made for the application of the controller and a kinematic analysis for trajectory planning to simple object retrieval (chase/approach and capture/grasp) scenarios in two dimensions.
Generalized friendship paradox in complex networks: The case of scientific collaboration
NASA Astrophysics Data System (ADS)
Eom, Young-Ho; Jo, Hang-Hyun
2014-04-01
The friendship paradox states that your friends have on average more friends than you have. Does the paradox ``hold'' for other individual characteristics like income or happiness? To address this question, we generalize the friendship paradox for arbitrary node characteristics in complex networks. By analyzing two coauthorship networks of Physical Review journals and Google Scholar profiles, we find that the generalized friendship paradox (GFP) holds at the individual and network levels for various characteristics, including the number of coauthors, the number of citations, and the number of publications. The origin of the GFP is shown to be rooted in positive correlations between degree and characteristics. As a fruitful application of the GFP, we suggest effective and efficient sampling methods for identifying high characteristic nodes in large-scale networks. Our study on the GFP can shed lights on understanding the interplay between network structure and node characteristics in complex networks.
Generalized friendship paradox in complex networks: The case of scientific collaboration
Eom, Young-Ho; Jo, Hang-Hyun
2014-01-01
The friendship paradox states that your friends have on average more friends than you have. Does the paradox “hold” for other individual characteristics like income or happiness? To address this question, we generalize the friendship paradox for arbitrary node characteristics in complex networks. By analyzing two coauthorship networks of Physical Review journals and Google Scholar profiles, we find that the generalized friendship paradox (GFP) holds at the individual and network levels for various characteristics, including the number of coauthors, the number of citations, and the number of publications. The origin of the GFP is shown to be rooted in positive correlations between degree and characteristics. As a fruitful application of the GFP, we suggest effective and efficient sampling methods for identifying high characteristic nodes in large-scale networks. Our study on the GFP can shed lights on understanding the interplay between network structure and node characteristics in complex networks. PMID:24714092
Peer influence on marijuana use in different types of friendships.
Tucker, Joan S; de la Haye, Kayla; Kennedy, David P; Green, Harold D; Pollard, Michael S
2014-01-01
Although several social network studies have demonstrated peer influence effects on adolescent substance use, findings for marijuana use have been equivocal. This study examines whether structural features of friendships moderate friends' influence on adolescent marijuana use over time. Using 1-year longitudinal data from the National Longitudinal Study of Adolescent Health, this article examines whether three structural features of friendships moderate friends' influence on adolescent marijuana use: whether the friendship is reciprocated, the popularity of the nominated friend, and the popularity/status difference between the nominated friend and the adolescent. The sample consists of students in grade 10/11 at wave I, who were in grade 11/12 at wave II, from two large schools with complete grade-based friendship network data (N = 1,612). In one school, friends' influence on marijuana use was more likely to occur within mutual, reciprocated friendships compared with nonreciprocated relationships. In the other school, friends' influence was stronger when the friends were relatively popular within the school setting or much more popular than the adolescents themselves. Friends' influence on youth marijuana use may play out in different ways, depending on the school context. In one school, influence occurred predominantly within reciprocated relationships that are likely characterized by closeness and trust, whereas in the other school adopting friends' drug use behaviors appeared to be a strategy to attain social status. Further research is needed to better understand the conditions under which structural features of friendships moderate friends' influence on adolescent marijuana use. Copyright © 2014 Society for Adolescent Health and Medicine. All rights reserved.
A Robotic Solution for Assisting People with MCI at Home: Preliminary Tests of the ENRICHME System.
Salatino, Claudia; Pigini, Lucia; Van Kol, Marlies Maria Elisabeth; Gower, Valerio; Andrich, Renzo; Munaro, Giulia; Rosso, Roberto; Castellani, Angelo P; Farina, Elisabetta
2017-01-01
Robots have the potential to support care and independence of older adults. The ENRICHME project is developing an integrated system composed of a robot, sensors and a networking care platform, aiming at assisting older adults with MCI in their home environment. This paper reports findings of the tests performed on a sample of MCI users and their caregivers, with the first version of the ENRICHME system, in a controlled environment.
Survey of Methods and Algorithms of Robot Swarm Aggregation
NASA Astrophysics Data System (ADS)
E Shlyakhov, N.; Vatamaniuk, I. V.; Ronzhin, A. L.
2017-01-01
The paper considers the problem of swarm aggregation of autonomous robots with the use of three methods based on the analogy of the behavior of biological objects. The algorithms substantiating the requirements for hardware realization of sensor, computer and network resources and propulsion devices are presented. Techniques for efficiency estimation of swarm aggregation via space-time characteristics are described. The developed model of the robot swarm reconfiguration into a predetermined three-dimensional shape is presented.
Cyber Moat: Adaptive Virtualized Network Framework for Deception and Disinformation
2016-12-12
As one type of bots, web crawlers have been leveraged by search engines (e.g., Googlebot by Google) to popularize websites through website indexing...However, the number of malicious bots is increasing too. To regulate the behavior of crawlers, most websites include a file called "robots.txt" that...However, "robots.txt" only provides a guideline, and almost all malicious robots ignore it. Moreover, since this file is publicly available, malicious
Biobotic insect swarm based sensor networks for search and rescue
NASA Astrophysics Data System (ADS)
Bozkurt, Alper; Lobaton, Edgar; Sichitiu, Mihail; Hedrick, Tyson; Latif, Tahmid; Dirafzoon, Alireza; Whitmire, Eric; Verderber, Alexander; Marin, Juan; Xiong, Hong
2014-06-01
The potential benefits of distributed robotics systems in applications requiring situational awareness, such as search-and-rescue in emergency situations, are indisputable. The efficiency of such systems requires robotic agents capable of coping with uncertain and dynamic environmental conditions. For example, after an earthquake, a tremendous effort is spent for days to reach to surviving victims where robotic swarms or other distributed robotic systems might play a great role in achieving this faster. However, current technology falls short of offering centimeter scale mobile agents that can function effectively under such conditions. Insects, the inspiration of many robotic swarms, exhibit an unmatched ability to navigate through such environments while successfully maintaining control and stability. We have benefitted from recent developments in neural engineering and neuromuscular stimulation research to fuse the locomotory advantages of insects with the latest developments in wireless networking technologies to enable biobotic insect agents to function as search-and-rescue agents. Our research efforts towards this goal include development of biobot electronic backpack technologies, establishment of biobot tracking testbeds to evaluate locomotion control efficiency, investigation of biobotic control strategies with Gromphadorhina portentosa cockroaches and Manduca sexta moths, establishment of a localization and communication infrastructure, modeling and controlling collective motion by learning deterministic and stochastic motion models, topological motion modeling based on these models, and the development of a swarm robotic platform to be used as a testbed for our algorithms.
Biodegradable and edible gelatine actuators for use as artificial muscles
NASA Astrophysics Data System (ADS)
Chambers, L. D.; Winfield, J.; Ieropoulos, I.; Rossiter, J.
2014-03-01
The expense and use of non-recyclable materials often requires the retrieval and recovery of exploratory robots. Therefore, conventional materials such as plastics and metals in robotics can be limiting. For applications such as environmental monitoring, a fully biodegradable or edible robot may provide the optimum solution. Materials that provide power and actuation as well as biodegradability provide a compelling dimension to future robotic systems. To highlight the potential of novel biodegradable and edible materials as artificial muscles, the actuation of a biodegradable hydrogel was investigated. The fabricated gelatine based polymer gel was inexpensive, easy to handle, biodegradable and edible. The electro-mechanical performance was assessed using two contactless, parallel stainless steel electrodes immersed in 0.1M NaOH solution and fixed 40 mm apart with the strip actuator pinned directly between the electrodes. The actuation displacement in response to a bias voltage was measured over hydration/de-hydration cycles. Long term (11 days) and short term (1 hour) investigations demonstrated the bending behaviour of the swollen material in response to an electric field. Actuation voltage was low (<10 V) resulting in a slow actuation response with large displacement angles (<55 degrees). The stability of the immersed material decreased within the first hour due to swelling, however, was recovered on de-hydrating between actuations. The controlled degradation of biodegradable and edible artificial muscles could help to drive the development of environmentally friendly robotics.
Epidemic spreading on evolving signed networks
NASA Astrophysics Data System (ADS)
Saeedian, M.; Azimi-Tafreshi, N.; Jafari, G. R.; Kertesz, J.
2017-02-01
Most studies of disease spreading consider the underlying social network as obtained without the contagion, though epidemic influences people's willingness to contact others: A "friendly" contact may be turned to "unfriendly" to avoid infection. We study the susceptible-infected disease-spreading model on signed networks, in which each edge is associated with a positive or negative sign representing the friendly or unfriendly relation between its end nodes. In a signed network, according to Heider's theory, edge signs evolve such that finally a state of structural balance is achieved, corresponding to no frustration in physics terms. However, the danger of infection affects the evolution of its edge signs. To describe the coupled problem of the sign evolution and disease spreading, we generalize the notion of structural balance by taking into account the state of the nodes. We introduce an energy function and carry out Monte Carlo simulations on complete networks to test the energy landscape, where we find local minima corresponding to the so-called jammed states. We study the effect of the ratio of initial friendly to unfriendly connections on the propagation of disease. The steady state can be balanced or a jammed state such that a coexistence occurs between susceptible and infected nodes in the system.
Momeni, Naghmeh; Rabbat, Michael
2016-01-01
The friendship paradox is the phenomenon that in social networks, people on average have fewer friends than their friends do. The generalized friendship paradox is an extension to attributes other than the number of friends. The friendship paradox and its generalized version have gathered recent attention due to the information they provide about network structure and local inequalities. In this paper, we propose several measures of nodal qualities which capture different aspects of their activities and influence in online social networks. Using these measures we analyse the prevalence of the generalized friendship paradox over Twitter and we report high levels of prevalence (up to over 90% of nodes). We contend that this prevalence of the friendship paradox and its generalized version arise because of the hierarchical nature of the connections in the network. This hierarchy is nested as opposed to being star-like. We conclude that these paradoxes are collective phenomena not created merely by a minority of well-connected or high-attribute nodes. Moreover, our results show that a large fraction of individuals can experience the generalized friendship paradox even in the absence of a significant correlation between degrees and attributes.
Popularity, similarity, and the network extraversion bias.
Feiler, Daniel C; Kleinbaum, Adam M
2015-05-01
Using the emergent friendship network of an incoming cohort of students in an M.B.A. program, we examined the role of extraversion in shaping social networks. Extraversion has two important implications for the emergence of network ties: a popularity effect, in which extraverts accumulate more friends than introverts do, and a homophily effect, in which the more similar are two people's levels of extraversion, the more likely they are to become friends. These effects result in a systematic network extraversion bias, in which people's social networks will tend to be overpopulated with extraverts and underpopulated with introverts. Moreover, the most extraverted people have the greatest network extraversion bias, and the most introverted people have the least network extraversion bias. Our finding that social networks were systematically misrepresentative of the broader social environment raises questions about whether there is a societal bias toward believing other people are more extraverted than they actually are and whether introverts are better socially calibrated than extraverts. © The Author(s) 2015.
A GPU-accelerated cortical neural network model for visually guided robot navigation.
Beyeler, Michael; Oros, Nicolas; Dutt, Nikil; Krichmar, Jeffrey L
2015-12-01
Humans and other terrestrial animals use vision to traverse novel cluttered environments with apparent ease. On one hand, although much is known about the behavioral dynamics of steering in humans, it remains unclear how relevant perceptual variables might be represented in the brain. On the other hand, although a wealth of data exists about the neural circuitry that is concerned with the perception of self-motion variables such as the current direction of travel, little research has been devoted to investigating how this neural circuitry may relate to active steering control. Here we present a cortical neural network model for visually guided navigation that has been embodied on a physical robot exploring a real-world environment. The model includes a rate based motion energy model for area V1, and a spiking neural network model for cortical area MT. The model generates a cortical representation of optic flow, determines the position of objects based on motion discontinuities, and combines these signals with the representation of a goal location to produce motor commands that successfully steer the robot around obstacles toward the goal. The model produces robot trajectories that closely match human behavioral data. This study demonstrates how neural signals in a model of cortical area MT might provide sufficient motion information to steer a physical robot on human-like paths around obstacles in a real-world environment, and exemplifies the importance of embodiment, as behavior is deeply coupled not only with the underlying model of brain function, but also with the anatomical constraints of the physical body it controls. Copyright © 2015 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Bhasin, Kul; Hayden, Jeffrey L.
