Flight data acquisition methodology for validation of passive ranging algorithms for obstacle avoidance

NASA Technical Reports Server (NTRS)

Smith, Phillip N.

1990-01-01

The automation of low-altitude rotorcraft flight depends on the ability to detect, locate, and navigate around obstacles lying in the rotorcraft's intended flightpath. Computer vision techniques provide a passive method of obstacle detection and range estimation, for obstacle avoidance. Several algorithms based on computer vision methods have been developed for this purpose using laboratory data; however, further development and validation of candidate algorithms require data collected from rotorcraft flight. A data base containing low-altitude imagery augmented with the rotorcraft and sensor parameters required for passive range estimation is not readily available. Here, the emphasis is on the methodology used to develop such a data base from flight-test data consisting of imagery, rotorcraft and sensor parameters, and ground-truth range measurements. As part of the data preparation, a technique for obtaining the sensor calibration parameters is described. The data base will enable the further development of algorithms for computer vision-based obstacle detection and passive range estimation, as well as provide a benchmark for verification of range estimates against ground-truth measurements.

A switching formation strategy for obstacle avoidance of a multi-robot system based on robot priority model.

PubMed

Dai, Yanyan; Kim, YoonGu; Wee, SungGil; Lee, DongHa; Lee, SukGyu

2015-05-01

This paper describes a switching formation strategy for multi-robots with velocity constraints to avoid and cross obstacles. In the strategy, a leader robot plans a safe path using the geometric obstacle avoidance control method (GOACM). By calculating new desired distances and bearing angles with the leader robot, the follower robots switch into a safe formation. With considering collision avoidance, a novel robot priority model, based on the desired distance and bearing angle between the leader and follower robots, is designed during the obstacle avoidance process. The adaptive tracking control algorithm guarantees that the trajectory and velocity tracking errors converge to zero. To demonstrate the validity of the proposed methods, simulation and experiment results present that multi-robots effectively form and switch formation avoiding obstacles without collisions. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Numerical approach of collision avoidance and optimal control on robotic manipulators

NASA Technical Reports Server (NTRS)

Wang, Jyhshing Jack

1990-01-01

Collision-free optimal motion and trajectory planning for robotic manipulators are solved by a method of sequential gradient restoration algorithm. Numerical examples of a two degree-of-freedom (DOF) robotic manipulator are demonstrated to show the excellence of the optimization technique and obstacle avoidance scheme. The obstacle is put on the midway, or even further inward on purpose, of the previous no-obstacle optimal trajectory. For the minimum-time purpose, the trajectory grazes by the obstacle and the minimum-time motion successfully avoids the obstacle. The minimum-time is longer for the obstacle avoidance cases than the one without obstacle. The obstacle avoidance scheme can deal with multiple obstacles in any ellipsoid forms by using artificial potential fields as penalty functions via distance functions. The method is promising in solving collision-free optimal control problems for robotics and can be applied to any DOF robotic manipulators with any performance indices and mobile robots as well. Since this method generates optimum solution based on Pontryagin Extremum Principle, rather than based on assumptions, the results provide a benchmark against which any optimization techniques can be measured.

Research on Collection System Optimal Design of Wind Farm with Obstacles

NASA Astrophysics Data System (ADS)

Huang, W.; Yan, B. Y.; Tan, R. S.; Liu, L. F.

2017-05-01

To the collection system optimal design of offshore wind farm, the factors considered are not only the reasonable configuration of the cable and switch, but also the influence of the obstacles on the topology design of the offshore wind farm. This paper presents a concrete topology optimization algorithm with obstacles. The minimal area rectangle encasing box of the obstacle is obtained by using the method of minimal area encasing box. Then the optimization algorithm combining the advantages of Dijkstra algorithm and Prim algorithm is used to gain the scheme of avoidance obstacle path planning. Finally a fuzzy comprehensive evaluation model based on the analytic hierarchy process is constructed to compare the performance of the different topologies. Case studies demonstrate the feasibility of the proposed algorithm and model.

Radar-based collision avoidance for unmanned surface vehicles

NASA Astrophysics Data System (ADS)

Zhuang, Jia-yuan; Zhang, Lei; Zhao, Shi-qi; Cao, Jian; Wang, Bo; Sun, Han-bing

2016-12-01

Unmanned surface vehicles (USVs) have become a focus of research because of their extensive applications. To ensure safety and reliability and to perform complex tasks autonomously, USVs are required to possess accurate perception of the environment and effective collision avoidance capabilities. To achieve these, investigation into realtime marine radar target detection and autonomous collision avoidance technologies is required, aiming at solving the problems of noise jamming, uneven brightness, target loss, and blind areas in marine radar images. These technologies should also satisfy the requirements of real-time and reliability related to high navigation speeds of USVs. Therefore, this study developed an embedded collision avoidance system based on the marine radar, investigated a highly real-time target detection method which contains adaptive smoothing algorithm and robust segmentation algorithm, developed a stable and reliable dynamic local environment model to ensure the safety of USV navigation, and constructed a collision avoidance algorithm based on velocity obstacle (V-obstacle) which adjusts the USV's heading and speed in real-time. Sea trials results in multi-obstacle avoidance firstly demonstrate the effectiveness and efficiency of the proposed avoidance system, and then verify its great adaptability and relative stability when a USV sailing in a real and complex marine environment. The obtained results will improve the intelligent level of USV and guarantee the safety of USV independent sailing.

Underwater Sensor Network Redeployment Algorithm Based on Wolf Search

PubMed Central

Jiang, Peng; Feng, Yang; Wu, Feng

2016-01-01

This study addresses the optimization of node redeployment coverage in underwater wireless sensor networks. Given that nodes could easily become invalid under a poor environment and the large scale of underwater wireless sensor networks, an underwater sensor network redeployment algorithm was developed based on wolf search. This study is to apply the wolf search algorithm combined with crowded degree control in the deployment of underwater wireless sensor networks. The proposed algorithm uses nodes to ensure coverage of the events, and it avoids the prematurity of the nodes. The algorithm has good coverage effects. In addition, considering that obstacles exist in the underwater environment, nodes are prevented from being invalid by imitating the mechanism of avoiding predators. Thus, the energy consumption of the network is reduced. Comparative analysis shows that the algorithm is simple and effective in wireless sensor network deployment. Compared with the optimized artificial fish swarm algorithm, the proposed algorithm exhibits advantages in network coverage, energy conservation, and obstacle avoidance. PMID:27775659

Pigeon interaction mode switch-based UAV distributed flocking control under obstacle environments.

PubMed

Qiu, Huaxin; Duan, Haibin

2017-11-01

Unmanned aerial vehicle (UAV) flocking control is a serious and challenging problem due to local interactions and changing environments. In this paper, a pigeon flocking model and a pigeon coordinated obstacle-avoiding model are proposed based on a behavior that pigeon flocks will switch between hierarchical and egalitarian interaction mode at different flight phases. Owning to the similarity between bird flocks and UAV swarms in essence, a distributed flocking control algorithm based on the proposed pigeon flocking and coordinated obstacle-avoiding models is designed to coordinate a heterogeneous UAV swarm to fly though obstacle environments with few informed individuals. The comparative simulation results are elaborated to show the feasibility, validity and superiority of our proposed algorithm. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Cosine Kuramoto Based Distribution of a Convoy with Limit-Cycle Obstacle Avoidance Through the Use of Simulated Agents

NASA Astrophysics Data System (ADS)

Howerton, William

This thesis presents a method for the integration of complex network control algorithms with localized agent specific algorithms for maneuvering and obstacle avoidance. This method allows for successful implementation of group and agent specific behaviors. It has proven to be robust and will work for a variety of vehicle platforms. Initially, a review and implementation of two specific algorithms will be detailed. The first, a modified Kuramoto model was developed by Xu [1] which utilizes tools from graph theory to efficiently perform the task of distributing agents. The second algorithm developed by Kim [2] is an effective method for wheeled robots to avoid local obstacles using a limit-cycle navigation method. The results of implementing these methods on a test-bed of wheeled robots will be presented. Control issues related to outside disturbances not anticipated in the original theory are then discussed. A novel method of using simulated agents to separate the task of distributing agents from agent specific velocity and heading commands has been developed and implemented to address these issues. This new method can be used to combine various behaviors and is not limited to a specific control algorithm.

Application of Decision Tree on Collision Avoidance System Design and Verification for Quadcopter

NASA Astrophysics Data System (ADS)

Chen, C.-W.; Hsieh, P.-H.; Lai, W.-H.

2017-08-01

The purpose of the research is to build a collision avoidance system with decision tree algorithm used for quadcopters. While the ultrasonic range finder judges the distance is in collision avoidance interval, the access will be replaced from operator to the system to control the altitude of the UAV. According to the former experiences on operating quadcopters, we can obtain the appropriate pitch angle. The UAS implement the following three motions to avoid collisions. Case1: initial slow avoidance stage, Case2: slow avoidance stage and Case3: Rapid avoidance stage. Then the training data of collision avoidance test will be transmitted to the ground station via wireless transmission module to further analysis. The entire decision tree algorithm of collision avoidance system, transmission data, and ground station have been verified in some flight tests. In the flight test, the quadcopter can implement avoidance motion in real-time and move away from obstacles steadily. In the avoidance area, the authority of the collision avoidance system is higher than the operator and implements the avoidance process. The quadcopter can successfully fly away from the obstacles in 1.92 meter per second and the minimum distance between the quadcopter and the obstacle is 1.05 meters.

Reactive, Safe Navigation for Lunar and Planetary Robots

NASA Technical Reports Server (NTRS)

Utz, Hans; Ruland, Thomas

2008-01-01

When humans return to the moon, Astronauts will be accompanied by robotic helpers. Enabling robots to safely operate near astronauts on the lunar surface has the potential to significantly improve the efficiency of crew surface operations. Safely operating robots in close proximity to astronauts on the lunar surface requires reactive obstacle avoidance capabilities not available on existing planetary robots. In this paper we present work on safe, reactive navigation using a stereo based high-speed terrain analysis and obstacle avoidance system. Advances in the design of the algorithms allow it to run terrain analysis and obstacle avoidance algorithms at full frame rate (30Hz) on off the shelf hardware. The results of this analysis are fed into a fast, reactive path selection module, enforcing the safety of the chosen actions. The key components of the system are discussed and test results are presented.

Research on robot mobile obstacle avoidance control based on visual information

NASA Astrophysics Data System (ADS)

Jin, Jiang

2018-03-01

Robots to detect obstacles and control robots to avoid obstacles has been a key research topic of robot control. In this paper, a scheme of visual information acquisition is proposed. By judging visual information, the visual information is transformed into the information source of path processing. In accordance with the established route, in the process of encountering obstacles, the algorithm real-time adjustment trajectory to meet the purpose of intelligent control of mobile robots. Simulation results show that, through the integration of visual sensing information, the obstacle information is fully obtained, while the real-time and accuracy of the robot movement control is guaranteed.

Tracked robot controllers for climbing obstacles autonomously

NASA Astrophysics Data System (ADS)

Vincent, Isabelle

2009-05-01

Research in mobile robot navigation has demonstrated some success in navigating flat indoor environments while avoiding obstacles. However, the challenge of analyzing complex environments to climb obstacles autonomously has had very little success due to the complexity of the task. Unmanned ground vehicles currently exhibit simple autonomous behaviours compared to the human ability to move in the world. This paper presents the control algorithms designed for a tracked mobile robot to autonomously climb obstacles by varying its tracks configuration. Two control algorithms are proposed to solve the autonomous locomotion problem for climbing obstacles. First, a reactive controller evaluates the appropriate geometric configuration based on terrain and vehicle geometric considerations. Then, a reinforcement learning algorithm finds alternative solutions when the reactive controller gets stuck while climbing an obstacle. The methodology combines reactivity to learning. The controllers have been demonstrated in box and stair climbing simulations. The experiments illustrate the effectiveness of the proposed approach for crossing obstacles.

A Method on Dynamic Path Planning for Robotic Manipulator Autonomous Obstacle Avoidance Based on an Improved RRT Algorithm.

PubMed

Wei, Kun; Ren, Bingyin

2018-02-13

In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human-Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the process of improving robotic manipulator intelligence. Among the path-planning methods, the Rapidly Exploring Random Tree (RRT) algorithm based on random sampling has been widely applied in dynamic path planning for a high-dimensional robotic manipulator, especially in a complex environment because of its probability completeness, perfect expansion, and fast exploring speed over other planning methods. However, the existing RRT algorithm has a limitation in path planning for a robotic manipulator in a dynamic unstructured environment. Therefore, an autonomous obstacle avoidance dynamic path-planning method for a robotic manipulator based on an improved RRT algorithm, called Smoothly RRT (S-RRT), is proposed. This method that targets a directional node extends and can increase the sampling speed and efficiency of RRT dramatically. A path optimization strategy based on the maximum curvature constraint is presented to generate a smooth and curved continuous executable path for a robotic manipulator. Finally, the correctness, effectiveness, and practicability of the proposed method are demonstrated and validated via a MATLAB static simulation and a Robot Operating System (ROS) dynamic simulation environment as well as a real autonomous obstacle avoidance experiment in a dynamic unstructured environment for a robotic manipulator. The proposed method not only provides great practical engineering significance for a robotic manipulator's obstacle avoidance in an intelligent factory, but also theoretical reference value for other type of robots' path planning.

Improved obstacle avoidance and navigation for an autonomous ground vehicle

NASA Astrophysics Data System (ADS)

Giri, Binod; Cho, Hyunsu; Williams, Benjamin C.; Tann, Hokchhay; Shakya, Bicky; Bharam, Vishal; Ahlgren, David J.

2015-01-01

This paper presents improvements made to the intelligence algorithms employed on Q, an autonomous ground vehicle, for the 2014 Intelligent Ground Vehicle Competition (IGVC). In 2012, the IGVC committee combined the formerly separate autonomous and navigation challenges into a single AUT-NAV challenge. In this new challenge, the vehicle is required to navigate through a grassy obstacle course and stay within the course boundaries (a lane of two white painted lines) that guide it toward a given GPS waypoint. Once the vehicle reaches this waypoint, it enters an open course where it is required to navigate to another GPS waypoint while avoiding obstacles. After reaching the final waypoint, the vehicle is required to traverse another obstacle course before completing the run. Q uses modular parallel software architecture in which image processing, navigation, and sensor control algorithms run concurrently. A tuned navigation algorithm allows Q to smoothly maneuver through obstacle fields. For the 2014 competition, most revisions occurred in the vision system, which detects white lines and informs the navigation component. Barrel obstacles of various colors presented a new challenge for image processing: the previous color plane extraction algorithm would not suffice. To overcome this difficulty, laser range sensor data were overlaid on visual data. Q also participates in the Joint Architecture for Unmanned Systems (JAUS) challenge at IGVC. For 2014, significant updates were implemented: the JAUS component accepted a greater variety of messages and showed better compliance to the JAUS technical standard. With these improvements, Q secured second place in the JAUS competition.

Whole arm manipulation planning based on feedback velocity fields and sampling-based techniques.

PubMed

Talaei, B; Abdollahi, F; Talebi, H A; Omidi Karkani, E

2013-09-01

Changing the configuration of a cooperative whole arm manipulator is not easy while enclosing an object. This difficulty is mainly because of risk of jamming caused by kinematic constraints. To reduce this risk, this paper proposes a feedback manipulation planning algorithm that takes grasp kinematics into account. The idea is based on a vector field that imposes perturbation in object motion inducing directions when the movement is considerably along manipulator redundant directions. Obstacle avoidance problem is then considered by combining the algorithm with sampling-based techniques. As experimental results confirm, the proposed algorithm is effective in avoiding jamming as well as obstacles for a 6-DOF dual arm whole arm manipulator. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor.

PubMed

Kikutis, Ramūnas; Stankūnas, Jonas; Rudinskas, Darius; Masiulionis, Tadas

2017-09-28

Current research on Unmanned Aerial Vehicles (UAVs) shows a lot of interest in autonomous UAV navigation. This interest is mainly driven by the necessity to meet the rules and restrictions for small UAV flights that are issued by various international and national legal organizations. In order to lower these restrictions, new levels of automation and flight safety must be reached. In this paper, a new method for ground obstacle avoidance derived by using UAV navigation based on the Dubins paths algorithm is presented. The accuracy of the proposed method has been tested, and research results have been obtained by using Software-in-the-Loop (SITL) simulation and real UAV flights, with the measurements done with a low cost Global Navigation Satellite System (GNSS) sensor. All tests were carried out in a three-dimensional space, but the height accuracy was not assessed. The GNSS navigation data for the ground obstacle avoidance algorithm is evaluated statistically.

Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor

PubMed Central

Kikutis, Ramūnas; Stankūnas, Jonas; Rudinskas, Darius; Masiulionis, Tadas

2017-01-01

Current research on Unmanned Aerial Vehicles (UAVs) shows a lot of interest in autonomous UAV navigation. This interest is mainly driven by the necessity to meet the rules and restrictions for small UAV flights that are issued by various international and national legal organizations. In order to lower these restrictions, new levels of automation and flight safety must be reached. In this paper, a new method for ground obstacle avoidance derived by using UAV navigation based on the Dubins paths algorithm is presented. The accuracy of the proposed method has been tested, and research results have been obtained by using Software-in-the-Loop (SITL) simulation and real UAV flights, with the measurements done with a low cost Global Navigation Satellite System (GNSS) sensor. All tests were carried out in a three-dimensional space, but the height accuracy was not assessed. The GNSS navigation data for the ground obstacle avoidance algorithm is evaluated statistically. PMID:28956839

Fuzzy Logic Based Control for Autonomous Mobile Robot Navigation

PubMed Central

Masmoudi, Mohamed Slim; Masmoudi, Mohamed

2016-01-01

This paper describes the design and the implementation of a trajectory tracking controller using fuzzy logic for mobile robot to navigate in indoor environments. Most of the previous works used two independent controllers for navigation and avoiding obstacles. The main contribution of the paper can be summarized in the fact that we use only one fuzzy controller for navigation and obstacle avoidance. The used mobile robot is equipped with DC motor, nine infrared range (IR) sensors to measure the distance to obstacles, and two optical encoders to provide the actual position and speeds. To evaluate the performances of the intelligent navigation algorithms, different trajectories are used and simulated using MATLAB software and SIMIAM navigation platform. Simulation results show the performances of the intelligent navigation algorithms in terms of simulation times and travelled path. PMID:27688748

Local pursuit strategy-inspired cooperative trajectory planning algorithm for a class of nonlinear constrained dynamical systems

NASA Astrophysics Data System (ADS)

Xu, Yunjun; Remeikas, Charles; Pham, Khanh

2014-03-01

Cooperative trajectory planning is crucial for networked vehicles to respond rapidly in cluttered environments and has a significant impact on many applications such as air traffic or border security monitoring and assessment. One of the challenges in cooperative planning is to find a computationally efficient algorithm that can accommodate both the complexity of the environment and real hardware and configuration constraints of vehicles in the formation. Inspired by a local pursuit strategy observed in foraging ants, feasible and optimal trajectory planning algorithms are proposed in this paper for a class of nonlinear constrained cooperative vehicles in environments with densely populated obstacles. In an iterative hierarchical approach, the local behaviours, such as the formation stability, obstacle avoidance, and individual vehicle's constraints, are considered in each vehicle's (i.e. follower's) decentralised optimisation. The cooperative-level behaviours, such as the inter-vehicle collision avoidance, are considered in the virtual leader's centralised optimisation. Early termination conditions are derived to reduce the computational cost by not wasting time in the local-level optimisation if the virtual leader trajectory does not satisfy those conditions. The expected advantages of the proposed algorithms are (1) the formation can be globally asymptotically maintained in a decentralised manner; (2) each vehicle decides its local trajectory using only the virtual leader and its own information; (3) the formation convergence speed is controlled by one single parameter, which makes it attractive for many practical applications; (4) nonlinear dynamics and many realistic constraints, such as the speed limitation and obstacle avoidance, can be easily considered; (5) inter-vehicle collision avoidance can be guaranteed in both the formation transient stage and the formation steady stage; and (6) the computational cost in finding both the feasible and optimal solutions is low. In particular, the feasible solution can be computed in a very quick fashion. The minimum energy trajectory planning for a group of robots in an obstacle-laden environment is simulated to showcase the advantages of the proposed algorithms.

Online optimal obstacle avoidance for rotary-wing autonomous unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kang, Keeryun

This thesis presents an integrated framework for online obstacle avoidance of rotary-wing unmanned aerial vehicles (UAVs), which can provide UAVs an obstacle field navigation capability in a partially or completely unknown obstacle-rich environment. The framework is composed of a LIDAR interface, a local obstacle grid generation, a receding horizon (RH) trajectory optimizer, a global shortest path search algorithm, and a climb rate limit detection logic. The key feature of the framework is the use of an optimization-based trajectory generation in which the obstacle avoidance problem is formulated as a nonlinear trajectory optimization problem with state and input constraints over the finite range of the sensor. This local trajectory optimization is combined with a global path search algorithm which provides a useful initial guess to the nonlinear optimization solver. Optimization is the natural process of finding the best trajectory that is dynamically feasible, safe within the vehicle's flight envelope, and collision-free at the same time. The optimal trajectory is continuously updated in real time by the numerical optimization solver, Nonlinear Trajectory Generation (NTG), which is a direct solver based on the spline approximation of trajectory for dynamically flat systems. In fact, the overall approach of this thesis to finding the optimal trajectory is similar to the model predictive control (MPC) or the receding horizon control (RHC), except that this thesis followed a two-layer design; thus, the optimal solution works as a guidance command to be followed by the controller of the vehicle. The framework is implemented in a real-time simulation environment, the Georgia Tech UAV Simulation Tool (GUST), and integrated in the onboard software of the rotary-wing UAV test-bed at Georgia Tech. Initially, the 2D vertical avoidance capability of real obstacles was tested in flight. The flight test evaluations were extended to the benchmark tests for 3D avoidance capability over the virtual obstacles, and finally it was demonstrated on real obstacles located at the McKenna MOUT site in Fort Benning, Georgia. Simulations and flight test evaluations demonstrate the feasibility of the developed framework for UAV applications involving low-altitude flight in an urban area.

Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boardman, Beth Leigh

The common theme of this dissertation is sampling-based motion planning with the two key contributions being in the area of replanning and spatial load balancing for robotic systems. Here, we begin by recalling two sampling-based motion planners: the asymptotically optimal rapidly-exploring random tree (RRT*), and the asymptotically optimal probabilistic roadmap (PRM*). We also provide a brief background on collision cones and the Distributed Reactive Collision Avoidance (DRCA) algorithm. The next four chapters detail novel contributions for motion replanning in environments with unexpected static obstacles, for multi-agent collision avoidance, and spatial load balancing. First, we show improved performance of the RRT*more » when using the proposed Grandparent-Connection (GP) or Focused-Refinement (FR) algorithms. Next, the Goal Tree algorithm for replanning with unexpected static obstacles is detailed and proven to be asymptotically optimal. A multi-agent collision avoidance problem in obstacle environments is approached via the RRT*, leading to the novel Sampling-Based Collision Avoidance (SBCA) algorithm. The SBCA algorithm is proven to guarantee collision free trajectories for all of the agents, even when subject to uncertainties in the knowledge of the other agents’ positions and velocities. Given that a solution exists, we prove that livelocks and deadlock will lead to the cost to the goal being decreased. We introduce a new deconfliction maneuver that decreases the cost-to-come at each step. This new maneuver removes the possibility of livelocks and allows a result to be formed that proves convergence to the goal configurations. Finally, we present a limited range Graph-based Spatial Load Balancing (GSLB) algorithm which fairly divides a non-convex space among multiple agents that are subject to differential constraints and have a limited travel distance. The GSLB is proven to converge to a solution when maximizing the area covered by the agents. The analysis for each of the above mentioned algorithms is confirmed in simulations.« less

The application of Markov decision process in restaurant delivery robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Hu, Zhen; Wang, Ying

2017-05-01

As the restaurant delivery robot is often in a dynamic and complex environment, including the chairs inadvertently moved to the channel and customers coming and going. The traditional path planning algorithm is not very ideal. To solve this problem, this paper proposes the Markov dynamic state immediate reward (MDR) path planning algorithm according to the traditional Markov decision process. First of all, it uses MDR to plan a global path, then navigates along this path. When the sensor detects there is no obstructions in front state, increase its immediate state reward value; when the sensor detects there is an obstacle in front, plan a global path that can avoid obstacle with the current position as the new starting point and reduce its state immediate reward value. This continues until the target is reached. When the robot learns for a period of time, it can avoid those places where obstacles are often present when planning the path. By analyzing the simulation experiment, the algorithm has achieved good results in the global path planning under the dynamic environment.

Particle Filtering for Obstacle Tracking in UAS Sense and Avoid Applications

PubMed Central

Moccia, Antonio

2014-01-01

Obstacle detection and tracking is a key function for UAS sense and avoid applications. In fact, obstacles in the flight path must be detected and tracked in an accurate and timely manner in order to execute a collision avoidance maneuver in case of collision threat. The most important parameter for the assessment of a collision risk is the Distance at Closest Point of Approach, that is, the predicted minimum distance between own aircraft and intruder for assigned current position and speed. Since assessed methodologies can cause some loss of accuracy due to nonlinearities, advanced filtering methodologies, such as particle filters, can provide more accurate estimates of the target state in case of nonlinear problems, thus improving system performance in terms of collision risk estimation. The paper focuses on algorithm development and performance evaluation for an obstacle tracking system based on a particle filter. The particle filter algorithm was tested in off-line simulations based on data gathered during flight tests. In particular, radar-based tracking was considered in order to evaluate the impact of particle filtering in a single sensor framework. The analysis shows some accuracy improvements in the estimation of Distance at Closest Point of Approach, thus reducing the delay in collision detection. PMID:25105154

Sensorimotor Model of Obstacle Avoidance in Echolocating Bats

PubMed Central

Vanderelst, Dieter; Holderied, Marc W.; Peremans, Herbert

2015-01-01

Bat echolocation is an ability consisting of many subtasks such as navigation, prey detection and object recognition. Understanding the echolocation capabilities of bats comes down to isolating the minimal set of acoustic cues needed to complete each task. For some tasks, the minimal cues have already been identified. However, while a number of possible cues have been suggested, little is known about the minimal cues supporting obstacle avoidance in echolocating bats. In this paper, we propose that the Interaural Intensity Difference (IID) and travel time of the first millisecond of the echo train are sufficient cues for obstacle avoidance. We describe a simple control algorithm based on the use of these cues in combination with alternating ear positions modeled after the constant frequency bat Rhinolophus rouxii. Using spatial simulations (2D and 3D), we show that simple phonotaxis can steer a bat clear from obstacles without performing a reconstruction of the 3D layout of the scene. As such, this paper presents the first computationally explicit explanation for obstacle avoidance validated in complex simulated environments. Based on additional simulations modelling the FM bat Phyllostomus discolor, we conjecture that the proposed cues can be exploited by constant frequency (CF) bats and frequency modulated (FM) bats alike. We hypothesize that using a low level yet robust cue for obstacle avoidance allows bats to comply with the hard real-time constraints of this basic behaviour. PMID:26502063

Advanced obstacle avoidance for a laser based wheelchair using optimised Bayesian neural networks.

PubMed

Trieu, Hoang T; Nguyen, Hung T; Willey, Keith

2008-01-01

In this paper we present an advanced method of obstacle avoidance for a laser based intelligent wheelchair using optimized Bayesian neural networks. Three neural networks are designed for three separate sub-tasks: passing through a door way, corridor and wall following and general obstacle avoidance. The accurate usable accessible space is determined by including the actual wheelchair dimensions in a real-time map used as inputs to each networks. Data acquisitions are performed separately to collect the patterns required for specified sub-tasks. Bayesian frame work is used to determine the optimal neural network structure in each case. Then these networks are trained under the supervision of Bayesian rule. Experiment results showed that compare to the VFH algorithm our neural networks navigated a smoother path following a near optimum trajectory.

Path Planning Method in Multi-obstacle Marine Environment

NASA Astrophysics Data System (ADS)

Zhang, Jinpeng; Sun, Hanxv

2017-12-01

In this paper, an improved algorithm for particle swarm optimization is proposed for the application of underwater robot in the complex marine environment. Not only did consider to avoid obstacles when path planning, but also considered the current direction and the size effect on the performance of the robot dynamics. The algorithm uses the trunk binary tree structure to construct the path search space and A * heuristic search method is used in the search space to find a evaluation standard path. Then the particle swarm algorithm to optimize the path by adjusting evaluation function, which makes the underwater robot in the current navigation easier to control, and consume less energy.

Orbital navigation, docking and obstacle avoidance as a form of three dimensional model-based image understanding

NASA Technical Reports Server (NTRS)

Beyer, J.; Jacobus, C.; Mitchell, B.

1987-01-01

Range imagery from a laser scanner can be used to provide sufficient information for docking and obstacle avoidance procedures to be performed automatically. Three dimensional model-based computer vision algorithms in development can perform these tasks even with targets which may not be cooperative (that is, objects without special targets or markers to provide unambiguous location points). Roll, pitch and yaw of the vehicle can be taken into account as image scanning takes place, so that these can be corrected when the image is converted from egocentric to world coordinates. Other attributes of the sensor, such as the registered reflectence and texture channels, provide additional data sources for algorithm robustness. Temporal fusion of sensor immages can take place in the work coordinate domain, allowing for the building of complex maps in three dimensional space.

Design and evaluation of an autonomous, obstacle avoiding, flight control system using visual sensors

NASA Astrophysics Data System (ADS)

Crawford, Bobby Grant

In an effort to field smaller and cheaper Uninhabited Aerial Vehicles (UAVs), the Army has expressed an interest in an ability of the vehicle to autonomously detect and avoid obstacles. Current systems are not suitable for small aircraft. NASA Langley Research Center has developed a vision sensing system that uses small semiconductor cameras. The feasibility of using this sensor for the purpose of autonomous obstacle avoidance by a UAV is the focus of the research presented in this document. The vision sensor characteristics are modeled and incorporated into guidance and control algorithms designed to generate flight commands based on obstacle information received from the sensor. The system is evaluated by simulating the response to these flight commands using a six degree-of-freedom, non-linear simulation of a small, fixed wing UAV. The simulation is written using the MATLAB application and runs on a PC. Simulations were conducted to test the longitudinal and lateral capabilities of the flight control for a range of airspeeds, camera characteristics, and wind speeds. Results indicate that the control system is suitable for obstacle avoiding flight control using the simulated vision system. In addition, a method for designing and evaluating the performance of such a system has been developed that allows the user to easily change component characteristics and evaluate new systems through simulation.

The research of autonomous obstacle avoidance of mobile robot based on multi-sensor integration

NASA Astrophysics Data System (ADS)

Zhao, Ming; Han, Baoling

2016-11-01

The object of this study is the bionic quadruped mobile robot. The study has proposed a system design plan for mobile robot obstacle avoidance with the binocular stereo visual sensor and the self-control 3D Lidar integrated with modified ant colony optimization path planning to realize the reconstruction of the environmental map. Because the working condition of a mobile robot is complex, the result of the 3D reconstruction with a single binocular sensor is undesirable when feature points are few and the light condition is poor. Therefore, this system integrates the stereo vision sensor blumblebee2 and the Lidar sensor together to detect the cloud information of 3D points of environmental obstacles. This paper proposes the sensor information fusion technology to rebuild the environment map. Firstly, according to the Lidar data and visual data on obstacle detection respectively, and then consider two methods respectively to detect the distribution of obstacles. Finally fusing the data to get the more complete, more accurate distribution of obstacles in the scene. Then the thesis introduces ant colony algorithm. It has analyzed advantages and disadvantages of the ant colony optimization and its formation cause deeply, and then improved the system with the help of the ant colony optimization to increase the rate of convergence and precision of the algorithm in robot path planning. Such improvements and integrations overcome the shortcomings of the ant colony optimization like involving into the local optimal solution easily, slow search speed and poor search results. This experiment deals with images and programs the motor drive under the compiling environment of Matlab and Visual Studio and establishes the visual 2.5D grid map. Finally it plans a global path for the mobile robot according to the ant colony algorithm. The feasibility and effectiveness of the system are confirmed by ROS and simulation platform of Linux.

Wheelchair Navigation System for Disabled and Elderly People

PubMed Central

Kim, Eun Yi

2016-01-01

An intelligent wheelchair (IW) system is developed in order to support safe mobility for disabled or elderly people with various impairments. The proposed IW offers two main functions: obstacle detection and avoidance, and situation recognition. First, through a combination of a vision sensor and eight ultrasonic ones, it detects diverse obstacles and produces occupancy grid maps (OGMs) that describe environmental information, including the positions and sizes of obstacles, which is then given to the learning-based algorithm. By learning the common patterns among OGMs assigned to the same directions, the IW can automatically find paths to prevent collisions with obstacles. Second, it distinguishes a situation whereby the user is standing on a sidewalk, traffic intersection, or roadway through analyzing the texture and shape of the images, which aids in preventing any accidents that would result in fatal injuries to the user, such as collisions with vehicles. From the experiments that were performed in various environments, we can prove the following: (1) the proposed system can recognize different types of outdoor places with 98.3% accuracy; and (2) it can produce paths that avoid obstacles with 92.0% accuracy. PMID:27801852

Laser radar system for obstacle avoidance

NASA Astrophysics Data System (ADS)

Bers, Karlheinz; Schulz, Karl R.; Armbruster, Walter

2005-09-01

The threat of hostile surveillance and weapon systems require military aircraft to fly under extreme conditions such as low altitude, high speed, poor visibility and incomplete terrain information. The probability of collision with natural and man-made obstacles during such contour missions is high if detection capability is restricted to conventional vision aids. Forward-looking scanning laser radars which are build by the EADS company and presently being flight tested and evaluated at German proving grounds, provide a possible solution, having a large field of view, high angular and range resolution, a high pulse repetition rate, and sufficient pulse energy to register returns from objects at distances of military relevance with a high hit-and-detect probability. The development of advanced 3d-scene analysis algorithms had increased the recognition probability and reduced the false alarm rate by using more readily recognizable objects such as terrain, poles, pylons, trees, etc. to generate a parametric description of the terrain surface as well as the class, position, orientation, size and shape of all objects in the scene. The sensor system and the implemented algorithms can be used for other applications such as terrain following, autonomous obstacle avoidance, and automatic target recognition. This paper describes different 3D-imaging ladar sensors with unique system architecture but different components matched for different military application. Emphasis is laid on an obstacle warning system with a high probability of detection of thin wires, the real time processing of the measured range image data, obstacle classification und visualization.

Follow-the-Leader Control for the PIPS Prototype Hardware

NASA Technical Reports Server (NTRS)

Williams, Robert L. II; Lippitt, Thimas

1996-01-01

This report describes the payload inspection and processing system (PIPS), an automated system programmed off-line for inspection of space shuttle payloads after integration and prior to launch. PIPS features a hyper-redundant 18-degree of freedom (DOF) serpentine truss manipulator capable of snake like motions to avoid obstacles. During the summer of 1995, the author worked on the same project, developing a follow-the-leader (FTL) algorithm in graphical simulation which ensures whole arm collision avoidance by forcing ensuing links to follow the same tip trajectory. The summer 1996 work was to control the prototype PIPS hardware in follow-the-leader mode. The project was successful in providing FTL control in hardware. The STS-82 payload mockup was used in the laboratory to demonstrate serpentine motions to avoid obstacles in a realistic environment.

Path planning for robotic truss assembly

NASA Technical Reports Server (NTRS)

Sanderson, Arthur C.

1993-01-01

A new Potential Fields approach to the robotic path planning problem is proposed and implemented. Our approach, which is based on one originally proposed by Munger, computes an incremental joint vector based upon attraction to a goal and repulsion from obstacles. By repetitively adding and computing these 'steps', it is hoped (but not guaranteed) that the robot will reach its goal. An attractive force exerted by the goal is found by solving for the the minimum norm solution to the linear Jacobian equation. A repulsive force between obstacles and the robot's links is used to avoid collisions. Its magnitude is inversely proportional to the distance. Together, these forces make the goal the global minimum potential point, but local minima can stop the robot from ever reaching that point. Our approach improves on a basic, potential field paradigm developed by Munger by using an active, adaptive field - what we will call a 'flexible' potential field. Active fields are stronger when objects move towards one another and weaker when they move apart. An adaptive field's strength is individually tailored to be just strong enough to avoid any collision. In addition to the local planner, a global planning algorithm helps the planner to avoid local field minima by providing subgoals. These subgoals are based on the obstacles which caused the local planner to fail. A best-first search algorithm A* is used for graph search.

Terrain mapping and control of unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kang, Yeonsik

In this thesis, methods for terrain mapping and control of unmanned aerial vehicles (UAVs) are proposed. First, robust obstacle detection and tracking algorithm are introduced to eliminate the clutter noise uncorrelated with the real obstacle. This is an important problem since most types of sensor measurements are vulnerable to noise. In order to eliminate such noise, a Kalman filter-based interacting multiple model (IMM) algorithm is employed to effectively detect obstacles and estimate their positions precisely. Using the outcome of the IMM-based obstacle detection algorithm, a new method of building a probabilistic occupancy grid map is proposed based on Bayes rule in probability theory. Since the proposed map update law uses the outputs of the IMM-based obstacle detection algorithm, simultaneous tracking of moving targets and mapping of stationary obstacles are possible. This can be helpful especially in a noisy outdoor environment where different types of obstacles exist. Another feature of the algorithm is its capability to eliminate clutter noise as well as measurement noise. The proposed algorithm is simulated in Matlab using realistic sensor models. The results show close agreement with the layout of real obstacles. An efficient method called "quadtree" is used to process massive geographical information in a convenient manner. The algorithm is evaluated in a realistic simulation environment called RIPTIDE, which the NASA Ames Research Center developed to access the performance of complicated software for UAVs. Supposing that a UAV is equipped with abovementioned obstacle detection and mapping algorithm, the control problem of a small fixed-wing UAV is studied. A Nonlinear Model Predictive Control (NMPC is designed as a high level controller for the fixed-wing UAV using a kinematic model of the UAV. The kinematic model is employed because of the assumption that there exist low level controls on the UAV. The UAV dynamics are nonlinear with input constraints which is the main challenge explored in this thesis. The control objective of the NMPC is determined to track a desired line, and the analysis of the designed NMPC's stability is followed to find the conditions that can assure stability. Then, the control objective is extended to track adjoined multiple line segments with obstacle avoidance capability. In simulation, the performance of the NMPC is superb with fast convergence and small overshoot. The computation time is not a burden for a fixed-wing UAV controller with a Pentium level on-board computer that provides a reasonable control update rate.

Aviation obstacle auto-extraction using remote sensing information

NASA Astrophysics Data System (ADS)

Zimmer, N.; Lugsch, W.; Ravenscroft, D.; Schiefele, J.

2008-10-01

An Obstacle, in the aviation context, may be any natural, man-made, fixed or movable object, permanent or temporary. Currently, the most common way to detect relevant aviation obstacles from an aircraft or helicopter for navigation purposes and collision avoidance is the use of merged infrared and synthetic information of obstacle data. Several algorithms have been established to utilize synthetic and infrared images to generate obstacle information. There might be a situation however where the system is error-prone and may not be able to consistently determine the current environment. This situation can be avoided when the system knows the true position of the obstacle. The quality characteristics of the obstacle data strongly depends on the quality of the source data such as maps and official publications. In some countries such as newly industrializing and developing countries, quality and quantity of obstacle information is not available. The aviation world has two specifications - RTCA DO-276A and ICAO ANNEX 15 Ch. 10 - which describe the requirements for aviation obstacles. It is essential to meet these requirements to be compliant with the specifications and to support systems based on these specifications, e.g. 3D obstacle warning systems where accurate coordinates based on WGS-84 is a necessity. Existing aerial and satellite or soon to exist high quality remote sensing data makes it feasible to think about automated aviation obstacle data origination. This paper will describe the feasibility to auto-extract aviation obstacles from remote sensing data considering limitations of image and extraction technologies. Quality parameters and possible resolution of auto-extracted obstacle data will be discussed and presented.

Training toddlers seated on mobile robots to drive indoors amidst obstacles.

PubMed

Chen, Xi; Ragonesi, Christina; Galloway, James C; Agrawal, Sunil K

2011-06-01

Mobility is a causal factor in development. Children with mobility impairments may rely upon power mobility for independence and thus require advanced driving skills to function independently. Our previous studies show that while infants can learn to drive directly to a goal using conventional joysticks in several months of training, they are unable in this timeframe to acquire the advanced skill to avoid obstacles while driving. Without adequate driving training, children are unable to explore the environment safely, the consequences of which may in turn increase their risk for developmental delay. The goal of this research therefore is to train children seated on mobile robots to purposefully and safely drive indoors. In this paper, we present results where ten typically-developing toddlers are trained to drive a robot within an obstacle course. We also report a case study with a toddler with spina-bifida who cannot independently walk. Using algorithms based on artificial potential fields to avoid obstacles, we create force field on the joystick that trains the children to navigate while avoiding obstacles. In this "assist-as-needed" approach, if the child steers the joystick outside a force tunnel centered on the desired direction, the driver experiences a bias force on the hand. Our results suggest that the use of a force-feedback joystick may yield faster learning than the use of a conventional joystick.

Developing Autonomy for Unmanned Surface Vehicles by Using Virtual Environments

DTIC Science & Technology

2010-10-11

successfully evolved for a wide variety of behaviors as obstacle avoidance (Barate and Manzanera 2007; Nehmzow 2002), wall-following ( Dain 1998...Advances in unmanned marine vehicles pp 311-328 Dain R (1998) Developing mobile robot wall-following algorithms using ge- netic programming. Applied

A stereo vision-based obstacle detection system in vehicles

NASA Astrophysics Data System (ADS)

Huh, Kunsoo; Park, Jaehak; Hwang, Junyeon; Hong, Daegun

2008-02-01

Obstacle detection is a crucial issue for driver assistance systems as well as for autonomous vehicle guidance function and it has to be performed with high reliability to avoid any potential collision with the front vehicle. The vision-based obstacle detection systems are regarded promising for this purpose because they require little infrastructure on a highway. However, the feasibility of these systems in passenger car requires accurate and robust sensing performance. In this paper, an obstacle detection system using stereo vision sensors is developed. This system utilizes feature matching, epipoplar constraint and feature aggregation in order to robustly detect the initial corresponding pairs. After the initial detection, the system executes the tracking algorithm for the obstacles. The proposed system can detect a front obstacle, a leading vehicle and a vehicle cutting into the lane. Then, the position parameters of the obstacles and leading vehicles can be obtained. The proposed obstacle detection system is implemented on a passenger car and its performance is verified experimentally.

Velodyne HDL-64E lidar for unmanned surface vehicle obstacle detection

NASA Astrophysics Data System (ADS)

Halterman, Ryan; Bruch, Michael

2010-04-01

The Velodyne HDL-64E is a 64 laser 3D (360×26.8 degree) scanning LIDAR. It was designed to fill perception needs of DARPA Urban Challenge vehicles. As such, it was principally intended for ground use. This paper presents the performance of the HDL-64E as it relates to the marine environment for unmanned surface vehicle (USV) obstacle detection and avoidance. We describe the sensor's capacity for discerning relevant objects at sea- both through subjective observations of the raw data and through a rudimentary automated obstacle detection algorithm. We also discuss some of the complications that have arisen with the sensor.

On Algorithms for Nonlinear Minimax and Min-Max-Min Problems and Their Efficiency

DTIC Science & Technology

2011-03-01

dissertation is complete, I can finally stay home after dinner to play Wii with you. LET’S GO Mario and Yellow Mushroom... xv THIS PAGE INTENTIONALLY... balance the accuracy of the approximation with problem ill-conditioning. The sim- plest smoothing algorithm creates an accurate smooth approximating...sizing in electronic circuit boards (Chen & Fan, 1998), obstacle avoidance for robots (Kirjner- Neto & Polak, 1998), optimal design centering

Overcoming an obstacle in expanding a UMLS semantic type extent.

PubMed

Chen, Yan; Gu, Huanying; Perl, Yehoshua; Geller, James

2012-02-01

This paper strives to overcome a major problem encountered by a previous expansion methodology for discovering concepts highly likely to be missing a specific semantic type assignment in the UMLS. This methodology is the basis for an algorithm that presents the discovered concepts to a human auditor for review and possible correction. We analyzed the problem of the previous expansion methodology and discovered that it was due to an obstacle constituted by one or more concepts assigned the UMLS Semantic Network semantic type Classification. A new methodology was designed that bypasses such an obstacle without a combinatorial explosion in the number of concepts presented to the human auditor for review. The new expansion methodology with obstacle avoidance was tested with the semantic type Experimental Model of Disease and found over 500 concepts missed by the previous methodology that are in need of this semantic type assignment. Furthermore, other semantic types suffering from the same major problem were discovered, indicating that the methodology is of more general applicability. The algorithmic discovery of concepts that are likely missing a semantic type assignment is possible even in the face of obstacles, without an explosion in the number of processed concepts. Copyright © 2011 Elsevier Inc. All rights reserved.

Overcoming an Obstacle in Expanding a UMLS Semantic Type Extent

PubMed Central

Chen, Yan; Gu, Huanying; Perl, Yehoshua; Geller, James

2011-01-01

This paper strives to overcome a major problem encountered by a previous expansion methodology for discovering concepts highly likely to be missing a specific semantic type assignment in the UMLS. This methodology is the basis for an algorithm that presents the discovered concepts to a human auditor for review and possible correction. We analyzed the problem of the previous expansion methodology and discovered that it was due to an obstacle constituted by one or more concepts assigned the UMLS Semantic Network semantic type Classification. A new methodology was designed that bypasses such an obstacle without a combinatorial explosion in the number of concepts presented to the human auditor for review. The new expansion methodology with obstacle avoidance was tested with the semantic type Experimental Model of Disease and found over 500 concepts missed by the previous methodology that are in need of this semantic type assignment. Furthermore, other semantic types suffering from the same major problem were discovered, indicating that the methodology is of more general applicability. The algorithmic discovery of concepts that are likely missing a semantic type assignment is possible even in the face of obstacles, without an explosion in the number of processed concepts. PMID:21925287

Simple Smartphone-Based Guiding System for Visually Impaired People

PubMed Central

Lin, Bor-Shing; Lee, Cheng-Che; Chiang, Pei-Ying

2017-01-01

Visually impaired people are often unaware of dangers in front of them, even in familiar environments. Furthermore, in unfamiliar environments, such people require guidance to reduce the risk of colliding with obstacles. This study proposes a simple smartphone-based guiding system for solving the navigation problems for visually impaired people and achieving obstacle avoidance to enable visually impaired people to travel smoothly from a beginning point to a destination with greater awareness of their surroundings. In this study, a computer image recognition system and smartphone application were integrated to form a simple assisted guiding system. Two operating modes, online mode and offline mode, can be chosen depending on network availability. When the system begins to operate, the smartphone captures the scene in front of the user and sends the captured images to the backend server to be processed. The backend server uses the faster region convolutional neural network algorithm or the you only look once algorithm to recognize multiple obstacles in every image, and it subsequently sends the results back to the smartphone. The results of obstacle recognition in this study reached 60%, which is sufficient for assisting visually impaired people in realizing the types and locations of obstacles around them. PMID:28608811

Simple Smartphone-Based Guiding System for Visually Impaired People.

PubMed

Lin, Bor-Shing; Lee, Cheng-Che; Chiang, Pei-Ying

2017-06-13

Visually impaired people are often unaware of dangers in front of them, even in familiar environments. Furthermore, in unfamiliar environments, such people require guidance to reduce the risk of colliding with obstacles. This study proposes a simple smartphone-based guiding system for solving the navigation problems for visually impaired people and achieving obstacle avoidance to enable visually impaired people to travel smoothly from a beginning point to a destination with greater awareness of their surroundings. In this study, a computer image recognition system and smartphone application were integrated to form a simple assisted guiding system. Two operating modes, online mode and offline mode, can be chosen depending on network availability. When the system begins to operate, the smartphone captures the scene in front of the user and sends the captured images to the backend server to be processed. The backend server uses the faster region convolutional neural network algorithm or the you only look once algorithm to recognize multiple obstacles in every image, and it subsequently sends the results back to the smartphone. The results of obstacle recognition in this study reached 60%, which is sufficient for assisting visually impaired people in realizing the types and locations of obstacles around them.

Virtual reality-based navigation task to reveal obstacle avoidance performance in individuals with visuospatial neglect.

PubMed

Aravind, Gayatri; Darekar, Anuja; Fung, Joyce; Lamontagne, Anouk

2015-03-01

Persons with post-stroke visuospatial neglect (VSN) often collide with moving obstacles while walking. It is not well understood whether the collisions occur as a result of attentional-perceptual deficits caused by VSN or due to post-stroke locomotor deficits. We assessed individuals with VSN on a seated, joystick-driven obstacle avoidance task, thus eliminating the influence of locomotion. Twelve participants with VSN were tested on obstacle detection and obstacle avoidance tasks in a virtual environment that included three obstacles approaching head-on or 30 (°) contralesionally/ipsilesionally. Our results indicate that in the detection task, the contralesional and head-on obstacles were detected at closer proximities compared to the ipsilesional obstacle. For the avoidance task collisions were observed only for the contralesional and head-on obstacle approaches. For the contralesional obstacle approach, participants initiated their avoidance strategies at smaller distances from the obstacle and maintained smaller minimum distances from the obstacles. The distance at detection showed a negative association with the distance at the onset of avoidance strategy for all three obstacle approaches. We conclusion the observation of collisions with contralesional and head-on obstacles, in the absence of locomotor burden, provides evidence that attentional-perceptual deficits due to VSN, independent of post-stroke locomotor deficits, alter obstacle avoidance abilities.

Application of Optical Flow Sensors for Dead Reckoning, Heading Reference, Obstacle Detection, and Obstacle Avoidance

DTIC Science & Technology

2015-09-01

OPTICAL FLOW SENSORS FOR DEAD RECKONING, HEADING REFERENCE, OBSTACLE DETECTION, AND OBSTACLE AVOIDANCE by Tarek M. Nejah September 2015...SENSORS FOR DEAD RECKONING, HEADING REFERENCE, OBSTACLE DETECTION, AND OBSTACLE AVOIDANCE 5. FUNDING NUMBERS 6. AUTHOR(S) Nejah, Tarek M. 7...DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) A novel approach for dead reckoning, heading reference, obstacle detection, and obstacle

Range Sensor-Based Efficient Obstacle Avoidance through Selective Decision-Making.

PubMed

Shim, Youngbo; Kim, Gon-Woo

2018-03-29

In this paper, we address a collision avoidance method for mobile robots. Many conventional obstacle avoidance methods have been focused solely on avoiding obstacles. However, this can cause instability when passing through a narrow passage, and can also generate zig-zag motions. We define two strategies for obstacle avoidance, known as Entry mode and Bypass mode. Entry mode is a pattern for passing through the gap between obstacles, while Bypass mode is a pattern for making a detour around obstacles safely. With these two modes, we propose an efficient obstacle avoidance method based on the Expanded Guide Circle (EGC) method with selective decision-making. The simulation and experiment results show the validity of the proposed method.

Grasping rigid objects in zero-g

NASA Astrophysics Data System (ADS)

Anderson, Greg D.

1993-12-01

The extra vehicular activity helper/retriever (EVAHR) is a prototype for an autonomous free- flying robotic astronaut helper. The ability to grasp a moving object is a fundamental skill required for any autonomous free-flyer. This paper discusses an algorithm that couples resolved acceleration control with potential field based obstacle avoidance to enable a manipulator to track and capture a rigid object in (imperfect) zero-g while avoiding joint limits, singular configurations, and unintentional impacts between the manipulator and the environment.

Optimal path planning for video-guided smart munitions via multitarget tracking

NASA Astrophysics Data System (ADS)

Borkowski, Jeffrey M.; Vasquez, Juan R.

2006-05-01

An advent in the development of smart munitions entails autonomously modifying target selection during flight in order to maximize the value of the target being destroyed. A unique guidance law can be constructed that exploits both attribute and kinematic data obtained from an onboard video sensor. An optimal path planning algorithm has been developed with the goals of obstacle avoidance and maximizing the value of the target impacted by the munition. Target identification and classification provides a basis for target value which is used in conjunction with multi-target tracks to determine an optimal waypoint for the munition. A dynamically feasible trajectory is computed to provide constraints on the waypoint selection. Results demonstrate the ability of the autonomous system to avoid moving obstacles and revise target selection in flight.

Development of collision avoidance system for useful UAV applications using image sensors with laser transmitter

NASA Astrophysics Data System (ADS)

Cheong, M. K.; Bahiki, M. R.; Azrad, S.

2016-10-01

The main goal of this study is to demonstrate the approach of achieving collision avoidance on Quadrotor Unmanned Aerial Vehicle (QUAV) using image sensors with colour- based tracking method. A pair of high definition (HD) stereo cameras were chosen as the stereo vision sensor to obtain depth data from flat object surfaces. Laser transmitter was utilized to project high contrast tracking spot for depth calculation using common triangulation. Stereo vision algorithm was developed to acquire the distance from tracked point to QUAV and the control algorithm was designed to manipulate QUAV's response based on depth calculated. Attitude and position controller were designed using the non-linear model with the help of Optitrack motion tracking system. A number of collision avoidance flight tests were carried out to validate the performance of the stereo vision and control algorithm based on image sensors. In the results, the UAV was able to hover with fairly good accuracy in both static and dynamic collision avoidance for short range collision avoidance. Collision avoidance performance of the UAV was better with obstacle of dull surfaces in comparison to shiny surfaces. The minimum collision avoidance distance achievable was 0.4 m. The approach was suitable to be applied in short range collision avoidance.

Low-Altitude Operation of Unmanned Rotorcraft

NASA Astrophysics Data System (ADS)

Scherer, Sebastian

Currently deployed unmanned rotorcraft rely on preplanned missions or teleoperation and do not actively incorporate information about obstacles, landing sites, wind, position uncertainty, and other aerial vehicles during online motion planning. Prior work has successfully addressed some tasks such as obstacle avoidance at slow speeds, or landing at known to be good locations. However, to enable autonomous missions in cluttered environments, the vehicle has to react quickly to previously unknown obstacles, respond to changing environmental conditions, and find unknown landing sites. We consider the problem of enabling autonomous operation at low-altitude with contributions to four problems. First we address the problem of fast obstacle avoidance for a small aerial vehicle and present results from over a 1000 rims at speeds up to 10 m/s. Fast response is achieved through a reactive algorithm whose response is learned based on observing a pilot. Second, we show an algorithm to update the obstacle cost expansion for path planning quickly and demonstrate it on a micro aerial vehicle, and an autonomous helicopter avoiding obstacles. Next, we examine the mission of finding a place to land near a ground goal. Good landing sites need to be detected and found and the final touch down goal is unknown. To detect the landing sites we convey a model based algorithm for landing sites that incorporates many helicopter relevant constraints such as landing sites, approach, abort, and ground paths in 3D range data. The landing site evaluation algorithm uses a patch-based coarse evaluation for slope and roughness, and a fine evaluation that fits a 3D model of the helicopter and landing gear to calculate a goodness measure. The data are evaluated in real-time to enable the helicopter to decide on a place to land. We show results from urban, vegetated, and desert environments, and demonstrate the first autonomous helicopter that selects its own landing sites. We present a generalized planning framework that enables reaching a goal point, searching for unknown landing sites, and approaching a landing zone. In the framework, sub-objective functions, constraints, and a state machine define the mission and behavior of an UAV. As the vehicle gathers information by moving through the environment, the objective functions account for this new information. The operator in this framework can directly specify his intent as an objective function that defines the mission rather than giving a sequence of pre-specified goal points. This allows the robot to react to new information received and adjust its path accordingly. The objective is used in a combined coarse planning and trajectory optimization algorithm to determine the best patch the robot should take. We show simulated results for several different missions and in particular focus on active landing zone search. We presented several effective approaches for perception and action for low-altitude flight and demonstrated their effectiveness in field experiments on three autonomous aerial vehicles: a 1m quadrocopter, a 36m helicopter, and a hill-size helicopter. These techniques permit rotorcraft to operate where they have their greatest advantage: In unstructured, unknown environments at low-altitude.

SGM-based seamline determination for urban orthophoto mosaicking

NASA Astrophysics Data System (ADS)

Pang, Shiyan; Sun, Mingwei; Hu, Xiangyun; Zhang, Zuxun

2016-02-01

Mosaicking is a key step in the production of digital orthophoto maps (DOMs), especially for large-scale urban orthophotos. During this step, manual intervention is commonly involved to avoid the case where the seamline crosses obvious objects (e.g., buildings), which causes geometric discontinuities on the DOMs. How to guide the seamline to avoid crossing obvious objects has become a popular topic in the field of photogrammetry and remote sensing. Thus, a new semi-global matching (SGM)-based method to guide seamline determination is proposed for urban orthophoto mosaicking in this study, which can greatly eliminate geometric discontinuities. The approximate epipolar geometry of the orthophoto pairs is first derived and proven, and the approximate epipolar image pair is then generated by rotating the two orthorectified images according to the parallax direction. A SGM algorithm is applied to their overlaps to obtain the corresponding pixel-wise disparity. According to a predefined disparity threshold, the overlap area is identified as the obstacle and non-obstacle areas. For the non-obstacle regions, Hilditch thinning algorithm is used to obtain the skeleton line, followed by Dijkstra's algorithm to search for the optimal path on the skeleton network as the seamline between two orthophotos. A whole seamline network is constructed based on the strip information recorded in flight. In the experimental section, the approximate epipolar geometric theory of the orthophoto is first analyzed and verified, and the effectiveness of the proposed method is then validated by comparing its results with the results of the geometry-based, OrthoVista, and orthoimage elevation synchronous model (OESM)-based methods.

Asymptotically Optimal Motion Planning for Learned Tasks Using Time-Dependent Cost Maps

PubMed Central

Bowen, Chris; Ye, Gu; Alterovitz, Ron

2015-01-01

In unstructured environments in people’s homes and workspaces, robots executing a task may need to avoid obstacles while satisfying task motion constraints, e.g., keeping a plate of food level to avoid spills or properly orienting a finger to push a button. We introduce a sampling-based method for computing motion plans that are collision-free and minimize a cost metric that encodes task motion constraints. Our time-dependent cost metric, learned from a set of demonstrations, encodes features of a task’s motion that are consistent across the demonstrations and, hence, are likely required to successfully execute the task. Our sampling-based motion planner uses the learned cost metric to compute plans that simultaneously avoid obstacles and satisfy task constraints. The motion planner is asymptotically optimal and minimizes the Mahalanobis distance between the planned trajectory and the distribution of demonstrations in a feature space parameterized by the locations of task-relevant objects. The motion planner also leverages the distribution of the demonstrations to significantly reduce plan computation time. We demonstrate the method’s effectiveness and speed using a small humanoid robot performing tasks requiring both obstacle avoidance and satisfaction of learned task constraints. Note to Practitioners Motivated by the desire to enable robots to autonomously operate in cluttered home and workplace environments, this paper presents an approach for intuitively training a robot in a manner that enables it to repeat the task in novel scenarios and in the presence of unforeseen obstacles in the environment. Based on user-provided demonstrations of the task, our method learns features of the task that are consistent across the demonstrations and that we expect should be repeated by the robot when performing the task. We next present an efficient algorithm for planning robot motions to perform the task based on the learned features while avoiding obstacles. We demonstrate the effectiveness of our motion planner for scenarios requiring transferring a powder and pushing a button in environments with obstacles, and we plan to extend our results to more complex tasks in the future. PMID:26279642

Formation control of robotic swarm using bounded artificial forces.

PubMed

Qin, Long; Zha, Yabing; Yin, Quanjun; Peng, Yong

2013-01-01

Formation control of multirobot systems has drawn significant attention in the recent years. This paper presents a potential field control algorithm, navigating a swarm of robots into a predefined 2D shape while avoiding intermember collisions. The algorithm applies in both stationary and moving targets formation. We define the bounded artificial forces in the form of exponential functions, so that the behavior of the swarm drove by the forces can be adjusted via selecting proper control parameters. The theoretical analysis of the swarm behavior proves the stability and convergence properties of the algorithm. We further make certain modifications upon the forces to improve the robustness of the swarm behavior in the presence of realistic implementation considerations. The considerations include obstacle avoidance, local minima, and deformation of the shape. Finally, detailed simulation results validate the efficiency of the proposed algorithm, and the direction of possible futrue work is discussed in the conclusions.

