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.

Autonomous path-planning navigation system for site characterization

NASA Astrophysics Data System (ADS)

Rankin, Arturo L.; Crane, Carl D., III; Armstrong, David G., II; Nease, Allen D.; Brown, H. Edward

1996-05-01

The location and removal of buried munitions is an important yet hazardous task. Current development is aimed at performing both the ordnance location and removal tasks autonomously. An autonomous survey vehicle (ASV) named the Gator has been developed at the Center for Intelligent Machines and Robotics, under the direction of Wright Laboratory, Tyndall Air Force Base, Florida, and the Navy Explosive Ordnance Disposal Technology Division, Indian Head, Maryland. The primary task of the survey vehicle is to autonomously traverse an off-road site, towing behind it a trailer containing a sensor package capable of characterizing the sub-surface contents. Achieving 00 percent coverage of the site is critical to fully characterizing the site. This paper presents a strategy for planning efficient paths for the survey vehicle that guarantees near-complete coverage of a site. A small library of three in-house developed path planners are reviewed. A strategy is also presented to keep the trailer on-path and to calculate the percent of coverage of a site with a resolution of 0.01 m2. All of the algorithms discussed in this paper were initially developed in simulation on a Silicon Graphics computer and subsequently implemented on the survey vehicle.

Trajectory Generation and Path Planning for Autonomous Aerobots

NASA Technical Reports Server (NTRS)

Sharma, Shivanjli; Kulczycki, Eric A.; Elfes, Alberto

2007-01-01

This paper presents global path planning algorithms for the Titan aerobot based on user defined waypoints in 2D and 3D space. The algorithms were implemented using information obtained through a planner user interface. The trajectory planning algorithms were designed to accurately represent the aerobot's characteristics, such as minimum turning radius. Additionally, trajectory planning techniques were implemented to allow for surveying of a planar area based solely on camera fields of view, airship altitude, and the location of the planar area's perimeter. The developed paths allow for planar navigation and three-dimensional path planning. These calculated trajectories are optimized to produce the shortest possible path while still remaining within realistic bounds of airship dynamics.

Integration of Hierarchical Goal Network Planning and Autonomous Path Planning

DTIC Science & Technology

2016-03-01

Conference on Robotics and Automation (ICRA); 2010 May 3– 7; Anchorage, AK. p. 2902–2908. 4. Ayan NF, Kuter U, Yaman F, Goldman RP. Hotride...DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release; distribution unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT Automated planning has...world robotic systems. This report documents work to integrate a hierarchical goal network planning algorithm with low-level path planning. The system

Autonomous search and surveillance with small fixed wing aircraft

NASA Astrophysics Data System (ADS)

McGee, Timothy Garland

Small unmanned aerial vehicles (UAVs) have the potential to act as low cost tools in a variety of both civilian and military applications including traffic monitoring, border patrol, and search and rescue. While most current operational UAV systems require human operators, advances in autonomy will allow these systems to reach their full potential as sensor platforms. This dissertation specifically focuses on developing advanced control, path planning, search, and image processing techniques that allow small fixed wing aircraft to autonomously collect data. The problems explored were motivated by experience with the development and experimental flight testing of a fleet of small autonomous fixed wing aircraft. These issues, which have not been fully addressed in past work done on ground vehicles or autonomous helicopters, include the influence of wind and turning rate constraints, the non-negligible velocity of ground targets relative to the aircraft velocity, and limitations on sensor size and processing power on small vehicles. Several contributions for the autonomous operation of small fixed wing aircraft are presented. Several sliding surface controllers are designed which extend previous techniques to include variable sliding surface coefficients and the use of spatial vehicle dynamics. These advances eliminate potential singularities in the control laws to follow spatially defined paths and allow smooth transition between controllers. The optimal solution for the problem of path planning through an ordered set of points for an aircraft with a bounded turning rate in the presence of a constant wind is then discussed. Path planning strategies are also explored to guarantee that a searcher will travel within sensing distance of a mobile ground target. This work assumes only a maximum velocity of the target and is designed to succeed for any possible path of the target. Closed-loop approximations of both the path planning and search techniques, using the sliding surface controllers already discussed, are also studied. Finally, a novel method is presented to detect obstacles by segmenting an image into sky and non-sky regions. The feasibility of this method is demonstrated experimentally on an aircraft test bed.

Application of ant colony algorithm in path planning of the data center room robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Ma, Jianming; Wang, Ying

2017-05-01

According to the Internet Data Center (IDC) room patrol robot as the background, the robot in the search path of autonomous obstacle avoidance and path planning ability, worked out in advance of the robot room patrol mission. The simulation experimental results show that the improved ant colony algorithm for IDC room patrol robot obstacle avoidance planning, makes the robot along an optimal or suboptimal and safe obstacle avoidance path to reach the target point to complete the task. To prove the feasibility of the method.

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.

Multiresolution motion planning for autonomous agents via wavelet-based cell decompositions.

PubMed

Cowlagi, Raghvendra V; Tsiotras, Panagiotis

2012-10-01

We present a path- and motion-planning scheme that is "multiresolution" both in the sense of representing the environment with high accuracy only locally and in the sense of addressing the vehicle kinematic and dynamic constraints only locally. The proposed scheme uses rectangular multiresolution cell decompositions, efficiently generated using the wavelet transform. The wavelet transform is widely used in signal and image processing, with emerging applications in autonomous sensing and perception systems. The proposed motion planner enables the simultaneous use of the wavelet transform in both the perception and in the motion-planning layers of vehicle autonomy, thus potentially reducing online computations. We rigorously prove the completeness of the proposed path-planning scheme, and we provide numerical simulation results to illustrate its efficacy.

Vehicle path-planning in three dimensions using optics analogs for optimizing visibility and energy cost

NASA Technical Reports Server (NTRS)

Rowe, Neil C.; Lewis, David H.

1989-01-01

Path planning is an important issue for space robotics. Finding safe and energy-efficient paths in the presence of obstacles and other constraints can be complex although important. High-level (large-scale) path planning for robotic vehicles was investigated in three-dimensional space with obstacles, accounting for: (1) energy costs proportional to path length; (2) turn costs where paths change trajectory abruptly; and (3) safety costs for the danger associated with traversing a particular path due to visibility or invisibility from a fixed set of observers. Paths optimal with respect to these cost factors are found. Autonomous or semi-autonomous vehicles were considered operating either in a space environment around satellites and space platforms, or aircraft, spacecraft, or smart missiles operating just above lunar and planetary surfaces. One class of applications concerns minimizing detection, as for example determining the best way to make complex modifications to a satellite without being observed by hostile sensors; another example is verifying there are no paths (holes) through a space defense system. Another class of applications concerns maximizing detection, as finding a good trajectory between mountain ranges of a planet while staying reasonably close to the surface, or finding paths for a flight between two locations that maximize the average number of triangulation points available at any time along the path.

A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles

PubMed Central

2017-01-01

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently. PMID:28255297

A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles.

PubMed

Ni, Jianjun; Wu, Liuying; Shi, Pengfei; Yang, Simon X

2017-01-01

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.

Search Problems in Mission Planning and Navigation of Autonomous Aircraft. M.S. Thesis

NASA Technical Reports Server (NTRS)

Krozel, James A.

1988-01-01

An architecture for the control of an autonomous aircraft is presented. The architecture is a hierarchical system representing an anthropomorphic breakdown of the control problem into planner, navigator, and pilot systems. The planner system determines high level global plans from overall mission objectives. This abstract mission planning is investigated by focusing on the Traveling Salesman Problem with variations on local and global constraints. Tree search techniques are applied including the breadth first, depth first, and best first algorithms. The minimum-column and row entries for the Traveling Salesman Problem cost matrix provides a powerful heuristic to guide these search techniques. Mission planning subgoals are directed from the planner to the navigator for planning routes in mountainous terrain with threats. Terrain/threat information is abstracted into a graph of possible paths for which graph searches are performed. It is shown that paths can be well represented by a search graph based on the Voronoi diagram of points representing the vertices of mountain boundaries. A comparison of Dijkstra's dynamic programming algorithm and the A* graph search algorithm from artificial intelligence/operations research is performed for several navigation path planning examples. These examples illustrate paths that minimize a combination of distance and exposure to threats. Finally, the pilot system synthesizes the flight trajectory by creating the control commands to fly the aircraft.

Research on global path planning based on ant colony optimization for AUV

NASA Astrophysics Data System (ADS)

Wang, Hong-Jian; Xiong, Wei

2009-03-01

Path planning is an important issue for autonomous underwater vehicles (AUVs) traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning using large-scale chart data was studied, and the principles of ant colony optimization (ACO) were applied. This paper introduced the idea of a visibility graph based on the grid workspace model. It also brought a series of pheromone updating rules for the ACO planning algorithm. The operational steps of the ACO algorithm are proposed as a model for a global path planning method for AUV. To mimic the process of smoothing a planned path, a cutting operator and an insertion-point operator were designed. Simulation results demonstrated that the ACO algorithm is suitable for global path planning. The system has many advantages, including that the operating path of the AUV can be quickly optimized, and it is shorter, safer, and smoother. The prototype system successfully demonstrated the feasibility of the concept, proving it can be applied to surveys of unstructured unmanned environments.

Sampling-based real-time motion planning under state uncertainty for autonomous micro-aerial vehicles in GPS-denied environments.

PubMed

Li, Dachuan; Li, Qing; Cheng, Nong; Song, Jingyan

2014-11-18

This paper presents a real-time motion planning approach for autonomous vehicles with complex dynamics and state uncertainty. The approach is motivated by the motion planning problem for autonomous vehicles navigating in GPS-denied dynamic environments, which involves non-linear and/or non-holonomic vehicle dynamics, incomplete state estimates, and constraints imposed by uncertain and cluttered environments. To address the above motion planning problem, we propose an extension of the closed-loop rapid belief trees, the closed-loop random belief trees (CL-RBT), which incorporates predictions of the position estimation uncertainty, using a factored form of the covariance provided by the Kalman filter-based estimator. The proposed motion planner operates by incrementally constructing a tree of dynamically feasible trajectories using the closed-loop prediction, while selecting candidate paths with low uncertainty using efficient covariance update and propagation. The algorithm can operate in real-time, continuously providing the controller with feasible paths for execution, enabling the vehicle to account for dynamic and uncertain environments. Simulation results demonstrate that the proposed approach can generate feasible trajectories that reduce the state estimation uncertainty, while handling complex vehicle dynamics and environment constraints.

Sampling-Based Real-Time Motion Planning under State Uncertainty for Autonomous Micro-Aerial Vehicles in GPS-Denied Environments

PubMed Central

Li, Dachuan; Li, Qing; Cheng, Nong; Song, Jingyan

2014-01-01

This paper presents a real-time motion planning approach for autonomous vehicles with complex dynamics and state uncertainty. The approach is motivated by the motion planning problem for autonomous vehicles navigating in GPS-denied dynamic environments, which involves non-linear and/or non-holonomic vehicle dynamics, incomplete state estimates, and constraints imposed by uncertain and cluttered environments. To address the above motion planning problem, we propose an extension of the closed-loop rapid belief trees, the closed-loop random belief trees (CL-RBT), which incorporates predictions of the position estimation uncertainty, using a factored form of the covariance provided by the Kalman filter-based estimator. The proposed motion planner operates by incrementally constructing a tree of dynamically feasible trajectories using the closed-loop prediction, while selecting candidate paths with low uncertainty using efficient covariance update and propagation. The algorithm can operate in real-time, continuously providing the controller with feasible paths for execution, enabling the vehicle to account for dynamic and uncertain environments. Simulation results demonstrate that the proposed approach can generate feasible trajectories that reduce the state estimation uncertainty, while handling complex vehicle dynamics and environment constraints. PMID:25412217

Mission-directed path planning for planetary rover exploration

NASA Astrophysics Data System (ADS)

Tompkins, Paul

2005-07-01

Robotic rovers uniquely benefit planetary exploration---they enable regional exploration with the precision of in-situ measurements, a combination impossible from an orbiting spacecraft or fixed lander. Mission planning for planetary rover exploration currently utilizes sophisticated software for activity planning and scheduling, but simplified path planning and execution approaches tailored for localized operations to individual targets. This approach is insufficient for the investigation of multiple, regionally distributed targets in a single command cycle. Path planning tailored for this task must consider the impact of large scale terrain on power, speed and regional access; the effect of route timing on resource availability; the limitations of finite resource capacity and other operational constraints on vehicle range and timing; and the mutual influence between traverses and upstream and downstream stationary activities. Encapsulating this reasoning in an efficient autonomous planner would allow a rover to continue operating rationally despite significant deviations from an initial plan. This research presents mission-directed path planning that enables an autonomous, strategic reasoning capability for robotic explorers. Planning operates in a space of position, time and energy. Unlike previous hierarchical approaches, it treats these dimensions simultaneously to enable globally-optimal solutions. The approach calls on a near incremental search algorithm designed for planning and re-planning under global constraints, in spaces of higher than two dimensions. Solutions under this method specify routes that avoid terrain obstacles, optimize the collection and use of rechargable energy, satisfy local and global mission constraints, and account for the time and energy of interleaved mission activities. Furthermore, the approach efficiently re-plans in response to updates in vehicle state and world models, and is well suited to online operation aboard a robot. Simulations exhibit that the new methodology succeeds where conventional path planners would fail. Three planetary-relevant field experiments demonstrate the power of mission-directed path planning in directing actual exploration robots. Offline mission-directed planning sustained a solar-powered rover in a 24-hour sun-synchronous traverse. Online planning and re-planning enabled full navigational autonomy of over 1 kilometer, and supported the execution of science activities distributed over hundreds of meters.

Mobile transporter path planning

NASA Technical Reports Server (NTRS)

Baffes, Paul; Wang, Lui

1990-01-01

The use of a genetic algorithm (GA) for solving the mobile transporter path planning problem is investigated. The mobile transporter is a traveling robotic vehicle proposed for the space station which must be able to reach any point of the structure autonomously. Elements of the genetic algorithm are explored in both a theoretical and experimental sense. Specifically, double crossover, greedy crossover, and tournament selection techniques are examined. Additionally, the use of local optimization techniques working in concert with the GA are also explored. Recent developments in genetic algorithm theory are shown to be particularly effective in a path planning problem domain, though problem areas can be cited which require more research.

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

Safe Maritime Autonomous Path Planning in a High Sea State

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Quadrelli, Marco; Huntsberger, Terrance L.

2014-01-01

This paper presents a path planning method for sea surface vehicles that prevents capsizing and bow-diving in a high sea-state. A key idea is to use response amplitude operators (RAOs) or, in control terminology, the transfer functions from a sea state to a vessel's motion, in order to find a set of speeds and headings that results in excessive pitch and roll oscillations. This information is translated to arithmetic constraints on the ship's velocity, which are passed to a model predictive control (MPC)-based path planner to find a safe and optimal path that achieves specified goals. An obstacle avoidance capability is also added to the path planner. The proposed method is demonstrated by simulations.

Very fast motion planning for highly dexterous-articulated robots

NASA Technical Reports Server (NTRS)

Challou, Daniel J.; Gini, Maria; Kumar, Vipin

1994-01-01

Due to the inherent danger of space exploration, the need for greater use of teleoperated and autonomous robotic systems in space-based applications has long been apparent. Autonomous and semi-autonomous robotic devices have been proposed for carrying out routine functions associated with scientific experiments aboard the shuttle and space station. Finally, research into the use of such devices for planetary exploration continues. To accomplish their assigned tasks, all such autonomous and semi-autonomous devices will require the ability to move themselves through space without hitting themselves or the objects which surround them. In space it is important to execute the necessary motions correctly when they are first attempted because repositioning is expensive in terms of both time and resources (e.g., fuel). Finally, such devices will have to function in a variety of different environments. Given these constraints, a means for fast motion planning to insure the correct movement of robotic devices would be ideal. Unfortunately, motion planning algorithms are rarely used in practice because of their computational complexity. Fast methods have been developed for detecting imminent collisions, but the more general problem of motion planning remains computationally intractable. However, in this paper we show how the use of multicomputers and appropriate parallel algorithms can substantially reduce the time required to synthesize paths for dexterous articulated robots with a large number of joints. We have developed a parallel formulation of the Randomized Path Planner proposed by Barraquand and Latombe. We have shown that our parallel formulation is capable of formulating plans in a few seconds or less on various parallel architectures including: the nCUBE2 multicomputer with up to 1024 processors (nCUBE2 is a registered trademark of the nCUBE corporation), and a network of workstations.

Spatial abstraction for autonomous robot navigation.

PubMed

Epstein, Susan L; Aroor, Anoop; Evanusa, Matthew; Sklar, Elizabeth I; Parsons, Simon

2015-09-01

Optimal navigation for a simulated robot relies on a detailed map and explicit path planning, an approach problematic for real-world robots that are subject to noise and error. This paper reports on autonomous robots that rely on local spatial perception, learning, and commonsense rationales instead. Despite realistic actuator error, learned spatial abstractions form a model that supports effective travel.

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.

Autonomous Robot Navigation in Human-Centered Environments Based on 3D Data Fusion

NASA Astrophysics Data System (ADS)

Steinhaus, Peter; Strand, Marcus; Dillmann, Rüdiger

2007-12-01

Efficient navigation of mobile platforms in dynamic human-centered environments is still an open research topic. We have already proposed an architecture (MEPHISTO) for a navigation system that is able to fulfill the main requirements of efficient navigation: fast and reliable sensor processing, extensive global world modeling, and distributed path planning. Our architecture uses a distributed system of sensor processing, world modeling, and path planning units. In this arcticle, we present implemented methods in the context of data fusion algorithms for 3D world modeling and real-time path planning. We also show results of the prototypic application of the system at the museum ZKM (center for art and media) in Karlsruhe.

Autonomous Path Planning for On-Orbit Servicing Vehicles

NASA Astrophysics Data System (ADS)

McInnes, C. R.

On-orbit servicing has long been considered as a means of reducing mission costs. While automated on-orbit servicing of satellites in LEO and GEO has yet to be realised, the International Space Station (ISS) will require servicing in a number of forms for re-supply, external visual inspection and maintenance. This paper will discuss a unified approach to path planning for such servicing vehicles using artificial potential field methods. In particular, path constrained rendezvous and docking of the ESA Automated Transfer Vehicle (ATV) at the ISS will be investigated as will mission and path planning tools for the Daimler-Chrysler Aerospace ISS Inspector free-flying camera. Future applications for free-flying microcameras and co-operative control between multiple free-flyers for on-orbit assembly will also be considered.

Using Planning, Scheduling and Execution for Autonomous Mars Rover Operations

NASA Technical Reports Server (NTRS)

Estlin, Tara A.; Gaines, Daniel M.; Chouinard, Caroline M.; Fisher, Forest W.; Castano, Rebecca; Judd, Michele J.; Nesnas, Issa A.

2006-01-01

With each new rover mission to Mars, rovers are traveling significantly longer distances. This distance increase raises not only the opportunities for science data collection, but also amplifies the amount of environment and rover state uncertainty that must be handled in rover operations. This paper describes how planning, scheduling and execution techniques can be used onboard a rover to autonomously generate and execute rover activities and in particular to handle new science opportunities that have been identified dynamically. We also discuss some of the particular challenges we face in supporting autonomous rover decision-making. These include interaction with rover navigation and path-planning software and handling large amounts of uncertainty in state and resource estimations. Finally, we describe our experiences in testing this work using several Mars rover prototypes in a realistic environment.

Experiments in autonomous robotics

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

Hamel, W.R.

1987-01-01

The Center for Engineering Systems Advanced Research (CESAR) is performing basic research in autonomous robotics for energy-related applications in hazardous environments. The CESAR research agenda includes a strong experimental component to assure practical evaluation of new concepts and theories. An evolutionary sequence of mobile research robots has been planned to support research in robot navigation, world sensing, and object manipulation. A number of experiments have been performed in studying robot navigation and path planning with planar sonar sensing. Future experiments will address more complex tasks involving three-dimensional sensing, dexterous manipulation, and human-scale operations.

Mobile robots IV; Proceedings of the Meeting, Philadelphia, PA, Nov. 6, 7, 1989

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

Wolfe, W.J.; Chun, W.H.

1990-01-01

The present conference on mobile robot systems discusses high-speed machine perception based on passive sensing, wide-angle optical ranging, three-dimensional path planning for flying/crawling robots, navigation of autonomous mobile intelligence in an unstructured natural environment, mechanical models for the locomotion of a four-articulated-track robot, a rule-based command language for a semiautonomous Mars rover, and a computer model of the structured light vision system for a Mars rover. Also discussed are optical flow and three-dimensional information for navigation, feature-based reasoning trail detection, a symbolic neural-net production system for obstacle avoidance and navigation, intelligent path planning for robot navigation in an unknown environment,more » behaviors from a hierarchical control system, stereoscopic TV systems, the REACT language for autonomous robots, and a man-amplifying exoskeleton.« less

Autonomous underwater vehicle adaptive path planning for target classification

NASA Astrophysics Data System (ADS)

Edwards, Joseph R.; Schmidt, Henrik

2002-11-01

Autonomous underwater vehicles (AUVs) are being rapidly developed to carry sensors into the sea in ways that have previously not been possible. The full use of the vehicles, however, is still not near realization due to lack of the true vehicle autonomy that is promised in the label (AUV). AUVs today primarily attempt to follow as closely as possible a preplanned trajectory. The key to increasing the autonomy of the AUV is to provide the vehicle with a means to make decisions based on its sensor receptions. The current work examines the use of active sonar returns from mine-like objects (MLOs) as a basis for sensor-based adaptive path planning, where the path planning objective is to discriminate between real mines and rocks. Once a target is detected in the mine hunting phase, the mine classification phase is initialized with a derivative cost function to emphasize signal differences and enhance classification capability. The AUV moves adaptively to minimize the cost function. The algorithm is verified using at-sea data derived from the joint MIT/SACLANTCEN GOATS experiments and advanced acoustic simulation using SEALAB. The mission oriented operating system (MOOS) real-time simulator is then used to test the onboard implementation of the algorithm.

Navigation of military and space unmanned ground vehicles in unstructured terrains

NASA Technical Reports Server (NTRS)

Lescoe, Paul; Lavery, David; Bedard, Roger

1991-01-01

Development of unmanned vehicles for local navigation in terrains unstructured by humans is reviewed. Modes of navigation include teleoperation or remote control, computer assisted remote driving (CARD), and semiautonomous navigation (SAN). A first implementation of a CARD system was successfully tested using the Robotic Technology Test Vehicle developed by Jet Propulsion Laboratory. Stereo pictures were transmitted to a remotely located human operator, who performed the sensing, perception, and planning functions of navigation. A computer provided range and angle measurements and the path plan was transmitted to the vehicle which autonomously executed the path. This implementation is to be enhanced by providing passive stereo vision and a reflex control system for autonomously stopping the vehicle if blocked by an obstacle. SAN achievements include implementation of a navigation testbed on a six wheel, three-body articulated rover vehicle, development of SAN algorithms and code, integration of SAN software onto the vehicle, and a successful feasibility demonstration that represents a step forward towards the technology required for long-range exploration of the lunar or Martian surface. The vehicle includes a passive stereo vision system with real-time area-based stereo image correlation, a terrain matcher, a path planner, and a path execution planner.