2005-01-01
For human and robotic exploration missions in the Vision for Exploration, roadmaps are needed for capability development and investments based on advanced technology developments. A roadmap development process was undertaken for the needed communications, and networking capabilities and technologies for the future human and robotics missions. The underlying processes are derived from work carried out during development of the future space communications architecture, an d NASA's Space Architect Office (SAO) defined formats and structures for accumulating data. Interrelationships were established among emerging requirements, the capability analysis and technology status, and performance data. After developing an architectural communications and networking framework structured around the assumed needs for human and robotic exploration, in the vicinity of Earth, Moon, along the path to Mars, and in the vicinity of Mars, information was gathered from expert participants. This information was used to identify the capabilities expected from the new infrastructure and the technological gaps in the way of obtaining them. We define realistic, long-term space communication architectures based on emerging needs and translate the needs into interfaces, functions, and computer processing that will be required. In developing our roadmapping process, we defined requirements for achieving end-to-end activities that will be carried out by future NASA human and robotic missions. This paper describes: 10 the architectural framework developed for analysis; 2) our approach to gathering and analyzing data from NASA, industry, and academia; 3) an outline of the technology research to be done, including milestones for technology research and demonstrations with timelines; and 4) the technology roadmaps themselves.
NASA Astrophysics Data System (ADS)
Zhou, Changjiu; Meng, Qingchun; Guo, Zhongwen; Qu, Wiefen; Yin, Bo
2002-04-01
Robot learning in unstructured environments has been proved to be an extremely challenging problem, mainly because of many uncertainties always present in the real world. Human beings, on the other hand, seem to cope very well with uncertain and unpredictable environments, often relying on perception-based information. Furthermore, humans beings can also utilize perceptions to guide their learning on those parts of the perception-action space that are actually relevant to the task. Therefore, we conduct a research aimed at improving robot learning through the incorporation of both perception-based and measurement-based information. For this reason, a fuzzy reinforcement learning (FRL) agent is proposed in this paper. Based on a neural-fuzzy architecture, different kinds of information can be incorporated into the FRL agent to initialise its action network, critic network and evaluation feedback module so as to accelerate its learning. By making use of the global optimisation capability of GAs (genetic algorithms), a GA-based FRL (GAFRL) agent is presented to solve the local minima problem in traditional actor-critic reinforcement learning. On the other hand, with the prediction capability of the critic network, GAs can perform a more effective global search. Different GAFRL agents are constructed and verified by using the simulation model of a physical biped robot. The simulation analysis shows that the biped learning rate for dynamic balance can be improved by incorporating perception-based information on biped balancing and walking evaluation. The biped robot can find its application in ocean exploration, detection or sea rescue activity, as well as military maritime activity.
Ha, Jung-Hwa; Hougham, Gavin W; Meltzer, David O
2018-03-02
To examine the prevalence of social isolation among older patients admitted to a hospital, and the effects of sociodemographic and health-related factors on the availability of their family, friends, and neighbor networks. Analyses are based on interviews with a sample of 2,449 older patients admitted to an urban academic medical center in the United States. A nine-item version of Lubben's Social Network Scale was developed and used to assess the availability of different social networks. About 47% of the sample was at risk of social isolation. The oldest old and non-White older adults showed greater risk. The availability of family networks was associated with age, sex, marital status, and prior hospitalization; friend networks with age, race, education, prior hospitalization, and functional limitations; neighbor networks with race, education, marital status, and functional limitations. The risk of social isolation and the availability of social support for hospitalized older adults varies by both patient and network characteristics. Health professionals should attend to this risk and the factors associated with such risk. By assessing the availability of various types and frequency of support among older patients, health professionals can better identify those who may need additional support after discharge. Such information should be used in discharge planning to help prevent unnecessary complications and potential readmission.
User Vulnerability and its Reduction on a Social Networking Site
2014-01-01
social networking sites bring about new...and explore other users’ profiles and friend networks. Social networking sites have reshaped business models [Vayner- chuk 2009], provided platform... social networking sites is to enable users to be more social, user privacy and security issues cannot be ignored. On one hand, most social networking sites
Yoo, Sung Jin; Park, Bong Seok
2017-09-06
This paper addresses a distributed connectivity-preserving synchronized tracking problem of multiple uncertain nonholonomic mobile robots with limited communication ranges. The information of the time-varying leader robot is assumed to be accessible to only a small fraction of follower robots. The main contribution of this paper is to introduce a new distributed nonlinear error surface for dealing with both the synchronized tracking and the preservation of the initial connectivity patterns among nonholonomic robots. Based on this nonlinear error surface, the recursive design methodology is presented to construct the approximation-based local adaptive tracking scheme at the robot dynamic level. Furthermore, a technical lemma is established to analyze the stability and the connectivity preservation of the total closed-loop control system in the Lyapunov sense. An example is provided to illustrate the effectiveness of the proposed methodology.
Towards a Sociological Understanding of Robots as Companions
NASA Astrophysics Data System (ADS)
van Oost, Ellen; Reed, Darren
While Information Communication Technologies (ICTs) have, in the past, primarily mediated or facilitated emotional bonding between humans, contemporary robot technologies are increasingly making the bond between human and robots the core issue. Thinking of robots as companions is not only a development that opens up huge potential for new applications, it also raises social and ethical issues. In this paper we will argue that current conceptions of human-robot companionship are primarily rooted in cognitive psychological traditions and provide important, yet limited understanding of the companion relationship. Elaborating on a sociological perspective on the appropriation of new technology, we will argue for a richer understanding of companionship that takes the situatedness (in location, network and time) of the use-context into account.
NASA Astrophysics Data System (ADS)
Hsu, Roy CHaoming; Jian, Jhih-Wei; Lin, Chih-Chuan; Lai, Chien-Hung; Liu, Cheng-Ting
2013-01-01
The main purpose of this paper is to use machine learning method and Kinect and its body sensation technology to design a simple, convenient, yet effective robot remote control system. In this study, a Kinect sensor is used to capture the human body skeleton with depth information, and a gesture training and identification method is designed using the back propagation neural network to remotely command a mobile robot for certain actions via the Bluetooth. The experimental results show that the designed mobile robots remote control system can achieve, on an average, more than 96% of accurate identification of 7 types of gestures and can effectively control a real e-puck robot for the designed commands.
Calibration of an Outdoor Distributed Camera Network with a 3D Point Cloud
Ortega, Agustín; Silva, Manuel; Teniente, Ernesto H.; Ferreira, Ricardo; Bernardino, Alexandre; Gaspar, José; Andrade-Cetto, Juan
2014-01-01
Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matemàtiques i Estadística (FME) patio at the Universitat Politècnica de Catalunya (UPC). PMID:25076221
Calibration of an outdoor distributed camera network with a 3D point cloud.
Ortega, Agustín; Silva, Manuel; Teniente, Ernesto H; Ferreira, Ricardo; Bernardino, Alexandre; Gaspar, José; Andrade-Cetto, Juan
2014-07-29
Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matemàtiques i Estadística (FME) patio at the Universitat Politècnica de Catalunya (UPC).
Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992
NASA Technical Reports Server (NTRS)
Schenker, Paul S. (Editor)
1992-01-01
Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)
Developing a Telescope Simulator Towards a Global Autonomous Robotic Telescope Network
NASA Astrophysics Data System (ADS)
Giakoumidis, N.; Ioannou, Z.; Dong, H.; Mavridis, N.
2013-05-01
A robotic telescope network is a system that integrates a number of telescopes to observe a variety of astronomical targets without being operated by a human. This system autonomously selects and observes targets in accordance to an optimized target. It dynamically allocates telescope resources depending on the observation requests, specifications of the telescopes, target visibility, meteorological conditions, daylight, location restrictions and availability and many other factors. In this paper, we introduce a telescope simulator, which can control a telescope to a desired position in order to observe a specific object. The system includes a Client Module, a Server Module, and a Dynamic Scheduler module. We make use and integrate a number of open source software to simulate the movement of a robotic telescope, the telescope characteristics, the observational data and weather conditions in order to test and optimize our system.
A Dynamic Model of Adolescent Friendship Networks, Parental Influences, and Smoking.
Lakon, Cynthia M; Wang, Cheng; Butts, Carter T; Jose, Rupa; Timberlake, David S; Hipp, John R
2015-09-01
Peer and parental influences are critical socializing forces shaping adolescent development, including the co-evolving processes of friendship tie choice and adolescent smoking. This study examines aspects of adolescent friendship networks and dimensions of parental influences shaping friendship tie choice and smoking, including parental support, parental monitoring, and the parental home smoking environment using a Stochastic Actor-Based model. With data from three waves of the National Longitudinal Study of Adolescent Health of youth in grades 7 through 12, including the In-School Survey, the first wave of the In-Home survey occurring 6 months later, and the second wave of the In-Home survey, occurring one year later, this study utilizes two samples based on the social network data collected in the longitudinal saturated sample of sixteen schools. One consists of twelve small schools (n = 1,284, 50.93 % female), and the other of one large school (n = 976, 48.46 % female). The findings indicated that reciprocity, choosing a friend of a friend as a friend, and smoking similarity increased friendship tie choice behavior, as did parental support. Parental monitoring interacted with choosing friends who smoke in affecting friendship tie choice, as at higher levels of parental monitoring, youth chose fewer friends that smoked. A parental home smoking context conducive to smoking decreased the number of friends adolescents chose. Peer influence and a parental home smoking environment conducive to smoking increased smoking, while parental monitoring decreased it in the large school. Overall, peer and parental factors affected the coevolution of friendship tie choice and smoking, directly and multiplicatively.
A Dynamic Model of Adolescent Friendship Networks, Parental Influences, and Smoking
Wang, Cheng; Butts, Carter T.; Jose, Rupa; Timberlake, David S.; Hipp, John R.
2015-01-01
Peer and parental influences are critical socializing forces shaping adolescent development, including the co-evolving processes of friendship tie choice and adolescent smoking. This study examines aspects of adolescent friendship networks and dimensions of parental influences shaping friendship tie choice and smoking, including parental support, parental monitoring, and the parental home smoking environment using a Stochastic Actor-Based model. With data from three waves of the National Longitudinal Study of Adolescent Health of youth in grades 7 through 12, including the In-School Survey, the first wave of the In-Home survey occurring 6 months later, and the second wave of the In-Home survey, occurring one year later, this study utilizes two samples based on the social network data collected in the longitudinal saturated sample of sixteen schools. One consists of twelve small schools (n = 1,284, 50.93 % female), and the other of one large school (n = 976, 48.46 % female). The findings indicated that reciprocity, choosing a friend of a friend as a friend, and smoking similarity increased friendship tie choice behavior, as did parental support. Parental monitoring interacted with choosing friends who smoke in affecting friendship tie choice, as at higher levels of parental monitoring, youth chose fewer friends that smoked. A parental home smoking context conducive to smoking decreased the number of friends adolescents chose. Peer influence and a parental home smoking environment conducive to smoking increased smoking, while parental monitoring decreased it in the large school. Overall, peer and parental factors affected the coevolution of friendship tie choice and smoking, directly and multiplicatively. PMID:25239115
Cruz, Jennifer E.; Emery, Robert E.; Turkheimer, Eric
2013-01-01
Research consistently links adolescents' and young adults' drinking with their peers' alcohol intake. In interpreting this correlation, 2 essential questions are often overlooked. First, which peers are more important, best friends or broader social networks? Second, do peers cause increased drinking, or do young people select friends whose drinking habits match their own? The present study combines social network analyses with family (twin and sibling) designs to answer these questions via data from the National Longitudinal Study of Adolescent Health. Analysis of peer nomination data from 134 schools (n = 82,629) and 1,846 twin and sibling pairs shows that peer network substance use predicts changes in drinking from adolescence into young adult life even after controlling for genetic and shared environmental selection, as well as best friend substance use. This effect was particularly strong for high-intensity friendships. Although the peer-adolescent drinking correlation is partially explained by selection, the present finding offers powerful evidence that peers also cause increased drinking. PMID:22390657
Center for Neural Engineering at Tennessee State University, ASSERT Annual Progress Report.
1995-07-01
neural networks . Their research topics are: (1) developing frequency dependent oscillatory neural networks ; (2) long term pontentiation learning rules...as applied to spatial navigation; (3) design and build a servo joint robotic arm and (4) neural network based prothesis control. One graduate student
Orthogonal Patterns In A Binary Neural Network
NASA Technical Reports Server (NTRS)
Baram, Yoram
1991-01-01
Report presents some recent developments in theory of binary neural networks. Subject matter relevant to associate (content-addressable) memories and to recognition of patterns - both of considerable importance in advancement of robotics and artificial intelligence. When probed by any pattern, network converges to one of stored patterns.
Feasibility study of robotic neural controllers
NASA Technical Reports Server (NTRS)
Magana, Mario E.
1990-01-01
The results are given of a feasibility study performed to establish if an artificial neural controller could be used to achieve joint space trajectory tracking of a two-link robot manipulator. The study is based on the results obtained by Hecht-Nielsen, who claims that a functional map can be implemented to a desired degree of accuracy with a three layer feedforward artificial neural network. Central to this study is the assumption that the robot model as well as its parameters values are known.