Formation Control of Robotic Swarm Using Bounded Artificial Forces

PubMed Central

Zha, Yabing; Peng, Yong

2013-01-01

Formation control of multirobot systems has drawn significant attention in the recent years. This paper presents a potential field control algorithm, navigating a swarm of robots into a predefined 2D shape while avoiding intermember collisions. The algorithm applies in both stationary and moving targets formation. We define the bounded artificial forces in the form of exponential functions, so that the behavior of the swarm drove by the forces can be adjusted via selecting proper control parameters. The theoretical analysis of the swarm behavior proves the stability and convergence properties of the algorithm. We further make certain modifications upon the forces to improve the robustness of the swarm behavior in the presence of realistic implementation considerations. The considerations include obstacle avoidance, local minima, and deformation of the shape. Finally, detailed simulation results validate the efficiency of the proposed algorithm, and the direction of possible futrue work is discussed in the conclusions. PMID:24453809

Obstacle Detection using Binocular Stereo Vision in Trajectory Planning for Quadcopter Navigation

NASA Astrophysics Data System (ADS)

Bugayong, Albert; Ramos, Manuel, Jr.

2018-02-01

Quadcopters are one of the most versatile unmanned aerial vehicles due to its vertical take-off and landing as well as hovering capabilities. This research uses the Sum of Absolute Differences (SAD) block matching algorithm for stereo vision. A complementary filter was used in sensor fusion to combine obtained quadcopter orientation data from the accelerometer and the gyroscope. PID control was implemented for the motor control and VFH+ algorithm was implemented for trajectory planning. Results show that the quadcopter was able to consistently actuate itself in the roll, yaw and z-axis during obstacle avoidance but was however found to be inconsistent in the pitch axis during forward and backward maneuvers due to the significant noise present in the pitch axis angle outputs compared to the roll and yaw axes.

Multi-AUV Target Search Based on Bioinspired Neurodynamics Model in 3-D Underwater Environments.

PubMed

Cao, Xiang; Zhu, Daqi; Yang, Simon X

2016-11-01

Target search in 3-D underwater environments is a challenge in multiple autonomous underwater vehicles (multi-AUVs) exploration. This paper focuses on an effective strategy for multi-AUV target search in the 3-D underwater environments with obstacles. First, the Dempster-Shafer theory of evidence is applied to extract information of environment from the sonar data to build a grid map of the underwater environments. Second, a topologically organized bioinspired neurodynamics model based on the grid map is constructed to represent the dynamic environment. The target globally attracts the AUVs through the dynamic neural activity landscape of the model, while the obstacles locally push the AUVs away to avoid collision. Finally, the AUVs plan their search path to the targets autonomously by a steepest gradient descent rule. The proposed algorithm deals with various situations, such as static targets search, dynamic targets search, and one or several AUVs break down in the 3-D underwater environments with obstacles. The simulation results show that the proposed algorithm is capable of guiding multi-AUV to achieve search task of multiple targets with higher efficiency and adaptability compared with other algorithms.

Obstacle avoidance handling and mixed integer predictive control for space robots

NASA Astrophysics Data System (ADS)

Zong, Lijun; Luo, Jianjun; Wang, Mingming; Yuan, Jianping

2018-04-01

This paper presents a novel obstacle avoidance constraint and a mixed integer predictive control (MIPC) method for space robots avoiding obstacles and satisfying physical limits during performing tasks. Firstly, a novel kind of obstacle avoidance constraint of space robots, which needs the assumption that the manipulator links and the obstacles can be represented by convex bodies, is proposed by limiting the relative velocity between two closest points which are on the manipulator and the obstacle, respectively. Furthermore, the logical variables are introduced into the obstacle avoidance constraint, which have realized the constraint form is automatically changed to satisfy different obstacle avoidance requirements in different distance intervals between the space robot and the obstacle. Afterwards, the obstacle avoidance constraint and other system physical limits, such as joint angle ranges, the amplitude boundaries of joint velocities and joint torques, are described as inequality constraints of a quadratic programming (QP) problem by using the model predictive control (MPC) method. To guarantee the feasibility of the obtained multi-constraint QP problem, the constraints are treated as soft constraints and assigned levels of priority based on the propositional logic theory, which can realize that the constraints with lower priorities are always firstly violated to recover the feasibility of the QP problem. Since the logical variables have been introduced, the optimization problem including obstacle avoidance and system physical limits as prioritized inequality constraints is termed as MIPC method of space robots, and its computational complexity as well as possible strategies for reducing calculation amount are analyzed. Simulations of the space robot unfolding its manipulator and tracking the end-effector's desired trajectories with the existence of obstacles and physical limits are presented to demonstrate the effectiveness of the proposed obstacle avoidance strategy and MIPC control method of space robots.

Obstacle Avoidance for Quadcopter using Ultrasonic Sensor

NASA Astrophysics Data System (ADS)

Fazlur Rahman, Muhammad; Adhy Sasongko, Rianto

2018-04-01

An obstacle avoidance system is being proposed. The system will combine available flight controller with a proposed avoidance method as a proof of concept. Quadcopter as a UAV is integrated with the system which consist of several modes in order to do avoidance. As the previous study, obstacle will be determined using ultrasonic sensor and servo. As result, the quadcopter will move according to its mode and successfully avoid obstacle.

Implementation of Autonomous Navigation and Mapping using a Laser Line Scanner on a Tactical Unmanned Aerial Vehicle

DTIC Science & Technology

2011-12-01

study new multi-agent algorithms to avoid collision and obstacles. Others, including Hanford et al. [2], have tried to build low-cost experimental...2007. [2] S. D. Hanford , L. N. Long, and J. F. Horn, “A Small Semi-Autonomous Rotary-Wing Unmanned Air Vehicle ( UAV ),” 2003 AIAA Atmospheric

Constrained navigation for unmanned systems

NASA Astrophysics Data System (ADS)

Vasseur, Laurent; Gosset, Philippe; Carpentier, Luc; Marion, Vincent; Morillon, Joel G.; Ropars, Patrice

2005-05-01

The French Military Robotic Study Program (introduced in Aerosense 2003), sponsored by the French Defense Procurement Agency and managed by Thales as the prime contractor, focuses on about 15 robotic themes which can provide an immediate "operational add-on value". The paper details the "constrained navigation" study (named TEL2), which main goal is to identify and test a well-balanced task sharing between man and machine to accomplish a robotic task that cannot be performed autonomously at the moment because of technological limitations. The chosen function is "obstacle avoidance" on rough ground and quite high speed (40 km/h). State of the art algorithms have been implemented to perform autonomous obstacle avoidance and following of forest borders, using scanner laser sensor and standard localization functions. Such an "obstacle avoidance" function works well most of the time, BUT fails sometimes. The study analyzed how the remote operator can manage such failures so that the system remains fully operationally reliable; he can act according to two ways: a) finely adjust the vehicle current heading; b) take the control of the vehicle "on the fly" (without stopping) and bring it back to autonomous behavior when motion is secured again. The paper also presents the results got from the military acceptance tests performed on French 4x4 DARDS ATD.

Optimizing Design Parameters for Sets of Concentric Tube Robots using Sampling-based Motion Planning

PubMed Central

Baykal, Cenk; Torres, Luis G.; Alterovitz, Ron

2015-01-01

Concentric tube robots are tentacle-like medical robots that can bend around anatomical obstacles to access hard-to-reach clinical targets. The component tubes of these robots can be swapped prior to performing a task in order to customize the robot’s behavior and reachable workspace. Optimizing a robot’s design by appropriately selecting tube parameters can improve the robot’s effectiveness on a procedure-and patient-specific basis. In this paper, we present an algorithm that generates sets of concentric tube robot designs that can collectively maximize the reachable percentage of a given goal region in the human body. Our algorithm combines a search in the design space of a concentric tube robot using a global optimization method with a sampling-based motion planner in the robot’s configuration space in order to find sets of designs that enable motions to goal regions while avoiding contact with anatomical obstacles. We demonstrate the effectiveness of our algorithm in a simulated scenario based on lung anatomy. PMID:26951790

Optimizing Design Parameters for Sets of Concentric Tube Robots using Sampling-based Motion Planning.

PubMed

Baykal, Cenk; Torres, Luis G; Alterovitz, Ron

2015-09-28

Concentric tube robots are tentacle-like medical robots that can bend around anatomical obstacles to access hard-to-reach clinical targets. The component tubes of these robots can be swapped prior to performing a task in order to customize the robot's behavior and reachable workspace. Optimizing a robot's design by appropriately selecting tube parameters can improve the robot's effectiveness on a procedure-and patient-specific basis. In this paper, we present an algorithm that generates sets of concentric tube robot designs that can collectively maximize the reachable percentage of a given goal region in the human body. Our algorithm combines a search in the design space of a concentric tube robot using a global optimization method with a sampling-based motion planner in the robot's configuration space in order to find sets of designs that enable motions to goal regions while avoiding contact with anatomical obstacles. We demonstrate the effectiveness of our algorithm in a simulated scenario based on lung anatomy.

Development of a Guide-Dog Robot: Leading and Recognizing a Visually-Handicapped Person using a LRF

NASA Astrophysics Data System (ADS)

Saegusa, Shozo; Yasuda, Yuya; Uratani, Yoshitaka; Tanaka, Eiichirou; Makino, Toshiaki; Chang, Jen-Yuan (James

A conceptual Guide-Dog Robot prototype to lead and to recognize a visually-handicapped person is developed and discussed in this paper. Key design features of the robot include a movable platform, human-machine interface, and capability of avoiding obstacles. A novel algorithm enabling the robot to recognize its follower's locomotion as well to detect the center of corridor is proposed and implemented in the robot's human-machine interface. It is demonstrated that using the proposed novel leading and detecting algorithm along with a rapid scanning laser range finder (LRF) sensor, the robot is able to successfully and effectively lead a human walking in corridor without running into obstacles such as trash boxes or adjacent walking persons. Position and trajectory of the robot leading a human maneuvering in common corridor environment are measured by an independent LRF observer. The measured data suggest that the proposed algorithms are effective to enable the robot to detect center of the corridor and position of its follower correctly.

A biomimetic, energy-harvesting, obstacle-avoiding, path-planning algorithm for UAVs

NASA Astrophysics Data System (ADS)

Gudmundsson, Snorri

This dissertation presents two new approaches to energy harvesting for Unmanned Aerial Vehicles (UAV). One method is based on the Potential Flow Method (PFM); the other method seeds a wind-field map based on updraft peak analysis and then applies a variant of the Bellman-Ford algorithm to find the minimum-cost path. Both methods are enhanced by taking into account the performance characteristics of the aircraft using advanced performance theory. The combined approach yields five possible trajectories from which the one with the minimum energy cost is selected. The dissertation concludes by using the developed theory and modeling tools to simulate the flight paths of two small Unmanned Aerial Vehicles (sUAV) in the 500 kg and 250 kg class. The results show that, in mountainous regions, substantial energy can be recovered, depending on topography and wind characteristics. For the examples presented, as much as 50% of the energy was recovered for a complex, multi-heading, multi-altitude, 170 km mission in an average wind speed of 9 m/s. The algorithms constitute a Generic Intelligent Control Algorithm (GICA) for autonomous unmanned aerial vehicles that enables an extraction of atmospheric energy while completing a mission trajectory. At the same time, the algorithm. automatically adjusts the flight path in order to avoid obstacles, in a fashion not unlike what one would expect from living organisms, such as birds and insects. This multi-disciplinary approach renders the approach biomimetic, i.e. it constitutes a synthetic system that “mimics the formation and function of biological mechanisms and processes.”.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kurt Derr

Mobile Ad hoc NETworks (MANETs) are distributed self-organizing networks that can change locations and configure themselves on the fly. This paper focuses on an algorithmic approach for the deployment of a MANET within an enclosed area, such as a building in a disaster scenario, which can provide a robust communication infrastructure for search and rescue operations. While a virtual spring mesh (VSM) algorithm provides scalable, self-organizing, and fault-tolerant capabilities required by aMANET, the VSM lacks the MANET's capabilities of deployment mechanisms for blanket coverage of an area and does not provide an obstacle avoidance mechanism. This paper presents a newmore » technique, an extended VSM (EVSM) algorithm that provides the following novelties: (1) new control laws for exploration and expansion to provide blanket coverage, (2) virtual adaptive springs enabling the mesh to expand as necessary, (3) adapts to communications disturbances by varying the density and movement of mobile nodes, and (4) new metrics to assess the performance of the EVSM algorithm. Simulation results show that EVSM provides up to 16% more coverage and is 3.5 times faster than VSM in environments with eight obstacles.« less

Autonomous Navigation by a Mobile Robot

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Aghazarian, Hrand

2005-01-01

ROAMAN is a computer program for autonomous navigation of a mobile robot on a long (as much as hundreds of meters) traversal of terrain. Developed for use aboard a robotic vehicle (rover) exploring the surface of a remote planet, ROAMAN could also be adapted to similar use on terrestrial mobile robots. ROAMAN implements a combination of algorithms for (1) long-range path planning based on images acquired by mast-mounted, wide-baseline stereoscopic cameras, and (2) local path planning based on images acquired by body-mounted, narrow-baseline stereoscopic cameras. The long-range path-planning algorithm autonomously generates a series of waypoints that are passed to the local path-planning algorithm, which plans obstacle-avoiding legs between the waypoints. Both the long- and short-range algorithms use an occupancy-grid representation in computations to detect obstacles and plan paths. Maps that are maintained by the long- and short-range portions of the software are not shared because substantial localization errors can accumulate during any long traverse. ROAMAN is not guaranteed to generate an optimal shortest path, but does maintain the safety of the rover.

Three-dimensional obstacle classification in laser range data

NASA Astrophysics Data System (ADS)

Armbruster, Walter; Bers, Karl-Heinz

1998-10-01

The threat of hostile surveillance and weapon systems require military aircraft to fly under extreme conditions such as low altitude, high speed, poor visibility and incomplete terrain information. The probability of collision with natural and man-made obstacles during such contour missions is high if detection capability is restricted to conventional vision aids. Forward-looking scanning laser rangefinders which are presently being flight tested and evaluated at German proving grounds, provide a possible solution, having a large field of view, high angular and range resolution, a high pulse repetition rate, and sufficient pulse energy to register returns from wires at over 500 m range (depends on the system) with a high hit-and-detect probability. Despite the efficiency of the sensor, acceptance of current obstacle warning systems by test pilots is not very high, mainly due to the systems' inadequacies in obstacle recognition and visualization. This has motivated the development and the testing of more advanced 3d-scene analysis algorithm at FGAN-FIM to replace the obstacle recognition component of current warning systems. The basic ideas are to increase the recognition probability and to reduce the false alarm rate for hard-to-extract obstacles such as wires, by using more readily recognizable objects such as terrain, poles, pylons, trees, etc. by implementing a hierarchical classification procedure to generate a parametric description of the terrain surface as well as the class, position, orientation, size and shape of all objects in the scene. The algorithms can be used for other applications such as terrain following, autonomous obstacle avoidance, and automatic target recognition.

Strategies for obstacle avoidance during walking in the cat.

PubMed

Chu, Kevin M I; Seto, Sandy H; Beloozerova, Irina N; Marlinski, Vladimir

2017-08-01

Avoiding obstacles is essential for successful navigation through complex environments. This study aimed to clarify what strategies are used by a typical quadruped, the cat, to avoid obstacles during walking. Four cats walked along a corridor 2.5 m long and 25 or 15 cm wide. Obstacles, small round objects 2.5 cm in diameter and 1 cm in height, were placed on the floor in various locations. Movements of the paw were recorded with a motion capture and analysis system (Visualeyez, PTI). During walking in the wide corridor, cats' preferred strategy for avoiding a single obstacle was circumvention, during which the stride direction changed while stride duration and swing-to-stride duration ratio were preserved. Another strategy, stepping over the obstacle, was used during walking in the narrow corridor, when lateral deviations of walking trajectory were restricted. Stepping over the obstacle involved changes in two consecutive strides. The stride preceding the obstacle was shortened, and swing-to-stride ratio was reduced. The obstacle was negotiated in the next stride of increased height and normal duration and swing-to-stride ratio. During walking on a surface with multiple obstacles, both strategies were used. To avoid contact with the obstacle, cats placed the paw away from the object at a distance roughly equal to the diameter of the paw. During obstacle avoidance cats prefer to alter muscle activities without altering the locomotor rhythm. We hypothesize that a choice of the strategy for obstacle avoidance is determined by minimizing the complexity of neuro-motor processes required to achieve the behavioral goal. NEW & NOTEWORTHY In a study of feline locomotor behavior we found that the preferred strategy to avoid a small obstacle is circumvention. During circumvention, stride direction changes but length and temporal structure are preserved. Another strategy, stepping over the obstacle, is used in narrow walkways. During overstepping, two strides adjust. A stride preceding the obstacle decreases in length and duration. The following stride negotiating the obstacle increases in height while retaining normal temporal structure and nearly normal length. Copyright © 2017 the American Physiological Society.

Algorithms for Collision Detection Between a Point and a Moving Polygon, with Applications to Aircraft Weather Avoidance

NASA Technical Reports Server (NTRS)

Narkawicz, Anthony; Hagen, George

2016-01-01

This paper proposes mathematical definitions of functions that can be used to detect future collisions between a point and a moving polygon. The intended application is weather avoidance, where the given point represents an aircraft and bounding polygons are chosen to model regions with bad weather. Other applications could possibly include avoiding other moving obstacles. The motivation for the functions presented here is safety, and therefore they have been proved to be mathematically correct. The functions are being developed for inclusion in NASA's Stratway software tool, which allows low-fidelity air traffic management concepts to be easily prototyped and quickly tested.

Dynamic Obstacle Avoidance for Unmanned Underwater Vehicles Based on an Improved Velocity Obstacle Method

PubMed Central

Zhang, Wei; Wei, Shilin; Teng, Yanbin; Zhang, Jianku; Wang, Xiufang; Yan, Zheping

2017-01-01

In view of a dynamic obstacle environment with motion uncertainty, we present a dynamic collision avoidance method based on the collision risk assessment and improved velocity obstacle method. First, through the fusion optimization of forward-looking sonar data, the redundancy of the data is reduced and the position, size and velocity information of the obstacles are obtained, which can provide an accurate decision-making basis for next-step collision avoidance. Second, according to minimum meeting time and the minimum distance between the obstacle and unmanned underwater vehicle (UUV), this paper establishes the collision risk assessment model, and screens key obstacles to avoid collision. Finally, the optimization objective function is established based on the improved velocity obstacle method, and a UUV motion characteristic is used to calculate the reachable velocity sets. The optimal collision speed of UUV is searched in velocity space. The corresponding heading and speed commands are calculated, and outputted to the motion control module. The above is the complete dynamic obstacle avoidance process. The simulation results show that the proposed method can obtain a better collision avoidance effect in the dynamic environment, and has good adaptability to the unknown dynamic environment. PMID:29186878

Navigation and Self-Semantic Location of Drones in Indoor Environments by Combining the Visual Bug Algorithm and Entropy-Based Vision.

PubMed

Maravall, Darío; de Lope, Javier; Fuentes, Juan P

2017-01-01

We introduce a hybrid algorithm for the self-semantic location and autonomous navigation of robots using entropy-based vision and visual topological maps. In visual topological maps the visual landmarks are considered as leave points for guiding the robot to reach a target point (robot homing) in indoor environments. These visual landmarks are defined from images of relevant objects or characteristic scenes in the environment. The entropy of an image is directly related to the presence of a unique object or the presence of several different objects inside it: the lower the entropy the higher the probability of containing a single object inside it and, conversely, the higher the entropy the higher the probability of containing several objects inside it. Consequently, we propose the use of the entropy of images captured by the robot not only for the landmark searching and detection but also for obstacle avoidance. If the detected object corresponds to a landmark, the robot uses the suggestions stored in the visual topological map to reach the next landmark or to finish the mission. Otherwise, the robot considers the object as an obstacle and starts a collision avoidance maneuver. In order to validate the proposal we have defined an experimental framework in which the visual bug algorithm is used by an Unmanned Aerial Vehicle (UAV) in typical indoor navigation tasks.

Navigation and Self-Semantic Location of Drones in Indoor Environments by Combining the Visual Bug Algorithm and Entropy-Based Vision

PubMed Central

Maravall, Darío; de Lope, Javier; Fuentes, Juan P.

2017-01-01

We introduce a hybrid algorithm for the self-semantic location and autonomous navigation of robots using entropy-based vision and visual topological maps. In visual topological maps the visual landmarks are considered as leave points for guiding the robot to reach a target point (robot homing) in indoor environments. These visual landmarks are defined from images of relevant objects or characteristic scenes in the environment. The entropy of an image is directly related to the presence of a unique object or the presence of several different objects inside it: the lower the entropy the higher the probability of containing a single object inside it and, conversely, the higher the entropy the higher the probability of containing several objects inside it. Consequently, we propose the use of the entropy of images captured by the robot not only for the landmark searching and detection but also for obstacle avoidance. If the detected object corresponds to a landmark, the robot uses the suggestions stored in the visual topological map to reach the next landmark or to finish the mission. Otherwise, the robot considers the object as an obstacle and starts a collision avoidance maneuver. In order to validate the proposal we have defined an experimental framework in which the visual bug algorithm is used by an Unmanned Aerial Vehicle (UAV) in typical indoor navigation tasks. PMID:28900394

Advanced computer graphic techniques for laser range finder (LRF) simulation

NASA Astrophysics Data System (ADS)

Bedkowski, Janusz; Jankowski, Stanislaw

2008-11-01

This paper show an advanced computer graphic techniques for laser range finder (LRF) simulation. The LRF is the common sensor for unmanned ground vehicle, autonomous mobile robot and security applications. The cost of the measurement system is extremely high, therefore the simulation tool is designed. The simulation gives an opportunity to execute algorithm such as the obstacle avoidance[1], slam for robot localization[2], detection of vegetation and water obstacles in surroundings of the robot chassis[3], LRF measurement in crowd of people[1]. The Axis Aligned Bounding Box (AABB) and alternative technique based on CUDA (NVIDIA Compute Unified Device Architecture) is presented.

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm.

PubMed

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability.

Dynamic path planning for mobile robot based on particle swarm optimization

NASA Astrophysics Data System (ADS)

Wang, Yong; Cai, Feng; Wang, Ying

2017-08-01

In the contemporary, robots are used in many fields, such as cleaning, medical treatment, space exploration, disaster relief and so on. The dynamic path planning of robot without collision is becoming more and more the focus of people's attention. A new method of path planning is proposed in this paper. Firstly, the motion space model of the robot is established by using the MAKLINK graph method. Then the A* algorithm is used to get the shortest path from the start point to the end point. Secondly, this paper proposes an effective method to detect and avoid obstacles. When an obstacle is detected on the shortest path, the robot will choose the nearest safety point to move. Moreover, calculate the next point which is nearest to the target. Finally, the particle swarm optimization algorithm is used to optimize the path. The experimental results can prove that the proposed method is more effective.

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm

PubMed Central

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability. PMID:26880881

A nonlinear model predictive control formulation for obstacle avoidance in high-speed autonomous ground vehicles in unstructured environments

NASA Astrophysics Data System (ADS)

Liu, Jiechao; Jayakumar, Paramsothy; Stein, Jeffrey L.; Ersal, Tulga

2018-06-01

This paper presents a nonlinear model predictive control (MPC) formulation for obstacle avoidance in high-speed, large-size autono-mous ground vehicles (AGVs) with high centre of gravity (CoG) that operate in unstructured environments, such as military vehicles. The term 'unstructured' in this context denotes that there are no lanes or traffic rules to follow. Existing MPC formulations for passenger vehicles in structured environments do not readily apply to this context. Thus, a new nonlinear MPC formulation is developed to navigate an AGV from its initial position to a target position at high-speed safely. First, a new cost function formulation is used that aims to find the shortest path to the target position, since no reference trajectory exists in unstructured environments. Second, a region partitioning approach is used in conjunction with a multi-phase optimal control formulation to accommodate the complicated forms the obstacle-free region can assume due to the presence of multiple obstacles in the prediction horizon in an unstructured environment. Third, the no-wheel-lift-off condition, which is the major dynamical safety concern for high-speed, high-CoG AGVs, is ensured by limiting the steering angle within a range obtained offline using a 14 degrees-of-freedom vehicle dynamics model. Thus, a safe, high-speed navigation is enabled in an unstructured environment. Simulations of an AGV approaching multiple obstacles are provided to demonstrate the effectiveness of the algorithm.

A novel artificial immune algorithm for spatial clustering with obstacle constraint and its applications.

PubMed

Sun, Liping; Luo, Yonglong; Ding, Xintao; Zhang, Ji

2014-01-01

An important component of a spatial clustering algorithm is the distance measure between sample points in object space. In this paper, the traditional Euclidean distance measure is replaced with innovative obstacle distance measure for spatial clustering under obstacle constraints. Firstly, we present a path searching algorithm to approximate the obstacle distance between two points for dealing with obstacles and facilitators. Taking obstacle distance as similarity metric, we subsequently propose the artificial immune clustering with obstacle entity (AICOE) algorithm for clustering spatial point data in the presence of obstacles and facilitators. Finally, the paper presents a comparative analysis of AICOE algorithm and the classical clustering algorithms. Our clustering model based on artificial immune system is also applied to the case of public facility location problem in order to establish the practical applicability of our approach. By using the clone selection principle and updating the cluster centers based on the elite antibodies, the AICOE algorithm is able to achieve the global optimum and better clustering effect.

Healthy young adults implement distinctive avoidance strategies while walking and circumventing virtual human vs. non-human obstacles in a virtual environment.

PubMed

Souza Silva, Wagner; Aravind, Gayatri; Sangani, Samir; Lamontagne, Anouk

2018-03-01

This study examines how three types of obstacles (cylinder, virtual human and virtual human with footstep sounds) affect circumvention strategies of healthy young adults. Sixteen participants aged 25.2 ± 2.5 years (mean ± 1SD) were tested while walking overground and viewing a virtual room through a helmet mounted display. As participants walked towards a stationary target in the far space, they avoided an obstacle (cylinder or virtual human) approaching either from the right (+40°), left (-40°) or head-on (0°). Obstacle avoidance strategies were characterized using the position and orientation of the head. Repeated mixed model analysis showed smaller minimal distances (p = 0.007) while avoiding virtual humans as compared to cylinders. Footstep sounds added to virtual humans did not modify (p = 0.2) minimal distances compared to when no sound was provided. Onset times of avoidance strategies were similar across conditions (p = 0.06). Results indicate that the nature of the obstacle (human-like vs. non-human object) matters and can modify avoidance strategies. Smaller obstacle clearances in response to virtual humans may reflect the use of a less conservative avoidance strategy, due to a resemblance of obstacles to pedestrians and a recall of strategies used in daily locomotion. The lack of influence of footstep sounds supports the fact that obstacle avoidance primarily relies on visual cues and the principle of 'inverse effectiveness' whereby multisensory neurons' response to multimodal stimuli becomes weaker when the unimodal sensory stimulus (vision) is strong. Present findings should be taken into consideration to optimize the ecological validity of VR-based obstacle avoidance paradigms used in research and rehabilitation. Copyright © 2018 Elsevier B.V. All rights reserved.

Using Collision Cones to Asses Biological Deconiction Methods

NASA Astrophysics Data System (ADS)

Brace, Natalie

For autonomous vehicles to navigate the world as efficiently and effectively as biological species, improvements are needed in terms of control strategies and estimation algorithms. Reactive collision avoidance is one specific area where biological systems outperform engineered algorithms. To better understand the discrepancy between engineered and biological systems, a collision avoidance algorithm was applied to frames of trajectory data from three biological species (Myotis velifer, Hirundo rustica, and Danio aequipinnatus). The algorithm uses information that can be sensed through visual cues (relative position and velocity) to define collision cones which are used to determine if agents are on a collision course and if so, to find a safe velocity that requires minimal deviation from the original velocity for each individual agent. Two- and three-dimensional versions of the algorithm with constant speed and maximum speed velocity requirements were considered. The obstacles provided to the algorithm were determined by the sensing range in terms of either metric or topological distance. The calculated velocities showed good correlation with observed velocities over the range of sensing parameters, indicating that the algorithm is a good basis for comparison and could potentially be improved with further study.

A parallel implementation of a multisensor feature-based range-estimation method

NASA Technical Reports Server (NTRS)

Suorsa, Raymond E.; Sridhar, Banavar

1993-01-01

There are many proposed vision based methods to perform obstacle detection and avoidance for autonomous or semi-autonomous vehicles. All methods, however, will require very high processing rates to achieve real time performance. A system capable of supporting autonomous helicopter navigation will need to extract obstacle information from imagery at rates varying from ten frames per second to thirty or more frames per second depending on the vehicle speed. Such a system will need to sustain billions of operations per second. To reach such high processing rates using current technology, a parallel implementation of the obstacle detection/ranging method is required. This paper describes an efficient and flexible parallel implementation of a multisensor feature-based range-estimation algorithm, targeted for helicopter flight, realized on both a distributed-memory and shared-memory parallel computer.

Trust-based learning and behaviors for convoy obstacle avoidance

NASA Astrophysics Data System (ADS)

Mikulski, Dariusz G.; Karlsen, Robert E.

2015-05-01

In many multi-agent systems, robots within the same team are regarded as being fully trustworthy for cooperative tasks. However, the assumption of trustworthiness is not always justified, which may not only increase the risk of mission failure, but also endanger the lives of friendly forces. In prior work, we addressed this issue by using RoboTrust to dynamically adjust to observed behaviors or recommendations in order to mitigate the risks of illegitimate behaviors. However, in the simulations in prior work, all members of the convoy had knowledge of the convoy goal. In this paper, only the lead vehicle has knowledge of the convoy goals and the follow vehicles must infer trustworthiness strictly from lead vehicle performance. In addition, RoboTrust could only respond to observed performance and did not dynamically learn agent behavior. In this paper, we incorporate an adaptive agent-specific bias into the RoboTrust algorithm that modifies its trust dynamics. This bias is learned incrementally from agent interactions, allowing good agents to benefit from faster trust growth and slower trust decay and bad agents to be penalized with slower trust growth and faster trust decay. We then integrate this new trust model into a trust-based controller for decentralized autonomous convoy operations. We evaluate its performance in an obstacle avoidance mission, where the convoy attempts to learn the best speed and following distances combinations for an acceptable obstacle avoidance probability.

Learning robotic eye-arm-hand coordination from human demonstration: a coupled dynamical systems approach.

PubMed

Lukic, Luka; Santos-Victor, José; Billard, Aude

2014-04-01

We investigate the role of obstacle avoidance in visually guided reaching and grasping movements. We report on a human study in which subjects performed prehensile motion with obstacle avoidance where the position of the obstacle was systematically varied across trials. These experiments suggest that reaching with obstacle avoidance is organized in a sequential manner, where the obstacle acts as an intermediary target. Furthermore, we demonstrate that the notion of workspace travelled by the hand is embedded explicitly in a forward planning scheme, which is actively involved in detecting obstacles on the way when performing reaching. We find that the gaze proactively coordinates the pattern of eye-arm motion during obstacle avoidance. This study provides also a quantitative assessment of the coupling between the eye-arm-hand motion. We show that the coupling follows regular phase dependencies and is unaltered during obstacle avoidance. These observations provide a basis for the design of a computational model. Our controller extends the coupled dynamical systems framework and provides fast and synchronous control of the eyes, the arm and the hand within a single and compact framework, mimicking similar control system found in humans. We validate our model for visuomotor control of a humanoid robot.

Multiple-camera/motion stereoscopy for range estimation in helicopter flight

NASA Technical Reports Server (NTRS)

Smith, Phillip N.; Sridhar, Banavar; Suorsa, Raymond E.

1993-01-01

Aiding the pilot to improve safety and reduce pilot workload by detecting obstacles and planning obstacle-free flight paths during low-altitude helicopter flight is desirable. Computer vision techniques provide an attractive method of obstacle detection and range estimation for objects within a large field of view ahead of the helicopter. Previous research has had considerable success by using an image sequence from a single moving camera to solving this problem. The major limitations of single camera approaches are that no range information can be obtained near the instantaneous direction of motion or in the absence of motion. These limitations can be overcome through the use of multiple cameras. This paper presents a hybrid motion/stereo algorithm which allows range refinement through recursive range estimation while avoiding loss of range information in the direction of travel. A feature-based approach is used to track objects between image frames. An extended Kalman filter combines knowledge of the camera motion and measurements of a feature's image location to recursively estimate the feature's range and to predict its location in future images. Performance of the algorithm will be illustrated using an image sequence, motion information, and independent range measurements from a low-altitude helicopter flight experiment.

Reflexive obstacle avoidance for kinematically-redundant manipulators

NASA Technical Reports Server (NTRS)

Karlen, James P.; Thompson, Jack M., Jr.; Farrell, James D.; Vold, Havard I.

1989-01-01

Dexterous telerobots incorporating 17 or more degrees of freedom operating under coordinated, sensor-driven computer control will play important roles in future space operations. They will also be used on Earth in assignments like fire fighting, construction and battlefield support. A real time, reflexive obstacle avoidance system, seen as a functional requirement for such massively redundant manipulators, was developed using arm-mounted proximity sensors to control manipulator pose. The project involved a review and analysis of alternative proximity sensor technologies for space applications, the development of a general-purpose algorithm for synthesizing sensor inputs, and the implementation of a prototypical system for demonstration and testing. A 7 degree of freedom Robotics Research K-2107HR manipulator was outfitted with ultrasonic proximity sensors as a testbed, and Robotics Research's standard redundant motion control algorithm was modified such that an object detected by sensor arrays located at the elbow effectively applies a force to the manipulator elbow, normal to the axis. The arm is repelled by objects detected by the sensors, causing the robot to steer around objects in the workspace automatically while continuing to move its tool along the commanded path without interruption. The mathematical approach formulated for synthesizing sensor inputs can be employed for redundant robots of any kinematic configuration.

Application of particle swarm optimization in path planning of mobile robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Cai, Feng; Wang, Ying

2017-08-01

In order to realize the optimal path planning of mobile robot in unknown environment, a particle swarm optimization algorithm based on path length as fitness function is proposed. The location of the global optimal particle is determined by the minimum fitness value, and the robot moves along the points of the optimal particles to the target position. The process of moving to the target point is done with MATLAB R2014a. Compared with the standard particle swarm optimization algorithm, the simulation results show that this method can effectively avoid all obstacles and get the optimal path.

Extensibility in local sensor based planning for hyper-redundant manipulators (robot snakes)

NASA Technical Reports Server (NTRS)

Choset, Howie; Burdick, Joel

1994-01-01

Partial Shape Modification (PSM) is a local sensor feedback method used for hyper-redundant robot manipulators, in which the redundancy is very large or infinite such as that of a robot snake. This aspect of redundancy enables local obstacle avoidance and end-effector placement in real time. Due to the large number of joints or actuators in a hyper-redundant manipulator, small displacement errors of such easily accumulate to large errors in the position of the tip relative to the base. The accuracy could be improved by a local sensor based planning method in which sensors are distributed along the length of the hyper-redundant robot. This paper extends the local sensor based planning strategy beyond the limitations of the fixed length of such a manipulator when its joint limits are met. This is achieved with an algorithm where the length of the deforming part of the robot is variable. Thus , the robot's local avoidance of obstacles is improved through the enhancement of its extensibility.

Effect of visuospatial neglect on spatial navigation and heading after stroke.

PubMed

Aravind, Gayatri; Lamontagne, Anouk

2017-06-09

Visuospatial neglect (VSN) impairs the control of locomotor heading in post-stroke individuals, which may affect their ability to safely avoid moving objects while walking. We aimed to compare VSN+ and VSN- stroke individuals in terms of changes in heading and head orientation in space while avoiding obstacles approaching from different directions and reorienting toward the final target. Stroke participants with VSN (VSN+) and without VSN (VSN-) walked in a virtual environment avoiding obstacles that approached contralesionally, head-on or ipsilesionally. Measures of obstacle avoidance (onset-of-heading change, maximum mediolateral deviation) and target alignment (heading and head-rotation errors with respect to target) were compared across groups and obstacle directions. In total, 26 participants with right-hemisphere stroke participated (13 VSN+ and 13 VSN-; 24 males; mean age 60.3 years, range 48 to 72 years). A larger proportion of VSN+ (75%) than VSN- (38%) participants collided with contralesional and head-on obstacles. For VSN- participants, deviating to the same side as the obstacle was a safe strategy to avoid diagonal obstacles and deviating to the opposite-side led to occasional collisions. VSN+ participants deviated ipsilesionally, displaying same-side and opposite-side strategies for ipsilesional and contralesional obstacles, respectively. Overall, VSN+ participants showed greater distances at onset-of-heading change, smaller maximum mediolateral deviation and larger errors in target alignment as compared with VSN- participants. The ipsilesional bias arising from VSN influences the modulation of heading in response to obstacles and, along with the adoption of the "riskier" strategies, contribute to the higher number colliders and poor goal-directed walking abilities in stroke survivors with VSN. Future research should focus on developing assessment and training tools for complex locomotor tasks such as obstacle avoidance in this population. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

A Motion Planning Approach to Automatic Obstacle Avoidance during Concentric Tube Robot Teleoperation

PubMed Central

Torres, Luis G.; Kuntz, Alan; Gilbert, Hunter B.; Swaney, Philip J.; Hendrick, Richard J.; Webster, Robert J.; Alterovitz, Ron

2015-01-01

Concentric tube robots are thin, tentacle-like devices that can move along curved paths and can potentially enable new, less invasive surgical procedures. Safe and effective operation of this type of robot requires that the robot’s shaft avoid sensitive anatomical structures (e.g., critical vessels and organs) while the surgeon teleoperates the robot’s tip. However, the robot’s unintuitive kinematics makes it difficult for a human user to manually ensure obstacle avoidance along the entire tentacle-like shape of the robot’s shaft. We present a motion planning approach for concentric tube robot teleoperation that enables the robot to interactively maneuver its tip to points selected by a user while automatically avoiding obstacles along its shaft. We achieve automatic collision avoidance by precomputing a roadmap of collision-free robot configurations based on a description of the anatomical obstacles, which are attainable via volumetric medical imaging. We also mitigate the effects of kinematic modeling error in reaching the goal positions by adjusting motions based on robot tip position sensing. We evaluate our motion planner on a teleoperated concentric tube robot and demonstrate its obstacle avoidance and accuracy in environments with tubular obstacles. PMID:26413381

A Motion Planning Approach to Automatic Obstacle Avoidance during Concentric Tube Robot Teleoperation.

PubMed

Torres, Luis G; Kuntz, Alan; Gilbert, Hunter B; Swaney, Philip J; Hendrick, Richard J; Webster, Robert J; Alterovitz, Ron

2015-05-01

Concentric tube robots are thin, tentacle-like devices that can move along curved paths and can potentially enable new, less invasive surgical procedures. Safe and effective operation of this type of robot requires that the robot's shaft avoid sensitive anatomical structures (e.g., critical vessels and organs) while the surgeon teleoperates the robot's tip. However, the robot's unintuitive kinematics makes it difficult for a human user to manually ensure obstacle avoidance along the entire tentacle-like shape of the robot's shaft. We present a motion planning approach for concentric tube robot teleoperation that enables the robot to interactively maneuver its tip to points selected by a user while automatically avoiding obstacles along its shaft. We achieve automatic collision avoidance by precomputing a roadmap of collision-free robot configurations based on a description of the anatomical obstacles, which are attainable via volumetric medical imaging. We also mitigate the effects of kinematic modeling error in reaching the goal positions by adjusting motions based on robot tip position sensing. We evaluate our motion planner on a teleoperated concentric tube robot and demonstrate its obstacle avoidance and accuracy in environments with tubular obstacles.

Symmetric caging formation for convex polygonal object transportation by multiple mobile robots based on fuzzy sliding mode control.

PubMed

Dai, Yanyan; Kim, YoonGu; Wee, SungGil; Lee, DongHa; Lee, SukGyu

2016-01-01

In this paper, the problem of object caging and transporting is considered for multiple mobile robots. With the consideration of minimizing the number of robots and decreasing the rotation of the object, the proper points are calculated and assigned to the multiple mobile robots to allow them to form a symmetric caging formation. The caging formation guarantees that all of the Euclidean distances between any two adjacent robots are smaller than the minimal width of the polygonal object so that the object cannot escape. In order to avoid collision among robots, the parameter of the robots radius is utilized to design the caging formation, and the A⁎ algorithm is used so that mobile robots can move to the proper points. In order to avoid obstacles, the robots and the object are regarded as a rigid body to apply artificial potential field method. The fuzzy sliding mode control method is applied for tracking control of the nonholonomic mobile robots. Finally, the simulation and experimental results show that multiple mobile robots are able to cage and transport the polygonal object to the goal position, avoiding obstacles. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

A Concept of the Differentially Driven Three Wheeled Robot

NASA Astrophysics Data System (ADS)

Kelemen, M.; Colville, D. J.; Kelemenová, T.; Virgala, I.; Miková, L.

2013-08-01

The paper deals with the concept of a differentially driven three wheeled robot. The main task for the robot is to follow the navigation black line on white ground. The robot also contains anti-collision sensors for avoiding obstacles on track. Students learn how to deal with signals from sensors and how to control DC motors. Students work with the controller and develop the locomotion algorithm and can attend a competition

Vision based obstacle detection and grouping for helicopter guidance

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Chatterji, Gano

1993-01-01

Electro-optical sensors can be used to compute range to objects in the flight path of a helicopter. The computation is based on the optical flow/motion at different points in the image. The motion algorithms provide a sparse set of ranges to discrete features in the image sequence as a function of azimuth and elevation. For obstacle avoidance guidance and display purposes, these discrete set of ranges, varying from a few hundreds to several thousands, need to be grouped into sets which correspond to objects in the real world. This paper presents a new method for object segmentation based on clustering the sparse range information provided by motion algorithms together with the spatial relation provided by the static image. The range values are initially grouped into clusters based on depth. Subsequently, the clusters are modified by using the K-means algorithm in the inertial horizontal plane and the minimum spanning tree algorithms in the image plane. The object grouping allows interpolation within a group and enables the creation of dense range maps. Researchers in robotics have used densely scanned sequence of laser range images to build three-dimensional representation of the outside world. Thus, modeling techniques developed for dense range images can be extended to sparse range images. The paper presents object segmentation results for a sequence of flight images.

Interpretation of laser/multi-sensor data for short range terrain modeling and hazard detection

NASA Technical Reports Server (NTRS)

Messing, B. S.

1980-01-01

A terrain modeling algorithm that would reconstruct the sensed ground images formed by the triangulation scheme, and classify as unsafe any terrain feature that would pose a hazard to a roving vehicle is described. This modeler greatly reduces quantization errors inherent in a laser/sensing system through the use of a thinning algorithm. Dual filters are employed to separate terrain steps from the general landscape, simplifying the analysis of terrain features. A crosspath analysis is utilized to detect and avoid obstacles that would adversely affect the roll of the vehicle. Computer simulations of the rover on various terrains examine the performance of the modeler.

Robust Path Planning and Feedback Design Under Stochastic Uncertainty

NASA Technical Reports Server (NTRS)

Blackmore, Lars

2008-01-01

Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. This requires that mission constraint violation can occur with a probability less than a prescribed value.In this paper we describe a novel method for optimal chance constrained path planning with feedback design. The approach optimizes both the reference trajectory to be followed and the feedback controller used to reject uncertainty. Our method extends recent results in constrained control synthesis based on convex optimization to solve control problems with nonconvex constraints. This extension is essential for path planning problems, which inherently have nonconvex obstacle avoidance constraints. Unlike previous approaches to chance constrained path planning, the new approach optimizes the feedback gain as wellas the reference trajectory.The key idea is to couple a fast, nonconvex solver that does not take into account uncertainty, with existing robust approaches that apply only to convex feasible regions. By alternating between robust and nonrobust solutions, the new algorithm guarantees convergence to a global optimum. We apply the new method to an unmanned aircraft and show simulation results that demonstrate the efficacy of the approach.

Teleoperation with virtual force feedback

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, R.J.

1993-08-01

In this paper we describe an algorithm for generating virtual forces in a bilateral teleoperator system. The virtual forces are generated from a world model and are used to provide real-time obstacle avoidance and guidance capabilities. The algorithm requires that the slaves tool and every object in the environment be decomposed into convex polyhedral Primitives. Intrusion distance and extraction vectors are then derived at every time step by applying Gilbert`s polyhedra distance algorithm, which has been adapted for the task. This information is then used to determine the compression and location of nonlinear virtual spring-dampers whose total force is summedmore » and applied to the manipulator/teleoperator system. Experimental results validate the whole approach, showing that it is possible to compute the algorithm and generate realistic, useful psuedo forces for a bilateral teleoperator system using standard VME bus hardware.« less

A Compact Magnetic Field-Based Obstacle Detection and Avoidance System for Miniature Spherical Robots.

PubMed

Wu, Fang; Vibhute, Akash; Soh, Gim Song; Wood, Kristin L; Foong, Shaohui

2017-05-28

Due to their efficient locomotion and natural tolerance to hazardous environments, spherical robots have wide applications in security surveillance, exploration of unknown territory and emergency response. Numerous studies have been conducted on the driving mechanism, motion planning and trajectory tracking methods of spherical robots, yet very limited studies have been conducted regarding the obstacle avoidance capability of spherical robots. Most of the existing spherical robots rely on the "hit and run" technique, which has been argued to be a reasonable strategy because spherical robots have an inherent ability to recover from collisions. Without protruding components, they will not become stuck and can simply roll back after running into bstacles. However, for small scale spherical robots that contain sensitive surveillance sensors and cannot afford to utilize heavy protective shells, the absence of obstacle avoidance solutions would leave the robot at the mercy of potentially dangerous obstacles. In this paper, a compact magnetic field-based obstacle detection and avoidance system has been developed for miniature spherical robots. It utilizes a passive magnetic field so that the system is both compact and power efficient. The proposed system can detect not only the presence, but also the approaching direction of a ferromagnetic obstacle, therefore, an intelligent avoidance behavior can be generated by adapting the trajectory tracking method with the detection information. Design optimization is conducted to enhance the obstacle detection performance and detailed avoidance strategies are devised. Experimental results are also presented for validation purposes.

Application of a distributed systems architecture for increased speed in image processing on an autonomous ground vehicle

NASA Astrophysics Data System (ADS)

Wright, Adam A.; Momin, Orko; Shin, Young Ho; Shakya, Rahul; Nepal, Kumud; Ahlgren, David J.

2010-01-01

This paper presents the application of a distributed systems architecture to an autonomous ground vehicle, Q, that participates in both the autonomous and navigation challenges of the Intelligent Ground Vehicle Competition. In the autonomous challenge the vehicle is required to follow a course, while avoiding obstacles and staying within the course boundaries, which are marked by white lines. For the navigation challenge, the vehicle is required to reach a set of target destinations, known as way points, with given GPS coordinates and avoid obstacles that it encounters in the process. Previously the vehicle utilized a single laptop to execute all processing activities including image processing, sensor interfacing and data processing, path planning and navigation algorithms and motor control. National Instruments' (NI) LabVIEW served as the programming language for software implementation. As an upgrade to last year's design, a NI compact Reconfigurable Input/Output system (cRIO) was incorporated to the system architecture. The cRIO is NI's solution for rapid prototyping that is equipped with a real time processor, an FPGA and modular input/output. Under the current system, the real time processor handles the path planning and navigation algorithms, the FPGA gathers and processes sensor data. This setup leaves the laptop to focus on running the image processing algorithm. Image processing as previously presented by Nepal et. al. is a multi-step line extraction algorithm and constitutes the largest processor load. This distributed approach results in a faster image processing algorithm which was previously Q's bottleneck. Additionally, the path planning and navigation algorithms are executed more reliably on the real time processor due to the deterministic nature of operation. The implementation of this architecture required exploration of various inter-system communication techniques. Data transfer between the laptop and the real time processor using UDP packets was established as the most reliable protocol after testing various options. Improvement can be made to the system by migrating more algorithms to the hardware based FPGA to further speed up the operations of the vehicle.

Automated path planning of the Payload Inspection and Processing System

NASA Technical Reports Server (NTRS)

Byers, Robert M.

1994-01-01

The Payload Changeout Room Inspection and Processing System (PIPS) is a highly redundant manipulator intended for performing tasks in the crowded and sensitive environment of the Space Shuttle Orbiter payload bay. Its dexterity will be exploited to maneuver the end effector in a workspace populated with obstacles. A method is described by which the end effector of a highly redundant manipulator is directed toward a target via a Lyapunov stability function. A cost function is constructed which represents the distance from the manipulator links to obstacles. Obstacles are avoided by causing the vector of joint parameters to move orthogonally to the gradient of the workspace cost function. A C language program implements the algorithm to generate a joint history. The resulting motion is graphically displayed using the Interactive Graphical Robot Instruction Program (IGRIP) produced by Deneb Robotics. The graphical simulation has the potential to be a useful tool in path planning for the PIPS in the Shuttle Payload Bay environment.

A proposed UAV for indoor patient care.

PubMed

Todd, Catherine; Watfa, Mohamed; El Mouden, Yassine; Sahir, Sana; Ali, Afrah; Niavarani, Ali; Lutfi, Aoun; Copiaco, Abigail; Agarwal, Vaibhavi; Afsari, Kiyan; Johnathon, Chris; Okafor, Onyeka; Ayad, Marina

2015-09-10

Indoor flight, obstacle avoidance and client-server communication of an Unmanned Aerial Vehicle (UAV) raises several unique research challenges. This paper examines current methods and associated technologies adapted within the literature toward autonomous UAV flight, for consideration in a proposed system for indoor healthcare administration with a quadcopter. We introduce Healthbuddy, a unique research initiative towards overcoming challenges associated with indoor navigation, collision detection and avoidance, stability, wireless drone-server communications and automated decision support for patient care in a GPS-denied environment. To address the identified research deficits, a drone-based solution is presented. The solution is preliminary as we develop and refine the suggested algorithms and hardware system to achieve the research objectives.

Virtual obstacle crossing: Reliability and differences in stroke survivors who prospectively experienced falls or no falls.

PubMed

Punt, Michiel; Bruijn, Sjoerd M; Wittink, Harriet; van de Port, Ingrid G; Wubbels, Gijs; van Dieën, Jaap H

2017-10-01

Stroke survivors often fall during walking. To reduce fall risk, gait testing and training with avoidance of virtual obstacles is gaining popularity. However, it is unknown whether and how virtual obstacle crossing is associated with fall risk. The present study assessed whether obstacle crossing characteristics are reliable and assessed differences in stroke survivors who prospectively experienced falls or no falls. We recruited twenty-nine community dwelling chronic stroke survivors. Participants crossed five virtual obstacles with increasing lengths. After a break, the test was repeated to assess test-retest reliability. For each obstacle length and trial, we determined; success rate, leading limb preference, pre and post obstacle distance, margins of stability, toe clearance, and crossing step length and speed. Subsequently, fall incidence was monitored using a fall calendar and monthly phone calls over a six-month period. Test-retest reliability was poor, but improved with increasing obstacle-length. Twelve participants reported at least one fall. No association of fall incidence with any of the obstacle crossing characteristics was found. Given the absence of height of the virtual obstacles, obstacle avoidance may have been relatively easy, allowing participants to cross obstacles in multiple ways, increasing variability of crossing characteristics and reducing the association with fall risk. These finding cast some doubt on current protocols for testing and training of obstacle avoidance in stroke rehabilitation. Copyright © 2017 Elsevier B.V. All rights reserved.

Obstacle avoidance system with sonar sensing and fuzzy logic

NASA Astrophysics Data System (ADS)

Chiang, Wen-chuan; Kelkar, Nikhal; Hall, Ernest L.

1997-09-01

Automated guided vehicles (AGVs) have many potential applications in manufacturing, medicine, space and defense. The purpose of this paper is to describe exploratory research on the design of an obstacle avoidance system using sonar sensors for a modular autonomous mobile robot controller. The advantages of a modular system are related to portability and the fact that any vehicle can become autonomous with minimal modifications. A mobile robot test-bed has been constructed using a golf cart base. The obstacle avoidance system is based on a micro-controller interfaced with multiple ultrasonic transducers. This micro-controller independently handles all timing and distance calculations and sends a distance measurement back to the computer via the serial line. This design yields a portable independent system. Testing of these systems has been done in the lab as well as on an outside test track with positive results that show that at five mph the vehicle can follow a line and at the same time avoid obstacles. This design, in its modularity, creates a portable autonomous obstacle avoidance controller applicable for any mobile vehicle with only minor adaptations.

Path planning for assembly of strut-based structures. Thesis

NASA Technical Reports Server (NTRS)

Muenger, Rolf

1991-01-01

A path planning method with collision avoidance for a general single chain nonredundant or redundant robot is proposed. Joint range boundary overruns are also avoided. The result is a sequence of joint vectors which are passed to a trajectory planner. A potential field algorithm in joint space computes incremental joint vectors delta-q = delta-q(sub a) + delta-q(sub c) + delta-q(sub r). Adding delta-q to the robot's current joint vector leads to the next step in the path. Delta-q(sub a) is obtained by computing the minimum norm solution of the underdetermined linear system J delta-q(sub a) = x(sub a) where x(sub a) is a translational and rotational force vector that attracts the robot to its goal position and orientation. J is the manipulator Jacobian. Delta-q(sub c) is a collision avoidance term encompassing collisions between the robot (links and payload) and obstacles in the environment as well as collisions among links and payload of the robot themselves. It is obtained in joint space directly. Delta-q(sub r) is a function of the current joint vector and avoids joint range overruns. A higher level discrete search over candidate safe positions is used to provide alternatives in case the potential field algorithm encounters a local minimum and thus fails to reach the goal. The best first search algorithm A* is used for graph search. Symmetry properties of the payload and equivalent rotations are exploited to further enlarge the number of alternatives passed to the potential field algorithm.

A Nonlinear Model Predictive Control Algorithm for Obstacle Avoidance in Autonomous Ground Vehicles within Unknown Environments

DTIC Science & Technology

2015-04-24

xs , ys , xe , ye ) double EndPo in t s [L...Distribution Statement A. Approved for public release. #26161 350 400 450 100 150 200 250 300 350 400 450 500 550 600 x (m) y (m ) Start Target U0 = 10...longitudinal speed 350 400 450 100 150 200 250 300 350 400 450 500 550 600 x (m) y (m ) Start Target (a) Trajectory 0 5 10 15 0 1 t (s) f ( U0 = 30

Team VaCAS Design and Development of Cooperative UGV System

DTIC Science & Technology

2011-02-04

Mapping ( SLAM ) [24]. Similar to such work, the technique to be used in the project will also (1) use the last reliably available data as the reference...Losada1, D., Matia1, F., Pedraza1, L., Jimenez A. and Galan, R., Consistency of SLAM -EKF Algorithms for Indoor Environments, Journal of Intelligent and...mounted on the UGV 1 include GPS for outdoor navigation, LiDAR for obstacle avoidance and mapping and camera for OOI detection and localization. UGVs 2

Non linear predictive control of a LEGO mobile robot

NASA Astrophysics Data System (ADS)

Merabti, H.; Bouchemal, B.; Belarbi, K.; Boucherma, D.; Amouri, A.

2014-10-01

Metaheuristics are general purpose heuristics which have shown a great potential for the solution of difficult optimization problems. In this work, we apply the meta heuristic, namely particle swarm optimization, PSO, for the solution of the optimization problem arising in NLMPC. This algorithm is easy to code and may be considered as alternatives for the more classical solution procedures. The PSO- NLMPC is applied to control a mobile robot for the tracking trajectory and obstacles avoidance. Experimental results show the strength of this approach.

An MPC Algorithm with Combined Speed and Steering Control for Obstacle Avoidance in Autonomous Ground Vehicles

DTIC Science & Technology

2015-04-24

from this line to the upper left side is caused by aerodynamic drag. The data for estimating the lateral load transfer coefficients is generated by...2013. [13] J. H. Jeon, R. V. Cowlagi, S. C. Peters, S. Karaman, E. Frazzoli, P. Tsiotras, and K. Iagnemma, “Optimal motion planning with the half- car ...Elsevier, 2005. [21] A. Rucco, G. Notarstefano, and J. Hauser, “Optimal control based dynamics exploration of a rigid car with longitudinal load

Obstacle Avoidance On Roadways Using Range Data

NASA Astrophysics Data System (ADS)

Dunlay, R. Terry; Morgenthaler, David G.

1987-02-01

This report describes range data based obstacle avoidance techniques developed for use on an autonomous road-following robot vehicle. The purpose of these techniques is to detect and locate obstacles present in a road environment for navigation of a robot vehicle equipped with an active laser-based range sensor. Techniques are presented for obstacle detection, obstacle location, and coordinate transformations needed in the construction of Scene Models (symbolic structures representing the 3-D obstacle boundaries used by the vehicle's Navigator for path planning). These techniques have been successfully tested on an outdoor robotic vehicle, the Autonomous Land Vehicle (ALV), at speeds up to 3.5 km/hour.

Control of vertical posture while elevating one foot to avoid a real or virtual obstacle.

PubMed

Ida, Hirofumi; Mohapatra, Sambit; Aruin, Alexander

2017-06-01

The purpose of this study is to investigate the control of vertical posture during obstacle avoidance in a real versus a virtual reality (VR) environment. Ten healthy participants stood upright and lifted one leg to avoid colliding with a real obstacle sliding on the floor toward a participant and with its virtual image. Virtual obstacles were delivered by a head mounted display (HMD) or a 3D projector. The acceleration of the foot, center of pressure, and electrical activity of the leg and trunk muscles were measured and analyzed during the time intervals typical for early postural adjustments (EPAs), anticipatory postural adjustments (APAs), and compensatory postural adjustments (CPAs). The results showed that the peak acceleration of foot elevation in the HMD condition decreased significantly when compared with that of the real and 3D projector conditions. Reduced activity of the leg and trunk muscles was seen when dealing with virtual obstacles (HMD and 3D projector) as compared with that seen when dealing with real obstacles. These effects were more pronounced during APAs and CPAs. The onsets of muscle activities in the supporting limb were seen during EPAs and APAs. The observed modulation of muscle activity and altered patterns of movement seen while avoiding a virtual obstacle should be considered when designing virtual rehabilitation protocols.

Motion planning with complete knowledge using a colored SOM.

PubMed

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.

Thorough exploration of complex environments with a space-based potential field

NASA Astrophysics Data System (ADS)

Kenealy, Alina; Primiano, Nicholas; Keyes, Alex; Lyons, Damian M.

2015-01-01

Robotic exploration, for the purposes of search and rescue or explosive device detection, can be improved by using a team of multiple robots. Potential field navigation methods offer natural and efficient distributed exploration algorithms in which team members are mutually repelled to spread out and cover the area efficiently. However, they also suffer from field minima issues. Liu and Lyons proposed a Space-Based Potential Field (SBPF) algorithm that disperses robots efficiently and also ensures they are driven in a distributed fashion to cover complex geometry. In this paper, the approach is modified to handle two problems with the original SBPF method: fast exploration of enclosed spaces, and fast navigation of convex obstacles. Firstly, a "gate-sensing" function was implemented. The function draws the robot to narrow openings, such as doors or corridors that it might otherwise pass by, to ensure every room can be explored. Secondly, an improved obstacle field conveyor belt function was developed which allows the robot to avoid walls and barriers while using their surface as a motion guide to avoid being trapped. Simulation results, where the modified SPBF program controls the MobileSim Pioneer 3-AT simulator program, are presented for a selection of maps that capture difficult to explore geometries. Physical robot results are also presented, where a team of Pioneer 3-AT robots is controlled by the modified SBPF program. Data collected prior to the improvements, new simulation results, and robot experiments are presented as evidence of performance improvements.

A Monocular Vision Sensor-Based Obstacle Detection Algorithm for Autonomous Robots.

PubMed

Lee, Tae-Jae; Yi, Dong-Hoon; Cho, Dong-Il Dan

2016-03-01

This paper presents a monocular vision sensor-based obstacle detection algorithm for autonomous robots. Each individual image pixel at the bottom region of interest is labeled as belonging either to an obstacle or the floor. While conventional methods depend on point tracking for geometric cues for obstacle detection, the proposed algorithm uses the inverse perspective mapping (IPM) method. This method is much more advantageous when the camera is not high off the floor, which makes point tracking near the floor difficult. Markov random field-based obstacle segmentation is then performed using the IPM results and a floor appearance model. Next, the shortest distance between the robot and the obstacle is calculated. The algorithm is tested by applying it to 70 datasets, 20 of which include nonobstacle images where considerable changes in floor appearance occur. The obstacle segmentation accuracies and the distance estimation error are quantitatively analyzed. For obstacle datasets, the segmentation precision and the average distance estimation error of the proposed method are 81.4% and 1.6 cm, respectively, whereas those for a conventional method are 57.5% and 9.9 cm, respectively. For nonobstacle datasets, the proposed method gives 0.0% false positive rates, while the conventional method gives 17.6%.