Context Aware TCP for Intelligence, Surveillance and Reconnaissance Missions on Autonomous Platforms

DTIC Science & Technology

2014-10-08

under the Unmanned Vehicle Experimental Communications Testbed (UVECT) flight test plan and were done over the Stockbridge Research Facility in the...sure the payload did not interfere with the command and control systems of the aircraft several flight paths were selected to exert the link and the...throughput from data source to destination. Figure 1 shows the flight path of a small RPA in a PoL flight path scenario. The change of SNR

A Descent Rate Control Approach to Developing an Autonomous Descent Vehicle

NASA Astrophysics Data System (ADS)

Fields, Travis D.

Circular parachutes have been used for aerial payload/personnel deliveries for over 100 years. In the past two decades, significant work has been done to improve the landing accuracies of cargo deliveries for humanitarian and military applications. This dissertation discusses the approach developed in which a circular parachute is used in conjunction with an electro-mechanical reefing system to manipulate the landing location. Rather than attempt to steer the autonomous descent vehicle directly, control of the landing location is accomplished by modifying the amount of time spent in a particular wind layer. Descent rate control is performed by reversibly reefing the parachute canopy. The first stage of the research investigated the use of a single actuation during descent (with periodic updates), in conjunction with a curvilinear target. Simulation results using real-world wind data are presented, illustrating the utility of the methodology developed. Additionally, hardware development and flight-testing of the single actuation autonomous descent vehicle are presented. The next phase of the research focuses on expanding the single actuation descent rate control methodology to incorporate a multi-actuation path-planning system. By modifying the parachute size throughout the descent, the controllability of the system greatly increases. The trajectory planning methodology developed provides a robust approach to accurately manipulate the landing location of the vehicle. The primary benefits of this system are the inherent robustness to release location errors and the ability to overcome vehicle uncertainties (mass, parachute size, etc.). A separate application of the path-planning methodology is also presented. An in-flight path-prediction system was developed for use in high-altitude ballooning by utilizing the path-planning methodology developed for descent vehicles. The developed onboard system improves landing location predictions in-flight using collected flight information during the ascent and descent. Simulation and real-world flight tests (using the developed low-cost hardware) demonstrate the significance of the improvements achievable when flying the developed system.

Enabling Autonomous Rover Science through Dynamic Planning and Scheduling

NASA Technical Reports Server (NTRS)

Estlin, Tara A.; Gaines, Daniel; Chouinard, Caroline; Fisher, Forest; Castano, Rebecca; Judd, Michele; Nesnas, Issa

2005-01-01

This paper describes how dynamic planning and scheduling techniques can be used onboard a rover to autonomously adjust rover activities in support of science goals. These goals could be identified by scientists on the ground or could be identified by onboard data-analysis software. Several different types of dynamic decisions are described, including the handling of opportunistic science goals identified during rover traverses, preserving high priority science targets when resources, such as power, are unexpectedly over-subscribed, and dynamically adding additional, ground-specified science targets when rover actions are executed more quickly than expected. After describing our specific system approach, we discuss some of the particular challenges we have examined to support autonomous rover decision-making. These include interaction with rover navigation and path-planning software and handling large amounts of uncertainty in state and resource estimations.

Autonomous Vehicle Mission Planning Using AI (Artificial Intelligence) Techniques.

DTIC Science & Technology

1985-12-01

it uses are declarative patterns that encode facts about how goals may give rise to - . plans. The program processes a story a sentence at a time...the planning process. By separating the knowledge about how to plan from the specific domain knowledge, an understander can use this knowledge about how ...path planning program developed in a previous thesis effort will be incorporated into the overall program in order to demonstrate the operating system

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.

Levels of Autonomy and Autonomous System Performance Assessment for Intelligent Unmanned Systems

DTIC Science & Technology

2014-04-01

LIDAR and camera sensors that is driven entirely by teleoperation would be AL 0. If that same robot used its LIDAR and camera data to generate a...obstacle detection, mapping, path planning 3 CMMAD semi- autonomous counter- mine system (Few 2010) Talon UGV, camera, LIDAR , metal detector...NCAP framework are performed on individual UMS components and do not require mission level evaluations. For example, bench testing of camera, LIDAR

Lagrangian coherent structure assisted path planning for transoceanic autonomous underwater vehicle missions.

PubMed

Ramos, A G; García-Garrido, V J; Mancho, A M; Wiggins, S; Coca, J; Glenn, S; Schofield, O; Kohut, J; Aragon, D; Kerfoot, J; Haskins, T; Miles, T; Haldeman, C; Strandskov, N; Allsup, B; Jones, C; Shapiro, J

2018-03-15

Transoceanic Gliders are Autonomous Underwater Vehicles (AUVs) for which there is a developing and expanding range of applications in open-seas research, technology and underwater clean transport. Mature glider autonomy, operating depth (0-1000 meters) and low energy consumption without a CO 2 footprint enable evolutionary access across ocean basins. Pursuant to the first successful transatlantic glider crossing in December 2009, the Challenger Mission has opened the door to long-term, long-distance routine transoceanic AUV missions. These vehicles, which glide through the water column between 0 and 1000 meters depth, are highly sensitive to the ocean current field. Consequently, it is essential to exploit the complex space-time structure of the ocean current field in order to plan a path that optimizes scientific payoff and navigation efficiency. This letter demonstrates the capability of dynamical system theory for achieving this goal by realizing the real-time navigation strategy for the transoceanic AUV named Silbo, which is a Slocum deep-glider (0-1000 m), that crossed the North Atlantic from April 2016 to March 2017. Path planning in real time based on this approach has facilitated an impressive speed up of the AUV to unprecedented velocities resulting in major battery savings on the mission, offering the potential for routine transoceanic long duration missions.

Real-time Collision Avoidance and Path Optimizer for Semi-autonomous UAVs.

NASA Astrophysics Data System (ADS)

Hawary, A. F.; Razak, N. A.

2018-05-01

Whilst UAV offers a potentially cheaper and more localized observation platform than current satellite or land-based approaches, it requires an advance path planner to reveal its true potential, particularly in real-time missions. Manual control by human will have limited line-of-sights and prone to errors due to careless and fatigue. A good alternative solution is to equip the UAV with semi-autonomous capabilities that able to navigate via a pre-planned route in real-time fashion. In this paper, we propose an easy-and-practical path optimizer based on the classical Travelling Salesman Problem and adopts a brute force search method to re-optimize the route in the event of collisions using range finder sensor. The former utilizes a Simple Genetic Algorithm and the latter uses Nearest Neighbour algorithm. Both algorithms are combined to optimize the route and avoid collision at once. Although many researchers proposed various path planning algorithms, we find that it is difficult to integrate on a basic UAV model and often lacks of real-time collision detection optimizer. Therefore, we explore a practical benefit from this approach using on-board Arduino and Ardupilot controllers by manually emulating the motion of an actual UAV model prior to test on the flying site. The result showed that the range finder sensor provides a real-time data to the algorithm to find a collision-free path and eventually optimized the route successfully.

Autonomous terrain characterization and modelling for dynamic control of unmanned vehicles

NASA Technical Reports Server (NTRS)

Talukder, A.; Manduchi, R.; Castano, R.; Owens, K.; Matthies, L.; Castano, A.; Hogg, R.

2002-01-01

This end-to-end obstacle negotiation system is envisioned to be useful in optimized path planning and vehicle navigation in terrain conditions cluttered with vegetation, bushes, rocks, etc. Results on natural terrain with various natural materials are presented.

Information surfing with the JHU/APL coherent imager

NASA Astrophysics Data System (ADS)

Ratto, Christopher R.; Shipley, Kara R.; Beagley, Nathaniel; Wolfe, Kevin C.

2015-05-01

The ability to perform remote forensics in situ is an important application of autonomous undersea vehicles (AUVs). Forensics objectives may include remediation of mines and/or unexploded ordnance, as well as monitoring of seafloor infrastructure. At JHU/APL, digital holography is being explored for the potential application to underwater imaging and integration with an AUV. In previous work, a feature-based approach was developed for processing the holographic imagery and performing object recognition. In this work, the results of the image processing method were incorporated into a Bayesian framework for autonomous path planning referred to as information surfing. The framework was derived assuming that the location of the object of interest is known a priori, but the type of object and its pose are unknown. The path-planning algorithm adaptively modifies the trajectory of the sensing platform based on historical performance of object and pose classification. The algorithm is called information surfing because the direction of motion is governed by the local information gradient. Simulation experiments were carried out using holographic imagery collected from submerged objects. The autonomous sensing algorithm was compared to a deterministic sensing CONOPS, and demonstrated improved accuracy and faster convergence in several cases.

Toward Autonomous Multi-floor Exploration: Ascending Stairway Localization and Modeling

DTIC Science & Technology

2013-03-01

robots have traditionally been restricted to single floors of a building or outdoor areas free of abrupt elevation changes such as curbs and stairs ...solution to this problem and is motivated by the rich potential of an autonomous ground robot that can climb stairs while exploring a multi-floor...parameters of the stairways, the robot could plan a path that traverses the stairs in order to explore the frontier at other elevations that were previously

Reasoning on the Self-Organizing Incremental Associative Memory for Online Robot Path Planning

NASA Astrophysics Data System (ADS)

Kawewong, Aram; Honda, Yutaro; Tsuboyama, Manabu; Hasegawa, Osamu

Robot path-planning is one of the important issues in robotic navigation. This paper presents a novel robot path-planning approach based on the associative memory using Self-Organizing Incremental Neural Networks (SOINN). By the proposed method, an environment is first autonomously divided into a set of path-fragments by junctions. Each fragment is represented by a sequence of preliminarily generated common patterns (CPs). In an online manner, a robot regards the current path as the associative path-fragments, each connected by junctions. The reasoning technique is additionally proposed for decision making at each junction to speed up the exploration time. Distinct from other methods, our method does not ignore the important information about the regions between junctions (path-fragments). The resultant number of path-fragments is also less than other method. Evaluation is done via Webots physical 3D-simulated and real robot experiments, where only distance sensors are available. Results show that our method can represent the environment effectively; it enables the robot to solve the goal-oriented navigation problem in only one episode, which is actually less than that necessary for most of the Reinforcement Learning (RL) based methods. The running time is proved finite and scales well with the environment. The resultant number of path-fragments matches well to the environment.

Implications of path tolerance and path characteristics on critical vehicle manoeuvres

NASA Astrophysics Data System (ADS)

Lundahl, K.; Frisk, E.; Nielsen, L.

2017-12-01

Path planning and path following are core components in safe autonomous driving. Typically, a path planner provides a path with some tolerance on how tightly the path should be followed. Based on that, and other path characteristics, for example, sharpness of curves, a speed profile needs to be assigned so that the vehicle can stay within the given tolerance without going unnecessarily slow. Here, such trajectory planning is based on optimal control formulations where critical cases arise as on-the-limit solutions. The study focuses on heavy commercial vehicles, causing rollover to be of a major concern, due to the relatively high centre of gravity. Several results are obtained on required model complexity depending on path characteristics, for example, quantification of required path tolerance for a simple model to be sufficient, quantification of when yaw inertia needs to be considered in more detail, and how the curvature rate of change interplays with available friction. Overall, in situations where the vehicle is subject to a wide range of driving conditions, from good transport roads to more tricky avoidance manoeuvres, the requirements on the path following will vary. For this, the provided results form a basis for real-time path following.

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †

PubMed Central

Zhang, Meiyan; Zheng, Yahong Rosa

2017-01-01

This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D) underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP) problem and the Genetic Algorithm (GA) is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB) or Tour Length Balance (TLB) constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X−Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem. PMID:28696377

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †.

PubMed

Cai, Wenyu; Zhang, Meiyan; Zheng, Yahong Rosa

2017-07-11

This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D) underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP) problem and the Genetic Algorithm (GA) is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB) or Tour Length Balance (TLB) constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X - Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G 1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem.

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.

Autonomous Navigation, Dynamic Path and Work Flow Planning in Multi-Agent Robotic Swarms Project

NASA Technical Reports Server (NTRS)

Falker, John; Zeitlin, Nancy; Leucht, Kurt; Stolleis, Karl

2015-01-01

Kennedy Space Center has teamed up with the Biological Computation Lab at the University of New Mexico to create a swarm of small, low-cost, autonomous robots, called Swarmies, to be used as a ground-based research platform for in-situ resource utilization missions. The behavior of the robot swarm mimics the central-place foraging strategy of ants to find and collect resources in an unknown environment and return those resources to a central site.

Optimal path planning for a mobile robot using cuckoo search algorithm

NASA Astrophysics Data System (ADS)

Mohanty, Prases K.; Parhi, Dayal R.

2016-03-01

The shortest/optimal path planning is essential for efficient operation of autonomous vehicles. In this article, a new nature-inspired meta-heuristic algorithm has been applied for mobile robot path planning in an unknown or partially known environment populated by a variety of static obstacles. This meta-heuristic algorithm is based on the levy flight behaviour and brood parasitic behaviour of cuckoos. A new objective function has been formulated between the robots and the target and obstacles, which satisfied the conditions of obstacle avoidance and target-seeking behaviour of robots present in the terrain. Depending upon the objective function value of each nest (cuckoo) in the swarm, the robot avoids obstacles and proceeds towards the target. The smooth optimal trajectory is framed with this algorithm when the robot reaches its goal. Some simulation and experimental results are presented at the end of the paper to show the effectiveness of the proposed navigational controller.

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.

A linguistic geometry for 3D strategic planning

NASA Technical Reports Server (NTRS)

Stilman, Boris

1995-01-01

This paper is a new step in the development and application of the Linguistic Geometry. This formal theory is intended to discover the inner properties of human expert heuristics, which have been successful in a certain class of complex control systems, and apply them to different systems. In this paper we investigate heuristics extracted in the form of hierarchical networks of planning paths of autonomous agents. Employing Linguistic Geometry tools the dynamic hierarchy of networks is represented as a hierarchy of formal attribute languages. The main ideas of this methodology are shown in this paper on the new pilot example of the solution of the extremely complex 3D optimization problem of strategic planning for the space combat of autonomous vehicles. This example demonstrates deep and highly selective search in comparison with conventional search algorithms.

A 2D chaotic path planning for mobile robots accomplishing boundary surveillance missions in adversarial conditions

NASA Astrophysics Data System (ADS)

Curiac, Daniel-Ioan; Volosencu, Constantin

2014-10-01

The path-planning algorithm represents a crucial issue for every autonomous mobile robot. In normal circumstances a patrol robot will compute an optimal path to ensure its task accomplishment, but in adversarial conditions the problem is getting more complicated. Here, the robot’s trajectory needs to be altered into a misleading and unpredictable path to cope with potential opponents. Chaotic systems provide the needed framework for obtaining unpredictable motion in all of the three basic robot surveillance missions: area, points of interests and boundary monitoring. Proficient approaches have been provided for the first two surveillance tasks, but for boundary patrol missions no method has been reported yet. This paper addresses the mentioned research gap by proposing an efficient method, based on chaotic dynamic of the Hénon system, to ensure unpredictable boundary patrol on any shape of chosen closed contour.

Path planning in GPS-denied environments via collective intelligence of distributed sensor networks

NASA Astrophysics Data System (ADS)

Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok

2016-05-01

This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.

Intelligent control and adaptive systems; Proceedings of the Meeting, Philadelphia, PA, Nov. 7, 8, 1989

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Editor)

1990-01-01

Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.

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.

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.

Navigation system for autonomous mapper robots

NASA Astrophysics Data System (ADS)

Halbach, Marc; Baudoin, Yvan

1993-05-01

This paper describes the conception and realization of a fast, robust, and general navigation system for a mobile (wheeled or legged) robot. A database, representing a high level map of the environment is generated and continuously updated. The first part describes the legged target vehicle and the hexapod robot being developed. The second section deals with spatial and temporal sensor fusion for dynamic environment modeling within an obstacle/free space probabilistic classification grid. Ultrasonic sensors are used, others are suspected to be integrated, and a-priori knowledge is treated. US sensors are controlled by the path planning module. The third part concerns path planning and a simulation of a wheeled robot is also presented.

Visual identification and similarity measures used for on-line motion planning of autonomous robots in unknown environments

NASA Astrophysics Data System (ADS)

Martínez, Fredy; Martínez, Fernando; Jacinto, Edwar

2017-02-01

In this paper we propose an on-line motion planning strategy for autonomous robots in dynamic and locally observable environments. In this approach, we first visually identify geometric shapes in the environment by filtering images. Then, an ART-2 network is used to establish the similarity between patterns. The proposed algorithm allows that a robot establish its relative location in the environment, and define its navigation path based on images of the environment and its similarity to reference images. This is an efficient and minimalist method that uses the similarity of landmark view patterns to navigate to the desired destination. Laboratory tests on real prototypes demonstrate the performance of the algorithm.

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.

Sensitivity analysis of an optimization-based trajectory planner for autonomous vehicles in urban environments

NASA Astrophysics Data System (ADS)

Hardy, Jason; Campbell, Mark; Miller, Isaac; Schimpf, Brian

2008-10-01

The local path planner implemented on Cornell's 2007 DARPA Urban Challenge entry vehicle Skynet utilizes a novel mixture of discrete and continuous path planning steps to facilitate a safe, smooth, and human-like driving behavior. The planner first solves for a feasible path through the local obstacle map using a grid based search algorithm. The resulting path is then refined using a cost-based nonlinear optimization routine with both hard and soft constraints. The behavior of this optimization is influenced by tunable weighting parameters which govern the relative cost contributions assigned to different path characteristics. This paper studies the sensitivity of the vehicle's performance to these path planner weighting parameters using a data driven simulation based on logged data from the National Qualifying Event. The performance of the path planner in both the National Qualifying Event and in the Urban Challenge is also presented and analyzed.

Hierarchical Motion Planning for Autonomous Aerial and Terrestrial Vehicles

NASA Astrophysics Data System (ADS)

Cowlagi, Raghvendra V.

Autonomous mobile robots---both aerial and terrestrial vehicles---have gained immense importance due to the broad spectrum of their potential military and civilian applications. One of the indispensable requirements for the autonomy of a mobile vehicle is the vehicle's capability of planning and executing its motion, that is, finding appropriate control inputs for the vehicle such that the resulting vehicle motion satisfies the requirements of the vehicular task. The motion planning and control problem is inherently complex because it involves two disparate sub-problems: (1) satisfaction of the vehicular task requirements, which requires tools from combinatorics and/or formal methods, and (2) design of the vehicle control laws, which requires tools from dynamical systems and control theory. Accordingly, this problem is usually decomposed and solved over two levels of hierarchy. The higher level, called the geometric path planning level, finds a geometric path that satisfies the vehicular task requirements, e.g., obstacle avoidance. The lower level, called the trajectory planning level, involves sufficient smoothening of this geometric path followed by a suitable time parametrization to obtain a reference trajectory for the vehicle. Although simple and efficient, such hierarchical decomposition suffers a serious drawback: the geometric path planner has no information of the kinematical and dynamical constraints of the vehicle. Consequently, the geometric planner may produce paths that the trajectory planner cannot transform into a feasible reference trajectory. Two main ideas appear in the literature to remedy this problem: (a) randomized sampling-based planning, which eliminates the geometric planner altogether by planning in the vehicle state space, and (b) geometric planning supported by feedback control laws. The former class of methods suffer from a lack of optimality of the resultant trajectory, while the latter class of methods makes a restrictive assumption concerning the vehicle kinematical model. We propose a hierarchical motion planning framework based on a novel mode of interaction between these two levels of planning. This interaction rests on the solution of a special shortest-path problem on graphs, namely, one using costs defined on multiple edge transitions in the path instead of the usual single edge transition costs. These costs are provided by a local trajectory generation algorithm, which we implement using model predictive control and the concept of effective target sets for simplifying the non-convex constraints involved in the problem. The proposed motion planner ensures "consistency" between the two levels of planning, i.e., a guarantee that the higher level geometric path is always associated with a kinematically and dynamically feasible trajectory. The main contributions of this thesis are: 1. A motion planning framework based on history-dependent costs (H-costs) in cell decomposition graphs for incorporating vehicle dynamical constraints: this framework offers distinct advantages in comparison with the competing approaches of discretization of the state space, of randomized sampling-based motion planning, and of local feedback-based, decoupled hierarchical motion planning, 2. An efficient and flexible algorithm for finding optimal H-cost paths, 3. A precise and general formulation of a local trajectory problem (the tile motion planning problem) that allows independent development of the discrete planner and the trajectory planner, while maintaining "compatibility" between the two planners, 4. A local trajectory generation algorithm using mpc, and the application of the concept of effective target sets for a significant simplification of the local trajectory generation problem, 5. The geometric analysis of curvature-bounded traversal of rectangular channels, leading to less conservative results in comparison with a result reported in the literature, and also to the efficient construction of effective target sets for the solution of the tile motion planning problem, 6. A wavelet-based multi-resolution path planning scheme, and a proof of completeness of the proposed scheme: such proofs are altogether absent from other works on multi-resolution path planning, 7. A technique for extracting all information about cells---namely, the locations, the sizes, and the associated image intensities---directly from the set of significant detail coefficients considered for path planning at a given iteration, and 8. The extension of the multi-resolution path planning scheme to include vehicle dynamical constraints using the aforementioned history-dependent costs approach. The future work includes an implementation of the proposed framework involving a discrete planner that solves classical planning problems more general than the single-query path planning problem considered thus far, and involving trajectory generation schemes for realistic vehicle dynamical models such as the bicycle model.

Redundant manipulator techniques for partially decentralized path planning and control of a platoon of autonomous vehicles.

PubMed

Stilwell, Daniel J; Bishop, Bradley E; Sylvester, Caleb A

2005-08-01

An approach to real-time trajectory generation for platoons of autonomous vehicles is developed from well-known control techniques for redundant robotic manipulators. The partially decentralized structure of this approach permits each vehicle to independently compute its trajectory in real-time using only locally generated information and low-bandwidth feedback generated by a system exogenous to the platoon. Our work is motivated by applications for which communications bandwidth is severely limited, such for platoons of autonomous underwater vehicles. The communication requirements for our trajectory generation approach are independent of the number of vehicles in the platoon, enabling platoons composed of a large number of vehicles to be coordinated despite limited communication bandwidth.

Energy Optimal Path Planning: Integrating Coastal Ocean Modelling with Optimal Control

NASA Astrophysics Data System (ADS)

Subramani, D. N.; Haley, P. J., Jr.; Lermusiaux, P. F. J.

2016-02-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. To set up the energy optimization, the relative vehicle speed and headings are considered to be stochastic, and new stochastic Dynamically Orthogonal (DO) level-set equations that govern their stochastic time-optimal reachability fronts are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. The accuracy and efficiency of the DO level-set equations for solving the governing stochastic level-set reachability fronts are quantitatively assessed, including comparisons with independent semi-analytical solutions. Energy-optimal missions are studied in wind-driven barotropic quasi-geostrophic double-gyre circulations, and in realistic data-assimilative re-analyses of multiscale coastal ocean flows. The latter re-analyses are obtained from multi-resolution 2-way nested primitive-equation simulations of tidal-to-mesoscale dynamics in the Middle Atlantic Bight and Shelbreak Front region. The effects of tidal currents, strong wind events, coastal jets, and shelfbreak fronts on the energy-optimal paths are illustrated and quantified. Results showcase the opportunities for longer-duration missions that intelligently utilize the ocean environment to save energy, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.