Rapid Human-Computer Interactive Conceptual Design of Mobile and Manipulative Robot Systems
2015-05-19
algorithm based on Age-Fitness Pareto Optimization (AFPO) ([9]) with an additional user prefer- ence objective and a neural network-based user model, we...greater than 40, which is about 5 times further than any robot traveled in our experiments. 6 3.3 Methods The algorithm uses a client -server computational...architecture. The client here is an interactive pro- gram which takes a pair of controllers as input, simulates4 two copies of the robot with
(abstract) Telecommunications for Mars Rovers and Robotic Missions
NASA Technical Reports Server (NTRS)
Cesarone, Robert J.; Hastrup, Rolf C.; Horne, William; McOmber, Robert
1997-01-01
Telecommunications plays a key role in all rover and robotic missions to Mars both as a conduit for command information to the mission and for scientific data from the mission. Telecommunications to the Earth may be accomplished using direct-to-Earth links via the Deep Space Network (DSN) or by relay links supported by other missions at Mars. This paper reviews current plans for missions to Mars through the 2005 launch opportunity and their capabilities in support of rover and robotic telecommunications.
Neural Network Based Sensory Fusion for Landmark Detection
NASA Technical Reports Server (NTRS)
Kumbla, Kishan -K.; Akbarzadeh, Mohammad R.
1997-01-01
NASA is planning to send numerous unmanned planetary missions to explore the space. This requires autonomous robotic vehicles which can navigate in an unstructured, unknown, and uncertain environment. Landmark based navigation is a new area of research which differs from the traditional goal-oriented navigation, where a mobile robot starts from an initial point and reaches a destination in accordance with a pre-planned path. The landmark based navigation has the advantage of allowing the robot to find its way without communication with the mission control station and without exact knowledge of its coordinates. Current algorithms based on landmark navigation however pose several constraints. First, they require large memories to store the images. Second, the task of comparing the images using traditional methods is computationally intensive and consequently real-time implementation is difficult. The method proposed here consists of three stages, First stage utilizes a heuristic-based algorithm to identify significant objects. The second stage utilizes a neural network (NN) to efficiently classify images of the identified objects. The third stage combines distance information with the classification results of neural networks for efficient and intelligent navigation.
SLAM algorithm applied to robotics assistance for navigation in unknown environments.
Cheein, Fernando A Auat; Lopez, Natalia; Soria, Carlos M; di Sciascio, Fernando A; Pereira, Fernando Lobo; Carelli, Ricardo
2010-02-17
The combination of robotic tools with assistance technology determines a slightly explored area of applications and advantages for disability or elder people in their daily tasks. Autonomous motorized wheelchair navigation inside an environment, behaviour based control of orthopaedic arms or user's preference learning from a friendly interface are some examples of this new field. In this paper, a Simultaneous Localization and Mapping (SLAM) algorithm is implemented to allow the environmental learning by a mobile robot while its navigation is governed by electromyographic signals. The entire system is part autonomous and part user-decision dependent (semi-autonomous). The environmental learning executed by the SLAM algorithm and the low level behaviour-based reactions of the mobile robot are robotic autonomous tasks, whereas the mobile robot navigation inside an environment is commanded by a Muscle-Computer Interface (MCI). In this paper, a sequential Extended Kalman Filter (EKF) feature-based SLAM algorithm is implemented. The features correspond to lines and corners -concave and convex- of the environment. From the SLAM architecture, a global metric map of the environment is derived. The electromyographic signals that command the robot's movements can be adapted to the patient's disabilities. For mobile robot navigation purposes, five commands were obtained from the MCI: turn to the left, turn to the right, stop, start and exit. A kinematic controller to control the mobile robot was implemented. A low level behavior strategy was also implemented to avoid robot's collisions with the environment and moving agents. The entire system was tested in a population of seven volunteers: three elder, two below-elbow amputees and two young normally limbed patients. The experiments were performed within a closed low dynamic environment. Subjects took an average time of 35 minutes to navigate the environment and to learn how to use the MCI. The SLAM results have shown a consistent reconstruction of the environment. The obtained map was stored inside the Muscle-Computer Interface. The integration of a highly demanding processing algorithm (SLAM) with a MCI and the communication between both in real time have shown to be consistent and successful. The metric map generated by the mobile robot would allow possible future autonomous navigation without direct control of the user, whose function could be relegated to choose robot destinations. Also, the mobile robot shares the same kinematic model of a motorized wheelchair. This advantage can be exploited for wheelchair autonomous navigation.
Networking observers and observatories with remote telescope markup language
NASA Astrophysics Data System (ADS)
Hessman, Frederic V.; Tuparev, Georg; Allan, Alasdair
2006-06-01
Remote Telescope Markup Language (RTML) is an XML-based protocol for the transport of the high-level description of a set of observations to be carried out on a remote, robotic or service telescope. We describe how RTML is being used in a wide variety of contexts: the transport of service and robotic observing requests in the Hands-On Universe TM, ACP, eSTAR, and MONET networks; how RTML is easily combined with other XML protocols for more localized control of telescopes; RTML as a secondary observation report format for the IVOA's VOEvent protocol; the input format for a general-purpose observation simulator; and the observatory-independent means for carrying out request transactions for the international Heterogeneous Telescope Network (HTN).
Automation and Robotics for Space-Based Systems, 1991
NASA Technical Reports Server (NTRS)
Williams, Robert L., II (Editor)
1992-01-01
The purpose of this in-house workshop was to assess the state-of-the-art of automation and robotics for space operations from an LaRC perspective and to identify areas of opportunity for future research. Over half of the presentations came from the Automation Technology Branch, covering telerobotic control, extravehicular activity (EVA) and intra-vehicular activity (IVA) robotics, hand controllers for teleoperation, sensors, neural networks, and automated structural assembly, all applied to space missions. Other talks covered the Remote Manipulator System (RMS) active damping augmentation, space crane work, modeling, simulation, and control of large, flexible space manipulators, and virtual passive controller designs for space robots.
Igarashi, Tasuku; Yoshida, Toshikazu
2003-10-01
This longitudinal study investigated the extent to which the use of mobile phone text messages, including e-mail and short message service, affected freshmen's loneliness during the transition to college. A total of 83 freshmen completed measures of loneliness and social network at the beginning and end of their first semester. Perceived utility of mobile phone text messages was assessed at the beginning of the semester. Results showed that perceived functional usefulness and affiliation fulfillment of text messages affected formation of social network during the period. It was found that the higher the functional usefulness, the larger increase in the number of messages to college friends, and the higher the affiliation fulfillment, the less important the text messages to pre-college friends. Furthermore, it was noted that the more important the relationship with pre-college and college friends that was not dependent on text messages, and the fewer messages to pre-college friends, the less the loneliness. In contrast, greater importance of text messages to pre-college friends was associated with an increase in loneliness.
Shin, Huiyoung; Ryan, Allison M
2014-11-01
This study investigated early adolescent friendship selection and social influence with regard to academic motivation (self-efficacy and intrinsic value), engagement (effortful and disruptive behavior), and achievement (GPA calculated from report card grades) among 6th graders (N = 587, 50% girls at Wave 1; N = 576, 52% girls at Wave 2) followed from fall to spring within 1 academic year. A stochastic actor-based model of social network analysis was used to overcome methodological limitations of prior research on friends, peer groups, and academic adjustment. Evidence that early adolescents sought out friends who were similar to themselves (selection) was found in regard to academic self-efficacy, and a similar trend was found for achievement. Evidence that friends became more similar to their friends over time (influence) was found for all aspects of academic adjustment except academic self-efficacy. Collectively, results indicate that selection effects were not as pervasive as influence effects in explaining similarity among friends in academic adjustment. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
Zhang, Jie; Wei, Shimin; Ayres, David W; Smith, Harold T; Tse, Francis L S
2011-09-01
Although it is well known that automation can provide significant improvement in the efficiency of biological sample preparation in quantitative LC-MS/MS analysis, it has not been widely implemented in bioanalytical laboratories throughout the industry. This can be attributed to the lack of a sound strategy and practical procedures in working with robotic liquid-handling systems. Several comprehensive automation assisted procedures for biological sample preparation and method validation were developed and qualified using two types of Hamilton Microlab liquid-handling robots. The procedures developed were generic, user-friendly and covered the majority of steps involved in routine sample preparation and method validation. Generic automation procedures were established as a practical approach to widely implement automation into the routine bioanalysis of samples in support of drug-development programs.
Using Robots and Contract Learning to Teach Cyber-Physical Systems to Undergraduates
ERIC Educational Resources Information Center
Crenshaw, T. L. A.
2013-01-01
Cyber-physical systems are a genre of networked real-time systems that monitor and control the physical world. Examples include unmanned aerial vehicles and industrial robotics. The experts who develop these complex systems are retiring much faster than universities are graduating engineering majors. As a result, it is important for undergraduates…
Heterogeneous Associations of Second-Graders' Learning in Robotics Class
ERIC Educational Resources Information Center
Cho, Eunji; Lee, Kyunghwa; Cherniak, Shara; Jung, Sung Eun
2017-01-01
Drawing on Latour's (Reassembling the social: an introduction to actor--network-theory, Oxford University Press, New York, 2005), this manuscript discusses a study of a robotics class in a public, Title I elementary school. Compared with theoretical frameworks (e.g., constructivism and constructionism) dominant in the field of early childhood…
A bio-inspired auditory perception model for amplitude-frequency clustering (keynote Paper)
NASA Astrophysics Data System (ADS)
Arena, Paolo; Fortuna, Luigi; Frasca, Mattia; Ganci, Gaetana; Patane, Luca
2005-06-01
In this paper a model for auditory perception is introduced. This model is based on a network of integrate-and-fire and resonate-and-fire neurons and is aimed to control the phonotaxis behavior of a roving robot. The starting point is the model of phonotaxis in Gryllus Bimaculatus: the model consists of four integrate-and-fire neurons and is able of discriminating the calling song of male cricket and orienting the robot towards the sound source. This paper aims to extend the model to include an amplitude-frequency clustering. The proposed spiking network shows different behaviors associated with different characteristics of the input signals (amplitude and frequency). The behavior implemented on the robot is similar to the cricket behavior, where some frequencies are associated with the calling song of male crickets, while other ones indicate the presence of predators. Therefore, the whole model for auditory perception is devoted to control different responses (attractive or repulsive) depending on the input characteristics. The performance of the control system has been evaluated with several experiments carried out on a roving robot.
Cardiac ultrasonography over 4G wireless networks using a tele-operated robot
Panayides, Andreas S.; Jossif, Antonis P.; Christoforou, Eftychios G.; Vieyres, Pierre; Novales, Cyril; Voskarides, Sotos; Pattichis, Constantinos S.
2016-01-01
This Letter proposes an end-to-end mobile tele-echography platform using a portable robot for remote cardiac ultrasonography. Performance evaluation investigates the capacity of long-term evolution (LTE) wireless networks to facilitate responsive robot tele-manipulation and real-time ultrasound video streaming that qualifies for clinical practice. Within this context, a thorough video coding standards comparison for cardiac ultrasound applications is performed, using a data set of ten ultrasound videos. Both objective and subjective (clinical) video quality assessment demonstrate that H.264/AVC and high efficiency video coding standards can achieve diagnostically-lossless video quality at bitrates well within the LTE supported data rates. Most importantly, reduced latencies experienced throughout the live tele-echography sessions allow the medical expert to remotely operate the robot in a responsive manner, using the wirelessly communicated cardiac ultrasound video to reach a diagnosis. Based on preliminary results documented in this Letter, the proposed robotised tele-echography platform can provide for reliable, remote diagnosis, achieving comparable quality of experience levels with in-hospital ultrasound examinations. PMID:27733929
Kim, Ha Yeon; Yang, Sung Phil; Park, Gyu Lee; Kim, Eun Joo; You, Joshua Sung Hyun
2016-01-01
Robot-assisted and treadmill-gait training are promising neurorehabilitation techniques, with advantages over conventional gait training, but the neural substrates underpinning locomotor control remain unknown particularly during different gait training modes and speeds. The present optical imaging study compared cortical activities during conventional stepping walking (SW), treadmill walking (TW), and robot-assisted walking (RW) at different speeds. Fourteen healthy subjects (6 women, mean age 30.06, years ± 4.53) completed three walking training modes (SW, TW, and RW) at various speeds (self-selected, 1.5, 2.0, 2.5, and 3.0 km/h). A functional near-infrared spectroscopy (fNIRS) system determined cerebral hemodynamic changes associated with cortical locomotor network areas in the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), prefrontal cortex (PFC), and sensory association cortex (SAC). There was increased cortical activation in the SMC, PMC, and SMA during different walking training modes. More global locomotor network activation was observed during RW than TW or SW. As walking speed increased, multiple locomotor network activations were observed, and increased activation power spectrum. This is the first empirical evidence highlighting the neural substrates mediating dynamic locomotion for different gait training modes and speeds. Fast, robot-assisted gait training best facilitated cortical activation associated with locomotor control.