Method for detecting and avoiding flight hazards

NASA Astrophysics Data System (ADS)

von Viebahn, Harro; Schiefele, Jens

1997-06-01

Today's aircraft equipment comprise several independent warning and hazard avoidance systems like GPWS, TCAS or weather radar. It is the pilot's task to monitor all these systems and take the appropriate action in case of an emerging hazardous situation. The developed method for detecting and avoiding flight hazards combines all potential external threats for an aircraft into a single system. It is based on an aircraft surrounding airspace model consisting of discrete volume elements. For each element of the volume the threat probability is derived or computed from sensor output, databases, or information provided via datalink. The position of the own aircraft is predicted by utilizing a probability distribution. This approach ensures that all potential positions of the aircraft within the near future are considered while weighting the most likely flight path. A conflict detection algorithm initiates an alarm in case the threat probability exceeds a threshold. An escape manoeuvre is generated taking into account all potential hazards in the vicinity, not only the one which caused the alarm. The pilot gets a visual information about the type, the locating, and severeness o the threat. The algorithm was implemented and tested in a flight simulator environment. The current version comprises traffic, terrain and obstacle hazards avoidance functions. Its general formulation allows an easy integration of e.g. weather information or airspace restrictions.

Hierarchical Shared Control of Cane-Type Walking-Aid Robot

PubMed Central

Tao, Chunjing

2017-01-01

A hierarchical shared-control method of the walking-aid robot for both human motion intention recognition and the obstacle emergency-avoidance method based on artificial potential field (APF) is proposed in this paper. The human motion intention is obtained from the interaction force measurements of the sensory system composed of 4 force-sensing registers (FSR) and a torque sensor. Meanwhile, a laser-range finder (LRF) forward is applied to detect the obstacles and try to guide the operator based on the repulsion force calculated by artificial potential field. An obstacle emergency-avoidance method which comprises different control strategies is also assumed according to the different states of obstacles or emergency cases. To ensure the user's safety, the hierarchical shared-control method combines the intention recognition method with the obstacle emergency-avoidance method based on the distance between the walking-aid robot and the obstacles. At last, experiments validate the effectiveness of the proposed hierarchical shared-control method. PMID:29093805

Automatic Quadcopter Control Avoiding Obstacle Using Camera with Integrated Ultrasonic Sensor

NASA Astrophysics Data System (ADS)

Anis, Hanafi; Haris Indra Fadhillah, Ahmad; Darma, Surya; Soekirno, Santoso

2018-04-01

Automatic navigation on the drone is being developed these days, a wide variety of types of drones and its automatic functions. Drones used in this study was an aircraft with four propellers or quadcopter. In this experiment, image processing used to recognize the position of an object and ultrasonic sensor used to detect obstacle distance. The method used to trace an obsctacle in image processing was the Lucas-Kanade-Tomasi Tracker, which had been widely used due to its high accuracy. Ultrasonic sensor used to complement the image processing success rate to be fully detected object. The obstacle avoidance system was to observe at the program decisions from some obstacle conditions read by the camera and ultrasonic sensors. Visual feedback control based PID controllers are used as a control of drones movement. The conclusion of the obstacle avoidance system was to observe at the program decisions from some obstacle conditions read by the camera and ultrasonic sensors.

Virtual local target method for avoiding local minimum in potential field based robot navigation.

PubMed

Zou, Xi-Yong; Zhu, Jing

2003-01-01

A novel robot navigation algorithm with global path generation capability is presented. Local minimum is a most intractable but is an encountered frequently problem in potential field based robot navigation. Through appointing appropriately some virtual local targets on the journey, it can be solved effectively. The key concept employed in this algorithm are the rules that govern when and how to appoint these virtual local targets. When the robot finds itself in danger of local minimum, a virtual local target is appointed to replace the global goal temporarily according to the rules. After the virtual target is reached, the robot continues on its journey by heading towards the global goal. The algorithm prevents the robot from running into local minima anymore. Simulation results showed that it is very effective in complex obstacle environments.

Bio-inspired Computing for Robots

NASA Technical Reports Server (NTRS)

Laufenberg, Larry

2003-01-01

Living creatures may provide algorithms to enable active sensing/control systems in robots. Active sensing could enable planetary rovers to feel their way in unknown environments. The surface of Jupiter's moon Europa consists of fractured ice over a liquid sea that may contain microbes similar to those on Earth. To explore such extreme environments, NASA needs robots that autonomously survive, navigate, and gather scientific data. They will be too far away for guidance from Earth. They must sense their environment and control their own movements to avoid obstacles or investigate a science opportunity. To meet this challenge, CICT's Information Technology Strategic Research (ITSR) Project is funding neurobiologists at NASA's Jet Propulsion Laboratory (JPL) and selected universities to search for biologically inspired algorithms that enable robust active sensing and control for exploratory robots. Sources for these algorithms are living creatures, including rats and electric fish.

Combing VFH with bezier for motion planning of an autonomous vehicle

NASA Astrophysics Data System (ADS)

Ye, Feng; Yang, Jing; Ma, Chao; Rong, Haijun

2017-08-01

Vector Field Histogram (VFH) is a method for mobile robot obstacle avoidance. However, due to the nonholonomic constraints of the vehicle, the algorithm is seldom applied to autonomous vehicles. Especially when we expect the vehicle to reach target location in a certain direction, the algorithm is often unsatisfactory. Fortunately, the Bezier Curve is defined by the states of the starting point and the target point. We can use this feature to make the vehicle in the expected direction. Therefore, we propose an algorithm to combine the Bezier Curve with the VFH algorithm, to search for the collision-free states with the VFH search method, and to select the optimal trajectory point with the Bezier Curve as the reference line. This means that we will improve the cost function in the VFH algorithm by comparing the distance between candidate directions and reference line. Finally, select the closest direction to the reference line to be the optimal motion direction.

Teleautonomous guidance for mobile robots

NASA Technical Reports Server (NTRS)

Borenstein, J.; Koren, Y.

1990-01-01

Teleautonomous guidance (TG), a technique for the remote guidance of fast mobile robots, has been developed and implemented. With TG, the mobile robot follows the general direction prescribed by an operator. However, if the robot encounters an obstacle, it autonomously avoids collision with that obstacle while trying to match the prescribed direction as closely as possible. This type of shared control is completely transparent and transfers control between teleoperation and autonomous obstacle avoidance gradually. TG allows the operator to steer vehicles and robots at high speeds and in cluttered environments, even without visual contact. TG is based on the virtual force field (VFF) method, which was developed earlier for autonomous obstacle avoidance. The VFF method is especially suited to the accommodation of inaccurate sensor data (such as that produced by ultrasonic sensors) and sensor fusion, and allows the mobile robot to travel quickly without stopping for obstacles.

An enhanced obstacle avoiding system for AUV`s

DOE Office of Scientific and Technical Information (OSTI.GOV)

Conte, G.; Zanoli, S.M.

1994-12-31

This paper concerns the development of a sonar-based navigation and guidance system for underwater, unmanned vehicles. In particular, the authors describe and discuss an obstacle avoidance procedure that is capable of dealing with situations involving several obstacles. The main features of the system are the use of a Kalman filter, both for estimating data and for predicting the evolution of the observed scene, and the possibility of working at different levels of data abstraction. The system has shown satisfactory performances in dealing with moving obstacles in general situations.

Performance Analysis of the Enhanced Bio-Inspired Planning Algorithm for Rapid Situation Awareness Response

DTIC Science & Technology

2013-10-18

low cost robot testbed. 15. SUBJECT TERMS Bio-inspired trajectory generation, in-situ obstacle avoidance, low-cost LEGO robots, vision- based...will not affect the solution optimality and thus will be regarded as zero. Following the LP motion strategy Eq. (1), the position vector of the Lego ...Lobatto (LGL) method [14], the position of Lego robot can be further represented as ’ 1 ,( )j p jD   ζ ζ (6) in which ,0 ,,..., T j j j

A Monocular Vision Sensor-Based Obstacle Detection Algorithm for Autonomous Robots

PubMed Central

Lee, Tae-Jae; Yi, Dong-Hoon; Cho, Dong-Il “Dan”

2016-01-01

This paper presents a monocular vision sensor-based obstacle detection algorithm for autonomous robots. Each individual image pixel at the bottom region of interest is labeled as belonging either to an obstacle or the floor. While conventional methods depend on point tracking for geometric cues for obstacle detection, the proposed algorithm uses the inverse perspective mapping (IPM) method. This method is much more advantageous when the camera is not high off the floor, which makes point tracking near the floor difficult. Markov random field-based obstacle segmentation is then performed using the IPM results and a floor appearance model. Next, the shortest distance between the robot and the obstacle is calculated. The algorithm is tested by applying it to 70 datasets, 20 of which include nonobstacle images where considerable changes in floor appearance occur. The obstacle segmentation accuracies and the distance estimation error are quantitatively analyzed. For obstacle datasets, the segmentation precision and the average distance estimation error of the proposed method are 81.4% and 1.6 cm, respectively, whereas those for a conventional method are 57.5% and 9.9 cm, respectively. For nonobstacle datasets, the proposed method gives 0.0% false positive rates, while the conventional method gives 17.6%. PMID:26938540

Integrated Collision Avoidance System for Air Vehicle

NASA Technical Reports Server (NTRS)

Lin, Ching-Fang (Inventor)

2013-01-01

Collision with ground/water/terrain and midair obstacles is one of the common causes of severe aircraft accidents. The various data from the coremicro AHRS/INS/GPS Integration Unit, terrain data base, and object detection sensors are processed to produce collision warning audio/visual messages and collision detection and avoidance of terrain and obstacles through generation of guidance commands in a closed-loop system. The vision sensors provide more information for the Integrated System, such as, terrain recognition and ranging of terrain and obstacles, which plays an important role to the improvement of the Integrated Collision Avoidance System.

PRIMUS: autonomous navigation in open terrain with a tracked vehicle

NASA Astrophysics Data System (ADS)

Schaub, Guenter W.; Pfaendner, Alfred H.; Schaefer, Christoph

2004-09-01

The German experimental robotics program PRIMUS (PRogram for Intelligent Mobile Unmanned Systems) is focused on solutions for autonomous driving in unknown open terrain, over several project phases under specific realization aspects for more than 12 years. The main task of the program is to develop algorithms for a high degree of autonomous navigation skills with off-the-shelf available hardware/sensor technology and to integrate this into military vehicles. For obstacle detection a Dornier-3D-LADAR is integrated on a tracked vehicle "Digitized WIESEL 2". For road-following a digital video camera and a visual perception module from the Universitaet der Bundeswehr Munchen (UBM) has been integrated. This paper gives an overview of the PRIMUS program with a focus on the last program phase D (2001 - 2003). This includes the system architecture, the description of the modes of operation and the technology development with the focus on obstacle avoidance and obstacle classification using a 3-D LADAR. A collection of experimental results and a short look at the next steps in the German robotics program will conclude the paper.

Dynamic clearance measure to evaluate locomotor and perceptuo-motor strategies used for obstacle circumvention in a virtual environment.

PubMed

Darekar, Anuja; Lamontagne, Anouk; Fung, Joyce

2015-04-01

Circumvention around an obstacle entails a dynamic interaction with the obstacle to maintain a safe clearance. We used a novel mathematical interpolation method based on the modified Shepard's method of Inverse Distance Weighting to compute dynamic clearance that reflected this interaction as well as minimal clearance. This proof-of-principle study included seven young healthy, four post-stroke and four healthy age-matched individuals. A virtual environment designed to assess obstacle circumvention was used to administer a locomotor (walking) and a perceptuo-motor (navigation with a joystick) task. In both tasks, participants were asked to navigate towards a target while avoiding collision with a moving obstacle that approached from either head-on, or 30° left or right. Among young individuals, dynamic clearance did not differ significantly between obstacle approach directions in both tasks. Post-stroke individuals maintained larger and smaller dynamic clearance during the locomotor and the perceptuo-motor task respectively as compared to age-matched controls. Dynamic clearance was larger than minimal distance from the obstacle irrespective of the group, task and obstacle approach direction. Also, in contrast to minimal distance, dynamic clearance can respond differently to different avoidance behaviors. Such a measure can be beneficial in contrasting obstacle avoidance behaviors in different populations with mobility problems. Copyright © 2015 Elsevier B.V. All rights reserved.

Real-time obstacle avoidance using harmonic potential functions

NASA Technical Reports Server (NTRS)

Kim, Jin-Oh; Khosla, Pradeep K.

1992-01-01

This paper presents a new formulation of the artificial potential approach to the obstacle avoidance problem for a mobile robot or a manipulator in a known environment. Previous formulations of artificial potentials for obstacle avoidance have exhibited local minima in a cluttered environment. To build an artificial potential field, harmonic functions that completely eliminate local minima even for a cluttered environment are used. The panel method is employed to represent arbitrarily shaped obstacles and to derive the potential over the whole space. Based on this potential function, an elegant control strategy is proposed for the real-time control of a robot. The harmonic potential, the panel method, and the control strategy are tested with a bar-shaped mobile robot and a three-degree-of-freedom planar redundant manipulator.

Autonomous collision avoidance system by combined control of steering and braking using geometrically optimised vehicular trajectory

NASA Astrophysics Data System (ADS)

Hayashi, Ryuzo; Isogai, Juzo; Raksincharoensak, Pongsathorn; Nagai, Masao

2012-01-01

This study proposes an autonomous obstacle avoidance system not only by braking but also by steering, as one of the active safety technologies to prevent traffic accidents. The proposed system prevents the vehicle from colliding with a moving obstacle like a pedestrian jumping out from the roadside. In the proposed system, to avoid the predicted colliding position based on constant-velocity obstacle motion assumption, the avoidance trajectory is derived as connected two identical arcs. The system then controls the vehicle autonomously by the combined control of the braking and steering systems. In this paper, the proposed system is examined by real car experiments and its effectiveness is shown from the results of the experiments.

Real-time piloted simulation of fully automatic guidance and control for rotorcraft nap-of-the-earth (NOE) flight following planned profiles

NASA Technical Reports Server (NTRS)

Clement, Warren F.; Gorder, Pater J.; Jewell, Wayne F.; Coppenbarger, Richard

1990-01-01

Developing a single-pilot all-weather NOE capability requires fully automatic NOE navigation and flight control. Innovative guidance and control concepts are being investigated to (1) organize the onboard computer-based storage and real-time updating of NOE terrain profiles and obstacles; (2) define a class of automatic anticipative pursuit guidance algorithms to follow the vertical, lateral, and longitudinal guidance commands; (3) automate a decision-making process for unexpected obstacle avoidance; and (4) provide several rapid response maneuvers. Acquired knowledge from the sensed environment is correlated with the recorded environment which is then used to determine an appropriate evasive maneuver if a nonconformity is observed. This research effort has been evaluated in both fixed-base and moving-base real-time piloted simulations thereby evaluating pilot acceptance of the automated concepts, supervisory override, manual operation, and reengagement of the automatic system.

Distance estimation and collision prediction for on-line robotic motion planning

NASA Technical Reports Server (NTRS)

Kyriakopoulos, K. J.; Saridis, G. N.

1991-01-01

An efficient method for computing the minimum distance and predicting collisions between moving objects is presented. This problem has been incorporated in the framework of an in-line motion planning algorithm to satisfy collision avoidance between a robot and moving objects modeled as convex polyhedra. In the beginning the deterministic problem, where the information about the objects is assumed to be certain is examined. If instead of the Euclidean norm, L(sub 1) or L(sub infinity) norms are used to represent distance, the problem becomes a linear programming problem. The stochastic problem is formulated, where the uncertainty is induced by sensing and the unknown dynamics of the moving obstacles. Two problems are considered: (1) filtering of the minimum distance between the robot and the moving object, at the present time; and (2) prediction of the minimum distance in the future, in order to predict possible collisions with the moving obstacles and estimate the collision time.

Using Thermal Radiation in Detection of Negative Obstacles

NASA Technical Reports Server (NTRS)

Rankin, Arturo L.; Matthies, Larry H.

2009-01-01

A method of automated detection of negative obstacles (potholes, ditches, and the like) ahead of ground vehicles at night involves processing of imagery from thermal-infrared cameras aimed at the terrain ahead of the vehicles. The method is being developed as part of an overall obstacle-avoidance scheme for autonomous and semi-autonomous offroad robotic vehicles. The method could also be applied to help human drivers of cars and trucks avoid negative obstacles -- a development that may entail only modest additional cost inasmuch as some commercially available passenger cars are already equipped with infrared cameras as aids for nighttime operation.

UAV formation control design with obstacle avoidance in dynamic three-dimensional environment.

PubMed

Chang, Kai; Xia, Yuanqing; Huang, Kaoli

2016-01-01

This paper considers the artificial potential field method combined with rotational vectors for a general problem of multi-unmanned aerial vehicle (UAV) systems tracking a moving target in dynamic three-dimensional environment. An attractive potential field is generated between the leader and the target. It drives the leader to track the target based on the relative position of them. The other UAVs in the formation are controlled to follow the leader by the attractive control force. The repulsive force affects among the UAVs to avoid collisions and distribute the UAVs evenly on the spherical surface whose center is the leader-UAV. Specific orders or positions of the UAVs are not required. The trajectories of avoidance obstacle can be obtained through two kinds of potential field with rotation vectors. Every UAV can choose the optimal trajectory to avoid the obstacle and reconfigure the formation after passing the obstacle. Simulations study on UAV are presented to demonstrate the effectiveness of proposed method.

Constrained trajectory optimization for kinematically redundant arms

NASA Technical Reports Server (NTRS)

Carignan, Craig R.; Tarrant, Janice M.

1990-01-01

Two velocity optimization schemes for resolving redundant joint configurations are compared. The Extended Moore-Penrose Technique minimizes the joint velocities and avoids obstacles indirectly by adjoining a cost gradient to the solution. A new method can incorporate inequality constraints directly to avoid obstacles and singularities in the workspace. A four-link arm example is used to illustrate singularity avoidance while tracking desired end-effector paths.

Assessing gait adaptability in people with a unilateral amputation on an instrumented treadmill with a projected visual context.

PubMed

Houdijk, Han; van Ooijen, Mariëlle W; Kraal, Jos J; Wiggerts, Henri O; Polomski, Wojtek; Janssen, Thomas W J; Roerdink, Melvyn

2012-11-01

Gait adaptability, including the ability to avoid obstacles and to take visually guided steps, is essential for safe movement through a cluttered world. This aspect of walking ability is important for regaining independent mobility but is difficult to assess in clinical practice. The objective of this study was to investigate the validity of an instrumented treadmill with obstacles and stepping targets projected on the belt's surface for assessing prosthetic gait adaptability. This was an observational study. A control group of people who were able bodied (n=12) and groups of people with transtibial (n=12) and transfemoral (n=12) amputations participated. Participants walked at a self-selected speed on an instrumented treadmill with projected visual obstacles and stepping targets. Gait adaptability was evaluated in terms of anticipatory and reactive obstacle avoidance performance (for obstacles presented 4 steps and 1 step ahead, respectively) and accuracy of stepping on regular and irregular patterns of stepping targets. In addition, several clinical tests were administered, including timed walking tests and reports of incidence of falls and fear of falling. Obstacle avoidance performance and stepping accuracy were significantly lower in the groups with amputations than in the control group. Anticipatory obstacle avoidance performance was moderately correlated with timed walking test scores. Reactive obstacle avoidance performance and stepping accuracy performance were not related to timed walking tests. Gait adaptability scores did not differ in groups stratified by incidence of falls or fear of falling. Because gait adaptability was affected by walking speed, differences in self-selected walking speed may have diminished differences in gait adaptability between groups. Gait adaptability can be validly assessed by use of an instrumented treadmill with a projected visual context. When walking speed is taken into account, this assessment provides unique, quantitative information about walking ability in people with a lower-limb amputation.

Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System

PubMed Central

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

Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System.

PubMed

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.

Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization

NASA Technical Reports Server (NTRS)

Birge, Brian

2013-01-01

The design priority for manned space exploration missions is almost always placed on human safety. Proposed manned surface exploration tasks (lunar, asteroid sample returns, Mars) have the possibility of astronauts traveling several kilometers away from a home base. Deviations from preplanned paths are expected while exploring. In a time-critical emergency situation, there is a need to develop an optimal home base return path. The return path may or may not be similar to the outbound path, and what defines optimal may change with, and even within, each mission. A novel path planning algorithm and prototype program was developed using biologically inspired particle swarm optimization (PSO) that generates an optimal path of traversal while avoiding obstacles. Applications include emergency path planning on lunar, Martian, and/or asteroid surfaces, generating multiple scenarios for outbound missions, Earth-based search and rescue, as well as human manual traversal and/or path integration into robotic control systems. The strategy allows for a changing environment, and can be re-tasked at will and run in real-time situations. Given a random extraterrestrial planetary or small body surface position, the goal was to find the fastest (or shortest) path to an arbitrary position such as a safe zone or geographic objective, subject to possibly varying constraints. The problem requires a workable solution 100% of the time, though it does not require the absolute theoretical optimum. Obstacles should be avoided, but if they cannot be, then the algorithm needs to be smart enough to recognize this and deal with it. With some modifications, it works with non-stationary error topologies as well.

Obstacle Detection Algorithms for Aircraft Navigation: Performance Characterization of Obstacle Detection Algorithms for Aircraft Navigation

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar; Camps, Octavia; Coraor, Lee

2000-01-01

The research reported here is a part of NASA's Synthetic Vision System (SVS) project for the development of a High Speed Civil Transport Aircraft (HSCT). One of the components of the SVS is a module for detection of potential obstacles in the aircraft's flight path by analyzing the images captured by an on-board camera in real-time. Design of such a module includes the selection and characterization of robust, reliable, and fast techniques and their implementation for execution in real-time. This report describes the results of our research in realizing such a design. It is organized into three parts. Part I. Data modeling and camera characterization; Part II. Algorithms for detecting airborne obstacles; and Part III. Real time implementation of obstacle detection algorithms on the Datacube MaxPCI architecture. A list of publications resulting from this grant as well as a list of relevant publications resulting from prior NASA grants on this topic are presented.

An integrated collision prediction and avoidance scheme for mobile robots in non-stationary environments

NASA Technical Reports Server (NTRS)

Kyriakopoulos, K. J.; Saridis, G. N.

1993-01-01

A formulation that makes possible the integration of collision prediction and avoidance stages for mobile robots moving in general terrains containing moving obstacles is presented. A dynamic model of the mobile robot and the dynamic constraints are derived. Collision avoidance is guaranteed if the distance between the robot and a moving obstacle is nonzero. A nominal trajectory is assumed to be known from off-line planning. The main idea is to change the velocity along the nominal trajectory so that collisions are avoided. A feedback control is developed and local asymptotic stability is proved if the velocity of the moving obstacle is bounded. Furthermore, a solution to the problem of inverse dynamics for the mobile robot is given. Simulation results verify the value of the proposed strategy.

Concept development of automatic guidance for rotorcraft obstacle avoidance

NASA Technical Reports Server (NTRS)

Cheng, Victor H. L.

1990-01-01

The automatic guidance of rotorcraft for obstacle avoidance in nap-of-the-earth flight is studied. A hierarchical breakdown of the guidance components is used to identify the functional requirements. These requirements and anticipated sensor capabilities lead to a preliminary guidance concept, which has been evaluated via computer simulations.

Optimal guidance with obstacle avoidance for nap-of-the-earth flight

NASA Technical Reports Server (NTRS)

Pekelsma, Nicholas J.

1988-01-01

The development of automatic guidance is discussed for helicopter Nap-of-the-Earth (NOE) and near-NOE flight. It deals with algorithm refinements relating to automated real-time flight path planning and to mission planning. With regard to path planning, it relates rotorcraft trajectory characteristics to the NOE computation scheme and addresses real-time computing issues and both ride quality issues and pilot-vehicle interfaces. The automated mission planning algorithm refinements include route optimization, automatic waypoint generation, interactive applications, and provisions for integrating the results into the real-time path planning software. A microcomputer based mission planning workstation was developed and is described. Further, the application of Defense Mapping Agency (DMA) digital terrain to both the mission planning workstation and to automatic guidance is both discussed and illustrated.

Visual feedback training improves postural adjustments associated with moving obstacle avoidance in elderly women.

PubMed

Hatzitaki, V; Voudouris, D; Nikodelis, T; Amiridis, I G

2009-02-01

The study examined the impact of visually guided weight shifting (WS) practice on the postural adjustments evoked by elderly women when avoiding collision with a moving obstacle while standing. Fifty-six healthy elderly women (70.9+/-5.7 years, 87.5+/-9.6 kg) were randomly assigned into one of three groups: a group that completed 12 sessions (25 min, 3s/week) of WS practice in the Anterior/Posterior direction (A/P group, n=20), a group that performed the same practice in the medio/lateral direction (M/L group, n=20) and a control group (n=16). Pre- and post-training, participants were tested in a moving obstacle avoidance task. As a result of practice, postural response onset shifted closer to the time of collision with the obstacle. Side-to-side WS resulted in a reduction of the M/L sway amplitude and an increase of the trunk's velocity during avoidance. It is concluded that visually guided WS practice enhances elderly's ability for on-line visuo-motor processing when avoiding collision eliminating reliance on anticipatory scaling. Specifying the direction of WS seems to be critical for optimizing the transfer of training adaptations.

Obstacle detection and avoiding of quadcopter

NASA Astrophysics Data System (ADS)

Wang, Dizhong; Lin, Jiajian

2017-10-01

Recent years, the flight control technology over quadcopter has been boosted vigorously and acquired the comprehensive application in a variety of industries. However, it is prominent for there to be problems existed in the stable and secure flight with the development of its autonomous flight. Through comparing with the characteristics of ultrasonic ranging and laser Time-of-Flight(abbreviated to ToF) distance as well as vision measurement and its related sensors, the obstacle detection and identification sensors need to be installed in order to effectively enhance the safety flying for aircraft, which is essential for avoiding the dangers around the surroundings. That the major sensors applied to objects perception at present are distance measuring instruments which based on the principle and application of non-contact detection technology . Prior to acknowledging the general principles of flight and obstacle avoiding, the aerodynamics modeling of the quadcopter and its object detection means has been initially determined on this paper. Based on such premise, this article emphasized on describing and analyzing the research on obstacle avoiding technology and its application status, and making an expectation for the trend of its development after analyzing the primary existing problems concerning its accuracy object avoidance.

Robust analysis of an underwater navigational strategy in electrically heterogeneous corridors.

PubMed

Dimble, Kedar D; Ranganathan, Badri N; Keshavan, Jishnu; Humbert, J Sean

2016-08-01

Obstacles and other global stimuli provide relevant navigational cues to a weakly electric fish. In this work, robust analysis of a control strategy based on electrolocation for performing obstacle avoidance in electrically heterogeneous corridors is presented and validated. Static output feedback control is shown to achieve the desired goal of reflexive obstacle avoidance in such environments in simulation and experimentation. The proposed approach is computationally inexpensive and readily implementable on a small scale underwater vehicle, making underwater autonomous navigation feasible in real-time.

Kinematic path planning for space-based robotics

NASA Astrophysics Data System (ADS)

Seereeram, Sanjeev; Wen, John T.

1998-01-01

Future space robotics tasks require manipulators of significant dexterity, achievable through kinematic redundancy and modular reconfigurability, but with a corresponding complexity of motion planning. Existing research aims for full autonomy and completeness, at the expense of efficiency, generality or even user friendliness. Commercial simulators require user-taught joint paths-a significant burden for assembly tasks subject to collision avoidance, kinematic and dynamic constraints. Our research has developed a Kinematic Path Planning (KPP) algorithm which bridges the gap between research and industry to produce a powerful and useful product. KPP consists of three key components: path-space iterative search, probabilistic refinement, and an operator guidance interface. The KPP algorithm has been successfully applied to the SSRMS for PMA relocation and dual-arm truss assembly tasks. Other KPP capabilities include Cartesian path following, hybrid Cartesian endpoint/intermediate via-point planning, redundancy resolution and path optimization. KPP incorporates supervisory (operator) input at any detail to influence the solution, yielding desirable/predictable paths for multi-jointed arms, avoiding obstacles and obeying manipulator limits. This software will eventually form a marketable robotic planner suitable for commercialization in conjunction with existing robotic CAD/CAM packages.

Integrating obstacle avoidance, global path planning, visual cue detection, and landmark triangulation in a mobile robot

NASA Astrophysics Data System (ADS)

Kortenkamp, David; Huber, Marcus J.; Congdon, Clare B.; Huffman, Scott B.; Bidlack, Clint R.; Cohen, Charles J.; Koss, Frank V.; Raschke, Ulrich; Weymouth, Terry E.

1993-05-01

This paper describes the design and implementation of an integrated system for combining obstacle avoidance, path planning, landmark detection and position triangulation. Such an integrated system allows the robot to move from place to place in an environment, avoiding obstacles and planning its way out of traps, while maintaining its position and orientation using distinctive landmarks. The task the robot performs is to search a 22 m X 22 m arena for 10 distinctive objects, visiting each object in turn. This same task was recently performed by a dozen different robots at a competition in which the robot described in this paper finished first.

Obstacle Detection in Indoor Environment for Visually Impaired Using Mobile Camera

NASA Astrophysics Data System (ADS)

Rahman, Samiur; Ullah, Sana; Ullah, Sehat

2018-01-01

Obstacle detection can improve the mobility as well as the safety of visually impaired people. In this paper, we present a system using mobile camera for visually impaired people. The proposed algorithm works in indoor environment and it uses a very simple technique of using few pre-stored floor images. In indoor environment all unique floor types are considered and a single image is stored for each unique floor type. These floor images are considered as reference images. The algorithm acquires an input image frame and then a region of interest is selected and is scanned for obstacle using pre-stored floor images. The algorithm compares the present frame and the next frame and compute mean square error of the two frames. If mean square error is less than a threshold value α then it means that there is no obstacle in the next frame. If mean square error is greater than α then there are two possibilities; either there is an obstacle or the floor type is changed. In order to check if the floor is changed, the algorithm computes mean square error of next frame and all stored floor types. If minimum of mean square error is less than a threshold value α then flour is changed otherwise there exist an obstacle. The proposed algorithm works in real-time and 96% accuracy has been achieved.

Semi-autonomous unmanned ground vehicle control system

NASA Astrophysics Data System (ADS)

Anderson, Jonathan; Lee, Dah-Jye; Schoenberger, Robert; Wei, Zhaoyi; Archibald, James

2006-05-01

Unmanned Ground Vehicles (UGVs) have advantages over people in a number of different applications, ranging from sentry duty, scouting hazardous areas, convoying goods and supplies over long distances, and exploring caves and tunnels. Despite recent advances in electronics, vision, artificial intelligence, and control technologies, fully autonomous UGVs are still far from being a reality. Currently, most UGVs are fielded using tele-operation with a human in the control loop. Using tele-operations, a user controls the UGV from the relative safety and comfort of a control station and sends commands to the UGV remotely. It is difficult for the user to issue higher level commands such as patrol this corridor or move to this position while avoiding obstacles. As computer vision algorithms are implemented in hardware, the UGV can easily become partially autonomous. As Field Programmable Gate Arrays (FPGAs) become larger and more powerful, vision algorithms can run at frame rate. With the rapid development of CMOS imagers for consumer electronics, frame rate can reach as high as 200 frames per second with a small size of the region of interest. This increase in the speed of vision algorithm processing allows the UGVs to become more autonomous, as they are able to recognize and avoid obstacles in their path, track targets, or move to a recognized area. The user is able to focus on giving broad supervisory commands and goals to the UGVs, allowing the user to control multiple UGVs at once while still maintaining the convenience of working from a central base station. In this paper, we will describe a novel control system for the control of semi-autonomous UGVs. This control system combines a user interface similar to a simple tele-operation station along with a control package, including the FPGA and multiple cameras. The control package interfaces with the UGV and provides the necessary control to guide the UGV.

Learn to Avoid or Overcome Leadership Obstacles

ERIC Educational Resources Information Center

D'Auria, John

2015-01-01

Leadership is increasingly recognized as an important factor in moving schools forward, yet we have been relatively random in how we prepare and support them. Four obstacles often block or diminish their effectiveness. Avoiding or overcoming each of these requires an underlying set of skills and knowledge that we believe can be learned and…

Obstacle avoidance in social groups: new insights from asynchronous models

PubMed Central

Croft, Simon; Budgey, Richard; Pitchford, Jonathan W.; Wood, A. Jamie

2015-01-01

For moving animals, the successful avoidance of hazardous obstacles is an important capability. Despite this, few models of collective motion have addressed the relationship between behavioural and social features and obstacle avoidance. We develop an asynchronous individual-based model for social movement which allows social structure within groups to be included. We assess the dynamics of group navigation and resulting collision risk in the context of information transfer through the system. In agreement with previous work, we find that group size has a nonlinear effect on collision risk. We implement examples of possible network structures to explore the impact social preferences have on collision risk. We show that any social heterogeneity induces greater obstacle avoidance with further improvements corresponding to groups containing fewer influential individuals. The model provides a platform for both further theoretical investigation and practical application. In particular, we argue that the role of social structures within bird flocks may have an important role to play in assessing the risk of collisions with wind turbines, but that new methods of data analysis are needed to identify these social structures. PMID:25833245

Walking-adaptability assessments with the Interactive Walkway: Between-systems agreement and sensitivity to task and subject variations.

PubMed

Geerse, Daphne J; Coolen, Bert H; Roerdink, Melvyn

2017-05-01

The ability to adapt walking to environmental circumstances is an important aspect of walking, yet difficult to assess. The Interactive Walkway was developed to assess walking adaptability by augmenting a multi-Kinect-v2 10-m walkway with gait-dependent visual context (stepping targets, obstacles) using real-time processed markerless full-body kinematics. In this study we determined Interactive Walkway's usability for walking-adaptability assessments in terms of between-systems agreement and sensitivity to task and subject variations. Under varying task constraints, 21 healthy subjects performed obstacle-avoidance, sudden-stops-and-starts and goal-directed-stepping tasks. Various continuous walking-adaptability outcome measures were concurrently determined with the Interactive Walkway and a gold-standard motion-registration system: available response time, obstacle-avoidance and sudden-stop margins, step length, stepping accuracy and walking speed. The same holds for dichotomous classifications of success and failure for obstacle-avoidance and sudden-stops tasks and performed short-stride versus long-stride obstacle-avoidance strategies. Continuous walking-adaptability outcome measures generally agreed well between systems (high intraclass correlation coefficients for absolute agreement, low biases and narrow limits of agreement) and were highly sensitive to task and subject variations. Success and failure ratings varied with available response times and obstacle types and agreed between systems for 85-96% of the trials while obstacle-avoidance strategies were always classified correctly. We conclude that Interactive Walkway walking-adaptability outcome measures are reliable and sensitive to task and subject variations, even in high-functioning subjects. We therefore deem Interactive Walkway walking-adaptability assessments usable for obtaining an objective and more task-specific examination of one's ability to walk, which may be feasible for both high-functioning and fragile populations since walking adaptability can be assessed at various levels of difficulty. Copyright © 2017 Elsevier B.V. All rights reserved.

A five-week exercise program can reduce falls and improve obstacle avoidance in the elderly.

PubMed

Weerdesteyn, Vivian; Rijken, Hennie; Geurts, Alexander C H; Smits-Engelsman, Bouwien C M; Mulder, Theo; Duysens, Jacques

2006-01-01

Falls in the elderly are a major health problem. Although exercise programs have been shown to reduce the risk of falls, the optimal exercise components, as well as the working mechanisms that underlie the effectiveness of these programs, have not yet been established. To test whether the Nijmegen Falls Prevention Program was effective in reducing falls and improving standing balance, balance confidence, and obstacle avoidance performance in community-dwelling elderly people. A total of 113 elderly with a history of falls participated in this study (exercise group, n = 79; control group, n = 28; dropouts before randomization, n = 6). Exercise sessions were held twice weekly for 5 weeks. Pre- and post-intervention fall monitoring and quantitative motor control assessments were performed. The outcome measures were the number of falls, standing balance and obstacle avoidance performance, and balance confidence scores. The number of falls in the exercise group decreased by 46% (incidence rate ratio (IRR) 0.54, 95% confidence interval (CI) 0.36-0.79) compared to the number of falls during the baseline period and by 46% (IRR 0.54, 95% CI 0.34-0.86) compared to the control group. Obstacle avoidance success rates improved significantly more in the exercise group (on average 12%) compared to the control group (on average 6%). Quiet stance and weight-shifting measures did not show significant effects of exercise. The exercise group also had a 6% increase of balance confidence scores. The Nijmegen Falls Prevention Program was effective in reducing the incidence of falls in otherwise healthy elderly. There was no evidence of improved control of posture as a mechanism underlying this result. In contrast, an obstacle avoidance task indicated that subjects improved their performance. Laboratory obstacle avoidance tests may therefore be better instruments to evaluate future fall prevention studies than posturographic balance assessments. Copyright (c) 2006 S. Karger AG, Basel.

Suppression of emission rates improves sonar performance by flying bats.

PubMed

Adams, Amanda M; Davis, Kaylee; Smotherman, Michael

2017-01-31

Echolocating bats face the challenge of actively sensing their environment through their own emissions, while also hearing calls and echoes of nearby conspecifics. How bats mitigate interference is a long-standing question that has both ecological and technological implications, as biosonar systems continue to outperform man-made sonar systems in noisy, cluttered environments. We recently showed that perched bats decreased calling rates in groups, displaying a behavioral strategy resembling the back-off algorithms used in artificial communication networks to optimize information throughput at the group level. We tested whether free-tailed bats (Tadarida brasiliensis) would employ such a coordinated strategy while performing challenging flight maneuvers, and report here that bats navigating obstacles lowered emission rates when hearing artificial playback of another bat's calls. We measured the impact of acoustic interference on navigation performance and show that the calculated reductions in interference rates are sufficient to reduce interference and improve obstacle avoidance. When bats flew in pairs, each bat responded to the presence of the other as an obstacle by increasing emissions, but hearing the sonar emissions of the nearby bat partially suppressed this response. This behavior supports social cohesion by providing a key mechanism for minimizing mutual interference.

Suppression of emission rates improves sonar performance by flying bats

PubMed Central

Adams, Amanda M.; Davis, Kaylee; Smotherman, Michael

2017-01-01

Echolocating bats face the challenge of actively sensing their environment through their own emissions, while also hearing calls and echoes of nearby conspecifics. How bats mitigate interference is a long-standing question that has both ecological and technological implications, as biosonar systems continue to outperform man-made sonar systems in noisy, cluttered environments. We recently showed that perched bats decreased calling rates in groups, displaying a behavioral strategy resembling the back-off algorithms used in artificial communication networks to optimize information throughput at the group level. We tested whether free-tailed bats (Tadarida brasiliensis) would employ such a coordinated strategy while performing challenging flight maneuvers, and report here that bats navigating obstacles lowered emission rates when hearing artificial playback of another bat’s calls. We measured the impact of acoustic interference on navigation performance and show that the calculated reductions in interference rates are sufficient to reduce interference and improve obstacle avoidance. When bats flew in pairs, each bat responded to the presence of the other as an obstacle by increasing emissions, but hearing the sonar emissions of the nearby bat partially suppressed this response. This behavior supports social cohesion by providing a key mechanism for minimizing mutual interference. PMID:28139707

Target Trailing With Safe Navigation With Colregs for Maritime Autonomous Surface Vehicles

NASA Technical Reports Server (NTRS)

Kuwata, Yoshiaki (Inventor); Aghazarian, Hrand (Inventor); Huntsberger, Terrance L. (Inventor); Howard, Andrew B. (Inventor); Wolf, Michael T. (Inventor); Zarzhitsky, Dimitri V. (Inventor)

2014-01-01

Systems and methods for operating autonomous waterborne vessels in a safe manner. The systems include hardware for identifying the locations and motions of other vessels, as well as the locations of stationary objects that represent navigation hazards. By applying a computational method that uses a maritime navigation algorithm for avoiding hazards and obeying COLREGS using Velocity Obstacles to the data obtained, the autonomous vessel computes a safe and effective path to be followed in order to accomplish a desired navigational end result, while operating in a manner so as to avoid hazards and to maintain compliance with standard navigational procedures defined by international agreement. The systems and methods have been successfully demonstrated on water with radar and stereo cameras as the perception sensors, and integrated with a higher level planner for trailing a maneuvering target.

Stereo-vision-based terrain mapping for off-road autonomous navigation

NASA Astrophysics Data System (ADS)

Rankin, Arturo L.; Huertas, Andres; Matthies, Larry H.

2009-05-01

Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with perception sensors mounted to a UGV: binary obstacle detection and traversability cost analysis. Binary obstacle detectors label terrain as either traversable or non-traversable, whereas, traversability cost analysis assigns a cost to driving over a discrete patch of terrain. In uncluttered environments where the non-obstacle terrain is equally traversable, binary obstacle detection is sufficient. However, in cluttered environments, some form of traversability cost analysis is necessary. The Jet Propulsion Laboratory (JPL) has explored both approaches using stereo vision systems. A set of binary detectors has been implemented that detect positive obstacles, negative obstacles, tree trunks, tree lines, excessive slope, low overhangs, and water bodies. A compact terrain map is built from each frame of stereo images. The mapping algorithm labels cells that contain obstacles as nogo regions, and encodes terrain elevation, terrain classification, terrain roughness, traversability cost, and a confidence value. The single frame maps are merged into a world map where temporal filtering is applied. In previous papers, we have described our perception algorithms that perform binary obstacle detection. In this paper, we summarize the terrain mapping capabilities that JPL has implemented during several UGV programs over the last decade and discuss some challenges to building terrain maps with stereo range data.

Stereo Vision Based Terrain Mapping for Off-Road Autonomous Navigation

NASA Technical Reports Server (NTRS)

Rankin, Arturo L.; Huertas, Andres; Matthies, Larry H.

2009-01-01

Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with perception sensors mounted to a UGV: binary obstacle detection and traversability cost analysis. Binary obstacle detectors label terrain as either traversable or non-traversable, whereas, traversability cost analysis assigns a cost to driving over a discrete patch of terrain. In uncluttered environments where the non-obstacle terrain is equally traversable, binary obstacle detection is sufficient. However, in cluttered environments, some form of traversability cost analysis is necessary. The Jet Propulsion Laboratory (JPL) has explored both approaches using stereo vision systems. A set of binary detectors has been implemented that detect positive obstacles, negative obstacles, tree trunks, tree lines, excessive slope, low overhangs, and water bodies. A compact terrain map is built from each frame of stereo images. The mapping algorithm labels cells that contain obstacles as no-go regions, and encodes terrain elevation, terrain classification, terrain roughness, traversability cost, and a confidence value. The single frame maps are merged into a world map where temporal filtering is applied. In previous papers, we have described our perception algorithms that perform binary obstacle detection. In this paper, we summarize the terrain mapping capabilities that JPL has implemented during several UGV programs over the last decade and discuss some challenges to building terrain maps with stereo range data.

Any way you look at it, successful obstacle negotiation needs visually guided on-line foot placement regulation during the approach phase.

PubMed

Patla, Aftab E; Greig, Michael

In the two experiments discussed in this paper we quantified obstacle avoidance performance characteristics carried out open loop (without vision) but with different initial visual sampling conditions and compared it to the full vision condition. The initial visual sampling conditions included: static vision (SV), vision during forward walking for three steps and stopping (FW), vision during forward walking for three steps and not stopping (FW-NS), and vision during backward walking for three steps and stopping (BW). In experiment 1, we compared performance during SV, FW and BW with full vision condition, while in the second experiment we compared performance during FW and FW-NS conditions. The questions we wanted to address are: Is ecologically valid dynamic visual sampling of the environment superior to static visual sampling for open loop obstacle avoidance task? What are the reasons for failure in performing open loop obstacle avoidance task? The results showed that irrespective of the initial visual sampling condition when open loop control is initiated from a standing posture, the success rate was only approximately 50%. The main reason for the high failure rates was not inappropriate limb elevation, but incorrect foot placement before the obstacle. The second experiment showed that it is not the nature of visual sampling per se that influences success rate, but the fact that the open loop obstacle avoidance task is initiated from a standing posture. The results of these two experiments clearly demonstrate the importance of on-line visual information for adaptive human locomotion.

Real-time obstacle and collision avoidance system for fixed wing unmanned aerial systems

NASA Astrophysics Data System (ADS)

Esposito, Julien F.

The first original contribution of this research is the Advanced Mapping and Waypoint Generator (AMWG), a piece of software which processes publicly available elevation data in order to only retain the information necessary for a given altitude-specific flight mission. The AMWG is what makes systematic offline trajectory possible. The AMWG first creates altitude groups in order to discard elevations points which are not relevant to a specific mission because of the altitude flown at. Those groups referred to as altitude layers can in turn be reused if the original layer becomes unsafe for the altitude range in use, and the other layers are used for altitude re-scheduling in order to update the current altitude layer to a safer layer. Each layer is bounded by a lower and higher altitude, within which terrain contours are considered constant according to a conservative approach involving the principle of natural erosion. The AMWG then proceeds to obstacle contours extraction using threshold and edge detection vision algorithms. A simplification of those obstacle contours and their corresponding free space zones counterparts is performed using a fixed -tolerance Douglas-Peucker algorithm. This simplification allows free space zones to be described by vectors instead of point clouds, which enables UAS point location. The final product of the AWMG is a network of connected free space trapezoidal cells with embedded connectivity information referred to as the Synthetic Terrain Avoidance (STA network). The walls of the trapezoidal cells are then extruded as the AWMG essentially approximates a three-dimensional world by considering it as a stratification of two-dimensional layers, but the real-time phase needs 3D support. Using the graph conceptual view and the depth first search algorithm, all the connected cell sequences joining the departure to the arrival cell can be listed, a capability which is used during aircraft rerouting. By connecting two adjacent cells' centroids to their common midpoint located on the shared edge, the resulting flying legs remain within the two cells. The next step for paths between two cells is to be converted into flyable paths, and the conversion uses main and fallback methods to achieve that. The preferred method is the closed-form Dubins paths method involving the design of sequences of arc circle-straight line-arc circle (CLC) in order to account for the minimum radius turn constrain of the UAS. An additional geometric transformation is developed and applied to the initial waypoints used in the Dubins method so the flying leg directions are respected which is not possible by using the Dubins method alone. The second original contribution of this research is the development and demonstration of the Double Dispersion reduction RRT (DDRRT), an algorithm which employs two new developed logic schemes respectively referred to as Punctual Dispersion Reduction (PDR), and Spatial Dispersion Reduction exploration (SDR). The DDRRT is employed during the real-time in-flight phase where it initially assumes a perfect terrain and no unpredictable threat, consequently following a 100% adaptive goal biasing toward the next waypoint in its list. When a threat such as an unpredicted obstacle is detected, the (PDR) acknowledges the fact that the DDRRT tree branches have met an obstacle and the its goal-biasing toward the next waypoint is decreased. If the PDR keeps decreasing, the DDRRT develops awareness of its surrounding obstacles by relaxing its PDR and switching to SDR which has the effect of increasing the dispersion of its branches, but keeping their extension bounded by the cell containing the last good position of the UAS, Csafe. (Abstract shortened by UMI.)

Age-related changes in gait adaptability in response to unpredictable obstacles and stepping targets.

PubMed

Caetano, Maria Joana D; Lord, Stephen R; Schoene, Daniel; Pelicioni, Paulo H S; Sturnieks, Daina L; Menant, Jasmine C

2016-05-01

A large proportion of falls in older people occur when walking. Limitations in gait adaptability might contribute to tripping; a frequently reported cause of falls in this group. To evaluate age-related changes in gait adaptability in response to obstacles or stepping targets presented at short notice, i.e.: approximately two steps ahead. Fifty older adults (aged 74±7 years; 34 females) and 21 young adults (aged 26±4 years; 12 females) completed 3 usual gait speed (baseline) trials. They then completed the following randomly presented gait adaptability trials: obstacle avoidance, short stepping target, long stepping target and no target/obstacle (3 trials of each). Compared with the young, the older adults slowed significantly in no target/obstacle trials compared with the baseline trials. They took more steps and spent more time in double support while approaching the obstacle and stepping targets, demonstrated poorer stepping accuracy and made more stepping errors (failed to hit the stepping targets/avoid the obstacle). The older adults also reduced velocity of the two preceding steps and shortened the previous step in the long stepping target condition and in the obstacle avoidance condition. Compared with their younger counterparts, the older adults exhibited a more conservative adaptation strategy characterised by slow, short and multiple steps with longer time in double support. Even so, they demonstrated poorer stepping accuracy and made more stepping errors. This reduced gait adaptability may place older adults at increased risk of falling when negotiating unexpected hazards. Copyright © 2016 Elsevier B.V. All rights reserved.

A Neural Model of Visually Guided Steering, Obstacle Avoidance, and Route Selection

ERIC Educational Resources Information Center

Elder, David M.; Grossberg, Stephen; Mingolla, Ennio

2009-01-01

A neural model is developed to explain how humans can approach a goal object on foot while steering around obstacles to avoid collisions in a cluttered environment. The model uses optic flow from a 3-dimensional virtual reality environment to determine the position of objects on the basis of motion discontinuities and computes heading direction,…

The role of tragus on echolocating bat, Eptesicus fuscus

NASA Astrophysics Data System (ADS)

Chiu, Chen; Moss, Cynthia

2005-04-01

Echolocating bats produce ultrasonic vocal signals and utilize the returning echoes to detect, localize and track prey, and also to avoid obstacles. The pinna and tragus, two major components of the bats external ears, play important roles in filtering returning echoes. The tragus is generally believed to play a role in vertical sound localization. The purpose of this study is to further examine how manipulation of the tragus affects a free-flying bat's prey capture and obstacle avoidance behavior. The first part of this study involved a prey capture experiment, and the bat was trained to catch the tethered mealworms in a large room. The second experiment involved obstacle avoidance, and the bat's task was to fly through the largest opening from a horizontal wire array without touching the wires. In both experiments, the bat performed the tasks under three different conditions: with intact tragus, tragus-deflection and recovery from tragus-deflection. Significantly lower performance was observed in both experiments when tragi were glued down. However, the bat adjusted quickly and returned to baseline performance a few days after the manipulation. The results suggest that tragus-deflection does have effects on both the prey capture and obstacle avoidance behavior. [Work supported by NSF.

Vision and agility training in community dwelling older adults: incorporating visual training into programs for fall prevention.

PubMed

Reed-Jones, Rebecca J; Dorgo, Sandor; Hitchings, Maija K; Bader, Julia O

2012-04-01

This study aimed to examine the effect of visual training on obstacle course performance of independent community dwelling older adults. Agility is the ability to rapidly alter ongoing motor patterns, an important aspect of mobility which is required in obstacle avoidance. However, visual information is also a critical factor in successful obstacle avoidance. We compared obstacle course performance of a group that trained in visually driven body movements and agility drills, to a group that trained only in agility drills. We also included a control group that followed the American College of Sports Medicine exercise recommendations for older adults. Significant gains in fitness, mobility and power were observed across all training groups. Obstacle course performance results revealed that visual training had the greatest improvement on obstacle course performance (22%) following a 12 week training program. These results suggest that visual training may be an important consideration for fall prevention programs. Copyright © 2011 Elsevier B.V. All rights reserved.

The retrieval of a buried cylindrical obstacle by a constrained modified gradient method in the H-polarization case and for Maxwellian materials

NASA Astrophysics Data System (ADS)

Lambert, M.; Lesselier, D.; Kooij, B. J.

1998-10-01

The retrieval of an unknown, possibly inhomogeneous, penetrable cylindrical obstacle buried entirely in a known homogeneous half-space - the constitutive material parameters of the obstacle and of its embedding obey a Maxwell model - is considered from single- or multiple-frequency aspect-limited data collected by ideal sensors located in air above the embedding half-space, when a small number of time-harmonic transverse electric (TE)-polarized line sources - the magnetic field H is directed along the axis of the cylinder - is also placed in air. The wavefield is modelled from a rigorous H-field domain integral-differential formulation which involves the dot product of the gradients of the single component of H and of the Green function of the stratified environment times a scalar-valued contrast function which contains the obstacle parameters (the frequency-independent, position-dependent relative permittivity and conductivity). A modified gradient method is developed in order to reconstruct the maps of such parameters within a prescribed search domain from the iterative minimization of a cost functional which incorporates both the error in reproducing the data and the error on the field built inside this domain. Non-physical values are excluded and convergence reached by incorporating in the solution algorithm, from a proper choice of unknowns, the condition that the relative permittivity be larger than or equal to 1, and the conductivity be non-negative. The efficiency of the constrained method is illustrated from noiseless and noisy synthetic data acquired independently. The importance of the choice of the initial values of the sought quantities, the need for a periodic refreshment of the constitutive parameters to avoid the algorithm providing inconsistent results, and the interest of a frequency-hopping strategy to obtain finer and finer features of the obstacle when the frequency is raised, are underlined. It is also shown that though either the permittivity map or the conductivity map can be obtained for a fair variety of cases, retrieving both of them may be difficult unless further information is made available.

Obstacle-avoiding robot with IR and PIR motion sensors

NASA Astrophysics Data System (ADS)

Ismail, R.; Omar, Z.; Suaibun, S.

2016-10-01

Obstacle avoiding robot was designed, constructed and programmed which may be potentially used for educational and research purposes. The developed robot will move in a particular direction once the infrared (IR) and the PIR passive infrared (PIR) sensors sense a signal while avoiding the obstacles in its path. The robot can also perform desired tasks in unstructured environments without continuous human guidance. The hardware was integrated in one application board as embedded system design. The software was developed using C++ and compiled by Arduino IDE 1.6.5. The main objective of this project is to provide simple guidelines to the polytechnic students and beginners who are interested in this type of research. It is hoped that this robot could benefit students who wish to carry out research on IR and PIR sensors.

An intelligent rollator for mobility impaired persons, especially stroke patients.

PubMed

Hellström, Thomas; Lindahl, Olof; Bäcklund, Tomas; Karlsson, Marcus; Hohnloser, Peter; Bråndal, Anna; Hu, Xiaolei; Wester, Per

2016-07-01

An intelligent rollator (IRO) was developed that aims at obstacle detection and guidance to avoid collisions and accidental falls. The IRO is a retrofit four-wheeled rollator with an embedded computer, two solenoid brakes, rotation sensors on the wheels and IR-distance sensors. The value reported by each distance sensor was compared in the computer to a nominal distance. Deviations indicated a present obstacle and caused activation of one of the brakes in order to influence the direction of motion to avoid the obstacle. The IRO was tested by seven healthy subjects with simulated restricted and blurred sight and five stroke subjects on a standardised indoor track with obstacles. All tested subjects walked faster with intelligence deactivated. Three out of five stroke patients experienced more detected obstacles with intelligence activated. This suggests enhanced safety during walking with IRO. Further studies are required to explore the full value of the IRO.

Optimal Control of Hybrid Systems in Air Traffic Applications

NASA Astrophysics Data System (ADS)

Kamgarpour, Maryam

Growing concerns over the scalability of air traffic operations, air transportation fuel emissions and prices, as well as the advent of communication and sensing technologies motivate improvements to the air traffic management system. To address such improvements, in this thesis a hybrid dynamical model as an abstraction of the air traffic system is considered. Wind and hazardous weather impacts are included using a stochastic model. This thesis focuses on the design of algorithms for verification and control of hybrid and stochastic dynamical systems and the application of these algorithms to air traffic management problems. In the deterministic setting, a numerically efficient algorithm for optimal control of hybrid systems is proposed based on extensions of classical optimal control techniques. This algorithm is applied to optimize the trajectory of an Airbus 320 aircraft in the presence of wind and storms. In the stochastic setting, the verification problem of reaching a target set while avoiding obstacles (reach-avoid) is formulated as a two-player game to account for external agents' influence on system dynamics. The solution approach is applied to air traffic conflict prediction in the presence of stochastic wind. Due to the uncertainty in forecasts of the hazardous weather, and hence the unsafe regions of airspace for aircraft flight, the reach-avoid framework is extended to account for stochastic target and safe sets. This methodology is used to maximize the probability of the safety of aircraft paths through hazardous weather. Finally, the problem of modeling and optimization of arrival air traffic and runway configuration in dense airspace subject to stochastic weather data is addressed. This problem is formulated as a hybrid optimal control problem and is solved with a hierarchical approach that decouples safety and performance. As illustrated with this problem, the large scale of air traffic operations motivates future work on the efficient implementation of the proposed algorithms.

A New Technique for Compensating Joint Limits in a Robot Manipulator

NASA Technical Reports Server (NTRS)

Litt, Jonathan; Hickman, Andre; Guo, Ten-Huei

1996-01-01

A new robust, optimal, adaptive technique for compensating rate and position limits in the joints of a six degree-of-freedom elbow manipulator is presented. In this new algorithm, the unmet demand as a result of actuator saturation is redistributed among the remaining unsaturated joints. The scheme is used to compensate for inadequate path planning, problems such as joint limiting, joint freezing, or even obstacle avoidance, where a desired position and orientation are not attainable due to an unrealizable joint command. Once a joint encounters a limit, supplemental commands are sent to other joints to best track, according to a selected criterion, the desired trajectory.

Embedded mobile farm robot for identification of diseased plants

NASA Astrophysics Data System (ADS)

Sadistap, S. S.; Botre, B. A.; Pandit, Harshavardhan; Chandrasekhar; Rao, Adesh

2013-07-01

This paper presents the development of a mobile robot used in farms for identification of diseased plants. It puts forth two of the major aspects of robotics namely automated navigation and image processing. The robot navigates on the basis of the GPS (Global Positioning System) location and data obtained from IR (Infrared) sensors to avoid any obstacles in its path. It uses an image processing algorithm to differentiate between diseased and non-diseased plants. A robotic platform consisting of an ARM9 processor, motor drivers, robot mechanical assembly, camera and infrared sensors has been used. Mini2440 microcontroller has been used wherein Embedded linux OS (Operating System) is implemented.

Obstacle Avoidance, Visual Detection Performance, and Eye-Scanning Behavior of Glaucoma Patients in a Driving Simulator: A Preliminary Study

PubMed Central

Prado Vega, Rocío; van Leeuwen, Peter M.; Rendón Vélez, Elizabeth; Lemij, Hans G.; de Winter, Joost C. F.

2013-01-01

The objective of this study was to evaluate differences in driving performance, visual detection performance, and eye-scanning behavior between glaucoma patients and control participants without glaucoma. Glaucoma patients (n = 23) and control participants (n = 12) completed four 5-min driving sessions in a simulator. The participants were instructed to maintain the car in the right lane of a two-lane highway while their speed was automatically maintained at 100 km/h. Additional tasks per session were: Session 1: none, Session 2: verbalization of projected letters, Session 3: avoidance of static obstacles, and Session 4: combined letter verbalization and avoidance of static obstacles. Eye-scanning behavior was recorded with an eye-tracker. Results showed no statistically significant differences between patients and control participants for lane keeping, obstacle avoidance, and eye-scanning behavior. Steering activity, number of missed letters, and letter reaction time were significantly higher for glaucoma patients than for control participants. In conclusion, glaucoma patients were able to avoid objects and maintain a nominal lane keeping performance, but applied more steering input than control participants, and were more likely than control participants to miss peripherally projected stimuli. The eye-tracking results suggest that glaucoma patients did not use extra visual search to compensate for their visual field loss. Limitations of the study, such as small sample size, are discussed. PMID:24146975

Dynamic Distributed Cooperative Control of Multiple Heterogeneous Resources

DTIC Science & Technology

2012-10-01

of the UAVs to maximize the total sensor footprint over the region of interest. The algorithm utilized to solve this problem was based on sampling a...and moving obstacles. Obstacle positions were assumed known a priori. Kingston and Beard [22] presented an algorithm to keep moving UAVs equally spaced...Planning Algorithms , Cambridge University Press, 2006. 11. Ma, C. S. and Miller, R. H., “Mixed integer linear programming trajectory generation for

Evolutionary programming-based univector field navigation method for past mobile robots.