Autonomous Lawnmower using FPGA implementation.

NASA Astrophysics Data System (ADS)

Ahmad, Nabihah; Lokman, Nabill bin; Helmy Abd Wahab, Mohd

2016-11-01

Nowadays, there are various types of robot have been invented for multiple purposes. The robots have the special characteristic that surpass the human ability and could operate in extreme environment which human cannot endure. In this paper, an autonomous robot is built to imitate the characteristic of a human cutting grass. A Field Programmable Gate Array (FPGA) is used to control the movements where all data and information would be processed. Very High Speed Integrated Circuit (VHSIC) Hardware Description Language (VHDL) is used to describe the hardware using Quartus II software. This robot has the ability of avoiding obstacle using ultrasonic sensor. This robot used two DC motors for its movement. It could include moving forward, backward, and turning left and right. The movement or the path of the automatic lawn mower is based on a path planning technique. Four Global Positioning System (GPS) plot are set to create a boundary. This to ensure that the lawn mower operates within the area given by user. Every action of the lawn mower is controlled by the FPGA DE' Board Cyclone II with the help of the sensor. Furthermore, Sketch Up software was used to design the structure of the lawn mower. The autonomous lawn mower was able to operate efficiently and smoothly return to coordinated paths after passing the obstacle. It uses 25% of total pins available on the board and 31% of total Digital Signal Processing (DSP) blocks.

Adaptable mission planning for kino-dynamic systems

NASA Astrophysics Data System (ADS)

Bush, Lawrence A. M.; Jimenez, Tony R.; Williams, Brian C.

Autonomous systems can perform tasks that are dangerous, monotonous, or even impossible for humans. To approach the problem of planning for Unmanned Aerial Vehicles (UAVs) we present a hierarchical method that combines a high-level planner with a low-level planner. We pose the problem of high-level planning as a Selective Traveling Salesman Problem (STSP) and select the order in which to visit our science sites. We then use a kino-dynamic path planner to create a large number of intermediate waypoints. This is a complete system that combines high and low level planning to achieve a goal. This paper demonstrates the benefits gained by adaptable high-level plans versus static and greedy plans.

Vector Pursuit Path Tracking for Autonomous Ground Vehicles

DTIC Science & Technology

2000-08-01

vi INTRODUCTION ...........................................................................................................1...other geometric path-tracking techniques. 1 CHAPTER 1 INTRODUCTION An autonomous vehicle is one that is capable of automatic navigation. It is...Joint Architecture for Unmanned Ground Vehicles ( JAUGS ) working group meeting held at the University of Florida. 5 Figure 1.5: Autonomous

Risk-Aware Planetary Rover Operation: Autonomous Terrain Classification and Path Planning

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Fuchs, Thoams J.; Steffy, Amanda; Maimone, Mark; Yen, Jeng

2015-01-01

Identifying and avoiding terrain hazards (e.g., soft soil and pointy embedded rocks) are crucial for the safety of planetary rovers. This paper presents a newly developed groundbased Mars rover operation tool that mitigates risks from terrain by automatically identifying hazards on the terrain, evaluating their risks, and suggesting operators safe paths options that avoids potential risks while achieving specified goals. The tool will bring benefits to rover operations by reducing operation cost, by reducing cognitive load of rover operators, by preventing human errors, and most importantly, by significantly reducing the risk of the loss of rovers.

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.

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.

Human-like robots for space and hazardous environments

NASA Technical Reports Server (NTRS)

1994-01-01

The three year goal for the Kansas State USRA/NASA Senior Design team is to design and build a walking autonomous robotic rover. The rover should be capable of crossing rough terrain, traversing human made obstacles (such as stairs and doors), and moving through human and robot occupied spaces without collision. The rover is also to evidence considerable decision making ability, navigation, and path planning skills.

Human-like robots for space and hazardous environments

NASA Astrophysics Data System (ADS)

The three year goal for the Kansas State USRA/NASA Senior Design team is to design and build a walking autonomous robotic rover. The rover should be capable of crossing rough terrain, traversing human made obstacles (such as stairs and doors), and moving through human and robot occupied spaces without collision. The rover is also to evidence considerable decision making ability, navigation, and path planning skills.

Autonomous Motion Planning Using a Predictive Temporal Method

DTIC Science & Technology

2009-01-01

interception test. ......150 5-20 Target and solution path heading angles for target interception test. ..............................151 10 LIST...environment as a series of distances and angles . Regardless of the technique, this knowledge of the surrounding area is crucial for the issue of...to, the rather simplistic vector driver algorithms which compute the angle between the current vehicle heading and the heading to the goal and

Multi-Modal Active Perception for Autonomously Selecting Landing Sites on Icy Moons

NASA Technical Reports Server (NTRS)

Arora, A.; Furlong, P. M.; Wong, U.; Fong, T.; Sukkarieh, S.

2017-01-01

Selecting suitable landing sites is fundamental to achieving many mission objectives in planetary robotic lander missions. However, due to sensing limitations, landing sites which are both safe and scientifically valuable often cannot be determined reliably from orbit, particularly, in icy moon missions where orbital sensing data is noisy and incomplete. This paper presents an active perception approach to Entry Descent and Landing (EDL) which enables the lander to autonomously plan informative descent trajectories, acquire high quality sensing data during descent and exploit this additional information to select higher utility landing sites. Our approach consists of two components: probabilistic modeling of landing site features and approximate trajectory planning using a sampling based planner. The proposed framework allows the lander to plan long horizons paths and remain robust to noisy data. Results in simulated environments show large performance improvements over alternative approaches and show promise that our approach has strong potential to improve science return of not only icy moon missions but EDL systems in general.

Autonomous Underwater Navigation and Optical Mapping in Unknown Natural Environments.

PubMed

Hernández, Juan David; Istenič, Klemen; Gracias, Nuno; Palomeras, Narcís; Campos, Ricard; Vidal, Eduard; García, Rafael; Carreras, Marc

2016-07-26

We present an approach for navigating in unknown environments while, simultaneously, gathering information for inspecting underwater structures using an autonomous underwater vehicle (AUV). To accomplish this, we first use our pipeline for mapping and planning collision-free paths online, which endows an AUV with the capability to autonomously acquire optical data in close proximity. With that information, we then propose a reconstruction pipeline to create a photo-realistic textured 3D model of the inspected area. These 3D models are also of particular interest to other fields of study in marine sciences, since they can serve as base maps for environmental monitoring, thus allowing change detection of biological communities and their environment over time. Finally, we evaluate our approach using the Sparus II, a torpedo-shaped AUV, conducting inspection missions in a challenging, real-world and natural scenario.

Autonomous Underwater Navigation and Optical Mapping in Unknown Natural Environments

PubMed Central

Hernández, Juan David; Istenič, Klemen; Gracias, Nuno; Palomeras, Narcís; Campos, Ricard; Vidal, Eduard; García, Rafael; Carreras, Marc

2016-01-01

We present an approach for navigating in unknown environments while, simultaneously, gathering information for inspecting underwater structures using an autonomous underwater vehicle (AUV). To accomplish this, we first use our pipeline for mapping and planning collision-free paths online, which endows an AUV with the capability to autonomously acquire optical data in close proximity. With that information, we then propose a reconstruction pipeline to create a photo-realistic textured 3D model of the inspected area. These 3D models are also of particular interest to other fields of study in marine sciences, since they can serve as base maps for environmental monitoring, thus allowing change detection of biological communities and their environment over time. Finally, we evaluate our approach using the Sparus II, a torpedo-shaped AUV, conducting inspection missions in a challenging, real-world and natural scenario. PMID:27472337

Design and implementation of a biomimetic turtle hydrofoil for an autonomous underwater vehicle.

PubMed

Font, Davinia; Tresanchez, Marcel; Siegentahler, Cedric; Pallejà, Tomàs; Teixidó, Mercè; Pradalier, Cedric; Palacin, Jordi

2011-01-01

This paper presents the design and implementation of a turtle hydrofoil for an Autonomous Underwater Vehicle (AUV). The final design of the AUV must have navigation performance like a turtle, which has also been the biomimetic inspiration for the design of the hydrofoil and propulsion system. The hydrofoil design is based on a National Advisory Committee for Aeronautics (NACA) 0014 hydrodynamic profile. During the design stage, four different propulsion systems were compared in terms of propulsion path, compactness, sealing and required power. The final implementation is based on a ball-and-socket mechanism because it is very compact and provides three degrees of freedom (DoF) to the hydrofoil with very few restrictions on the propulsion path. The propulsion obtained with the final implementation of the hydrofoil has been empirically evaluated in a water channel comparing different motion strategies. The results obtained have confirmed that the proposed turtle hydrofoil controlled with a mechanism with three DoF generates can be used in the future implementation of the planned AUV.

POSTMAN: Point of Sail Tacking for Maritime Autonomous Navigation

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance L.; Reinhart, Felix

2012-01-01

Waves apply significant forces to small boats, in particular when such vessels are moving at a high speed in severe sea conditions. In addition, small high-speed boats run the risk of diving with the bow into the next wave crest during operations in the wavelengths and wave speeds that are typical for shallow water. In order to mitigate the issues of autonomous navigation in rough water, a hybrid controller called POSTMAN combines the concept of POS (point of sail) tack planning from the sailing domain with a standard PID (proportional-integral-derivative) controller that implements reliable target reaching for the motorized small boat control task. This is an embedded, adaptive software controller that uses look-ahead sensing in a closed loop method to perform path planning for safer navigation in rough waters. State-of-the-art controllers for small boats are based on complex models of the vessel's kinematics and dynamics. They enable the vessel to follow preplanned paths accurately and can theoretically control all of the small boat s six degrees of freedom. However, the problems of bow diving and other undesirable incidents are not addressed, and it is questionable if a six-DOF controller with basically a single actuator is possible at all. POSTMAN builds an adaptive capability into the controller based on sensed wave characteristics. This software will bring a muchneeded capability to unmanned small boats moving at high speeds. Previously, this class of boat was limited to wave heights of less than one meter in the sea states in which it could operate. POSTMAN is a major advance in autonomous safety for small maritime craft.

Physics-Aware Informative Coverage Planning for Autonomous Vehicles

DTIC Science & Technology

2014-06-01

environment and find the optimal path connecting fixed nodes, which is equivalent to solving the Traveling Salesman Problem (TSP). While TSP is an NP...intended for application to USV harbor patrolling, it is applicable to many different domains. The problem of traveling over an area and gathering...environment. I. INTRODUCTION There are many applications that need persistent monitor- ing of a given area, requiring repeated travel over the area to

Trajectory generation for an on-road autonomous vehicle

NASA Astrophysics Data System (ADS)

Horst, John; Barbera, Anthony

2006-05-01

We describe an algorithm that generates a smooth trajectory (position, velocity, and acceleration at uniformly sampled instants of time) for a car-like vehicle autonomously navigating within the constraints of lanes in a road. The technique models both vehicle paths and lane segments as straight line segments and circular arcs for mathematical simplicity and elegance, which we contrast with cubic spline approaches. We develop the path in an idealized space, warp the path into real space and compute path length, generate a one-dimensional trajectory along the path length that achieves target speeds and positions, and finally, warp, translate, and rotate the one-dimensional trajectory points onto the path in real space. The algorithm moves a vehicle in lane safely and efficiently within speed and acceleration maximums. The algorithm functions in the context of other autonomous driving functions within a carefully designed vehicle control hierarchy.

H-SLAM: Rao-Blackwellized Particle Filter SLAM Using Hilbert Maps.

PubMed

Vallicrosa, Guillem; Ridao, Pere

2018-05-01

Occupancy Grid maps provide a probabilistic representation of space which is important for a variety of robotic applications like path planning and autonomous manipulation. In this paper, a SLAM (Simultaneous Localization and Mapping) framework capable of obtaining this representation online is presented. The H-SLAM (Hilbert Maps SLAM) is based on Hilbert Map representation and uses a Particle Filter to represent the robot state. Hilbert Maps offer a continuous probabilistic representation with a small memory footprint. We present a series of experimental results carried both in simulation and with real AUVs (Autonomous Underwater Vehicles). These results demonstrate that our approach is able to represent the environment more consistently while capable of running online.

Autonomous power management and distribution

NASA Technical Reports Server (NTRS)

Dolce, Jim; Kish, Jim

1990-01-01

The goal of the Autonomous Power System program is to develop and apply intelligent problem solving and control to the Space Station Freedom's electric power testbed being developed at NASA's Lewis Research Center. Objectives are to establish artificial intelligence technology paths, craft knowledge-based tools and products for power systems, and integrate knowledge-based and conventional controllers. This program represents a joint effort between the Space Station and Office of Aeronautics and Space Technology to develop and demonstrate space electric power automation technology capable of: (1) detection and classification of system operating status, (2) diagnosis of failure causes, and (3) cooperative problem solving for power scheduling and failure recovery. Program details, status, and plans will be presented.

Quantifying Traversability of Terrain for a Mobile Robot

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Seraji, Homayoun; Werger, Barry

2005-01-01

A document presents an updated discussion on a method of autonomous navigation for a robotic vehicle navigating across rough terrain. The method involves, among other things, the use of a measure of traversability, denoted the fuzzy traversability index, which embodies the information about the slope and roughness of terrain obtained from analysis of images acquired by cameras mounted on the robot. The improvements presented in the report focus on the use of the fuzzy traversability index to generate a traversability map and a grid map for planning the safest path for the robot. Once grid traversability values have been computed, they are utilized for rejecting unsafe path segments and for computing a traversalcost function for ranking candidate paths, selected by a search algorithm, from a specified initial position to a specified final position. The output of the algorithm is a set of waypoints designating a path having a minimal-traversal cost.

Radial polar histogram: obstacle avoidance and path planning for robotic cognition and motion control

NASA Astrophysics Data System (ADS)

Wang, Po-Jen; Keyawa, Nicholas R.; Euler, Craig

2012-01-01

In order to achieve highly accurate motion control and path planning for a mobile robot, an obstacle avoidance algorithm that provided a desired instantaneous turning radius and velocity was generated. This type of obstacle avoidance algorithm, which has been implemented in California State University Northridge's Intelligent Ground Vehicle (IGV), is known as Radial Polar Histogram (RPH). The RPH algorithm utilizes raw data in the form of a polar histogram that is read from a Laser Range Finder (LRF) and a camera. A desired open block is determined from the raw data utilizing a navigational heading and an elliptical approximation. The left and right most radii are determined from the calculated edges of the open block and provide the range of possible radial paths the IGV can travel through. In addition, the calculated obstacle edge positions allow the IGV to recognize complex obstacle arrangements and to slow down accordingly. A radial path optimization function calculates the best radial path between the left and right most radii and is sent to motion control for speed determination. Overall, the RPH algorithm allows the IGV to autonomously travel at average speeds of 3mph while avoiding all obstacles, with a processing time of approximately 10ms.

Invited Article: Autonomous assembly of atomically perfect nanostructures using a scanning tunneling microscope.

PubMed

Celotta, Robert J; Balakirsky, Stephen B; Fein, Aaron P; Hess, Frank M; Rutter, Gregory M; Stroscio, Joseph A

2014-12-01

A major goal of nanotechnology is to develop the capability to arrange matter at will by placing individual atoms at desired locations in a predetermined configuration to build a nanostructure with specific properties or function. The scanning tunneling microscope has demonstrated the ability to arrange the basic building blocks of matter, single atoms, in two-dimensional configurations. An array of various nanostructures has been assembled, which display the quantum mechanics of quantum confined geometries. The level of human interaction needed to physically locate the atom and bring it to the desired location limits this atom assembly technology. Here we report the use of autonomous atom assembly via path planning technology; this allows atomically perfect nanostructures to be assembled without the need for human intervention, resulting in precise constructions in shorter times. We demonstrate autonomous assembly by assembling various quantum confinement geometries using atoms and molecules and describe the benefits of this approach.

Toward Shared Working Space of Human and Robotic Agents Through Dipole Flow Field for Dependable Path Planning.

PubMed

Trinh, Lan Anh; Ekström, Mikael; Cürüklü, Baran

2018-01-01

Recent industrial developments in autonomous systems, or agents, which assume that humans and the agents share the same space or even work in close proximity, open for new challenges in robotics, especially in motion planning and control. In these settings, the control system should be able to provide these agents a reliable path following control when they are working in a group or in collaboration with one or several humans in complex and dynamic environments. In such scenarios, these agents are not only moving to reach their goals, i.e., locations, they are also aware of the movements of other entities to find a collision-free path. Thus, this paper proposes a dependable, i.e., safe, reliable and effective, path planning algorithm for a group of agents that share their working space with humans. Firstly, the method employs the Theta * algorithm to initialize the paths from a starting point to a goal for a set of agents. As Theta * algorithm is computationally heavy, it only reruns when there is a significant change of the environment. To deal with the movements of the agents, a static flow field along the configured path is defined. This field is used by the agents to navigate and reach their goals even if the planned trajectories are changed. Secondly, a dipole field is calculated to avoid the collision of agents with other agents and human subjects. In this approach, each agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. The effectiveness of the proposed approach has been evaluated with extensive simulations. The results show that the static flow field is able to drive agents to the goals with a small number of requirements to update the path of agents. Meanwhile, the dipole flow field plays an important role to prevent collisions. The combination of these two fields results in a safe path planning algorithm, with a deterministic outcome, to navigate agents to their desired goals.

Computer graphics testbed to simulate and test vision systems for space applications

NASA Technical Reports Server (NTRS)

Cheatham, John B.

1991-01-01

Artificial intelligence concepts are applied to robotics. Artificial neural networks, expert systems and laser imaging techniques for autonomous space robots are being studied. A computer graphics laser range finder simulator developed by Wu has been used by Weiland and Norwood to study use of artificial neural networks for path planning and obstacle avoidance. Interest is expressed in applications of CLIPS, NETS, and Fuzzy Control. These applications are applied to robot navigation.

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.

Energy-optimal path planning by stochastic dynamically orthogonal level-set optimization

NASA Astrophysics Data System (ADS)

Subramani, Deepak N.; Lermusiaux, Pierre F. J.

2016-04-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. Based on partial differential equations, the methodology rigorously leverages the level-set equation that governs time-optimal reachability fronts for a given relative vehicle-speed function. To set up the energy optimization, the relative vehicle-speed and headings are considered to be stochastic and new stochastic Dynamically Orthogonal (DO) level-set equations are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. Numerical schemes to solve the reduced stochastic DO level-set equations are obtained, and accuracy and efficiency considerations are discussed. These reduced equations are first shown to be efficient at solving the governing stochastic level-sets, in part by comparisons with direct Monte Carlo simulations. To validate the methodology and illustrate its accuracy, comparisons with semi-analytical energy-optimal path solutions are then completed. In particular, we consider the energy-optimal crossing of a canonical steady front and set up its semi-analytical solution using a energy-time nested nonlinear double-optimization scheme. We then showcase the inner workings and nuances of the energy-optimal path planning, considering different mission scenarios. Finally, we study and discuss results of energy-optimal missions in a wind-driven barotropic quasi-geostrophic double-gyre ocean circulation.

Design and Implementation of a Biomimetic Turtle Hydrofoil for an Autonomous Underwater Vehicle

PubMed Central

Font, Davinia; Tresanchez, Marcel; Siegentahler, Cedric; Pallejà, Tomàs; Teixidó, Mercè; Pradalier, Cedric; Palacin, Jordi

2011-01-01

This paper presents the design and implementation of a turtle hydrofoil for an Autonomous Underwater Vehicle (AUV). The final design of the AUV must have navigation performance like a turtle, which has also been the biomimetic inspiration for the design of the hydrofoil and propulsion system. The hydrofoil design is based on a National Advisory Committee for Aeronautics (NACA) 0014 hydrodynamic profile. During the design stage, four different propulsion systems were compared in terms of propulsion path, compactness, sealing and required power. The final implementation is based on a ball-and-socket mechanism because it is very compact and provides three degrees of freedom (DoF) to the hydrofoil with very few restrictions on the propulsion path. The propulsion obtained with the final implementation of the hydrofoil has been empirically evaluated in a water channel comparing different motion strategies. The results obtained have confirmed that the proposed turtle hydrofoil controlled with a mechanism with three DoF generates can be used in the future implementation of the planned AUV. PMID:22247660

Coordinating robot motion, sensing, and control in plans. LDRD project final report

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

Xavier, P.G.; Brown, R.G.; Watterberg, P.A.

1997-08-01

The goal of this project was to develop a framework for robotic planning and execution that provides a continuum of adaptability with respect to model incompleteness, model error, and sensing error. For example, dividing robot motion into gross-motion planning, fine-motion planning, and sensor-augmented control had yielded productive research and solutions to individual problems. Unfortunately, these techniques could only be combined by hand with ad hoc methods and were restricted to systems where all kinematics are completely modeled in planning. The original intent was to develop methods for understanding and autonomously synthesizing plans that coordinate motion, sensing, and control. The projectmore » considered this problem from several perspectives. Results included (1) theoretical methods to combine and extend gross-motion and fine-motion planning; (2) preliminary work in flexible-object manipulation and an implementable algorithm for planning shortest paths through obstacles for the free-end of an anchored cable; (3) development and implementation of a fast swept-body distance algorithm; and (4) integration of Sandia`s C-Space Toolkit geometry engine and SANDROS motion planer and improvements, which yielded a system practical for everyday motion planning, with path-segment planning at interactive speeds. Results (3) and (4) have either led to follow-on work or are being used in current projects, and they believe that (2) will eventually be also.« less

Dynamic Task Assignment and Path Planning of Multi-AUV System Based on an Improved Self-Organizing Map and Velocity Synthesis Method in Three-Dimensional Underwater Workspace.

PubMed

Zhu, Daqi; Huang, Huan; Yang, S X

2013-04-01

For a 3-D underwater workspace with a variable ocean current, an integrated multiple autonomous underwater vehicle (AUV) dynamic task assignment and path planning algorithm is proposed by combing the improved self-organizing map (SOM) neural network and a novel velocity synthesis approach. The goal is to control a team of AUVs to reach all appointed target locations for only one time on the premise of workload balance and energy sufficiency while guaranteeing the least total and individual consumption in the presence of the variable ocean current. First, the SOM neuron network is developed to assign a team of AUVs to achieve multiple target locations in 3-D ocean environment. The working process involves special definition of the initial neural weights of the SOM network, the rule to select the winner, the computation of the neighborhood function, and the method to update weights. Then, the velocity synthesis approach is applied to plan the shortest path for each AUV to visit the corresponding target in a dynamic environment subject to the ocean current being variable and targets being movable. Lastly, to demonstrate the effectiveness of the proposed approach, simulation results are given in this paper.