Design and Implementation of Sound Searching Robots in Wireless Sensor Networks
Han, Lianfu; Shen, Zhengguang; Fu, Changfeng; Liu, Chao
2016-01-01
A sound target-searching robot system which includes a 4-channel microphone array for sound collection, magneto-resistive sensor for declination measurement, and a wireless sensor networks (WSN) for exchanging information is described. It has an embedded sound signal enhancement, recognition and location method, and a sound searching strategy based on a digital signal processor (DSP). As the wireless network nodes, three robots comprise the WSN a personal computer (PC) in order to search the three different sound targets in task-oriented collaboration. The improved spectral subtraction method is used for noise reduction. As the feature of audio signal, Mel-frequency cepstral coefficient (MFCC) is extracted. Based on the K-nearest neighbor classification method, we match the trained feature template to recognize sound signal type. This paper utilizes the improved generalized cross correlation method to estimate time delay of arrival (TDOA), and then employs spherical-interpolation for sound location according to the TDOA and the geometrical position of the microphone array. A new mapping has been proposed to direct the motor to search sound targets flexibly. As the sink node, the PC receives and displays the result processed in the WSN, and it also has the ultimate power to make decision on the received results in order to improve their accuracy. The experiment results show that the designed three-robot system implements sound target searching function without collisions and performs well. PMID:27657088
Design and Implementation of Sound Searching Robots in Wireless Sensor Networks.
Han, Lianfu; Shen, Zhengguang; Fu, Changfeng; Liu, Chao
2016-09-21
A sound target-searching robot system which includes a 4-channel microphone array for sound collection, magneto-resistive sensor for declination measurement, and a wireless sensor networks (WSN) for exchanging information is described. It has an embedded sound signal enhancement, recognition and location method, and a sound searching strategy based on a digital signal processor (DSP). As the wireless network nodes, three robots comprise the WSN a personal computer (PC) in order to search the three different sound targets in task-oriented collaboration. The improved spectral subtraction method is used for noise reduction. As the feature of audio signal, Mel-frequency cepstral coefficient (MFCC) is extracted. Based on the K-nearest neighbor classification method, we match the trained feature template to recognize sound signal type. This paper utilizes the improved generalized cross correlation method to estimate time delay of arrival (TDOA), and then employs spherical-interpolation for sound location according to the TDOA and the geometrical position of the microphone array. A new mapping has been proposed to direct the motor to search sound targets flexibly. As the sink node, the PC receives and displays the result processed in the WSN, and it also has the ultimate power to make decision on the received results in order to improve their accuracy. The experiment results show that the designed three-robot system implements sound target searching function without collisions and performs well.
ERIC Educational Resources Information Center
Fortuin, Janna; van Geel, Mitch; Vedder, Paul
2016-01-01
The present study was conducted to analyze whether in-class friends influence each other's grades, and whether adolescents tend to select friends that are similar to them in terms of academic achievement. During 1 academic year, 542 eighth-grade students (M age = 13.3 years) reported on 3 different occasions on their in-class friendship networks.…
Alcohol peer influence of participating in organized school activities: a network approach.
Fujimoto, Kayo; Valente, Thomas W
2013-10-01
This study compares the network influences on adolescent substance use from peers who coparticipated in school-sponsored organized activities (affiliation-based peer influence) with the influence both from their "nominated" friends (i.e., the adolescent named the alter as a friend), and only "reciprocated" friends (i.e., both adolescents mutually named each other as friends). The study also attempts to parse affiliation-based peer influence into the influence of both activity members who are also friends and those who are not, to address the potential confounding of these sources of peer influence. The study data consisted of a nationally representative sample of 12,551 adolescents in Grades 7-12 within 106 schools from the Add Health data. Ordinal logistic regression was conducted to estimate the effects of affiliation-based and friends influence on alcohol use and drinking frequency. Peer influence via organized activities (sports or clubs) with drinkers and the influence of friends who drink had significant effects on adolescent drinking. Peer influence through club activities with drinkers had a stronger effect on any drinking behavior than through sports activities with drinkers. After decomposing peer influence through activities by friendship status, influence through sport activities had a significant effect on drinking only when coparticipant drinkers were also reciprocated friends (but not nominated friends), whereas influence through club activities had a significant effect on drinking, regardless of friendship reciprocation. The design and implementation of school based substance use prevention and treatment programs should consider the contextual effects of school-sponsored activities. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
Alcohol Peer Influence of Participating in Organized School Activities: A Network Approach
Valente, Thomas W.
2014-01-01
Objective This study compares the network influences on adolescent substance use from peers who co-participated in school-sponsored organized activities (affiliation-based peer influence) with the influence both from their “nominated” friends (i.e., the adolescent named the alter as a friend), and only “reciprocated” friends (i.e., both adolescents mutually named each other as friends). The study also attempts to parse affiliation-based peer influence into the influence of both activity members who are also friends, and those who are not, to address the potential confounding of these sources of peer influence. Methods The study data consisted of a nationally representative sample of 12,551 adolescents in Grades 7–12 within 106 schools from the Add Health data. Ordinal logistic regression was conducted to estimate the effects of affiliation-based and friends influence on alcohol use and drinking frequency. Results Peer influence via organized activities (sports or clubs) with drinkers and the influence of friends who drink had significant effects on adolescent drinking. Peer influence through club activities with drinkers had a stronger effect on any drinking behavior than through sports activities with drinkers. After decomposing peer influence through activities by friendship status, influence through sport activities had a significant effect on drinking only when co-participant drinkers were also “reciprocated” friends (but not “nominated” friends), whereas influence through club activities had a significant effect on drinking, regardless of friendship reciprocation. Conclusions The design and implementation of school based substance use prevention and treatment programs should consider the contextual effects of school-sponsored activities. PMID:22924449
Solace in solidarity: Disability friendship networks buffer well-being.
Silverman, Arielle M; Molton, Ivan R; Smith, Amanda E; Jensen, Mark P; Cohen, Geoffrey L
2017-11-01
To determine whether having friends who share one's disability experiences is associated with higher well-being, and whether these friendships buffer well-being from disability-related stressors. Research Method/Design: In 2 cross-sectional studies, adults with long-term physical disabilities identified close friends who shared their diagnosis. We assessed well-being as a function of the number of friends that participants identified in each group. Study 1 included 71 adults with legal blindness living in the United States, while Study 2 included 1,453 adults in the United States with either muscular dystrophy (MD), multiple sclerosis (MS), post-polio syndrome (PPS), or spinal cord injury (SCI). In Study 1, having more friends sharing a blindness diagnosis was associated with higher life satisfaction, even controlling for the number of friends who were not blind. In Study 2, Participants with more friends sharing their diagnosis reported higher quality of life and satisfaction with social role participation. Participants with more friends sharing their diagnosis also showed and attenuated associations between the severity of their functional impairment and their quality of life and social role satisfaction, suggesting that their friendships buffered the impact of their functional impairment on well-being. Participants reporting more friends with any physical disability showed similar benefits. Friends with disabilities can offer uniquely important informational and emotional support resources that buffer the impact of a functional impairment on well-being. Psychosocial interventions should help people with long-term disabilities build their peer support networks. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
NASA Astrophysics Data System (ADS)
Naharudin, N.; Ahamad, M. S. S.; Sadullah, A. F. M.
2017-10-01
Every transit trip begins and ends with pedestrian travel. People need to walk to access the transit services. However, their choice to walk depends on many factors including the connectivity, level of comfort and safety. These factors can influence the pleasantness of riding the transit itself, especially during the first/last mile (FLM) journey. This had triggered few studies attempting to measure the pedestrian-friendliness a walking environment can offer. There were studies that implement the pedestrian experience on walking to assess the pedestrian-friendliness of a walking environment. There were also studies that use spatial analysis to measure it based on the path connectivity and accessibility to public facilities and amenities. Though both are good, but the perception-based studies and spatial analysis can be combined to derive more holistic results. This paper proposes a framework for selecting a pedestrian-friendly path for the FLM transit journey by using the two techniques (perception-based and spatial analysis). First, the degree of importance for the factors influencing a good walking environment will be aggregated by using Analytical Network Process (ANP) decision rules based on people's preferences on those factors. The weight will then be used as attributes in the GIS network analysis. Next, the network analysis will be performed to find a pedestrian-friendly walking route based on the priorities aggregated by ANP. It will choose routes passing through the preferred attributes accordingly. The final output is a map showing pedestrian-friendly walking path for the FLM transit journey.
Social Relationships and Allostatic Load in the MIDUS Study
Brooks, Kathryn P.; Gruenwald, Tara; Karlamanga, Arun; Hu, Peifung; Koretz, Brandon; Seeman, Teresa E.
2014-01-01
OBJECTIVE This study examines how the social environment is related to allostatic load (AL), a multi-system index of biological risk. METHODS A national sample of adults (N = 949) aged 34-84 rated their relationships with spouse, family, and friends at two time points 10 years apart. At the second time point, participants completed a biological protocol in which indices of autonomic, hypothalamic-pituitary-adrenal axis, cardiovascular, inflammatory, and metabolic function were obtained and used to create an AL summary score. Generalized estimating equations were used to examine the associations among three aspects of social relationships – social support, social negativity, and frequency of social contact – and AL. RESULTS Higher levels of spouse negativity, family negativity, friend contact, and network level contact were each associated with higher AL, and higher levels of spouse support were associated with lower AL, independent of age, sociodemographic factors, and health covariates. Tests for age interactions suggested that friend support and network support were each associated with higher AL among older adults, but at younger ages there appeared to be no association between friend support and AL and a negative association between network support and AL. For network negativity, there was a marginal interaction such that network negativity was associated with higher AL among younger adults but there was no association among older adults. CONCLUSIONS These findings demonstrate that structural and functional aspects of the social environment are associated with AL, and extend previous work by demonstrating that these associations vary based on the type of relationship assessed and by age. PMID:24447186
Takahashi, Yoshimitsu; Uchida, Chiyoko; Miyaki, Koichi; Sakai, Michi; Shimbo, Takuro; Nakayama, Takeo
2009-07-23
Internet peer support groups for depression are becoming popular and could be affected by an increasing number of social network services (SNSs). However, little is known about participant characteristics, social relationships in SNSs, and the reasons for usage. In addition, the effects of SNS participation on people with depression are rather unknown. The aim was to explore the potential benefits and harms of an SNS for depression based on a concurrent triangulation design of mixed methods strategy, including qualitative content analysis and social network analysis. A cross-sectional Internet survey of participants, which involved the collection of SNS log files and a questionnaire, was conducted in an SNS for people with self-reported depressive tendencies in Japan in 2007. Quantitative data, which included user demographics, depressive state, and assessment of the SNS (positive vs not positive), were statistically analyzed. Descriptive contents of responses to open-ended questions concerning advantages and disadvantages of SNS participation were analyzed using the inductive approach of qualitative content analysis. Contents were organized into codes, concepts, categories, and a storyline based on the grounded theory approach. Social relationships, derived from data of "friends," were analyzed using social network analysis, in which network measures and the extent of interpersonal association were calculated based on the social network theory. Each analysis and integration of results were performed through a concurrent triangulation design of mixed methods strategy. There were 105 participants. Median age was 36 years, and 51% (36/71) were male. There were 37 valid respondents; their number of friends and frequency of accessing the SNS were significantly higher than for invalid/nonrespondents (P = .008 and P = .003). Among respondents, 90% (28/31) were mildly, moderately, or severely depressed. Assessment of the SNS was performed by determining the access frequency of the SNS and the number of friends. Qualitative content analysis indicated that user-selectable peer support could be passive, active, and/or interactive based on anonymity or ease of use, and there was the potential harm of a downward depressive spiral triggered by aggravated psychological burden. Social network analysis revealed that users communicated one-on-one with each other or in small groups (five people or less). A downward depressive spiral was related to friends who were moderately or severely depressed and friends with negative assessment of the SNS. An SNS for people with depressive tendencies provides various opportunities to obtain support that meets users' needs. To avoid a downward depressive spiral, we recommend that participants do not use SNSs when they feel that the SNS is not user-selectable, when they get egocentric comments, when friends have a negative assessment of the SNS, or when they have additional psychological burden.
3D printing of soft-matter to open a new era of soft-matter MEMS/robotics (Conference Presentation)
NASA Astrophysics Data System (ADS)
Furukawa, Hidemitsu
2017-04-01
3D printing technology is becoming useful and applicable by the progress of information and communication technology (ICT). It means 3D printer is a kind of useful robot for additive manufacturing and is controlled by computer with human-friendly software. Once user starts to use 3D printing of soft-matter, one can immediately understand computer-aided design (CAD) and engineering (CAE) technology will be more important and applicable for soft-matter systems. User can easily design soft-matter objects and 3D-print them. User can easily apply 3D-printed soft-matter objects to develop new research and application on MEMS and robotics. Here we introduce the recent progress of 3D printing (i.e. additive manufacturing), especially focusing on our 3D gel printing. We are trying to develop new advanced research and applications of 3D gel printer, including GEL-MECHANICS, GEL-PHOTONICS, and GEL-ROBOTICS. In the gel-mechanics, we are developing new gel materials for mechanical engineering. Some gels have high-mechanical strength and shape memory properties. In the gel-photonics. We are applying our original characterizing system, named `Scanning Microscopic Light Scattering (SMILS)', to analyze 3D printed gel materials. In the gel-robotics, we focus on 3D printing of soft parts for soft-robotics made form gel materials, like gel finger. Also we are challenging to apply 3D gel printing to start new company, to innovate new businesses in county side, and to create new 3D-printed foods.
Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots.
Duarte, Miguel; Costa, Vasco; Gomes, Jorge; Rodrigues, Tiago; Silva, Fernando; Oliveira, Sancho Moura; Christensen, Anders Lyhne
2016-01-01
Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers.
Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots
Duarte, Miguel; Costa, Vasco; Gomes, Jorge; Rodrigues, Tiago; Silva, Fernando; Oliveira, Sancho Moura; Christensen, Anders Lyhne
2016-01-01
Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers. PMID:26999614
To friend or not to friend: the use of social media in clinical oncology.
Wiener, Lori; Crum, Caroline; Grady, Christine; Merchant, Melinda
2012-03-01
Online social networking has replaced more traditional methods of personal and professional communication in many segments of society today. The wide reach and immediacy of social media facilitate dissemination of knowledge in advocacy and cancer education, but the usefulness of social media in personal relationships between patients and providers is still unclear. Although professional guidelines regarding e-mail communication may be relevant to social media, the inherent openness in social networks creates potential boundary and privacy issues in the provider-patient context. This commentary seeks to increase provider awareness of unique issues and challenges raised by the integration of social networking into oncology communications.
Structural diversity effect on hashtag adoption in Twitter
NASA Astrophysics Data System (ADS)
Zhang, Aihua; Zheng, Mingxing; Pang, Bowen
2018-03-01
With online social network developing rapidly these years, user' behavior in online social network has attracted a lot of attentions to it. In this paper, we study Twitter user's behavior of hashtag adoption from the perspective of social contagion and focus on "structure diversity" effect on individual's behavior in Twitter. We achieve data through Twitter's API by crawling and build a users' network to carry on empirical research. The Girvan-Newman (G-N) algorithm is used to analyze the structural diversity of user's ego network, and Logistic regression model is adopted to examine the hypothesis. The findings of our empirical study indicate that user' behavior in online social network is indeed influenced by his friends and his decision is significantly affected by the number of groups that these friends belong to, which we call structural diversity.
Leverage Between the Buffering Effect and the Bystander Effect in Social Networking.
Chiu, Yu-Ping; Chang, Shu-Chen
2015-08-01
This study examined encouraged and inhibited social feedback behaviors based on the theories of the buffering effect and the bystander effect. A system program was used to collect personal data and social feedback from a Facebook data set to test the research model. The results revealed that the buffering effect induced a positive relationship between social network size and feedback gained from friends when people's social network size was under a certain cognitive constraint. For people with a social network size that exceeds this cognitive constraint, the bystander effect may occur, in which having more friends may inhibit social feedback. In this study, two social psychological theories were applied to explain social feedback behavior on Facebook, and it was determined that social network size and social feedback exhibited no consistent linear relationship.
Social networks and links to isolation and loneliness among elderly HCBS clients.
Medvene, Louis J; Nilsen, Kari M; Smith, Rachel; Ofei-Dodoo, Samuel; DiLollo, Anthony; Webster, Noah; Graham, Annette; Nance, Anita
2016-01-01
The purpose of this study was to explore the network types of HCBS clients based on the structural characteristics of their social networks. We also examined how the network types were associated with social isolation, relationship quality and loneliness. Forty personal interviews were carried out with HCBS clients to assess the structure of their social networks as indicated by frequency of contact with children, friends, family and participation in religious and community organizations. Hierarchical cluster analysis was conducted to identify network types. Four network types were found including: family (n = 16), diverse (n = 8), restricted (n = 8) and religious (n = 7). Family members comprised almost half of participants' social networks, and friends comprised less than one-third. Clients embedded in family, diverse and religious networks had significantly more positive relationships than clients embedded in restricted networks. Clients embedded in restricted networks had significantly higher social isolation scores and were lonelier than clients in diverse and family networks. The findings suggest that HCBS clients' isolation and loneliness are linked to the types of social networks in which they are embedded. The findings also suggest that clients embedded in restricted networks are at high risk for negative outcomes.
Cracking the egg: virtual embryogenesis of real robots.
Cussat-Blanc, Sylvain; Pollack, Jordan
2014-01-01
All multicellular living beings are created from a single cell. A developmental process, called embryogenesis, takes this first fertilized cell down a complex path of reproduction, migration, and specialization into a complex organism adapted to its environment. In most cases, the first steps of the embryogenesis take place in a protected environment such as in an egg or in utero. Starting from this observation, we propose a new approach to the generation of real robots, strongly inspired by living systems. Our robots are composed of tens of specialized cells, grown from a single cell using a bio-inspired virtual developmental process. Virtual cells, controlled by gene regulatory networks, divide, migrate, and specialize to produce the robot's body plan (morphology), and then the robot is manually built from this plan. Because the robot is as easy to assemble as Lego, the building process could be easily automated.
Nocchi, Federico; Gazzellini, Simone; Grisolia, Carmela; Petrarca, Maurizio; Cannatà, Vittorio; Cappa, Paolo; D'Alessio, Tommaso; Castelli, Enrico
2012-07-24
The potential of robot-mediated therapy and virtual reality in neurorehabilitation is becoming of increasing importance. However, there is limited information, using neuroimaging, on the neural networks involved in training with these technologies. This study was intended to detect the brain network involved in the visual processing of movement during robotic training. The main aim was to investigate the existence of a common cerebral network able to assimilate biological (human upper limb) and non-biological (abstract object) movements, hence testing the suitability of the visual non-biological feedback provided by the InMotion2 Robot. A visual functional Magnetic Resonance Imaging (fMRI) task was administered to 22 healthy subjects. The task required observation and retrieval of motor gestures and of the visual feedback used in robotic training. Functional activations of both biological and non-biological movements were examined to identify areas activated in both conditions, along with differential activity in upper limb vs. abstract object trials. Control of response was also tested by administering trials with congruent and incongruent reaching movements. The observation of upper limb and abstract object movements elicited similar patterns of activations according to a caudo-rostral pathway for the visual processing of movements (including specific areas of the occipital, temporal, parietal, and frontal lobes). Similarly, overlapping activations were found for the subsequent retrieval of the observed movement. Furthermore, activations of frontal cortical areas were associated with congruent trials more than with the incongruent ones. This study identified the neural pathway associated with visual processing of movement stimuli used in upper limb robot-mediated training and investigated the brain's ability to assimilate abstract object movements with human motor gestures. In both conditions, activations were elicited in cerebral areas involved in visual perception, sensory integration, recognition of movement, re-mapping on the somatosensory and motor cortex, storage in memory, and response control. Results from the congruent vs. incongruent trials revealed greater activity for the former condition than the latter in a network including cingulate cortex, right inferior and middle frontal gyrus that are involved in the go-signal and in decision control. Results on healthy subjects would suggest the appropriateness of an abstract visual feedback provided during motor training. The task contributes to highlight the potential of fMRI in improving the understanding of visual motor processes and may also be useful in detecting brain reorganisation during training.
MIT-Skywalker: On the use of a markerless system.
Goncalves, Rogerio S; Hamilton, Taya; Krebs, Hermano I
2017-07-01
This paper describes our efforts to employ the Microsoft Kinect as a low cost vision control system for the MIT-Skywalker, a robotic gait rehabilitation device. The Kinect enables an alternative markerless solution to control the MIT-Skywalker and allows a more user-friendly set-up. A study involving eight healthy subjects and two stroke survivors using the MIT-Skywalker device demonstrates the advantages and challenges of this new proposed approach.
Kelly, John F; Stout, Robert L; Greene, M Claire; Slaymaker, Valerie
2014-01-01
Social factors play a key role in addiction recovery. Research with adults indicates individuals with substance use disorder (SUD) benefit from mutual-help organizations (MHOs), such as Alcoholics Anonymous, via their ability to facilitate adaptive network changes. Given the lower prevalence of sobriety-conducive, and sobriety-supportive, social contexts in the general population during the life-stage of young adulthood, however, 12-step MHOs may play an even more crucial recovery-supportive social role for young adults, but have not been investigated. Greater knowledge could enhance understanding of recovery-related change and inform young adults' continuing care recommendations. Emerging adults (N = 302; 18-24 yrs; 26% female; 95% White) enrolled in a study of residential treatment effectiveness were assessed at intake, 1, 3, 6, and 12 months on 12-step attendance, peer network variables ("high [relapse] risk" and "low [relapse] risk" friends), and treatment outcomes (Percent Days Abstinent; Percent Days Heavy Drinking). Hierarchical linear models tested for change in social risk over time and lagged mediational analyses tested whether 12-step attendance conferred recovery benefits via change in social risk. High-risk friends were common at treatment entry, but decreased during follow-up; low-risk friends increased. Contrary to predictions, while substantial recovery-supportive friend network changes were observed, this was unrelated to 12-step participation and, thus, not found to mediate its positive influence on outcome. Young adult 12-step participation confers recovery benefit; yet, while encouraging social network change, 12-step MHOs may be less able to provide social network change directly for young adults, perhaps because similar-aged peers are less common in MHOs. Findings highlight the importance of both social networks and 12-step MHOs and raise further questions as to how young adults benefit from 12-step MHOs.
Yue, Shigang; Rind, F Claire
2006-05-01
The lobula giant movement detector (LGMD) is an identified neuron in the locust brain that responds most strongly to the images of an approaching object such as a predator. Its computational model can cope with unpredictable environments without using specific object recognition algorithms. In this paper, an LGMD-based neural network is proposed with a new feature enhancement mechanism to enhance the expanded edges of colliding objects via grouped excitation for collision detection with complex backgrounds. The isolated excitation caused by background detail will be filtered out by the new mechanism. Offline tests demonstrated the advantages of the presented LGMD-based neural network in complex backgrounds. Real time robotics experiments using the LGMD-based neural network as the only sensory system showed that the system worked reliably in a wide range of conditions; in particular, the robot was able to navigate in arenas with structured surrounds and complex backgrounds.
A telerobotic digital controller system
NASA Technical Reports Server (NTRS)
Brown, Richard J.
1992-01-01
This system is a network of joint mounted dual axes digital servo-controllers (DDSC), providing control of various joints and end effectors of different robotic systems. This report provides description of and user required information for the Digital Controller System Network (DSCN) and, in particular, the DDSC, Model DDSC-2, developed to perform the controller functions. The DDSC can control 3 phase brushless or brush type DC motors, requiring up to 8 amps. Only four wires, two for power and 2 for serial communication, are required, except for local sensor and motor connections. This highly capable, very flexible, programmable servo-controller, contained on a single, compact printed circuit board measuring only 4.5 x 5.1 inches, is applicable to control systems of all types from sub-arc second precision pointing to control of robotic joints and end effectors. This document concentrates on the robotic applications for the DDSC.
Towards multi-platform software architecture for Collaborative Teleoperation
NASA Astrophysics Data System (ADS)
Domingues, Christophe; Otmane, Samir; Davesne, Frederic; Mallem, Malik
2009-03-01
Augmented Reality (AR) can provide to a Human Operator (HO) a real help in achieving complex tasks, such as remote control of robots and cooperative teleassistance. Using appropriate augmentations, the HO can interact faster, safer and easier with the remote real world. In this paper, we present an extension of an existing distributed software and network architecture for collaborative teleoperation based on networked human-scaled mixed reality and mobile platform. The first teleoperation system was composed by a VR application and a Web application. However the 2 systems cannot be used together and it is impossible to control a distant robot simultaneously. Our goal is to update the teleoperation system to permit a heterogeneous collaborative teleoperation between the 2 platforms. An important feature of this interface is based on the use of different Virtual Reality platforms and different Mobile platforms to control one or many robots.
Optimizing Double-Network Hydrogel for Biomedical Soft Robots.
Banerjee, Hritwick; Ren, Hongliang
2017-09-01
Double-network hydrogel with standardized chemical parameters demonstrates a reasonable and viable alternative to silicone in soft robotic fabrication due to its biocompatibility, comparable mechanical properties, and customizability through the alterations of key variables. The most viable hydrogel sample in our article shows tensile strain of 851% and maximum tensile strength of 0.273 MPa. The elasticity and strength range of this hydrogel can be customized according to application requirements by simple alterations in the recipe. Furthermore, we incorporated Agar/PAM hydrogel into our highly constrained soft pneumatic actuator (SPA) design and eventually produced SPAs with escalated capabilities, such as larger range of motion, higher force output, and power efficiency. Incorporating SPAs made of Agar/PAM hydrogel resulted in low viscosity, thermos-reversibility, and ultralow elasticity, which we believe can help to combine with the other functions of hydrogel, tailoring a better solution for fabricating biocompatible soft robots.
Cortical Spiking Network Interfaced with Virtual Musculoskeletal Arm and Robotic Arm.