PubMed

Kim, Y J; Kim, J H; Kwon, D S

2001-01-01

Most of navigation techniques with obstacle avoidance do not consider the robot orientation at the target position. These techniques deal with the robot position only and are independent of its orientation and velocity. To solve these problems this paper proposes a novel univector field method for fast mobile robot navigation which introduces a normalized two dimensional vector field. The method provides fast moving robots with the desired posture at the target position and obstacle avoidance. To obtain the sub-optimal vector field, a function approximator is used and trained by evolutionary programming. Two kinds of vector fields are trained, one for the final posture acquisition and the other for obstacle avoidance. Computer simulations and real experiments are carried out for a fast moving mobile robot to demonstrate the effectiveness of the proposed scheme.

Fuzzy Logic Path Planning System for Collision Avoidance by an Autonomous Rover Vehicle

NASA Technical Reports Server (NTRS)

Murphy, Michael G.

1991-01-01

Systems already developed at JSC have shown the benefits of applying fuzzy logic control theory to space related operations. Four major issues are addressed that are associated with developing an autonomous collision avoidance subsystem within a path planning system designed for application in a remote, hostile environment that does not lend itself well to remote manipulation of the vehicle involved through Earth-based telecommunication. A good focus for this is unmanned exploration of the surface of Mars. The uncertainties involved indicate that robust approaches such as fuzzy logic control are particularly appropriate. The four major issues addressed are: (1) avoidance of a single fuzzy moving obstacle; (2) back off from a dead end in a static obstacle environment; (3) fusion of sensor data to detect obstacles; and (4) options for adaptive learning in a path planning system.

Fast obstacle detection based on multi-sensor information fusion

NASA Astrophysics Data System (ADS)

Lu, Linli; Ying, Jie

2014-11-01

Obstacle detection is one of the key problems in areas such as driving assistance and mobile robot navigation, which cannot meet the actual demand by using a single sensor. A method is proposed to realize the real-time access to the information of the obstacle in front of the robot and calculating the real size of the obstacle area according to the mechanism of the triangle similarity in process of imaging by fusing datum from a camera and an ultrasonic sensor, which supports the local path planning decision. In the part of image analyzing, the obstacle detection region is limited according to complementary principle. We chose ultrasonic detection range as the region for obstacle detection when the obstacle is relatively near the robot, and the travelling road area in front of the robot is the region for a relatively-long-distance detection. The obstacle detection algorithm is adapted from a powerful background subtraction algorithm ViBe: Visual Background Extractor. We extracted an obstacle free region in front of the robot in the initial frame, this region provided a reference sample set of gray scale value for obstacle detection. Experiments of detecting different obstacles at different distances respectively, give the accuracy of the obstacle detection and the error percentage between the calculated size and the actual size of the detected obstacle. Experimental results show that the detection scheme can effectively detect obstacles in front of the robot and provide size of the obstacle with relatively high dimensional accuracy.

Environmental Recognition and Guidance Control for Autonomous Vehicles using Dual Vision Sensor and Applications

NASA Astrophysics Data System (ADS)

Moriwaki, Katsumi; Koike, Issei; Sano, Tsuyoshi; Fukunaga, Tetsuya; Tanaka, Katsuyuki

We propose a new method of environmental recognition around an autonomous vehicle using dual vision sensor and navigation control based on binocular images. We consider to develop a guide robot that can play the role of a guide dog as the aid to people such as the visually impaired or the aged, as an application of above-mentioned techniques. This paper presents a recognition algorithm, which finds out the line of a series of Braille blocks and the boundary line between a sidewalk and a roadway where a difference in level exists by binocular images obtained from a pair of parallelarrayed CCD cameras. This paper also presents a tracking algorithm, with which the guide robot traces along a series of Braille blocks and avoids obstacles and unsafe areas which exist in the way of a person with the guide robot.

Stochastic performance modeling and evaluation of obstacle detectability with imaging range sensors

NASA Technical Reports Server (NTRS)

Matthies, Larry; Grandjean, Pierrick

1993-01-01

Statistical modeling and evaluation of the performance of obstacle detection systems for Unmanned Ground Vehicles (UGVs) is essential for the design, evaluation, and comparison of sensor systems. In this report, we address this issue for imaging range sensors by dividing the evaluation problem into two levels: quality of the range data itself and quality of the obstacle detection algorithms applied to the range data. We review existing models of the quality of range data from stereo vision and AM-CW LADAR, then use these to derive a new model for the quality of a simple obstacle detection algorithm. This model predicts the probability of detecting obstacles and the probability of false alarms, as a function of the size and distance of the obstacle, the resolution of the sensor, and the level of noise in the range data. We evaluate these models experimentally using range data from stereo image pairs of a gravel road with known obstacles at several distances. The results show that the approach is a promising tool for predicting and evaluating the performance of obstacle detection with imaging range sensors.

A soft robot capable of 2D mobility and self-sensing for obstacle detection and avoidance

NASA Astrophysics Data System (ADS)

Qin, Lei; Tang, Yucheng; Gupta, Ujjaval; Zhu, Jian

2018-04-01

Soft robots have shown great potential for surveillance applications due to their interesting attributes including inherent flexibility, extreme adaptability, and excellent ability to move in confined spaces. High mobility combined with the sensing systems that can detect obstacles plays a significant role in performing surveillance tasks. Extensive studies have been conducted on movement mechanisms of traditional hard-bodied robots to increase their mobility. However, there are limited efforts in the literature to explore the mobility of soft robots. In addition, little attempt has been made to study the obstacle-detection capability of a soft mobile robot. In this paper, we develop a soft mobile robot capable of high mobility and self-sensing for obstacle detection and avoidance. This robot, consisting of a dielectric elastomer actuator as the robot body and four electroadhesion actuators as the robot feet, can generate 2D mobility, i.e. translations and turning in a 2D plane, by programming the actuation sequence of the robot body and feet. Furthermore, we develop a self-sensing method which models the robot body as a deformable capacitor. By measuring the real-time capacitance of the robot body, the robot can detect an obstacle when the peak capacitance drops suddenly. This sensing method utilizes the robot body itself instead of external sensors to achieve detection of obstacles, which greatly reduces the weight and complexity of the robot system. The 2D mobility and self-sensing capability ensure the success of obstacle detection and avoidance, which paves the way for the development of lightweight and intelligent soft mobile robots.

Uncertainty management for aerial vehicles: Coordination, deconfliction, and disturbance rejection

NASA Astrophysics Data System (ADS)

Panyakeow, Prachya

The presented dissertation aims to develop control algorithms that deal with three types of uncertainties managements. First, we examine the situation when unmanned aerial vehicles (UAVs) fly through uncertain environments that contain both stationary and moving obstacles. Moreover, a guarantee of collision avoidance is necessary when UAVs operate in close proximity of each other. Second, we look at the communication uncertainty among the network of cooperative UAVs and the efforts to establish and maintain the connectivity throughout their entire missions. Third, we explore the scenario when the aircraft flies through wind gust. The introduction of an appropriate control scheme to actively alleviate the gust loads can result into weight reduction and consequently lower the fuel cost. In the first part of this dissertation, we develop a deconfliction algorithm that guarantees collision avoidance between a pair of constant speed unicycle-type UAVs as well as convergence to the desired destination for each UAV in presence of static obstacles. We use a combination of navigation and swirling functions to direct the unicycle vehicles along the planned trajectories while avoiding inter-vehicle collisions. The main feature of our contribution is proposing means of designing a deconfliction algorithm for unicycle vehicles that more closely capture the dynamics of constant speed UAVs as opposed to double integrator models. Specifically, we consider the issue of UAV turn-rate constraints and proceed to explore the selection of key algorithmic parameters in order to minimize undesirable trajectories and overshoots induced by the avoidance algorithm. The avoidance and convergence analysis of the proposed algorithm is then performed for two cooperative UAVs and simulation results are provided to support the viability of the proposed framework for more general mission scenarios. For the uncertainty of the UAV network, we provides two approaches to establish connectivity among a collection of UAVs that are initially scattered in space. The goal is to find shortest trajectories that bring the UAVs to a connected formation where they are in the range of detection of one another and headed in the same direction to maintain the connectivity. Pontryagin Minimum Principle (PMP) is utilized to determine the control law and path synthesis for the UAVs under the turn-rate constraints. We introduce an algorithm to search for the optimal solution when the final network topology is specified; followed by a nonlinear programming method in which the final configuration is emerged from the optimization routine under the constraints that the final topology is connected. Each method has its own advantages based on the size of corporative networks. For the uncertainty due to gust turbulence, we choose a model predictive control (MPC) technique to address gust load alleviation (GLA) for a flexible aircraft. MPC is a discrete method based on repeated online optimization that allows direct consideration of control actuator constraints into the feedback computation. Gust alleviation systems are dependent on how the structural flexibility of the aircraft affects its dynamics. Hence, we develop a six-degree-of-freedom flexible aircraft model that can integrate rigid body dynamic with structural deflection. The structural stick-and-beam model is utilized for the calculation of aeroelastic mode shapes and airframe loads. Another important feature of MPC for GLA design is the ability to include the preview of gust information ahead of the aircraft nose into the prediction process. This helps raising the prediction accuracy and consequently improves the load alleviation performance. Finally, the aircraft is modified by the addition of the flap-array, a composition of small trailing edge flaps throughout the entire span of the wings. These flaps are used in conjunction with the distributed spoilers. With the availability of the control surfaces closer to the wing root, the MPC with flap-array can reduce the wing bending moment from different mode shapes and achieve better load alleviation performance than the original aircraft.

Needle Steering in 3-D Via Rapid Replanning

PubMed Central

Patil, Sachin; Burgner, Jessica; Webster, Robert J.; Alterovitz, Ron

2014-01-01

Steerable needles have the potential to improve the effectiveness of needle-based clinical procedures such as biopsy and drug delivery by improving targeting accuracy and reaching previously inaccessible targets that are behind sensitive or impenetrable anatomical regions. We present a new needle steering system capable of automatically reaching targets in 3-D environments while avoiding obstacles and compensating for real-world uncertainties. Given a specification of anatomical obstacles and a clinical target (e.g., from preoperative medical images), our system plans and controls needle motion in a closed-loop fashion under sensory feedback to optimize a clinical metric. We unify planning and control using a new fast algorithm that continuously replans the needle motion. Our rapid replanning approach is enabled by an efficient sampling-based rapidly exploring random tree (RRT) planner that achieves orders-of-magnitude reduction in computation time compared with prior 3-D approaches by incorporating variable curvature kinematics and a novel distance metric for planning. Our system uses an electromagnetic tracking system to sense the state of the needle tip during the procedure. We experimentally evaluate our needle steering system using tissue phantoms and animal tissue ex vivo. We demonstrate that our rapid replanning strategy successfully guides the needle around obstacles to desired 3-D targets with an average error of less than 3 mm. PMID:25435829

Two Formal Gas Models For Multi-Agent Sweeping and Obstacle Avoidance

NASA Technical Reports Server (NTRS)

Kerr, Wesley; Spears, Diana; Spears, William; Thayer, David

2004-01-01

The task addressed here is a dynamic search through a bounded region, while avoiding multiple large obstacles, such as buildings. In the case of limited sensors and communication, maintaining spatial coverage - especially after passing the obstacles - is a challenging problem. Here, we investigate two physics-based approaches to solving this task with multiple simulated mobile robots, one based on artificial forces and the other based on the kinetic theory of gases. The desired behavior is achieved with both methods, and a comparison is made between them. Because both approaches are physics-based, formal assurances about the multi-robot behavior are straightforward, and are included in the paper.

Micro air vehicle autonomous obstacle avoidance from stereo-vision

NASA Astrophysics Data System (ADS)

Brockers, Roland; Kuwata, Yoshiaki; Weiss, Stephan; Matthies, Lawrence

2014-06-01

We introduce a new approach for on-board autonomous obstacle avoidance for micro air vehicles flying outdoors in close proximity to structure. Our approach uses inverse-range, polar-perspective stereo-disparity maps for obstacle detection and representation, and deploys a closed-loop RRT planner that considers flight dynamics for trajectory generation. While motion planning is executed in 3D space, we reduce collision checking to a fast z-buffer-like operation in disparity space, which allows for significant speed-up compared to full 3d methods. Evaluations in simulation illustrate the robustness of our approach, whereas real world flights under tree canopy demonstrate the potential of the approach.

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.

Obstacle-avoiding navigation system

DOEpatents

Borenstein, Johann; Koren, Yoram; Levine, Simon P.

1991-01-01

A system for guiding an autonomous or semi-autonomous vehicle through a field of operation having obstacles thereon to be avoided employs a memory for containing data which defines an array of grid cells which correspond to respective subfields in the field of operation of the vehicle. Each grid cell in the memory contains a value which is indicative of the likelihood, or probability, that an obstacle is present in the respectively associated subfield. The values in the grid cells are incremented individually in response to each scan of the subfields, and precomputation and use of a look-up table avoids complex trigonometric functions. A further array of grid cells is fixed with respect to the vehicle form a conceptual active window which overlies the incremented grid cells. Thus, when the cells in the active window overly grid cell having values which are indicative of the presence of obstacles, the value therein is used as a multiplier of the precomputed vectorial values. The resulting plurality of vectorial values are summed vectorially in one embodiment of the invention to produce a virtual composite repulsive vector which is then summed vectorially with a target-directed vector for producing a resultant vector for guiding the vehicle. In an alternative embodiment, a plurality of vectors surrounding the vehicle are computed, each having a value corresponding to obstacle density. In such an embodiment, target location information is used to select between alternative directions of travel having low associated obstacle densities.

Obstacle stepping involves spinal anticipatory activity associated with quadrupedal limb coordination.

PubMed

Michel, J; van Hedel, H J A; Dietz, V

2008-04-01

Obstacle avoidance steps are associated with a facilitation of spinal reflexes in leg muscles. Here we have examined the involvement of both leg and arm muscles. Subjects walking with reduced vision on a treadmill were acoustically informed about an approaching obstacle and received feedback about task performance. Reflex responses evoked by tibial nerve stimulation were observed in all arm and leg muscles examined in this study. They were enhanced before the execution of obstacle avoidance compared with normal steps and showed an exponential adaptation in contralateral arm flexor muscles corresponding to the improvement of task performance. This enhancement was absent when the body was partially supported during the task. During the execution of obstacle steps, electromyographic activity in the arm muscles mimicked the preceding reflex behaviour with respect to enhancement and adaptation. Our results demonstrate an anticipatory quadrupedal limb coordination with an involvement of proximal arm muscles in the acquisition and performance of this precision locomotor task. This is presumably achieved by an up-regulated activity of coupled cervico-thoracal interneuronal circuits.

Prevention 0f Unwanted Free-Declaration of Static Obstacles in Probability Occupancy Grids

NASA Astrophysics Data System (ADS)

Krause, Stefan; Scholz, M.; Hohmann, R.

2017-10-01

Obstacle detection and avoidance are major research fields in unmanned aviation. Map based obstacle detection approaches often use discrete world representations such as probabilistic grid maps to fuse incremental environment data from different views or sensors to build a comprehensive representation. The integration of continuous measurements into a discrete representation can result in rounding errors which, in turn, leads to differences between the artificial model and real environment. The cause of these deviations is a low spatial resolution of the world representation comparison to the used sensor data. Differences between artificial representations which are used for path planning or obstacle avoidance and the real world can lead to unexpected behavior up to collisions with unmapped obstacles. This paper presents three approaches to the treatment of errors that can occur during the integration of continuous laser measurement in the discrete probabilistic grid. Further, the quality of the error prevention and the processing performance are compared with real sensor data.

Energy aware path planning in complex four dimensional environments

NASA Astrophysics Data System (ADS)

Chakrabarty, Anjan

This dissertation addresses the problem of energy-aware path planning for small autonomous vehicles. While small autonomous vehicles can perform missions that are too risky (or infeasible) for larger vehicles, the missions are limited by the amount of energy that can be carried on board the vehicle. Path planning techniques that either minimize energy consumption or exploit energy available in the environment can thus increase range and endurance. Path planning is complicated by significant spatial (and potentially temporal) variations in the environment. While the main focus is on autonomous aircraft, this research also addresses autonomous ground vehicles. Range and endurance of small unmanned aerial vehicles (UAVs) can be greatly improved by utilizing energy from the atmosphere. Wind can be exploited to minimize energy consumption of a small UAV. But wind, like any other atmospheric component , is a space and time varying phenomenon. To effectively use wind for long range missions, both exploration and exploitation of wind is critical. This research presents a kinematics based tree algorithm which efficiently handles the four dimensional (three spatial and time) path planning problem. The Kinematic Tree algorithm provides a sequence of waypoints, airspeeds, heading and bank angle commands for each segment of the path. The planner is shown to be resolution complete and computationally efficient. Global optimality of the cost function cannot be claimed, as energy is gained from the atmosphere, making the cost function inadmissible. However the Kinematic Tree is shown to be optimal up to resolution if the cost function is admissible. Simulation results show the efficacy of this planning method for a glider in complex real wind data. Simulation results verify that the planner is able to extract energy from the atmosphere enabling long range missions. The Kinematic Tree planning framework, developed to minimize energy consumption of UAVs, is applied for path planning in ground robots. In traditional path planning problem the focus is on obstacle avoidance and navigation. The optimal Kinematic Tree algorithm named Kinematic Tree* is shown to find optimal paths to reach the destination while avoiding obstacles. A more challenging path planning scenario arises for planning in complex terrain. This research shows how the Kinematic Tree* algorithm can be extended to find minimum energy paths for a ground vehicle in difficult mountainous terrain.

A Path Planning and Obstacle Avoidance Hybrid System Using a Connectionist Network

DTIC Science & Technology

1990-06-01

Department lele7 Prfessor of Aerospace Sciences and Mathematical Sciences Houston, Texas June, 1990 Abstract A PATH PLANNING AND OBSTACLE AVOIDANCE HYBRID...See Weiland (1989), Wu (1989), Norwood (1989), Cheatham (1987 & 1989), Adnan (1990), and Regalbuto (1988 & 1990).] Possible applications of this...neuron model’s output can be described mathematically as: Yj(t+ At) =sgn ijXi(t)-O Other non-linearity functions, such as and the sigmoid/ logistics

Vision-Based UAV Flight Control and Obstacle Avoidance

DTIC Science & Technology

2006-01-01

denoted it by Vb = (Vb1, Vb2 , Vb3). Fig. 2 shows the block diagram of the proposed vision-based motion analysis and obstacle avoidance system. We denote...structure analysis often involve computation- intensive computer vision tasks, such as feature extraction and geometric modeling. Computation-intensive...First, we extract a set of features from each block. 2) Second, we compute the distance between these two sets of features. In conventional motion

Navigable points estimation for mobile robots using binary image skeletonization

NASA Astrophysics Data System (ADS)

Martinez S., Fernando; Jacinto G., Edwar; Montiel A., Holman

2017-02-01

This paper describes the use of image skeletonization for the estimation of all the navigable points, inside a scene of mobile robots navigation. Those points are used for computing a valid navigation path, using standard methods. The main idea is to find the middle and the extreme points of the obstacles in the scene, taking into account the robot size, and create a map of navigable points, in order to reduce the amount of information for the planning algorithm. Those points are located by means of the skeletonization of a binary image of the obstacles and the scene background, along with some other digital image processing algorithms. The proposed algorithm automatically gives a variable number of navigable points per obstacle, depending on the complexity of its shape. As well as, the way how the algorithm can change some of their parameters in order to change the final number of the resultant key points is shown. The results shown here were obtained applying different kinds of digital image processing algorithms on static scenes.

Interaction dynamics of multiple autonomous mobile robots in bounded spatial domains

NASA Technical Reports Server (NTRS)

Wang, P. K. C.

1989-01-01

A general navigation strategy for multiple autonomous robots in a bounded domain is developed analytically. Each robot is modeled as a spherical particle (i.e., an effective spatial domain about the center of mass); its interactions with other robots or with obstacles and domain boundaries are described in terms of the classical many-body problem; and a collision-avoidance strategy is derived and combined with homing, robot-robot, and robot-obstacle collision-avoidance strategies. Results from homing simulations involving (1) a single robot in a circular domain, (2) two robots in a circular domain, and (3) one robot in a domain with an obstacle are presented in graphs and briefly characterized.

Coarsening of three-dimensional structured and unstructured grids for subsurface flow

NASA Astrophysics Data System (ADS)

Aarnes, Jørg Espen; Hauge, Vera Louise; Efendiev, Yalchin

2007-11-01

We present a generic, semi-automated algorithm for generating non-uniform coarse grids for modeling subsurface flow. The method is applicable to arbitrary grids and does not impose smoothness constraints on the coarse grid. One therefore avoids conventional smoothing procedures that are commonly used to ensure that the grids obtained with standard coarsening procedures are not too rough. The coarsening algorithm is very simple and essentially involves only two parameters that specify the level of coarsening. Consequently the algorithm allows the user to specify the simulation grid dynamically to fit available computer resources, and, e.g., use the original geomodel as input for flow simulations. This is of great importance since coarse grid-generation is normally the most time-consuming part of an upscaling phase, and therefore the main obstacle that has prevented simulation workflows with user-defined resolution. We apply the coarsening algorithm to a series of two-phase flow problems on both structured (Cartesian) and unstructured grids. The numerical results demonstrate that one consistently obtains significantly more accurate results using the proposed non-uniform coarsening strategy than with corresponding uniform coarse grids with roughly the same number of cells.

Validation of vision-based obstacle detection algorithms for low-altitude helicopter flight

NASA Technical Reports Server (NTRS)

Suorsa, Raymond; Sridhar, Banavar

1991-01-01

A validation facility being used at the NASA Ames Research Center is described which is aimed at testing vision based obstacle detection and range estimation algorithms suitable for low level helicopter flight. The facility is capable of processing hundreds of frames of calibrated multicamera 6 degree-of-freedom motion image sequencies, generating calibrated multicamera laboratory images using convenient window-based software, and viewing range estimation results from different algorithms along with truth data using powerful window-based visualization software.

A Stochastic Approach to Path Planning in the Weighted-Region Problem

DTIC Science & Technology

1991-03-01

polynomial time. However, the polyhedrons in this three-dimensional obstacle-avoidance problem are all obstacles (i.e. travel is not permitted within...them). Therefore, optimal paths tend to avoid their vertices, and settle into closest approach tangents across polyhedron edges. So, in a sense...intersection update map database with new vertex for this edge 3. IF (C1 > D) and (C2 > D) THEN edge intersects ellipse at two points OR edge is

Fuzzy logic path planning system for collision avoidance by an autonomous rover vehicle

NASA Technical Reports Server (NTRS)

Murphy, Michael G.

1993-01-01

The Space Exploration Initiative of the United States will make great demands upon NASA and its limited resources. One aspect of great importance will be providing for autonomous (unmanned) operation of vehicles and/or subsystems in space flight and surface exploration. An additional, complicating factor is that much of the need for autonomy of operation will take place under conditions of great uncertainty or ambiguity. Issues in developing an autonomous collision avoidance subsystem within a path planning system for application in a remote, hostile environment that does not lend itself well to remote manipulation by Earth-based telecommunications is addressed. A good focus is unmanned surface exploration of Mars. The uncertainties involved indicate that robust approaches such as fuzzy logic control are particularly appropriate. Four major issues addressed are (1) avoidance of a fuzzy moving obstacle; (2) backoff from a deadend in a static obstacle environment; (3) fusion of sensor data to detect obstacles; and (4) options for adaptive learning in a path planning system. Examples of the need for collision avoidance by an autonomous rover vehicle on the surface of Mars with a moving obstacle would be wind-blown debris, surface flow or anomalies due to subsurface disturbances, another vehicle, etc. The other issues of backoff, sensor fusion, and adaptive learning are important in the overall path planning system.

Suboptimal artificial potential function sliding mode control for spacecraft rendezvous with obstacle avoidance

NASA Astrophysics Data System (ADS)

Cao, Lu; Qiao, Dong; Xu, Jingwen

2018-02-01

Sub-Optimal Artificial Potential Function Sliding Mode Control (SOAPF-SMC) is proposed for the guidance and control of spacecraft rendezvous considering the obstacles avoidance, which is derived based on the theories of artificial potential function (APF), sliding mode control (SMC) and state dependent riccati equation (SDRE) technique. This new methodology designs a new improved APF to describe the potential field. It can guarantee the value of potential function converge to zero at the desired state. Moreover, the nonlinear terminal sliding mode is introduced to design the sliding mode surface with the potential gradient of APF, which offer a wide variety of controller design alternatives with fast and finite time convergence. Based on the above design, the optimal control theory (SDRE) is also employed to optimal the shape parameter of APF, in order to add some degree of optimality in reducing energy consumption. The new methodology is applied to spacecraft rendezvous with the obstacles avoidance problem, which is simulated to compare with the traditional artificial potential function sliding mode control (APF-SMC) and SDRE to evaluate the energy consumption and control precision. It is demonstrated that the presented method can avoiding dynamical obstacles whilst satisfying the requirements of autonomous rendezvous. In addition, it can save more energy than the traditional APF-SMC and also have better control accuracy than the SDRE.

Improved numerical methods for infinite spin chains with long-range interactions

NASA Astrophysics Data System (ADS)

Nebendahl, V.; Dür, W.

2013-02-01

We present several improvements of the infinite matrix product state (iMPS) algorithm for finding ground states of one-dimensional quantum systems with long-range interactions. As a main ingredient, we introduce the superposed multioptimization method, which allows an efficient optimization of exponentially many MPS of different lengths at different sites all in one step. Here, the algorithm becomes protected against position-dependent effects as caused by spontaneously broken translational invariance. So far, these have been a major obstacle to convergence for the iMPS algorithm if no prior knowledge of the system's translational symmetry was accessible. Further, we investigate some more general methods to speed up calculations and improve convergence, which might be partially interesting in a much broader context, too. As a more special problem, we also look into translational invariant states close to an invariance-breaking phase transition and show how to avoid convergence into wrong local minima for such systems. Finally, we apply these methods to polar bosons with long-range interactions. We calculate several detailed Devil's staircases with the corresponding phase diagrams and investigate some supersolid properties.

How does visual manipulation affect obstacle avoidance strategies used by athletes?

PubMed

Bijman, M P; Fisher, J J; Vallis, L A

2016-01-01

Research examining our ability to avoid obstacles in our path has stressed the importance of visual input. The aim of this study was to determine if athletes playing varsity-level field sports, who rely on visual input to guide motor behaviour, are more able to guide their foot over obstacles compared to recreational individuals. While wearing kinematic markers, eight varsity athletes and eight age-matched controls (aged 18-25) walked along a walkway and stepped over stationary obstacles (180° motion arc). Visual input was manipulated using PLATO visual goggles three or two steps pre-obstacle crossing and compared to trials where vision was given throughout. A main effect between groups for peak trail toe elevation was shown with greater values generated by the controls for all crossing conditions during full vision trials only. This may be interpreted as athletes not perceiving this obstacle as an increased threat to their postural stability. Collectively, findings suggest the athletic group is able to transfer their abilities to non-specific conditions during full vision trials; however, varsity-level athletes were equally reliant on visual cues for these visually guided stepping tasks as their performance was similar to the controls when vision is removed.

Model Predictive Control considering Reachable Range of Wheels for Leg / Wheel Mobile Robots

NASA Astrophysics Data System (ADS)

Suzuki, Naito; Nonaka, Kenichiro; Sekiguchi, Kazuma

2016-09-01

Obstacle avoidance is one of the important tasks for mobile robots. In this paper, we study obstacle avoidance control for mobile robots equipped with four legs comprised of three DoF SCARA leg/wheel mechanism, which enables the robot to change its shape adapting to environments. Our previous method achieves obstacle avoidance by model predictive control (MPC) considering obstacle size and lateral wheel positions. However, this method does not ensure existence of joint angles which achieves reference wheel positions calculated by MPC. In this study, we propose a model predictive control considering reachable mobile ranges of wheels positions by combining multiple linear constraints, where each reachable mobile range is approximated as a convex trapezoid. Thus, we achieve to formulate a MPC as a quadratic problem with linear constraints for nonlinear problem of longitudinal and lateral wheel position control. By optimization of MPC, the reference wheel positions are calculated, while each joint angle is determined by inverse kinematics. Considering reachable mobile ranges explicitly, the optimal joint angles are calculated, which enables wheels to reach the reference wheel positions. We verify its advantages by comparing the proposed method with the previous method through numerical simulations.

Computer vision techniques for rotorcraft low altitude flight

NASA Technical Reports Server (NTRS)

Sridhar, Banavar

1990-01-01

Rotorcraft operating in high-threat environments fly close to the earth's surface to utilize surrounding terrain, vegetation, or manmade objects to minimize the risk of being detected by an enemy. Increasing levels of concealment are achieved by adopting different tactics during low-altitude flight. Rotorcraft employ three tactics during low-altitude flight: low-level, contour, and nap-of-the-earth (NOE). The key feature distinguishing the NOE mode from the other two modes is that the whole rotorcraft, including the main rotor, is below tree-top whenever possible. This leads to the use of lateral maneuvers for avoiding obstacles, which in fact constitutes the means for concealment. The piloting of the rotorcraft is at best a very demanding task and the pilot will need help from onboard automation tools in order to devote more time to mission-related activities. The development of an automation tool which has the potential to detect obstacles in the rotorcraft flight path, warn the crew, and interact with the guidance system to avoid detected obstacles, presents challenging problems. Research is described which applies techniques from computer vision to automation of rotorcraft navigtion. The effort emphasizes the development of a methodology for detecting the ranges to obstacles in the region of interest based on the maximum utilization of passive sensors. The range map derived from the obstacle-detection approach can be used as obstacle data for the obstacle avoidance in an automatic guidance system and as advisory display to the pilot. The lack of suitable flight imagery data presents a problem in the verification of concepts for obstacle detection. This problem is being addressed by the development of an adequate flight database and by preprocessing of currently available flight imagery. The presentation concludes with some comments on future work and how research in this area relates to the guidance of other autonomous vehicles.

Mission-based guidance system design for autonomous UAVs

NASA Astrophysics Data System (ADS)

Moon, Jongki

The advantages of UAVs in the aviation arena have led to extensive research activities on autonomous technology of UAVs to achieve specific mission objectives. This thesis mainly focuses on the development of a mission-based guidance system. Among various missions expected for future needs, autonomous formation flight (AFF) and obstacle avoidance within safe operation limits are investigated. In the design of an adaptive guidance system for AFF, the leader information except position is assumed to be unknown to a follower. Thus, the only measured information related to the leader is the line-of-sight (LOS) range and angle. Adding an adaptive element with neural networks into the guidance system provides a capability to effectively handle leader's velocity changes. Therefore, this method can be applied to the AFF control systems that use a passive sensing method. In this thesis, an adaptive velocity command guidance system and an adaptive acceleration command guidance system are developed and presented. Since relative degrees of the LOS range and angle are different depending on the outputs from the guidance system, the architecture of the guidance system changes accordingly. Simulations and flight tests are performed using the Georgia Tech UAV helicopter, the GTMax, to evaluate the proposed guidance systems. The simulation results show that the neural network (NN) based adaptive element can improve the tracking performance by effectively compensating for the effect of unknown dynamics. It has also been shown that the combination of an adaptive velocity command guidance system and the existing GTMax autopilot controller performs better than the combination of an adaptive acceleration command guidance system and the GTMax autopilot controller. The successful flight evaluation using an adaptive velocity command guidance system clearly shows that the adaptive guidance control system is a promising solution for autonomous formation flight of UAVs. In addition, an integrated approach is proposed to resolve the conflict between aggressive maneuvering needed for obstacle avoidance and the constrained maneuvering needed for envelope protection. A time-optimal problem with obstacle and envelope constraints is used for an integrated approach for obstacle avoidance and envelope protection. The Nonlinear trajectory generator (NTG) is used as a real-time optimization solver. The computational complexity arising from the obstacle constraints is reduced by converting the obstacle constraints into a safe waypoint constraint along with an implicit requirement that the horizontal velocity during the avoidance maneuver must be nonnegative. The issue of when to initiate a time-optimal avoidance maneuver is addressed by including a requirement that the vehicle must maintain its original flight path to the maximum extent possible. The simulation evaluations are preformed for the nominal case, the unsafe avoidance solution case, the multiple safe waypoint case, and the unidentified obstacle size case. Artificial values for the load factor limit and the longitudinal flap angle limit are imposed as safe operational boundaries. Also, simulation results for different limit values and different initial flight speed are compared. Simulation results using a nonlinear model of a rotary wing UAV demonstrate the feasibility of the proposed approach for obstacle avoidance with envelope protection.

Sensorimotor and Cognitive Predictors of Impaired Gait Adaptability in Older People.

PubMed

Caetano, Maria Joana D; Menant, Jasmine C; Schoene, Daniel; Pelicioni, Paulo H S; Sturnieks, Daina L; Lord, Stephen R

2017-09-01

The ability to adapt gait when negotiating unexpected hazards is crucial to maintain stability and avoid falling. This study investigated whether impaired gait adaptability in a task including obstacle and stepping targets is associated with cognitive and sensorimotor capacities in older adults. Fifty healthy older adults (74±7 years) were instructed to either (a) avoid an obstacle at usual step distance or (b) step onto a target at either a short or long step distance projected on a walkway two heel strikes ahead and then continue walking. Participants also completed cognitive and sensorimotor function assessments. Stroop test and reaction time performance significantly discriminated between participants who did and did not make stepping errors, and poorer Trail-Making test performance predicted shorter penultimate step length in the obstacle avoidance condition. Slower reaction time predicted poorer stepping accuracy; increased postural sway, weaker quadriceps strength, and poorer Stroop and Trail-Making test performances predicted increased number of steps taken to approach the target/obstacle and shorter step length; and increased postural sway and higher concern about falling predicted slower step velocity. Superior executive function, fast processing speed, and good muscle strength and balance were all associated with successful gait adaptability. Processing speed appears particularly important for precise foot placements; cognitive capacity for step length adjustments; and early and/or additional cognitive processing involving the inhibition of a stepping pattern for obstacle avoidance. This information may facilitate fall risk assessments and fall prevention strategies. © 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.

A kinematic analysis of the Space Station remote manipulator system (SSRMS)

NASA Technical Reports Server (NTRS)

Crane, Carl D., III; Duffy, Joseph; Carnahan, Tim

1991-01-01

An efficient reverse analysis of three 6-degree-of-freedom (dof) subchains of the 7-dof SSRMS is presented. The first subchain is formed by locking the seventh joint. The second subchain is formed by locking the second joint, while the third subchain is formed by locking the first joint (the grounded joint is counted as the first joint in the chain). There are a maximum of eight different arm configurations in each of the three subchains, and these were determined by employing a computer-efficient algorithm, which required the rooting of only at most quadratic polynomials. The algorithms were implemented, and the SSRMS was employed in an animated environment to perform and practice a number of useful tasks for Space Station servicing. The locking of the second joint has the advantage in that an operator can choose the orientation of the plane that contains the two longest links so as to avoid collisions with obstacles. However, it has the disadvantage that when the second joint angle equals 0 deg or 180 deg, the manipulator is in a singularity configuration. This plane can also be oriented by specifying the first joint angle, so that the plane can be oriented arbitrarily and, in this, the singularity is avoided.

Collision recognition and direction changes for small scale fish robots by acceleration sensors

NASA Astrophysics Data System (ADS)

Na, Seung Y.; Shin, Daejung; Kim, Jin Y.; Lee, Bae-Ho

2005-05-01

Typical obstacles are walls, rocks, water plants and other nearby robots for a group of small scale fish robots and submersibles that have been constructed in our lab. Sonar sensors are not employed to make the robot structure simple enough. All of circuits, sensors and processor cards are contained in a box of 9 x 7 x 4 cm dimension except motors, fins and external covers. Therefore, image processing results are applied to avoid collisions. However, it is useful only when the obstacles are located far enough to give images processing time for detecting them. Otherwise, acceleration sensors are used to detect collision immediately after it happens. Two of 2-axes acceleration sensors are employed to measure the three components of collision angles, collision magnitudes, and the angles of robot propulsion. These data are integrated to calculate the amount of propulsion direction change. The angle of a collision incident upon an obstacle is the fundamental value to obtain a direction change needed to design a following path. But there is a significant amount of noise due to a caudal fin motor. Because caudal fin provides the main propulsion for a fish robot, there is a periodic swinging noise at the head of a robot. This noise provides a random acceleration effect on the measured acceleration data at the collision. We propose an algorithm which shows that the MEMS-type accelerometers are very effective to provide information for direction changes in spite of the intrinsic noise after the small scale fish robots have made obstacle collision.

Autonomous Rover Traverse and Precise Arm Placement on Remotely Designated Targets

NASA Technical Reports Server (NTRS)

Nesnas, Issa A.; Pivtoraiko, Mihail N.; Kelly, Alonzo; Fleder, Michael

2012-01-01

This software controls a rover platform to traverse rocky terrain autonomously, plan paths, and avoid obstacles using its stereo hazard and navigation cameras. It does so while continuously tracking a target of interest selected from 10 20 m away. The rover drives and tracks the target until it reaches the vicinity of the target. The rover then positions itself to approach the target, deploys its robotic arm, and places the end effector instrument on the designated target to within 2-3-cm accuracy of the originally selected target. This software features continuous navigation in a fairly rocky field in an outdoor environment and the ability to enable the rover to avoid large rocks and traverse over smaller ones. Using point-and-click mouse commands, a scientist designates targets in the initial imagery acquired from the rover s mast cameras. The navigation software uses stereo imaging, traversability analysis, path planning, trajectory generation, and trajectory execution. It also includes visual target tracking of a designated target selected from 10 m away while continuously navigating the rocky terrain. Improvements in this design include steering while driving, which uses continuous curvature paths. There are also several improvements to the traversability analyzer, including improved data fusion of traversability maps that result from pose estimation uncertainties, dealing with boundary effects to enable tighter maneuvers, and handling a wider range of obstacles. This work advances what has been previously developed and integrated on the Mars Exploration Rovers by using algorithms that are capable of traversing more rock-dense terrains, enabling tight, thread-the-needle maneuvers. These algorithms were integrated on the newly refurbished Athena Mars research rover, and were fielded in the JPL Mars Yard. Forty-three runs were conducted with targets at distances ranging from 5 to 15 m, and a success rate of 93% was achieved for placement of the instrument within 2-3 cm of the target.

A Mobile Robot Sonar System with Obstacle Avoidance.

DTIC Science & Technology

1994-03-01

WITH OBSTACLE - AVOIDANCE __ by __ Patrick Gerard Byrne March 1994 Thesis Advisor : Yutaka Kanayama Approved for public release; distribution is...point p is on a line L whose normal has an orientation a and whose distance from the origin is r (Figure 5). This method has an advantage in expressing...sonar(FRONTR); Wine(&pl); while(hitl I >’- 100.0 11 hitl 1 - 0.0 ){ hitl I = sonar(FRONTR); I skipO; line(&p3); gat- robO (&posit 1); while(positl.x

Evacuation simulation with consideration of obstacle removal and using game theory

NASA Astrophysics Data System (ADS)

Lin, Guan-Wen; Wong, Sai-Keung

2018-06-01

In this paper, we integrate a cellular automaton model with game theory to simulate crowd evacuation from a room with consideration of obstacle removal. The room has one or more exits, one of which is blocked by obstacles. The obstacles at the exit can be removed by volunteers. We investigate the cooperative and defective behaviors of pedestrians during evacuation. The yielder game and volunteer's dilemma game are employed to resolve interpedestrian conflict. An anticipation floor field is proposed to guide the pedestrians to avoid obstacles that are being removed. We conducted experiments to determine how a variety of conditions affect overall crowd evacuation and volunteer evacuation times. The conditions were the start time of obstacle removal, number of obstacles, placement of obstacles, time spent in obstacle removal, strength of the anticipation floor field, and obstacle visibility distance. We demonstrate how reciprocity can be achieved among pedestrians and increases the efficiency of the entire evacuation process.

A fuzzy logic controller for an autonomous mobile robot

NASA Technical Reports Server (NTRS)

Yen, John; Pfluger, Nathan

1993-01-01

The ability of a mobile robot system to plan and move intelligently in a dynamic system is needed if robots are to be useful in areas other than controlled environments. An example of a use for this system is to control an autonomous mobile robot in a space station, or other isolated area where it is hard or impossible for human life to exist for long periods of time (e.g., Mars). The system would allow the robot to be programmed to carry out the duties normally accomplished by a human being. Some of the duties that could be accomplished include operating instruments, transporting objects, and maintenance of the environment. The main focus of our early work has been on developing a fuzzy controller that takes a path and adapts it to a given environment. The robot only uses information gathered from the sensors, but retains the ability to avoid dynamically placed obstacles near and along the path. Our fuzzy logic controller is based on the following algorithm: (1) determine the desired direction of travel; (2) determine the allowed direction of travel; and (3) combine the desired and allowed directions in order to determine a direciton that is both desired and allowed. The desired direction of travel is determined by projecting ahead to a point along the path that is closer to the goal. This gives a local direction of travel for the robot and helps to avoid obstacles.

An efficient approach for inverse kinematics and redundancy resolution scheme of hyper-redundant manipulators

NASA Astrophysics Data System (ADS)

Chembuly, V. V. M. J. Satish; Voruganti, Hari Kumar

2018-04-01

Hyper redundant manipulators have a large number of degrees of freedom (DOF) than the required to perform a given task. Additional DOF of manipulators provide the flexibility to work in highly cluttered environment and in constrained workspaces. Inverse kinematics (IK) of hyper-redundant manipulators is complicated due to large number of DOF and these manipulators have multiple IK solutions. The redundancy gives a choice of selecting best solution out of multiple solutions based on certain criteria such as obstacle avoidance, singularity avoidance, joint limit avoidance and joint torque minimization. This paper focuses on IK solution and redundancy resolution of hyper-redundant manipulator using classical optimization approach. Joint positions are computed by optimizing various criteria for a serial hyper redundant manipulators while traversing different paths in the workspace. Several cases are addressed using this scheme to obtain the inverse kinematic solution while optimizing the criteria like obstacle avoidance, joint limit avoidance.

New vision system and navigation algorithm for an autonomous ground vehicle

NASA Astrophysics Data System (ADS)

Tann, Hokchhay; Shakya, Bicky; Merchen, Alex C.; Williams, Benjamin C.; Khanal, Abhishek; Zhao, Jiajia; Ahlgren, David J.

2013-12-01

Improvements were made to the intelligence algorithms of an autonomously operating ground vehicle, Q, which competed in the 2013 Intelligent Ground Vehicle Competition (IGVC). The IGVC required the vehicle to first navigate between two white lines on a grassy obstacle course, then pass through eight GPS waypoints, and pass through a final obstacle field. Modifications to Q included a new vision system with a more effective image processing algorithm for white line extraction. The path-planning algorithm adopted the vision system, creating smoother, more reliable navigation. With these improvements, Q successfully completed the basic autonomous navigation challenge, finishing tenth out of over 50 teams.

Dual stage potential field method for robotic path planning

NASA Astrophysics Data System (ADS)

Singh, Pradyumna Kumar; Parida, Pramod Kumar

2018-04-01

Path planning for autonomous mobile robots are the root for all autonomous mobile systems. Various methods are used for optimization of path to be followed by the autonomous mobile robots. Artificial potential field based path planning method is one of the most used methods for the researchers. Various algorithms have been proposed using the potential field approach. But in most of the common problems are encounters while heading towards the goal or target. i.e. local minima problem, zero potential regions problem, complex shaped obstacles problem, target near obstacle problem. In this paper we provide a new algorithm in which two types of potential functions are used one after another. The former one is to use to get the probable points and later one for getting the optimum path. In this algorithm we consider only the static obstacle and goal.

Stochastic reaction-diffusion algorithms for macromolecular crowding

NASA Astrophysics Data System (ADS)

Sturrock, Marc

2016-06-01

Compartment-based (lattice-based) reaction-diffusion algorithms are often used for studying complex stochastic spatio-temporal processes inside cells. In this paper the influence of macromolecular crowding on stochastic reaction-diffusion simulations is investigated. Reaction-diffusion processes are considered on two different kinds of compartmental lattice, a cubic lattice and a hexagonal close packed lattice, and solved using two different algorithms, the stochastic simulation algorithm and the spatiocyte algorithm (Arjunan and Tomita 2010 Syst. Synth. Biol. 4, 35-53). Obstacles (modelling macromolecular crowding) are shown to have substantial effects on the mean squared displacement and average number of molecules in the domain but the nature of these effects is dependent on the choice of lattice, with the cubic lattice being more susceptible to the effects of the obstacles. Finally, improvements for both algorithms are presented.

Foliage discrimination using a rotating ladar

NASA Technical Reports Server (NTRS)

Castano, A.; Matthies, L.

2003-01-01

We present a real time algorithm that detects foliage using range from a rotating laser. Objects not classified as foliage are conservatively labeled as non-driving obstacles. In contrast to related work that uses range statistics to classify objects, we exploit the expected localities and continuities of an obstacle, in both space and time. Also, instead of attempting to find a single accurate discriminating factor for every ladar return, we hypothesize the class of some few returns and then spread the confidence (and classification) to other returns using the locality constraints. The Urbie robot is presently using this algorithm to descriminate drivable grass from obstacles during outdoor autonomous navigation tasks.

Robust Planning for Autonomous Navigation of Mobile Robots in Unstructured, Dynamic Environments: An LDRD Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

EISLER, G. RICHARD

This report summarizes the analytical and experimental efforts for the Laboratory Directed Research and Development (LDRD) project entitled ''Robust Planning for Autonomous Navigation of Mobile Robots In Unstructured, Dynamic Environments (AutoNav)''. The project goal was to develop an algorithmic-driven, multi-spectral approach to point-to-point navigation characterized by: segmented on-board trajectory planning, self-contained operation without human support for mission duration, and the development of appropriate sensors and algorithms to navigate unattended. The project was partially successful in achieving gains in sensing, path planning, navigation, and guidance. One of three experimental platforms, the Minimalist Autonomous Testbed, used a repetitive sense-and-re-plan combination to demonstratemore » the majority of elements necessary for autonomous navigation. However, a critical goal for overall success in arbitrary terrain, that of developing a sensor that is able to distinguish true obstacles that need to be avoided as a function of vehicle scale, still needs substantial research to bring to fruition.« less

Road-Following Formation Control of Autonomous Ground Vehicles

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Droge, Greg; Grip, Havard; Toupet, Olivier; Scrapper, Chris; Rahmani, Amir

2015-01-01

This work presents a novel cooperative path planning for formation keeping robots traversing along a road with obstacles and possible narrow passages. A unique challenge in this problem is a requirement for spatial and temporal coordination between vehicles while ensuring collision and obstacle avoidance.

An Intelligent Robotic Hospital Bed for Safe Transportation of Critical Neurosurgery Patients Along Crowded Hospital Corridors.

PubMed

Wang, Chao; Savkin, Andrey V; Clout, Ray; Nguyen, Hung T

2015-09-01

We present a novel design of an intelligent robotic hospital bed, named Flexbed, with autonomous navigation ability. The robotic bed is developed for fast and safe transportation of critical neurosurgery patients without changing beds. Flexbed is more efficient and safe during the transportation process comparing to the conventional hospital beds. Flexbed is able to avoid en-route obstacles with an efficient easy-to-implement collision avoidance strategy when an obstacle is nearby and to move towards its destination at maximum speed when there is no threat of collision. We present extensive simulation results of navigation of Flexbed in the crowded hospital corridor environments with moving obstacles. Moreover, results of experiments with Flexbed in the real world scenarios are also presented and discussed.

Laser range measurement for a satellite navigation scheme and mid-range path selection and obstacle avoidance. M.S. Thesis

NASA Technical Reports Server (NTRS)

Zuraski, G. D.

1972-01-01

The functions of a laser rangefinder on board an autonomous Martian roving vehicle are discussed. The functions are: (1) navigation by means of a passive satellite and (2) mid-range path selection and obstacle avoidance. The feasibility of using a laser to make the necessary range measurements is explored and a preliminary design is presented. The two uses of the rangefinder dictate widely different operating parameters making it impossible to use the same system for both functions.

Autonomous navigation and obstacle avoidance for unmanned surface vehicles

NASA Astrophysics Data System (ADS)

Larson, Jacoby; Bruch, Michael; Ebken, John

2006-05-01

The US Navy and other Department of Defense (DoD) and Department of Homeland Security (DHS) organizations are increasingly interested in the use of unmanned surface vehicles (USVs) for a variety of missions and applications. In order for USVs to fill these roles, they must be capable of a relatively high degree of autonomous navigation. Space and Naval Warfare Systems Center, San Diego is developing core technologies required for robust USV operation in a real-world environment, primarily focusing on autonomous navigation, obstacle avoidance, and path planning.

Learning Impasses in Problem Solving

NASA Technical Reports Server (NTRS)

Hodgson, J. P. E.

1992-01-01

Problem Solving systems customarily use backtracking to deal with obstacles that they encounter in the course of trying to solve a problem. This paper outlines an approach in which the possible obstacles are investigated prior to the search for a solution. This provides a solution strategy that avoids backtracking.

Energy dissipation by submarine obstacles during landslide impact on reservoir - potentially avoiding catastrophic dam collapse

NASA Astrophysics Data System (ADS)

Kafle, Jeevan; Kattel, Parameshwari; Mergili, Martin; Fischer, Jan-Thomas; Tuladhar, Bhadra Man; Pudasaini, Shiva P.

2017-04-01

Dense geophysical mass flows such as landslides, debris flows and debris avalanches may generate super tsunami waves as they impact water bodies such as the sea, hydraulic reservoirs or mountain lakes. Here, we apply a comprehensive and general two-phase, physical-mathematical mass flow model (Pudasaini, 2012) that consists of non-linear and hyperbolic-parabolic partial differential equations for mass and momentum balances, and present novel, high-resolution simulation results for two-phase flows, as a mixture of solid grains and viscous fluid, impacting fluid reservoirs with obstacles. The simulations demonstrate that due to the presence of different obstacles in the water body, the intense flow-obstacle-interaction dramatically reduces the flow momentum resulting in the rapid energy dissipation around the obstacles. With the increase of obstacle height overtopping decreases but, the deflection and capturing (holding) of solid mass increases. In addition, the submarine solid mass is captured by the multiple obstacles and the moving mass decreases both in amount and speed as each obstacle causes the flow to deflect into two streams and also captures a portion of it. This results in distinct tsunami and submarine flow dynamics with multiple surface water and submarine debris waves. This novel approach can be implemented in open source GIS modelling framework r.avaflow, and be applied in hazard mitigation, prevention and relevant engineering or environmental tasks. This might be in particular for process chains, such as debris impacts in lakes and subsequent overtopping. So, as the complex flow-obstacle-interactions strongly and simultaneously dissipate huge energy at impact such installations potentially avoid great threat against the integrity of the dam. References: Pudasaini, S. P. (2012): A general two-phase debris flow model. J. Geophys. Res. 117, F03010, doi: 10.1029/ 2011JF002186.

Steering of an automated vehicle in an unstructured environment

NASA Astrophysics Data System (ADS)

Kanakaraju, Sampath; Shanmugasundaram, Sathish K.; Thyagarajan, Ramesh; Hall, Ernest L.

1999-08-01

The purpose of this paper is to describe a high-level path planning logic, which processes the data from a vision system and an ultrasonic obstacle avoidance system and steers an autonomous mobile robot between obstacles. The test bed was an autonomous root built at University of Cincinnati, and this logic was tested and debugged on this machine. Attempts have already been made to incorporate fuzzy system on a similar robot, and this paper extends them to take advantage of the robot's ZTR capability. Using the integrated vision syste, the vehicle senses its location and orientation. A rotating ultrasonic sensor is used to map the location and size of possible obstacles. With these inputs the fuzzy logic controls the speed and the steering decisions of the robot. With the incorporation of this logic, it has been observed that Bearcat II has been very successful in avoiding obstacles very well. This was achieved in the Ground Robotics Competition conducted by the AUVS in June 1999, where it travelled a distance of 154 feet in a 10ft. wide path ridden with obstacles. This logic proved to be a significant contributing factor in this feat of Bearcat II.

3D-Sonification for Obstacle Avoidance in Brownout Conditions

NASA Technical Reports Server (NTRS)

Godfroy-Cooper, M.; Miller, J. D.; Szoboszlay, Z.; Wenzel, E. M.

2017-01-01

Helicopter brownout is a phenomenon that occurs when making landing approaches in dusty environments, whereby sand or dust particles become swept up in the rotor outwash. Brownout is characterized by partial or total obscuration of the terrain, which degrades visual cues necessary for hovering and safe landing. Furthermore, the motion of the dust cloud produced during brownout can lead to the pilot experiencing motion cue anomalies such as vection illusions. In this context, the stability and guidance control functions can be intermittently or continuously degraded, potentially leading to undetected surface hazards and obstacles as well as unnoticed drift. Safe and controlled landing in brownout can be achieved using an integrated presentation of LADAR and RADAR imagery and aircraft state symbology. However, though detected by the LADAR and displayed on the sensor image, small obstacles can be difficult to discern from the background so that changes in obstacle elevation may go unnoticed. Moreover, pilot workload associated with tracking the displayed symbology is often so high that the pilot cannot give sufficient attention to the LADAR/RADAR image. This paper documents a simulation evaluating the use of 3D auditory cueing for obstacle avoidance in brownout as a replacement for or compliment to LADAR/RADAR imagery.

Echolocation behaviour of the big brown bat (Eptesicus fuscus) in an obstacle avoidance task of increasing difficulty.

PubMed

Sändig, Sonja; Schnitzler, Hans-Ulrich; Denzinger, Annette

2014-08-15

Four big brown bats (Eptesicus fuscus) were challenged in an obstacle avoidance experiment to localize vertically stretched wires requiring progressively greater accuracy by diminishing the wire-to-wire distance from 50 to 10 cm. The performance of the bats decreased with decreasing gap size. The avoidance task became very difficult below a wire separation of 30 cm, which corresponds to the average wingspan of E. fuscus. Two of the bats were able to pass without collisions down to a gap size of 10 cm in some of the flights. The other two bats only managed to master gap sizes down to 20 and 30 cm, respectively. They also performed distinctly worse at all other gap sizes. With increasing difficulty of the task, the bats changed their flight and echolocation behaviour. Especially at gap sizes of 30 cm and below, flight paths increased in height and flight speed was reduced. In addition, the bats emitted approach signals that were arranged in groups. At all gap sizes, the largest numbers of pulses per group were observed in the last group before passing the obstacle. The more difficult the obstacle avoidance task, the more pulses there were in the groups and the shorter the within-group pulse intervals. In comparable situations, the better-performing bats always emitted groups with more pulses than the less well-performing individuals. We hypothesize that the accuracy of target localization increases with the number of pulses per group and that each group is processed as a package. © 2014. Published by The Company of Biologists Ltd.

Effectiveness and driver acceptance of a semi-autonomous forward obstacle collision avoidance system.

PubMed

Itoh, Makoto; Horikome, Tatsuya; Inagaki, Toshiyuki

2013-09-01

This paper proposes a semi-autonomous collision avoidance system for the prevention of collisions between vehicles and pedestrians and objects on a road. The system is designed to be compatible with the human-centered automation principle, i.e., the decision to perform a maneuver to avoid a collision is made by the driver. However, the system is partly autonomous in that it turns the steering wheel independently when the driver only applies the brake, indicating his or her intent to avoid the obstacle. With a medium-fidelity driving simulator, we conducted an experiment to investigate the effectiveness of this system for improving safety in emergency situations, as well as its acceptance by drivers. The results indicate that the system effectively improves safety in emergency situations, and the semi-autonomous characteristic of the system was found to be acceptable to drivers. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field.

PubMed

Christiansen, Peter; Nielsen, Lars N; Steen, Kim A; Jørgensen, Rasmus N; Karstoft, Henrik

2016-11-11

Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily occluded objects and are, by definition, not capable of detecting unknown object types or unusual scenarios. The visual characteristics of an agriculture field is homogeneous, and obstacles, like people, animals and other obstacles, occur rarely and are of distinct appearance compared to the field. This paper introduces DeepAnomaly, an algorithm combining deep learning and anomaly detection to exploit the homogenous characteristics of a field to perform anomaly detection. We demonstrate DeepAnomaly as a fast state-of-the-art detector for obstacles that are distant, heavily occluded and unknown. DeepAnomaly is compared to state-of-the-art obstacle detectors including "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks" (RCNN). In a human detector test case, we demonstrate that DeepAnomaly detects humans at longer ranges (45-90 m) than RCNN. RCNN has a similar performance at a short range (0-30 m). However, DeepAnomaly has much fewer model parameters and (182 ms/25 ms =) a 7.28-times faster processing time per image. Unlike most CNN-based methods, the high accuracy, the low computation time and the low memory footprint make it suitable for a real-time system running on a embedded GPU (Graphics Processing Unit).

DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field

PubMed Central

Christiansen, Peter; Nielsen, Lars N.; Steen, Kim A.; Jørgensen, Rasmus N.; Karstoft, Henrik

2016-01-01

Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily occluded objects and are, by definition, not capable of detecting unknown object types or unusual scenarios. The visual characteristics of an agriculture field is homogeneous, and obstacles, like people, animals and other obstacles, occur rarely and are of distinct appearance compared to the field. This paper introduces DeepAnomaly, an algorithm combining deep learning and anomaly detection to exploit the homogenous characteristics of a field to perform anomaly detection. We demonstrate DeepAnomaly as a fast state-of-the-art detector for obstacles that are distant, heavily occluded and unknown. DeepAnomaly is compared to state-of-the-art obstacle detectors including “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks” (RCNN). In a human detector test case, we demonstrate that DeepAnomaly detects humans at longer ranges (45–90 m) than RCNN. RCNN has a similar performance at a short range (0–30 m). However, DeepAnomaly has much fewer model parameters and (182 ms/25 ms =) a 7.28-times faster processing time per image. Unlike most CNN-based methods, the high accuracy, the low computation time and the low memory footprint make it suitable for a real-time system running on a embedded GPU (Graphics Processing Unit). PMID:27845717

Waist-up protection for blind individuals using the EyeCane as a primary and secondary mobility aid.

PubMed

Buchs, Galit; Simon, Noa; Maidenbaum, Shachar; Amedi, Amir

2017-01-01

One of the most stirring statistics in relation to the mobility of blind individuals is the high rate of upper body injuries, even when using the white-cane. We here addressed a rehabilitation- oriented challenge of providing a reliable tool for blind people to avoid waist-up obstacles, namely one of the impediments to their successful mobility using currently available methods (e.g., white-cane). We used the EyeCane, a device we developed which translates distances from several angles to haptic and auditory cues in an intuitive and unobtrusive manner, serving both as a primary and secondary mobility aid. We investigated the rehabilitation potential of such a device in facilitating visionless waist-up body protection. After ∼5 minutes of training with the EyeCane blind participants were able to successfully detect and avoid obstacles waist-high and up. This was significantly higher than their success when using the white-cane alone. As avoidance of obstacles required participants to perform an additional cognitive process after their detection, the avoidance rate was significantly lower than the detection rate. Our work has demonstrated that the EyeCane has the potential to extend the sensory world of blind individuals by expanding their currently accessible inputs, and has offered them a new practical rehabilitation tool.

Evaluation of a Portable Collision Warning Device for Patients With Peripheral Vision Loss in an Obstacle Course.

PubMed

Pundlik, Shrinivas; Tomasi, Matteo; Luo, Gang

2015-04-01

A pocket-sized collision warning device equipped with a video camera was developed to predict impending collisions based on time to collision rather than proximity. A study was conducted in a high-density obstacle course to evaluate the effect of the device on collision avoidance in people with peripheral field loss (PFL). The 41-meter-long loop-shaped obstacle course consisted of 46 stationary obstacles from floor to head level and oncoming pedestrians. Twenty-five patients with tunnel vision (n = 13) or hemianopia (n = 12) completed four consecutive loops with and without the device, while not using any other habitual mobility aid. Walking direction and device usage order were counterbalanced. Number of collisions and preferred percentage of walking speed (PPWS) were compared within subjects. Collisions were reduced significantly by approximately 37% (P < 0.001) with the device (floor-level obstacles were excluded because the device was not designed for them). No patient had more collisions when using the device. Although the PPWS were also reduced with the device from 52% to 49% (P = 0.053), this did not account for the lower number of collisions, as the changes in collisions and PPWS were not correlated (P = 0.516). The device may help patients with a wide range of PFL avoid collisions with high-level obstacles while barely affecting their walking speed.

Automatic guidance and control laws for helicopter obstacle avoidance

NASA Technical Reports Server (NTRS)

Cheng, Victor H. L.; Lam, T.