Autonomous Control Modes and Optimized Path Guidance for Shipboard Landing in High Sea States

DTIC Science & Technology

2017-04-15

50 0 50 Singular Values Frequency (rad/s) S in g u la r V a lu e s ( d B ) controller . The non -output variables can be estimated by reliable linear...Contract # N00014-14-C-0004 Autonomous Control Modes and Optimized Path Guidance for Shipboard Landing in High Sea States Progress Report...recovery of a VTOL UAV. There is a clear need for additional levels of stability and control augmentation and, ultimately, fully autonomous landing

Human-like robots for space and hazardous environments

NASA Technical Reports Server (NTRS)

Cogley, Allen; Gustafson, David; White, Warren; Dyer, Ruth; Hampton, Tom (Editor); Freise, Jon (Editor)

1990-01-01

The three year goal for this NASA Senior Design team is to design and build a walking autonomous robotic rover. The rover should be capable of rough terrain crossing, traversing human made obstacles (such as stairs and doors), and moving through human and robot occupied spaces without collision. The rover is also to evidence considerable decision making ability, navigation and path planning skills. These goals came from the concept that the robot should have the abilities of both a planetary rover and a hazardous waste site scout.

Human-like robots for space and hazardous environments

NASA Astrophysics Data System (ADS)

Cogley, Allen; Gustafson, David; White, Warren; Dyer, Ruth; Hampton, Tom; Freise, Jon

The three year goal for this NASA Senior Design team is to design and build a walking autonomous robotic rover. The rover should be capable of rough terrain crossing, traversing human made obstacles (such as stairs and doors), and moving through human and robot occupied spaces without collision. The rover is also to evidence considerable decision making ability, navigation and path planning skills. These goals came from the concept that the robot should have the abilities of both a planetary rover and a hazardous waste site scout.

Learning Preference Models for Autonomous Mobile Robots in Complex Domains

DTIC Science & Technology

2010-12-01

van Niekerk, E. Jensen, P. Alessandrini, G. Bradski, B. Davies, S. Ettinger, A. Kaehler, A. Nefian, and P. Mahoney , “Stanley: The robot that won the...Learning, vol. 24, pp. 123–140, 1996. 137 [277] L. Murphy and P. Newman , “Planning most-likely paths from overhead imagery,” in Inter- national Conference...B. [150] Nashman, M. [64] Nehmzow, U. [265, 266] Neto, H. [265] Newman , P. [277] Ng, A. Y. [199, 203, 222, 223, 241–243, 254] Nguyen, T. [115] Niekum

An Analysis of Navigation Algorithms for Smartphones Using J2ME

NASA Astrophysics Data System (ADS)

Santos, André C.; Tarrataca, Luís; Cardoso, João M. P.

Embedded systems are considered one of the most potential areas for future innovations. Two embedded fields that will most certainly take a primary role in future innovations are mobile robotics and mobile computing. Mobile robots and smartphones are growing in number and functionalities, becoming a presence in our daily life. In this paper, we study the current feasibility of a smartphone to execute navigation algorithms. As a test case, we use a smartphone to control an autonomous mobile robot. We tested three navigation problems: Mapping, Localization and Path Planning. For each of these problems, an algorithm has been chosen, developed in J2ME, and tested on the field. Results show the current mobile Java capacity for executing computationally demanding algorithms and reveal the real possibility of using smartphones for autonomous navigation.

Invited Article: Autonomous assembly of atomically perfect nanostructures using a scanning tunneling microscope

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

Celotta, Robert J., E-mail: robert.celotta@nist.gov, E-mail: joseph.stroscio@nist.gov; Hess, Frank M.; Rutter, Gregory M.

2014-12-15

A major goal of nanotechnology is to develop the capability to arrange matter at will by placing individual atoms at desired locations in a predetermined configuration to build a nanostructure with specific properties or function. The scanning tunneling microscope has demonstrated the ability to arrange the basic building blocks of matter, single atoms, in two-dimensional configurations. An array of various nanostructures has been assembled, which display the quantum mechanics of quantum confined geometries. The level of human interaction needed to physically locate the atom and bring it to the desired location limits this atom assembly technology. Here we report themore » use of autonomous atom assembly via path planning technology; this allows atomically perfect nanostructures to be assembled without the need for human intervention, resulting in precise constructions in shorter times. We demonstrate autonomous assembly by assembling various quantum confinement geometries using atoms and molecules and describe the benefits of this approach.« less

On-board autonomous attitude maneuver planning for planetary spacecraft using genetic algorithms

NASA Technical Reports Server (NTRS)

Kornfeld, Richard P.

2003-01-01

A key enabling technology that leads to greater spacecraft autonomy is the capability to autonomously and optimally slew the spacecraft from and to different attitudes while operating under a number of celestial and dynamic constraints. The task of finding an attitude trajectory that meets all the constraints is a formidable one, in particular for orbiting or fly-by spacecraft where the constraints and initial and final conditions are of time-varying nature. This paper presents an approach for attitude path planning that makes full use of a priori constraint knowledge and is computationally tractable enough to be executed on-board a spacecraft. The approach is based on incorporating the constraints into a cost function and using a Genetic Algorithm to iteratively search for and optimize the solution. This results in a directed random search that explores a large part of the solution space while maintaining the knowledge of good solutions from iteration to iteration. A solution obtained this way may be used 'as is' or as an initial solution to initialize additional deterministic optimization algorithms. A number of example simulations are presented including the case examples of a generic Europa Orbiter spacecraft in cruise as well as in orbit around Europa. The search times are typically on the order of minutes, thus demonstrating the viability of the presented approach. The results are applicable to all future deep space missions where greater spacecraft autonomy is required. In addition, onboard autonomous attitude planning greatly facilitates navigation and science observation planning, benefiting thus all missions to planet Earth as well.

Who's Got the Bridge? - Towards Safe, Robust Autonomous Operations at NASA Langley's Autonomy Incubator

NASA Technical Reports Server (NTRS)

Allen, B. Danette; Cross, Charles D.; Motter, Mark A.; Neilan, James H.; Qualls, Garry D.; Rothhaar, Paul M.; Tran, Loc; Trujillo, Anna C.; Crisp, Vicki K.

2015-01-01

NASA aeronautics research has made decades of contributions to aviation. Both aircraft and air traffic management (ATM) systems in use today contain NASA-developed and NASA sponsored technologies that improve safety and efficiency. Recent innovations in robotics and autonomy for automobiles and unmanned systems point to a future with increased personal mobility and access to transportation, including aviation. Automation and autonomous operations will transform the way we move people and goods. Achieving this mobility will require safe, robust, reliable operations for both the vehicle and the airspace and challenges to this inevitable future are being addressed now in government labs, universities, and industry. These challenges are the focus of NASA Langley Research Center's Autonomy Incubator whose R&D portfolio includes mission planning, trajectory and path planning, object detection and avoidance, object classification, sensor fusion, controls, machine learning, computer vision, human-machine teaming, geo-containment, open architecture design and development, as well as the test and evaluation environment that will be critical to prove system reliability and support certification. Safe autonomous operations will be enabled via onboard sensing and perception systems in both data-rich and data-deprived environments. Applied autonomy will enable safety, efficiency and unprecedented mobility as people and goods take to the skies tomorrow just as we do on the road today.

Avoiding space robot collisions utilizing the NASA/GSFC tri-mode skin sensor

NASA Technical Reports Server (NTRS)

Prinz, F. B.

1991-01-01

Sensor based robot motion planning research has primarily focused on mobile robots. Consider, however, the case of a robot manipulator expected to operate autonomously in a dynamic environment where unexpected collisions can occur with many parts of the robot. Only a sensor based system capable of generating collision free paths would be acceptable in such situations. Recently, work in this area has been reported in which a deterministic solution for 2DOF systems has been generated. The arm was sensitized with 'skin' of infra-red sensors. We have proposed a heuristic (potential field based) methodology for redundant robots with large DOF's. The key concepts are solving the path planning problem by cooperating global and local planning modules, the use of complete information from the sensors and partial (but appropriate) information from a world model, representation of objects with hyper-ellipsoids in the world model, and the use of variational planning. We intend to sensitize the robot arm with a 'skin' of capacitive proximity sensors. These sensors were developed at NASA, and are exceptionally suited for the space application. In the first part of the report, we discuss the development and modeling of the capacitive proximity sensor. In the second part we discuss the motion planning algorithm.

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.

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.

Path Planning for Non-Circular, Non-Holonomic Robots in Highly Cluttered Environments.

PubMed

Samaniego, Ricardo; Lopez, Joaquin; Vazquez, Fernando

2017-08-15

This paper presents an algorithm for finding a solution to the problem of planning a feasible path for a slender autonomous mobile robot in a large and cluttered environment. The presented approach is based on performing a graph search on a kinodynamic-feasible lattice state space of high resolution; however, the technique is applicable to many search algorithms. With the purpose of allowing the algorithm to consider paths that take the robot through narrow passes and close to obstacles, high resolutions are used for the lattice space and the control set. This introduces new challenges because one of the most computationally expensive parts of path search based planning algorithms is calculating the cost of each one of the actions or steps that could potentially be part of the trajectory. The reason for this is that the evaluation of each one of these actions involves convolving the robot's footprint with a portion of a local map to evaluate the possibility of a collision, an operation that grows exponentially as the resolution is increased. The novel approach presented here reduces the need for these convolutions by using a set of offline precomputed maps that are updated, by means of a partial convolution, as new information arrives from sensors or other sources. Not only does this improve run-time performance, but it also provides support for dynamic search in changing environments. A set of alternative fast convolution methods are also proposed, depending on whether the environment is cluttered with obstacles or not. Finally, we provide both theoretical and experimental results from different experiments and applications.

Vision-based mapping with cooperative robots

NASA Astrophysics Data System (ADS)

Little, James J.; Jennings, Cullen; Murray, Don

1998-10-01

Two stereo-vision-based mobile robots navigate and autonomously explore their environment safely while building occupancy grid maps of the environment. The robots maintain position estimates within a global coordinate frame using landmark recognition. This allows them to build a common map by sharing position information and stereo data. Stereo vision processing and map updates are done at 3 Hz and the robots move at speeds of 200 cm/s. Cooperative mapping is achieved through autonomous exploration of unstructured and dynamic environments. The map is constructed conservatively, so as to be useful for collision-free path planning. Each robot maintains a separate copy of a shared map, and then posts updates to the common map when it returns to observe a landmark at home base. Issues include synchronization, mutual localization, navigation, exploration, registration of maps, merging repeated views (fusion), centralized vs decentralized maps.

Biogeography-based combinatorial strategy for efficient autonomous underwater vehicle motion planning and task-time management

NASA Astrophysics Data System (ADS)

Zadeh, S. M.; Powers, D. M. W.; Sammut, K.; Yazdani, A. M.

2016-12-01

Autonomous Underwater Vehicles (AUVs) are capable of spending long periods of time for carrying out various underwater missions and marine tasks. In this paper, a novel conflict-free motion planning framework is introduced to enhance underwater vehicle's mission performance by completing maximum number of highest priority tasks in a limited time through a large scale waypoint cluttered operating field, and ensuring safe deployment during the mission. The proposed combinatorial route-path planner model takes the advantages of the Biogeography-Based Optimization (BBO) algorithm toward satisfying objectives of both higher-lower level motion planners and guarantees maximization of the mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios including the particular cost constraints in time-varying operating fields. To show the reliability of the proposed model, performance of each motion planner assessed separately and then statistical analysis is undertaken to evaluate the total performance of the entire model. The simulation results indicate the stability of the contributed model and its feasible application for real experiments.

Dynamic Curvature Steering Control for Autonomous Vehicle: Performance Analysis

NASA Astrophysics Data System (ADS)

Aizzat Zakaria, Muhammad; Zamzuri, Hairi; Amri Mazlan, Saiful

2016-02-01

This paper discusses the design of dynamic curvature steering control for autonomous vehicle. The lateral control and longitudinal control are discussed in this paper. The controller is designed based on the dynamic curvature calculation to estimate the path condition and modify the vehicle speed and steering wheel angle accordingly. In this paper, the simulation results are presented to show the capability of the controller to track the reference path. The controller is able to predict the path and modify the vehicle speed to suit the path condition. The effectiveness of the controller is shown in this paper whereby identical performance is achieved with the benchmark but with extra curvature adaptation capabilites.

Learning from Demonstration for Autonomous Navigation in Complex Unstructured Terrain

DTIC Science & Technology

2010-06-24

unstructured terrain Seraji and Howard, 2002, Huertas et al., 2005, Biesiadecki and Maimone, 2006] The common thread amongst these approaches is that they con...can be gathered either of- fline [ Seraji and Howard, 2002, Howard et al., 2007] or online [Thrun et al., 2006, Sun et al., 2007] by ob- serving where... Fe = F∗ = ~0; foreach P ie do P i∗ = planLossAugPath(start(P i e), goal(P ie), M); foreach x ∈ P ie do Fe + = Fe + Fx; foreach x ∈ P i∗ do F∗ = F∗ + Fx

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.

Merge Fuzzy Visual Servoing and GPS-Based Planning to Obtain a Proper Navigation Behavior for a Small Crop-Inspection Robot.

PubMed

Bengochea-Guevara, José M; Conesa-Muñoz, Jesus; Andújar, Dionisio; Ribeiro, Angela

2016-02-24

The concept of precision agriculture, which proposes farming management adapted to crop variability, has emerged in recent years. To effectively implement precision agriculture, data must be gathered from the field in an automated manner at minimal cost. In this study, a small autonomous field inspection vehicle was developed to minimise the impact of the scouting on the crop and soil compaction. The proposed approach integrates a camera with a GPS receiver to obtain a set of basic behaviours required of an autonomous mobile robot to inspect a crop field with full coverage. A path planner considered the field contour and the crop type to determine the best inspection route. An image-processing method capable of extracting the central crop row under uncontrolled lighting conditions in real time from images acquired with a reflex camera positioned on the front of the robot was developed. Two fuzzy controllers were also designed and developed to achieve vision-guided navigation. A method for detecting the end of a crop row using camera-acquired images was developed. In addition, manoeuvres necessary for the robot to change rows were established. These manoeuvres enabled the robot to autonomously cover the entire crop by following a previously established plan and without stepping on the crop row, which is an essential behaviour for covering crops such as maize without damaging them.

Merge Fuzzy Visual Servoing and GPS-Based Planning to Obtain a Proper Navigation Behavior for a Small Crop-Inspection Robot

PubMed Central

Bengochea-Guevara, José M.; Conesa-Muñoz, Jesus; Andújar, Dionisio; Ribeiro, Angela

2016-01-01

The concept of precision agriculture, which proposes farming management adapted to crop variability, has emerged in recent years. To effectively implement precision agriculture, data must be gathered from the field in an automated manner at minimal cost. In this study, a small autonomous field inspection vehicle was developed to minimise the impact of the scouting on the crop and soil compaction. The proposed approach integrates a camera with a GPS receiver to obtain a set of basic behaviours required of an autonomous mobile robot to inspect a crop field with full coverage. A path planner considered the field contour and the crop type to determine the best inspection route. An image-processing method capable of extracting the central crop row under uncontrolled lighting conditions in real time from images acquired with a reflex camera positioned on the front of the robot was developed. Two fuzzy controllers were also designed and developed to achieve vision-guided navigation. A method for detecting the end of a crop row using camera-acquired images was developed. In addition, manoeuvres necessary for the robot to change rows were established. These manoeuvres enabled the robot to autonomously cover the entire crop by following a previously established plan and without stepping on the crop row, which is an essential behaviour for covering crops such as maize without damaging them. PMID:26927102

Development and demonstration of autonomous behaviors for urban environment exploration

NASA Astrophysics Data System (ADS)

Ahuja, Gaurav; Fellars, Donald; Kogut, Gregory; Pacis Rius, Estrellina; Schoolov, Misha; Xydes, Alexander

2012-06-01

Under the Urban Environment Exploration project, the Space and Naval Warfare Systems Center Pacic (SSC- PAC) is maturing technologies and sensor payloads that enable man-portable robots to operate autonomously within the challenging conditions of urban environments. Previously, SSC-PAC has demonstrated robotic capabilities to navigate and localize without GPS and map the ground oors of various building sizes.1 SSC-PAC has since extended those capabilities to localize and map multiple multi-story buildings within a specied area. To facilitate these capabilities, SSC-PAC developed technologies that enable the robot to detect stairs/stairwells, maintain localization across multiple environments (e.g. in a 3D world, on stairs, with/without GPS), visualize data in 3D, plan paths between any two points within the specied area, and avoid 3D obstacles. These technologies have been developed as independent behaviors under the Autonomous Capabilities Suite, a behavior architecture, and demonstrated at a MOUT site at Camp Pendleton. This paper describes the perceptions and behaviors used to produce these capabilities, as well as an example demonstration scenario.

Fuzzy logic control system to provide autonomous collision avoidance for Mars rover vehicle

NASA Technical Reports Server (NTRS)

Murphy, Michael G.

1990-01-01

NASA is currently involved with planning unmanned missions to Mars to investigate the terrain and process soil samples in advance of a manned mission. A key issue involved in unmanned surface exploration on Mars is that of supporting autonomous maneuvering since radio communication involves lengthy delays. It is anticipated that specific target locations will be designated for sample gathering. In maneuvering autonomously from a starting position to a target position, the rover will need to avoid a variety of obstacles such as boulders or troughs that may block the shortest path to the target. The physical integrity of the rover needs to be maintained while minimizing the time and distance required to attain the target position. Fuzzy logic lends itself well to building reliable control systems that function in the presence of uncertainty or ambiguity. The following major issues are discussed: (1) the nature of fuzzy logic control systems and software tools to implement them; (2) collision avoidance in the presence of fuzzy parameters; and (3) techniques for adaptation in fuzzy logic control systems.

Broadening the trans-contextual model of motivation: A study with Spanish adolescents.

PubMed

González-Cutre, D; Sicilia, Á; Beas-Jiménez, M; Hagger, M S

2014-08-01

The original trans-contextual model of motivation proposed that autonomy support from teachers develops students' autonomous motivation in physical education (PE), and that autonomous motivation is transferred from PE contexts to physical activity leisure-time contexts, and predicts attitudes, perceived behavioral control and subjective norms, and forming intentions to participate in future physical activity behavior. The purpose of this study was to test an extended trans-contextual model of motivation including autonomy support from peers and parents and basic psychological needs in a Spanish sample. School students (n = 400) aged between 12 and 18 years completed measures of perceived autonomy support from three sources, autonomous motivation and constructs from the theory of planned behavior at three different points in time and in two contexts, PE and leisure-time. A path analysis controlling for past physical activity behavior supported the main postulates of the model. Autonomous motivation in a PE context predicted autonomous motivation in a leisure-time physical activity context, perceived autonomy support from teachers predicted satisfaction of basic psychological needs in PE, and perceived autonomy support from peers and parents predicted need satisfaction in leisure-time. This study provides a cross-cultural replication of the trans-contextual model of motivation and broadens it to encompass basic psychological needs. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Managing search complexity in linguistic geometry.

PubMed

Stilman, B

1997-01-01

This paper is a new step in the development of linguistic geometry. This formal theory is intended to discover and generalize the inner properties of human expert heuristics, which have been successful in a certain class of complex control systems, and apply them to different systems. In this paper, we investigate heuristics extracted in the form of hierarchical networks of planning paths of autonomous agents. Employing linguistic geometry tools the dynamic hierarchy of networks is represented as a hierarchy of formal attribute languages. The main ideas of this methodology are shown in the paper on two pilot examples of the solution of complex optimization problems. The first example is a problem of strategic planning for the air combat, in which concurrent actions of four vehicles are simulated as serial interleaving moves. The second example is a problem of strategic planning for the space comb of eight autonomous vehicles (with interleaving moves) that requires generation of the search tree of the depth 25 with the branching factor 30. This is beyond the capabilities of modern and conceivable future computers (employing conventional approaches). In both examples the linguistic geometry tools showed deep and highly selective searches in comparison with conventional search algorithms. For the first example a sketch of the proof of optimality of the solution is considered.

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.

Tracking Control of Mobile Robots Localized via Chained Fusion of Discrete and Continuous Epipolar Geometry, IMU and Odometry.

PubMed

Tick, David; Satici, Aykut C; Shen, Jinglin; Gans, Nicholas

2013-08-01

This paper presents a novel navigation and control system for autonomous mobile robots that includes path planning, localization, and control. A unique vision-based pose and velocity estimation scheme utilizing both the continuous and discrete forms of the Euclidean homography matrix is fused with inertial and optical encoder measurements to estimate the pose, orientation, and velocity of the robot and ensure accurate localization and control signals. A depth estimation system is integrated in order to overcome the loss of scale inherent in vision-based estimation. A path following control system is introduced that is capable of guiding the robot along a designated curve. Stability analysis is provided for the control system and experimental results are presented that prove the combined localization and control system performs with high accuracy.

Optimization of OSPF Routing in IP Networks

NASA Astrophysics Data System (ADS)

Bley, Andreas; Fortz, Bernard; Gourdin, Eric; Holmberg, Kaj; Klopfenstein, Olivier; Pióro, Michał; Tomaszewski, Artur; Ümit, Hakan

The Internet is a huge world-wide packet switching network comprised of more than 13,000 distinct subnetworks, referred to as Autonomous Systems (ASs) autonomous system AS . They all rely on the Internet Protocol (IP) internet protocol IP for transport of packets across the network. And most of them use shortest path routing protocols shortest path routing!protocols , such as OSPF or IS-IS, to control the routing of IP packets routing!of IP packets within an AS. The idea of the routing is extremely simple — every packet is forwarded on IP links along the shortest route between its source and destination nodes of the AS. The AS network administrator can manage the routing of packets in the AS by supplying the so-called administrative weights of IP links, which specify the link lengths that are used by the routing protocols for their shortest path computations. The main advantage of the shortest path routing policy is its simplicity, allowing for little administrative overhead. From the network engineering perspective, however, shortest path routing can pose problems in achieving satisfactory traffic handling efficiency. As all routing paths depend on the same routing metric routing!metric , it is not possible to configure the routing paths for the communication demands between different pairs of nodes explicitly or individually; the routing can be controlled only indirectly and only as a whole by modifying the routing metric. Thus, one of the main tasks when planning such networks is to find administrative link weights that induce a globally efficient traffic routing traffic!routing configuration of an AS. It turns out that this task leads to very difficult mathematical optimization problems. In this chapter, we discuss and describe exact integer programming models and solution approaches as well as practically efficient smart heuristics for such shortest path routing problems shortest path routing!problems .

Single-Command Approach and Instrument Placement by a Robot on a Target

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Cheng, Yang

2005-01-01

AUTOAPPROACH is a computer program that enables a mobile robot to approach a target autonomously, starting from a distance of as much as 10 m, in response to a single command. AUTOAPPROACH is used in conjunction with (1) software that analyzes images acquired by stereoscopic cameras aboard the robot and (2) navigation and path-planning software that utilizes odometer readings along with the output of the image-analysis software. Intended originally for application to an instrumented, wheeled robot (rover) in scientific exploration of Mars, AUTOAPPROACH could be adapted to terrestrial applications, notably including the robotic removal of land mines and other unexploded ordnance. A human operator generates the approach command by selecting the target in images acquired by the robot cameras. The approach path consists of multiple legs. Feature points are derived from images that contain the target and are thereafter tracked to correct odometric errors and iteratively refine estimates of the position and orientation of the robot relative to the target on successive legs. The approach is terminated when the robot attains the position and orientation required for placing a scientific instrument at the target. The workspace of the robot arm is then autonomously checked for self/terrain collisions prior to the deployment of the scientific instrument onto the target.