Dura-Bernal, Salvador; Zhou, Xianlian; Neymotin, Samuel A; Przekwas, Andrzej; Francis, Joseph T; Lytton, William W
2015-01-01
Embedding computational models in the physical world is a critical step towards constraining their behavior and building practical applications. Here we aim to drive a realistic musculoskeletal arm model using a biomimetic cortical spiking model, and make a robot arm reproduce the same trajectories in real time. Our cortical model consisted of a 3-layered cortex, composed of several hundred spiking model-neurons, which display physiologically realistic dynamics. We interconnected the cortical model to a two-joint musculoskeletal model of a human arm, with realistic anatomical and biomechanical properties. The virtual arm received muscle excitations from the neuronal model, and fed back proprioceptive information, forming a closed-loop system. The cortical model was trained using spike timing-dependent reinforcement learning to drive the virtual arm in a 2D reaching task. Limb position was used to simultaneously control a robot arm using an improved network interface. Virtual arm muscle activations responded to motoneuron firing rates, with virtual arm muscles lengths encoded via population coding in the proprioceptive population. After training, the virtual arm performed reaching movements which were smoother and more realistic than those obtained using a simplistic arm model. This system provided access to both spiking network properties and to arm biophysical properties, including muscle forces. The use of a musculoskeletal virtual arm and the improved control system allowed the robot arm to perform movements which were smoother than those reported in our previous paper using a simplistic arm. This work provides a novel approach consisting of bidirectionally connecting a cortical model to a realistic virtual arm, and using the system output to drive a robotic arm in real time. Our techniques are applicable to the future development of brain neuroprosthetic control systems, and may enable enhanced brain-machine interfaces with the possibility for finer control of limb prosthetics.
LCOGT: A World-Wide Network of Robotic Telescopes
NASA Astrophysics Data System (ADS)
Brown, T.
2013-05-01
Las Cumbres Observatory Global Telescope (LCOGT) is an organization dedicated to time-domain astronomy. To carry out the necessary observations in fields such as supernovae, extrasolar planets, small solar-system bodies, and pulsating stars, we have developed and are now deploying a set of robotic optical telescopes at sites around the globe. In this talk I will concentrate on the core of this network, consisting of up to 15 identical 1m telescopes deployed across multiple sites in both the northern and southern hemispheres. I will summarize the technical and performance aspect of these telescopes, including both their imaging and their anticipated spectroscopic capabilities. But I will also delve into the network organization, including communication among telescopes (to assure that observations are properly carried out), interactions among the institutions and scientists who will use the network (to optimize the scientific returns), and our funding model (which until now has relied entirely on one private donor, but will soon require funding from outside sources, if the full potential of the network is to be achieved).
ERIC Educational Resources Information Center
Pennington, Natalie
2013-01-01
This research examined how various members of a social network interact with the Facebook (FB) profile page of a friend who has died. From 43 in-depth qualitative interviews, FB friends of deceased FB users maintained their FB connection with the deceased. Most participants who visited the profile found it helpful to look at pictures; a few wrote…
Optimal social-networking strategy is a function of socioeconomic conditions.
Oishi, Shigehiro; Kesebir, Selin
2012-12-01
In the two studies reported here, we examined the relation among residential mobility, economic conditions, and optimal social-networking strategy. In study 1, a computer simulation showed that regardless of economic conditions, having a broad social network with weak friendship ties is advantageous when friends are likely to move away. By contrast, having a small social network with deep friendship ties is advantageous when the economy is unstable but friends are not likely to move away. In study 2, we examined the validity of the computer simulation using a sample of American adults. Results were consistent with the simulation: American adults living in a zip code where people are residentially stable but economically challenged were happier if they had a narrow but deep social network, whereas in other socioeconomic conditions, people were generally happier if they had a broad but shallow networking strategy. Together, our studies demonstrate that the optimal social-networking strategy varies as a function of socioeconomic conditions.
Self-organization via active exploration in robotic applications. Phase 2: Hybrid hardware prototype
NASA Technical Reports Server (NTRS)
Oegmen, Haluk
1993-01-01
In many environments human-like intelligent behavior is required from robots to assist and/or replace human operators. The purpose of these robots is to reduce human time and effort in various tasks. Thus the robot should be robust and as autonomous as possible in order to eliminate or to keep to a strict minimum its maintenance and external control. Such requirements lead to the following properties: fault tolerance, self organization, and intelligence. A good insight into implementing these properties in a robot can be gained by considering human behavior. In the first phase of this project, a neural network architecture was developed that captures some fundamental aspects of human categorization, habit, novelty, and reinforcement behavior. The model, called FRONTAL, is a 'cognitive unit' regulating the exploratory behavior of the robot. In the second phase of the project, FRONTAL was interfaced with an off-the-shelf robotic arm and a real-time vision system. The components of this robotic system, a review of FRONTAL, and simulation studies are presented in this report.
The Structure, Design, and Closed-Loop Motion Control of a Differential Drive Soft Robot.
Wu, Pang; Jiangbei, Wang; Yanqiong, Fei
2018-02-01
This article presents the structure, design, and motion control of an inchworm inspired pneumatic soft robot, which can perform differential movement. This robot mainly consists of two columns of pneumatic multi-airbags (actuators), one sensor, one baseboard, front feet, and rear feet. According to the different inflation time of left and right actuators, the robot can perform both linear and turning movements. The actuators of this robot are composed of multiple airbags, and the design of the airbags is analyzed. To deal with the nonlinear performance of the soft robot, we use radial basis function neural networks to train the turning ability of this robot on three different surfaces and create a mathematical model among coefficient of friction, deflection angle, and inflation time. Then, we establish the closed-loop automatic control model using three-axis electronic compass sensor. Finally, the automatic control model is verified by linear and turning movement experiments. According to the experiment, the robot can finish the linear and turning movements under the closed-loop control system.
Too Many Friends: Social Integration, Network Cohesion and Adolescent Depressive Symptoms
ERIC Educational Resources Information Center
Falci, Christina; McNeely, Clea
2009-01-01
Using a nationally representative sample of adolescents, we examine associations among social integration (network size), network cohesion (alter-density), perceptions of social relationships (e.g., social support) and adolescent depressive symptoms. We find that adolescents with either too large or too small a network have higher levels of…
DANGEROUS LIAISONS? DATING AND DRINKING DIFFUSION IN ADOLESCENT PEER NETWORKS*
Kreager, Derek A.; Haynie, Dana L.
2014-01-01
The onset and escalation of alcohol consumption and romantic relationships are hallmarks of adolescence, yet only recently have these domains jointly been the focus of sociological inquiry. We extend this literature by connecting alcohol use, dating and peers to understand the diffusion of drinking behavior in school-based friendship networks. Drawing on Granovetter’s classic concept of weak ties, we argue that adolescent romantic partners are likely to be network bridges, or liaisons, connecting daters to new peer contexts which, in turn, promote changes in individual drinking behaviors and allow these behaviors to spread across peer networks. Using longitudinal data of 459 couples from the National Longitudinal Study of Adolescent Health, we estimate Actor-Partner Interdependence Models and identify the unique contributions of partners’ drinking, friends’ drinking, and friends-of-partners’ drinking to daters’ own future binge drinking and drinking frequency. Findings support the liaison hypothesis and suggest that friends-of-partners’ drinking have net associations with adolescent drinking patterns. Moreover, the coefficient for friends-of-partners drinking is larger than the coefficient for one’s own peers and generally immune to prior selection. Our findings suggest that romantic relationships are important mechanisms for understanding the diffusion of emergent problem behaviors in adolescent peer networks. PMID:25328162
A 61-million-person experiment in social influence and political mobilization
Bond, Robert M.; Fariss, Christopher J.; Jones, Jason J.; Kramer, Adam D. I.; Marlow, Cameron; Settle, Jaime E.; Fowler, James H.
2013-01-01
Human behaviour is thought to spread through face-to-face social networks, but it is difficult to identify social influence effects in observational studies9–13, and it is unknown whether online social networks operate in the same way14–19. Here we report results from a randomized controlled trial of political mobilization messages delivered to 61 million Facebook users during the 2010 US congressional elections. The results show that the messages directly influenced political self-expression, information seeking and real-world voting behaviour of millions of people. Furthermore, the messages not only influenced the users who received them but also the users’ friends, and friends of friends. The effect of social transmission on real-world voting was greater than the direct effect of the messages themselves, and nearly all the transmission occurred between ‘close friends’ who were more likely to have a face-to-face relationship. These results suggest that strong ties are instrumental for spreading both online and real-world behaviour in human social networks. PMID:22972300
NASA Technical Reports Server (NTRS)
Thakoor, Anil
1990-01-01
Viewgraphs on electronic neural networks for space station are presented. Topics covered include: electronic neural networks; electronic implementations; VLSI/thin film hybrid hardware for neurocomputing; computations with analog parallel processing; features of neuroprocessors; applications of neuroprocessors; neural network hardware for terrain trafficability determination; a dedicated processor for path planning; neural network system interface; neural network for robotic control; error backpropagation algorithm for learning; resource allocation matrix; global optimization neuroprocessor; and electrically programmable read only thin-film synaptic array.
75 FR 55392 - Employment Network Report Card
Federal Register 2010, 2011, 2012, 2013, 2014
2010-09-10
... SOCIAL SECURITY ADMINISTRATION [Docket No. SSA-2010-0046] Employment Network Report Card AGENCY... quality assurance, including a ticket consumer Employment Network Report Card. SUMMARY: We are soliciting... this goal by combining a user-friendly EN Report Card, which contains customer satisfaction feedback...
Robot, computer problem solving system
NASA Technical Reports Server (NTRS)
Becker, J. D.; Merriam, E. W.
1973-01-01
The TENEX computer system, the ARPA network, and computer language design technology was applied to support the complex system programs. By combining the pragmatic and theoretical aspects of robot development, an approach is created which is grounded in realism, but which also has at its disposal the power that comes from looking at complex problems from an abstract analytical point of view.
An Embedded Systems Laboratory to Support Rapid Prototyping of Robotics and the Internet of Things
ERIC Educational Resources Information Center
Hamblen, J. O.; van Bekkum, G. M. E.
2013-01-01
This paper describes a new approach for a course and laboratory designed to allow students to develop low-cost prototypes of robotic and other embedded devices that feature Internet connectivity, I/O, networking, a real-time operating system (RTOS), and object-oriented C/C++. The application programming interface (API) libraries provided permit…
Fernandez Y-Garcia, Erik; Duberstein, Paul; Paterniti, Debora A; Cipri, Camille S; Kravitz, Richard L; Epstein, Ronald M
2012-06-29
Family and friends may help patients seek out and engage in depression care. However, patients' social networks can also undermine depression treatment and recovery. In an effort to improve depression care in primary care settings, we sought to identify, categorize, and alert primary care clinicians to depression-related messages that patients hear from friends and family that patients perceive as unhelpful or detrimental. We conducted 15 focus groups in 3 cities. Participants (n = 116) with a personal history or knowledge of depression responded to open-ended questions about depression, including self-perceived barriers to care-seeking. Focus group conversations were audio-recorded and analyzed using iterative qualitative analysis. Four themes emerged related to negatively-received depression messages delivered by family and friends. Specifically, participants perceived these messages as making them feel labeled, judged, lectured to, and rejected by family and friends when discussing depression. Some participants also expressed their interpretation of their families' motivations for delivering the messages and described how hearing these messages affected depression care. The richness of our results reflects the complexity of communication within depression sufferers' social networks around this stigmatized issue. To leverage patients' social support networks effectively in depression care, primary care clinicians should be aware of both the potentially beneficial and detrimental aspects of social support. Specifically, clinicians should consider using open-ended queries into patients' experiences with discussing depression with family and friends as an initial step in the process. An open-ended approach may avoid future emotional trauma or stigmatization and assist patients in overcoming self-imposed barriers to depression discussion, symptom disclosure, treatment adherence and follow-up care.
2012-01-01
Background Family and friends may help patients seek out and engage in depression care. However, patients’ social networks can also undermine depression treatment and recovery. In an effort to improve depression care in primary care settings, we sought to identify, categorize, and alert primary care clinicians to depression-related messages that patients hear from friends and family that patients perceive as unhelpful or detrimental. Methods We conducted 15 focus groups in 3 cities. Participants (n = 116) with a personal history or knowledge of depression responded to open-ended questions about depression, including self-perceived barriers to care-seeking. Focus group conversations were audio-recorded and analyzed using iterative qualitative analysis. Results Four themes emerged related to negatively-received depression messages delivered by family and friends. Specifically, participants perceived these messages as making them feel labeled, judged, lectured to, and rejected by family and friends when discussing depression. Some participants also expressed their interpretation of their families’ motivations for delivering the messages and described how hearing these messages affected depression care. Conclusions The richness of our results reflects the complexity of communication within depression sufferers’ social networks around this stigmatized issue. To leverage patients’ social support networks effectively in depression care, primary care clinicians should be aware of both the potentially beneficial and detrimental aspects of social support. Specifically, clinicians should consider using open-ended queries into patients’ experiences with discussing depression with family and friends as an initial step in the process. An open-ended approach may avoid future emotional trauma or stigmatization and assist patients in overcoming self-imposed barriers to depression discussion, symptom disclosure, treatment adherence and follow-up care. PMID:22747989
Path planning on cellular nonlinear network using active wave computing technique
NASA Astrophysics Data System (ADS)
Yeniçeri, Ramazan; Yalçın, Müstak E.