1992-01-01

The authors describe the implementation of a full-function guidance and control system for automatic obstacle avoidance in helicopter nap-of-the-earth (NOE) flight. The guidance function assumes that the helicopter is sufficiently responsive so that the flight path can be readily adjusted at NOE speeds. The controller, basically an autopilot for following the derived flight path, was implemented with parameter values to control a generic helicopter model used in the simulation. Evaluation of the guidance and control system with a 3-dimensional graphical helicopter simulation suggests that the guidance has the potential for providing good and meaningful flight trajectories.

A linear photodiode array employed in a short range laser triangulation obstacle avoidance sensor. M.S. Thesis; [Martian roving vehicle sensor

NASA Technical Reports Server (NTRS)

Odenthal, J. P.

1980-01-01

An opto-electronic receiver incorporating a multi-element linear photodiode array as a component of a laser-triangulation rangefinder was developed as an obstacle avoidance sensor for a Martian roving vehicle. The detector can resolve the angle of laser return in 1.5 deg increments within a field of view of 30 deg and a range of five meters. A second receiver with a 1024 elements over 60 deg and a 3 meter range is also documented. Design criteria, circuit operation, schematics, experimental results and calibration procedures are discussed.

Passive detection of subpixel obstacles for flight safety

NASA Astrophysics Data System (ADS)

Nixon, Matthew D.; Loveland, Rohan C.

2001-12-01

Military aircraft fly below 100 ft. above ground level in support of their missions. These aircraft include fixed and rotary wing and may be manned or unmanned. Flying at these low altitudes presents a safety hazard to the aircrew and aircraft, due to the occurrences of obstacles within the aircraft's flight path. The pilot must rely on eyesight and in some cases, infrared sensors to see obstacles. Many conditions can exacerbate visibility creating a situation in which obstacles are essentially invisible, creating a safety hazard, even to an alerted aircrew. Numerous catastrophic accidents have occurred in which aircraft have collided with undetected obstacles. Accidents of this type continue to be a problem for low flying military and commercial aircraft. Unmanned Aerial Vehicles (UAVs) have the same problem, whether operating autonomously or under control of a ground operator. Boeing-SVS has designed a passive, small, low- cost (under $100k) gimbaled, infrared imaging based system with advanced obstacle detection algorithms. Obstacles are detected in the infrared band, and linear features are analyzed by innovative cellular automata based software. These algorithms perform detection and location of sub-pixel linear features. The detection of the obstacles is performed on a frame by frame basis, in real time. Processed images are presented to the aircrew on their display as color enhanced features. The system has been designed such that the detected obstacles are displayed to the aircrew in sufficient time to react and maneuver the aircraft to safety. A patent for this system is on file with the US patent office, and all material herein should be treated accordingly.

Metalevel programming in robotics: Some issues

NASA Technical Reports Server (NTRS)

Kumarn, A.; Parameswaran, N.

1987-01-01

Computing in robotics has two important requirements: efficiency and flexibility. Algorithms for robot actions are implemented usually in procedural languages such as VAL and AL. But, since their excessive bindings create inflexible structures of computation, it is proposed that Logic Programming is a more suitable language for robot programming due to its non-determinism, declarative nature, and provision for metalevel programming. Logic Programming, however, results in inefficient computations. As a solution to this problem, researchers discuss a framework in which controls can be described to improve efficiency. They have divided controls into: (1) in-code and (2) metalevel and discussed them with reference to selection of rules and dataflow. Researchers illustrated the merit of Logic Programming by modelling the motion of a robot from one point to another avoiding obstacles.

Evolution and advanced technology. [of Flight Telerobotic Servicer

NASA Technical Reports Server (NTRS)

Ollendorf, Stanford; Pennington, Jack E.; Hansen, Bert, III

1990-01-01

The NASREM architecture with its standard interfaces permits development and evolution of the Flight Telerobotic Servicer to greater autonomy. Technologies in control strategies for an arm with seven DOF, including a safety system containing skin sensors for obstacle avoidance, are being developed. Planning and robotic execution software includes symbolic task planning, world model data bases, and path planning algorithms. Research over the last five years has led to the development of laser scanning and ranging systems, which use coherent semiconductor laser diodes for short range sensing. The possibility of using a robot to autonomously assemble space structures is being investigated. A control framework compatible with NASREM is being developed that allows direct global control of the manipulator. Researchers are developing systems that permit an operator to quickly reconfigure the telerobot to do new tasks safely.

Event-Based Control Strategy for Mobile Robots in Wireless Environments.

PubMed

Socas, Rafael; Dormido, Sebastián; Dormido, Raquel; Fabregas, Ernesto

2015-12-02

In this paper, a new event-based control strategy for mobile robots is presented. It has been designed to work in wireless environments where a centralized controller has to interchange information with the robots over an RF (radio frequency) interface. The event-based architectures have been developed for differential wheeled robots, although they can be applied to other kinds of robots in a simple way. The solution has been checked over classical navigation algorithms, like wall following and obstacle avoidance, using scenarios with a unique or multiple robots. A comparison between the proposed architectures and the classical discrete-time strategy is also carried out. The experimental results shows that the proposed solution has a higher efficiency in communication resource usage than the classical discrete-time strategy with the same accuracy.

Event-Based Control Strategy for Mobile Robots in Wireless Environments

PubMed Central

Socas, Rafael; Dormido, Sebastián; Dormido, Raquel; Fabregas, Ernesto

2015-01-01

In this paper, a new event-based control strategy for mobile robots is presented. It has been designed to work in wireless environments where a centralized controller has to interchange information with the robots over an RF (radio frequency) interface. The event-based architectures have been developed for differential wheeled robots, although they can be applied to other kinds of robots in a simple way. The solution has been checked over classical navigation algorithms, like wall following and obstacle avoidance, using scenarios with a unique or multiple robots. A comparison between the proposed architectures and the classical discrete-time strategy is also carried out. The experimental results shows that the proposed solution has a higher efficiency in communication resource usage than the classical discrete-time strategy with the same accuracy. PMID:26633412

Fuzzy integral-based gaze control architecture incorporated with modified-univector field-based navigation for humanoid robots.

PubMed

Yoo, Jeong-Ki; Kim, Jong-Hwan

2012-02-01

When a humanoid robot moves in a dynamic environment, a simple process of planning and following a path may not guarantee competent performance for dynamic obstacle avoidance because the robot acquires limited information from the environment using a local vision sensor. Thus, it is essential to update its local map as frequently as possible to obtain more information through gaze control while walking. This paper proposes a fuzzy integral-based gaze control architecture incorporated with the modified-univector field-based navigation for humanoid robots. To determine the gaze direction, four criteria based on local map confidence, waypoint, self-localization, and obstacles, are defined along with their corresponding partial evaluation functions. Using the partial evaluation values and the degree of consideration for criteria, fuzzy integral is applied to each candidate gaze direction for global evaluation. For the effective dynamic obstacle avoidance, partial evaluation functions about self-localization error and surrounding obstacles are also used for generating virtual dynamic obstacle for the modified-univector field method which generates the path and velocity of robot toward the next waypoint. The proposed architecture is verified through the comparison with the conventional weighted sum-based approach with the simulations using a developed simulator for HanSaRam-IX (HSR-IX).

Intelligent walkers for the elderly: performance and safety testing of VA-PAMAID robotic walker.

PubMed

Rentschler, Andrew J; Cooper, Rory A; Blasch, Bruce; Boninger, Michael L

2003-01-01

A walker that could help navigate and avoid collisions with obstacles could help reduce health costs and increase the quality of care and independence of thousands of people. This study evaluated the safety and performance of the Veterans Affairs Personal Adaptive Mobility Aid (VA-PAMAID). We performed engineering tests on the VA-PAMAID to determine safety factors, including stability, energy consumption, fatigue life, and sensor and control malfunctions. The VA-PAMAID traveled 10.9 km on a full charge and avoided obstacles while traveling at a speed of up to 1.2 m/s. No failures occurred during static stability, climatic, or fatigue testing. Some problems were encountered during obstacle climbing and sensor and control testing. The VA-PAMAID has good range, has adequate reaction time, and is structurally sound. Clinical trials are planned to compare the device to other low-technical adaptive mobility devices.

Starfish Behavior as an Anticipatory System: Its Flexibility in Obstacle Avoidance

NASA Astrophysics Data System (ADS)

Migita, Masao

2006-06-01

As starfish do not have central nervous systems, their behaviors such as walking, righting, feeding, and so on, must be produced by some processes of self-organization of many motor organs. It has been noticed that self-organized behavioral patterns are not strictly determined by external stimuli, though such stimuli may elicit the very self-organization processes. In this sense, starfish are not only reactive like a conventional discourse of comparative psychology have presupposed. In this study, I will show diversity in self-organized behavior of a starfish exhibited under experiments on obstacle avoidance. The starfish may be considered as an anticipatory system, because it usually appeared to be free from serious deadlock at the obstacles. I will also discuss that to view the animal as an anticipatory system may have an interesting implication on the fields of behavioral biology and comparative psychology.

The MITy micro-rover: Sensing, control, and operation

NASA Technical Reports Server (NTRS)

Malafeew, Eric; Kaliardos, William

1994-01-01

The sensory, control, and operation systems of the 'MITy' Mars micro-rover are discussed. It is shown that the customized sun tracker and laser rangefinder provide internal, autonomous dead reckoning and hazard detection in unstructured environments. The micro-rover consists of three articulated platforms with sensing, processing and payload subsystems connected by a dual spring suspension system. A reactive obstacle avoidance routine makes intelligent use of robot-centered laser information to maneuver through cluttered environments. The hazard sensors include a rangefinder, inclinometers, proximity sensors and collision sensors. A 486/66 laptop computer runs the graphical user interface and programming environment. A graphical window displays robot telemetry in real time and a small TV/VCR is used for real time supervisory control. Guidance, navigation, and control routines work in conjunction with the mapping and obstacle avoidance functions to provide heading and speed commands that maneuver the robot around obstacles and towards the target.

Analysis of the minimum swerving distance for the development of a motorcycle autonomous braking system.

PubMed

Giovannini, Federico; Savino, Giovanni; Pierini, Marco; Baldanzini, Niccolò

2013-10-01

In the recent years the autonomous emergency brake (AEB) was introduced in the automotive field to mitigate the injury severity in case of unavoidable collisions. A crucial element for the activation of the AEB is to establish when the obstacle is no longer avoidable by lateral evasive maneuvers (swerving). In the present paper a model to compute the minimum swerving distance needed by a powered two-wheeler (PTW) to avoid the collision against a fixed obstacle, named last-second swerving model (Lsw), is proposed. The effectiveness of the model was investigated by an experimental campaign involving 12 volunteers riding a scooter equipped with a prototype autonomous emergency braking, named motorcycle autonomous emergency braking system (MAEB). The tests showed the performance of the model in evasive trajectory computation for different riding styles and fixed obstacles. Copyright © 2013 Elsevier Ltd. All rights reserved.

State estimation for autonomous flight in cluttered environments

NASA Astrophysics Data System (ADS)

Langelaan, Jacob Willem

Safe, autonomous operation in complex, cluttered environments is a critical challenge facing autonomous mobile systems. The research described in this dissertation was motivated by a particularly difficult example of autonomous mobility: flight of a small Unmanned Aerial Vehicle (UAV) through a forest. In cluttered environments (such as forests or natural and urban canyons) signals from navigation beacons such as GPS may frequently be occluded. Direct measurements of vehicle position are therefore unavailable, and information required for flight control, obstacle avoidance, and navigation must be obtained using only on-board sensors. However, payload limitations of small UAVs restrict both the mass and physical dimensions of sensors that can be carried. This dissertation describes the development and proof-of-concept demonstration of a navigation system that uses only a low-cost inertial measurement unit and a monocular camera. Micro electromechanical inertial measurements units are well suited to small UAV applications and provide measurements of acceleration and angular rate. However, they do not provide information about nearby obstacles (needed for collision avoidance) and their noise and bias characteristics lead to unbounded growth in computed position. A monocular camera can provide bearings to nearby obstacles and landmarks. These bearings can be used both to enable obstacle avoidance and to aid navigation. Presented here is a solution to the problem of estimating vehicle state (position, orientation and velocity) as well as positions of obstacles in the environment using only inertial measurements and bearings to obstacles. This is a highly nonlinear estimation problem, and standard estimation techniques such as the Extended Kalman Filter are prone to divergence in this application. In this dissertation a Sigma Point Kalman Filter is implemented, resulting in an estimator which is able to cope with the significant nonlinearities in the system equations and uncertainty in state estimates while remaining tractable for real-time operation. In addition, the issues of data association and landmark initialization are addressed. Estimator performance is examined through Monte Carlo simulations in both two and three dimensions for scenarios involving UAV flight in cluttered environments. Hardware tests and simulations demonstrate navigation through an obstacle-strewn environment by a small Unmanned Ground Vehicle.

UAVs Task and Motion Planning in the Presence of Obstacles and Prioritized Targets

PubMed Central

Gottlieb, Yoav; Shima, Tal

2015-01-01

The intertwined task assignment and motion planning problem of assigning a team of fixed-winged unmanned aerial vehicles to a set of prioritized targets in an environment with obstacles is addressed. It is assumed that the targets’ locations and initial priorities are determined using a network of unattended ground sensors used to detect potential threats at restricted zones. The targets are characterized by a time-varying level of importance, and timing constraints must be fulfilled before a vehicle is allowed to visit a specific target. It is assumed that the vehicles are carrying body-fixed sensors and, thus, are required to approach a designated target while flying straight and level. The fixed-winged aerial vehicles are modeled as Dubins vehicles, i.e., having a constant speed and a minimum turning radius constraint. The investigated integrated problem of task assignment and motion planning is posed in the form of a decision tree, and two search algorithms are proposed: an exhaustive algorithm that improves over run time and provides the minimum cost solution, encoded in the tree, and a greedy algorithm that provides a quick feasible solution. To satisfy the target’s visitation timing constraint, a path elongation motion planning algorithm amidst obstacles is provided. Using simulations, the performance of the algorithms is compared, evaluated and exemplified. PMID:26610522

Robust mobility in human-populated environments

NASA Astrophysics Data System (ADS)

Gonzalez, Juan Pablo; Phillips, Mike; Neuman, Brad; Likhachev, Max

2012-06-01

Creating robots that can help humans in a variety of tasks requires robust mobility and the ability to safely navigate among moving obstacles. This paper presents an overview of recent research in the Robotics Collaborative Technology Alliance (RCTA) that addresses many of the core requirements for robust mobility in human-populated environments. Safe Interval Path Planning (SIPP) allows for very fast planning in dynamic environments when planning timeminimal trajectories. Generalized Safe Interval Path Planning extends this concept to trajectories that minimize arbitrary cost functions. Finally, generalized PPCP algorithm is used to generate plans that reason about the uncertainty in the predicted trajectories of moving obstacles and try to actively disambiguate the intentions of humans whenever necessary. We show how these approaches consider moving obstacles and temporal constraints and produce high-fidelity paths. Experiments in simulated environments show the performance of the algorithms under different controlled conditions, and experiments on physical mobile robots interacting with humans show how the algorithms perform under the uncertainties of the real world.

Modality-specific, multitask locomotor deficits persist despite good recovery after a traumatic brain injury.

PubMed

McFadyen, Bradford J; Cantin, Jean-François; Swaine, Bonnie; Duchesneau, Guylaine; Doyon, Julien; Dumas, Denyse; Fait, Philippe

2009-09-01

To study the effects of sensory modality of simultaneous tasks during walking with and without obstacles after moderate to severe traumatic brain injury (TBI). Group comparison study. Gait analysis laboratory within a postacute rehabilitation facility. Volunteer sample (N=18). Persons with moderate to severe TBI (n=11) (9 men, 3 women; age, 37.56+/-13.79 y) and a comparison group (n=7) of subjects without neurologic problems matched on average for body mass index and age (4 men, 3 women; age, 39.19+/-17.35 y). Not applicable. Magnitudes and variability for walking speeds, foot clearance margins (ratio of foot clearance distance to obstacle height), and response reaction times (both direct and as a relative cost because of obstacle avoidance). The TBI group had well-recovered walking speeds and a general ability to avoid obstacles. However, these subjects did show lower trail limb toe clearances (P=.003) across all conditions. Response reaction times to the Stroop tasks were longer in general for the TBI group (P=.017), and this group showed significant increases in response reaction times for the visual modality within the more challenging obstacle avoidance task that was not observed for control subjects. A measure of multitask costs related to differences in response reaction times between obstructed and unobstructed trials also only showed increased attention costs for the visual over the auditory stimuli for the TBI group (P=.002). Mobility is a complex construct, and the present results provide preliminary findings that, even after good locomotor recovery, subjects with moderate to severe TBI show residual locomotor deficits in multitasking. Furthermore, our results suggest that sensory modality is important, and greater multitask costs occur during sensory competition (ie, visual interference).

Path planning for persistent surveillance applications using fixed-wing unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Keller, James F.

This thesis addresses coordinated path planning for fixed-wing Unmanned Aerial Vehicles (UAVs) engaged in persistent surveillance missions. While uniquely suited to this mission, fixed wing vehicles have maneuver constraints that can limit their performance in this role. Current technology vehicles are capable of long duration flight with a minimal acoustic footprint while carrying an array of cameras and sensors. Both military tactical and civilian safety applications can benefit from this technology. We make three main contributions: C1 A sequential path planner that generates a C 2 flight plan to persistently acquire a covering set of data over a user designated area of interest. The planner features the following innovations: • A path length abstraction that embeds kino-dynamic motion constraints to estimate feasible path length. • A Traveling Salesman-type planner to generate a covering set route based on the path length abstraction. • A smooth path generator that provides C 2 routes that satisfy user specified curvature constraints. C2 A set of algorithms to coordinate multiple UAVs, including mission commencement from arbitrary locations to the start of a coordinated mission and de-confliction of paths to avoid collisions with other vehicles and fixed obstacles. C3 A numerically robust toolbox of spline-based algorithms tailored for vehicle routing validated through flight test experiments on multiple platforms. A variety of tests and platforms are discussed. The algorithms presented are based on a technical approach with approximately equal emphasis on analysis, computation, dynamic simulation, and flight test experimentation. Our planner (C1) directly takes into account vehicle maneuverability and agility constraints that could otherwise render simple solutions infeasible. This is especially important when surveillance objectives elevate the importance of optimized paths. Researchers have developed a diverse range of solutions for persistent surveillance applications but few directly address dynamic maneuver constraints. The key feature of C1 is a two stage sequential solution that discretizes the problem so that graph search techniques can be combined with parametric polynomial curve generation. A method to abstract the kino-dynamics of the aerial platforms is then presented so that a graph search solution can be adapted for this application. An A* Traveling Salesman Problem (TSP) algorithm is developed to search the discretized space using the abstract distance metric to acquire more data or avoid obstacles. Results of the graph search are then transcribed into smooth paths based on vehicle maneuver constraints. A complete solution for a single vehicle periodic tour of the area is developed using the results of the graph search algorithm. To execute the mission, we present a simultaneous arrival algorithm (C2) to coordinate execution by multiple vehicles to satisfy data refresh requirements and to ensure there are no collisions at any of the path intersections. We present a toolbox of spline-based algorithms (C3) to streamline the development of C2 continuous paths with numerical stability. These tools are applied to an aerial persistent surveillance application to illustrate their utility. Comparisons with other parametric polynomial approaches are highlighted to underscore the benefits of the B-spline framework. Performance limits with respect to feasibility constraints are documented.

Visual control of foot placement when walking over complex terrain.

PubMed

Matthis, Jonathan S; Fajen, Brett R

2014-02-01

The aim of this study was to investigate the role of visual information in the control of walking over complex terrain with irregularly spaced obstacles. We developed an experimental paradigm to measure how far along the future path people need to see in order to maintain forward progress and avoid stepping on obstacles. Participants walked over an array of randomly distributed virtual obstacles that were projected onto the floor by an LCD projector while their movements were tracked by a full-body motion capture system. Walking behavior in a full-vision control condition was compared with behavior in a number of other visibility conditions in which obstacles did not appear until they fell within a window of visibility centered on the moving observer. Collisions with obstacles were more frequent and, for some participants, walking speed was slower when the visibility window constrained vision to less than two step lengths ahead. When window sizes were greater than two step lengths, the frequency of collisions and walking speed were weakly affected or unaffected. We conclude that visual information from at least two step lengths ahead is needed to guide foot placement when walking over complex terrain. When placed in the context of recent research on the biomechanics of walking, the findings suggest that two step lengths of visual information may be needed because it allows walkers to exploit the passive mechanical forces inherent to bipedal locomotion, thereby avoiding obstacles while maximizing energetic efficiency. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Dual tasking negatively impacts obstacle avoidance abilities in post-stroke individuals with visuospatial neglect: Task complexity matters!

PubMed

Aravind, Gayatri; Lamontagne, Anouk

2017-01-01

Persons with perceptual-attentional deficits due to visuospatial neglect (VSN) after a stroke are at a risk of collisions while walking in the presence of moving obstacles. The attentional burden of performing a dual-task may further compromise their obstacle avoidance performance, putting them at a greater risk of collisions. The objective of this study was to compare the ability of persons with (VSN+) and without VSN (VSN-) to dual task while negotiating moving obstacles. Twenty-six stroke survivors (13 VSN+, 13 VSN-) were assessed on their ability to (a) negotiate moving obstacles while walking (locomotor single task); (b) perform a pitch-discrimination task (cognitive single task) and (c) simultaneously perform the walking and cognitive tasks (dual task). We compared the groups on locomotor (collision rates, minimum distance from obstacle and onset of strategies) and cognitive (error rates) outcomes. For both single and dual task walking, VSN+ individuals showed higher collision rates compared to VSN- individuals. Dual tasking caused deterioration of locomotor (more collisions, delayed onset and smaller minimum distances) and cognitive performances (higher error rate) in VSN+ individuals. Contrastingly, VSN- individuals maintained collision rates, increased minimum distance, but showed more cognitive errors, prioritizing their locomotor performance. Individuals with VSN demonstrate cognitive-locomotor interference under dual task conditions, which could severely compromise safety when ambulating in community environments and may explain the poor recovery of independent community ambulation in these individuals.

Computer simulation and evaluation of edge detection algorithms and their application to automatic path selection

NASA Technical Reports Server (NTRS)

Longendorfer, B. A.

1976-01-01

The construction of an autonomous roving vehicle requires the development of complex data-acquisition and processing systems, which determine the path along which the vehicle travels. Thus, a vehicle must possess algorithms which can (1) reliably detect obstacles by processing sensor data, (2) maintain a constantly updated model of its surroundings, and (3) direct its immediate actions to further a long range plan. The first function consisted of obstacle recognition. Obstacles may be identified by the use of edge detection techniques. Therefore, the Kalman Filter was implemented as part of a large scale computer simulation of the Mars Rover. The second function consisted of modeling the environment. The obstacle must be reconstructed from its edges, and the vast amount of data must be organized in a readily retrievable form. Therefore, a Terrain Modeller was developed which assembled and maintained a rectangular grid map of the planet. The third function consisted of directing the vehicle's actions.

Waist-up protection for blind individuals using the EyeCane as a primary and secondary mobility aid

PubMed Central

Buchs, Galit; Simon, Noa; Maidenbaum, Shachar; Amedi, Amir

2017-01-01

Background: One of the most stirring statistics in relation to the mobility of blind individuals is the high rate of upper body injuries, even when using the white-cane. Objective: We here addressed a rehabilitation- oriented challenge of providing a reliable tool for blind people to avoid waist-up obstacles, namely one of the impediments to their successful mobility using currently available methods (e.g., white-cane). Methods: We used the EyeCane, a device we developed which translates distances from several angles to haptic and auditory cues in an intuitive and unobtrusive manner, serving both as a primary and secondary mobility aid. We investigated the rehabilitation potential of such a device in facilitating visionless waist-up body protection. Results: After ∼5 minutes of training with the EyeCane blind participants were able to successfully detect and avoid obstacles waist-high and up. This was significantly higher than their success when using the white-cane alone. As avoidance of obstacles required participants to perform an additional cognitive process after their detection, the avoidance rate was significantly lower than the detection rate. Conclusion: Our work has demonstrated that the EyeCane has the potential to extend the sensory world of blind individuals by expanding their currently accessible inputs, and has offered them a new practical rehabilitation tool. PMID:28157111

Stepping over obstacles: gait patterns of healthy young and old adults.

PubMed

Chen, H C; Ashton-Miller, J A; Alexander, N B; Schultz, A B

1991-11-01

Falls associated with tripping over an obstacle can be devastating to elderly individuals, yet little is known about the strategies used for stepping over obstacles by either old or young adults. The gait of gender-matched groups of 24 young and 24 old healthy adults (mean ages 22 and 71 years) was studied during a 4 m approach to and while stepping over obstacles of 0, 25, 51, or 152 mm height and in level obstacle-free walking. Optoelectronic cameras and recorders were used to record approach and obstacle crossing speeds as well as bilateral lower extremity kinematic parameters that described foot placement and movement trajectories relative to the obstacle. The results showed that age had no effect on minimum swing foot clearance (FC) over an obstacle. For the 25 mm obstacle, mean FC was 64 mm, or approximately three times that used in level gait; FC increased nonlinearly with obstacle height for all subjects. Although no age differences were found in obstacle-free gait, old adults exhibited a significantly more conservative strategy when crossing obstacles, with slower crossing speed, shorter step length, and shorter obstacle-heel strike distance. In addition, the old adults crossed the obstacle so that it was 10% further forward in their obstacle-crossing step. Although all subjects successfully avoided the riskiest form of obstacle contact, tripping, 4/24 healthy old adults stepped on an obstacle, demonstrating an increased risk for obstacle contact with age.

Path planning for mobile robot using the novel repulsive force algorithm

NASA Astrophysics Data System (ADS)

Sun, Siyue; Yin, Guoqiang; Li, Xueping

2018-01-01

A new type of repulsive force algorithm is proposed to solve the problem of local minimum and the target unreachable of the classic Artificial Potential Field (APF) method in this paper. The Gaussian function that is related to the distance between the robot and the target is added to the traditional repulsive force, solving the problem of the goal unreachable with the obstacle nearby; variable coefficient is added to the repulsive force component to resize the repulsive force, which can solve the local minimum problem when the robot, the obstacle and the target point are in the same line. The effectiveness of the algorithm is verified by simulation based on MATLAB and actual mobile robot platform.

Intelligent Surveillance Robot with Obstacle Avoidance Capabilities Using Neural Network

PubMed Central

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

A sub-target approach to the kinodynamic motion control of a wheeled mobile robot

NASA Astrophysics Data System (ADS)

Motonaka, Kimiko; Watanabe, Keigo; Maeyama, Shoichi

2018-02-01

A mobile robot with two independently driven wheels is popular, but it is difficult to stabilize it by a continuous controller with a constant gain, due to its nonholonomic property. It is guaranteed that a nonholonomic controlled object can always be converged to an arbitrary point using a switching control method or a quasi-continuous control method based on an invariant manifold in a chained form. From this, the authors already proposed a kinodynamic controller to converge the states of such a two-wheeled mobile robot to the arbitrary target position while avoiding obstacles, by combining the control based on the invariant manifold and the harmonic potential field (HPF). On the other hand, it was confirmed in the previous research that there is a case that the robot cannot avoid the obstacle because there is no enough space to converge the current state to the target state. In this paper, we propose a method that divides the final target position into some sub-target positions and moves the robot step by step, and it is confirmed by the simulation that the robot can converge to the target position while avoiding obstacles using the proposed method.

Semi-autonomous wheelchair system using stereoscopic cameras.

PubMed

Nguyen, Jordan S; Nguyen, Thanh H; Nguyen, Hung T

2009-01-01

This paper is concerned with the design and development of a semi-autonomous wheelchair system using stereoscopic cameras to assist hands-free control technologies for severely disabled people. The stereoscopic cameras capture an image from both the left and right cameras, which are then processed with a Sum of Absolute Differences (SAD) correlation algorithm to establish correspondence between image features in the different views of the scene. This is used to produce a stereo disparity image containing information about the depth of objects away from the camera in the image. A geometric projection algorithm is then used to generate a 3-Dimensional (3D) point map, placing pixels of the disparity image in 3D space. This is then converted to a 2-Dimensional (2D) depth map allowing objects in the scene to be viewed and a safe travel path for the wheelchair to be planned and followed based on the user's commands. This assistive technology utilising stereoscopic cameras has the purpose of automated obstacle detection, path planning and following, and collision avoidance during navigation. Experimental results obtained in an indoor environment displayed the effectiveness of this assistive technology.

Discrete range clustering using Monte Carlo methods

NASA Technical Reports Server (NTRS)

Chatterji, G. B.; Sridhar, B.

1993-01-01

For automatic obstacle avoidance guidance during rotorcraft low altitude flight, a reliable model of the nearby environment is needed. Such a model may be constructed by applying surface fitting techniques to the dense range map obtained by active sensing using radars. However, for covertness, passive sensing techniques using electro-optic sensors are desirable. As opposed to the dense range map obtained via active sensing, passive sensing algorithms produce reliable range at sparse locations, and therefore, surface fitting techniques to fill the gaps in the range measurement are not directly applicable. Both for automatic guidance and as a display for aiding the pilot, these discrete ranges need to be grouped into sets which correspond to objects in the nearby environment. The focus of this paper is on using Monte Carlo methods for clustering range points into meaningful groups. One of the aims of the paper is to explore whether simulated annealing methods offer significant advantage over the basic Monte Carlo method for this class of problems. We compare three different approaches and present application results of these algorithms to a laboratory image sequence and a helicopter flight sequence.

Robot path planning using a genetic algorithm

NASA Technical Reports Server (NTRS)

Cleghorn, Timothy F.; Baffes, Paul T.; Wang, Liu

1988-01-01

Robot path planning can refer either to a mobile vehicle such as a Mars Rover, or to an end effector on an arm moving through a cluttered workspace. In both instances there may exist many solutions, some of which are better than others, either in terms of distance traversed, energy expended, or joint angle or reach capabilities. A path planning program has been developed based upon a genetic algorithm. This program assumes global knowledge of the terrain or workspace, and provides a family of good paths between the initial and final points. Initially, a set of valid random paths are constructed. Successive generations of valid paths are obtained using one of several possible reproduction strategies similar to those found in biological communities. A fitness function is defined to describe the goodness of the path, in this case including length, slope, and obstacle avoidance considerations. It was found that with some reproduction strategies, the average value of the fitness function improved for successive generations, and that by saving the best paths of each generation, one could quite rapidly obtain a collection of good candidate solutions.

Automated Robot Movement in the Mapped Area Using Fuzzy Logic for Wheel Chair Application

NASA Astrophysics Data System (ADS)

Siregar, B.; Efendi, S.; Ramadhana, H.; Andayani, U.; Fahmi, F.

2018-03-01

The difficulties of the disabled to move make them unable to live independently. People with disabilities need supporting device to move from place to place. For that, we proposed a solution that can help people with disabilities to move from one room to another automatically. This study aims to create a wheelchair prototype in the form of a wheeled robot as a means to learn the automatic mobilization. The fuzzy logic algorithm was used to determine motion direction based on initial position, ultrasonic sensors reading in avoiding obstacles, infrared sensors reading as a black line reader for the wheeled robot to move smooth and smartphone as a mobile controller. As a result, smartphones with the Android operating system can control the robot using Bluetooth. Here Bluetooth technology can be used to control the robot from a maximum distance of 15 meters. The proposed algorithm was able to work stable for automatic motion determination based on initial position, and also able to modernize the wheelchair movement from one room to another automatically.

Applications of fuzzy logic to control and decision making

NASA Technical Reports Server (NTRS)

Lea, Robert N.; Jani, Yashvant

1991-01-01

Long range space missions will require high operational efficiency as well as autonomy to enhance the effectivity of performance. Fuzzy logic technology has been shown to be powerful and robust in interpreting imprecise measurements and generating appropriate control decisions for many space operations. Several applications are underway, studying the fuzzy logic approach to solving control and decision making problems. Fuzzy logic algorithms for relative motion and attitude control have been developed and demonstrated for proximity operations. Based on this experience, motion control algorithms that include obstacle avoidance were developed for a Mars Rover prototype for maneuvering during the sample collection process. A concept of an intelligent sensor system that can identify objects and track them continuously and learn from its environment is under development to support traffic management and proximity operations around the Space Station Freedom. For safe and reliable operation of Lunar/Mars based crew quarters, high speed controllers with ability to combine imprecise measurements from several sensors is required. A fuzzy logic approach that uses high speed fuzzy hardware chips is being studied.

Does practicing a wide range of joint angle configurations lead to higher flexibility in a manual obstacle-avoidance target-pointing task?

PubMed Central

Bootsma, Reinoud J.; Schoemaker, Marina M.; Otten, Egbert; Mouton, Leonora J.; Bongers, Raoul M.

2017-01-01

Flexibility in motor actions can be defined as variability in the use of degrees of freedom (e.g., joint angles in the arm) over repetitions while keeping performance (e.g., fingertip position) stabilized. We examined whether flexibility can be increased through enlarging the joint angle range during practice in a manual obstacle-avoidance target-pointing task. To establish differences in flexibility we partitioned the variability in joint angles over repetitions in variability within (GEV) and variability outside the solution space (NGEV). More GEV than NGEV reflects flexibility; when the ratio of the GEV and NGEV is higher, flexibility is higher. The pretest and posttest consisted of 30 repetitions of manual pointing to a target while moving over a 10 cm high obstacle. To enlarge the joint angle range during practice participants performed 600 target-pointing movements while moving over obstacles of different heights (5–9 cm, 11–15 cm). The results indicated that practicing movements over obstacles of different heights led participants to use enlarged range of joint angles compared to the range of joint angles used in movements over the 10 cm obstacle in the pretest. However, for each individual obstacle neither joint angle variance nor flexibility were higher during practice. We also did not find more flexibility after practice. In the posttest, joint angle variance was in fact smaller than before practice, primarily in GEV. The potential influences of learning effects and the task used that could underlie the results obtained are discussed. We conclude that with this specific type of practice in this specific task, enlarging the range of joint angles does not lead to more flexibility. PMID:28700695

Negative obstacle detection by thermal signature

NASA Technical Reports Server (NTRS)

Matthies, Larry; Rankin, A.

2003-01-01

Detecting negative obstacles (ditches, potholes, and other depressions) is one of the most difficult problems in perception for autonomous, off-road navigation. Past work has largely relied on range imagery, because that is based on the geometry of the obstacle, is largely insensitive to illumination variables, and because there have not been other reliable alternatives. However, the visible aspect of negative obstacles shrinks rapidly with range, making them impossible to detect in time to avoid them at high speed. To relive this problem, we show that the interiors of negative obstacles generally remain warmer than the surrounding terrain throughout the night, making thermal signature a stable property for night-time negative obstacle detection. Experimental results to date have achieved detection distances 45% greater by using thermal signature than by using range data alone. Thermal signature is the first known observable with potential to reveal a deep negative obstacle without actually seeing far into it. Modeling solar illumination has potential to extend the usefulness of thermal signature through daylight hours.

The Effects of Shoe Traction and Obstacle Height on Lower Extremity Coordination Dynamics during Walking

PubMed Central

Decker, Leslie; Houser, Jeremy J.; Noble, John M.; Karst, Gregory M.; Stergiou, Nicholas

2009-01-01

This study aims to investigate the effects of shoe traction and obstacle height on lower extremity relative phase dynamics (analysis of intralimb coordination) during walking to better understand the mechanisms employed to avoid slippage following obstacle clearance. Ten participants walked at a self-selected pace during eight conditions: four obstacle heights (0%, 10%, 20%, and 40% of limb length) while wearing two pairs of shoes (low and high traction). A coordination analysis was used and phasing relationships between lower extremity segments were examined. The results demonstrated that significant behavioral changes were elicited under varied obstacle heights and frictional conditions. Both decreasing shoe traction and increasing obstacle height resulted in a more in-phase relationship between the interacting lower limb segments. The higher the obstacle and the lower the shoe traction, the more unstable the system became. These changes in phasing relationship and variability are indicators of alterations in coordinative behavior, which if pushed further may have lead to falling. PMID:19187929

Multi-actuators vehicle collision avoidance system - Experimental validation

NASA Astrophysics Data System (ADS)

Hamid, Umar Zakir Abdul; Zakuan, Fakhrul Razi Ahmad; Akmal Zulkepli, Khairul; Zulfaqar Azmi, Muhammad; Zamzuri, Hairi; Rahman, Mohd Azizi Abdul; Aizzat Zakaria, Muhammad

2018-04-01

The Insurance Institute for Highway Safety (IIHS) of the United States of America in their reports has mentioned that a significant amount of the road mishaps would be preventable if more automated active safety applications are adopted into the vehicle. This includes the incorporation of collision avoidance system. The autonomous intervention by the active steering and braking systems in the hazardous scenario can aid the driver in mitigating the collisions. In this work, a real-time platform of a multi-actuators vehicle collision avoidance system is developed. It is a continuous research scheme to develop a fully autonomous vehicle in Malaysia. The vehicle is a modular platform which can be utilized for different research purposes and is denominated as Intelligent Drive Project (iDrive). The vehicle collision avoidance proposed design is validated in a controlled environment, where the coupled longitudinal and lateral motion control system is expected to provide desired braking and steering actuation in the occurrence of a frontal static obstacle. Results indicate the ability of the platform to yield multi-actuators collision avoidance navigation in the hazardous scenario, thus avoiding the obstacle. The findings of this work are beneficial for the development of a more complex and nonlinear real-time collision avoidance work in the future.

Focusing a Transition: A Report by the Defense Business Board

DTIC Science & Technology

2009-01-01

2. NEAR-TERM OBSTACLES THAT COULD HAMPER LONG -TERM SUCCESS .................................................................25 Lowering the Overhead...requiring immediate att ention, (2) near-term obstacles that could hamper long -term success, (3) organizational issues for the Department to address for...begin early – long before January 20th - to avoid major leadership gaps (see Figure 1-2) and unnecessary vulnerabilities to the Department. Department

Robonaut Mobile Autonomy: Initial Experiments

NASA Technical Reports Server (NTRS)

Diftler, M. A.; Ambrose, R. O.; Goza, S. M.; Tyree, K. S.; Huber, E. L.

2006-01-01

A mobile version of the NASA/DARPA Robonaut humanoid recently completed initial autonomy trials working directly with humans in cluttered environments. This compact robot combines the upper body of the Robonaut system with a Segway Robotic Mobility Platform yielding a dexterous, maneuverable humanoid ideal for interacting with human co-workers in a range of environments. This system uses stereovision to locate human teammates and tools and a navigation system that uses laser range and vision data to follow humans while avoiding obstacles. Tactile sensors provide information to grasping algorithms for efficient tool exchanges. The autonomous architecture utilizes these pre-programmed skills to form complex behaviors. The initial behavior demonstrates a robust capability to assist a human by acquiring a tool from a remotely located individual and then following the human in a cluttered environment with the tool for future use.

Distance estimation and collision prediction for on-line robotic motion planning

NASA Technical Reports Server (NTRS)

Kyriakopoulos, K. J.; Saridis, G. N.

1992-01-01

An efficient method for computing the minimum distance and predicting collisions between moving objects is presented. This problem is incorporated into the framework of an in-line motion-planning algorithm to satisfy collision avoidance between a robot and moving objects modeled as convex polyhedra. In the beginning, the deterministic problem where the information about the objects is assumed to be certain is examined. L(1) or L(infinity) norms are used to represent distance and the problem becomes a linear programming problem. The stochastic problem is formulated where the uncertainty is induced by sensing and the unknown dynamics of the moving obstacles. Two problems are considered: First, filtering of the distance between the robot and the moving object at the present time. Second, prediction of the minimum distance in the future in order to predict the collision time.

Characterization of selected elementary motion detector cells to image primitives.

PubMed

Benson, Leslie A; Barrett, Steven F; Wright, Cameron H G

2008-01-01

Developing a visual sensing system, complete with motion processing hardware and software would have many applications to current technology. It could be mounted on many autonomous vehicles to provide information about the navigational environment, as well as obstacle avoidance features. Incorporating the motion processing capabilities into the sensor requires a new approach to the algorithm implementation. This research, and that of many others, have turned to nature for inspiration. Elementary motion detector (EMD) cells are involved in a biological preprocessing network to provide information to the motion processing lobes of the house degrees y Musca domestica. This paper describes the response of the photoreceptor inputs to the EMDs. The inputs to the EMD components are tested as they are stimulated with varying image primitives. This is the first of many steps in characterizing the EMD response to image primitives.

Needle path planning and steering in a three-dimensional non-static environment using two-dimensional ultrasound images

PubMed Central

Vrooijink, Gustaaf J.; Abayazid, Momen; Patil, Sachin; Alterovitz, Ron; Misra, Sarthak

2015-01-01

Needle insertion is commonly performed in minimally invasive medical procedures such as biopsy and radiation cancer treatment. During such procedures, accurate needle tip placement is critical for correct diagnosis or successful treatment. Accurate placement of the needle tip inside tissue is challenging, especially when the target moves and anatomical obstacles must be avoided. We develop a needle steering system capable of autonomously and accurately guiding a steerable needle using two-dimensional (2D) ultrasound images. The needle is steered to a moving target while avoiding moving obstacles in a three-dimensional (3D) non-static environment. Using a 2D ultrasound imaging device, our system accurately tracks the needle tip motion in 3D space in order to estimate the tip pose. The needle tip pose is used by a rapidly exploring random tree-based motion planner to compute a feasible needle path to the target. The motion planner is sufficiently fast such that replanning can be performed repeatedly in a closed-loop manner. This enables the system to correct for perturbations in needle motion, and movement in obstacle and target locations. Our needle steering experiments in a soft-tissue phantom achieves maximum targeting errors of 0.86 ± 0.35 mm (without obstacles) and 2.16 ± 0.88 mm (with a moving obstacle). PMID:26279600

Measures for simulator evaluation of a helicopter obstacle avoidance system

NASA Technical Reports Server (NTRS)

Demaio, Joe; Sharkey, Thomas J.; Kennedy, David; Hughes, Micheal; Meade, Perry

1993-01-01

The U.S. Army Aeroflightdynamics Directorate (AFDD) has developed a high-fidelity, full-mission simulation facility for the demonstration and evaluation of advanced helicopter mission equipment. The Crew Station Research and Development Facility (CSRDF) provides the capability to conduct one- or two-crew full-mission simulations in a state-of-the-art helicopter simulator. The CSRDF provides a realistic, full field-of-regard visual environment with simulation of state-of-the-art weapons, sensors, and flight control systems. We are using the CSRDF to evaluate the ability of an obstacle avoidance system (OASYS) to support low altitude flight in cluttered terrain using night vision goggles (NVG). The OASYS uses a laser radar to locate obstacles to safe flight in the aircraft's flight path. A major concern is the detection of wires, which can be difficult to see with NVG, but other obstacles--such as trees, poles or the ground--are also a concern. The OASYS symbology is presented to the pilot on a head-up display mounted on the NVG (NVG-HUD). The NVG-HUD presents head-stabilized symbology to the pilot while allowing him to view the image intensified, out-the-window scene through the HUD. Since interference with viewing through the display is a major concern, OASYS symbology must be designed to present usable obstacle clearance information with a minimum of clutter.

Self-crowding of AMPA receptors in the excitatory postsynaptic density can effectuate anomalous receptor sub-diffusion.

PubMed

Gupta, Rahul

2018-02-01

AMPA receptors (AMPARs) and their associations with auxiliary transmembrane proteins are bulky structures with large steric-exclusion volumes. Hence, self-crowding of AMPARs, depending on the local density, may affect their lateral diffusion in the postsynaptic membrane as well as in the highly crowded postsynaptic density (PSD) at excitatory synapses. Earlier theoretical studies considered only the roles of transmembrane obstacles and the AMPAR-binding submembranous scaffold proteins in shaping receptor diffusion within PSD. Using lattice model of diffusion, the present study investigates the additional impacts of self-crowding on the anomalousity and effective diffusion coefficient (Deff) of AMPAR diffusion. A recursive algorithm for avoiding false self-blocking during diffusion simulation is also proposed. The findings suggest that high density of AMPARs in the obstacle-free membrane itself engenders strongly anomalous diffusion and severe decline in Deff. Adding transmembrane obstacles to the membrane accentuates the anomalousity arising from self-crowding due to the reduced free diffusion space. Contrarily, enhanced AMPAR-scaffold binding, either through increase in binding strength or scaffold density or both, ameliorates the anomalousity resulting from self-crowding. However, binding has differential impacts on Deff depending on the receptor density. Increase in binding causes consistent decrease in Deff for low and moderate receptor density. For high density, binding increases Deff as long as it reduces anomalousity associated with intense self-crowding. Given a sufficiently strong binding condition when diffusion acquires normal behavior, further increase in binding causes decrease in Deff. Supporting earlier experimental observations are mentioned and implications of present findings to the experimental observations on AMPAR diffusion are also drawn.

Reinforcement learning algorithms for robotic navigation in dynamic environments.

PubMed

Yen, Gary G; Hickey, Travis W

2004-04-01

The purpose of this study was to examine improvements to reinforcement learning (RL) algorithms in order to successfully interact within dynamic environments. The scope of the research was that of RL algorithms as applied to robotic navigation. Proposed improvements include: addition of a forgetting mechanism, use of feature based state inputs, and hierarchical structuring of an RL agent. Simulations were performed to evaluate the individual merits and flaws of each proposal, to compare proposed methods to prior established methods, and to compare proposed methods to theoretically optimal solutions. Incorporation of a forgetting mechanism did considerably improve the learning times of RL agents in a dynamic environment. However, direct implementation of a feature-based RL agent did not result in any performance enhancements, as pure feature-based navigation results in a lack of positional awareness, and the inability of the agent to determine the location of the goal state. Inclusion of a hierarchical structure in an RL agent resulted in significantly improved performance, specifically when one layer of the hierarchy included a feature-based agent for obstacle avoidance, and a standard RL agent for global navigation. In summary, the inclusion of a forgetting mechanism, and the use of a hierarchically structured RL agent offer substantially increased performance when compared to traditional RL agents navigating in a dynamic environment.

3D sensor algorithms for spacecraft pose determination

NASA Astrophysics Data System (ADS)

Trenkle, John M.; Tchoryk, Peter, Jr.; Ritter, Greg A.; Pavlich, Jane C.; Hickerson, Aaron S.

2006-05-01

Researchers at the Michigan Aerospace Corporation have developed accurate and robust 3-D algorithms for pose determination (position and orientation) of satellites as part of an on-going effort supporting autonomous rendezvous, docking and space situational awareness activities. 3-D range data from a LAser Detection And Ranging (LADAR) sensor is the expected input; however, the approach is unique in that the algorithms are designed to be sensor independent. Parameterized inputs allow the algorithms to be readily adapted to any sensor of opportunity. The cornerstone of our approach is the ability to simulate realistic range data that may be tailored to the specifications of any sensor. We were able to modify an open-source raytracing package to produce point cloud information from which high-fidelity simulated range images are generated. The assumptions made in our experimentation are as follows: 1) we have access to a CAD model of the target including information about the surface scattering and reflection characteristics of the components; 2) the satellite of interest may appear at any 3-D attitude; 3) the target is not necessarily rigid, but does have a limited number of configurations; and, 4) the target is not obscured in any way and is the only object in the field of view of the sensor. Our pose estimation approach then involves rendering a large number of exemplars (100k to 5M), extracting 2-D (silhouette- and projection-based) and 3-D (surface-based) features, and then training ensembles of decision trees to predict: a) the 4-D regions on a unit hypersphere into which the unit quaternion that represents the vehicle [Q X, Q Y, Q Z, Q W] is pointing, and, b) the components of that unit quaternion. Results have been quite promising and the tools and simulation environment developed for this application may also be applied to non-cooperative spacecraft operations, Autonomous Hazard Detection and Avoidance (AHDA) for landing craft, terrain mapping, vehicle guidance, path planning and obstacle avoidance.

Using Rollback Avoidance to Mitigate Failures in Next-Generation Extreme-Scale Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levy, Scott N.

2016-05-01

High-performance computing (HPC) systems enable scientists to numerically model complex phenomena in many important physical systems. The next major milestone in the development of HPC systems is the construction of the rst supercomputer capable executing more than an exa op, 10 18 oating point operations per second. On systems of this scale, failures will occur much more frequently than on current systems. As a result, resilience is a key obstacle to building next-generation extremescale systems. Coordinated checkpointing is currently the most widely-used mechanism for handling failures on HPC systems. Although coordinated checkpointing remains e ective on current systems, increasing themore » scale of today's systems to build next-generation systems will increase the cost of fault tolerance as more and more time is taken away from the application to protect against or recover from failure. Rollback avoidance techniques seek to mitigate the cost of checkpoint/restart by allowing an application to continue its execution rather than rolling back to an earlier checkpoint when failures occur. These techniqes include failure prediction and preventive migration, replicated computation, fault-tolerant algorithms, and softwarebased memory fault correction. In this thesis, we examine how rollback avoidance techniques can be used to address failures on extreme-scale systems. Using a combination of analytic modeling and simulation, we evaluate the potential impact of rollback avoidance on these systems. We then present a novel rollback avoidance technique that exploits similarities in application memory. Finally, we examine the feasibility of using this technique to protect against memory faults in kernel memory.« less

Developing operation algorithms for vision subsystems in autonomous mobile robots

NASA Astrophysics Data System (ADS)

Shikhman, M. V.; Shidlovskiy, S. V.

2018-05-01

The paper analyzes algorithms for selecting keypoints on the image for the subsequent automatic detection of people and obstacles. The algorithm is based on the histogram of oriented gradients and the support vector method. The combination of these methods allows successful selection of dynamic and static objects. The algorithm can be applied in various autonomous mobile robots.

Development and human factors analysis of an augmented reality interface for multi-robot tele-operation and control

NASA Astrophysics Data System (ADS)

Lee, Sam; Lucas, Nathan P.; Ellis, R. Darin; Pandya, Abhilash

2012-06-01

This paper presents a seamlessly controlled human multi-robot system comprised of ground and aerial robots of semiautonomous nature for source localization tasks. The system combines augmented reality interfaces capabilities with human supervisor's ability to control multiple robots. The role of this human multi-robot interface is to allow an operator to control groups of heterogeneous robots in real time in a collaborative manner. It used advanced path planning algorithms to ensure obstacles are avoided and that the operators are free for higher-level tasks. Each robot knows the environment and obstacles and can automatically generate a collision-free path to any user-selected target. It displayed sensor information from each individual robot directly on the robot in the video view. In addition, a sensor data fused AR view is displayed which helped the users pin point source information or help the operator with the goals of the mission. The paper studies a preliminary Human Factors evaluation of this system in which several interface conditions are tested for source detection tasks. Results show that the novel Augmented Reality multi-robot control (Point-and-Go and Path Planning) reduced mission completion times compared to the traditional joystick control for target detection missions. Usability tests and operator workload analysis are also investigated.

Stereo vision tracking of multiple objects in complex indoor environments.

PubMed

Marrón-Romera, Marta; García, Juan C; Sotelo, Miguel A; Pizarro, Daniel; Mazo, Manuel; Cañas, José M; Losada, Cristina; Marcos, Alvaro

2010-01-01

This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot's environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors' proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found.

Speeded Reaching Movements around Invisible Obstacles

PubMed Central

Hudson, Todd E.; Wolfe, Uta; Maloney, Laurence T.

2012-01-01

We analyze the problem of obstacle avoidance from a Bayesian decision-theoretic perspective using an experimental task in which reaches around a virtual obstacle were made toward targets on an upright monitor. Subjects received monetary rewards for touching the target and incurred losses for accidentally touching the intervening obstacle. The locations of target-obstacle pairs within the workspace were varied from trial to trial. We compared human performance to that of a Bayesian ideal movement planner (who chooses motor strategies maximizing expected gain) using the Dominance Test employed in Hudson et al. (2007). The ideal movement planner suffers from the same sources of noise as the human, but selects movement plans that maximize expected gain in the presence of that noise. We find good agreement between the predictions of the model and actual performance in most but not all experimental conditions. PMID:23028276

Computer vision techniques for rotorcraft low-altitude flight

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Cheng, Victor H. L.

1988-01-01

A description is given of research that applies techniques from computer vision to automation of rotorcraft navigation. The effort emphasizes the development of a methodology for detecting the ranges to obstacles in the region of interest based on the maximum utilization of passive sensors. The range map derived from the obstacle detection approach can be used as obstacle data for the obstacle avoidance in an automataic guidance system and as advisory display to the pilot. The lack of suitable flight imagery data, however, presents a problem in the verification of concepts for obstacle detection. This problem is being addressed by the development of an adequate flight database and by preprocessing of currently available flight imagery. Some comments are made on future work and how research in this area relates to the guidance of other autonomous vehicles.

Innovative research of AD HOC network mobility model

NASA Astrophysics Data System (ADS)

Chen, Xin

2017-08-01

It is difficult for researchers of AD HOC network to conduct actual deployment during experimental stage as the network topology is changeable and location of nodes is unfixed. Thus simulation still remains the main research method of the network. Mobility model is an important component of AD HOC network simulation. It is used to describe the movement pattern of nodes in AD HOC network (including location and velocity, etc.) and decides the movement trail of nodes, playing as the abstraction of the movement modes of nodes. Therefore, mobility model which simulates node movement is an important foundation for simulation research. In AD HOC network research, mobility model shall reflect the movement law of nodes as truly as possible. In this paper, node generally refers to the wireless equipment people carry. The main research contents include how nodes avoid obstacles during movement process and the impacts of obstacles on the mutual relation among nodes, based on which a Node Self Avoiding Obstacle, i.e. NASO model is established in AD HOC network.

Obstacle Detection Algorithms for Rotorcraft Navigation

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar; Camps, Octavia I.; Huang, Ying; Narasimhamurthy, Anand; Pande, Nitin; Ahumada, Albert (Technical Monitor)

2001-01-01

In this research we addressed the problem of obstacle detection for low altitude rotorcraft flight. In particular, the problem of detecting thin wires in the presence of image clutter and noise was studied. Wires present a serious hazard to rotorcrafts. Since they are very thin, their detection early enough so that the pilot has enough time to take evasive action is difficult, as their images can be less than one or two pixels wide. After reviewing the line detection literature, an algorithm for sub-pixel edge detection proposed by Steger was identified as having good potential to solve the considered task. The algorithm was tested using a set of images synthetically generated by combining real outdoor images with computer generated wire images. The performance of the algorithm was evaluated both, at the pixel and the wire levels. It was observed that the algorithm performs well, provided that the wires are not too thin (or distant) and that some post processing is performed to remove false alarms due to clutter.

Nonlinear Geometric and Differential Geometric Guidance of UAVs with Vision Sensing for Reactive Obstacle Avoidance

DTIC Science & Technology

2010-09-29

1 1 1 2 2 2ˆ ˆ ˆ ˆ ˆ ˆˆ ˆ ˆ ˆ0 0 0 0 0 0 0 0 0 0 T r ob ob ob ob ob ob tr tr trX r r rθ φ θ φ θ φ= (3.28) 29...ˆ ˆ ˆ ˆˆ ˆ ˆ0 0 0 0 0 0 0 T r ob ob ob tr tr trX r rθ φ θ φ⎡ ⎤= ⎣ ⎦ (3.29) Since obstacles are assumed to be point obstacles, it

Active avoidance: escape and dodging behaviors for reactive control

NASA Astrophysics Data System (ADS)

Arkin, Ronald C.; Carter, William M.

1992-03-01

New methods for producing avoidance behavior among moving obstacles within the context of reactive robotic control are described. These specifically include escape and dodging behaviors. Dodging is concerned with the avoidance of a ballistic projectile while escape is more useful within the context of chase. The motivation and formulation of these new reactive behaviors are presented. Simulation results of a robot in a cluttered and moving world are also provided.

Cascading a systolic array and a feedforward neural network for navigation and obstacle avoidance using potential fields

NASA Technical Reports Server (NTRS)

Plumer, Edward S.

1991-01-01

A technique is developed for vehicle navigation and control in the presence of obstacles. A potential function was devised that peaks at the surface of obstacles and has its minimum at the proper vehicle destination. This function is computed using a systolic array and is guaranteed not to have local minima. A feedfoward neural network is then used to control the steering of the vehicle using local potential field information. In this case, the vehicle is a trailer truck backing up. Previous work has demonstrated the capability of a neural network to control steering of such a trailer truck backing to a loading platform, but without obstacles. Now, the neural network was able to learn to navigate a trailer truck around obstacles while backing toward its destination. The network is trained in an obstacle free space to follow the negative gradient of the field, after which the network is able to control and navigate the truck to its target destination in a space of obstacles which may be stationary or movable.

Using distributed partial memories to improve self-organizing collective movements.

PubMed

Winder, Ransom; Reggia, James A

2004-08-01

Past self-organizing models of collectively moving "particles" (simulated bird flocks, fish schools, etc.) have typically been based on purely reflexive agents that have no significant memory of past movements. We hypothesized that giving such individual particles a limited distributed memory of past obstacles they encountered could lead to significantly faster travel between goal destinations. Systematic computational experiments using six terrains that had different arrangements of obstacles demonstrated that, at least in some domains, this conjecture is true. Furthermore, these experiments demonstrated that improved performance over time came not only from the avoidance of previously seen obstacles, but also (surprisingly) immediately after first encountering obstacles due to decreased delays in circumventing those obstacles. Simulations also showed that, of the four strategies we tested for removal of remembered obstacles when memory was full and a new obstacle was to be saved, none was better than random selection. These results may be useful in interpreting future experimental research on group movements in biological populations, and in improving existing methodologies for control of collective movements in computer graphics, robotic teams, particle swarm optimization, and computer games.

Prism adaptation and generalization during visually guided locomotor tasks.

PubMed

Alexander, M Scott; Flodin, Brent W G; Marigold, Daniel S

2011-08-01

The ability of individuals to adapt locomotion to constraints associated with the complex environments normally encountered in everyday life is paramount for survival. Here, we tested the ability of 24 healthy young adults to adapt to a rightward prism shift (∼11.3°) while either walking and stepping to targets (i.e., precision stepping task) or stepping over an obstacle (i.e., obstacle avoidance task). We subsequently tested for generalization to the other locomotor task. In the precision stepping task, we determined the lateral end-point error of foot placement from the targets. In the obstacle avoidance task, we determined toe clearance and lateral foot placement distance from the obstacle before and after stepping over the obstacle. We found large, rightward deviations in foot placement on initial exposure to prisms in both tasks. The majority of measures demonstrated adaptation over repeated trials, and adaptation rates were dependent mainly on the task. On removal of the prisms, we observed negative aftereffects for measures of both tasks. Additionally, we found a unilateral symmetric generalization pattern in that the left, but not the right, lower limb indicated generalization across the 2 locomotor tasks. These results indicate that the nervous system is capable of rapidly adapting to a visuomotor mismatch during visually demanding locomotor tasks and that the prism-induced adaptation can, at least partially, generalize across these tasks. The results also support the notion that the nervous system utilizes an internal model for the control of visually guided locomotion.

Performance and three-dimensional kinematics of bipedal lizards during obstacle negotiation.

PubMed

Olberding, Jeffrey P; McBrayer, Lance D; Higham, Timothy E

2012-01-15

Bipedal running is common among lizard species, but although the kinematics and performance of this gait have been well characterized, the advantages in biologically relevant situations are still unclear. Obstacle negotiation is a task that is ecologically relevant to many animals while moving at high speeds, such as during bipedal running, yet little is known about how obstacles impact locomotion and performance. We examined the effects of obstacle negotiation on the kinematics and performance of lizards during bipedal locomotion. We quantified three-dimensional kinematics from high-speed video (500 Hz) of six-lined racerunners (Aspidoscelis sexlineata) running on a 3 m racetrack both with and without an obstacle spanning the width of the track. The lizards did not alter their kinematics prior to contacting the obstacle. Although contact with the obstacle caused changes to the hindlimb kinematics, mean forward speed did not differ between treatments. The deviation of the vertical position of the body center of mass did not differ between treatments, suggesting that in the absence of a cost to overall performance, lizards forgo maintaining normal kinematics while negotiating obstacles in favor of a steady body center of mass height to avoid destabilizing locomotion.

Laser development for optimal helicopter obstacle warning system LADAR performance

NASA Astrophysics Data System (ADS)

Yaniv, A.; Krupkin, V.; Abitbol, A.; Stern, J.; Lurie, E.; German, A.; Solomonovich, S.; Lubashitz, B.; Harel, Y.; Engart, S.; Shimoni, Y.; Hezy, S.; Biltz, S.; Kaminetsky, E.; Goldberg, A.; Chocron, J.; Zuntz, N.; Zajdman, A.