Autonomous Control Modes and Optimized Path Guidance for Shipboard Landing in High Sea States

DTIC Science & Technology

2016-04-28

Contract # N00014-14-C-0004 Autonomous Control Modes and Optimized Path Guidance for Shipboard Landing in High Sea States Progress Report...Aviation (ONR BAA12-SN-0028). This project addresses the Sea Based Aviation (SBA) initiative in Advanced Handling Qualities for Rotorcraft. Landing a...and a degraded visual environment, workload during the landing task begins to approach the limits of a human pilot’s capability. It is a similarly

Towards Autonomous Operations of the Robonaut 2 Humanoid Robotic Testbed

NASA Technical Reports Server (NTRS)

Badger, Julia; Nguyen, Vienny; Mehling, Joshua; Hambuchen, Kimberly; Diftler, Myron; Luna, Ryan; Baker, William; Joyce, Charles

2016-01-01

The Robonaut project has been conducting research in robotics technology on board the International Space Station (ISS) since 2012. Recently, the original upper body humanoid robot was upgraded by the addition of two climbing manipulators ("legs"), more capable processors, and new sensors, as shown in Figure 1. While Robonaut 2 (R2) has been working through checkout exercises on orbit following the upgrade, technology development on the ground has continued to advance. Through the Active Reduced Gravity Offload System (ARGOS), the Robonaut team has been able to develop technologies that will enable full operation of the robotic testbed on orbit using similar robots located at the Johnson Space Center. Once these technologies have been vetted in this way, they will be implemented and tested on the R2 unit on board the ISS. The goal of this work is to create a fully-featured robotics research platform on board the ISS to increase the technology readiness level of technologies that will aid in future exploration missions. Technology development has thus far followed two main paths, autonomous climbing and efficient tool manipulation. Central to both technologies has been the incorporation of a human robotic interaction paradigm that involves the visualization of sensory and pre-planned command data with models of the robot and its environment. Figure 2 shows screenshots of these interactive tools, built in rviz, that are used to develop and implement these technologies on R2. Robonaut 2 is designed to move along the handrails and seat track around the US lab inside the ISS. This is difficult for many reasons, namely the environment is cluttered and constrained, the robot has many degrees of freedom (DOF) it can utilize for climbing, and remote commanding for precision tasks such as grasping handrails is time-consuming and difficult. Because of this, it is important to develop the technologies needed to allow the robot to reach operator-specified positions as autonomously as possible. The most important progress in this area has been the work towards efficient path planning for high DOF, highly constrained systems. Other advances include machine vision algorithms for localizing and automatically docking with handrails, the ability of the operator to place obstacles in the robot's virtual environment, autonomous obstacle avoidance techniques, and constraint management.

SNC’s Dream Chaser Achieves Successful Free Flight at NASA Armstrong

NASA Image and Video Library

2017-11-17

Sierra Nevada Corporation's Dream Chaser® spacecraft underwent a successful free-flight test on November 11, 2017 at NASA’s Armstrong Flight Research Center, Edwards, California. The test verified and validated the performance of the Dream Chaser in the critical final approach and landing phase of flight, meeting expected models for a future return from the International Space Station. The full-scale Dream Chaser test vehicle was lifted to 12,400 feet altitude by a 234-UT Chinook helicopter, released and flew a pre-planned flight path ending with a successful autonomous landing.

Autonomous Control Modes and Optimized Path Guidance for Shipboard Landing in High Sea States

DTIC Science & Technology

2016-08-12

Performing Organization: The Pennsylvania State University Department of Aerospace Engineering 231C Hammond Building University Park, PA 16802 Attn...Plant Models Used in the Study The H-60 class model was developed and distributed by ART to both NAVAIR and Penn State research teams. The model...To) 07 109 I 201 4 tD 07 I 08 12016 ’t TITLE AND SUBTITLE Autonomous Control Modes and Optimized Path Guidance for Shipboard Landing in High Sea States

Development and Evaluation of Positioning Systems for Autonomous Vehicle Navigation

DTIC Science & Technology

2001-12-01

generation of autonomous vehicles to utilize NTV technology is built on a commercially-available vehicle built by ASV. The All-Purpose Remote Transport...larger scale, AFRL and CIMAR are involved in the development of a standard approach in the design and specification of autonomous vehicles being...1996. Shi92 Shin, D.H., Sanjiv, S., and Lee, J.J., “Explicit Path Tracking by Autonomous Vehicles ,” Robotica, 10, (1992), 69-87. Ste95

Multipass Target Search in Natural Environments

PubMed Central

Otte, Michael W.; Sofge, Donald; Gupta, Satyandra K.

2017-01-01

Consider a disaster scenario where search and rescue workers must search difficult to access buildings during an earthquake or flood. Often, finding survivors a few hours sooner results in a dramatic increase in saved lives, suggesting the use of drones for expedient rescue operations. Entropy can be used to quantify the generation and resolution of uncertainty. When searching for targets, maximizing mutual information of future sensor observations will minimize expected target location uncertainty by minimizing the entropy of the future estimate. Motion planning for multi-target autonomous search requires planning over an area with an imperfect sensor and may require multiple passes, which is hindered by the submodularity property of mutual information. Further, mission duration constraints must be handled accordingly, requiring consideration of the vehicle’s dynamics to generate feasible trajectories and must plan trajectories spanning the entire mission duration, something which most information gathering algorithms are incapable of doing. If unanticipated changes occur in an uncertain environment, new plans must be generated quickly. In addition, planning multipass trajectories requires evaluating path dependent rewards, requiring planning in the space of all previously selected actions, compounding the problem. We present an anytime algorithm for autonomous multipass target search in natural environments. The algorithm is capable of generating long duration dynamically feasible multipass coverage plans that maximize mutual information using a variety of techniques such as ϵ-admissible heuristics to speed up the search. To the authors’ knowledge this is the first attempt at efficiently solving multipass target search problems of such long duration. The proposed algorithm is based on best first branch and bound and is benchmarked against state of the art algorithms adapted to the problem in natural Simplex environments, gathering the most information in the given search time. PMID:29099087

Sensor-driven area coverage for an autonomous fixed-wing unmanned aerial vehicle.

PubMed

Paull, Liam; Thibault, Carl; Nagaty, Amr; Seto, Mae; Li, Howard

2014-09-01

Area coverage with an onboard sensor is an important task for an unmanned aerial vehicle (UAV) with many applications. Autonomous fixed-wing UAVs are more appropriate for larger scale area surveying since they can cover ground more quickly. However, their non-holonomic dynamics and susceptibility to disturbances make sensor coverage a challenging task. Most previous approaches to area coverage planning are offline and assume that the UAV can follow the planned trajectory exactly. In this paper, this restriction is removed as the aircraft maintains a coverage map based on its actual pose trajectory and makes control decisions based on that map. The aircraft is able to plan paths in situ based on sensor data and an accurate model of the on-board camera used for coverage. An information theoretic approach is used that selects desired headings that maximize the expected information gain over the coverage map. In addition, the branch entropy concept previously developed for autonomous underwater vehicles is extended to UAVs and ensures that the vehicle is able to achieve its global coverage mission. The coverage map over the workspace uses the projective camera model and compares the expected area of the target on the ground and the actual area covered on the ground by each pixel in the image. The camera is mounted on a two-axis gimbal and can either be stabilized or optimized for maximal coverage. Hardware-in-the-loop simulation results and real hardware implementation on a fixed-wing UAV show the effectiveness of the approach. By including the already developed automatic takeoff and landing capabilities, we now have a fully automated and robust platform for performing aerial imagery surveys.

Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles

NASA Astrophysics Data System (ADS)

Aghababa, Mohammad Pourmahmood; Amrollahi, Mohammad Hossein; Borjkhani, Mehdi

2012-09-01

In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP). An energy performance index as a cost function, which should be minimized, was defined. The resulting problem was a two-point boundary value problem (TPBVP). A genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.

Mid-L/D Lifting Body Entry Demise Analysis

NASA Technical Reports Server (NTRS)

Ling, Lisa

2017-01-01

The mid-lift-to-drag ratio (mid-L/D) lifting body is a fully autonomous spacecraft under design at NASA for enabling a rapid return of scientific payloads from the International Space Station (ISS). For contingency planning and risk assessment for the Earth-return trajectory, an entry demise analysis was performed to examine three potential failure scenarios: (1) nominal entry interface conditions with loss of control, (2) controlled entry at maximum flight path angle, and (3) controlled entry at minimum flight path angle. The objectives of the analysis were to predict the spacecraft breakup sequence and timeline, determine debris survival, and calculate the debris dispersion footprint. Sensitivity analysis was also performed to determine the effect of the initial pitch rate on the spacecraft stability and breakup during the entry. This report describes the mid-L/D lifting body and presents the results of the entry demise and sensitivity analyses.

Rapid Onboard Trajectory Design for Autonomous Spacecraft in Multibody Systems

NASA Astrophysics Data System (ADS)

Trumbauer, Eric Michael

This research develops automated, on-board trajectory planning algorithms in order to support current and new mission concepts. These include orbiter missions to Phobos or Deimos, Outer Planet Moon orbiters, and robotic and crewed missions to small bodies. The challenges stem from the limited on-board computing resources which restrict full trajectory optimization with guaranteed convergence in complex dynamical environments. The approach taken consists of leveraging pre-mission computations to create a large database of pre-computed orbits and arcs. Such a database is used to generate a discrete representation of the dynamics in the form of a directed graph, which acts to index these arcs. This allows the use of graph search algorithms on-board in order to provide good approximate solutions to the path planning problem. Coupled with robust differential correction and optimization techniques, this enables the determination of an efficient path between any boundary conditions with very little time and computing effort. Furthermore, the optimization methods developed here based on sequential convex programming are shown to have provable convergence properties, as well as generating feasible major iterates in case of a system interrupt -- a key requirement for on-board application. The outcome of this project is thus the development of an algorithmic framework which allows the deployment of this approach in a variety of specific mission contexts. Test cases related to missions of interest to NASA and JPL such as a Phobos orbiter and a Near Earth Asteroid interceptor are demonstrated, including the results of an implementation on the RAD750 flight processor. This method fills a gap in the toolbox being developed to create fully autonomous space exploration systems.

Autonomous soaring and surveillance in wind fields with an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Gao, Chen

Small unmanned aerial vehicles (UAVs) play an active role in developing a low-cost, low-altitude autonomous aerial surveillance platform. The success of the applications needs to address the challenge of limited on-board power plant that limits the endurance performance in surveillance mission. This thesis studies the mechanics of soaring flight, observed in nature where birds utilize various wind patterns to stay airborne without flapping their wings, and investigates its application to small UAVs in their surveillance missions. In a proposed integrated framework of soaring and surveillance, a bird-mimicking soaring maneuver extracts energy from surrounding wind environment that improves surveillance performance in terms of flight endurance, while the surveillance task not only covers the target area, but also detects energy sources within the area to allow for potential soaring flight. The interaction of soaring and surveillance further enables novel energy based, coverage optimal path planning. Two soaring and associated surveillance strategies are explored. In a so-called static soaring surveillance, the UAV identifies spatially-distributed thermal updrafts for soaring, while incremental surveillance is achieved through gliding flight to visit concentric expanding regions. A Gaussian-process-regression-based algorithm is developed to achieve computationally-efficient and smooth updraft estimation. In a so-called dynamic soaring surveillance, the UAV performs one cycle of dynamic soaring to harvest energy from the horizontal wind gradient to complete one surveillance task by visiting from one target to the next one. A Dubins-path-based trajectory planning approach is proposed to maximize wind energy extraction and ensure smooth transition between surveillance tasks. Finally, a nonlinear trajectory tracking controller is designed for a full six-degree-of-freedom nonlinear UAV dynamics model and extensive simulations are carried to demonstrate the effectiveness of the proposed soaring and surveillance strategies.

A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots.

PubMed

Sherwin, Tyrone; Easte, Mikala; Chen, Andrew Tzer-Yeu; Wang, Kevin I-Kai; Dai, Wenbin

2018-02-14

Location-aware services are one of the key elements of modern intelligent applications. Numerous real-world applications such as factory automation, indoor delivery, and even search and rescue scenarios require autonomous robots to have the ability to navigate in an unknown environment and reach mobile targets with minimal or no prior infrastructure deployment. This research investigates and proposes a novel approach of dynamic target localisation using a single RF emitter, which will be used as the basis of allowing autonomous robots to navigate towards and reach a target. Through the use of multiple directional antennae, Received Signal Strength (RSS) is compared to determine the most probable direction of the targeted emitter, which is combined with the distance estimates to improve the localisation performance. The accuracy of the position estimate is further improved using a particle filter to mitigate the fluctuating nature of real-time RSS data. Based on the direction information, a motion control algorithm is proposed, using Simultaneous Localisation and Mapping (SLAM) and A* path planning to enable navigation through unknown complex environments. A number of navigation scenarios were developed in the context of factory automation applications to demonstrate and evaluate the functionality and performance of the proposed system.

A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots

PubMed Central

Sherwin, Tyrone; Easte, Mikala; Wang, Kevin I-Kai; Dai, Wenbin

2018-01-01

Location-aware services are one of the key elements of modern intelligent applications. Numerous real-world applications such as factory automation, indoor delivery, and even search and rescue scenarios require autonomous robots to have the ability to navigate in an unknown environment and reach mobile targets with minimal or no prior infrastructure deployment. This research investigates and proposes a novel approach of dynamic target localisation using a single RF emitter, which will be used as the basis of allowing autonomous robots to navigate towards and reach a target. Through the use of multiple directional antennae, Received Signal Strength (RSS) is compared to determine the most probable direction of the targeted emitter, which is combined with the distance estimates to improve the localisation performance. The accuracy of the position estimate is further improved using a particle filter to mitigate the fluctuating nature of real-time RSS data. Based on the direction information, a motion control algorithm is proposed, using Simultaneous Localisation and Mapping (SLAM) and A* path planning to enable navigation through unknown complex environments. A number of navigation scenarios were developed in the context of factory automation applications to demonstrate and evaluate the functionality and performance of the proposed system. PMID:29443906

From goal motivation to goal progress: the mediating role of coping in the Self-Concordance Model.

PubMed

Gaudreau, Patrick; Carraro, Natasha; Miranda, Dave

2012-01-01

The present studies examined the mediating role of self-regulatory mechanisms in the relationship between goal motivation and goal progress in the Self-Concordance Model. First, a systematic review, using meta-analytical path analysis, supported the mediating role of effort and action planning in the positive association between autonomous goal motivation and goal progress. Second, results from two additional empirical studies, using structural equation modeling, lent credence to the mediating role of coping in the relationship between goal motivation and goal progress of university students. Autonomous goal motivation was positively associated with task-oriented coping, which predicted greater goal progress during midterm exams (Study 1, N=702) and at the end of the semester in a different sample (Study 2, N=167). Controlled goal motivation was associated with greater disengagement-oriented coping (Study 1 and Study 2) and lesser use of task-oriented coping (Study 2), which reduced goal progress. These results held up after controlling for perceived stress (Study 2). Our findings highlight the importance of coping in the "inception-to-attainment" goal process because autonomous goal motivation indirectly rather than directly predicts goal progress of university students through their usage of task-oriented coping.

Autonomous Mission Design in Extreme Orbit Environments

NASA Astrophysics Data System (ADS)

Surovik, David Allen

An algorithm for autonomous online mission design at asteroids, comets, and small moons is developed to meet the novel challenges of their complex non-Keplerian orbit environments, which render traditional methods inapplicable. The core concept of abstract reachability analysis, in which a set of impulsive maneuvering options is mapped onto a space of high-level mission outcomes, is applied to enable goal-oriented decision-making with robustness to uncertainty. These nuanced analyses are efficiently computed by utilizing a heuristic-based adaptive sampling scheme that either maximizes an objective function for autonomous planning or resolves details of interest for preliminary analysis and general study. Illustrative examples reveal the chaotic nature of small body systems through the structure of various families of reachable orbits, such as those that facilitate close-range observation of targeted surface locations or achieve soft impact upon them. In order to fulfill extensive sets of observation tasks, the single-maneuver design method is implemented in a receding-horizon framework such that a complete mission is constructed on-the-fly one piece at a time. Long-term performance and convergence are assured by augmenting the objective function with a prospect heuristic, which approximates the likelihood that a reachable end-state will benefit the subsequent planning horizon. When state and model uncertainty produce larger trajectory deviations than were anticipated, the next control horizon is advanced to allow for corrective action -- a low-frequency form of feedback control. Through Monte Carlo analysis, the planning algorithm is ultimately demonstrated to produce mission profiles that vary drastically in their physical paths but nonetheless consistently complete all goals, suggesting a high degree of flexibility. It is further shown that the objective function can be tuned to preferentially minimize fuel cost or mission duration, as well as to optimize performance under different levels of uncertainty by appropriately balancing the mitigation paradigms of robust planning and reactive execution.

Teacher, peer and parent autonomy support in physical education and leisure-time physical activity: A trans-contextual model of motivation in four nations.

PubMed

Hagger, Martin; Chatzisarantis, Nikos L D; Hein, Vello; Soós, István; Karsai, István; Lintunen, Taru; Leemans, Sofie

2009-07-01

An extended trans-contextual model of motivation for health-related physical activity was tested in samples from four nations. The model proposes a motivational sequence in which perceived autonomy support from teachers in a physical education (PE) context and from peers and parents in a leisure-time physical activity context predict autonomous motivation, intentions and physical activity behaviour in a leisure-time context. A three-wave prospective correlational design was employed. High-school pupils from Britain, Estonia, Finland and Hungary completed measures of perceived autonomy support from PE teachers, autonomous motivation in both contexts, perceived autonomy support from peers and parents, attitudes, subjective norms, perceived behavioural control and intentions from the Theory of Planned Behaviour (TPB), and measures of behaviour and past behaviour in a leisure-time context. Path-analyses controlling for past behaviour supported trans-contextual model hypotheses across all samples. Effects of perceived autonomy support from peers and parents on leisure-time autonomous motivation were small and inconsistent, while effects on TPB variables were stronger. There was a unique effect of perceived autonomy support from PE teachers on leisure-time autonomous motivation. Findings support the model, which provides an explanation of the processes by which perceived autonomy support from different sources affects health-related physical activity motivation across these contexts.

Handling Trajectory Uncertainties for Airborne Conflict Management

NASA Technical Reports Server (NTRS)

Barhydt, Richard; Doble, Nathan A.; Karr, David; Palmer, Michael T.

2005-01-01

Airborne conflict management is an enabling capability for NASA's Distributed Air-Ground Traffic Management (DAG-TM) concept. DAGTM has the goal of significantly increasing capacity within the National Airspace System, while maintaining or improving safety. Under DAG-TM, autonomous aircraft maintain separation from each other and from managed aircraft unequipped for autonomous flight. NASA Langley Research Center has developed the Autonomous Operations Planner (AOP), an onboard decision support system that provides airborne conflict management (ACM) and strategic flight planning support for autonomous aircraft pilots. The AOP performs conflict detection, prevention, and resolution from nearby traffic aircraft and area hazards. Traffic trajectory information is assumed to be provided by Automatic Dependent Surveillance Broadcast (ADS-B). Reliable trajectory prediction is a key capability for providing effective ACM functions. Trajectory uncertainties due to environmental effects, differences in aircraft systems and performance, and unknown intent information lead to prediction errors that can adversely affect AOP performance. To accommodate these uncertainties, the AOP has been enhanced to create cross-track, vertical, and along-track buffers along the predicted trajectories of both ownship and traffic aircraft. These buffers will be structured based on prediction errors noted from previous simulations such as a recent Joint Experiment between NASA Ames and Langley Research Centers and from other outside studies. Currently defined ADS-B parameters related to navigation capability, trajectory type, and path conformance will be used to support the algorithms that generate the buffers.

Robust H∞ output-feedback control for path following of autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Hu, Chuan; Jing, Hui; Wang, Rongrong; Yan, Fengjun; Chadli, Mohammed

2016-03-01

This paper presents a robust H∞ output-feedback control strategy for the path following of autonomous ground vehicles (AGVs). Considering the vehicle lateral velocity is usually hard to measure with low cost sensor, a robust H∞ static output-feedback controller based on the mixed genetic algorithms (GA)/linear matrix inequality (LMI) approach is proposed to realize the path following without the information of the lateral velocity. The proposed controller is robust to the parametric uncertainties and external disturbances, with the parameters including the tire cornering stiffness, vehicle longitudinal velocity, yaw rate and road curvature. Simulation results based on CarSim-Simulink joint platform using a high-fidelity and full-car model have verified the effectiveness of the proposed control approach.

Robot Trajectories Comparison: A Statistical Approach

PubMed Central

Ansuategui, A.; Arruti, A.; Susperregi, L.; Yurramendi, Y.; Jauregi, E.; Lazkano, E.; Sierra, B.

2014-01-01

The task of planning a collision-free trajectory from a start to a goal position is fundamental for an autonomous mobile robot. Although path planning has been extensively investigated since the beginning of robotics, there is no agreement on how to measure the performance of a motion algorithm. This paper presents a new approach to perform robot trajectories comparison that could be applied to any kind of trajectories and in both simulated and real environments. Given an initial set of features, it automatically selects the most significant ones and performs a statistical comparison using them. Additionally, a graphical data visualization named polygraph which helps to better understand the obtained results is provided. The proposed method has been applied, as an example, to compare two different motion planners, FM2 and WaveFront, using different environments, robots, and local planners. PMID:25525618

Identification of limit cycles in multi-nonlinearity, multiple path systems

NASA Technical Reports Server (NTRS)

Mitchell, J. R.; Barron, O. L.

1979-01-01

A method of analysis which identifies limit cycles in autonomous systems with multiple nonlinearities and multiple forward paths is presented. The FORTRAN code for implementing the Harmonic Balance Algorithm is reported. The FORTRAN code is used to identify limit cycles in multiple path and nonlinearity systems while retaining the effects of several harmonic components.

Energy-optimal path planning in the coastal ocean

NASA Astrophysics Data System (ADS)

Subramani, Deepak N.; Haley, Patrick J.; Lermusiaux, Pierre F. J.

2017-05-01

We integrate data-driven ocean modeling with the stochastic Dynamically Orthogonal (DO) level-set optimization methodology to compute and study energy-optimal paths, speeds, and headings for ocean vehicles in the Middle-Atlantic Bight (MAB) region. We hindcast the energy-optimal paths from among exact time-optimal paths for the period 28 August 2006 to 9 September 2006. To do so, we first obtain a data-assimilative multiscale reanalysis, combining ocean observations with implicit two-way nested multiresolution primitive-equation simulations of the tidal-to-mesoscale dynamics in the region. Second, we solve the reduced-order stochastic DO level-set partial differential equations (PDEs) to compute the joint probability of minimum arrival time, vehicle-speed time series, and total energy utilized. Third, for each arrival time, we select the vehicle-speed time series that minimize the total energy utilization from the marginal probability of vehicle-speed and total energy. The corresponding energy-optimal path and headings are obtained through the exact particle-backtracking equation. Theoretically, the present methodology is PDE-based and provides fundamental energy-optimal predictions without heuristics. Computationally, it is 3-4 orders of magnitude faster than direct Monte Carlo methods. For the missions considered, we analyze the effects of the regional tidal currents, strong wind events, coastal jets, shelfbreak front, and other local circulations on the energy-optimal paths. Results showcase the opportunities for vehicles that intelligently utilize the ocean environment to minimize energy usage, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.