2009-05-01
This paper introduces a simple algorithm to solve robot path finding problem using active wave computing techniques. A two-dimensional Cellular Neural/Nonlinear Network (CNN), consist of relaxation oscillators, has been used to generate active waves and to process the visual information. The network, which has been implemented on a Field Programmable Gate Array (FPGA) chip, has the feature of being programmed, controlled and observed by a host computer. The arena of the robot is modelled as the medium of the active waves on the network. Active waves are employed to cover the whole medium with their own dynamics, by starting from an initial point. The proposed algorithm is achieved by observing the motion of the wave-front of the active waves. Host program first loads the arena model onto the active wave generator network and command to start the generation. Then periodically pulls the network image from the generator hardware to analyze evolution of the active waves. When the algorithm is completed, vectorial data image is generated. The path from any of the pixel on this image to the active wave generating pixel is drawn by the vectors on this image. The robot arena may be a complicated labyrinth or may have a simple geometry. But, the arena surface always must be flat. Our Autowave Generator CNN implementation which is settled on the Xilinx University Program Virtex-II Pro Development System is operated by a MATLAB program running on the host computer. As the active wave generator hardware has 16, 384 neurons, an arena with 128 × 128 pixels can be modeled and solved by the algorithm. The system also has a monitor and network image is depicted on the monitor simultaneously.
Collaborative Planning of Robotic Exploration
NASA Technical Reports Server (NTRS)
Norris, Jeffrey; Backes, Paul; Powell, Mark; Vona, Marsette; Steinke, Robert
2004-01-01
The Science Activity Planner (SAP) software system includes an uplink-planning component, which enables collaborative planning of activities to be undertaken by an exploratory robot on a remote planet or on Earth. Included in the uplink-planning component is the SAP-Uplink Browser, which enables users to load multiple spacecraft activity plans into a single window, compare them, and merge them. The uplink-planning component includes a subcomponent that implements the Rover Markup Language Activity Planning format (RML-AP), based on the Extensible Markup Language (XML) format that enables the representation, within a single document, of planned spacecraft and robotic activities together with the scientific reasons for the activities. Each such document is highly parseable and can be validated easily. Another subcomponent of the uplink-planning component is the Activity Dictionary Markup Language (ADML), which eliminates the need for two mission activity dictionaries - one in a human-readable format and one in a machine-readable format. Style sheets that have been developed along with the ADML format enable users to edit one dictionary in a user-friendly environment without compromising
Parasuraman, Ramviyas; Fabry, Thomas; Molinari, Luca; Kershaw, Keith; Di Castro, Mario; Masi, Alessandro; Ferre, Manuel
2014-12-12
The reliability of wireless communication in a network of mobile wireless robot nodes depends on the received radio signal strength (RSS). When the robot nodes are deployed in hostile environments with ionizing radiations (such as in some scientific facilities), there is a possibility that some electronic components may fail randomly (due to radiation effects), which causes problems in wireless connectivity. The objective of this paper is to maximize robot mission capabilities by maximizing the wireless network capacity and to reduce the risk of communication failure. Thus, in this paper, we consider a multi-node wireless tethering structure called the "server-relay-client" framework that uses (multiple) relay nodes in between a server and a client node. We propose a robust stochastic optimization (RSO) algorithm using a multi-sensor-based RSS sampling method at the relay nodes to efficiently improve and balance the RSS between the source and client nodes to improve the network capacity and to provide redundant networking abilities. We use pre-processing techniques, such as exponential moving averaging and spatial averaging filters on the RSS data for smoothing. We apply a receiver spatial diversity concept and employ a position controller on the relay node using a stochastic gradient ascent method for self-positioning the relay node to achieve the RSS balancing task. The effectiveness of the proposed solution is validated by extensive simulations and field experiments in CERN facilities. For the field trials, we used a youBot mobile robot platform as the relay node, and two stand-alone Raspberry Pi computers as the client and server nodes. The algorithm has been proven to be robust to noise in the radio signals and to work effectively even under non-line-of-sight conditions.
Parasuraman, Ramviyas; Fabry, Thomas; Molinari, Luca; Kershaw, Keith; Di Castro, Mario; Masi, Alessandro; Ferre, Manuel
2014-01-01
The reliability of wireless communication in a network of mobile wireless robot nodes depends on the received radio signal strength (RSS). When the robot nodes are deployed in hostile environments with ionizing radiations (such as in some scientific facilities), there is a possibility that some electronic components may fail randomly (due to radiation effects), which causes problems in wireless connectivity. The objective of this paper is to maximize robot mission capabilities by maximizing the wireless network capacity and to reduce the risk of communication failure. Thus, in this paper, we consider a multi-node wireless tethering structure called the “server-relay-client” framework that uses (multiple) relay nodes in between a server and a client node. We propose a robust stochastic optimization (RSO) algorithm using a multi-sensor-based RSS sampling method at the relay nodes to efficiently improve and balance the RSS between the source and client nodes to improve the network capacity and to provide redundant networking abilities. We use pre-processing techniques, such as exponential moving averaging and spatial averaging filters on the RSS data for smoothing. We apply a receiver spatial diversity concept and employ a position controller on the relay node using a stochastic gradient ascent method for self-positioning the relay node to achieve the RSS balancing task. The effectiveness of the proposed solution is validated by extensive simulations and field experiments in CERN facilities. For the field trials, we used a youBot mobile robot platform as the relay node, and two stand-alone Raspberry Pi computers as the client and server nodes. The algorithm has been proven to be robust to noise in the radio signals and to work effectively even under non-line-of-sight conditions. PMID:25615734
Self-organization via active exploration in robotic applications
NASA Technical Reports Server (NTRS)
Ogmen, H.; Prakash, R. V.
1992-01-01
We describe a neural network based robotic system. Unlike traditional robotic systems, our approach focussed on non-stationary problems. We indicate that self-organization capability is necessary for any system to operate successfully in a non-stationary environment. We suggest that self-organization should be based on an active exploration process. We investigated neural architectures having novelty sensitivity, selective attention, reinforcement learning, habit formation, flexible criteria categorization properties and analyzed the resulting behavior (consisting of an intelligent initiation of exploration) by computer simulations. While various computer vision researchers acknowledged recently the importance of active processes (Swain and Stricker, 1991), the proposed approaches within the new framework still suffer from a lack of self-organization (Aloimonos and Bandyopadhyay, 1987; Bajcsy, 1988). A self-organizing, neural network based robot (MAVIN) has been recently proposed (Baloch and Waxman, 1991). This robot has the capability of position, size rotation invariant pattern categorization, recognition and pavlovian conditioning. Our robot does not have initially invariant processing properties. The reason for this is the emphasis we put on active exploration. We maintain the point of view that such invariant properties emerge from an internalization of exploratory sensory-motor activity. Rather than coding the equilibria of such mental capabilities, we are seeking to capture its dynamics to understand on the one hand how the emergence of such invariances is possible and on the other hand the dynamics that lead to these invariances. The second point is crucial for an adaptive robot to acquire new invariances in non-stationary environments, as demonstrated by the inverting glass experiments of Helmholtz. We will introduce Pavlovian conditioning circuits in our future work for the precise objective of achieving the generation, coordination, and internalization of sequence of actions.
FOCU:S--future operator control unit: soldier
NASA Astrophysics Data System (ADS)
O'Brien, Barry J.; Karan, Cem; Young, Stuart H.
2009-05-01
The U.S. Army Research Laboratory's (ARL) Computational and Information Sciences Directorate (CISD) has long been involved in autonomous asset control, specifically as it relates to small robots. Over the past year, CISD has been making strides in the implementation of three areas of small robot autonomy, namely platform autonomy, Soldier-robot interface, and tactical behaviors. It is CISD's belief that these three areas must be considered as a whole in order to provide Soldiers with useful capabilities. In addressing the Soldier-robot interface aspect, CISD has begun development on a unique dismounted controller called the Future Operator Control Unit: Soldier (FOCU:S) that is based on an Apple iPod Touch. The iPod Touch's small form factor, unique touch-screen input device, and the presence of general purpose computing applications such as a web browser combine to give this device the potential to be a disruptive technology. Setting CISD's implementation apart from other similar iPod or iPhone-based devices is the ARL software that allows multiple robotic platforms to be controlled from a single OCU. The FOCU:S uses the same Agile Computing Infrastructure (ACI) that all other assets in the ARL robotic control system use, enabling automated asset discovery on any type of network. Further, a custom ad hoc routing implementation allows the FOCU:S to communicate with the ARL ad hoc communications system and enables it to extend the range of the network. This paper will briefly describe the current robotic control architecture employed by ARL and provide short descriptions of existing capabilities. Further, the paper will discuss FOCU:S specific software developed for the iPod Touch, including unique capabilities enabled by the device's unique hardware.
Falotico, Egidio; Vannucci, Lorenzo; Ambrosano, Alessandro; Albanese, Ugo; Ulbrich, Stefan; Vasquez Tieck, Juan Camilo; Hinkel, Georg; Kaiser, Jacques; Peric, Igor; Denninger, Oliver; Cauli, Nino; Kirtay, Murat; Roennau, Arne; Klinker, Gudrun; Von Arnim, Axel; Guyot, Luc; Peppicelli, Daniel; Martínez-Cañada, Pablo; Ros, Eduardo; Maier, Patrick; Weber, Sandro; Huber, Manuel; Plecher, David; Röhrbein, Florian; Deser, Stefan; Roitberg, Alina; van der Smagt, Patrick; Dillman, Rüdiger; Levi, Paul; Laschi, Cecilia; Knoll, Alois C.; Gewaltig, Marc-Oliver
2017-01-01
Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task. Rather, the embodiment has to be simulated as well. While adequate tools exist to simulate either complex neural networks or robots and their environments, there is so far no tool that allows to easily establish a communication between brain and body models. The Neurorobotics Platform is a new web-based environment that aims to fill this gap by offering scientists and technology developers a software infrastructure allowing them to connect brain models to detailed simulations of robot bodies and environments and to use the resulting neurorobotic systems for in silico experimentation. In order to simplify the workflow and reduce the level of the required programming skills, the platform provides editors for the specification of experimental sequences and conditions, environments, robots, and brain–body connectors. In addition to that, a variety of existing robots and environments are provided. This work presents the architecture of the first release of the Neurorobotics Platform developed in subproject 10 “Neurorobotics” of the Human Brain Project (HBP).1 At the current state, the Neurorobotics Platform allows researchers to design and run basic experiments in neurorobotics using simulated robots and simulated environments linked to simplified versions of brain models. We illustrate the capabilities of the platform with three example experiments: a Braitenberg task implemented on a mobile robot, a sensory-motor learning task based on a robotic controller, and a visual tracking embedding a retina model on the iCub humanoid robot. These use-cases allow to assess the applicability of the Neurorobotics Platform for robotic tasks as well as in neuroscientific experiments. PMID:28179882
Falotico, Egidio; Vannucci, Lorenzo; Ambrosano, Alessandro; Albanese, Ugo; Ulbrich, Stefan; Vasquez Tieck, Juan Camilo; Hinkel, Georg; Kaiser, Jacques; Peric, Igor; Denninger, Oliver; Cauli, Nino; Kirtay, Murat; Roennau, Arne; Klinker, Gudrun; Von Arnim, Axel; Guyot, Luc; Peppicelli, Daniel; Martínez-Cañada, Pablo; Ros, Eduardo; Maier, Patrick; Weber, Sandro; Huber, Manuel; Plecher, David; Röhrbein, Florian; Deser, Stefan; Roitberg, Alina; van der Smagt, Patrick; Dillman, Rüdiger; Levi, Paul; Laschi, Cecilia; Knoll, Alois C; Gewaltig, Marc-Oliver
2017-01-01
Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task. Rather, the embodiment has to be simulated as well. While adequate tools exist to simulate either complex neural networks or robots and their environments, there is so far no tool that allows to easily establish a communication between brain and body models. The Neurorobotics Platform is a new web-based environment that aims to fill this gap by offering scientists and technology developers a software infrastructure allowing them to connect brain models to detailed simulations of robot bodies and environments and to use the resulting neurorobotic systems for in silico experimentation. In order to simplify the workflow and reduce the level of the required programming skills, the platform provides editors for the specification of experimental sequences and conditions, environments, robots, and brain-body connectors. In addition to that, a variety of existing robots and environments are provided. This work presents the architecture of the first release of the Neurorobotics Platform developed in subproject 10 "Neurorobotics" of the Human Brain Project (HBP). At the current state, the Neurorobotics Platform allows researchers to design and run basic experiments in neurorobotics using simulated robots and simulated environments linked to simplified versions of brain models. We illustrate the capabilities of the platform with three example experiments: a Braitenberg task implemented on a mobile robot, a sensory-motor learning task based on a robotic controller, and a visual tracking embedding a retina model on the iCub humanoid robot. These use-cases allow to assess the applicability of the Neurorobotics Platform for robotic tasks as well as in neuroscientific experiments.