2005-04-01

Low lying obstacles present immediate danger to both military and civilian helicopters performing low-altitude flight missions. A LADAR obstacle detection system is the natural solution for enhancing helicopter safety and improving the pilot situation awareness. Elop is currently developing an advanced Surveillance and Warning Obstacle Ranging and Display (SWORD) system for the Israeli Air Force. Several key factors and new concepts have contributed to system optimization. These include an adaptive FOV, data memorization, autonomous obstacle detection and warning algorithms and the use of an agile laser transmitter. In the present work we describe the laser design and performance and discuss some of the experimental results. Our eye-safe laser is characterized by its pulse energy, repetition rate and pulse length agility. By dynamically controlling these parameters, we are able to locally optimize the system"s obstacle detection range and scan density in accordance with the helicopter instantaneous maneuver.

Visually guided gait modifications for stepping over an obstacle: a bio-inspired approach.

PubMed

Silva, Pedro; Matos, Vitor; Santos, Cristina P

2014-02-01

There is an increasing interest in conceiving robotic systems that are able to move and act in an unstructured and not predefined environment, for which autonomy and adaptability are crucial features. In nature, animals are autonomous biological systems, which often serve as bio-inspiration models, not only for their physical and mechanical properties, but also their control structures that enable adaptability and autonomy-for which learning is (at least) partially responsible. This work proposes a system which seeks to enable a quadruped robot to online learn to detect and to avoid stumbling on an obstacle in its path. The detection relies in a forward internal model that estimates the robot's perceptive information by exploring the locomotion repetitive nature. The system adapts the locomotion in order to place the robot optimally before attempting to step over the obstacle, avoiding any stumbling. Locomotion adaptation is achieved by changing control parameters of a central pattern generator (CPG)-based locomotion controller. The mechanism learns the necessary alterations to the stride length in order to adapt the locomotion by changing the required CPG parameter. Both learning tasks occur online and together define a sensorimotor map, which enables the robot to learn to step over the obstacle in its path. Simulation results show the feasibility of the proposed approach.

PSD Camera Based Position and Posture Control of Redundant Robot Considering Contact Motion

NASA Astrophysics Data System (ADS)

Oda, Naoki; Kotani, Kentaro

The paper describes a position and posture controller design based on the absolute position by external PSD vision sensor for redundant robot manipulator. The redundancy enables a potential capability to avoid obstacle while continuing given end-effector jobs under contact with middle link of manipulator. Under contact motion, the deformation due to joint torsion obtained by comparing internal and external position sensor, is actively suppressed by internal/external position hybrid controller. The selection matrix of hybrid loop is given by the function of the deformation. And the detected deformation is also utilized in the compliant motion controller for passive obstacle avoidance. The validity of the proposed method is verified by several experimental results of 3link planar redundant manipulator.

Procedures for the interpretation and use of elevation scanning laser/multi-sensor data for short range hazard detection and avoidance for an autonomous planetary rover

NASA Technical Reports Server (NTRS)

Troiani, N.; Yerazunis, S. W.

1978-01-01

An autonomous roving science vehicle that relies on terrain data acquired by a hierarchy of sensors for navigation was one method of carrying out such a mission. The hierarchy of sensors included a short range sensor with sufficient resolution to detect every possible obstacle and with the ability to make fast and reliable terrain characterizations. A multilaser, multidetector triangulation system was proposed as a short range sensor. The general system was studied to determine its perception capabilities and limitations. A specific rover and low resolution sensor system was then considered. After studying the data obtained, a hazard detection algorithm was developed that accounts for all possible terrains given the sensor resolution. Computer simulation of the rover on various terrains was used to test the entire hazard detection system.

Mobile Autonomous Humanoid Assistant

NASA Technical Reports Server (NTRS)

Diftler, M. A.; Ambrose, R. O.; Tyree, K. S.; Goza, S. M.; Huber, E. L.

2004-01-01

A mobile autonomous humanoid robot is assisting human co-workers at the Johnson Space Center with tool handling tasks. This robot combines the upper body of the National Aeronautics and Space Administration (NASA)/Defense Advanced Research Projects Agency (DARPA) Robonaut system with a Segway(TradeMark) Robotic Mobility Platform yielding a dexterous, maneuverable humanoid perfect for aiding human co-workers in a range of environments. This system uses stereo vision to locate human team mates and tools and a navigation system that uses laser range and vision data to follow humans while avoiding obstacles. Tactile sensors provide information to grasping algorithms for efficient tool exchanges. The autonomous architecture utilizes these pre-programmed skills to form human assistant behaviors. The initial behavior demonstrates a robust capability to assist a human by acquiring a tool from a remotely located individual and then following the human in a cluttered environment with the tool for future use.

Error-eliminating rapid ultrasonic firing

DOEpatents

Borenstein, Johann; Koren, Yoram

1993-08-24

A system for producing reliable navigation data for a mobile vehicle, such as a robot, combines multiple range samples to increase the "confidence" of the algorithm in the existence of an obstacle. At higher vehicle speed, it is crucial to sample each sensor quickly and repeatedly to gather multiple samples in time to avoid a collision. Erroneous data is rejected by delaying the issuance of an ultrasonic energy pulse by a predetermined wait-period, which may be different during alternate ultrasonic firing cycles. Consecutive readings are compared, and the corresponding data is rejected if the readings differ by more than a predetermined amount. The rejection rate for the data is monitored and the operating speed of the navigation system is reduced if the data rejection rate is increased. This is useful to distinguish and eliminate noise from the data which truly represents the existence of an article in the field of operation of the vehicle.

Error-eliminating rapid ultrasonic firing

DOEpatents

Borenstein, J.; Koren, Y.

1993-08-24

A system for producing reliable navigation data for a mobile vehicle, such as a robot, combines multiple range samples to increase the confidence'' of the algorithm in the existence of an obstacle. At higher vehicle speed, it is crucial to sample each sensor quickly and repeatedly to gather multiple samples in time to avoid a collision. Erroneous data is rejected by delaying the issuance of an ultrasonic energy pulse by a predetermined wait-period, which may be different during alternate ultrasonic firing cycles. Consecutive readings are compared, and the corresponding data is rejected if the readings differ by more than a predetermined amount. The rejection rate for the data is monitored and the operating speed of the navigation system is reduced if the data rejection rate is increased. This is useful to distinguish and eliminate noise from the data which truly represents the existence of an article in the field of operation of the vehicle.

A Car-Steering Model Based on an Adaptive Neuro-Fuzzy Controller

NASA Astrophysics Data System (ADS)

Amor, Mohamed Anis Ben; Oda, Takeshi; Watanabe, Shigeyoshi

This paper is concerned with the development of a car-steering model for traffic simulation. Our focus in this paper is to propose a model of the steering behavior of a human driver for different driving scenarios. These scenarios are modeled in a unified framework using the idea of target position. The proposed approach deals with the driver’s approximation and decision-making mechanisms in tracking a target position by means of fuzzy set theory. The main novelty in this paper lies in the development of a learning algorithm that has the intention to imitate the driver’s self-learning from his driving experience and to mimic his maneuvers on the steering wheel, using linear networks as local approximators in the corresponding fuzzy areas. Results obtained from the simulation of an obstacle avoidance scenario show the capability of the model to carry out a human-like behavior with emphasis on learned skills.

A Trajectory Generation Approach for Payload Directed Flight

NASA Technical Reports Server (NTRS)

Ippolito, Corey A.; Yeh, Yoo-Hsiu

2009-01-01

Presently, flight systems designed to perform payload-centric maneuvers require preconstructed procedures and special hand-tuned guidance modes. To enable intelligent maneuvering via strong coupling between the goals of payload-directed flight and the autopilot functions, there exists a need to rethink traditional autopilot design and function. Research into payload directed flight examines sensor and payload-centric autopilot modes, architectures, and algorithms that provide layers of intelligent guidance, navigation and control for flight vehicles to achieve mission goals related to the payload sensors, taking into account various constraints such as the performance limitations of the aircraft, target tracking and estimation, obstacle avoidance, and constraint satisfaction. Payload directed flight requires a methodology for accurate trajectory planning that lets the system anticipate expected return from a suite of onboard sensors. This paper presents an extension to the existing techniques used in the literature to quickly and accurately plan flight trajectories that predict and optimize the expected return of onboard payload sensors.

Vision-based obstacle avoidance

DOEpatents

Galbraith, John [Los Alamos, NM

2006-07-18

A method for allowing a robot to avoid objects along a programmed path: first, a field of view for an electronic imager of the robot is established along a path where the electronic imager obtains the object location information within the field of view; second, a population coded control signal is then derived from the object location information and is transmitted to the robot; finally, the robot then responds to the control signal and avoids the detected object.

Path Planning Algorithms for the Adaptive Sensor Fleet

NASA Technical Reports Server (NTRS)

Stoneking, Eric; Hosler, Jeff

2005-01-01

The Adaptive Sensor Fleet (ASF) is a general purpose fleet management and planning system being developed by NASA in coordination with NOAA. The current mission of ASF is to provide the capability for autonomous cooperative survey and sampling of dynamic oceanographic phenomena such as current systems and algae blooms. Each ASF vessel is a software model that represents a real world platform that carries a variety of sensors. The OASIS platform will provide the first physical vessel, outfitted with the systems and payloads necessary to execute the oceanographic observations described in this paper. The ASF architecture is being designed for extensibility to accommodate heterogenous fleet elements, and is not limited to using the OASIS platform to acquire data. This paper describes the path planning algorithms developed for the acquisition phase of a typical ASF task. Given a polygonal target region to be surveyed, the region is subdivided according to the number of vessels in the fleet. The subdivision algorithm seeks a solution in which all subregions have equal area and minimum mean radius. Once the subregions are defined, a dynamic programming method is used to find a minimum-time path for each vessel from its initial position to its assigned region. This path plan includes the effects of water currents as well as avoidance of known obstacles. A fleet-level planning algorithm then shuffles the individual vessel assignments to find the overall solution which puts all vessels in their assigned regions in the minimum time. This shuffle algorithm may be described as a process of elimination on the sorted list of permutations of a cost matrix. All these path planning algorithms are facilitated by discretizing the region of interest onto a hexagonal tiling.

Collision avoidance using neural networks

NASA Astrophysics Data System (ADS)

Sugathan, Shilpa; Sowmya Shree, B. V.; Warrier, Mithila R.; Vidhyapathi, C. M.

2017-11-01

Now a days, accidents on roads are caused due to the negligence of drivers and pedestrians or due to unexpected obstacles that come into the vehicle’s path. In this paper, a model (robot) is developed to assist drivers for a smooth travel without accidents. It reacts to the real time obstacles on the four critical sides of the vehicle and takes necessary action. The sensor used for detecting the obstacle was an IR proximity sensor. A single layer perceptron neural network is used to train and test all possible combinations of sensors result by using Matlab (offline). A microcontroller (ARM Cortex-M3 LPC1768) is used to control the vehicle through the output data which is received from Matlab via serial communication. Hence, the vehicle becomes capable of reacting to any combination of real time obstacles.

Self-crowding of AMPA receptors in the excitatory postsynaptic density can effectuate anomalous receptor sub-diffusion

PubMed Central

Gupta, Rahul

2018-01-01

AMPA receptors (AMPARs) and their associations with auxiliary transmembrane proteins are bulky structures with large steric-exclusion volumes. Hence, self-crowding of AMPARs, depending on the local density, may affect their lateral diffusion in the postsynaptic membrane as well as in the highly crowded postsynaptic density (PSD) at excitatory synapses. Earlier theoretical studies considered only the roles of transmembrane obstacles and the AMPAR-binding submembranous scaffold proteins in shaping receptor diffusion within PSD. Using lattice model of diffusion, the present study investigates the additional impacts of self-crowding on the anomalousity and effective diffusion coefficient (Deff) of AMPAR diffusion. A recursive algorithm for avoiding false self-blocking during diffusion simulation is also proposed. The findings suggest that high density of AMPARs in the obstacle-free membrane itself engenders strongly anomalous diffusion and severe decline in Deff. Adding transmembrane obstacles to the membrane accentuates the anomalousity arising from self-crowding due to the reduced free diffusion space. Contrarily, enhanced AMPAR-scaffold binding, either through increase in binding strength or scaffold density or both, ameliorates the anomalousity resulting from self-crowding. However, binding has differential impacts on Deff depending on the receptor density. Increase in binding causes consistent decrease in Deff for low and moderate receptor density. For high density, binding increases Deff as long as it reduces anomalousity associated with intense self-crowding. Given a sufficiently strong binding condition when diffusion acquires normal behavior, further increase in binding causes decrease in Deff. Supporting earlier experimental observations are mentioned and implications of present findings to the experimental observations on AMPAR diffusion are also drawn. PMID:29444074

Railway obstacle detection algorithm using neural network

NASA Astrophysics Data System (ADS)

Yu, Mingyang; Yang, Peng; Wei, Sen

2018-05-01

Aiming at the difficulty of detection of obstacle in outdoor railway scene, a data-oriented method based on neural network to obtain image objects is proposed. First, we mark objects of images(such as people, trains, animals) acquired on the Internet. and then use the residual learning units to build Fast R-CNN framework. Then, the neural network is trained to get the target image characteristics by using stochastic gradient descent algorithm. Finally, a well-trained model is used to identify an outdoor railway image. if it includes trains and other objects, it will issue an alert. Experiments show that the correct rate of warning reached 94.85%.

Flight test of a low-altitude helicopter guidance system with obstacle avoidance capability

NASA Technical Reports Server (NTRS)

Zelenka, Richard E.; Clark, Raymond F.; Branigan, Robert G.

1995-01-01

Military aircraft regularly conduct missions that include low-atltitude, near-terrain flight in order to increase covertness and payload effectiveness. Civilian applications include airborne fire fighting, police surveillance, search and rescue, and helicopter emergency medical service. Several fixed-wing aircraft now employ terrain elevation maps and forward-pointed radars to achieve automated terrain following or terrain avoidance flight. Similar systems specialized to helicopters and their flight regime have not received as much attention. A helicopter guidance system relying on digitized terrain elevation maps has been developed that employs airborne navigation, mission requirements, aircraft performance limits, and radar altimeter returns to generate a valley-seeking, low-altitude trajectory between waypoints. The guidance trajectory is symbolically presented to the pilot on a helmet mounted display. This system has been flight tested to 150 ft (45.7 m) above ground level altitude at 80 kts, and is primarily limited by the ability of the pilot to perform manual detection and avoidance of unmapped hazards. In this study, a wide field of view laser radar sensor has been incorporated into this guidance system to assist the pilot in obstacle detection and avoidance, while expanding the system's operational flight envelope. The results from early flight tests of this system are presented. Low-altitude missions to 100 ft (30.5 m) altitude at 80n kts in the presence of unmapped natural and man-made obstacles were demonstrated while the pilot maintained situational awareness and tracking of the guidance trajectory. Further reductions in altitude are expected with continued flight testing.

Math Avoidance: A Barrier to American Indian Science Education and Science Careers.

ERIC Educational Resources Information Center

Green, Rayna

1978-01-01

For American Indian students, math anxiety and math avoidance are the most serious obstacles to general education and to the choice of scientific careers. Indian students interviewed generally exhibited fear and loathing of mathematics and a major lack of basic skills which were caused by a missing or negative impression of the mathematics…

U.S. Army/FRG Army Mobility Symposium Proceedings held in April 1975

DTIC Science & Technology

1975-11-01

widths, etC.--and their interactions with soil strength, tree stems of various sizes and spacings, approach angles in ditches and streams, etc. At the...provides for their specific identification and user control so that the effects of various levels of driver motivation, associated with combat or...prevailing in the areal unit (braking-visility limit). d. Maneuvering to avoid trees and/or obstacles. e. Acceleration and deceleration between obstacles

Dynamic path planning for autonomous driving on various roads with avoidance of static and moving obstacles

NASA Astrophysics Data System (ADS)

Hu, Xuemin; Chen, Long; Tang, Bo; Cao, Dongpu; He, Haibo

2018-02-01

This paper presents a real-time dynamic path planning method for autonomous driving that avoids both static and moving obstacles. The proposed path planning method determines not only an optimal path, but also the appropriate acceleration and speed for a vehicle. In this method, we first construct a center line from a set of predefined waypoints, which are usually obtained from a lane-level map. A series of path candidates are generated by the arc length and offset to the center line in the s - ρ coordinate system. Then, all of these candidates are converted into Cartesian coordinates. The optimal path is selected considering the total cost of static safety, comfortability, and dynamic safety; meanwhile, the appropriate acceleration and speed for the optimal path are also identified. Various types of roads, including single-lane roads and multi-lane roads with static and moving obstacles, are designed to test the proposed method. The simulation results demonstrate the effectiveness of the proposed method, and indicate its wide practical application to autonomous driving.

Reinforcement Learning with Autonomous Small Unmanned Aerial Vehicles in Cluttered Environments

NASA Technical Reports Server (NTRS)

Tran, Loc; Cross, Charles; Montague, Gilbert; Motter, Mark; Neilan, James; Qualls, Garry; Rothhaar, Paul; Trujillo, Anna; Allen, B. Danette

2015-01-01

We present ongoing work in the Autonomy Incubator at NASA Langley Research Center (LaRC) exploring the efficacy of a data set aggregation approach to reinforcement learning for small unmanned aerial vehicle (sUAV) flight in dense and cluttered environments with reactive obstacle avoidance. The goal is to learn an autonomous flight model using training experiences from a human piloting a sUAV around static obstacles. The training approach uses video data from a forward-facing camera that records the human pilot's flight. Various computer vision based features are extracted from the video relating to edge and gradient information. The recorded human-controlled inputs are used to train an autonomous control model that correlates the extracted feature vector to a yaw command. As part of the reinforcement learning approach, the autonomous control model is iteratively updated with feedback from a human agent who corrects undesired model output. This data driven approach to autonomous obstacle avoidance is explored for simulated forest environments furthering autonomous flight under the tree canopy research. This enables flight in previously inaccessible environments which are of interest to NASA researchers in Earth and Atmospheric sciences.

The functional subdivision of the visual brain: Is there a real illusion effect on action? A multi-lab replication study.

PubMed

Kopiske, Karl K; Bruno, Nicola; Hesse, Constanze; Schenk, Thomas; Franz, Volker H

2016-06-01

It has often been suggested that visual illusions affect perception but not actions such as grasping, as predicted by the "two-visual-systems" hypothesis of Milner and Goodale (1995, The Visual Brain in Action, Oxford University press). However, at least for the Ebbinghaus illusion, relevant studies seem to reveal a consistent illusion effect on grasping (Franz & Gegenfurtner, 2008. Grasping visual illusions: consistent data and no dissociation. Cognitive Neuropsychology). Two interpretations are possible: either grasping is not immune to illusions (arguing against dissociable processing mechanisms for vision-for-perception and vision-for-action), or some other factors modulate grasping in ways that mimic a vision-for perception effect in actions. It has been suggested that one such factor may be obstacle avoidance (Haffenden Schiff & Goodale, 2001. The dissociation between perception and action in the Ebbinghaus illusion: nonillusory effects of pictorial cues on grasp. Current Biology, 11, 177-181). In four different labs (total N = 144), we conducted an exact replication of previous studies suggesting obstacle avoidance mechanisms, implementing conditions that tested grasping as well as multiple perceptual tasks. This replication was supplemented by additional conditions to obtain more conclusive results. Our results confirm that grasping is affected by the Ebbinghaus illusion and demonstrate that this effect cannot be explained by obstacle avoidance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Research on detection method of UAV obstruction based on binocular vision

NASA Astrophysics Data System (ADS)

Zhu, Xiongwei; Lei, Xusheng; Sui, Zhehao

2018-04-01

For the autonomous obstacle positioning and ranging in the process of UAV (unmanned aerial vehicle) flight, a system based on binocular vision is constructed. A three-stage image preprocessing method is proposed to solve the problem of the noise and brightness difference in the actual captured image. The distance of the nearest obstacle is calculated by using the disparity map that generated by binocular vision. Then the contour of the obstacle is extracted by post-processing of the disparity map, and a color-based adaptive parameter adjustment algorithm is designed to extract contours of obstacle automatically. Finally, the safety distance measurement and obstacle positioning during the UAV flight process are achieved. Based on a series of tests, the error of distance measurement can keep within 2.24% of the measuring range from 5 m to 20 m.

Combined distributed and concentrated transducer network for failure indication

NASA Astrophysics Data System (ADS)

Ostachowicz, Wieslaw; Wandowski, Tomasz; Malinowski, Pawel

2010-03-01

In this paper algorithm for discontinuities localisation in thin panels made of aluminium alloy is presented. Mentioned algorithm uses Lamb wave propagation methods for discontinuities localisation. Elastic waves were generated and received using piezoelectric transducers. They were arranged in concentrated arrays distributed on the specimen surface. In this way almost whole specimen could be monitored using this combined distributed-concentrated transducer network. Excited elastic waves propagate and reflect from panel boundaries and discontinuities existing in the panel. Wave reflection were registered through the piezoelectric transducers and used in signal processing algorithm. Proposed processing algorithm consists of two parts: signal filtering and extraction of obstacles location. The first part was used in order to enhance signals by removing noise from them. Second part allowed to extract features connected with wave reflections from discontinuities. Extracted features damage influence maps were a basis to create damage influence maps. Damage maps indicated intensity of elastic wave reflections which corresponds to obstacles coordinates. Described signal processing algorithms were implemented in the MATLAB environment. It should be underlined that in this work results based only on experimental signals were presented.

Plant root and shoot dynamics during subsurface obstacle interaction

NASA Astrophysics Data System (ADS)

Conn, Nathaniel; Aguilar, Jeffrey; Benfey, Philip; Goldman, Daniel

As roots grow, they must navigate complex underground environments to anchor and retrieve water and nutrients. From gravity sensing at the root tip to pressure sensing along the tip and elongation zone, the complex mechanosensory feedback system of the root allows it to bend towards greater depths and avoid obstacles of high impedance by asymmetrically suppressing cell elongation. Here we investigate the mechanical and physiological responses of roots to rigid obstacles. We grow Maize, Zea mays, plants in quasi-2D glass containers (22cm x 17cm x 1.4cm) filled with photoelastic gel and observe that, regardless of obstacle interaction, smaller roots branch off the primary root when the upward growing shoot (which contains the first leaf) reaches an average length of 40 mm, coinciding with when the first leaf emerges. However, prior to branching, contacts with obstacles result in reduced root growth rates. The growth rate of the root relative to the shoot is sensitive to the angle of the obstacle surface, whereby the relative root growth is greatest for horizontally oriented surfaces. We posit that root growth is prioritized when horizontal obstacles are encountered to ensure anchoring and access to nutrients during later stages of development. NSF Physics of Living Systems.

Detecting Negative Obstacles by Use of Radar

NASA Technical Reports Server (NTRS)

Mittskus, Anthony; Lux, James

2006-01-01

Robotic land vehicles would be equipped with small radar systems to detect negative obstacles, according to a proposal. The term "negative obstacles" denotes holes, ditches, and any other terrain features characterized by abrupt steep downslopes that could be hazardous for vehicles. Video cameras and other optically based obstacle-avoidance sensors now installed on some robotic vehicles cannot detect obstacles under adverse lighting conditions. Even under favorable lighting conditions, they cannot detect negative obstacles. A radar system according to the proposal would be of the frequency-modulation/ continuous-wave (FM/CW) type. It would be installed on a vehicle, facing forward, possibly with a downward slant of the main lobe(s) of the radar beam(s) (see figure). It would utilize one or more wavelength(s) of the order of centimeters. Because such wavelengths are comparable to the characteristic dimensions of terrain features associated with negative hazards, a significant amount of diffraction would occur at such features. In effect, the diffraction would afford a limited ability to see corners and to see around corners. Hence, the system might utilize diffraction to detect corners associated with negative obstacles. At the time of reporting the information for this article, preliminary analyses of diffraction at simple negative obstacles had been performed, but an explicit description of how the system would utilize diffraction was not available.

Recognition of three dimensional obstacles by an edge detection scheme. [for Mars roving vehicle using laser range finder

NASA Technical Reports Server (NTRS)

Reed, M. A.

1974-01-01

The need for an obstacle detection system on the Mars roving vehicle was assumed, and a practical scheme was investigated and simulated. The principal sensing device on this vehicle was taken to be a laser range finder. Both existing and original algorithms, ending with thresholding operations, were used to obtain the outlines of obstacles from the raw data of this laser scan. A theoretical analysis was carried out to show how proper value of threshold may be chosen. Computer simulations considered various mid-range boulders, for which the scheme was quite successful. The extension to other types of obstacles, such as craters, was considered. The special problems of bottom edge detection and scanning procedure are discussed.

A biologically inspired neural net for trajectory formation and obstacle avoidance.

PubMed

Glasius, R; Komoda, A; Gielen, S C

1996-06-01

In this paper we present a biologically inspired two-layered neural network for trajectory formation and obstacle avoidance. The two topographically ordered neural maps consist of analog neurons having continuous dynamics. The first layer, the sensory map, receives sensory information and builds up an activity pattern which contains the optimal solution (i.e. shortest path without collisions) for any given set of current position, target positions and obstacle positions. Targets and obstacles are allowed to move, in which case the activity pattern in the sensory map will change accordingly. The time evolution of the neural activity in the second layer, the motor map, results in a moving cluster of activity, which can be interpreted as a population vector. Through the feedforward connections between the two layers, input of the sensory map directs the movement of the cluster along the optimal path from the current position of the cluster to the target position. The smooth trajectory is the result of the intrinsic dynamics of the network only. No supervisor is required. The output of the motor map can be used for direct control of an autonomous system in a cluttered environment or for control of the actuators of a biological limb or robot manipulator. The system is able to reach a target even in the presence of an external perturbation. Computer simulations of a point robot and a multi-joint manipulator illustrate the theory.

INL Autonomous Navigation System

DOE Office of Scientific and Technical Information (OSTI.GOV)

2005-03-30

The INL Autonomous Navigation System provides instructions for autonomously navigating a robot. The system permits high-speed autonomous navigation including obstacle avoidance, waypoing navigation and path planning in both indoor and outdoor environments.

Assisting the visually impaired: obstacle detection and warning system by acoustic feedback.

PubMed

Rodríguez, Alberto; Yebes, J Javier; Alcantarilla, Pablo F; Bergasa, Luis M; Almazán, Javier; Cela, Andrés

2012-12-17

The aim of this article is focused on the design of an obstacle detection system for assisting visually impaired people. A dense disparity map is computed from the images of a stereo camera carried by the user. By using the dense disparity map, potential obstacles can be detected in 3D in indoor and outdoor scenarios. A ground plane estimation algorithm based on RANSAC plus filtering techniques allows the robust detection of the ground in every frame. A polar grid representation is proposed to account for the potential obstacles in the scene. The design is completed with acoustic feedback to assist visually impaired users while approaching obstacles. Beep sounds with different frequencies and repetitions inform the user about the presence of obstacles. Audio bone conducting technology is employed to play these sounds without interrupting the visually impaired user from hearing other important sounds from its local environment. A user study participated by four visually impaired volunteers supports the proposed system.

Assisting the Visually Impaired: Obstacle Detection and Warning System by Acoustic Feedback

PubMed Central

Rodríguez, Alberto; Yebes, J. Javier; Alcantarilla, Pablo F.; Bergasa, Luis M.; Almazán, Javier; Cela, Andrés

2012-01-01

The aim of this article is focused on the design of an obstacle detection system for assisting visually impaired people. A dense disparity map is computed from the images of a stereo camera carried by the user. By using the dense disparity map, potential obstacles can be detected in 3D in indoor and outdoor scenarios. A ground plane estimation algorithm based on RANSAC plus filtering techniques allows the robust detection of the ground in every frame. A polar grid representation is proposed to account for the potential obstacles in the scene. The design is completed with acoustic feedback to assist visually impaired users while approaching obstacles. Beep sounds with different frequencies and repetitions inform the user about the presence of obstacles. Audio bone conducting technology is employed to play these sounds without interrupting the visually impaired user from hearing other important sounds from its local environment. A user study participated by four visually impaired volunteers supports the proposed system. PMID:23247413

Fusion of 3D laser scanner and depth images for obstacle recognition in mobile applications

NASA Astrophysics Data System (ADS)

Budzan, Sebastian; Kasprzyk, Jerzy

2016-02-01

The problem of obstacle detection and recognition or, generally, scene mapping is one of the most investigated problems in computer vision, especially in mobile applications. In this paper a fused optical system using depth information with color images gathered from the Microsoft Kinect sensor and 3D laser range scanner data is proposed for obstacle detection and ground estimation in real-time mobile systems. The algorithm consists of feature extraction in the laser range images, processing of the depth information from the Kinect sensor, fusion of the sensor information, and classification of the data into two separate categories: road and obstacle. Exemplary results are presented and it is shown that fusion of information gathered from different sources increases the effectiveness of the obstacle detection in different scenarios, and it can be used successfully for road surface mapping.

Rule-Based vs. Behavior-Based Self-Deployment for Mobile Wireless Sensor Networks

PubMed Central

Urdiales, Cristina; Aguilera, Francisco; González-Parada, Eva; Cano-García, Jose; Sandoval, Francisco

2016-01-01

In mobile wireless sensor networks (MWSN), nodes are allowed to move autonomously for deployment. This process is meant: (i) to achieve good coverage; and (ii) to distribute the communication load as homogeneously as possible. Rather than optimizing deployment, reactive algorithms are based on a set of rules or behaviors, so nodes can determine when to move. This paper presents an experimental evaluation of both reactive deployment approaches: rule-based and behavior-based ones. Specifically, we compare a backbone dispersion algorithm with a social potential fields algorithm. Most tests are done under simulation for a large number of nodes in environments with and without obstacles. Results are validated using a small robot network in the real world. Our results show that behavior-based deployment tends to provide better coverage and communication balance, especially for a large number of nodes in areas with obstacles. PMID:27399709

Robotic Follow Algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

2005-03-30

The Robotic Follow Algorithm enables allows any robotic vehicle to follow a moving target while reactively choosing a route around nearby obstacles. The robotic follow behavior can be used with different camera systems and can be used with thermal or visual tracking as well as other tracking methods such as radio frequency tags.

Survey of computer vision technology for UVA navigation

NASA Astrophysics Data System (ADS)

Xie, Bo; Fan, Xiang; Li, Sijian

2017-11-01

Navigation based on computer version technology, which has the characteristics of strong independence, high precision and is not susceptible to electrical interference, has attracted more and more attention in the filed of UAV navigation research. Early navigation project based on computer version technology mainly applied to autonomous ground robot. In recent years, the visual navigation system is widely applied to unmanned machine, deep space detector and underwater robot. That further stimulate the research of integrated navigation algorithm based on computer version technology. In China, with many types of UAV development and two lunar exploration, the three phase of the project started, there has been significant progress in the study of visual navigation. The paper expounds the development of navigation based on computer version technology in the filed of UAV navigation research and draw a conclusion that visual navigation is mainly applied to three aspects as follows.(1) Acquisition of UAV navigation parameters. The parameters, including UAV attitude, position and velocity information could be got according to the relationship between the images from sensors and carrier's attitude, the relationship between instant matching images and the reference images and the relationship between carrier's velocity and characteristics of sequential images.(2) Autonomous obstacle avoidance. There are many ways to achieve obstacle avoidance in UAV navigation. The methods based on computer version technology ,including feature matching, template matching, image frames and so on, are mainly introduced. (3) The target tracking, positioning. Using the obtained images, UAV position is calculated by using optical flow method, MeanShift algorithm, CamShift algorithm, Kalman filtering and particle filter algotithm. The paper expounds three kinds of mainstream visual system. (1) High speed visual system. It uses parallel structure, with which image detection and processing are carried out at high speed. The system is applied to rapid response system. (2) The visual system of distributed network. There are several discrete image data acquisition sensor in different locations, which transmit image data to the node processor to increase the sampling rate. (3) The visual system combined with observer. The system combines image sensors with the external observers to make up for lack of visual equipment. To some degree, these systems overcome lacks of the early visual system, including low frequency, low processing efficiency and strong noise. In the end, the difficulties of navigation based on computer version technology in practical application are briefly discussed. (1) Due to the huge workload of image operation , the real-time performance of the system is poor. (2) Due to the large environmental impact , the anti-interference ability of the system is poor.(3) Due to the ability to work in a particular environment, the system has poor adaptability.

An optimal control strategy for collision avoidance of mobile robots in non-stationary environments

NASA Technical Reports Server (NTRS)

Kyriakopoulos, K. J.; Saridis, G. N.

1991-01-01

An optimal control formulation of the problem of collision avoidance of mobile robots in environments containing moving obstacles is presented. Collision avoidance is guaranteed if the minimum distance between the robot and the objects is nonzero. A nominal trajectory is assumed to be known from off-line planning. The main idea is to change the velocity along the nominal trajectory so that collisions are avoided. Furthermore, time consistency with the nominal plan is desirable. A numerical solution of the optimization problem is obtained. Simulation results verify the value of the proposed strategy.

Visual guidance of forward flight in hummingbirds reveals control based on image features instead of pattern velocity.

PubMed

Dakin, Roslyn; Fellows, Tyee K; Altshuler, Douglas L

2016-08-02

Information about self-motion and obstacles in the environment is encoded by optic flow, the movement of images on the eye. Decades of research have revealed that flying insects control speed, altitude, and trajectory by a simple strategy of maintaining or balancing the translational velocity of images on the eyes, known as pattern velocity. It has been proposed that birds may use a similar algorithm but this hypothesis has not been tested directly. We examined the influence of pattern velocity on avian flight by manipulating the motion of patterns on the walls of a tunnel traversed by Anna's hummingbirds. Contrary to prediction, we found that lateral course control is not based on regulating nasal-to-temporal pattern velocity. Instead, birds closely monitored feature height in the vertical axis, and steered away from taller features even in the absence of nasal-to-temporal pattern velocity cues. For vertical course control, we observed that birds adjusted their flight altitude in response to upward motion of the horizontal plane, which simulates vertical descent. Collectively, our results suggest that birds avoid collisions using visual cues in the vertical axis. Specifically, we propose that birds monitor the vertical extent of features in the lateral visual field to assess distances to the side, and vertical pattern velocity to avoid collisions with the ground. These distinct strategies may derive from greater need to avoid collisions in birds, compared with small insects.

Object classification for obstacle avoidance

NASA Astrophysics Data System (ADS)

Regensburger, Uwe; Graefe, Volker

1991-03-01

Object recognition is necessary for any mobile robot operating autonomously in the real world. This paper discusses an object classifier based on a 2-D object model. Obstacle candidates are tracked and analyzed false alarms generated by the object detector are recognized and rejected. The methods have been implemented on a multi-processor system and tested in real-world experiments. They work reliably under favorable conditions but sometimes problems occur e. g. when objects contain many features (edges) or move in front of structured background.

Three Dimensional Guidance for the NPS Autonomous Underwater Vehicle

DTIC Science & Technology

1991-09-01

is loaded into a least-squares-fit algorithm to determine surfaces of polyhedrons . These computed surfaces are then compared with the known...the obstacle information stored in the vehicle’s environmental database , there is great potential of encountering unplanned for obstacles during the... database that holds current posture information recorded by the navigator. This data store receives a new current posture on each cycle of the control

Automated Guided Vehicle For Phsically Handicapped People - A Cost Effective Approach

NASA Astrophysics Data System (ADS)

Kumar, G. Arun, Dr.; Sivasubramaniam, Mr. A.

2017-12-01

Automated Guided vehicle (AGV) is like a robot that can deliver the materials from the supply area to the technician automatically. This is faster and more efficient. The robot can be accessed wirelessly. A technician can directly control the robot to deliver the components rather than control it via a human operator (over phone, computer etc. who has to program the robot or ask a delivery person to make the delivery). The vehicle is automatically guided through its ways. To avoid collisions a proximity sensor is attached to the system. The sensor senses the signals of the obstacles and can stop the vehicle in the presence of obstacles. Thus vehicle can avoid accidents that can be very useful to the present industrial trend and material handling and equipment handling will be automated and easy time saving methodology.

Formation flight and collision avoidance for multiple UAVs based on modified tentacle algorithm in unstructured environments

PubMed Central

2017-01-01

This paper presents a method for formation flight and collision avoidance of multiple UAVs. Due to the shortcomings such as collision avoidance caused by UAV’s high-speed and unstructured environments, this paper proposes a modified tentacle algorithm to ensure the high performance of collision avoidance. Different from the conventional tentacle algorithm which uses inverse derivation, the modified tentacle algorithm rapidly matches the radius of each tentacle and the steering command, ensuring that the data calculation problem in the conventional tentacle algorithm is solved. Meanwhile, both the speed sets and tentacles in one speed set are reduced and reconstructed so as to be applied to multiple UAVs. Instead of path iterative optimization, the paper selects the best tentacle to obtain the UAV collision avoidance path quickly. The simulation results show that the method presented in the paper effectively enhances the performance of flight formation and collision avoidance for multiple high-speed UAVs in unstructured environments. PMID:28763498

Development of a mobile robot for the 1995 AUVS competition

NASA Astrophysics Data System (ADS)

Matthews, Bradley O.; Ruthemeyer, Michael A.; Perdue, David; Hall, Ernest L.

1995-12-01

Automated guided vehicles (AGVs) have many potential applications in manufacturing, medicine, space and defense. The purpose of this paper is to describe exploratory research on the design of a modular autonomous mobile robot controller. The advantages of a modular system are related to portability and the fact that any vehicle can become autonomous with minimal modifications. A mobile robot test-bed has been constructed using a golf cart base. This cart has full speed control with guidance provided by a vision system and obstacle avoidance using ultrasonic sensors systems. The speed and steering control are supervised by a 486 computer through a 3-axis motion controller. The obstacle avoidance system is based on a micro-controller interfaced with six ultrasonic transducers. The is micro-controller independently handles all timing and distance calculations and sends a steering angle correction back to the computer via the serial line. This design yields a portable independent system, where even computer communication is not necessary. Vision guidance is accomplished with a CCD camera with a zoom lens. The data is collected through a commercial tracking device, communicating with the computer the X,Y coordinates of the lane marker. Testing of these systems yielded positive results by showing that at five mph the vehicle can follow a line and at the same time avoid obstacles. This design, in its modularity, creates a portable autonomous controller applicable for any mobile vehicle with only minor adaptations.

A cognitive robotic system based on the Soar cognitive architecture for mobile robot navigation, search, and mapping missions

NASA Astrophysics Data System (ADS)

Hanford, Scott D.

Most unmanned vehicles used for civilian and military applications are remotely operated or are designed for specific applications. As these vehicles are used to perform more difficult missions or a larger number of missions in remote environments, there will be a great need for these vehicles to behave intelligently and autonomously. Cognitive architectures, computer programs that define mechanisms that are important for modeling and generating domain-independent intelligent behavior, have the potential for generating intelligent and autonomous behavior in unmanned vehicles. The research described in this presentation explored the use of the Soar cognitive architecture for cognitive robotics. The Cognitive Robotic System (CRS) has been developed to integrate software systems for motor control and sensor processing with Soar for unmanned vehicle control. The CRS has been tested using two mobile robot missions: outdoor navigation and search in an indoor environment. The use of the CRS for the outdoor navigation mission demonstrated that a Soar agent could autonomously navigate to a specified location while avoiding obstacles, including cul-de-sacs, with only a minimal amount of knowledge about the environment. While most systems use information from maps or long-range perceptual capabilities to avoid cul-de-sacs, a Soar agent in the CRS was able to recognize when a simple approach to avoiding obstacles was unsuccessful and switch to a different strategy for avoiding complex obstacles. During the indoor search mission, the CRS autonomously and intelligently searches a building for an object of interest and common intersection types. While searching the building, the Soar agent builds a topological map of the environment using information about the intersections the CRS detects. The agent uses this topological model (along with Soar's reasoning, planning, and learning mechanisms) to make intelligent decisions about how to effectively search the building. Once the object of interest has been detected, the Soar agent uses the topological map to make decisions about how to efficiently return to the location where the mission began. Additionally, the CRS can send an email containing step-by-step directions using the intersections in the environment as landmarks that describe a direct path from the mission's start location to the object of interest. The CRS has displayed several characteristics of intelligent behavior, including reasoning, planning, learning, and communication of learned knowledge, while autonomously performing two missions. The CRS has also demonstrated how Soar can be integrated with common robotic motor and perceptual systems that complement the strengths of Soar for unmanned vehicles and is one of the few systems that use perceptual systems such as occupancy grid, computer vision, and fuzzy logic algorithms with cognitive architectures for robotics. The use of these perceptual systems to generate symbolic information about the environment during the indoor search mission allowed the CRS to use Soar's planning and learning mechanisms, which have rarely been used by agents to control mobile robots in real environments. Additionally, the system developed for the indoor search mission represents the first known use of a topological map with a cognitive architecture on a mobile robot. The ability to learn both a topological map and production rules allowed the Soar agent used during the indoor search mission to make intelligent decisions and behave more efficiently as it learned about its environment. While the CRS has been applied to two different missions, it has been developed with the intention that it be extended in the future so it can be used as a general system for mobile robot control. The CRS can be expanded through the addition of new sensors and sensor processing algorithms, development of Soar agents with more production rules, and the use of new architectural mechanisms in Soar.

Obstacle avoidance and concealed target detection using the Army Research Lab ultra-wideband synchronous impulse reconstruction (UWB SIRE) forward imaging radar

NASA Astrophysics Data System (ADS)

Nguyen, Lam; Wong, David; Ressler, Marc; Koenig, Francois; Stanton, Brian; Smith, Gregory; Sichina, Jeffrey; Kappra, Karl

2007-04-01

The U.S. Army Research Laboratory (ARL), as part of a mission and customer funded exploratory program, has developed a new low-frequency, ultra-wideband (UWB) synthetic aperture radar (SAR) for forward imaging to support the Army's vision of an autonomous navigation system for robotic ground vehicles. These unmanned vehicles, equipped with an array of imaging sensors, will be tasked to help detect man-made obstacles such as concealed targets, enemy minefields, and booby traps, as well as other natural obstacles such as ditches, and bodies of water. The ability of UWB radar technology to help detect concealed objects has been documented in the past and could provide an important obstacle avoidance capability for autonomous navigation systems, which would improve the speed and maneuverability of these vehicles and consequently increase the survivability of the U. S. forces on the battlefield. One of the primary features of the radar is the ability to collect and process data at combat pace in an affordable, compact, and lightweight package. To achieve this, the radar is based on the synchronous impulse reconstruction (SIRE) technique where several relatively slow and inexpensive analog-to-digital (A/D) converters are used to sample the wide bandwidth of the radar signals. We conducted an experiment this winter at Aberdeen Proving Ground (APG) to support the phenomenological studies of the backscatter from positive and negative obstacles for autonomous robotic vehicle navigation, as well as the detection of concealed targets of interest to the Army. In this paper, we briefly describe the UWB SIRE radar and the test setup in the experiment. We will also describe the signal processing and the forward imaging techniques used in the experiment. Finally, we will present imagery of man-made obstacles such as barriers, concertina wires, and mines.

Through the eyes of a bird: modelling visually guided obstacle flight

PubMed Central

Lin, Huai-Ti; Ros, Ivo G.; Biewener, Andrew A.

2014-01-01

Various flight navigation strategies for birds have been identified at the large spatial scales of migratory and homing behaviours. However, relatively little is known about close-range obstacle negotiation through cluttered environments. To examine obstacle flight guidance, we tracked pigeons (Columba livia) flying through an artificial forest of vertical poles. Interestingly, pigeons adjusted their flight path only approximately 1.5 m from the forest entry, suggesting a reactive mode of path planning. Combining flight trajectories with obstacle pole positions, we reconstructed the visual experience of the pigeons throughout obstacle flights. Assuming proportional–derivative control with a constant delay, we searched the relevant parameter space of steering gains and visuomotor delays that best explained the observed steering. We found that a pigeon's steering resembles proportional control driven by the error angle between the flight direction and the desired opening, or gap, between obstacles. Using this pigeon steering controller, we simulated obstacle flights and showed that pigeons do not simply steer to the nearest opening in the direction of flight or destination. Pigeons bias their flight direction towards larger visual gaps when making fast steering decisions. The proposed behavioural modelling method converts the obstacle avoidance behaviour into a (piecewise) target-aiming behaviour, which is better defined and understood. This study demonstrates how such an approach decomposes open-loop free-flight behaviours into components that can be independently evaluated. PMID:24812052

Through the eyes of a bird: modelling visually guided obstacle flight.

PubMed

Lin, Huai-Ti; Ros, Ivo G; Biewener, Andrew A

2014-07-06

Various flight navigation strategies for birds have been identified at the large spatial scales of migratory and homing behaviours. However, relatively little is known about close-range obstacle negotiation through cluttered environments. To examine obstacle flight guidance, we tracked pigeons (Columba livia) flying through an artificial forest of vertical poles. Interestingly, pigeons adjusted their flight path only approximately 1.5 m from the forest entry, suggesting a reactive mode of path planning. Combining flight trajectories with obstacle pole positions, we reconstructed the visual experience of the pigeons throughout obstacle flights. Assuming proportional-derivative control with a constant delay, we searched the relevant parameter space of steering gains and visuomotor delays that best explained the observed steering. We found that a pigeon's steering resembles proportional control driven by the error angle between the flight direction and the desired opening, or gap, between obstacles. Using this pigeon steering controller, we simulated obstacle flights and showed that pigeons do not simply steer to the nearest opening in the direction of flight or destination. Pigeons bias their flight direction towards larger visual gaps when making fast steering decisions. The proposed behavioural modelling method converts the obstacle avoidance behaviour into a (piecewise) target-aiming behaviour, which is better defined and understood. This study demonstrates how such an approach decomposes open-loop free-flight behaviours into components that can be independently evaluated.

A problem of optimal control and observation for distributed homogeneous multi-agent system

NASA Astrophysics Data System (ADS)

Kruglikov, Sergey V.

2017-12-01

The paper considers the implementation of a algorithm for controlling a distributed complex of several mobile multi-robots. The concept of a unified information space of the controlling system is applied. The presented information and mathematical models of participants and obstacles, as real agents, and goals and scenarios, as virtual agents, create the base forming the algorithmic and software background for computer decision support system. The controlling scheme assumes the indirect management of the robotic team on the basis of optimal control and observation problem predicting intellectual behavior in a dynamic, hostile environment. A basic content problem is a compound cargo transportation by a group of participants in the case of a distributed control scheme in the terrain with multiple obstacles.

Obstacle avoidance locomotor tasks: adaptation, memory and skill transfer.

PubMed

Kloter, Evelyne; Dietz, Volker

2012-05-01

The aim of this study was to explore the neural basis of adaptation, memory and skill transfer during human stepping over obstacles. Whilst walking on a treadmill, subjects had to perform uni- and bilateral obstacle steps. Acoustic feedback information about foot clearance was provided. Non-noxious electrical stimuli were applied to the right tibial nerve during the mid-stance phase of the right leg, i.e. 'prior' to the right or 'during' the left leg swing over the obstacle. The electromyogram (EMG) responses evoked by these stimuli in arm and leg muscles are known to reflect the neural coordination during normal and obstacle steps. The leading and trailing legs rapidly adapted foot clearance during obstacle steps with small further changes when the same obstacle condition was repeated. This adaptation was associated with a corresponding decrease in arm and leg muscle reflex EMG responses. Arm (but not leg) muscle EMG responses were greater when the stimulus was applied 'during' obstacle crossing by the left leg leading compared with stimulation 'prior' to right leg swing over the obstacle. A corresponding difference existed in arm muscle background EMG. The results indicate that, firstly, the somatosensory information gained by the performance and adaptation of uni- and bilateral obstacle stepping becomes transferred to the trailing leg in a context-specific manner. Secondly, EMG activity in arm and leg muscles parallels biomechanical adaptation of foot clearance. Thirdly, a consistently high EMG activity in the arm muscles during swing over the obstacle is required for equilibrium control. Thus, such a precision locomotor task is achieved by a context-specific, coordinated activation of arm and leg muscles for performance and equilibrium control that includes adaptation, memory and skill transfer. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Mechanical energy assessment of adult with Down syndrome during walking with obstacle avoidance.

PubMed

Salami, Firooz; Vimercati, Sara Laura; Rigoldi, Chiara; Taebi, Amirtaha; Albertini, Giorgio; Galli, Manuela

2014-08-01

The aim of this study is analyzing the differences between plane walking and stepping over an obstacle for two groups of healthy people and people with Down syndrome and then, evaluating the movement efficiency between the groups by comprising of their mechanical energy exchanges. 39 adults including two groups of 21 people with Down syndrome (age: 21.6 ± 7 years) and 18 healthy people (age: 25.1 ± 2.4 years) participated in this research. The test has been done in two conditions, first in plane walking and second in walking with an obstacle (10% of the subject's height). The gait data were acquired using quantitative movement analysis, composed of an optoelectronic system (Elite2002, BTS) with eight infrared cameras. Mechanical energy exchanges are computed by dedicated software and finally the data including spatiotemporal parameters, mechanical energy parameters and energy recovery of gait cycle are analyzed by statistical software to find significant differences. Regards to spatiotemporal parameters velocity and step length are lower in people with Down syndrome. Mechanical energy parameters particularly energy recovery does not change from healthy people to people with Down syndrome. However, there are some differences in inter-group through plane walking to obstacle avoidance and it means people with Down syndrome probably use their residual abilities in the most efficient way to achieve the main goal of an efficient energy recovery. Copyright © 2014 Elsevier Ltd. All rights reserved.

High Order Accurate Algorithms for Shocks, Rapidly Changing Solutions and Multiscale Problems

DTIC Science & Technology

2014-11-13

for front propagation with obstacles, and homotopy method for steady states. Applications include high order simulations for 3D gaseous detonations ...obstacles, and homotopy method for steady states. Applications include high order simulations for 3D gaseous detonations , sound generation study via... detonation waves, Combustion and Flame, (02 2013): 0. doi: 10.1016/j.combustflame.2012.10.002 Yang Yang, Ishani Roy, Chi-Wang Shu, Li-Zhi Fang. THE

Line following using a two camera guidance system for a mobile robot

NASA Astrophysics Data System (ADS)

Samu, Tayib; Kelkar, Nikhal; Perdue, David; Ruthemeyer, Michael A.; Matthews, Bradley O.; Hall, Ernest L.

1996-10-01

Automated unmanned guided vehicles have many potential applications in manufacturing, medicine, space and defense. A mobile robot has been designed for the 1996 Automated Unmanned Vehicle Society competition which was held in Orlando, Florida on July 15, 1996. The competition required the vehicle to follow solid and dashed lines around an approximately 800 ft. path while avoiding obstacles, overcoming terrain changes such as inclines and sand traps, and attempting to maximize speed. The purpose of this paper is to describe the algorithm developed for the line following. The line following algorithm images two windows and locates their centroid and with the knowledge that the points are on the ground plane, a mathematical and geometrical relationship between the image coordinates of the points and their corresponding ground coordinates are established. The angle of the line and minimum distance from the robot centroid are then calculated and used in the steering control. Two cameras are mounted on the robot with a camera on each side. One camera guides the robot and when it loses track of the line on its side, the robot control system automatically switches to the other camera. The test bed system has provided an educational experience for all involved and permits understanding and extending the state of the art in autonomous vehicle design.

Topological visual mapping in robotics.

PubMed

Romero, Anna; Cazorla, Miguel

2012-08-01

A key problem in robotics is the construction of a map from its environment. This map could be used in different tasks, like localization, recognition, obstacle avoidance, etc. Besides, the simultaneous location and mapping (SLAM) problem has had a lot of interest in the robotics community. This paper presents a new method for visual mapping, using topological instead of metric information. For that purpose, we propose prior image segmentation into regions in order to group the extracted invariant features in a graph so that each graph defines a single region of the image. Although others methods have been proposed for visual SLAM, our method is complete, in the sense that it makes all the process: it presents a new method for image matching; it defines a way to build the topological map; and it also defines a matching criterion for loop-closing. The matching process will take into account visual features and their structure using the graph transformation matching (GTM) algorithm, which allows us to process the matching and to remove out the outliers. Then, using this image comparison method, we propose an algorithm for constructing topological maps. During the experimentation phase, we will test the robustness of the method and its ability constructing topological maps. We have also introduced new hysteresis behavior in order to solve some problems found building the graph.

Communication Avoiding and Overlapping for Numerical Linear Algebra

DTIC Science & Technology

2012-05-08

future exascale systems, communication cost must be avoided or overlapped. Communication-avoiding 2.5D algorithms improve scalability by reducing...linear algebra problems to future exascale systems, communication cost must be avoided or overlapped. Communication-avoiding 2.5D algorithms improve...will continue to grow relative to the cost of computation. With exascale computing as the long-term goal, the community needs to develop techniques

A model of neuro-musculo-skeletal system for human locomotion under position constraint condition.

PubMed

Ni, Jiangsheng; Hiramatsu, Seiji; Kato, Atsuo

2003-08-01

The human locomotion was studied on the basis of the interaction of the musculo-skeletal system, the neural system and the environment. A mathematical model of human locomotion under position constraint condition was established. Besides the neural rhythm generator, the posture controller and the sensory system, the environment feedback controller and the stability controller were taken into account in the model. The environment feedback controller was proposed for two purposes, obstacle avoidance and target position control of the swing foot. The stability controller was proposed to imitate the self-balancing ability of a human body and improve the stability of the model. In the stability controller, the ankle torque was used to control the velocity of the body gravity center. A prediction control algorithm was applied to calculate the torque magnitude of the stability controller. As an example, human stairs climbing movement was simulated and the results were given. The simulation result proved that the mathematical modeling of the task was successful.

Learning to classify wakes from local sensory information

NASA Astrophysics Data System (ADS)

Alsalman, Mohamad; Colvert, Brendan; Kanso, Eva; Kanso Team

2017-11-01

Aquatic organisms exhibit remarkable abilities to sense local flow signals contained in their fluid environment and to surmise the origins of these flows. For example, fish can discern the information contained in various flow structures and utilize this information for obstacle avoidance and prey tracking. Flow structures created by flapping and swimming bodies are well characterized in the fluid dynamics literature; however, such characterization relies on classical methods that use an external observer to reconstruct global flow fields. The reconstructed flows, or wakes, are then classified according to the unsteady vortex patterns. Here, we propose a new approach for wake identification: we classify the wakes resulting from a flapping airfoil by applying machine learning algorithms to local flow information. In particular, we simulate the wakes of an oscillating airfoil in an incoming flow, extract the downstream vorticity information, and train a classifier to learn the different flow structures and classify new ones. This data-driven approach provides a promising framework for underwater navigation and detection in application to autonomous bio-inspired vehicles.

Development of a new integrated local trajectory planning and tracking control framework for autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Li, Xiaohui; Sun, Zhenping; Cao, Dongpu; Liu, Daxue; He, Hangen

2017-03-01

This study proposes a novel integrated local trajectory planning and tracking control (ILTPTC) framework for autonomous vehicles driving along a reference path with obstacles avoidance. For this ILTPTC framework, an efficient state-space sampling-based trajectory planning scheme is employed to smoothly follow the reference path. A model-based predictive path generation algorithm is applied to produce a set of smooth and kinematically-feasible paths connecting the initial state with the sampling terminal states. A velocity control law is then designed to assign a speed value at each of the points along the generated paths. An objective function considering both safety and comfort performance is carefully formulated for assessing the generated trajectories and selecting the optimal one. For accurately tracking the optimal trajectory while overcoming external disturbances and model uncertainties, a combined feedforward and feedback controller is developed. Both simulation analyses and vehicle testing are performed to verify the effectiveness of the proposed ILTPTC framework, and future research is also briefly discussed.

Acoustic scattering reduction using layers of elastic materials

NASA Astrophysics Data System (ADS)

Dutrion, Cécile; Simon, Frank

2017-02-01

Making an object invisible to acoustic waves could prove useful for military applications or measurements in confined space. Different passive methods have been proposed in recent years to avoid acoustic scattering from rigid obstacles. These techniques are exclusively based on acoustic phenomena, and use for instance multiple resonators or scatterers. This paper examines the possibility of designing an acoustic cloak using a bi-layer elastic cylindrical shell to eliminate the acoustic field scattered from a rigid cylinder hit by plane waves. This field depends on the dimensional and mechanical characteristics of the elastic layers. It is computed by a semi-analytical code modelling the vibrations of the coating under plane wave excitation. Optimization by genetic algorithm is performed to determine the characteristics of a bi-layer material minimizing the scattering. Considering an external fluid consisting of air, realistic configurations of elastic coatings emerge, composed of a thick internal orthotopic layer and a thin external isotropic layer. These coatings are shown to enable scattering reduction at a precise frequency or over a larger frequency band.

When an object appears unexpectedly: anticipatory movement and object circumvention in individuals with and without Developmental Coordination Disorder.

PubMed

Wilmut, K; Barnett, A L

2017-05-01

Obstacles often appear unexpectedly in our pathway and these require us to make adjustments to avoid collision. Previous research has demonstrated that healthy adults will make anticipatory adjustments to gait where they have been told there is the possibility of an obstacle appearing. One population that may find this type of anticipatory movement difficult is individuals with Developmental Coordination Disorder (DCD). The current study considered how individuals with and without DCD adjust to the possibility of an obstacle appearing which would require circumvention. Fortyfour individuals with DCD and 44 age-matched controls (aged from 7 to 34 years of age) walked down an 11 m walkway under three conditions. Initially they were told this was a clear pathway and nothing in the environment would change (1, no possibility of an obstacle, no obstacle). They then performed a series of trials in which a gate may (2, possibility of an obstacle, obstacle) or may not (3, possibility of an obstacle, no obstacle) partially obstruct their pathway. We found that all participants increased medio-lateral trunk acceleration when there was the possibility of an obstacle but before the obstacle appeared, in addition the typical adults and older children also increased step width. When describing circumvention we found that the younger children showed an increase in trunk velocity and acceleration in all three directions compared to older children and adults. We also found that the individuals with DCD adjusted their path sooner and deviated more than their peers. The degree of adjustment to step width in anticipation of an obstacle was related to later medio-lateral velocity and timing of the deviation. Therefore, the lack of 'readying' the system where there is the possibility of an obstacle appearing seen in the individuals with DCD and the younger typical children may explain the increased medio-lateral velocity seen during circumvention.

Fully automatic guidance and control for rotorcraft nap-of-the-Earth flight following planned profiles. Volume 1: Real-time piloted simulation

NASA Technical Reports Server (NTRS)

Clement, Warren F.; Gorder, Peter J.; Jewell, Wayne F.

1991-01-01

Developing a single-pilot, all-weather nap-of-the-earth (NOE) capability requires fully automatic NOE (ANOE) navigation and flight control. Innovative guidance and control concepts are investigated in a four-fold research effort that: (1) organizes the on-board computer-based storage and real-time updating of NOE terrain profiles and obstacles in course-oriented coordinates indexed to the mission flight plan; (2) defines a class of automatic anticipative pursuit guidance algorithms and necessary data preview requirements to follow the vertical, lateral, and longitudinal guidance commands dictated by the updated flight profiles; (3) automates a decision-making process for unexpected obstacle avoidance; and (4) provides several rapid response maneuvers. Acquired knowledge from the sensed environment is correlated with the forehand knowledge of the recorded environment (terrain, cultural features, threats, and targets), which is then used to determine an appropriate evasive maneuver if a nonconformity of the sensed and recorded environments is observed. This four-fold research effort was evaluated in both fixed-based and moving-based real-time piloted simulations, thereby, providing a practical demonstration for evaluating pilot acceptance of the automated concepts, supervisory override, manual operation, and re-engagement of the automatic system. Volume one describes the major components of the guidance and control laws as well as the results of the piloted simulations. Volume two describes the complete mathematical model of the fully automatic guidance system for rotorcraft NOE flight following planned flight profiles.

Fully Automatic Guidance and Control for Rotorcraft Nap-of-the-earth Flight Following Planned Profiles. Volume 2: Mathematical Model

NASA Technical Reports Server (NTRS)

Clement, Warren F.; Gorder, Peter J.; Jewell, Wayne F.