Autonomous mobile robotic system for supporting counterterrorist and surveillance operations

NASA Astrophysics Data System (ADS)

Adamczyk, Marek; Bulandra, Kazimierz; Moczulski, Wojciech

2017-10-01

Contemporary research on mobile robots concerns applications to counterterrorist and surveillance operations. The goal is to develop systems that are capable of supporting the police and special forces by carrying out such operations. The paper deals with a dedicated robotic system for surveillance of large objects such as airports, factories, military bases, and many others. The goal is to trace unauthorised persons who try to enter to the guarded area, document the intrusion and report it to the surveillance centre, and then warn the intruder by sound messages and eventually subdue him/her by stunning through acoustic effect of great power. The system consists of several parts. An armoured four-wheeled robot assures required mobility of the system. The robot is equipped with a set of sensors including 3D mapping system, IR and video cameras, and microphones. It communicates with the central control station (CCS) by means of a wideband wireless encrypted system. A control system of the robot can operate autonomously, and under remote control. In the autonomous mode the robot follows the path planned by the CCS. Once an intruder has been detected, the robot can adopt its plan to allow tracking him/her. Furthermore, special procedures of treatment of the intruder are applied including warning about the breach of the border of the protected area, and incapacitation of an appropriately selected very loud sound until a patrol of guards arrives. Once getting stuck the robot can contact the operator who can remotely solve the problem the robot is faced with.

Data acquisition and path selection decision making for an autonomous roving vehicle

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Shen, C. N.; Yerazunis, S. W.

1976-01-01

Problems related to the guidance of an autonomous rover for unmanned planetary exploration were investigated. Topics included in these studies were: simulation on an interactive graphics computer system of the Rapid Estimation Technique for detection of discrete obstacles; incorporation of a simultaneous Bayesian estimate of states and inputs in the Rapid Estimation Scheme; development of methods for estimating actual laser rangefinder errors and their application to date provided by Jet Propulsion Laboratory; and modification of a path selection system simulation computer code for evaluation of a hazard detection system based on laser rangefinder data.

Modeling and Classifying Six-Dimensional Trajectories for Teleoperation Under a Time Delay

NASA Technical Reports Server (NTRS)

SunSpiral, Vytas; Wheeler, Kevin R.; Allan, Mark B.; Martin, Rodney

2006-01-01

Within the context of teleoperating the JSC Robonaut humanoid robot under 2-10 second time delays, this paper explores the technical problem of modeling and classifying human motions represented as six-dimensional (position and orientation) trajectories. A dual path research agenda is reviewed which explored both deterministic approaches and stochastic approaches using Hidden Markov Models. Finally, recent results are shown from a new model which represents the fusion of these two research paths. Questions are also raised about the possibility of automatically generating autonomous actions by reusing the same predictive models of human behavior to be the source of autonomous control. This approach changes the role of teleoperation from being a stand-in for autonomy into the first data collection step for developing generative models capable of autonomous control of the robot.

Probabilistic Tracking and Trajectory Planning for Autonomous Ground Vehicles in Urban Environments

DTIC Science & Technology

2016-03-05

SECURITY CLASSIFICATION OF: The aim of this research is to develop a unified theory for perception and planning in autonomous ground vehicles, with a...Report Title The aim of this research is to develop a unified theory for perception and planning in autonomous ground vehicles, with a specific focus on...a combination of experimentally collected vision data and Monte- Carlo simulations. Smoothing for improved perception and robustness in planning

Application of parallelized software architecture to an autonomous ground vehicle

NASA Astrophysics Data System (ADS)

Shakya, Rahul; Wright, Adam; Shin, Young Ho; Momin, Orko; Petkovsek, Steven; Wortman, Paul; Gautam, Prasanna; Norton, Adam

2011-01-01

This paper presents improvements made to Q, an autonomous ground vehicle designed to participate in the Intelligent Ground Vehicle Competition (IGVC). For the 2010 IGVC, Q was upgraded with a new parallelized software architecture and a new vision processor. Improvements were made to the power system reducing the number of batteries required for operation from six to one. In previous years, a single state machine was used to execute the bulk of processing activities including sensor interfacing, data processing, path planning, navigation algorithms and motor control. This inefficient approach led to poor software performance and made it difficult to maintain or modify. For IGVC 2010, the team implemented a modular parallel architecture using the National Instruments (NI) LabVIEW programming language. The new architecture divides all the necessary tasks - motor control, navigation, sensor data collection, etc. into well-organized components that execute in parallel, providing considerable flexibility and facilitating efficient use of processing power. Computer vision is used to detect white lines on the ground and determine their location relative to the robot. With the new vision processor and some optimization of the image processing algorithm used last year, two frames can be acquired and processed in 70ms. With all these improvements, Q placed 2nd in the autonomous challenge.

MOBLAB: a mobile laboratory for testing real-time vision-based systems in path monitoring

NASA Astrophysics Data System (ADS)

Cumani, Aldo; Denasi, Sandra; Grattoni, Paolo; Guiducci, Antonio; Pettiti, Giuseppe; Quaglia, Giorgio

1995-01-01

In the framework of the EUREKA PROMETHEUS European Project, a Mobile Laboratory (MOBLAB) has been equipped for studying, implementing and testing real-time algorithms which monitor the path of a vehicle moving on roads. Its goal is the evaluation of systems suitable to map the position of the vehicle within the environment where it moves, to detect obstacles, to estimate motion, to plan the path and to warn the driver about unsafe conditions. MOBLAB has been built with the financial support of the National Research Council and will be shared with teams working in the PROMETHEUS Project. It consists of a van equipped with an autonomous power supply, a real-time image processing system, workstations and PCs, B/W and color TV cameras, and TV equipment. This paper describes the laboratory outline and presents the computer vision system and the strategies that have been studied and are being developed at I.E.N. `Galileo Ferraris'. The system is based on several tasks that cooperate to integrate information gathered from different processes and sources of knowledge. Some preliminary results are presented showing the performances of the system.

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.

Optical information processing at NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Reid, Max B.; Bualat, Maria G.; Cho, Young C.; Downie, John D.; Gary, Charles K.; Ma, Paul W.; Ozcan, Meric; Pryor, Anna H.; Spirkovska, Lilly

1993-01-01

The combination of analog optical processors with digital electronic systems offers the potential of tera-OPS computational performance, while often requiring less power and weight relative to all-digital systems. NASA is working to develop and demonstrate optical processing techniques for on-board, real time science and mission applications. Current research areas and applications under investigation include optical matrix processing for space structure vibration control and the analysis of Space Shuttle Main Engine plume spectra, optical correlation-based autonomous vision for robotic vehicles, analog computation for robotic path planning, free-space optical interconnections for information transfer within digital electronic computers, and multiplexed arrays of fiber optic interferometric sensors for acoustic and vibration measurements.

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.

Simulation-Based Verification of Autonomous Controllers via Livingstone PathFinder

NASA Technical Reports Server (NTRS)

Lindsey, A. E.; Pecheur, Charles

2004-01-01

AI software is often used as a means for providing greater autonomy to automated systems, capable of coping with harsh and unpredictable environments. Due in part to the enormous space of possible situations that they aim to addrs, autonomous systems pose a serious challenge to traditional test-based verification approaches. Efficient verification approaches need to be perfected before these systems can reliably control critical applications. This publication describes Livingstone PathFinder (LPF), a verification tool for autonomous control software. LPF applies state space exploration algorithms to an instrumented testbed, consisting of the controller embedded in a simulated operating environment. Although LPF has focused on NASA s Livingstone model-based diagnosis system applications, the architecture is modular and adaptable to other systems. This article presents different facets of LPF and experimental results from applying the software to a Livingstone model of the main propulsion feed subsystem for a prototype space vehicle.

Mapping a Path to Autonomous Flight in the National Airspace

NASA Technical Reports Server (NTRS)

Lodding, Kenneth N.

2011-01-01

The introduction of autonomous flight, whether military, commercial, or civilian, into the National Airspace System (NAS) will present significant challenges. Minimizing the impact and preventing the changes from becoming disruptive, rather than an enhancing technology will not be without difficulty. From obstacle detection and avoidance to real-time verification and validation of system behavior, there are significant problems which must be solved prior to the general acceptance of autonomous systems. This paper examines some of the key challenges and the multi-disciplinary collaboration which must occur for autonomous systems to be accepted as equal partners in the NAS.

Layered Safe Motion Planning for Autonomous Vehicles.

DTIC Science & Technology

1995-09-01

The major problem addressed by this research is how to plan a safe motion for autonomous vehicles in a two dimensional, rectilinear world. With given start and goal configurations, the planner performs motion planning which

Intelligent systems for the autonomous exploration of Titan and Enceladus

NASA Astrophysics Data System (ADS)

Furfaro, Roberto; Lunine, Jonathan I.; Kargel, Jeffrey S.; Fink, Wolfgang

2008-04-01

Future planetary exploration of the outer satellites of the Solar System will require higher levels of onboard automation, including autonomous determination of sites where the probability of significant scientific findings is highest. Generally, the level of needed automation is heavily influenced by the distance between Earth and the robotic explorer(s) (e.g. spacecraft(s), rover(s), and balloon(s)). Therefore, planning missions to the outer satellites mandates the analysis, design and integration within the mission architecture of semi- and/or completely autonomous intelligence systems. Such systems should (1) include software packages that enable fully automated and comprehensive identification, characterization, and quantification of feature information within an operational region with subsequent target prioritization and selection for close-up reexamination; and (2) integrate existing information with acquired, "in transit" spatial and temporal sensor data to automatically perform intelligent planetary reconnaissance, which includes identification of sites with the highest potential to yield significant geological and astrobiological information. In this paper we review and compare some of the available Artificial Intelligence (AI) schemes and their adaptation to the problem of designing expert systems for onboard-based, autonomous science to be performed in the course of outer satellites exploration. More specifically, the fuzzy-logic framework proposed is analyzed in some details to show the effectiveness of such a scheme when applied to the problem of designing expert systems capable of identifying and further exploring regions on Titan and/or Enceladus that have the highest potential to yield evidence for past or present life. Based on available information (e.g., Cassini data), the current knowledge and understanding of Titan and Enceladus environments is evaluated to define a path for the design of a fuzzy-based system capable of reasoning over collected data and capable of providing the inference required to autonomously optimize future outer satellites explorations.

FlyAR: augmented reality supported micro aerial vehicle navigation.

PubMed

Zollmann, Stefanie; Hoppe, Christof; Langlotz, Tobias; Reitmayr, Gerhard

2014-04-01

Micro aerial vehicles equipped with high-resolution cameras can be used to create aerial reconstructions of an area of interest. In that context automatic flight path planning and autonomous flying is often applied but so far cannot fully replace the human in the loop, supervising the flight on-site to assure that there are no collisions with obstacles. Unfortunately, this workflow yields several issues, such as the need to mentally transfer the aerial vehicle’s position between 2D map positions and the physical environment, and the complicated depth perception of objects flying in the distance. Augmented Reality can address these issues by bringing the flight planning process on-site and visualizing the spatial relationship between the planned or current positions of the vehicle and the physical environment. In this paper, we present Augmented Reality supported navigation and flight planning of micro aerial vehicles by augmenting the user’s view with relevant information for flight planning and live feedback for flight supervision. Furthermore, we introduce additional depth hints supporting the user in understanding the spatial relationship of virtual waypoints in the physical world and investigate the effect of these visualization techniques on the spatial understanding.

A Safe Cooperative Framework for Atmospheric Science Missions with Multiple Heterogeneous UAS using Piecewise Bezier Curves

NASA Technical Reports Server (NTRS)

Mehdi, S. Bilal; Puig-Navarro, Javier; Choe, Ronald; Cichella, Venanzio; Hovakimyan, Naira; Chandarana, Meghan; Trujillo, Anna; Rothhaar, Paul M.; Tran, Loc; Neilan, James H.;

Planning and Execution for an Autonomous Aerobot

NASA Technical Reports Server (NTRS)

Gaines, Daniel M.; Estlin, Tara A.; Schaffer, Steven R.; Chouinard, Caroline M.

2010-01-01

The Aerial Onboard Autonomous Science Investigation System (AerOASIS) system provides autonomous planning and execution capabilities for aerial vehicles (see figure). The system is capable of generating high-quality operations plans that integrate observation requests from ground planning teams, as well as opportunistic science events detected onboard the vehicle while respecting mission and resource constraints. AerOASIS allows an airborne planetary exploration vehicle to summarize and prioritize the most scientifically relevant data; identify and select high-value science sites for additional investigation; and dynamically plan, schedule, and monitor the various science activities being performed, even during extended communications blackout periods with Earth.

Inverse optimal self-tuning PID control design for an autonomous underwater vehicle

NASA Astrophysics Data System (ADS)

Rout, Raja; Subudhi, Bidyadhar

2017-01-01

This paper presents a new approach to path following control design for an autonomous underwater vehicle (AUV). A NARMAX model of the AUV is derived first and then its parameters are adapted online using the recursive extended least square algorithm. An adaptive Propotional-Integral-Derivative (PID) controller is developed using the derived parameters to accomplish the path following task of an AUV. The gain parameters of the PID controller are tuned using an inverse optimal control technique, which alleviates the problem of solving Hamilton-Jacobian equation and also satisfies an error cost function. Simulation studies were pursued to verify the efficacy of the proposed control algorithm. From the obtained results, it is envisaged that the proposed NARMAX model-based self-tuning adaptive PID control provides good path following performance even in the presence of uncertainty arising due to ocean current or hydrodynamic parameter.

Computer-implemented method and apparatus for autonomous position determination using magnetic field data

NASA Technical Reports Server (NTRS)

Ketchum, Eleanor A. (Inventor)

2000-01-01

A computer-implemented method and apparatus for determining position of a vehicle within 100 km autonomously from magnetic field measurements and attitude data without a priori knowledge of position. An inverted dipole solution of two possible position solutions for each measurement of magnetic field data are deterministically calculated by a program controlled processor solving the inverted first order spherical harmonic representation of the geomagnetic field for two unit position vectors 180 degrees apart and a vehicle distance from the center of the earth. Correction schemes such as a successive substitutions and a Newton-Raphson method are applied to each dipole. The two position solutions for each measurement are saved separately. Velocity vectors for the position solutions are calculated so that a total energy difference for each of the two resultant position paths is computed. The position path with the smaller absolute total energy difference is chosen as the true position path of the vehicle.

Autonomous mobile platform with simultaneous localisation and mapping system for patrolling purposes

NASA Astrophysics Data System (ADS)

Mitka, Łukasz; Buratowski, Tomasz

2017-10-01

This work describes an autonomous mobile platform for supervision and surveillance purposes. The system can be adapted for mounting on different types of vehicles. The platform is based on a SLAM navigation system which performs a localization task. Sensor fusion including laser scanners, inertial measurement unit (IMU), odometry and GPS lets the system determine its position in a certain and precise way. The platform is able to create a 3D model of a supervised area and export it as a point cloud. The system can operate both inside and outside as the navigation algorithm is resistant to typical localization errors caused by wheel slippage or temporal GPS signal loss. The system is equipped with a path-planning module which allows operating in two modes. The first mode is for periodical observation of points in a selected area. The second mode is turned on in case of an alarm. When it is called, the platform moves with the fastest route to the place of the alert. The path planning is always performed online with use of the most current scans, therefore the platform is able to adjust its trajectory to the environment changes or obstacles that are in the motion. The control algorithms are developed under the Robot Operating System (ROS) since it comes with drivers for many devices used in robotics. Such a solution allows for extending the system with any type of sensor in order to incorporate its data into a created area model. Proposed appliance can be ported to other existing robotic platforms or used to develop a new platform dedicated to a specific kind of surveillance. The platform use cases are to patrol an area, such as airport or metro station, in search for dangerous substances or suspicious objects and in case of detection instantly inform security forces. Second use case is a tele-operation in hazardous area for an inspection purposes.

An Architecture for Autonomic Web Service Process Planning

NASA Astrophysics Data System (ADS)

Moore, Colm; Xue Wang, Ming; Pahl, Claus

Web service composition is a technology that has received considerable attention in the last number of years. Languages and tools to aid in the process of creating composite Web services have been received specific attention. Web service composition is the process of linking single Web services together in order to accomplish more complex tasks. One area of Web service composition that has not received as much attention is the area of dynamic error handling and re-planning, enabling autonomic composition. Given a repository of service descriptions and a task to complete, it is possible for AI planners to automatically create a plan that will achieve this goal. If however a service in the plan is unavailable or erroneous the plan will fail. Motivated by this problem, this paper suggests autonomous re-planning as a means to overcome dynamic problems. Our solution involves automatically recovering from faults and creating a context-dependent alternate plan. We present an architecture that serves as a basis for the central activities autonomous composition, monitoring and fault handling.

Optimal rotation sequences for active perception

NASA Astrophysics Data System (ADS)

Nakath, David; Rachuy, Carsten; Clemens, Joachim; Schill, Kerstin

2016-05-01

One major objective of autonomous systems navigating in dynamic environments is gathering information needed for self localization, decision making, and path planning. To account for this, such systems are usually equipped with multiple types of sensors. As these sensors often have a limited field of view and a fixed orientation, the task of active perception breaks down to the problem of calculating alignment sequences which maximize the information gain regarding expected measurements. Action sequences that rotate the system according to the calculated optimal patterns then have to be generated. In this paper we present an approach for calculating these sequences for an autonomous system equipped with multiple sensors. We use a particle filter for multi- sensor fusion and state estimation. The planning task is modeled as a Markov decision process (MDP), where the system decides in each step, what actions to perform next. The optimal control policy, which provides the best action depending on the current estimated state, maximizes the expected cumulative reward. The latter is computed from the expected information gain of all sensors over time using value iteration. The algorithm is applied to a manifold representation of the joint space of rotation and time. We show the performance of the approach in a spacecraft navigation scenario where the information gain is changing over time, caused by the dynamic environment and the continuous movement of the spacecraft

Time-Critical Cooperative Path Following of Multiple Unmanned Aerial Vehicles over Time-Varying Networks

DTIC Science & Technology

2013-03-01

Ciência e a Tecnologia . References [1] Kaminer, I., Pascoal, A.M., Hallberg, E., and Silvestreo, C., “Trajectory Tracking for Autonomous Vehicles: An...for publication). [53] Cichella, V., Xargay, E., Dobrokhodov, V., Kaminer, I., Pascoal, A. M., and Hovakimyan, N., “Geometric 3D Path-Following

Path selection system simulation and evaluation for a Martian roving vehicle

NASA Technical Reports Server (NTRS)

Boheim, S. L.; Prudon, W. C.

1972-01-01

The simulation and evaluation of proposed path selection systems for an autonomous Martian roving vehicle was developed. The package incorporates a number of realistic features, such as the simulation of random effects due to vehicle bounce and sensor-reading uncertainty, to increase the reliability of the results. Qualitative and quantitative evaluation criteria were established. The performance of three different path selection systems was evaluated to determine the effectiveness of the simulation package, and to form some preliminary conclusions regarding the tradeoffs involved in a path selection system design.

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

Mann, R.C.; Fujimura, K.; Unseren, M.A.

One of the frontiers in intelligent machine research is the understanding of how constructive cooperation among multiple autonomous agents can be effected. The effort at the Center for Engineering Systems Advanced Research (CESAR)at the Oak Ridge National Laboratory (ORNL) focuses on two problem areas: (1) cooperation by multiple mobile robots in dynamic, incompletely known environments; and (2) cooperating robotic manipulators. Particular emphasis is placed on experimental evaluation of research and developments using the CESAR robot system testbeds, including three mobile robots, and a seven-axis, kinematically redundant mobile manipulator. This paper summarizes initial results of research addressing the decoupling of positionmore » and force control for two manipulators holding a common object, and the path planning for multiple robots in a common workspace. 15 refs., 3 figs.« less

CMMAD Usability Case Study in Support of Countermine and Hazard Sensing

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

Victor G. Walker; David I. Gertman

2010-04-01

During field trials, operator usability data were collected in support of lane clearing missions and hazard sensing for two robot platforms with Robot Intelligence Kernel (RIK) software and sensor scanning payloads onboard. The tests featured autonomous and shared robot autonomy levels where tasking of the robot used a graphical interface featuring mine location and sensor readings. The goal of this work was to provide insights that could be used to further technology development. The efficacy of countermine systems in terms of mobility, search, path planning, detection, and localization were assessed. Findings from objective and subjective operator interaction measures are reviewedmore » along with commentary from soldiers having taken part in the study who strongly endorse the system.« less

A Petri-net coordination model for an intelligent mobile robot

NASA Technical Reports Server (NTRS)

Wang, F.-Y.; Kyriakopoulos, K. J.; Tsolkas, A.; Saridis, G. N.

1990-01-01

The authors present a Petri net model of the coordination level of an intelligent mobile robot system (IMRS). The purpose of this model is to specify the integration of the individual efforts on path planning, supervisory motion control, and vision systems that are necessary for the autonomous operation of the mobile robot in a structured dynamic environment. This is achieved by analytically modeling the various units of the system as Petri net transducers and explicitly representing the task precedence and information dependence among them. The model can also be used to simulate the task processing and to evaluate the efficiency of operations and the responsibility of decisions in the coordination level of the IMRS. Some simulation results on the task processing and learning are presented.

Decentralized Bayesian search using approximate dynamic programming methods.

PubMed

Zhao, Yijia; Patek, Stephen D; Beling, Peter A

2008-08-01

We consider decentralized Bayesian search problems that involve a team of multiple autonomous agents searching for targets on a network of search points operating under the following constraints: 1) interagent communication is limited; 2) the agents do not have the opportunity to agree in advance on how to resolve equivalent but incompatible strategies; and 3) each agent lacks the ability to control or predict with certainty the actions of the other agents. We formulate the multiagent search-path-planning problem as a decentralized optimal control problem and introduce approximate dynamic heuristics that can be implemented in a decentralized fashion. After establishing some analytical properties of the heuristics, we present computational results for a search problem involving two agents on a 5 x 5 grid.

Autonomous and controlled motivational regulations for multiple health-related behaviors: between- and within-participants analyses

PubMed Central

Hagger, M.S.; Hardcastle, S.J.; Chater, A.; Mallett, C.; Pal, S.; Chatzisarantis, N.L.D.