Bridging online and offline social networks: Multiplex analysis
NASA Astrophysics Data System (ADS)
Filiposka, Sonja; Gajduk, Andrej; Dimitrova, Tamara; Kocarev, Ljupco
2017-04-01
We show that three basic actor characteristics, namely normalized reciprocity, three cycles, and triplets, can be expressed using an unified framework that is based on computing the similarity index between two sets associated with the actor: the set of her/his friends and the set of those considering her/him as a friend. These metrics are extended to multiplex networks and then computed for two friendship networks generated by collecting data from two groups of undergraduate students. We found that in offline communication strong and weak ties are (almost) equally presented, while in online communication weak ties are dominant. Moreover, weak ties are much less reciprocal than strong ties. However, across different layers of the multiplex network reciprocities are preserved, while triads (measured with normalized three cycles and triplets) are not significant.
Bully Victimization: Selection and Influence Within Adolescent Friendship Networks and Cliques.
Lodder, Gerine M A; Scholte, Ron H J; Cillessen, Antonius H N; Giletta, Matteo
2016-01-01
Adolescents tend to form friendships with similar peers and, in turn, their friends further influence adolescents' behaviors and attitudes. Emerging work has shown that these selection and influence processes also might extend to bully victimization. However, no prior work has examined selection and influence effects involved in bully victimization within cliques, despite theoretical account emphasizing the importance of cliques in this regard. This study examined selection and influence processes in adolescence regarding bully victimization both at the level of the entire friendship network and the level of cliques. We used a two-wave design (5-month interval). Participants were 543 adolescents (50.1% male, Mage = 15.8) in secondary education. Stochastic actor-based models indicated that at the level of the larger friendship network, adolescents tended to select friends with similar levels of bully victimization as they themselves. In addition, adolescent friends influenced each other in terms of bully victimization over time. Actor Parter Interdependence models showed that similarities in bully victimization between clique members were not due to selection of clique members. For boys, average clique bully victimization predicted individual bully victimization over time (influence), but not vice versa. No influence was found for girls, indicating that different mechanisms may underlie friend influence on bully victimization for girls and boys. The differences in results at the level of the larger friendship network versus the clique emphasize the importance of taking the type of friendship ties into account in research on selection and influence processes involved in bully victimization.
Optimized Assistive Human-Robot Interaction Using Reinforcement Learning.
Modares, Hamidreza; Ranatunga, Isura; Lewis, Frank L; Popa, Dan O
2016-03-01
An intelligent human-robot interaction (HRI) system with adjustable robot behavior is presented. The proposed HRI system assists the human operator to perform a given task with minimum workload demands and optimizes the overall human-robot system performance. Motivated by human factor studies, the presented control structure consists of two control loops. First, a robot-specific neuro-adaptive controller is designed in the inner loop to make the unknown nonlinear robot behave like a prescribed robot impedance model as perceived by a human operator. In contrast to existing neural network and adaptive impedance-based control methods, no information of the task performance or the prescribed robot impedance model parameters is required in the inner loop. Then, a task-specific outer-loop controller is designed to find the optimal parameters of the prescribed robot impedance model to adjust the robot's dynamics to the operator skills and minimize the tracking error. The outer loop includes the human operator, the robot, and the task performance details. The problem of finding the optimal parameters of the prescribed robot impedance model is transformed into a linear quadratic regulator (LQR) problem which minimizes the human effort and optimizes the closed-loop behavior of the HRI system for a given task. To obviate the requirement of the knowledge of the human model, integral reinforcement learning is used to solve the given LQR problem. Simulation results on an x - y table and a robot arm, and experimental implementation results on a PR2 robot confirm the suitability of the proposed method.
Agent-Based Chemical Plume Tracing Using Fluid Dynamics
NASA Technical Reports Server (NTRS)
Zarzhitsky, Dimitri; Spears, Diana; Thayer, David; Spears, William
2004-01-01
This paper presents a rigorous evaluation of a novel, distributed chemical plume tracing algorithm. The algorithm is a combination of the best aspects of the two most popular predecessors for this task. Furthermore, it is based on solid, formal principles from the field of fluid mechanics. The algorithm is applied by a network of mobile sensing agents (e.g., robots or micro-air vehicles) that sense the ambient fluid velocity and chemical concentration, and calculate derivatives. The algorithm drives the robotic network to the source of the toxic plume, where measures can be taken to disable the source emitter. This work is part of a much larger effort in research and development of a physics-based approach to developing networks of mobile sensing agents for monitoring, tracking, reporting and responding to hazardous conditions.
Task allocation among multiple intelligent robots
NASA Technical Reports Server (NTRS)
Gasser, L.; Bekey, G.
1987-01-01
Researchers describe the design of a decentralized mechanism for allocating assembly tasks in a multiple robot assembly workstation. Currently, the approach focuses on distributed allocation to explore its feasibility and its potential for adaptability to changing circumstances, rather than for optimizing throughput. Individual greedy robots make their own local allocation decisions using both dynamic allocation policies which propagate through a network of allocation goals, and local static and dynamic constraints describing which robots are elibible for which assembly tasks. Global coherence is achieved by proper weighting of allocation pressures propagating through the assembly plan. Deadlock avoidance and synchronization is achieved using periodic reassessments of local allocation decisions, ageing of allocation goals, and short-term allocation locks on goals.
Canedo-Rodriguez, Adrián; Iglesias, Roberto; Regueiro, Carlos V.; Alvarez-Santos, Victor; Pardo, Xose Manuel
2013-01-01
To bring cutting edge robotics from research centres to social environments, the robotics community must start providing affordable solutions: the costs must be reduced and the quality and usefulness of the robot services must be enhanced. Unfortunately, nowadays the deployment of robots and the adaptation of their services to new environments are tasks that usually require several days of expert work. With this in view, we present a multi-agent system made up of intelligent cameras and autonomous robots, which is easy and fast to deploy in different environments. The cameras will enhance the robot perceptions and allow them to react to situations that require their services. Additionally, the cameras will support the movement of the robots. This will enable our robots to navigate even when there are not maps available. The deployment of our system does not require expertise and can be done in a short period of time, since neither software nor hardware tuning is needed. Every system task is automatic, distributed and based on self-organization processes. Our system is scalable, robust, and flexible to the environment. We carried out several real world experiments, which show the good performance of our proposal. PMID:23271604
Canedo-Rodriguez, Adrián; Iglesias, Roberto; Regueiro, Carlos V; Alvarez-Santos, Victor; Pardo, Xose Manuel
2012-12-27
To bring cutting edge robotics from research centres to social environments, the robotics community must start providing affordable solutions: the costs must be reduced and the quality and usefulness of the robot services must be enhanced. Unfortunately, nowadays the deployment of robots and the adaptation of their services to new environments are tasks that usually require several days of expert work. With this in view, we present a multi-agent system made up of intelligent cameras and autonomous robots, which is easy and fast to deploy in different environments. The cameras will enhance the robot perceptions and allow them to react to situations that require their services. Additionally, the cameras will support the movement of the robots. This will enable our robots to navigate even when there are not maps available. The deployment of our system does not require expertise and can be done in a short period of time, since neither software nor hardware tuning is needed. Every system task is automatic, distributed and based on self-organization processes. Our system is scalable, robust, and flexible to the environment. We carried out several real world experiments, which show the good performance of our proposal.
A Hexapod Robot to Demonstrate Mesh Walking in a Microgravity Environment
NASA Technical Reports Server (NTRS)
Foor, David C.
2005-01-01
The JPL Micro-Robot Explorer (MRE) Spiderbot is a robot that takes advantage of its small size to perform precision tasks suitable for space applications. The Spiderbot is a legged robot that can traverse harsh terrain otherwise inaccessible to wheeled robots. A team of Spiderbots can network and can exhibit collaborative efforts to SUCCeSSfUlly complete a set of tasks. The Spiderbot is designed and developed to demonstrate hexapods that can walk on flat surfaces, crawl on meshes, and assemble simple structures. The robot has six legs consisting of two spring-compliant joints and a gripping actuator. A hard-coded set of gaits allows the robot to move smoothly in a zero-gravity environment along the mesh. The primary objective of this project is to create a Spiderbot that traverses a flexible, deployable mesh, for use in space repair. Verification of this task will take place aboard a zero-gravity test flight. The secondary objective of this project is to adapt feedback from the joints to allow the robot to test each arm for a successful grip of the mesh. The end result of this research lends itself to a fault-tolerant robot suitable for a wide variety of space applications.
Algorithmic Coordination in Robotic Networks
2010-11-29
appropriate performance, robustness and scalability properties for various task allocation , surveillance, and information gathering applications is...networking, we envision designing and analyzing algorithms with appropriate performance, robustness and scalability properties for various task ...distributed algorithms for target assignments; based on the classic auction algorithms in static networks, we intend to design efficient algorithms in worst
Distributed communications and control network for robotic mining
NASA Technical Reports Server (NTRS)
Schiffbauer, William H.
1989-01-01
The application of robotics to coal mining machines is one approach pursued to increase productivity while providing enhanced safety for the coal miner. Toward that end, a network composed of microcontrollers, computers, expert systems, real time operating systems, and a variety of program languages are being integrated that will act as the backbone for intelligent machine operation. Actual mining machines, including a few customized ones, have been given telerobotic semiautonomous capabilities by applying the described network. Control devices, intelligent sensors and computers onboard these machines are showing promise of achieving improved mining productivity and safety benefits. Current research using these machines involves navigation, multiple machine interaction, machine diagnostics, mineral detection, and graphical machine representation. Guidance sensors and systems employed include: sonar, laser rangers, gyroscopes, magnetometers, clinometers, and accelerometers. Information on the network of hardware/software and its implementation on mining machines are presented. Anticipated coal production operations using the network are discussed. A parallelism is also drawn between the direction of present day underground coal mining research to how the lunar soil (regolith) may be mined. A conceptual lunar mining operation that employs a distributed communication and control network is detailed.
Online and Offline Social Networks: Use of Social Networking Sites by Emerging Adults
ERIC Educational Resources Information Center
Subrahmanyam, Kaveri; Reich, Stephanie M.; Waechter, Natalia; Espinoza, Guadalupe
2008-01-01
Social networking sites (e.g., MySpace and Facebook) are popular online communication forms among adolescents and emerging adults. Yet little is known about young people's activities on these sites and how their networks of "friends" relate to their other online (e.g., instant messaging) and offline networks. In this study, college students…
NASA Technical Reports Server (NTRS)
Lewandowski, Leon; Struckman, Keith
1994-01-01
Microwave Vision (MV), a concept originally developed in 1985, could play a significant role in the solution to robotic vision problems. Originally our Microwave Vision concept was based on a pattern matching approach employing computer based stored replica correlation processing. Artificial Neural Network (ANN) processor technology offers an attractive alternative to the correlation processing approach, namely the ability to learn and to adapt to changing environments. This paper describes the Microwave Vision concept, some initial ANN-MV experiments, and the design of an ANN-MV system that has led to a second patent disclosure in the robotic vision field.
Peluchette, Joy; Karl, Katherine; Coustasse, Alberto; Emmett, Dennis
2012-01-01
The purpose of this study was to examine the use of social networking (Facebook) among nurse anesthetists. We examined whether they would have concerns about their supervisor, patients, or physicians seeing their Facebook profile. We also examined their attitudes related to maintaining professional boundaries with regard to the initiation or receipt of Facebook "friend" requests from their supervisor, patients, or physicians they work with. Our respondents consisted of 103 nurses currently enrolled in a graduate-level nurse anesthetist program. All respondents had a minimum of 2 years of work experience in critical care nursing. Most respondents were found to be neutral about physicians and supervisors viewing their Facebook profiles but expressed concerns about patients seeing such information. A vast majority indicated they would accept a friend request from their supervisor and a physician but not a patient. Surprisingly, about 40% had initiated a friend request to their supervisor or physician they work with. Implications for health care managers are discussed.
Dynamics of Opinion Forming in Structurally Balanced Social Networks
Altafini, Claudio
2012-01-01
A structurally balanced social network is a social community that splits into two antagonistic factions (typical example being a two-party political system). The process of opinion forming on such a community is most often highly predictable, with polarized opinions reflecting the bipartition of the network. The aim of this paper is to suggest a class of dynamical systems, called monotone systems, as natural models for the dynamics of opinion forming on structurally balanced social networks. The high predictability of the outcome of a decision process is explained in terms of the order-preserving character of the solutions of this class of dynamical systems. If we represent a social network as a signed graph in which individuals are the nodes and the signs of the edges represent friendly or hostile relationships, then the property of structural balance corresponds to the social community being splittable into two antagonistic factions, each containing only friends. PMID:22761667
Modeling Dynamic Evolution of Online Friendship Network
NASA Astrophysics Data System (ADS)
Wu, Lian-Ren; Yan, Qiang
2012-10-01
In this paper, we study the dynamic evolution of friendship network in SNS (Social Networking Site). Our analysis suggests that an individual joining a community depends not only on the number of friends he or she has within the community, but also on the friendship network generated by those friends. In addition, we propose a model which is based on two processes: first, connecting nearest neighbors; second, strength driven attachment mechanism. The model reflects two facts: first, in the social network it is a universal phenomenon that two nodes are connected when they have at least one common neighbor; second, new nodes connect more likely to nodes which have larger weights and interactions, a phenomenon called strength driven attachment (also called weight driven attachment). From the simulation results, we find that degree distribution P(k), strength distribution P(s), and degree-strength correlation are all consistent with empirical data.