1991-01-01

Developing a single-pilot, all-weather nap-of-the-earth (NOE) capability requires fully automatic NOE (ANOE) navigation and flight control. Innovative guidance and control concepts are investigated in a four-fold research effort that: (1) organizes the on-board computer-based storage and real-time updating of NOE terrain profiles and obstacles in course-oriented coordinates indexed to the mission flight plan; (2) defines a class of automatic anticipative pursuit guidance algorithms and necessary data preview requirements to follow the vertical, lateral, and longitudinal guidance commands dictated by the updated flight profiles; (3) automates a decision-making process for unexpected obstacle avoidance; and (4) provides several rapid response maneuvers. Acquired knowledge from the sensed environment is correlated with the forehand knowledge of the recorded environment (terrain, cultural features, threats, and targets), which is then used to determine an appropriate evasive maneuver if a nonconformity of the sensed and recorded environments is observed. This four-fold research effort was evaluated in both fixed-base and moving-base real-time piloted simulations; thereby, providing a practical demonstration for evaluating pilot acceptance of the automated concepts, supervisory override, manual operation, and re-engagement of the automatic system. Volume one describes the major components of the guidance and control laws as well as the results of the piloted simulations. Volume two describes the complete mathematical model of the fully automatic guidance system for rotorcraft NOE flight following planned flight profiles.

Proceedings of the Image Understanding Workshop (18th) Held in Cambridge, Massachusetts on 6-8 April 1988. Volume 2

DTIC Science & Technology

1988-04-01

solution to a information. There is thus a biological motivation for investi- specific problem, e.g., solving the visual obstacle avoidance gating the...narticular practically motivated aspect of the image, known as the optical flow, does not necessarily the general problem. correspond to the 2-D motion...on (Z Z * "inexact" vision jThom8fi] The obvious motivation stems from a = X tancosa b - Z tan3sina; (1) the fact that an obstacle in relative motion

Does physical exercise improve obstacle negotiation in the elderly? A systematic review.

PubMed

Guadagnin, Eliane C; da Rocha, Emmanuel S; Duysens, Jacques; Carpes, Felipe P

2016-01-01

Physical exercise improves walking in the elderly but much less is known about its effect on more challenged gait, such as obstacle negotiation. We conducted a systematic review to discuss the effects of regular physical exercise on kinematics and kinetics of obstacle negotiation in the elderly. A comprehensive literature search revealed 859 citations for review, whereof 206 studies entered the full-text analysis. After application of inclusion and exclusion criteria, 13 studies were included in this systematic review. Most of them presented a reasonable quality (average 0.68) but none of them reached the level of a randomized control trial. Interventions were heterogeneous, with training periods lasting from 5 days to 10 months. Studies assessed obstacle negotiation basically considering 3 types of testing paradigm, namely a walkway with either a single obstacle crossing, or with multiple obstacles, or else a treadmill with an obstacle avoidance task under time pressure. In general, longer training programs had better results and very short ones were not effective. A weekly frequency of 2-3 times was the most common among the studies showing positive effects. Regardless of exercises types performed, most of them were effective and so far, there is no consensus about the best exercise for improving obstacle negotiation. A lack of studies on this topic still is evident. Including a record of fall score can further help in deciding which programs are to be preferred. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Brain activation related to the perception of minimal agency cues: the role of the mirror system.

PubMed

Stosic, Marina; Brass, Marcel; Van Hoeck, Nicole; Ma, Ning; Van Overwalle, Frank

2014-02-01

Recent fMRI studies indicate that the posterior superior temporal sulcus (pSTS) and the mirror system are involved in analyzing goal-directed actions performed by non-human objects. However, these studies have some limitations: the animations showed moving shapes that resemble humans and human movement, or showed the interaction of two moving shapes rather than one alone. This may have prompted participants to assume a human agent instead of an object. To avoid this potential confound, in this study, animations showed a small circular shape (agent) jumping toward a bigger circular shape (goal) with an obstacle separating them. We manipulated agency of the small circular shape by showing its movements as self-propelled (Agent condition) or as launched by a lever mechanism (Non-agent condition). The small shape succeeded in avoiding an obstacle and reaching the goal object or failed to do so. Our results showed that goal-directed actions performed by an agentic shape recruited the mirror system (the inferior parietal lobe and the premotor cortex) in comparison with shapes that were launched. Success or failure to avoid the obstacle had no effect on these areas. These results complement and further extend previous findings indicating that the mirror system does not appear to be selective for biological actions and their goals, nor does it require the presence of a human, human body parts or human-made objects. Instead, it seems to play a general role in representing goal-directed actions of agents regardless of their form. © 2013.

Dynamic Behavior Sequencing in a Hybrid Robot Architecture

DTIC Science & Technology

2008-03-01

107 Appendix A. Implemented Behavior Representations . . . . . . . . . . 109 Appendix B . Example Behavior...114 A.12 Implemented Behavior wander . . . . . . . . . . . . . . . . . . . . 115 B .1 Example Behavior avoid-obstacle...116 B .2 Example Behavior deliver-object . . . . . . . . . . . . . . . . . 117 B .3 Example Behavior get-object

Obstacle crossing with dual tasking is a danger for individuals with Alzheimer's disease and for healthy older people.

PubMed

Simieli, Lucas; Barbieri, Fabio Augusto; Orcioli-Silva, Diego; Lirani-Silva, Ellen; Stella, Florindo; Gobbi, Lilian Teresa Bucken

2015-01-01

The aim of this study was to analyze the effects of dual tasking on obstacle crossing during walking by individuals with Alzheimer's disease (AD) and by healthy older people. Thirty four elderly individuals (16 healthy subjects and 18 individuals with AD) were recruited to participate in this study. Three AD individuals and one control participant were excluded due to exclusion criteria. The participants were instructed to walk barefoot at their own speed along an 8 m long pathway. Each participant performed five trials for each condition (unobstructed walking, unobstructed walking with dual tasking, and obstacle crossing during walking with dual tasking). The trials were completely randomized for each participant. The mid-pathway stride was measured in the unobstructed walking trials and the stride that occurred during the obstacle avoidance was measured in the trials that involved obstacle crossing. The behavior of the healthy elderly subjects and individuals with AD was similar for obstacle crossing during walking with dual tasking. Both groups used the "posture first" strategy to prioritize stability and showed decreased attention to executive tasking while walking. Additionally, AD had a strong influence on the modifications that are made by the elderly while walking under different walking conditions.

Bim-Based Indoor Path Planning Considering Obstacles

NASA Astrophysics Data System (ADS)

Xu, M.; Wei, S.; Zlatanova, S.; Zhang, R.

2017-09-01

At present, 87 % of people's activities are in indoor environment; indoor navigation has become a research issue. As the building structures for people's daily life are more and more complex, many obstacles influence humans' moving. Therefore it is essential to provide an accurate and efficient indoor path planning. Nowadays there are many challenges and problems in indoor navigation. Most existing path planning approaches are based on 2D plans, pay more attention to the geometric configuration of indoor space, often ignore rich semantic information of building components, and mostly consider simple indoor layout without taking into account the furniture. Addressing the above shortcomings, this paper uses BIM (IFC) as the input data and concentrates on indoor navigation considering obstacles in the multi-floor buildings. After geometric and semantic information are extracted, 2D and 3D space subdivision methods are adopted to build the indoor navigation network and to realize a path planning that avoids obstacles. The 3D space subdivision is based on triangular prism. The two approaches are verified by the experiments.

Detection of obstacles on runway using Ego-Motion compensation and tracking of significant features

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar (Principal Investigator); Camps, Octavia (Principal Investigator); Gandhi, Tarak; Devadiga, Sadashiva

1996-01-01

This report describes a method for obstacle detection on a runway for autonomous navigation and landing of an aircraft. Detection is done in the presence of extraneous features such as tiremarks. Suitable features are extracted from the image and warping using approximately known camera and plane parameters is performed in order to compensate ego-motion as far as possible. Residual disparity after warping is estimated using an optical flow algorithm. Features are tracked from frame to frame so as to obtain more reliable estimates of their motion. Corrections are made to motion parameters with the residual disparities using a robust method, and features having large residual disparities are signaled as obstacles. Sensitivity analysis of the procedure is also studied. Nelson's optical flow constraint is proposed to separate moving obstacles from stationary ones. A Bayesian framework is used at every stage so that the confidence in the estimates can be determined.

The attribution of navigational- and goal-directed agency in dogs (Canis familiaris) and human toddlers (Homo sapiens).

PubMed

Tauzin, Tibor; Csík, Andor; Lovas, Kata; Gergely, György; Topál, József

2017-02-01

Both human infants and nonhuman primates can recognize unfamiliar entities as instrumental agents ascribing to them goals and efficiency of goal-pursuit. This competence relies on movement cues indicating distal sensitivity to the environment and choice of efficient goal-approach. Although dogs' evolved sensitivity to social cues allow them to recognize humans as communicative agents, it remains unclear whether they have also evolved a basic concept of instrumental agency. We used a preferential object-choice procedure to test whether adult pet dogs and human toddlers can identify unfamiliar entities as agents based on different types of movement cues that specify different levels of agency. In the navigational agency condition, dogs preferentially chose an object that modified its pathway to avoid collision with obstacles over another object showing no evidence of distal sensitivity (regularly bumping into obstacles). However, in the goal-efficiency condition where neither object collided with obstacles as it navigated toward a distal target, but only 1 of them exhibited efficient goal-approach as well, toddlers, but not dogs, showed a preference toward the efficient goal-directed agent. These findings indicate that dogs possess a limited concept of environmentally sensitive navigational agency that they attribute to self-propelled entities capable of modifying their movement to avoid colliding with obstacles. Toddlers, in contrast, demonstrated clear sensitivity to cues of efficient variability of goal-approach as the basis for differentiating, attributing, and showing preference for goal-directed instrumental agency. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Biosonar navigation above water II: exploiting mirror images.

PubMed

Genzel, Daria; Hoffmann, Susanne; Prosch, Selina; Firzlaff, Uwe; Wiegrebe, Lutz

2015-02-15

As in vision, acoustic signals can be reflected by a smooth surface creating an acoustic mirror image. Water bodies represent the only naturally occurring horizontal and acoustically smooth surfaces. Echolocating bats flying over smooth water bodies encounter echo-acoustic mirror images of objects above the surface. Here, we combined an electrophysiological approach with a behavioral experimental paradigm to investigate whether bats can exploit echo-acoustic mirror images for navigation and how these mirrorlike echo-acoustic cues are encoded in their auditory cortex. In an obstacle-avoidance task where the obstacles could only be detected via their echo-acoustic mirror images, most bats spontaneously exploited these cues for navigation. Sonar ensonifications along the bats' flight path revealed conspicuous changes of the reflection patterns with slightly increased target strengths at relatively long echo delays corresponding to the longer acoustic paths from the mirrored obstacles. Recordings of cortical spatiotemporal response maps (STRMs) describe the tuning of a unit across the dimensions of elevation and time. The majority of cortical single and multiunits showed a special spatiotemporal pattern of excitatory areas in their STRM indicating a preference for echoes with (relative to the setup dimensions) long delays and, interestingly, from low elevations. This neural preference could effectively encode a reflection pattern as it would be perceived by an echolocating bat detecting an object mirrored from below. The current study provides both behavioral and neurophysiological evidence that echo-acoustic mirror images can be exploited by bats for obstacle avoidance. This capability effectively supports echo-acoustic navigation in highly cluttered natural habitats. Copyright © 2015 the American Physiological Society.

Orthogonal on-off control of radar pulses for the suppression of mutual interference

NASA Astrophysics Data System (ADS)

Kim, Yong Cheol

1998-10-01

Intelligent vehicles of the future will be guided by radars and other sensors to avoid obstacles. When multiple vehicles move simultaneously in autonomous navigational mode, mutual interference among car radars becomes a serious problem. An obstacle is illuminated with electromagnetic pulses from several radars. The signal at a radar receiver is actually a mixture of the self-reflection and the reflection of interfering pulses emitted by others. When standardized pulse- type radars are employed on vehicles for obstacle avoidance and so self-pulse and interfering pulses have identical pulse repetition interval, this SI (synchronous Interference) is very difficult to separate from the true reflection. We present a method of suppressing such a synchronous interference. By controlling the pulse emission of a radar in a binary orthogonal ON, OFF pattern, the true self-reflection can be separated from the false one. Two range maps are generated, TRM (true-reflection map) and SIM (synchronous- interference map). TRM is updated for every ON interval and SIM is updated for every OFF interval of the self-radar. SIM represents the SI of interfering radars while TRM keeps a record of a mixture of the true self-reflection and SI. Hence the true obstacles can be identified by the set subtraction operation. The performance of the proposed method is compared with that of the conventional M of N method. Bayesian analysis shows that the probability of false alarm is improved by order of 103 to approximately 106 while the deterioration in the probability of detection is negligible.

Automated Escape Guidance Algorithms for An Escape Vehicle

NASA Technical Reports Server (NTRS)

Flanary, Ronald; Hammen, David; Ito, Daigoro; Rabalais, Bruce; Rishikof, Brian; Siebold, Karl

2002-01-01

An escape vehicle was designed to provide an emergency evacuation for crew members living on a space station. For maximum escape capability, the escape vehicle needs to have the ability to safely evacuate a station in a contingency scenario such as an uncontrolled (e.g., tumbling) station. This emergency escape sequence will typically be divided into three events: The fust separation event (SEP1), the navigation reconstruction event, and the second separation event (SEP2). SEP1 is responsible for taking the spacecraft from its docking port to a distance greater than the maximum radius of the rotating station. The navigation reconstruction event takes place prior to the SEP2 event and establishes the orbital state to within the tolerance limits necessary for SEP2. The SEP2 event calculates and performs an avoidance burn to prevent station recontact during the next several orbits. This paper presents the tools and results for the whole separation sequence with an emphasis on the two separation events. The fust challenge includes collision avoidance during the escape sequence while the station is in an uncontrolled rotational state, with rotation rates of up to 2 degrees per second. The task of avoiding a collision may require the use of the Vehicle's de-orbit propulsion system for maximum thrust and minimum dwell time within the vicinity of the station vicinity. The thrust of the propulsion system is in a single direction, and can be controlled only by the attitude of the spacecraft. Escape algorithms based on a look-up table or analytical guidance can be implemented since the rotation rate and the angular momentum vector can be sensed onboard and a-priori knowledge of the position and relative orientation are available. In addition, crew intervention has been provided for in the event of unforeseen obstacles in the escape path. The purpose of the SEP2 burn is to avoid re-contact with the station over an extended period of time. Performing this maneuver properly requires knowledge of the orbital state, which is obtained during the navigation state reconstruction event. Since the direction of the delta-v of the SEPI maneuver is a random variable with respect to the Local Vertical Local Horizontal (LVLH) coordinate system, calculating the required SEP2 burn is a challenge. This problem was solved using a neural network as a model-free function approximation technique.

Effects of aging on whole body and segmental control while obstacle crossing under impaired sensory conditions.

PubMed

Novak, Alison C; Deshpande, Nandini

2014-06-01

The ability to safely negotiate obstacles is an important component of independent mobility, requiring adaptive locomotor responses to maintain dynamic balance. This study examined the effects of aging and visual-vestibular interactions on whole-body and segmental control during obstacle crossing. Twelve young and 15 older adults walked along a straight pathway and stepped over one obstacle placed in their path. The task was completed under 4 conditions which included intact or blurred vision, and intact or perturbed vestibular information using galvanic vestibular stimulation (GVS). Global task performance significantly increased under suboptimal vision conditions. Vision also significantly influenced medial-lateral center of mass displacement, irrespective of age and GVS. Older adults demonstrated significantly greater trunk pitch and head roll angles under suboptimal vision conditions. Similar to whole-body control, no GVS effect was found for any measures of segmental control. The results indicate a significant reliance on visual but not vestibular information for locomotor control during obstacle crossing. The lack of differences in GVS effects suggests that vestibular information is not up-regulated for obstacle avoidance. This is not differentially affected by aging. In older adults, insufficient visual input appears to affect ability to minimize anterior-posterior trunk movement despite a slower obstacle crossing time and walking speed. Combined with larger medial-lateral deviation of the body COM with insufficient visual information, the older adults may be at a greater risk for imbalance or inability to recover from a possible trip when stepping over an obstacle. Copyright © 2014 Elsevier B.V. All rights reserved.

Do characteristics of a stationary obstacle lead to adjustments in obstacle stepping strategies?

PubMed

Worden, Timothy A; De Jong, Audrey F; Vallis, Lori Ann

2016-01-01

Navigating cluttered and complex environments increases the risk of falling. To decrease this risk, it is important to understand the influence of obstacle visual cues on stepping parameters, however the specific obstacle characteristics that have the greatest influence on avoidance strategies is still under debate. The purpose of the current work is to provide further insight on the relationship between obstacle appearance in the environment and modulation of stepping parameters. Healthy young adults (N=8) first stepped over an obstacle with one visible top edge ("floating"; 8 trials) followed by trials where experimenters randomly altered the location of a ground reference object to one of 7 different positions (8 trials per location), which ranged from 6cm in front of, directly under, or up to 6cm behind the floating obstacle (at 2cm intervals). Mean take-off and landing distance as well as minimum foot clearance values were unchanged across different positions of the ground reference object; a consistent stepping trajectory was observed for all experimental conditions. Contrary to our hypotheses, results of this study indicate that ground based visual cues are not essential for the planning of stepping and clearance strategies. The simultaneous presentation of both floating and ground based objects may have provided critical information that lead to the adoption of a consistent strategy for clearing the top edge of the obstacle. The invariant foot placement observed here may be an appropriate stepping strategy for young adults, however this may not be the case across the lifespan or in special populations. Copyright © 2015 Elsevier B.V. All rights reserved.

Mobile robot dynamic path planning based on improved genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

In dynamic unknown environment, the dynamic path planning of mobile robots is a difficult problem. In this paper, a dynamic path planning method based on genetic algorithm is proposed, and a reward value model is designed to estimate the probability of dynamic obstacles on the path, and the reward value function is applied to the genetic algorithm. Unique coding techniques reduce the computational complexity of the algorithm. The fitness function of the genetic algorithm fully considers three factors: the security of the path, the shortest distance of the path and the reward value of the path. The simulation results show that the proposed genetic algorithm is efficient in all kinds of complex dynamic environments.

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot.

PubMed

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.

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

PubMed Central

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

Nature-Inspired Acoustic Sensor Projects

DTIC Science & Technology

1999-08-24

m). The pager motors are worn on the wrists. Yale Intelligent Sensors Lab 8 Autonomous vehicle navigation Yago – Yale Autonomous Go-Cart Yago is used...proximity sensor determined the presence of close-by objects missed by the sonars. Yago operated autonomously by avoiding obstacles. Problems being

Three-dimensional landing zone ladar

NASA Astrophysics Data System (ADS)

Savage, James; Goodrich, Shawn; Burns, H. N.

2016-05-01

Three-Dimensional Landing Zone (3D-LZ) refers to a series of Air Force Research Laboratory (AFRL) programs to develop high-resolution, imaging ladar to address helicopter approach and landing in degraded visual environments with emphasis on brownout; cable warning and obstacle avoidance; and controlled flight into terrain. Initial efforts adapted ladar systems built for munition seekers, and success led to a the 3D-LZ Joint Capability Technology Demonstration (JCTD) , a 27-month program to develop and demonstrate a ladar subsystem that could be housed with the AN/AAQ-29 FLIR turret flown on US Air Force Combat Search and Rescue (CSAR) HH-60G Pave Hawk helicopters. Following the JCTD flight demonstration, further development focused on reducing size, weight, and power while continuing to refine the real-time geo-referencing, dust rejection, obstacle and cable avoidance, and Helicopter Terrain Awareness and Warning (HTAWS) capability demonstrated under the JCTD. This paper summarizes significant ladar technology development milestones to date, individual LADAR technologies within 3D-LZ, and results of the flight testing.

Fuzzy logic control of telerobot manipulators

NASA Technical Reports Server (NTRS)

Franke, Ernest A.; Nedungadi, Ashok

1992-01-01

Telerobot systems for advanced applications will require manipulators with redundant 'degrees of freedom' (DOF) that are capable of adapting manipulator configurations to avoid obstacles while achieving the user specified goal. Conventional methods for control of manipulators (based on solution of the inverse kinematics) cannot be easily extended to these situations. Fuzzy logic control offers a possible solution to these needs. A current research program at SRI developed a fuzzy logic controller for a redundant, 4 DOF, planar manipulator. The manipulator end point trajectory can be specified by either a computer program (robot mode) or by manual input (teleoperator). The approach used expresses end-point error and the location of manipulator joints as fuzzy variables. Joint motions are determined by a fuzzy rule set without requiring solution of the inverse kinematics. Additional rules for sensor data, obstacle avoidance and preferred manipulator configuration, e.g., 'righty' or 'lefty', are easily accommodated. The procedure used to generate the fuzzy rules can be extended to higher DOF systems.

Methods for predicting unsteady takeoff and landing trajectories of the aircraft

NASA Astrophysics Data System (ADS)

Shevchenko, A.; Pavlov, B.; Nachinkina, G.

2017-01-01

Informational and situational awareness of the aircrew greatly affects the probability of accidents, during takeoff and landing in particular. For the purpose of assessing the current and predicting the future states of an aircraft the energy approach to the flight control is used. Key energy balance equation is generalized to the ground phases. The equation describes the process of accumulating of the total energy of the aircraft along the entire trajectory, including the segment ahead. This segment length is defined by the required terminal energy state. For the takeoff phase the predict algorithm calculates the aircraft position on a runway after which it is possible to accelerate up to the speed of steady level flight and to reach the altitude sufficient for overcoming the high-rise obstacles. For the landing phase the braking distance length is determined. For increasing the likelihood of predicting the correction of the algorithm is introduced. The results of modeling many takeoffs and landings of passenger liner with different weights with the ahead obstacle and the engine failure are given. Working availability of the algorithm correction is shown.

Using probabilistic model as feature descriptor on a smartphone device for autonomous navigation of unmanned ground vehicles

NASA Astrophysics Data System (ADS)

Desai, Alok; Lee, Dah-Jye

2013-12-01

There has been significant research on the development of feature descriptors in the past few years. Most of them do not emphasize real-time applications. This paper presents the development of an affine invariant feature descriptor for low resource applications such as UAV and UGV that are equipped with an embedded system with a small microprocessor, a field programmable gate array (FPGA), or a smart phone device. UAV and UGV have proven suitable for many promising applications such as unknown environment exploration, search and rescue operations. These applications required on board image processing for obstacle detection, avoidance and navigation. All these real-time vision applications require a camera to grab images and match features using a feature descriptor. A good feature descriptor will uniquely describe a feature point thus allowing it to be correctly identified and matched with its corresponding feature point in another image. A few feature description algorithms are available for a resource limited system. They either require too much of the device's resource or too much simplification on the algorithm, which results in reduction in performance. This research is aimed at meeting the needs of these systems without sacrificing accuracy. This paper introduces a new feature descriptor called PRObabilistic model (PRO) for UGV navigation applications. It is a compact and efficient binary descriptor that is hardware-friendly and easy for implementation.

Optimal motion planning for collision avoidance of mobile robots in non-stationary environments

NASA Technical Reports Server (NTRS)

Kyriakopoulos, K. J.; Saridis, G. N.

1992-01-01

An optimal control formulation of the problem of collision avoidance of mobile robots moving in general terrains containing moving obstacles is presented. A dynamic model of the mobile robot and the dynamic constraints are derived. Collision avoidance is guaranteed if the minimum distance between the robot and the object is nonzero. A nominal trajectory is assumed to be known from off-line planning. The main idea is to change the velocity along the nominal trajectory so that collisions are avoided. Time consistency with the nominal plan is desirable. A numerical solution of the optimization problem is obtained. A perturbation control type of approach is used to update the optimal plan. Simulation results verify the value of the proposed strategy.

How do walkers avoid a mobile robot crossing their way?

PubMed

Vassallo, Christian; Olivier, Anne-Hélène; Souères, Philippe; Crétual, Armel; Stasse, Olivier; Pettré, Julien

2017-01-01

Robots and Humans have to share the same environment more and more often. In the aim of steering robots in a safe and convenient manner among humans it is required to understand how humans interact with them. This work focuses on collision avoidance between a human and a robot during locomotion. Having in mind previous results on human obstacle avoidance, as well as the description of the main principles which guide collision avoidance strategies, we observe how humans adapt a goal-directed locomotion task when they have to interfere with a mobile robot. Our results show differences in the strategy set by humans to avoid a robot in comparison with avoiding another human. Humans prefer to give the way to the robot even when they are likely to pass first at the beginning of the interaction. Copyright © 2016 Elsevier B.V. All rights reserved.

Apparent motion perception in lower limb amputees with phantom sensations: "obstacle shunning" and "obstacle tolerance".

PubMed

Saetta, Gianluca; Grond, Ilva; Brugger, Peter; Lenggenhager, Bigna; Tsay, Anthony J; Giummarra, Melita J

2018-03-21

Phantom limbs are the phenomenal persistence of postural and sensorimotor features of an amputated limb. Although immaterial, their characteristics can be modulated by the presence of physical matter. For instance, the phantom may disappear when its phenomenal space is invaded by objects ("obstacle shunning"). Alternatively, "obstacle tolerance" occurs when the phantom is not limited by the law of impenetrability and co-exists with physical objects. Here we examined the link between this under-investigated aspect of phantom limbs and apparent motion perception. The illusion of apparent motion of human limbs involves the perception that a limb moves through or around an object, depending on the stimulus onset asynchrony (SOA) for the two images. Participants included 12 unilateral lower limb amputees matched for obstacle shunning (n = 6) and obstacle tolerance (n = 6) experiences, and 14 non-amputees. Using multilevel linear models, we replicated robust biases for short perceived trajectories for short SOA (moving through the object), and long trajectories (circumventing the object) for long SOAs in both groups. Importantly, however, amputees with obstacle shunning perceived leg stimuli to predominantly move through the object, whereas amputees with obstacle tolerance perceived leg stimuli to predominantly move around the object. That is, in people who experience obstacle shunning, apparent motion perception of lower limbs was not constrained to the laws of impenetrability (as the phantom disappears when invaded by objects), and legs can therefore move through physical objects. Amputees who experience obstacle tolerance, however, had stronger solidity constraints for lower limb apparent motion, perhaps because they must avoid co-location of the phantom with physical objects. Phantom limb experience does, therefore, appear to be modulated by intuitive physics, but not in the same way for everyone. This may have important implications for limb experience post-amputation (e.g., improving prosthesis embodiment when limb representation is constrained by the same limits as an intact limb). Copyright © 2018 Elsevier Ltd. All rights reserved.

Reactive Collision Avoidance Algorithm

NASA Technical Reports Server (NTRS)

Scharf, Daniel; Acikmese, Behcet; Ploen, Scott; Hadaegh, Fred

2010-01-01

The reactive collision avoidance (RCA) algorithm allows a spacecraft to find a fuel-optimal trajectory for avoiding an arbitrary number of colliding spacecraft in real time while accounting for acceleration limits. In addition to spacecraft, the technology can be used for vehicles that can accelerate in any direction, such as helicopters and submersibles. In contrast to existing, passive algorithms that simultaneously design trajectories for a cluster of vehicles working to achieve a common goal, RCA is implemented onboard spacecraft only when an imminent collision is detected, and then plans a collision avoidance maneuver for only that host vehicle, thus preventing a collision in an off-nominal situation for which passive algorithms cannot. An example scenario for such a situation might be when a spacecraft in the cluster is approaching another one, but enters safe mode and begins to drift. Functionally, the RCA detects colliding spacecraft, plans an evasion trajectory by solving the Evasion Trajectory Problem (ETP), and then recovers after the collision is avoided. A direct optimization approach was used to develop the algorithm so it can run in real time. In this innovation, a parameterized class of avoidance trajectories is specified, and then the optimal trajectory is found by searching over the parameters. The class of trajectories is selected as bang-off-bang as motivated by optimal control theory. That is, an avoiding spacecraft first applies full acceleration in a constant direction, then coasts, and finally applies full acceleration to stop. The parameter optimization problem can be solved offline and stored as a look-up table of values. Using a look-up table allows the algorithm to run in real time. Given a colliding spacecraft, the properties of the collision geometry serve as indices of the look-up table that gives the optimal trajectory. For multiple colliding spacecraft, the set of trajectories that avoid all spacecraft is rapidly searched on-line. The optimal avoidance trajectory is implemented as a receding-horizon model predictive control law. Therefore, at each time step, the optimal avoidance trajectory is found and the first time step of its acceleration is applied. At the next time step of the control computer, the problem is re-solved and the new first time step is again applied. This continual updating allows the RCA algorithm to adapt to a colliding spacecraft that is making erratic course changes.

An Obstacle-Tolerant Path Planning Algorithm for Mobile-Anchor-Node-Assisted Localization

PubMed Central

Tsai, Rong-Guei

2018-01-01

The location information obtained using a sensor is a critical requirement in wireless sensor networks. Numerous localization schemes have been proposed, among which mobile-anchor-node-assisted localization (MANAL) can reduce costs and overcome environmental constraints. A mobile anchor node (MAN) provides its own location information to assist the localization of sensor nodes. Numerous path planning schemes have been proposed for MANAL, but most scenarios assume the absence of obstacles in the environment. However, in a realistic environment, sensor nodes cannot be located because the obstacles block the path traversed by the MAN, thereby rendering the sensor incapable of receiving sufficient three location information from the MAN. This study proposes the obstacle-tolerant path planning (OTPP) approach to solve the sensor location problem owing to obstacle blockage. OTPP can approximate the optimum beacon point number and path planning, thereby ensuring that all the unknown nodes can receive the three location information from the MAN and reduce the number of MAN broadcast packet times. Experimental results demonstrate that OTPP performs better than Z-curves because it reduces the total number of beacon points utilized and is thus more suitable in an obstacle-present environment. Compared to the Z-curve, OTPP can reduce localization error and improve localization coverage. PMID:29547582

47 CFR 87.483 - Audio visual warning systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 47 Telecommunication 5 2014-10-01 2014-10-01 false Audio visual warning systems. 87.483 Section 87... AVIATION SERVICES Stations in the Radiodetermination Service § 87.483 Audio visual warning systems. An audio visual warning system (AVWS) is a radar-based obstacle avoidance system. AVWS activates...

Integrating Millimeter Wave Radar with a Monocular Vision Sensor for On-Road Obstacle Detection Applications

PubMed Central

Wang, Tao; Zheng, Nanning; Xin, Jingmin; Ma, Zheng

2011-01-01

This paper presents a systematic scheme for fusing millimeter wave (MMW) radar and a monocular vision sensor for on-road obstacle detection. As a whole, a three-level fusion strategy based on visual attention mechanism and driver’s visual consciousness is provided for MMW radar and monocular vision fusion so as to obtain better comprehensive performance. Then an experimental method for radar-vision point alignment for easy operation with no reflection intensity of radar and special tool requirements is put forward. Furthermore, a region searching approach for potential target detection is derived in order to decrease the image processing time. An adaptive thresholding algorithm based on a new understanding of shadows in the image is adopted for obstacle detection, and edge detection is used to assist in determining the boundary of obstacles. The proposed fusion approach is verified through real experimental examples of on-road vehicle/pedestrian detection. In the end, the experimental results show that the proposed method is simple and feasible. PMID:22164117

Integrating millimeter wave radar with a monocular vision sensor for on-road obstacle detection applications.

PubMed

Wang, Tao; Zheng, Nanning; Xin, Jingmin; Ma, Zheng

2011-01-01

This paper presents a systematic scheme for fusing millimeter wave (MMW) radar and a monocular vision sensor for on-road obstacle detection. As a whole, a three-level fusion strategy based on visual attention mechanism and driver's visual consciousness is provided for MMW radar and monocular vision fusion so as to obtain better comprehensive performance. Then an experimental method for radar-vision point alignment for easy operation with no reflection intensity of radar and special tool requirements is put forward. Furthermore, a region searching approach for potential target detection is derived in order to decrease the image processing time. An adaptive thresholding algorithm based on a new understanding of shadows in the image is adopted for obstacle detection, and edge detection is used to assist in determining the boundary of obstacles. The proposed fusion approach is verified through real experimental examples of on-road vehicle/pedestrian detection. In the end, the experimental results show that the proposed method is simple and feasible.

On autonomous terrain model acquistion by a mobile robot

NASA Technical Reports Server (NTRS)

Rao, N. S. V.; Iyengar, S. S.; Weisbin, C. R.

1987-01-01

The following problem is considered: A point robot is placed in a terrain populated by an unknown number of polyhedral obstacles of varied sizes and locations in two/three dimensions. The robot is equipped with a sensor capable of detecting all the obstacle vertices and edges that are visible from the present location of the robot. The robot is required to autonomously navigate and build the complete terrain model using the sensor information. It is established that the necessary number of scanning operations needed for complete terrain model acquisition by any algorithm that is based on scan from vertices strategy is given by the summation of i = 1 (sup n) N(O sub i)-n and summation of i = 1 (sup n) N(O sub i)-2n in two- and three-dimensional terrains respectively, where O = (O sub 1, O sub 2,....O sub n) set of the obstacles in the terrain, and N(O sub i) is the number of vertices of the obstacle O sub i.

Imparting protean behavior to mobile robots accomplishing patrolling tasks in the presence of adversaries.

PubMed

Curiac, Daniel-Ioan; Volosencu, Constantin

2015-10-08

Providing unpredictable trajectories for patrol robots is essential when coping with adversaries. In order to solve this problem we developed an effective approach based on the known protean behavior of individual prey animals-random zig-zag movement. The proposed bio-inspired method modifies the normal robot's path by incorporating sudden and irregular direction changes without jeopardizing the robot's mission. Such a tactic is aimed to confuse the enemy (e.g. a sniper), offering less time to acquire and retain sight alignment and sight picture. This idea is implemented by simulating a series of fictive-temporary obstacles that will randomly appear in the robot's field of view, deceiving the obstacle avoiding mechanism to react. The new general methodology is particularized by using the Arnold's cat map to obtain the timely random appearance and disappearance of the fictive obstacles. The viability of the proposed method is confirmed through an extensive simulation case study.

Sensor Fusion Based Model for Collision Free Mobile Robot Navigation

PubMed Central

Almasri, Marwah; Elleithy, Khaled; Alajlan, Abrar

2015-01-01

Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have inaccurate readings. Therefore, the integration of sensor fusion will help to solve this dilemma and enhance the overall performance. This paper presents a collision free mobile robot navigation based on the fuzzy logic fusion model. Eight distance sensors and a range finder camera are used for the collision avoidance approach where three ground sensors are used for the line or path following approach. The fuzzy system is composed of nine inputs which are the eight distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot’s wheels, and 24 fuzzy rules for the robot’s movement. Webots Pro simulator is used for modeling the environment and the robot. The proposed methodology, which includes the collision avoidance based on fuzzy logic fusion model and line following robot, has been implemented and tested through simulation and real time experiments. Various scenarios have been presented with static and dynamic obstacles using one robot and two robots while avoiding obstacles in different shapes and sizes. PMID:26712766

Sensor Fusion Based Model for Collision Free Mobile Robot Navigation.

PubMed

Almasri, Marwah; Elleithy, Khaled; Alajlan, Abrar

2015-12-26

Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have inaccurate readings. Therefore, the integration of sensor fusion will help to solve this dilemma and enhance the overall performance. This paper presents a collision free mobile robot navigation based on the fuzzy logic fusion model. Eight distance sensors and a range finder camera are used for the collision avoidance approach where three ground sensors are used for the line or path following approach. The fuzzy system is composed of nine inputs which are the eight distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot's wheels, and 24 fuzzy rules for the robot's movement. Webots Pro simulator is used for modeling the environment and the robot. The proposed methodology, which includes the collision avoidance based on fuzzy logic fusion model and line following robot, has been implemented and tested through simulation and real time experiments. Various scenarios have been presented with static and dynamic obstacles using one robot and two robots while avoiding obstacles in different shapes and sizes.

Obstacles and challenges following the partial decriminalisation of abortion in Colombia.

PubMed

Amado, Eduardo Díaz; Calderón García, Maria Cristina; Cristancho, Katherine Romero; Salas, Elena Prada; Hauzeur, Eliane Barreto

2010-11-01

During a highly contested process, abortion was partially decriminalised in Colombia in 2006 by the Constitutional Court: when the pregnancy threatens a woman's life or health, in cases of severe fetal malformations incompatible with life, and in cases of rape, incest or unwanted insemination. However, Colombian women still face obstacles to accessing abortion services. This is illustrated by 36 cases of women who in 2006-08 were denied the right to a lawful termination of pregnancy, or had unjustified obstacles put in their path which delayed the termination, which are analysed in this article. We argue that the obstacles resulted from fundamental disagreements about abortion and misunderstandings regarding the ethical, legal and medical requirements arising from the Court's decision. In order to avoid obstacles such as demands for a judge's authorisation, institutional claims of conscientious objection, rejection of a claim of rape, or refusal of health insurance coverage for a legal termination, which constitute discrimination against women, three main strategies are suggested: public ownership of the Court's decision by all Colombian citizens, a professional approach by those involved in the provision of services in line with the law, and monitoring of its implementation by governmental and non-governmental organisations. Copyright © 2010 Reproductive Health Matters. Published by Elsevier Ltd. All rights reserved.

Localization Using Visual Odometry and a Single Downward-Pointing Camera

NASA Technical Reports Server (NTRS)

Swank, Aaron J.

2012-01-01

Stereo imaging is a technique commonly employed for vision-based navigation. For such applications, two images are acquired from different vantage points and then compared using transformations to extract depth information. The technique is commonly used in robotics for obstacle avoidance or for Simultaneous Localization And Mapping, (SLAM). Yet, the process requires a number of image processing steps and therefore tends to be CPU-intensive, which limits the real-time data rate and use in power-limited applications. Evaluated here is a technique where a monocular camera is used for vision-based odometry. In this work, an optical flow technique with feature recognition is performed to generate odometry measurements. The visual odometry sensor measurements are intended to be used as control inputs or measurements in a sensor fusion algorithm using low-cost MEMS based inertial sensors to provide improved localization information. Presented here are visual odometry results which demonstrate the challenges associated with using ground-pointing cameras for visual odometry. The focus is for rover-based robotic applications for localization within GPS-denied environments.

First stereo video dataset with ground truth for remote car pose estimation using satellite markers

NASA Astrophysics Data System (ADS)

Gil, Gustavo; Savino, Giovanni; Pierini, Marco

2018-04-01

Leading causes of PTW (Powered Two-Wheeler) crashes and near misses in urban areas are on the part of a failure or delayed prediction of the changing trajectories of other vehicles. Regrettably, misperception from both car drivers and motorcycle riders results in fatal or serious consequences for riders. Intelligent vehicles could provide early warning about possible collisions, helping to avoid the crash. There is evidence that stereo cameras can be used for estimating the heading angle of other vehicles, which is key to anticipate their imminent location, but there is limited heading ground truth data available in the public domain. Consequently, we employed a marker-based technique for creating ground truth of car pose and create a dataset∗ for computer vision benchmarking purposes. This dataset of a moving vehicle collected from a static mounted stereo camera is a simplification of a complex and dynamic reality, which serves as a test bed for car pose estimation algorithms. The dataset contains the accurate pose of the moving obstacle, and realistic imagery including texture-less and non-lambertian surfaces (e.g. reflectance and transparency).

Video rate color region segmentation for mobile robotic applications

NASA Astrophysics Data System (ADS)

de Cabrol, Aymeric; Bonnin, Patrick J.; Hugel, Vincent; Blazevic, Pierre; Chetto, Maryline

2005-08-01

Color Region may be an interesting image feature to extract for visual tasks in robotics, such as navigation and obstacle avoidance. But, whereas numerous methods are used for vision systems embedded on robots, only a few use this segmentation mainly because of the processing duration. In this paper, we propose a new real-time (ie. video rate) color region segmentation followed by a robust color classification and a merging of regions, dedicated to various applications such as RoboCup four-legged league or an industrial conveyor wheeled robot. Performances of this algorithm and confrontation with other methods, in terms of result quality and temporal performances are provided. For better quality results, the obtained speed up is between 2 and 4. For same quality results, the it is up to 10. We present also the outlines of the Dynamic Vision System of the CLEOPATRE Project - for which this segmentation has been developed - and the Clear Box Methodology which allowed us to create the new color region segmentation from the evaluation and the knowledge of other well known segmentations.

Autonomous manoeuvring systems for collision avoidance on single carriageway roads.

PubMed

Jiménez, Felipe; Naranjo, José Eugenio; Gómez, Oscar

2012-11-29

The accurate perception of the surroundings of a vehicle has been the subject of study of numerous automotive researchers for many years. Although several projects in this area have been successfully completed, very few prototypes have actually been industrialized and installed in mass produced cars. This indicates that these research efforts must continue in order to improve the present systems. Moreover, the trend to include communication systems in vehicles extends the potential of these perception systems transmitting their information via wireless to other vehicles that may be affected by the surveyed environment. In this paper we present a forward collision warning system based on a laser scanner that is able to detect several potential danger situations. Decision algorithms try to determine the most convenient manoeuvre when evaluating the obstacles' positions and speeds, road geometry, etc. Once detected, the presented system can act on the actuators of the ego-vehicle as well as transmit this information to other vehicles circulating in the same area using vehicle-to-vehicle communications. The system has been tested for overtaking manoeuvres under different scenarios and the correct actions have been performed.

7 CFR 1755.506 - Aerial wire services

Code of Federal Regulations, 2010 CFR

2010-01-01

.../Orange or White Orange 3 White/Green or White Green 4 White/Brown or White Brown 5 White/Slate or White... station protectors. (p) When it is necessary to avoid intervening obstacles between a pole and a building... lines to buildings shall follow the shortest feasible route commensurate with the requirements of...

The effect of collision avoidance for autonomous robot team formation

NASA Astrophysics Data System (ADS)

Seidman, Mark H.; Yang, Shanchieh J.

2007-04-01

As technology and research advance to the era of cooperative robots, many autonomous robot team algorithms have emerged. Shape formation is a common and critical task in many cooperative robot applications. While theoretical studies of robot team formation have shown success, it is unclear whether such algorithms will perform well in a real-world environment. This work examines the effect of collision avoidance schemes on an ideal circle formation algorithm, but behaves similarly if robot-to-robot communications are in place. Our findings reveal that robots with basic collision avoidance capabilities are still able to form into a circle, under most conditions. Moreover, the robot sizes, sensing ranges, and other critical physical parameters are examined to determine their effects on algorithm's performance.

Finding Out Critical Points For Real-Time Path Planning

NASA Astrophysics Data System (ADS)

Chen, Wei

1989-03-01

Path planning for a mobile robot is a classic topic, but the path planning under real-time environment is a different issue. The system sources including sampling time, processing time, processes communicating time, and memory space are very limited for this type of application. This paper presents a method which abstracts the world representation from the sensory data and makes the decision as to which point will be a potentially critical point to span the world map by using incomplete knowledge about physical world and heuristic rule. Without any previous knowledge or map of the workspace, the robot will determine the world map by roving through the workspace. The computational complexity for building and searching such a map is not more than O( n2 ) The find-path problem is well-known in robotics. Given an object with an initial location and orientation, a goal location and orientation, and a set of obstacles located in space, the problem is to find a continuous path for the object from the initial position to the goal position which avoids collisions with obstacles along the way. There are a lot of methods to find a collision-free path in given environment. Techniques for solving this problem can be classified into three approaches: 1) the configuration space approach [1],[2],[3] which represents the polygonal obstacles by vertices in a graph. The idea is to determine those parts of the free space which a reference point of the moving object can occupy without colliding with any obstacles. A path is then found for the reference point through this truly free space. Dealing with rotations turns out to be a major difficulty with the approach, requiring complex geometric algorithms which are computationally expensive. 2) the direct representation of the free space using basic shape primitives such as convex polygons [4] and overlapping generalized cones [5]. 3) the combination of technique 1 and 2 [6] by which the space is divided into the primary convex region, overlap region and obstacle region, then obstacle boundaries with attribute values are represented by the vertices of the hypergraph. The primary convex region and overlap region are represented by hyperedges, the centroids of overlap form the critical points. The difficulty is generating segment graph and estimating of minimum path width. The all techniques mentioned above need previous knowledge about the world to make path planning and the computational cost is not low. They are not available in an unknow and uncertain environment. Due to limited system resources such as CPU time, memory size and knowledge about the special application in an intelligent system (such as mobile robot), it is necessary to use algorithms that provide the good decision which is feasible with the available resources in real time rather than the best answer that could be achieved in unlimited time with unlimited resources. A real-time path planner should meet following requirements: - Quickly abstract the representation of the world from the sensory data without any previous knowledge about the robot environment. - Easily update the world model to spell out the global-path map and to reflect changes in the robot environment. - Must make a decision of where the robot must go and which direction the range sensor should point to in real time with limited resources. The method presented here assumes that the data from range sensors has been processed by signal process unite. The path planner will guide the scan of range sensor, find critical points, make decision where the robot should go and which point is poten- tial critical point, generate the path map and monitor the robot moves to the given point. The program runs recursively until the goal is reached or the whole workspace is roved through.

Numerical Study of Periodic Traveling Wave Solutions for the Predator-Prey Model with Landscape Features

NASA Astrophysics Data System (ADS)

Yun, Ana; Shin, Jaemin; Li, Yibao; Lee, Seunggyu; Kim, Junseok

We numerically investigate periodic traveling wave solutions for a diffusive predator-prey system with landscape features. The landscape features are modeled through the homogeneous Dirichlet boundary condition which is imposed at the edge of the obstacle domain. To effectively treat the Dirichlet boundary condition, we employ a robust and accurate numerical technique by using a boundary control function. We also propose a robust algorithm for calculating the numerical periodicity of the traveling wave solution. In numerical experiments, we show that periodic traveling waves which move out and away from the obstacle are effectively generated. We explain the formation of the traveling waves by comparing the wavelengths. The spatial asynchrony has been shown in quantitative detail for various obstacles. Furthermore, we apply our numerical technique to the complicated real landscape features.

Performance Characterization of Obstacle Detection Algorithms for Aircraft Navigation

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar; Camps, Octavia; Coraor, Lee; Gandhi, Tarak; Hartman, Kerry; Yang, Mau-Tsuen

2000-01-01

The research reported here is a part of NASA's Synthetic Vision System (SVS) project for the development of a High Speed Civil Transport Aircraft (HSCT). One of the components of the SVS is a module for detection of potential obstacles in the aircraft's flight path by analyzing the images captured by an on-board camera in real-time. Design of such a module includes the selection and characterization of robust, reliable, and fast techniques and their implementation for execution in real-time. This report describes the results of our research in realizing such a design.

Controlled motion in an elastic world. Research project: Manipulation strategies for massive space payloads

NASA Technical Reports Server (NTRS)

Book, Wayne J.

1992-01-01

The flexibility of the drives and structures of controlled motion systems are presented as an obstacle to be overcome in the design of high performance motion systems, particularly manipulator arms. The task and the measure of performance to be applied determine the technology appropriate to overcome this obstacle. Included in the technologies proposed are control algorithms (feedback and feed forward), passive damping enhancement, operational strategies, and structural design. Modeling of the distributed, nonlinear system is difficult, and alternative approaches are discussed. The author presents personal perspectives on the history, status, and future directions in this area.

Automated guidance algorithms for a space station-based crew escape vehicle.

PubMed

Flanary, R; Hammen, D G; Ito, D; Rabalais, B W; Rishikof, B H; Siebold, K H

2003-04-01

An escape vehicle was designed to provide an emergency evacuation for crew members living on a space station. For maximum escape capability, the escape vehicle needs to have the ability to safely evacuate a station in a contingency scenario such as an uncontrolled (e.g., tumbling) station. This emergency escape sequence will typically be divided into three events: The first separation event (SEP1), the navigation reconstruction event, and the second separation event (SEP2). SEP1 is responsible for taking the spacecraft from its docking port to a distance greater than the maximum radius of the rotating station. The navigation reconstruction event takes place prior to the SEP2 event and establishes the orbital state to within the tolerance limits necessary for SEP2. The SEP2 event calculates and performs an avoidance burn to prevent station recontact during the next several orbits. This paper presents the tools and results for the whole separation sequence with an emphasis on the two separation events. The first challenge includes collision avoidance during the escape sequence while the station is in an uncontrolled rotational state, with rotation rates of up to 2 degrees per second. The task of avoiding a collision may require the use of the Vehicle's de-orbit propulsion system for maximum thrust and minimum dwell time within the vicinity of the station vicinity. The thrust of the propulsion system is in a single direction, and can be controlled only by the attitude of the spacecraft. Escape algorithms based on a look-up table or analytical guidance can be implemented since the rotation rate and the angular momentum vector can be sensed onboard and a-priori knowledge of the position and relative orientation are available. In addition, crew intervention has been provided for in the event of unforeseen obstacles in the escape path. The purpose of the SEP2 burn is to avoid re-contact with the station over an extended period of time. Performing this maneuver requires knowledge of the orbital state, which is obtained during the navigation state reconstruction event. Since the direction of the delta-v of the SEP1 maneuver is a random variable with respect to the Local Vertical Local Horizontal (LVLH) coordinate system, calculating the required SEP2 burn is a challenge. This problem was solved using elements of neural network theory for model-free function approximation and decision making. c2003 COSPAR. Published by Elsevier Science Ltd. All rights reserved.

Longitudinal kinematic and kinetic adaptations to obstacle crossing in recent lower limb amputees.

PubMed

Barnett, Cleveland T; Polman, Remco C J; Vanicek, Natalie

2014-12-01

Obstacle crossing is an important activity of daily living, necessary to avoid tripping or falling, although it is not fully understood how transtibial amputees adapt to performing this activity of daily living following discharge from rehabilitation. The objective of this study was to investigate the longitudinal adaptations in obstacle crossing in transtibial amputees post-discharge from rehabilitation. Longitudinal repeated measures. Seven unilateral transtibial amputees crossed an obstacle 0.1m high positioned along a walkway while kinematic and kinetic data were recorded at 1, 3 and 6 months post-discharge. At 6 months post-discharge, walking velocity had increased (0.17 m.s(-1)) with most participants self-selecting an intact lead limb preference. During swing phase, peak knee flexion (p = 0.03) and peak knee power absorption (K4; p = 0.01) were greater with an intact versus affected lead limb preference. Having crossed the obstacle, intact limb peak ankle power generation in pre-swing (A2; p = 0.01) and knee power absorption (K3; p = 0.05) during stance phase were greater when compared to the affected limb. Obstacle crossing improved, although a greater reliance on intact limb function was highlighted. Results suggested that further improvements to locomotor performance may be obtained by increasing affected limb knee range of motion and concentric and eccentric strength of the knee extensors and flexors. The novel objective data from this study establish an understanding of how recent transtibial amputees adapt to performing obstacle crossing following discharge from rehabilitation. This allows for evidence-based clinical interventions to be developed, aimed at optimising biomechanical function, thus improving overall locomotor performance and perhaps subsequent quality of life. © The International Society for Prosthetics and Orthotics 2013.

Neural correlates of obstacle negotiation in older adults: An fNIRS study.

PubMed

Chen, Michelle; Pillemer, Sarah; England, Sarah; Izzetoglu, Meltem; Mahoney, Jeannette R; Holtzer, Roee

2017-10-01

Older adults are less efficient at avoiding obstacles compared to young adults, especially under attention-demanding conditions. Using functional near-infrared-spectroscopy (fNIRS), recent studies implicated the prefrontal cortex (PFC) in cognitive control of locomotion, notably under dual-task walking conditions. The neural substrates underlying Obstacle Negotiation (ON), however, have not been established. The current study determined the role of the PFC in ON during walking in seniors. Non-demented older adults (n=90; mean age=78.1±5.5years; %female=51) underwent fNIRS acquisition to assess changes in hemodynamic activity in the PFC during normal-walk [NW] and walk-while-talk [WWT] conditions with and without obstacles. Obstacles were presented as red elliptical shapes using advanced laser technology, which resemble potholes. Linear mixed effects models were used to determine differences in oxygenated hemoglobin (HbO 2 ) levels among the four task conditions. The presence of slow gait, a risk factor for dementia and falls, served as a predictor hypothesized to moderate the effect of obstacles on PFC HbO 2 levels. PFC HbO 2 levels were significantly higher in WWT compared to NW (p<0.001) irrespective of ON. Slow gait moderated the effect of obstacles on HbO 2 levels across task conditions. Specifically, compared to participants with normal gait, PFC HbO 2 levels were significantly increased in ON-NW relative to NW (p=0.017) and ON-WWT relative to WWT (p<0.001) among individuals with slow gait. Consistent with Compensatory Reallocation, ON required greater PFC involvement among individuals with mobility limitations. Copyright © 2017 Elsevier B.V. All rights reserved.

Bridging the Gap in Military Robotics (Combler le Fosse Existant dans le Domaine de la Robotique Militaire)

DTIC Science & Technology

2008-11-01

systems must be evaluated at the platform level as well ( regenerative braking and similar systems). 4.4.4 The Important Gaps Several gaps on robot...in three main categories : • Mobility function: • Obstacle avoidance and negotiation; • Terrain modelling and classification; and • Transport in

Modeling and Implementation of PID Control for Autonomous Robots

DTIC Science & Technology

2007-06-01

2 Figure 2. Bigfoot ...guidance, 802.11 wireless communications, and a motion triggered camera to monitor an area for IED placement. LT John Herkamp’s Bigfoot (Figure 2) is...designed to disable IED’s. Bigfoot includes the same obstacle avoidance software and sensors, but has a controllable arm to carry a counter charge

Some recollections of D. R. Griffin as a young man

NASA Astrophysics Data System (ADS)

Galambos, Robert

2004-05-01

In 1939 Don Griffin invited me to join him in his earliest bat echolocation experiments. I will tell a few stories about what we two graduate students did together, and show the sound movie in which, for the first time, we recorded their cries as they flew and avoided obstacles.

Elementary EFL Teachers' Computer Phobia and Computer Self-Efficacy in Taiwan

ERIC Educational Resources Information Center

Chen, Kate Tzuching

2012-01-01

The advent and application of computer and information technology has increased the overall success of EFL teaching; however, such success is hard to assess, and teachers prone to computer avoidance face negative consequences. Two major obstacles are high computer phobia and low computer self-efficacy. However, little research has been carried out…

Constraint-based semi-autonomy for unmanned ground vehicles using local sensing

NASA Astrophysics Data System (ADS)

Anderson, Sterling J.; Karumanchi, Sisir B.; Johnson, Bryan; Perlin, Victor; Rohde, Mitchell; Iagnemma, Karl

2012-06-01

Teleoperated vehicles are playing an increasingly important role in a variety of military functions. While advantageous in many respects over their manned counterparts, these vehicles also pose unique challenges when it comes to safely avoiding obstacles. Not only must operators cope with difficulties inherent to the manned driving task, but they must also perform many of the same functions with a restricted field of view, limited depth perception, potentially disorienting camera viewpoints, and significant time delays. In this work, a constraint-based method for enhancing operator performance by seamlessly coordinating human and controller commands is presented. This method uses onboard LIDAR sensing to identify environmental hazards, designs a collision-free path homotopy traversing that environment, and coordinates the control commands of a driver and an onboard controller to ensure that the vehicle trajectory remains within a safe homotopy. This system's performance is demonstrated via off-road teleoperation of a Kawasaki Mule in an open field among obstacles. In these tests, the system safely avoids collisions and maintains vehicle stability even in the presence of "routine" operator error, loss of operator attention, and complete loss of communications.

Interactive-rate Motion Planning for Concentric Tube Robots.

PubMed

Torres, Luis G; Baykal, Cenk; Alterovitz, Ron

2014-05-01

Concentric tube robots may enable new, safer minimally invasive surgical procedures by moving along curved paths to reach difficult-to-reach sites in a patient's anatomy. Operating these devices is challenging due to their complex, unintuitive kinematics and the need to avoid sensitive structures in the anatomy. In this paper, we present a motion planning method that computes collision-free motion plans for concentric tube robots at interactive rates. Our method's high speed enables a user to continuously and freely move the robot's tip while the motion planner ensures that the robot's shaft does not collide with any anatomical obstacles. Our approach uses a highly accurate mechanical model of tube interactions, which is important since small movements of the tip position may require large changes in the shape of the device's shaft. Our motion planner achieves its high speed and accuracy by combining offline precomputation of a collision-free roadmap with online position control. We demonstrate our interactive planner in a simulated neurosurgical scenario where a user guides the robot's tip through the environment while the robot automatically avoids collisions with the anatomical obstacles.

Trajectory optimization for lunar soft landing with complex constraints

NASA Astrophysics Data System (ADS)

Chu, Huiping; Ma, Lin; Wang, Kexin; Shao, Zhijiang; Song, Zhengyu

2017-11-01

A unified trajectory optimization framework with initialization strategies is proposed in this paper for lunar soft landing for various missions with specific requirements. Two main missions of interest are Apollo-like Landing from low lunar orbit and Vertical Takeoff Vertical Landing (a promising mobility method) on the lunar surface. The trajectory optimization is characterized by difficulties arising from discontinuous thrust, multi-phase connections, jump of attitude angle, and obstacles avoidance. Here R-function is applied to deal with the discontinuities of thrust, checkpoint constraints are introduced to connect multiple landing phases, attitude angular rate is designed to get rid of radical changes, and safeguards are imposed to avoid collision with obstacles. The resulting dynamic problems are generally with complex constraints. The unified framework based on Gauss Pseudospectral Method (GPM) and Nonlinear Programming (NLP) solver are designed to solve the problems efficiently. Advanced initialization strategies are developed to enhance both the convergence and computation efficiency. Numerical results demonstrate the adaptability of the framework for various landing missions, and the performance of successful solution of difficult dynamic problems.

Safe Local Navigation for Visually Impaired Users With a Time-of-Flight and Haptic Feedback Device.

PubMed

Katzschmann, Robert K; Araki, Brandon; Rus, Daniela

2018-03-01

This paper presents ALVU (Array of Lidars and Vibrotactile Units), a contactless, intuitive, hands-free, and discreet wearable device that allows visually impaired users to detect low- and high-hanging obstacles, as well as physical boundaries in their immediate environment. The solution allows for safe local navigation in both confined and open spaces by enabling the user to distinguish free space from obstacles. The device presented is composed of two parts: a sensor belt and a haptic strap. The sensor belt is an array of time-of-flight distance sensors worn around the front of a user's waist, and the pulses of infrared light provide reliable and accurate measurements of the distances between the user and surrounding obstacles or surfaces. The haptic strap communicates the measured distances through an array of vibratory motors worn around the user's upper abdomen, providing haptic feedback. The linear vibration motors are combined with a point-loaded pretensioned applicator to transmit isolated vibrations to the user. We validated the device's capability in an extensive user study entailing 162 trials with 12 blind users. Users wearing the device successfully walked through hallways, avoided obstacles, and detected staircases.

The didactic situation in geometry learning based on analysis of learning obstacles and learning trajectory

NASA Astrophysics Data System (ADS)

Sulistyowati, Fitria; Budiyono, Slamet, Isnandar

2017-12-01

This study aims to design a didactic situation based on the analysis of learning obstacles and learning trajectory on prism volume. The type of this research is qualitative and quantitative research with steps: analyzing the learning obstacles and learning trajectory, preparing the didactic situation, applying the didactic situation in the classroom, mean difference test of problem solving ability with t-test statistic. The subjects of the study were 8th grade junior high school students in Magelang 2016/2017 selected randomly from eight existing classes. The result of this research is the design of didactic situations that can be implemented in prism volume learning. The effectiveness of didactic situations that have been designed is shown by the mean difference test that is the problem solving ability of the students after the application of the didactic situation better than before the application. The didactic situation that has been generated is expected to be a consideration for teachers to design lessons that match the character of learners, classrooms and teachers themselves, so that the potential thinking of learners can be optimized to avoid the accumulation of learning obstacles.

On avoided words, absent words, and their application to biological sequence analysis.