2014-01-01

Self-determination theory has been applied to the prediction of a number of health-related behaviors with self-determined or autonomous forms of motivation generally more effective in predicting health behavior than non-self-determined or controlled forms. Research has been confined to examining the motivational predictors in single health behaviors rather than comparing effects across multiple behaviors. The present study addressed this gap in the literature by testing the relative contribution of autonomous and controlling motivation to the prediction of a large number of health-related behaviors, and examining individual differences in self-determined motivation as a moderator of the effects of autonomous and controlling motivation on health behavior. Participants were undergraduate students (N = 140) who completed measures of autonomous and controlled motivational regulations and behavioral intention for 20 health-related behaviors at an initial occasion with follow-up behavioral measures taken four weeks later. Path analysis was used to test a process model for each behavior in which motivational regulations predicted behavior mediated by intentions. Some minor idiosyncratic findings aside, between-participants analyses revealed significant effects for autonomous motivational regulations on intentions and behavior across the 20 behaviors. Effects for controlled motivation on intentions and behavior were relatively modest by comparison. Intentions mediated the effect of autonomous motivation on behavior. Within-participants analyses were used to segregate the sample into individuals who based their intentions on autonomous motivation (autonomy-oriented) and controlled motivation (control-oriented). Replicating the between-participants path analyses for the process model in the autonomy- and control-oriented samples did not alter the relative effects of the motivational orientations on intention and behavior. Results provide evidence for consistent effects of autonomous motivation on intentions and behavior across multiple health-related behaviors with little evidence of moderation by individual differences. Findings have implications for the generalizability of proposed effects in self-determination theory and intentions as a mediator of distal motivational factors on health-related behavior. PMID:25750803

Architecture for Control of the K9 Rover

NASA Technical Reports Server (NTRS)

Bresina, John L.; Bualat, maria; Fair, Michael; Wright, Anne; Washington, Richard

2006-01-01

Software featuring a multilevel architecture is used to control the hardware on the K9 Rover, which is a mobile robot used in research on robots for scientific exploration and autonomous operation in general. The software consists of five types of modules: Device Drivers - These modules, at the lowest level of the architecture, directly control motors, cameras, data buses, and other hardware devices. Resource Managers - Each of these modules controls several device drivers. Resource managers can be commanded by either a remote operator or the pilot or conditional-executive modules described below. Behaviors and Data Processors - These modules perform computations for such functions as planning paths, avoiding obstacles, visual tracking, and stereoscopy. These modules can be commanded only by the pilot. Pilot - The pilot receives a possibly complex command from the remote operator or the conditional executive, then decomposes the command into (1) more-specific commands to the resource managers and (2) requests for information from the behaviors and data processors. Conditional Executive - This highest-level module interprets a command plan sent by the remote operator, determines whether resources required for execution of the plan are available, monitors execution, and, if necessary, selects an alternate branch of the plan.

Autonomous planning and scheduling on the TechSat 21 mission

NASA Technical Reports Server (NTRS)

Sherwood, R.; Chien, S.; Castano, R.; Rabideau, G.

2002-01-01

The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting.

Distributed cooperating processes in a mobile robot control system

NASA Technical Reports Server (NTRS)

Skillman, Thomas L., Jr.

1988-01-01

A mobile inspection robot has been proposed for the NASA Space Station. It will be a free flying autonomous vehicle that will leave a berthing unit to accomplish a variety of inspection tasks around the Space Station, and then return to its berth to recharge, refuel, and transfer information. The Flying Eye robot will receive voice communication to change its attitude, move at a constant velocity, and move to a predefined location along a self generated path. This mobile robot control system requires integration of traditional command and control techniques with a number of AI technologies. Speech recognition, natural language understanding, task and path planning, sensory abstraction and pattern recognition are all required for successful implementation. The interface between the traditional numeric control techniques and the symbolic processing to the AI technologies must be developed, and a distributed computing approach will be needed to meet the real time computing requirements. To study the integration of the elements of this project, a novel mobile robot control architecture and simulation based on the blackboard architecture was developed. The control system operation and structure is discussed.

Automated Cartography by an Autonomous Mobile Robot Using Ultrasonic Range Finders

DTIC Science & Technology

1993-09-01

loco.c Temporal Type: Sequential Function (xd, yd, td, 0) dirctix vehicle fou TP S~obstacle IP EP Figure A.24 - The para function Move to a... tp (type POINT), and type (type int). In the case of an fline func- tion, the path element returned is a cubic spiral or an sline depending on the...geu~nst-> tp )) I --no_o...paths; currentsroboLpath.pc = get inst->c; currentLrobot...path.type = getLinst->class; readjinsto; )*end if * if (skipjflag

Multi-objective four-dimensional vehicle motion planning in large dynamic environments.

PubMed

Wu, Paul P-Y; Campbell, Duncan; Merz, Torsten

2011-06-01

This paper presents Multi-Step A∗ (MSA∗), a search algorithm based on A∗ for multi-objective 4-D vehicle motion planning (three spatial and one time dimensions). The research is principally motivated by the need for offline and online motion planning for autonomous unmanned aerial vehicles (UAVs). For UAVs operating in large dynamic uncertain 4-D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and a grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles, and the rules of the air. It is shown that MSA∗ finds a cost optimal solution using variable length, angle, and velocity trajectory segments. These segments are approximated with a grid-based cell sequence that provides an inherent tolerance to uncertainty. The computational efficiency is achieved by using variable successor operators to create a multiresolution memory-efficient lattice sampling structure. The simulation studies on the UAV flight planning problem show that MSA∗ meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of a vector neighborhood-based A∗.

Autonomous mission planning and scheduling: Innovative, integrated, responsive

NASA Technical Reports Server (NTRS)

Sary, Charisse; Liu, Simon; Hull, Larry; Davis, Randy

1994-01-01

Autonomous mission scheduling, a new concept for NASA ground data systems, is a decentralized and distributed approach to scientific spacecraft planning, scheduling, and command management. Systems and services are provided that enable investigators to operate their own instruments. In autonomous mission scheduling, separate nodes exist for each instrument and one or more operations nodes exist for the spacecraft. Each node is responsible for its own operations which include planning, scheduling, and commanding; and for resolving conflicts with other nodes. One or more database servers accessible to all nodes enable each to share mission and science planning, scheduling, and commanding information. The architecture for autonomous mission scheduling is based upon a realistic mix of state-of-the-art and emerging technology and services, e.g., high performance individual workstations, high speed communications, client-server computing, and relational databases. The concept is particularly suited to the smaller, less complex missions of the future.

Onboard autonomous mission re-planning for multi-satellite system

NASA Astrophysics Data System (ADS)

Zheng, Zixuan; Guo, Jian; Gill, Eberhard

2018-04-01

This paper presents an onboard autonomous mission re-planning system for Multi-Satellites System (MSS) to perform onboard re-planing in disruptive situations. The proposed re-planning system can deal with different potential emergency situations. This paper uses Multi-Objective Hybrid Dynamic Mutation Genetic Algorithm (MO-HDM GA) combined with re-planning techniques as the core algorithm. The Cyclically Re-planning Method (CRM) and the Near Real-time Re-planning Method (NRRM) are developed to meet different mission requirements. Simulations results show that both methods can provide feasible re-planning sequences under unforeseen situations. The comparisons illustrate that using the CRM is average 20% faster than the NRRM on computation time. However, by using the NRRM more raw data can be observed and transmitted than using the CRM within the same period. The usability of this onboard re-planning system is not limited to multi-satellite system. Other mission planning and re-planning problems related to autonomous multiple vehicles with similar demands are also applicable.

Advancing Autonomous Operations for Deep Space Vehicles

NASA Technical Reports Server (NTRS)

Haddock, Angie T.; Stetson, Howard K.

2014-01-01

Starting in Jan 2012, the Advanced Exploration Systems (AES) Autonomous Mission Operations (AMO) Project began to investigate the ability to create and execute "single button" crew initiated autonomous activities [1]. NASA Marshall Space Flight Center (MSFC) designed and built a fluid transfer hardware test-bed to use as a sub-system target for the investigations of intelligent procedures that would command and control a fluid transfer test-bed, would perform self-monitoring during fluid transfers, detect anomalies and faults, isolate the fault and recover the procedures function that was being executed, all without operator intervention. In addition to the development of intelligent procedures, the team is also exploring various methods for autonomous activity execution where a planned timeline of activities are executed autonomously and also the initial analysis of crew procedure development. This paper will detail the development of intelligent procedures for the NASA MSFC Autonomous Fluid Transfer System (AFTS) as well as the autonomous plan execution capabilities being investigated. Manned deep space missions, with extreme communication delays with Earth based assets, presents significant challenges for what the on-board procedure content will encompass as well as the planned execution of the procedures.

Amplifying human ability through autonomics and machine learning in IMPACT

NASA Astrophysics Data System (ADS)

Dzieciuch, Iryna; Reeder, John; Gutzwiller, Robert; Gustafson, Eric; Coronado, Braulio; Martinez, Luis; Croft, Bryan; Lange, Douglas S.

2017-05-01

Amplifying human ability for controlling complex environments featuring autonomous units can be aided by learned models of human and system performance. In developing a command and control system that allows a small number of people to control a large number of autonomous teams, we employ an autonomics framework to manage the networks that represent mission plans and the networks that are composed of human controllers and their autonomous assistants. Machine learning allows us to build models of human and system performance useful for monitoring plans and managing human attention and task loads. Machine learning also aids in the development of tactics that human supervisors can successfully monitor through the command and control system.

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.

Remote operation of the Black Knight unmanned ground combat vehicle

NASA Astrophysics Data System (ADS)

Valois, Jean-Sebastien; Herman, Herman; Bares, John; Rice, David P.

2008-04-01

The Black Knight is a 12-ton, C-130 deployable Unmanned Ground Combat Vehicle (UGCV). It was developed to demonstrate how unmanned vehicles can be integrated into a mechanized military force to increase combat capability while protecting Soldiers in a full spectrum of battlefield scenarios. The Black Knight is used in military operational tests that allow Soldiers to develop the necessary techniques, tactics, and procedures to operate a large unmanned vehicle within a mechanized military force. It can be safely controlled by Soldiers from inside a manned fighting vehicle, such as the Bradley Fighting Vehicle. Black Knight control modes include path tracking, guarded teleoperation, and fully autonomous movement. Its state-of-the-art Autonomous Navigation Module (ANM) includes terrain-mapping sensors for route planning, terrain classification, and obstacle avoidance. In guarded teleoperation mode, the ANM data, together with automotive dials and gages, are used to generate video overlays that assist the operator for both day and night driving performance. Remote operation of various sensors also allows Soldiers to perform effective target location and tracking. This document covers Black Knight's system architecture and includes implementation overviews of the various operation modes. We conclude with lessons learned and development goals for the Black Knight UGCV.

Research and development at ORNL/CESAR towards cooperating robotic systems for hazardous environments

NASA Technical Reports Server (NTRS)

Mann, R. C.; Fujimura, K.; Unseren, M. A.

1992-01-01

One of the frontiers in intelligent machine research is the understanding of how constructive cooperation among multiple autonomous agents can be effected. The effort at the Center for Engineering Systems Advanced Research (CESAR) at the Oak Ridge National Laboratory (ORNL) focuses on two problem areas: (1) cooperation by multiple mobile robots in dynamic, incompletely known environments; and (2) cooperating robotic manipulators. Particular emphasis is placed on experimental evaluation of research and developments using the CESAR robot system testbeds, including three mobile robots, and a seven-axis, kinematically redundant mobile manipulator. This paper summarizes initial results of research addressing the decoupling of position and force control for two manipulators holding a common object, and the path planning for multiple robots in a common workspace.

Development of Autonomous Optimal Cooperative Control in Relay Rover Configured Small Unmanned Aerial Systems

DTIC Science & Technology

2013-03-01

Unmanned Aircraft Systems Flight Plan that identified small unmanned aerial systems ( SUAS ) as “a profound technological...advances in small unmanned aerial systems ( SUAS ) cooperative control. The end state objective of the research effort was to flight test an autonomous...requirements were captured in the Unmanned Aircraft Systems Flight Plan . The flight plan

Autonomous Soaring Flight Results

NASA Technical Reports Server (NTRS)

Allen, Michael J.

2006-01-01

A viewgraph presentation on autonomous soaring flight results for Unmanned Aerial Vehicles (UAV)'s is shown. The topics include: 1) Background; 2) Thermal Soaring Flight Results; 3) Autonomous Dolphin Soaring; and 4) Future Plans.

Two arm robot path planning in a static environment using polytopes and string stretching. Thesis

NASA Technical Reports Server (NTRS)

Schima, Francis J., III

1990-01-01

The two arm robot path planning problem has been analyzed and reduced into components to be simplified. This thesis examines one component in which two Puma-560 robot arms are simultaneously holding a single object. The problem is to find a path between two points around obstacles which is relatively fast and minimizes the distance. The thesis involves creating a structure on which to form an advanced path planning algorithm which could ideally find the optimum path. An actual path planning method is implemented which is simple though effective in most common situations. Given the limits of computer technology, a 'good' path is currently found. Objects in the workspace are modeled with polytopes. These are used because they can be used for rapid collision detection and still provide a representation which is adequate for path planning.

The HAL 9000 Space Operating System Real-Time Planning Engine Design and Operations Requirements

NASA Technical Reports Server (NTRS)

Stetson, Howard; Watson, Michael D.; Shaughnessy, Ray

2012-01-01

In support of future deep space manned missions, an autonomous/automated vehicle, providing crew autonomy and an autonomous response planning system, will be required due to the light time delays in communication. Vehicle capabilities as a whole must provide for tactical response to vehicle system failures and space environmental effects induced failures, for risk mitigation of permanent loss of communication with Earth, and for assured crew return capabilities. The complexity of human rated space systems and the limited crew sizes and crew skills mix drive the need for a robust autonomous capability on-board the vehicle. The HAL 9000 Space Operating System[2] designed for such missions and space craft includes the first distributed real-time planning / re-planning system. This paper will detail the software architecture of the multiple planning engine system, and the interface design for plan changes, approval and implementation that is performed autonomously. Operations scenarios will be defined for analysis of the planning engines operations and its requirements for nominal / off nominal activities. An assessment of the distributed realtime re-planning system, in the defined operations environment, will be provided as well as findings as it pertains to the vehicle, crew, and mission control requirements needed for implementation.

Computational path planner for product assembly in complex environments

NASA Astrophysics Data System (ADS)

Shang, Wei; Liu, Jianhua; Ning, Ruxin; Liu, Mi

2013-03-01

Assembly path planning is a crucial problem in assembly related design and manufacturing processes. Sampling based motion planning algorithms are used for computational assembly path planning. However, the performance of such algorithms may degrade much in environments with complex product structure, narrow passages or other challenging scenarios. A computational path planner for automatic assembly path planning in complex 3D environments is presented. The global planning process is divided into three phases based on the environment and specific algorithms are proposed and utilized in each phase to solve the challenging issues. A novel ray test based stochastic collision detection method is proposed to evaluate the intersection between two polyhedral objects. This method avoids fake collisions in conventional methods and degrades the geometric constraint when a part has to be removed with surface contact with other parts. A refined history based rapidly-exploring random tree (RRT) algorithm which bias the growth of the tree based on its planning history is proposed and employed in the planning phase where the path is simple but the space is highly constrained. A novel adaptive RRT algorithm is developed for the path planning problem with challenging scenarios and uncertain environment. With extending values assigned on each tree node and extending schemes applied, the tree can adapts its growth to explore complex environments more efficiently. Experiments on the key algorithms are carried out and comparisons are made between the conventional path planning algorithms and the presented ones. The comparing results show that based on the proposed algorithms, the path planner can compute assembly path in challenging complex environments more efficiently and with higher success. This research provides the references to the study of computational assembly path planning under complex environments.

Optimal sensor fusion for land vehicle navigation

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

Morrow, J.D.

1990-10-01

Position location is a fundamental requirement in autonomous mobile robots which record and subsequently follow x,y paths. The Dept. of Energy, Office of Safeguards and Security, Robotic Security Vehicle (RSV) program involves the development of an autonomous mobile robot for patrolling a structured exterior environment. A straight-forward method for autonomous path-following has been adopted and requires digitizing'' the desired road network by storing x,y coordinates every 2m along the roads. The position location system used to define the locations consists of a radio beacon system which triangulates position off two known transponders, and dead reckoning with compass and odometer. Thismore » paper addresses the problem of combining these two measurements to arrive at a best estimate of position. Two algorithms are proposed: the optimal'' algorithm treats the measurements as random variables and minimizes the estimate variance, while the average error'' algorithm considers the bias in dead reckoning and attempts to guarantee an average error. Data collected on the algorithms indicate that both work well in practice. 2 refs., 7 figs.« less

Vision-based semi-autonomous outdoor robot system to reduce soldier workload

NASA Astrophysics Data System (ADS)

Richardson, Al; Rodgers, Michael H.

2001-09-01

Sensors and computational capability have not reached the point to enable small robots to navigate autonomously in unconstrained outdoor environments at tactically useful speeds. This problem is greatly reduced, however, if a soldier can lead the robot through terrain that he knows it can traverse. An application of this concept is a small pack-mule robot that follows a foot soldier over outdoor terrain. The solder would be responsible to avoid situations beyond the robot's limitations when encountered. Having learned the route, the robot could autonomously retrace the path carrying supplies and munitions. This would greatly reduce the soldier's workload under normal conditions. This paper presents a description of a developmental robot sensor system using low-cost commercial 3D vision and inertial sensors to address this application. The robot moves at fast walking speed and requires only short-range perception to accomplish its task. 3D-feature information is recorded on a composite route map that the robot uses to negotiate its local environment and retrace the path taught by the soldier leader.

Cooperative organic mine avoidance path planning

NASA Astrophysics Data System (ADS)

McCubbin, Christopher B.; Piatko, Christine D.; Peterson, Adam V.; Donnald, Creighton R.; Cohen, David

2005-06-01

The JHU/APL Path Planning team has developed path planning techniques to look for paths that balance the utility and risk associated with different routes through a minefield. Extending on previous years' efforts, we investigated real-world Naval mine avoidance requirements and developed a tactical decision aid (TDA) that satisfies those requirements. APL has developed new mine path planning techniques using graph based and genetic algorithms which quickly produce near-minimum risk paths for complicated fitness functions incorporating risk, path length, ship kinematics, and naval doctrine. The TDA user interface, a Java Swing application that obtains data via Corba interfaces to path planning databases, allows the operator to explore a fusion of historic and in situ mine field data, control the path planner, and display the planning results. To provide a context for the minefield data, the user interface also renders data from the Digital Nautical Chart database, a database created by the National Geospatial-Intelligence Agency containing charts of the world's ports and coastal regions. This TDA has been developed in conjunction with the COMID (Cooperative Organic Mine Defense) system. This paper presents a description of the algorithms, architecture, and application produced.

Ultrascalable Techniques Applied to the Global Intelligence Community Information Awareness Common Operating Picture (IA COP)

DTIC Science & Technology

2005-11-01

more random. Autonomous systems can exchange entropy statistics for packet streams with no confidentiality concerns, potentially enabling timely and... analysis began with simulation results, which were validated by analysis of actual data from an Autonomous System (AS). A scale-free network is one...traffic—for example, time series of flux at given nodes and mean path length Outputs the time series from any node queried Calculates

Relations Between Autonomous Motivation and Leisure-Time Physical Activity Participation: The Mediating Role of Self-Regulation Techniques.

PubMed

Nurmi, Johanna; Hagger, Martin S; Haukkala, Ari; Araújo-Soares, Vera; Hankonen, Nelli

2016-04-01

This study tested the predictive validity of a multitheory process model in which the effect of autonomous motivation from self-determination theory on physical activity participation is mediated by the adoption of self-regulatory techniques based on control theory. Finnish adolescents (N = 411, aged 17-19) completed a prospective survey including validated measures of the predictors and physical activity, at baseline and after one month (N = 177). A subsample used an accelerometer to objectively measure physical activity and further validate the physical activity self-report assessment tool (n = 44). Autonomous motivation statistically significantly predicted action planning, coping planning, and self-monitoring. Coping planning and self-monitoring mediated the effect of autonomous motivation on physical activity, although self-monitoring was the most prominent. Controlled motivation had no effect on self-regulation techniques or physical activity. Developing interventions that support autonomous motivation for physical activity may foster increased engagement in self-regulation techniques and positively affect physical activity behavior.

Global asymptotical ω-periodicity of a fractional-order non-autonomous neural networks.

PubMed

Chen, Boshan; Chen, Jiejie

2015-08-01

We study the global asymptotic ω-periodicity for a fractional-order non-autonomous neural networks. Firstly, based on the Caputo fractional-order derivative it is shown that ω-periodic or autonomous fractional-order neural networks cannot generate exactly ω-periodic signals. Next, by using the contraction mapping principle we discuss the existence and uniqueness of S-asymptotically ω-periodic solution for a class of fractional-order non-autonomous neural networks. Then by using a fractional-order differential and integral inequality technique, we study global Mittag-Leffler stability and global asymptotical periodicity of the fractional-order non-autonomous neural networks, which shows that all paths of the networks, starting from arbitrary points and responding to persistent, nonconstant ω-periodic external inputs, asymptotically converge to the same nonconstant ω-periodic function that may be not a solution. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Autonomous Ozone Instrument for Atmospheric Measurements from Ocean Buoys

NASA Astrophysics Data System (ADS)

Hintsa, E. J.; Rawlins, W. T.; Sholkovitz, E. R.; Hosom, D. S.; Allsup, G. P.; Purcell, M. J.; Scott, D. R.; Mulhall, P.

2002-05-01

Tropospheric ozone is an oxidant, a greenhouse gas, and a pollutant. Because of its adverse health effects, there are numerous monitoring stations on land but none over the oceans. We have built an ozone instrument for deployment anywhere at sea from ocean buoys, to study ozone chemistry over the oceans, intercontinental transport of pollution, diurnal and seasonal cycles of ozone, and to make baseline and long-term time series measurements of ozone in remote locations. The instrument uses direct (Beer's Law) absorption of UV radiation in a dual-path cell, with ambient and ozone-free air alternately switched between the two paths, to measure ozone. Ozone can be measured at a rate of 1 Hz, with a precision of about 1 ppb at sea level. The air inlet and outlet have valves which close automatically under high wind conditions or rain to protect the ozone sensor. The instrument has been packaged for deployment at sea, and tested on a 3-meter discus buoy with other instruments in coastal waters in fall 2001. It can operate autonomously or be controlled via line-of-sight modem or a satellite link. We will present the details of the instrument, and laboratory and buoy test data from its first deployment, including a comparison with a nearby ozone monitoring station on land. We will also present an evaluation of the instrument's performance and describe plans for improvements. In summer 2002, the ozone measurement system will be operated at the Martha's Vineyard Coastal Observatory; in the future we anticipate deploying on the Bermuda Testbed Mooring, followed by use on the open ocean to measure long-range transport of ozone.