PubMed

Almirantis, Yannis; Charalampopoulos, Panagiotis; Gao, Jia; Iliopoulos, Costas S; Mohamed, Manal; Pissis, Solon P; Polychronopoulos, Dimitris

2017-01-01

The deviation of the observed frequency of a word w from its expected frequency in a given sequence x is used to determine whether or not the word is avoided . This concept is particularly useful in DNA linguistic analysis. The value of the deviation of w , denoted by [Formula: see text], effectively characterises the extent of a word by its edge contrast in the context in which it occurs. A word w of length [Formula: see text] is a [Formula: see text]-avoided word in x if [Formula: see text], for a given threshold [Formula: see text]. Notice that such a word may be completely absent from x . Hence, computing all such words naïvely can be a very time-consuming procedure, in particular for large k . In this article, we propose an [Formula: see text]-time and [Formula: see text]-space algorithm to compute all [Formula: see text]-avoided words of length k in a given sequence of length n over a fixed-sized alphabet. We also present a time-optimal [Formula: see text]-time algorithm to compute all [Formula: see text]-avoided words (of any length) in a sequence of length n over an integer alphabet of size [Formula: see text]. In addition, we provide a tight asymptotic upper bound for the number of [Formula: see text]-avoided words over an integer alphabet and the expected length of the longest one. We make available an implementation of our algorithm. Experimental results, using both real and synthetic data, show the efficiency and applicability of our implementation in biological sequence analysis. The systematic search for avoided words is particularly useful for biological sequence analysis. We present a linear-time and linear-space algorithm for the computation of avoided words of length k in a given sequence x . We suggest a modification to this algorithm so that it computes all avoided words of x , irrespective of their length, within the same time complexity. We also present combinatorial results with regards to avoided words and absent words.

Experimental Semiautonomous Vehicle

NASA Technical Reports Server (NTRS)

Wilcox, Brian H.; Mishkin, Andrew H.; Litwin, Todd E.; Matthies, Larry H.; Cooper, Brian K.; Nguyen, Tam T.; Gat, Erann; Gennery, Donald B.; Firby, Robert J.; Miller, David P.;

Dense real-time stereo matching using memory efficient semi-global-matching variant based on FPGAs

NASA Astrophysics Data System (ADS)

Buder, Maximilian

2012-06-01

This paper presents a stereo image matching system that takes advantage of a global image matching method. The system is designed to provide depth information for mobile robotic applications. Typical tasks of the proposed system are to assist in obstacle avoidance, SLAM and path planning. Mobile robots pose strong requirements about size, energy consumption, reliability and output quality of the image matching subsystem. Current available systems either rely on active sensors or on local stereo image matching algorithms. The first are only suitable in controlled environments while the second suffer from low quality depth-maps. Top ranking quality results are only achieved by an iterative approach using global image matching and color segmentation techniques which are computationally demanding and therefore difficult to be executed in realtime. Attempts were made to still reach realtime performance with global methods by simplifying the routines. The depth maps are at the end almost comparable to local methods. An equally named semi-global algorithm was proposed earlier that shows both very good image matching results and relatively simple operations. A memory efficient variant of the Semi-Global-Matching algorithm is reviewed and adopted for an implementation based on reconfigurable hardware. The implementation is suitable for realtime execution in the field of robotics. It will be shown that the modified version of the efficient Semi-Global-Matching method is delivering equivalent result compared to the original algorithm based on the Middlebury dataset. The system has proven to be capable of processing VGA sized images with a disparity resolution of 64 pixel at 33 frames per second based on low cost to mid-range hardware. In case the focus is shifted to a higher image resolution, 1024×1024-sized stereo frames may be processed with the same hardware at 10 fps. The disparity resolution settings stay unchanged. A mobile system that covers preprocessing, matching and interfacing operations is also presented.

Range image registration based on hash map and moth-flame optimization

NASA Astrophysics Data System (ADS)

Zou, Li; Ge, Baozhen; Chen, Lei

2018-03-01

Over the past decade, evolutionary algorithms (EAs) have been introduced to solve range image registration problems because of their robustness and high precision. However, EA-based range image registration algorithms are time-consuming. To reduce the computational time, an EA-based range image registration algorithm using hash map and moth-flame optimization is proposed. In this registration algorithm, a hash map is used to avoid over-exploitation in registration process. Additionally, we present a search equation that is better at exploration and a restart mechanism to avoid being trapped in local minima. We compare the proposed registration algorithm with the registration algorithms using moth-flame optimization and several state-of-the-art EA-based registration algorithms. The experimental results show that the proposed algorithm has a lower computational cost than other algorithms and achieves similar registration precision.

Obstacle Recognition Based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System

PubMed Central

Beruvides, Gerardo

2017-01-01

Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors’ knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions. PMID:28906450

Obstacle Recognition Based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System.

PubMed

Castaño, Fernando; Beruvides, Gerardo; Haber, Rodolfo E; Artuñedo, Antonio

2017-09-14

Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors' knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions.

Planning Paths Through Singularities in the Center of Mass Space

NASA Technical Reports Server (NTRS)

Doggett, William R.; Messner, William C.; Juang, Jer-Nan

1998-01-01

The center of mass space is a convenient space for planning motions that minimize reaction forces at the robot's base or optimize the stability of a mechanism. A unique problem associated with path planning in the center of mass space is the potential existence of multiple center of mass images for a single Cartesian obstacle, since a single center of mass location can correspond to multiple robot joint configurations. The existence of multiple images results in a need to either maintain multiple center of mass obstacle maps or to update obstacle locations when the robot passes through a singularity, such as when it moves from an elbow-up to an elbow-down configuration. To illustrate the concepts presented in this paper, a path is planned for an example task requiring motion through multiple center of mass space maps. The object of the path planning algorithm is to locate the bang- bang acceleration profile that minimizes the robot's base reactions in the presence of a single Cartesian obstacle. To simplify the presentation, only non-redundant robots are considered and joint non-linearities are neglected.

Algorithm for Autonomous Landing

NASA Technical Reports Server (NTRS)

Kuwata, Yoshiaki

2011-01-01

Because of their small size, high maneuverability, and easy deployment, micro aerial vehicles (MAVs) are used for a wide variety of both civilian and military missions. One of their current drawbacks is the vast array of sensors (such as GPS, altimeter, radar, and the like) required to make a landing. Due to the MAV s small payload size, this is a major concern. Replacing the imaging sensors with a single monocular camera is sufficient to land a MAV. By applying optical flow algorithms to images obtained from the camera, time-to-collision can be measured. This is a measurement of position and velocity (but not of absolute distance), and can avoid obstacles as well as facilitate a landing on a flat surface given a set of initial conditions. The key to this approach is to calculate time-to-collision based on some image on the ground. By holding the angular velocity constant, horizontal speed decreases linearly with the height, resulting in a smooth landing. Mathematical proofs show that even with actuator saturation or modeling/ measurement uncertainties, MAVs can land safely. Landings of this nature may have a higher velocity than is desirable, but this can be compensated for by a cushioning or dampening system, or by using a system of legs to grab onto a surface. Such a monocular camera system can increase vehicle payload size (or correspondingly reduce vehicle size), increase speed of descent, and guarantee a safe landing by directly correlating speed to height from the ground.

UAS Collision Avoidance Algorithm that Minimizes the Impact on Route Surveillance

DTIC Science & Technology

2009-03-01

Appendix A: Collision Avoidance Algorithm/Virtual Cockpit Interface .......................124 Appendix B : Collision Cone Boundary Rates... b ) Split Cone (c) Multiple Intruders, Single and Split Cones [27] ........................................................ 27 3-3: Collision Cone...Approach in the Vertical Plane (a) Single Cone ( b ) Multiple Intruders, Single and Split Cone [27

Improvements of the Penalty Avoiding Rational Policy Making Algorithm and an Application to the Othello Game

NASA Astrophysics Data System (ADS)

Miyazaki, Kazuteru; Tsuboi, Sougo; Kobayashi, Shigenobu

The purpose of reinforcement learning is to learn an optimal policy in general. However, in 2-players games such as the othello game, it is important to acquire a penalty avoiding policy. In this paper, we focus on formation of a penalty avoiding policy based on the Penalty Avoiding Rational Policy Making algorithm [Miyazaki 01]. In applying it to large-scale problems, we are confronted with the curse of dimensionality. We introduce several ideas and heuristics to overcome the combinational explosion in large-scale problems. First, we propose an algorithm to save the memory by calculation of state transition. Second, we describe how to restrict exploration by two type knowledge; KIFU database and evaluation funcion. We show that our learning player can always defeat against the well-known othello game program KITTY.

Learned navigation in unknown terrains: A retraction method

NASA Technical Reports Server (NTRS)

Rao, Nageswara S. V.; Stoltzfus, N.; Iyengar, S. Sitharama

1989-01-01

The problem of learned navigation of a circular robot R, of radius delta (is greater than or equal to 0), through a terrain whose model is not a-priori known is considered. Two-dimensional finite-sized terrains populated by an unknown (but, finite) number of simple polygonal obstacles are also considered. The number and locations of the vertices of each obstacle are unknown to R. R is equipped with a sensor system that detects all vertices and edges that are visible from its present location. In this context two problems are covered. In the visit problem, the robot is required to visit a sequence of destination points, and in the terrain model acquisition problem, the robot is required to acquire the complete model of the terrain. An algorithmic framework is presented for solving these two problems using a retraction of the freespace onto the Voronoi diagram of the terrain. Algorithms are then presented to solve the visit problem and the terrain model acquisition problem.

Three-camera stereo vision for intelligent transportation systems

NASA Astrophysics Data System (ADS)

Bergendahl, Jason; Masaki, Ichiro; Horn, Berthold K. P.

1997-02-01

A major obstacle in the application of stereo vision to intelligent transportation system is high computational cost. In this paper, a PC based three-camera stereo vision system constructed with off-the-shelf components is described. The system serves as a tool for developing and testing robust algorithms which approach real-time performance. We present an edge based, subpixel stereo algorithm which is adapted to permit accurate distance measurements to objects in the field of view using a compact camera assembly. Once computed, the 3D scene information may be directly applied to a number of in-vehicle applications, such as adaptive cruise control, obstacle detection, and lane tracking. Moreover, since the largest computational costs is incurred in generating the 3D scene information, multiple applications that leverage this information can be implemented in a single system with minimal cost. On-road applications, such as vehicle counting and incident detection, are also possible. Preliminary in-vehicle road trial results are presented.

Bionic Vision-Based Intelligent Power Line Inspection System

PubMed Central

Ma, Yunpeng; He, Feijia; Xu, Jinxin

2017-01-01

Detecting the threats of the external obstacles to the power lines can ensure the stability of the power system. Inspired by the attention mechanism and binocular vision of human visual system, an intelligent power line inspection system is presented in this paper. Human visual attention mechanism in this intelligent inspection system is used to detect and track power lines in image sequences according to the shape information of power lines, and the binocular visual model is used to calculate the 3D coordinate information of obstacles and power lines. In order to improve the real time and accuracy of the system, we propose a new matching strategy based on the traditional SURF algorithm. The experimental results show that the system is able to accurately locate the position of the obstacles around power lines automatically, and the designed power line inspection system is effective in complex backgrounds, and there are no missing detection instances under different conditions. PMID:28203269

Mobility aid for the blind

NASA Technical Reports Server (NTRS)

1982-01-01

A project to develop an effective mobility aid for blind pedestrians which acquires consecutive images of the scenes before a moving pedestrian, which locates and identifies the pedestrian's path and potential obstacles in the path, which presents path and obstacle information to the pedestrian, and which operates in real-time is discussed. The mobility aid has three principal components: an image acquisition system, an image interpretation system, and an information presentation system. The image acquisition system consists of a miniature, solid-state TV camera which transforms the scene before the blind pedestrian into an image which can be received by the image interpretation system. The image interpretation system is implemented on a microprocessor which has been programmed to execute real-time feature extraction and scene analysis algorithms for locating and identifying the pedestrian's path and potential obstacles. Identity and location information is presented to the pedestrian by means of tactile coding and machine-generated speech.

Inverse obstacle problem for the scalar Helmholtz equation

NASA Astrophysics Data System (ADS)

Crosta, Giovanni F.

1994-07-01

The method presented is aimed at identifying the shape of an axially symmetric, sound soft acoustic scatterer from knowledge of the incident plane wave and of the scattering amplitude. The method relies on the approximate back propagation (ABP) of the estimated far field coefficients to the obstacle boundary and iteratively minimizes a boundary defect, without the addition of any penalty term. The ABP operator owes its structure to the properties of complete families of linearly independent solutions of Helmholtz equation. If the obstacle is known, as it happens in simulations, the theory also provides some independent means of predicting the performance of the ABP method. The ABP algorithm and the related computer code are outlined. Several reconstruction examples are considered, where noise is added to the estimated far field coefficients and other errors are deliberately introduced in the data. Many numerical and graphical results are provided.

A wearable multipoint ultrasonic travel aids for visually impaired

NASA Astrophysics Data System (ADS)

Ercoli, Ilaria; Marchionni, Paolo; Scalise, Lorenzo

2013-09-01

In 2010, the World Health Organization estimates that there were about 285 million people in the world with disabling eyesight loss (246 millions are visually impaired (VI) and 39 millions are totally blind). For such users, hits during mobility tasks are the reason of major concerns and can reduce the quality of their life. The white cane is the primary device used by the majority of blind or VI users to explore and possibly avoid obstacles; it can monitor only the ground (< 1m) and it does not provide protection for the legs, the trunk and the head. In this paper, authors propose a novel stand-alone Electronic Travel Aid (ETA) device for obstacle detection based on multi- sensing (by 4 ultrasonic transducers) and a microcontroller. Portability, simplicity, reduced dimensions and cost are among the major pros of the reported system, which can detect and localize (angular position and distance from the user) obstacles eventually present in the volume in front of him and on the ground in front of him.

Mapping Nearby Terrain in 3D by Use of a Grid of Laser Spots

NASA Technical Reports Server (NTRS)

Padgett, Curtis; Liebe, Carl; Chang, Johnny; Brown, Kenneth

2007-01-01

A proposed optoelectronic system, to be mounted aboard an exploratory robotic vehicle, would be used to generate a three-dimensional (3D) map of nearby terrain and obstacles for purposes of navigating the vehicle across the terrain and avoiding the obstacles. The difference between this system and the other systems would lie in the details of implementation. In this system, the illumination would be provided by a laser. The beam from the laser would pass through a two-dimensional diffraction grating, which would divide the beam into multiple beams propagating in different, fixed, known directions. These beams would form a grid of bright spots on the nearby terrain and obstacles. The centroid of each bright spot in the image would be computed. For each such spot, the combination of (1) the centroid, (2) the known direction of the light beam that produced the spot, and (3) the known baseline would constitute sufficient information for calculating the 3D position of the spot.

Multi-agent autonomous system

NASA Technical Reports Server (NTRS)

Fink, Wolfgang (Inventor); Dohm, James (Inventor); Tarbell, Mark A. (Inventor)

2010-01-01

A multi-agent autonomous system for exploration of hazardous or inaccessible locations. The multi-agent autonomous system includes simple surface-based agents or craft controlled by an airborne tracking and command system. The airborne tracking and command system includes an instrument suite used to image an operational area and any craft deployed within the operational area. The image data is used to identify the craft, targets for exploration, and obstacles in the operational area. The tracking and command system determines paths for the surface-based craft using the identified targets and obstacles and commands the craft using simple movement commands to move through the operational area to the targets while avoiding the obstacles. Each craft includes its own instrument suite to collect information about the operational area that is transmitted back to the tracking and command system. The tracking and command system may be further coupled to a satellite system to provide additional image information about the operational area and provide operational and location commands to the tracking and command system.

A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks

PubMed Central

González-Parada, Eva; Cano-García, Jose; Aguilera, Francisco; Sandoval, Francisco; Urdiales, Cristina

2017-01-01

Autonomous mobile nodes in mobile wireless sensor networks (MWSN) allow self-deployment and self-healing. In both cases, the goals are: (i) to achieve adequate coverage; and (ii) to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage. PMID:28075364

A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks.

PubMed

González-Parada, Eva; Cano-García, Jose; Aguilera, Francisco; Sandoval, Francisco; Urdiales, Cristina

2017-01-09

Autonomous mobile nodes in mobile wireless sensor networks (MWSN) allow self-deployment and self-healing. In both cases, the goals are: (i) to achieve adequate coverage; and (ii) to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage.

3D Numerical Simulation on the Rockslide Generated Tsunamis

NASA Astrophysics Data System (ADS)

Chuang, M.; Wu, T.; Wang, C.; Chu, C.

2013-12-01

The rockslide generated tsunami is one of the most devastating nature hazards. However, the involvement of the moving obstacle and dynamic free-surface movement makes the numerical simulation a difficult task. To describe both the fluid motion and solid movement at the same time, we newly developed a two-way fully-coupled moving solid algorithm with 3D LES turbulent model. The free-surface movement is tracked by volume of fluid (VOF) method. The two-step projection method is adopted to solve the Navier-Stokes type government equations. In the new moving solid algorithm, a fictitious body force is implicitly prescribed in MAC correction step to make the cell-center velocity satisfied with the obstacle velocity. We called this method the implicit velocity method (IVM). Because no extra terms are added to the pressure Poission correction, the pressure field of the fluid part is stable, which is the key of the two-way fluid-solid coupling. Because no real solid material is presented in the IVM, the time marching step is not restricted to the smallest effective grid size. Also, because the fictitious force is implicitly added to the correction step, the resulting velocity is accurate and fully coupled with the resulting pressure field. We validated the IVM by simulating a floating box moving up and down on the free-surface. We presented the time-history obstacle trajectory and compared it with the experimental data. Very accurate result can be seen in terms of the oscillating amplitude and the period (Fig. 1). We also presented the free-surface comparison with the high-speed snapshots. At the end, the IVM was used to study the rock-slide generated tsunamis (Liu et al., 2005). Good validations on the slide trajectory and the free-surface movement will be presented in the full paper. From the simulation results (Fig. 2), we observed that the rockslide generated waves are manly caused by the rebounding waves from two sides of the sliding rock after the water is dragging down by the solid downward motion. We also found that the turbulence has minor effect to the main flow field. The rock size, rock density, and the steepness of the slope were analyzed to understand their effects to the maximum runup height. The detailed algorithm of IVM, the validation, the simulation and analysis of rockslide tsunami will be presented in the full paper. Figure 1. Time-history trajectory of obstacle for the floating obstacle simulation. Figure 2. Snapshots of the free-surface elevation with streamlines for the rockslide tsunami simulation.

Adiabatic Quantum Search in Open Systems.

PubMed

Wild, Dominik S; Gopalakrishnan, Sarang; Knap, Michael; Yao, Norman Y; Lukin, Mikhail D

2016-10-07

Adiabatic quantum algorithms represent a promising approach to universal quantum computation. In isolated systems, a key limitation to such algorithms is the presence of avoided level crossings, where gaps become extremely small. In open quantum systems, the fundamental robustness of adiabatic algorithms remains unresolved. Here, we study the dynamics near an avoided level crossing associated with the adiabatic quantum search algorithm, when the system is coupled to a generic environment. At zero temperature, we find that the algorithm remains scalable provided the noise spectral density of the environment decays sufficiently fast at low frequencies. By contrast, higher order scattering processes render the algorithm inefficient at any finite temperature regardless of the spectral density, implying that no quantum speedup can be achieved. Extensions and implications for other adiabatic quantum algorithms will be discussed.

A Depth-Based Head-Mounted Visual Display to Aid Navigation in Partially Sighted Individuals

PubMed Central

Hicks, Stephen L.; Wilson, Iain; Muhammed, Louwai; Worsfold, John; Downes, Susan M.; Kennard, Christopher

2013-01-01

Independent navigation for blind individuals can be extremely difficult due to the inability to recognise and avoid obstacles. Assistive techniques such as white canes, guide dogs, and sensory substitution provide a degree of situational awareness by relying on touch or hearing but as yet there are no techniques that attempt to make use of any residual vision that the individual is likely to retain. Residual vision can restricted to the awareness of the orientation of a light source, and hence any information presented on a wearable display would have to limited and unambiguous. For improved situational awareness, i.e. for the detection of obstacles, displaying the size and position of nearby objects, rather than including finer surface details may be sufficient. To test whether a depth-based display could be used to navigate a small obstacle course, we built a real-time head-mounted display with a depth camera and software to detect the distance to nearby objects. Distance was represented as brightness on a low-resolution display positioned close to the eyes without the benefit focussing optics. A set of sighted participants were monitored as they learned to use this display to navigate the course. All were able to do so, and time and velocity rapidly improved with practise with no increase in the number of collisions. In a second experiment a cohort of severely sight-impaired individuals of varying aetiologies performed a search task using a similar low-resolution head-mounted display. The majority of participants were able to use the display to respond to objects in their central and peripheral fields at a similar rate to sighted controls. We conclude that the skill to use a depth-based display for obstacle avoidance can be rapidly acquired and the simplified nature of the display may appropriate for the development of an aid for sight-impaired individuals. PMID:23844067

Unstructured mesh algorithms for aerodynamic calculations

NASA Technical Reports Server (NTRS)

Mavriplis, D. J.

1992-01-01

The use of unstructured mesh techniques for solving complex aerodynamic flows is discussed. The principle advantages of unstructured mesh strategies, as they relate to complex geometries, adaptive meshing capabilities, and parallel processing are emphasized. The various aspects required for the efficient and accurate solution of aerodynamic flows are addressed. These include mesh generation, mesh adaptivity, solution algorithms, convergence acceleration, and turbulence modeling. Computations of viscous turbulent two-dimensional flows and inviscid three-dimensional flows about complex configurations are demonstrated. Remaining obstacles and directions for future research are also outlined.

A Neural Model of How the Brain Computes Heading from Optic Flow in Realistic Scenes

ERIC Educational Resources Information Center

Browning, N. Andrew; Grossberg, Stephen; Mingolla, Ennio

2009-01-01

Visually-based navigation is a key competence during spatial cognition. Animals avoid obstacles and approach goals in novel cluttered environments using optic flow to compute heading with respect to the environment. Most navigation models try either explain data, or to demonstrate navigational competence in real-world environments without regard…

Angle Concept: A High School and Tertiary Longitudinal Perspective to Minimize Obstacles

ERIC Educational Resources Information Center

Barabash, Marita

2017-01-01

The concept of angle emerges in numerous forms as the learning of mathematics and its applications advances through the high school and tertiary curriculum. Many difficulties and misconceptions in the usage of this multifaceted concept might be avoided or at least minimized should the lecturers in different areas of pure and applied mathematics be…

Hand Path Priming in Manual Obstacle Avoidance: Rapid Decay of Dorsal Stream Information

ERIC Educational Resources Information Center

Jax, Steven A.; Rosenbaum, David A.

2009-01-01

The dorsal, action-related, visual stream has been thought to have little or no memory. This hypothesis has seemed credible because functions related to the dorsal stream have been generally unsusceptible to priming from previous experience. Tests of this claim have yielded inconsistent results, however. We argue that these inconsistencies may be…

Mentors as Fellow Travelers

ERIC Educational Resources Information Center

Ambrosino, Roberta

2009-01-01

A junior faculty member arrives at an unfamiliar university for a new teaching assignment. She is poised for the adventure, but feels like a traveler at the edge of long, unknown road. She does not know what obstacles or vistas may appear on the road, and wants to avoid major potholes. She takes a nervous look around and finds an experienced…

An alternative to unstructured grids for computing gas dynamic flows around arbitrarily complex two-dimensional bodies

NASA Technical Reports Server (NTRS)

Quirk, James J.

1992-01-01

In this paper we describe an approach for dealing with arbitrary complex, two dimensional geometries, the so-called cartesian boundary method. Conceptually, the cartesian boundary method is quite simple. Solid bodies blank out areas of a background, cartesian mesh, and the resultant cut cells are singled out for special attention. However, there are several obstacles that must be overcome in order to achieve a practical scheme. We present a general strategy that overcomes these obstacles, together with some details of our successful conversion of an adaptive mesh algorithm from a body-fitted code to a cartesian boundary code.

A Bio-inspired Collision Avoidance Model Based on Spatial Information Derived from Motion Detectors Leads to Common Routes

PubMed Central

Bertrand, Olivier J. N.; Lindemann, Jens P.; Egelhaaf, Martin

2015-01-01

Avoiding collisions is one of the most basic needs of any mobile agent, both biological and technical, when searching around or aiming toward a goal. We propose a model of collision avoidance inspired by behavioral experiments on insects and by properties of optic flow on a spherical eye experienced during translation, and test the interaction of this model with goal-driven behavior. Insects, such as flies and bees, actively separate the rotational and translational optic flow components via behavior, i.e. by employing a saccadic strategy of flight and gaze control. Optic flow experienced during translation, i.e. during intersaccadic phases, contains information on the depth-structure of the environment, but this information is entangled with that on self-motion. Here, we propose a simple model to extract the depth structure from translational optic flow by using local properties of a spherical eye. On this basis, a motion direction of the agent is computed that ensures collision avoidance. Flying insects are thought to measure optic flow by correlation-type elementary motion detectors. Their responses depend, in addition to velocity, on the texture and contrast of objects and, thus, do not measure the velocity of objects veridically. Therefore, we initially used geometrically determined optic flow as input to a collision avoidance algorithm to show that depth information inferred from optic flow is sufficient to account for collision avoidance under closed-loop conditions. Then, the collision avoidance algorithm was tested with bio-inspired correlation-type elementary motion detectors in its input. Even then, the algorithm led successfully to collision avoidance and, in addition, replicated the characteristics of collision avoidance behavior of insects. Finally, the collision avoidance algorithm was combined with a goal direction and tested in cluttered environments. The simulated agent then showed goal-directed behavior reminiscent of components of the navigation behavior of insects. PMID:26583771

Voltage control on a train system

DOEpatents

Gordon, Susanna P.; Evans, John A.

2004-01-20

The present invention provides methods for preventing low train voltages and managing interference, thereby improving the efficiency, reliability, and passenger comfort associated with commuter trains. An algorithm implementing neural network technology is used to predict low voltages before they occur. Once voltages are predicted, then multiple trains can be controlled to prevent low voltage events. Further, algorithms for managing inference are presented in the present invention. Different types of interference problems are addressed in the present invention such as "Interference During Acceleration", "Interference Near Station Stops", and "Interference During Delay Recovery." Managing such interference avoids unnecessary brake/acceleration cycles during acceleration, immediately before station stops, and after substantial delays. Algorithms are demonstrated to avoid oscillatory brake/acceleration cycles due to interference and to smooth the trajectories of closely following trains. This is achieved by maintaining sufficient following distances to avoid unnecessary braking/accelerating. These methods generate smooth train trajectories, making for a more comfortable ride, and improve train motor reliability by avoiding unnecessary mode-changes between propulsion and braking. These algorithms can also have a favorable impact on traction power system requirements and energy consumption.

Method of managing interference during delay recovery on a train system

DOEpatents

Gordon, Susanna P.; Evans, John A.

2005-12-27

The present invention provides methods for preventing low train voltages and managing interference, thereby improving the efficiency, reliability, and passenger comfort associated with commuter trains. An algorithm implementing neural network technology is used to predict low voltages before they occur. Once voltages are predicted, then multiple trains can be controlled to prevent low voltage events. Further, algorithms for managing inference are presented in the present invention. Different types of interference problems are addressed in the present invention such as "Interference During Acceleration", "Interference Near Station Stops", and "Interference During Delay Recovery." Managing such interference avoids unnecessary brake/acceleration cycles during acceleration, immediately before station stops, and after substantial delays. Algorithms are demonstrated to avoid oscillatory brake/acceleration cycles due to interference and to smooth the trajectories of closely following trains. This is achieved by maintaining sufficient following distances to avoid unnecessary braking/accelerating. These methods generate smooth train trajectories, making for a more comfortable ride, and improve train motor reliability by avoiding unnecessary mode-changes between propulsion and braking. These algorithms can also have a favorable impact on traction power system requirements and energy consumption.

Efficient high density train operations

DOEpatents

Gordon, Susanna P.; Evans, John A.

2001-01-01

The present invention provides methods for preventing low train voltages and managing interference, thereby improving the efficiency, reliability, and passenger comfort associated with commuter trains. An algorithm implementing neural network technology is used to predict low voltages before they occur. Once voltages are predicted, then multiple trains can be controlled to prevent low voltage events. Further, algorithms for managing inference are presented in the present invention. Different types of interference problems are addressed in the present invention such as "Interference. During Acceleration", "Interference Near Station Stops", and "Interference During Delay Recovery." Managing such interference avoids unnecessary brake/acceleration cycles during acceleration, immediately before station stops, and after substantial delays. Algorithms are demonstrated to avoid oscillatory brake/acceleration cycles due to interference and to smooth the trajectories of closely following trains. This is achieved by maintaining sufficient following distances to avoid unnecessary braking/accelerating. These methods generate smooth train trajectories, making for a more comfortable ride, and improve train motor reliability by avoiding unnecessary mode-changes between propulsion and braking. These algorithms can also have a favorable impact on traction power system requirements and energy consumption.

A novel dynamic wavelength bandwidth allocation scheme over OFDMA PONs

NASA Astrophysics Data System (ADS)

Yan, Bo; Guo, Wei; Jin, Yaohui; Hu, Weisheng

2011-12-01

With rapid growth of Internet applications, supporting differentiated service and enlarging system capacity have been new tasks for next generation access system. In recent years, research in OFDMA Passive Optical Networks (PON) has experienced extraordinary development as for its large capacity and flexibility in scheduling. Although much work has been done to solve hardware layer obstacles for OFDMA PON, scheduling algorithm on OFDMA PON system is still under primary discussion. In order to support QoS service on OFDMA PON system, a novel dynamic wavelength bandwidth allocation (DWBA) algorithm is proposed in this paper. Per-stream QoS service is supported in this algorithm. Through simulation, we proved our bandwidth allocation algorithm performs better in bandwidth utilization and differentiate service support.

Efforts toward an autonomous wheelchair - biomed 2011.

PubMed

Barrett, Steven; Streeter, Robert

2011-01-01

An autonomous wheelchair is in development to provide mobility to those with significant physical challenges. The overall goal of the project is to develop a wheelchair that is fully autonomous with the ability to navigate about an environment and negotiate obstacles. As a starting point for the project, we have reversed engineered the joystick control system of an off-the-shelf commercially available wheelchair. The joystick control has been replaced with a microcontroller based system. The microcontroller has the capability to interface with a number of subsystems currently under development including wheel odometers, obstacle avoidance sensors, and ultrasonic-based wall sensors. This paper will discuss the microcontroller based system and provide a detailed system description. Results of this study may be adapted to commercial or military robot control.

Analyzing the Publish-or-Perish Paradigm with Game Theory: The Prisoner's Dilemma and a Possible Escape.

PubMed

Erren, T C; Shaw, D M; Morfeld, P

2016-10-01

The publish-or-perish paradigm is a prevailing facet of science. We apply game theory to show that, under rather weak assumptions, this publication scenario takes the form of a prisoner's dilemma, which constitutes a substantial obstacle to beneficial delayed publication of more complete results. One way of avoiding this obstacle while allowing researchers to establish priority of discoveries would be an updated "pli cacheté", a sealed envelope concept from the 1700s. We describe institutional rules that could additionally favour high-quality work and publications and provide examples of such policies that are already in place. Our analysis should be extended to other publication scenarios and the role of other stakeholders such as scientific journals or sponsors.

Multi-hop path tracing of mobile robot with multi-range image

NASA Astrophysics Data System (ADS)

Choudhury, Ramakanta; Samal, Chandrakanta; Choudhury, Umakanta

2010-02-01

It is well known that image processing depends heavily upon image representation technique . This paper intends to find out the optimal path of mobile robots for a specified area where obstacles are predefined as well as modified. Here the optimal path is represented by using the Quad tree method. Since there has been rising interest in the use of quad tree, we have tried to use the successive subdivision of images into quadrants from which the quad tree is developed. In the quad tree, obstacles-free area and the partial filled area are represented with different notations. After development of quad tree the algorithm is used to find the optimal path by employing neighbor finding technique, with a view to move the robot from the source to destination. The algorithm, here , permeates through the entire tree, and tries to locate the common ancestor for computation. The computation and the algorithm, aim at easing the ability of the robot to trace the optimal path with the help of adjacencies between the neighboring nodes as well as determining such adjacencies in the horizontal, vertical and diagonal directions. In this paper efforts have been made to determine the movement of the adjacent block in the quad tree and to detect the transition between the blocks equal size and finally generate the result.

String tightening as a self-organizing phenomenon.

PubMed

Banerjee, Bonny

2007-09-01

The phenomenon of self-organization has been of special interest to the neural network community throughout the last couple of decades. In this paper, we study a variant of the self-organizing map (SOM) that models the phenomenon of self-organization of the particles forming a string when the string is tightened from one or both of its ends. The proposed variant, called the string tightening self-organizing neural network (STON), can be used to solve certain practical problems, such as computation of shortest homotopic paths, smoothing paths to avoid sharp turns, computation of convex hull, etc. These problems are of considerable interest in computational geometry, robotics path-planning, artificial intelligence (AI) (diagrammatic reasoning), very large scale integration (VLSI) routing, and geographical information systems. Given a set of obstacles and a string with two fixed terminal points in a 2-D space, the STON model continuously tightens the given string until the unique shortest configuration in terms of the Euclidean metric is reached. The STON minimizes the total length of a string on convergence by dynamically creating and selecting feature vectors in a competitive manner. Proof of correctness of this anytime algorithm and experimental results obtained by its deployment have been presented in the paper.

Autonomous Navigation Results from the Mars Exploration Rover (MER) Mission

NASA Technical Reports Server (NTRS)

Maimone, Mark; Johnson, Andrew; Cheng, Yang; Willson, Reg; Matthies, Larry H.

2004-01-01

In January, 2004, the Mars Exploration Rover (MER) mission landed two rovers, Spirit and Opportunity, on the surface of Mars. Several autonomous navigation capabilities were employed in space for the first time in this mission. ]n the Entry, Descent, and Landing (EDL) phase, both landers used a vision system called the, Descent Image Motion Estimation System (DIMES) to estimate horizontal velocity during the last 2000 meters (m) of descent, by tracking features on the ground with a downlooking camera, in order to control retro-rocket firing to reduce horizontal velocity before impact. During surface operations, the rovers navigate autonomously using stereo vision for local terrain mapping and a local, reactive planning algorithm called Grid-based Estimation of Surface Traversability Applied to Local Terrain (GESTALT) for obstacle avoidance. ]n areas of high slip, stereo vision-based visual odometry has been used to estimate rover motion, As of mid-June, Spirit had traversed 3405 m, of which 1253 m were done autonomously; Opportunity had traversed 1264 m, of which 224 m were autonomous. These results have contributed substantially to the success of the mission and paved the way for increased levels of autonomy in future missions.

Multi-mounted X-ray cone-beam computed tomography

NASA Astrophysics Data System (ADS)

Fu, Jian; Wang, Jingzheng; Guo, Wei; Peng, Peng

2018-04-01

As a powerful nondestructive inspection technique, X-ray computed tomography (X-CT) has been widely applied to clinical diagnosis, industrial production and cutting-edge research. Imaging efficiency is currently one of the major obstacles for the applications of X-CT. In this paper, a multi-mounted three dimensional cone-beam X-CT (MM-CBCT) method is reported. It consists of a novel multi-mounted cone-beam scanning geometry and the corresponding three dimensional statistical iterative reconstruction algorithm. The scanning geometry is the most iconic design and significantly different from the current CBCT systems. Permitting the cone-beam scanning of multiple objects simultaneously, the proposed approach has the potential to achieve an imaging efficiency orders of magnitude greater than the conventional methods. Although multiple objects can be also bundled together and scanned simultaneously by the conventional CBCT methods, it will lead to the increased penetration thickness and signal crosstalk. In contrast, MM-CBCT avoids substantially these problems. This work comprises a numerical study of the method and its experimental verification using a dataset measured with a developed MM-CBCT prototype system. This technique will provide a possible solution for the CT inspection in a large scale.

High reliability outdoor sonar prototype based on efficient signal coding.

PubMed

Alvarez, Fernando J; Ureña, Jesús; Mazo, Manuel; Hernández, Alvaro; García, Juan J; de Marziani, Carlos

2006-10-01

Many mobile robots and autonomous vehicles designed for outdoor operation have incorporated ultrasonic sensors in their navigation systems, whose function is mainly to avoid possible collisions with very close obstacles. The use of these systems in more precise tasks requires signal encoding and the incorporation of pulse compression techniques that have already been used with success in the design of high-performance indoor sonars. However, the transmission of ultrasonic encoded signals outdoors entails a new challenge because of the effects of atmospheric turbulence. This phenomenon causes random fluctuations in the phase and amplitude of traveling acoustic waves, a fact that can make the encoded signal completely unrecognizable by its matched receiver. Atmospheric turbulence is investigated in this work, with the aim of determining the conditions under which it is possible to assure the reliable outdoor operation of an ultrasonic pulse compression system. As a result of this analysis, a novel sonar prototype based on complementary sequences coding is developed and experimentally tested. This encoding scheme provides the system with very useful additional features, namely, high robustness to noise, multi-mode operation capability (simultaneous emissions with minimum cross talk interference), and the possibility of applying an efficient detection algorithm that notably decreases the hardware resource requirements.

Honeybees as a model for the study of visually guided flight, navigation, and biologically inspired robotics.

PubMed

Srinivasan, Mandyam V

2011-04-01

Research over the past century has revealed the impressive capacities of the honeybee, Apis mellifera, in relation to visual perception, flight guidance, navigation, and learning and memory. These observations, coupled with the relative ease with which these creatures can be trained, and the relative simplicity of their nervous systems, have made honeybees an attractive model in which to pursue general principles of sensorimotor function in a variety of contexts, many of which pertain not just to honeybees, but several other animal species, including humans. This review begins by describing the principles of visual guidance that underlie perception of the world in three dimensions, obstacle avoidance, control of flight speed, and orchestrating smooth landings. We then consider how navigation over long distances is accomplished, with particular reference to how bees use information from the celestial compass to determine their flight bearing, and information from the movement of the environment in their eyes to gauge how far they have flown. Finally, we illustrate how some of the principles gleaned from these studies are now being used to design novel, biologically inspired algorithms for the guidance of unmanned aerial vehicles.

Feeling the force: how pollen tubes deal with obstacles.

PubMed

Burri, Jan T; Vogler, Hannes; Läubli, Nino F; Hu, Chengzhi; Grossniklaus, Ueli; Nelson, Bradley J

2018-06-15

Physical forces are involved in the regulation of plant development and morphogenesis by translating mechanical stress into the modification of physiological processes, which, in turn, can affect cellular growth. Pollen tubes respond rapidly to external stimuli and provide an ideal system to study the effect of mechanical cues at the single-cell level. Here, pollen tubes were exposed to mechanical stress while monitoring the reconfiguration of their growth and recording the generated forces in real-time. We combined a lab-on-a-chip device with a microelectromechanical systems (MEMS)-based capacitive force sensor to mimic and quantify the forces that are involved in pollen tube navigation upon confronting mechanical obstacles. Several stages of obstacle avoidance were identified, including force perception, growth adjustment and penetration. We have experimentally determined the perceptive force threshold, which is the force threshold at which the pollen tube reacts to an obstacle, for Lilium longiflorum and Arabidopsis thaliana. In addition, the method we developed provides a way to calculate turgor pressure based on force and optical data. Pollen tubes sense physical barriers and actively adjust their growth behavior to overcome them. Furthermore, our system offers an ideal platform to investigate intracellular activity during force perception and growth adaption in tip growing cells. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Avoidance as an obstacle to preventing depression among urban women at high risk for violent trauma.

PubMed

Silverstein, Michael; Kistin, Caroline; Bair-Merritt, Megan; Wiltsey-Stirman, Shannon; Feinberg, Emily; Diaz-Linhart, Yaminette; Sandler, Jenna; Chen, Ning; Cabral, Howard

2016-02-01

The impact of depression interventions is often attenuated in women who have experienced trauma. We explored whether psychological avoidance could explain this phenomenon. We synthesized two pilot randomized trials of problem-solving education (PSE) among a total of 93 urban mothers. Outcomes included depressive symptoms and perceived stress. Mothers with avoidant coping styles experienced an average 1.25 episodes of moderately severe depressive symptoms over 3 months of follow-up, compared to 0.40 episodes among those with non-avoidant coping (adjusted incident rate ratio [aIRR] 2.18; 95 % CI 1.06, 4.48). PSE tended to perform better among mothers with non-avoidant coping. Among mothers with non-avoidant coping, PSE mothers experienced an average 0.24 episodes, compared to 0.58 episodes among non-avoidant controls (aIRR 0.27; 95 % CI 0.05, 1.34). Among mothers with avoidant coping, PSE mothers experienced an average 1.26 episodes, compared to 1.20 episodes among avoidant controls (aIRR 0.76; 95 % CI 0.44, 1.33). This trend toward differential impact persisted when avoidance was measured as a problem-solving style and among traumatized mothers with and without avoidant PTSD symptoms. Further research is warranted to explore the hypothesis that psychological avoidance could explain why certain depression treatment and prevention strategies break down in the presence of trauma.

Modal element method for potential flow in non-uniform ducts: Combining closed form analysis with CFD

NASA Technical Reports Server (NTRS)

Baumeister, Kenneth J.; Baumeister, Joseph F.

1994-01-01

An analytical procedure is presented, called the modal element method, that combines numerical grid based algorithms with eigenfunction expansions developed by separation of variables. A modal element method is presented for solving potential flow in a channel with two-dimensional cylindrical like obstacles. The infinite computational region is divided into three subdomains; the bounded finite element domain, which is characterized by the cylindrical obstacle and the surrounding unbounded uniform channel entrance and exit domains. The velocity potential is represented approximately in the grid based domain by a finite element solution and is represented analytically by an eigenfunction expansion in the uniform semi-infinite entrance and exit domains. The calculated flow fields are in excellent agreement with exact analytical solutions. By eliminating the grid surrounding the obstacle, the modal element method reduces the numerical grid size, employs a more precise far field boundary condition, as well as giving theoretical insight to the interaction of the obstacle with the mean flow. Although the analysis focuses on a specific geometry, the formulation is general and can be applied to a variety of problems as seen by a comparison to companion theories in aeroacoustics and electromagnetics.

Hand Path Priming in Manual Obstacle Avoidance: Evidence for Abstract Spatiotemporal Forms in Human Motor Control

ERIC Educational Resources Information Center

van der Wel, Robrecht P. R. D.; Fleckenstein, Robin M.; Jax, Steven A.; Rosenbaum, David A.

2007-01-01

Previous research suggests that motor equivalence is achieved through reliance on effector-independent spatiotemporal forms. Here the authors report a series of experiments investigating the role of such forms in the production of movement sequences. Participants were asked to complete series of arm movements in time with a metronome and, on some…

Executive Programs for Brazilian Mid-Career Public Managers: Pitfalls and Challenges

ERIC Educational Resources Information Center

Pacheco, Regina Silvia; Franzese, Cibele

2017-01-01

This paper discusses the challenges of professional education for mid-career public managers at graduate level, pointing out pitfalls to avoid and obstacles to face. Analyzing the Brazilian case, the goal is to raise issues that may also be present in other cases. The main argument developed here is that the puzzle faced by graduate programs on…

Unmanned Surface Vehicle Human-Computer Interface for Amphibious Operations

DTIC Science & Technology

2013-08-01

Amy Bolton from 2007 through 2011, with a follow- on effort conducted during 2012 sponsored by LCS Mission Modules Program Office (PMS 420) under the...performance, the researchers conclude that improvements in on -board sensor capabilities and obstacle avoidance systems may still be necessary to safely...38 5.4.2 Phase I – One USV vs. Two USVs with Baseline HCI

AHPCRC - Army High Performance Computing Research Center

DTIC Science & Technology

2008-01-01

University) Birds and insects use complex flapping and twisting wing motions to maneuver, hover, avoid obstacles, and maintain or regain their...vehicles for use in sensing, surveillance, and wireless communications. HPC simulations examine plunging, pitching, and twisting motions of aeroelastic...wings, to optimize the amplitudes and frequencies of flapping and twisting motions for the maximum amount of thrust. Several methods of calculation

Collision Avoidance for UAVs Using Optic Flow Measurement With Line of Sight Rate Equalization and Looming

DTIC Science & Technology

2008-03-01

are arranged in horizon- 14 tal and vertical rows that give it a panoramic view of nearly 360◦. An interesting thing to note is that the fly’s eye...6280–6292, 2005. 18. Joarder, Kunal and Daniel Raviv . “A New Method to Calculate looming for Autonomous Obstacle Avoidance”. IEEE Proceedings of the

Performance testing of collision-avoidance system for power wheelchairs.

PubMed

Lopresti, Edmund F; Sharma, Vinod; Simpson, Richard C; Mostowy, L Casimir

2011-01-01

The Drive-Safe System (DSS) is a collision-avoidance system for power wheelchairs designed to support people with mobility impairments who also have visual, upper-limb, or cognitive impairments. The DSS uses a distributed approach to provide an add-on, shared-control, navigation-assistance solution. In this project, the DSS was tested for engineering goals such as sensor coverage, maximum safe speed, maximum detection distance, and power consumption while the wheelchair was stationary or driven by an investigator. Results indicate that the DSS provided uniform, reliable sensor coverage around the wheelchair; detected obstacles as small as 3.2 mm at distances of at least 1.6 m; and attained a maximum safe speed of 4.2 km/h. The DSS can drive reliably as close as 15.2 cm from a wall, traverse doorways as narrow as 81.3 cm without interrupting forward movement, and reduce wheelchair battery life by only 3%. These results have implications for a practical system to support safe, independent mobility for veterans who acquire multiple disabilities during Active Duty or later in life. These tests indicate that a system utilizing relatively low cost ultrasound, infrared, and force sensors can effectively detect obstacles in the vicinity of a wheelchair.

Perception for mobile robot navigation: A survey of the state of the art

NASA Technical Reports Server (NTRS)

Kortenkamp, David

1994-01-01

In order for mobile robots to navigate safely in unmapped and dynamic environments they must perceive their environment and decide on actions based on those perceptions. There are many different sensing modalities that can be used for mobile robot perception; the two most popular are ultrasonic sonar sensors and vision sensors. This paper examines the state-of-the-art in sensory-based mobile robot navigation. The first issue in mobile robot navigation is safety. This paper summarizes several competing sonar-based obstacle avoidance techniques and compares them. Another issue in mobile robot navigation is determining the robot's position and orientation (sometimes called the robot's pose) in the environment. This paper examines several different classes of vision-based approaches to pose determination. One class of approaches uses detailed, a prior models of the robot's environment. Another class of approaches triangulates using fixed, artificial landmarks. A third class of approaches builds maps using natural landmarks. Example implementations from each of these three classes are described and compared. Finally, the paper presents a completely implemented mobile robot system that integrates sonar-based obstacle avoidance with vision-based pose determination to perform a simple task.

Passivity-based control with collision avoidance for a hub-beam spacecraft

NASA Astrophysics Data System (ADS)

Wen, Hao; Chen, Ti; Jin, Dongping; Hu, Haiyan

2017-01-01

For the application of robotically assembling large space structures, a feedback control law is synthesized for transitional and rotational maneuvers of a 'tug' spacecraft in order to transport a flexible element to a desired position without colliding with other space bodies. The flexible element is treated as a long beam clamped to the 'tug' spacecraft modelled as a rigid hub. First, the physical property of passivity of Euler-Lagrange system is exploited to design the position and attitude controllers by taking a simpler obstacle-free control problem into account. To reduce sensing and actuating requirements, the vibration modes of the beam appendage are supposed to be not directly measured and actuated on. Besides, the requirements of measuring velocities are removed with the aid of a dynamic extension technique. Second, the bounding boxes in the form of super-quadric surfaces are exploited to enclose the maximal extents of the obstacles and the hub-beam spacecraft. The collision avoidance between bounding boxes is achieved by applying additional repulsive force and torque to the spacecraft based on the method of artificial potential field. Finally, the effectiveness of proposed control scheme is numerically demonstrated via case studies.

Interactive-rate Motion Planning for Concentric Tube Robots

PubMed Central

Torres, Luis G.; Baykal, Cenk; Alterovitz, Ron

2014-01-01

Concentric tube robots may enable new, safer minimally invasive surgical procedures by moving along curved paths to reach difficult-to-reach sites in a patient’s anatomy. Operating these devices is challenging due to their complex, unintuitive kinematics and the need to avoid sensitive structures in the anatomy. In this paper, we present a motion planning method that computes collision-free motion plans for concentric tube robots at interactive rates. Our method’s high speed enables a user to continuously and freely move the robot’s tip while the motion planner ensures that the robot’s shaft does not collide with any anatomical obstacles. Our approach uses a highly accurate mechanical model of tube interactions, which is important since small movements of the tip position may require large changes in the shape of the device’s shaft. Our motion planner achieves its high speed and accuracy by combining offline precomputation of a collision-free roadmap with online position control. We demonstrate our interactive planner in a simulated neurosurgical scenario where a user guides the robot’s tip through the environment while the robot automatically avoids collisions with the anatomical obstacles. PMID:25436176

New Algorithm and Software (BNOmics) for Inferring and Visualizing Bayesian Networks from Heterogeneous Big Biological and Genetic Data

PubMed Central

Gogoshin, Grigoriy; Boerwinkle, Eric

2017-01-01

Abstract Bayesian network (BN) reconstruction is a prototypical systems biology data analysis approach that has been successfully used to reverse engineer and model networks reflecting different layers of biological organization (ranging from genetic to epigenetic to cellular pathway to metabolomic). It is especially relevant in the context of modern (ongoing and prospective) studies that generate heterogeneous high-throughput omics datasets. However, there are both theoretical and practical obstacles to the seamless application of BN modeling to such big data, including computational inefficiency of optimal BN structure search algorithms, ambiguity in data discretization, mixing data types, imputation and validation, and, in general, limited scalability in both reconstruction and visualization of BNs. To overcome these and other obstacles, we present BNOmics, an improved algorithm and software toolkit for inferring and analyzing BNs from omics datasets. BNOmics aims at comprehensive systems biology—type data exploration, including both generating new biological hypothesis and testing and validating the existing ones. Novel aspects of the algorithm center around increasing scalability and applicability to varying data types (with different explicit and implicit distributional assumptions) within the same analysis framework. An output and visualization interface to widely available graph-rendering software is also included. Three diverse applications are detailed. BNOmics was originally developed in the context of genetic epidemiology data and is being continuously optimized to keep pace with the ever-increasing inflow of available large-scale omics datasets. As such, the software scalability and usability on the less than exotic computer hardware are a priority, as well as the applicability of the algorithm and software to the heterogeneous datasets containing many data types—single-nucleotide polymorphisms and other genetic/epigenetic/transcriptome variables, metabolite levels, epidemiological variables, endpoints, and phenotypes, etc. PMID:27681505

New Algorithm and Software (BNOmics) for Inferring and Visualizing Bayesian Networks from Heterogeneous Big Biological and Genetic Data.

PubMed

Gogoshin, Grigoriy; Boerwinkle, Eric; Rodin, Andrei S

2017-04-01

Bayesian network (BN) reconstruction is a prototypical systems biology data analysis approach that has been successfully used to reverse engineer and model networks reflecting different layers of biological organization (ranging from genetic to epigenetic to cellular pathway to metabolomic). It is especially relevant in the context of modern (ongoing and prospective) studies that generate heterogeneous high-throughput omics datasets. However, there are both theoretical and practical obstacles to the seamless application of BN modeling to such big data, including computational inefficiency of optimal BN structure search algorithms, ambiguity in data discretization, mixing data types, imputation and validation, and, in general, limited scalability in both reconstruction and visualization of BNs. To overcome these and other obstacles, we present BNOmics, an improved algorithm and software toolkit for inferring and analyzing BNs from omics datasets. BNOmics aims at comprehensive systems biology-type data exploration, including both generating new biological hypothesis and testing and validating the existing ones. Novel aspects of the algorithm center around increasing scalability and applicability to varying data types (with different explicit and implicit distributional assumptions) within the same analysis framework. An output and visualization interface to widely available graph-rendering software is also included. Three diverse applications are detailed. BNOmics was originally developed in the context of genetic epidemiology data and is being continuously optimized to keep pace with the ever-increasing inflow of available large-scale omics datasets. As such, the software scalability and usability on the less than exotic computer hardware are a priority, as well as the applicability of the algorithm and software to the heterogeneous datasets containing many data types-single-nucleotide polymorphisms and other genetic/epigenetic/transcriptome variables, metabolite levels, epidemiological variables, endpoints, and phenotypes, etc.

Power mobility with collision avoidance for older adults: user, caregiver, and prescriber perspectives.

PubMed

Wang, Rosalie H; Korotchenko, Alexandra; Hurd Clarke, Laura; Mortenson, W Ben; Mihailidis, Alex

2013-01-01

Collision avoidance technology has the capacity to facilitate safer mobility among older power mobility users with physical, sensory, and cognitive impairments, thus enabling independence for more users. Little is known about consumers' perceptions of collision avoidance. This article draws on interviews (29 users, 5 caregivers, and 10 prescribers) to examine views on design and utilization of this technology. Data analysis identified three themes: "useful situations or contexts," "technology design issues and real-life application," and "appropriateness of collision avoidance technology for a variety of users." Findings support ongoing development of collision avoidance for older adult users. The majority of participants supported the technology and felt that it might benefit current users and users with visual impairments, but might be unsuitable for people with significant cognitive impairments. Some participants voiced concerns regarding the risk for injury with power mobility use and some identified situations where collision avoidance might be beneficial (driving backward, avoiding dynamic obstacles, negotiating outdoor barriers, and learning power mobility use). Design issues include the need for context awareness, reliability, and user interface specifications. User desire to maintain driving autonomy supports development of collaboratively controlled systems. This research lays the groundwork for future development by illustrating consumer requirements for this technology.

A Cartesian cut cell method for rarefied flow simulations around moving obstacles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dechristé, G., E-mail: Guillaume.Dechriste@math.u-bordeaux1.fr; CNRS, IMB, UMR 5251, F-33400 Talence; Mieussens, L., E-mail: Luc.Mieussens@math.u-bordeaux1.fr

2016-06-01

For accurate simulations of rarefied gas flows around moving obstacles, we propose a cut cell method on Cartesian grids: it allows exact conservation and accurate treatment of boundary conditions. Our approach is designed to treat Cartesian cells and various kinds of cut cells by the same algorithm, with no need to identify the specific shape of each cut cell. This makes the implementation quite simple, and allows a direct extension to 3D problems. Such simulations are also made possible by using an adaptive mesh refinement technique and a hybrid parallel implementation. This is illustrated by several test cases, including amore » 3D unsteady simulation of the Crookes radiometer.« less

Safeguarding a Lunar Rover with Wald's Sequential Probability Ratio Test

NASA Technical Reports Server (NTRS)

Furlong, Michael; Dille, Michael; Wong, Uland; Nefian, Ara

2016-01-01

The virtual bumper is a safeguarding mechanism for autonomous and remotely operated robots. In this paper we take a new approach to the virtual bumper system by using an old statistical test. By using a modified version of Wald's sequential probability ratio test we demonstrate that we can reduce the number of false positive reported by the virtual bumper, thereby saving valuable mission time. We use the concept of sequential probability ratio to control vehicle speed in the presence of possible obstacles in order to increase certainty about whether or not obstacles are present. Our new algorithm reduces the chances of collision by approximately 98 relative to traditional virtual bumper safeguarding without speed control.

Vision based techniques for rotorcraft low altitude flight

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Suorsa, Ray; Smith, Philip

1991-01-01

An overview of research in obstacle detection at NASA Ames Research Center is presented. The research applies techniques from computer vision to automation of rotorcraft navigation. The development of a methodology for detecting the range to obstacles based on the maximum utilization of passive sensors is emphasized. The development of a flight and image data base for verification of vision-based algorithms, and a passive ranging methodology tailored to the needs of helicopter flight are discussed. Preliminary results indicate that it is possible to obtain adequate range estimates except at regions close to the FOE. Closer to the FOE, the error in range increases since the magnitude of the disparity gets smaller, resulting in a low SNR.

Critical Care Nurses' Perceptions of End-of-Life Care Obstacles: Comparative 17-Year Data.

PubMed

Beckstrand, Renea L; Lamoreaux, Nicole; Luthy, Karlen E; Macintosh, Janelle L B

Nurses working in intensive care units (ICUs) frequently care for patients and their families at the end of life (EOL). Providing high-quality EOL care is important for both patients and families, yet ICU nurses face many obstacles that hinder EOL care. Researchers have identified various ICU nurse-perceived obstacles, but no studies have been found addressing the progress that has been made for the last 17 years. The aims of this study were to determine the most common and current obstacles in EOL care as perceived by ICU nurses and then to evaluate whether meaningful changes have occurred since data were first gathered in 1998. A quantitative-qualitative mixed methods design was used. A random, geographically dispersed sample of 2000 members of the American Association of Critical-Care Nurses was surveyed. Five obstacle items increased in mean score and rank as compared with 1999 data including (1) family not understanding what the phrase "lifesaving measures" really means, (2) providing lifesaving measures at families' requests despite patient's advance directive listing no such care, (3) family not accepting patient's poor prognosis, (4) family members fighting about the use of life support, and (5) not enough time to provide EOL care because the nurse is consumed with lifesaving measures attempting to save the patient's life. Five obstacle items decreased in mean score and rank compared with 1999 data including (1) physicians differing in opinion about care of the patient, (2) family and friends who continually call the nurse rather than calling the designated family member, (3) physicians who are evasive and avoid families, (4) nurses having to deal with angry families, and (5) nurses not knowing their patient's wishes regarding continuing with tests and treatments. Obstacles in EOL care, as perceived by critical care nurses, still exist. Family-related obstacles have increased over time. Obstacles related to families may not be easily overcome as each family, dealing with a dying family member in an ICU, likely has not previously experienced a similar situation. On the basis of the current top 5 obstacles, recommendations for possible areas of focus include (1) improved health literacy assessment of families followed by earlier directed, appropriate, and specific EOL information; (2) improved physician/team communication; and (3) ensuring patients' wishes are followed as written. In general, patient- and family-centered care using clear and open EOL communication regarding wishes and desires between patients and families, their physicians, and nurses will help decrease common obstacles, thus improving the quality of EOL care provided to dying patients and families.

KSC-2012-6375

NASA Image and Video Library

2012-12-04

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, hazard avoidance instrumentation it being prepared for installation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Jim Grossmann

KSC-2012-6422

NASA Image and Video Library

2012-12-05

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Dmitri Gerondidakis

KSC-2012-6427

NASA Image and Video Library

2012-12-05

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Dmitri Gerondidakis

KSC-2012-6424

NASA Image and Video Library

2012-12-05

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Dmitri Gerondidakis

KSC-2012-6417

NASA Image and Video Library

2012-12-05

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Dmitri Gerondidakis

KSC-2012-6452

NASA Image and Video Library

2012-12-13

CAPE CANAVERAL, Fla. – A Huey helicopter tests hazard avoidance instrumentation at the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks using the instrument. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Photo credit: NASA/Jim Grossmann

KSC-2012-6419

NASA Image and Video Library

2012-12-05

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Dmitri Gerondidakis

KSC-2012-6425

NASA Image and Video Library

2012-12-05

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Dmitri Gerondidakis

KSC-2012-6420

NASA Image and Video Library

2012-12-05

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Dmitri Gerondidakis

KSC-2012-6374

NASA Image and Video Library

2012-12-04

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Jim Grossmann

KSC-2012-6421

NASA Image and Video Library

2012-12-05

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Dmitri Gerondidakis

KSC-2012-6376

NASA Image and Video Library

2012-12-04

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a technician installs hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Jim Grossmann

KSC-2012-6412

NASA Image and Video Library

2012-12-05

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Dmitri Gerondidakis

KSC-2012-6414

NASA Image and Video Library

2012-12-05

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Dmitri Gerondidakis

KSC-2012-6423

NASA Image and Video Library

2012-12-05

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Dmitri Gerondidakis

KSC-2012-6413

NASA Image and Video Library

2012-12-05

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Dmitri Gerondidakis

KSC-2012-6373

NASA Image and Video Library

2012-12-04

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Jim Grossmann

KSC-2012-6377

NASA Image and Video Library

2012-12-04

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a technician tests hazard avoidance instrumentation recently installed on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Jim Grossmann

KSC-2012-6416

NASA Image and Video Library

2012-12-05

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Dmitri Gerondidakis

KSC-2012-6372

NASA Image and Video Library

2012-12-04

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Jim Grossmann

KSC-2012-6415

NASA Image and Video Library

2012-12-05

CAPE CANAVERAL, Fla. – Near the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida, a space agency team installed and tested hazard avoidance instrumentation on a Huey helicopter. Led by the Johnson Space Center and supported by Jet Propulsion Laboratory and Langley Research Center, the Autonomous Landing Hazard Avoidance Technology, or ALHAT, laser system provides a planetary lander the ability to precisely land safely on a surface while detecting any dangerous obstacles such as rocks, holes and slopes. Just north of Kennedy's Shuttle Landing Facility runway, a rock- and crater-filled planetary scape has been built so engineers can test the ability to negotiate away from risks. Photo credit: NASA/Dmitri Gerondidakis