Robotic path-finding in inverse treatment planning for stereotactic radiosurgery with continuous dose delivery

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

Vandewouw, Marlee M., E-mail: marleev@mie.utoronto

Purpose: Continuous dose delivery in radiation therapy treatments has been shown to decrease total treatment time while improving the dose conformity and distribution homogeneity over the conventional step-and-shoot approach. The authors develop an inverse treatment planning method for Gamma Knife® Perfexion™ that continuously delivers dose along a path in the target. Methods: The authors’ method is comprised of two steps: find a path within the target, then solve a mixed integer optimization model to find the optimal collimator configurations and durations along the selected path. Robotic path-finding techniques, specifically, simultaneous localization and mapping (SLAM) using an extended Kalman filter, aremore » used to obtain a path that travels sufficiently close to selected isocentre locations. SLAM is novelly extended to explore a 3D, discrete environment, which is the target discretized into voxels. Further novel extensions are incorporated into the steering mechanism to account for target geometry. Results: The SLAM method was tested on seven clinical cases and compared to clinical, Hamiltonian path continuous delivery, and inverse step-and-shoot treatment plans. The SLAM approach improved dose metrics compared to the clinical plans and Hamiltonian path continuous delivery plans. Beam-on times improved over clinical plans, and had mixed performance compared to Hamiltonian path continuous plans. The SLAM method is also shown to be robust to path selection inaccuracies, isocentre selection, and dose distribution. Conclusions: The SLAM method for continuous delivery provides decreased total treatment time and increased treatment quality compared to both clinical and inverse step-and-shoot plans, and outperforms existing path methods in treatment quality. It also accounts for uncertainty in treatment planning by accommodating inaccuracies.« less

PHM Enabled Autonomous Propellant Loading Operations

NASA Technical Reports Server (NTRS)

Walker, Mark; Figueroa, Fernando

2017-01-01

The utility of Prognostics and Health Management (PHM) software capability applied to Autonomous Operations (AO) remains an active research area within aerospace applications. The ability to gain insight into which assets and subsystems are functioning properly, along with the derivation of confident predictions concerning future ability, reliability, and availability, are important enablers for making sound mission planning decisions. When coupled with software that fully supports mission planning and execution, an integrated solution can be developed that leverages state assessment and estimation for the purposes of delivering autonomous operations. The authors have been applying this integrated, model-based approach to the autonomous loading of cryogenic spacecraft propellants at Kennedy Space Center.

Crew Autonomous Scheduling Test (CAST)

NASA Image and Video Library

2017-07-18

iss052e016190 (July 18, 2017) --- Astronaut Peggy Whitson is photographed sitting in front of the Cupola windows during the final Crew Autonomous Scheduling Test (CAST) session. The CAST investigation analyzes whether crews can develop plans in a reasonable period of time with appropriate input, whether proximity of planners to the planned operations increases efficiency, and if crew members are more satisfied when given a role in plan development.

UAV path planning using artificial potential field method updated by optimal control theory

NASA Astrophysics Data System (ADS)

Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long

2016-04-01

The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.

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.”.

Design and Hardware-in-the-Loop Implementation of Optimal Canonical Maneuvers for an Autonomous Planetary Aerial Vehicle

DTIC Science & Technology

2012-12-01

selflessly working your own school and writing schedule around mine , supporting me throughout career paths that have been anything but traditional...observation, and other scientific research and exploration purposes. 4 A ground rover on a planet, moon, or other body such as an asteroid must...applied to autonomous craft that could eventually operate on the surface of planets, moons, and asteroids , as well as in Earth orbit or deep space

A Flight Deck Decision Support Tool for Autonomous Airborne Operations

NASA Technical Reports Server (NTRS)

Ballin, Mark G.; Sharma, Vivek; Vivona, Robert A.; Johnson, Edward J.; Ramiscal, Ermin

2002-01-01

NASA is developing a flight deck decision support tool to support research into autonomous operations in a future distributed air/ground traffic management environment. This interactive real-time decision aid, referred to as the Autonomous Operations Planner (AOP), will enable the flight crew to plan autonomously in the presence of dense traffic and complex flight management constraints. In assisting the flight crew, the AOP accounts for traffic flow management and airspace constraints, schedule requirements, weather hazards, aircraft operational limits, and crew or airline flight-planning goals. This paper describes the AOP and presents an overview of functional and implementation design considerations required for its development. Required AOP functionality is described, its application in autonomous operations research is discussed, and a prototype software architecture for the AOP is presented.

SSTAC/ARTS review of the draft Integrated Technology Plan (ITP). Volume 6: Controls and guidance

NASA Technical Reports Server (NTRS)

1991-01-01

Viewgraphs of briefings from the Space Systems and Technology Advisory Committee (SSTAC)/ARTS review of the draft Integrated Technology Plan (ITP) on controls and guidance are included. Topics covered include: strategic avionics technology planning and bridging programs; avionics technology plan; vehicle health management; spacecraft guidance research; autonomous rendezvous and docking; autonomous landing; computational control; fiberoptic rotation sensors; precision instrument and telescope pointing; microsensors and microinstruments; micro guidance and control initiative; and earth-orbiting platforms controls-structures interaction.

Integrating Terrain Maps Into a Reactive Navigation Strategy

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Werger, Barry; Seraji, Homayoun

2006-01-01

An improved method of processing information for autonomous navigation of a robotic vehicle across rough terrain involves the integration of terrain maps into a reactive navigation strategy. Somewhat more precisely, the method involves the incorporation, into navigation logic, of data equivalent to regional traversability maps. The terrain characteristic is mapped using a fuzzy-logic representation of the difficulty of traversing the terrain. The method is robust in that it integrates a global path-planning strategy with sensor-based regional and local navigation strategies to ensure a high probability of success in reaching a destination and avoiding obstacles along the way. The sensor-based strategies use cameras aboard the vehicle to observe the regional terrain, defined as the area of the terrain that covers the immediate vicinity near the vehicle to a specified distance a few meters away.

Adaptive Inner-Loop Rover Control

NASA Technical Reports Server (NTRS)

Kulkarni, Nilesh; Ippolito, Corey; Krishnakumar, Kalmanje; Al-Ali, Khalid M.

2006-01-01

Adaptive control technology is developed for the inner-loop speed and steering control of the MAX Rover. MAX, a CMU developed rover, is a compact low-cost 4-wheel drive, 4-wheel steer (double Ackerman), high-clearance agile durable chassis, outfitted with sensors and electronics that make it ideally suited for supporting research relevant to intelligent teleoperation and as a low-cost autonomous robotic test bed and appliance. The design consists of a feedback linearization based controller with a proportional - integral (PI) feedback that is augmented by an online adaptive neural network. The adaptation law has guaranteed stability properties for safe operation. The control design is retrofit in nature so that it fits inside the outer-loop path planning algorithms. Successful hardware implementation of the controller is illustrated for several scenarios consisting of actuator failures and modeling errors in the nominal design.

Using a Genetic Algorithm to Learn Behaviors for Autonomous Vehicles,

DTIC Science & Technology

1992-08-12

Truly autonomous vehicles will require both projective planning and reactive components in order to perform robustly. Projective components are...long time period. This work addresses the problem of creating reactive components for autonomous vehicles . Creating reactive behaviors (stimulus

Orbital Express mission operations planning and resource management using ASPEN

NASA Astrophysics Data System (ADS)

Chouinard, Caroline; Knight, Russell; Jones, Grailing; Tran, Daniel

2008-04-01

As satellite equipment and mission operations become more costly, the drive to keep working equipment running with less labor-power rises. Demonstrating the feasibility of autonomous satellite servicing was the main goal behind the Orbital Express (OE) mission. Like a tow-truck delivering gas to a car on the road, the "servicing" satellite of OE had to find the "client" from several kilometers away, connect directly to the client, and transfer fluid (or a battery) autonomously, while on earth-orbit. The mission met 100% of its success criteria, and proved that autonomous satellite servicing is now a reality for space operations. Planning the satellite mission operations for OE required the ability to create a plan which could be executed autonomously over variable conditions. As the constraints for execution could change weekly, daily, and even hourly, the tools used create the mission execution plans needed to be flexible and adaptable to many different kinds of changes. At the same time, the hard constraints of the plans needed to be maintained and satisfied. The Automated Scheduling and Planning Environment (ASPEN) tool, developed at the Jet Propulsion Laboratory, was used to create the schedule of events in each daily plan for the two satellites of the OE mission. This paper presents an introduction to the ASPEN tool, an overview of the constraints of the OE domain, the variable conditions that were presented within the mission, and the solution to operations that ASPEN provided. ASPEN has been used in several other domains, including research rovers, Deep Space Network scheduling research, and in flight operations for the NASA's Earth Observing One mission's EO1 satellite. Related work is discussed, as are the future of ASPEN and the future of autonomous satellite servicing.

Cooperative path following control of multiple nonholonomic mobile robots.

PubMed

Cao, Ke-Cai; Jiang, Bin; Yue, Dong

2017-11-01

Cooperative path following control problem of multiple nonholonomic mobile robots has been considered in this paper. Based on the framework of decomposition, the cooperative path following problem has been transformed into path following problem and cooperative control problem; Then cascaded theory of non-autonomous system has been employed in the design of controllers without resorting to feedback linearization. One time-varying coordinate transformation based on dilation has been introduced to solve the uncontrollable problem of nonholonomic robots when the whole group's reference converges to stationary point. Cooperative path following controllers for nonholonomic robots have been proposed under persistent reference or reference target that converges to stationary point respectively. Simulation results using Matlab have illustrated the effectiveness of the obtained theoretical results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017 Workshop by the North Atlantic Treaty Organization (NATO) Research Group IST-152 RTG

DTIC Science & Technology

2018-04-18

Significant research is currently conducted on dynamic learning and threat detection. However, this work is held back by gaps in validation methods ...and network path rotation (e.g., Stream Splitting MTD). Agents can also employ various cyber-deception methods , including direct observation hiding...ARL-SR-0395 ● APR 2018 US Army Research Laboratory Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017

Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017 Workshop by the North Atlantic Treaty Organization (NATO) Research Group IST-152-RTG

DTIC Science & Technology

2018-04-01

Significant research is currently conducted on dynamic learning and threat detection. However, this work is held back by gaps in validation methods ...and network path rotation (e.g., Stream Splitting MTD). Agents can also employ various cyber-deception methods , including direct observation hiding...ARL-SR-0395 ● APR 2018 US Army Research Laboratory Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017

Optimal strategies for the control of autonomous vehicles in data assimilation

NASA Astrophysics Data System (ADS)

McDougall, D.; Moore, R. O.

2017-08-01

We propose a method to compute optimal control paths for autonomous vehicles deployed for the purpose of inferring a velocity field. In addition to being advected by the flow, the vehicles are able to effect a fixed relative speed with arbitrary control over direction. It is this direction that is used as the basis for the locally optimal control algorithm presented here, with objective formed from the variance trace of the expected posterior distribution. We present results for linear flows near hyperbolic fixed points.

An Approach to Model Based Testing of Multiagent Systems

PubMed Central

Nadeem, Aamer

2015-01-01

Autonomous agents perform on behalf of the user to achieve defined goals or objectives. They are situated in dynamic environment and are able to operate autonomously to achieve their goals. In a multiagent system, agents cooperate with each other to achieve a common goal. Testing of multiagent systems is a challenging task due to the autonomous and proactive behavior of agents. However, testing is required to build confidence into the working of a multiagent system. Prometheus methodology is a commonly used approach to design multiagents systems. Systematic and thorough testing of each interaction is necessary. This paper proposes a novel approach to testing of multiagent systems based on Prometheus design artifacts. In the proposed approach, different interactions between the agent and actors are considered to test the multiagent system. These interactions include percepts and actions along with messages between the agents which can be modeled in a protocol diagram. The protocol diagram is converted into a protocol graph, on which different coverage criteria are applied to generate test paths that cover interactions between the agents. A prototype tool has been developed to generate test paths from protocol graph according to the specified coverage criterion. PMID:25874263

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.

Planning 3-D collision-free paths using spheres

NASA Technical Reports Server (NTRS)

Bonner, Susan; Kelley, Robert B.

1989-01-01

A scheme for the representation of objects, the Successive Spherical Approximation (SSA), facilitates the rapid planning of collision-free paths in a 3-D, dynamic environment. The hierarchical nature of the SSA allows collision-free paths to be determined efficiently while still providing for the exact representation of dynamic objects. The concept of a freespace cell is introduced to allow human 3-D conceptual knowledge to be used in facilitating satisfying choices for paths. Collisions can be detected at a rate better than 1 second per environment object per path. This speed enables the path planning process to apply a hierarchy of rules to create a heuristically satisfying collision-free path.

Integrated System for Autonomous Science

NASA Technical Reports Server (NTRS)

Chien, Steve; Sherwood, Robert; Tran, Daniel; Cichy, Benjamin; Davies, Ashley; Castano, Rebecca; Rabideau, Gregg; Frye, Stuart; Trout, Bruce; Shulman, Seth;

Neural Network Based Sensory Fusion for Landmark Detection

NASA Technical Reports Server (NTRS)

Kumbla, Kishan -K.; Akbarzadeh, Mohammad R.

1997-01-01

NASA is planning to send numerous unmanned planetary missions to explore the space. This requires autonomous robotic vehicles which can navigate in an unstructured, unknown, and uncertain environment. Landmark based navigation is a new area of research which differs from the traditional goal-oriented navigation, where a mobile robot starts from an initial point and reaches a destination in accordance with a pre-planned path. The landmark based navigation has the advantage of allowing the robot to find its way without communication with the mission control station and without exact knowledge of its coordinates. Current algorithms based on landmark navigation however pose several constraints. First, they require large memories to store the images. Second, the task of comparing the images using traditional methods is computationally intensive and consequently real-time implementation is difficult. The method proposed here consists of three stages, First stage utilizes a heuristic-based algorithm to identify significant objects. The second stage utilizes a neural network (NN) to efficiently classify images of the identified objects. The third stage combines distance information with the classification results of neural networks for efficient and intelligent navigation.

Methodology for Augmenting Existing Paths with Additional Parallel Transects

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

Wilson, John E.

2013-09-30

Visual Sample Plan (VSP) is sample planning software that is used, among other purposes, to plan transect sampling paths to detect areas that were potentially used for munition training. This module was developed for application on a large site where existing roads and trails were to be used as primary sampling paths. Gap areas between these primary paths needed to found and covered with parallel transect paths. These gap areas represent areas on the site that are more than a specified distance from a primary path. These added parallel paths needed to optionally be connected together into a single path—themore » shortest path possible. The paths also needed to optionally be attached to existing primary paths, again with the shortest possible path. Finally, the process must be repeatable and predictable so that the same inputs (primary paths, specified distance, and path options) will result in the same set of new paths every time. This methodology was developed to meet those specifications.« less

Autonomous mission management for UAVs using soar intelligent agents

NASA Astrophysics Data System (ADS)

Gunetti, Paolo; Thompson, Haydn; Dodd, Tony

2013-05-01

State-of-the-art unmanned aerial vehicles (UAVs) are typically able to autonomously execute a pre-planned mission. However, UAVs usually fly in a very dynamic environment which requires dynamic changes to the flight plan; this mission management activity is usually tasked to human supervision. Within this article, a software system that autonomously accomplishes the mission management task for a UAV will be proposed. The system is based on a set of theoretical concepts which allow the description of a flight plan and implemented using a combination of Soar intelligent agents and traditional control techniques. The system is capable of automatically generating and then executing an entire flight plan after being assigned a set of objectives. This article thoroughly describes all system components and then presents the results of tests that were executed using a realistic simulation environment.

A two-stage path planning approach for multiple car-like robots based on PH curves and a modified harmony search algorithm

NASA Astrophysics Data System (ADS)

Zeng, Wenhui; Yi, Jin; Rao, Xiao; Zheng, Yun

2017-11-01

In this article, collision-avoidance path planning for multiple car-like robots with variable motion is formulated as a two-stage objective optimization problem minimizing both the total length of all paths and the task's completion time. Accordingly, a new approach based on Pythagorean Hodograph (PH) curves and Modified Harmony Search algorithm is proposed to solve the two-stage path-planning problem subject to kinematic constraints such as velocity, acceleration, and minimum turning radius. First, a method of path planning based on PH curves for a single robot is proposed. Second, a mathematical model of the two-stage path-planning problem for multiple car-like robots with variable motion subject to kinematic constraints is constructed that the first-stage minimizes the total length of all paths and the second-stage minimizes the task's completion time. Finally, a modified harmony search algorithm is applied to solve the two-stage optimization problem. A set of experiments demonstrate the effectiveness of the proposed approach.

Utilization of the International Space Station for Crew Autonomous Scheduling Test (CAST)

NASA Technical Reports Server (NTRS)

Healy, Matthew; Marquez, Jesica; Hillenius, Steven; Korth, David; Bakalyar, Laure Rush; Woodbury, Neil; Larsen, Crystal M.; Bates, Shelby; Kockler, Mikayla; Rhodes, Brooke;

Design of an algorithm for autonomous docking with a freely tumbling target

NASA Astrophysics Data System (ADS)

Nolet, Simon; Kong, Edmund; Miller, David W.

2005-05-01

For complex unmanned docking missions, limited communication bandwidth and delays do not allow ground operators to have immediate access to all real-time state information and hence prevent them from playing an active role in the control loop. Advanced control algorithms are needed to make mission critical decisions to ensure safety of both spacecraft during close proximity maneuvers. This is especially true when unexpected contingencies occur. These algorithms will enable multiple space missions, including servicing of damaged spacecraft and missions to Mars. A key characteristic of spacecraft servicing missions is that the target spacecraft is likely to be freely tumbling due to various mechanical failures or fuel depletion. Very few technical references in the literature can be found on autonomous docking with a freely tumbling target and very few such maneuvers have been attempted. The MIT Space Systems Laboratory (SSL) is currently performing research on the subject. The objective of this research is to develop a control architecture that will enable safe and fuel-efficient docking of a thruster based spacecraft with a freely tumbling target in presence of obstacles and contingencies. The approach is to identify, select and implement state estimation, fault detection, isolation and recovery, optimal path planning and thruster management algorithms that, once properly integrated, can accomplish such a maneuver autonomously. Simulations and demonstrations on the SPHERES testbed developed by the MIT SSL will be executed to assess the performance of different combinations of algorithms. To date, experiments have been carried out at the MIT SSL 2-D Laboratory and at the NASA Marshall Space Flight Center (MSFC) flat floor.

Simulating Mission Command for Planning and Analysis

DTIC Science & Technology

2015-06-01

mission plan. 14. SUBJECT TERMS Mission Planning, CPM , PERT, Simulation, DES, Simkit, Triangle Distribution, Critical Path 15. NUMBER OF...Battalion Task Force CO Company CPM Critical Path Method DES Discrete Event Simulation FA BAT Field Artillery Battalion FEL Future Event List FIST...management tools that can be utilized to find the critical path in military projects. These are the Critical Path Method ( CPM ) and the Program Evaluation and

Coordinated path-following and direct yaw-moment control of autonomous electric vehicles with sideslip angle estimation

NASA Astrophysics Data System (ADS)

Guo, Jinghua; Luo, Yugong; Li, Keqiang; Dai, Yifan

2018-05-01

This paper presents a novel coordinated path following system (PFS) and direct yaw-moment control (DYC) of autonomous electric vehicles via hierarchical control technique. In the high-level control law design, a new fuzzy factor is introduced based on the magnitude of longitudinal velocity of vehicle, a linear time varying (LTV)-based model predictive controller (MPC) is proposed to acquire the wheel steering angle and external yaw moment. Then, a pseudo inverse (PI) low-level control allocation law is designed to realize the tracking of desired external moment torque and management of the redundant tire actuators. Furthermore, the vehicle sideslip angle is estimated by the data fusion of low-cost GPS and INS, which can be obtained by the integral of modified INS signals with GPS signals as initial value. Finally, the effectiveness of the proposed control system is validated by the simulation and experimental tests.

Grid Visualization Tool

NASA Technical Reports Server (NTRS)

Chouinard, Caroline; Fisher, Forest; Estlin, Tara; Gaines, Daniel; Schaffer, Steven

2005-01-01

The Grid Visualization Tool (GVT) is a computer program for displaying the path of a mobile robotic explorer (rover) on a terrain map. The GVT reads a map-data file in either portable graymap (PGM) or portable pixmap (PPM) format, representing a gray-scale or color map image, respectively. The GVT also accepts input from path-planning and activity-planning software. From these inputs, the GVT generates a map overlaid with one or more rover path(s), waypoints, locations of targets to be explored, and/or target-status information (indicating success or failure in exploring each target). The display can also indicate different types of paths or path segments, such as the path actually traveled versus a planned path or the path traveled to the present position versus planned future movement along a path. The program provides for updating of the display in real time to facilitate visualization of progress. The size of the display and the map scale can be changed as desired by the user. The GVT was written in the C++ language using the Open Graphics Library (OpenGL) software. It has been compiled for both Sun Solaris and Linux operating systems.

Experiences with operations and autonomy of the Mars Pathfinder Microrover.

NASA Astrophysics Data System (ADS)

Mishkin, A. H.; Morrison, J. C.; Nguyen, T. T.; Stone, H. W.; Cooper, B. K.; Wilcox, B. H.

The Microrover Flight Experiment (MFEX) is a NASA OACT (Office of Advanced Concepts and Technology) flight experiment which, integrated with the Mars Pathfinder (MPF) lander and spacecraft system, landed on Mars on July 4, 1997. In the succeeding 30 sols (1 sol = 1 Martian day), the Sojourner microrover accomplished all of its primary and extended mission objectives. After completion of the originally planned extended mission, MFEX continued to conduct a series of technology experiments, deploy its alpha proton X-ray spectrometer (APXS) on rocks and soil, and image both terrain features and the lander. This mission was conducted under the constraints of a once-per-sol opportunity for command and telemetry transmissions between the lander and Earth operators. As such, the MFEX rover was required to carry out its mission, including terrain navigation and contingency response, under supervised autonomous control. For example, goal locations were specified daily by human operators; the rover then safely traversed to these locations. During traverses, the rover autonomously detected and avoided rock, slope, and drop-off hazards, changing its path as needed before turning back towards its goal. This capability to operate in an unmodeled environment, choosing actions in response to sensor input to accomplish requested objectives, is unique among robotic space missions to date.

Predicting Athletes' Pre-Exercise Fluid Intake: A Theoretical Integration Approach.

PubMed

Li, Chunxiao; Sun, Feng-Hua; Zhang, Liancheng; Chan, Derwin King Chung

2018-05-21

Pre-exercise fluid intake is an important healthy behavior for maintaining athletes’ sports performances and health. However, athletes’ behavioral adherence to fluid intake and its underlying psychological mechanisms have not been investigated. This prospective study aimed to use a health psychology model that integrates the self-determination theory and the theory of planned behavior for understanding pre-exercise fluid intake among athletes. Participants ( n = 179) were athletes from college sport teams who completed surveys at two time points. Baseline (Time 1) assessment comprised psychological variables of the integrated model (i.e., autonomous and controlled motivation, attitude, subjective norm, perceived behavioral control, and intention) and fluid intake (i.e., behavior) was measured prospectively at one month (Time 2). Path analysis showed that the positive association between autonomous motivation and intention was mediated by subjective norm and perceived behavioral control. Controlled motivation positively predicted the subjective norm. Intentions positively predicted pre-exercise fluid intake behavior. Overall, the pattern of results was generally consistent with the integrated model, and it was suggested that athletes’ pre-exercise fluid intake behaviors were associated with the motivational and social cognitive factors of the model. The research findings could be informative for coaches and sport scientists to promote athletes’ pre-exercise fluid intake behaviors.

Dynamics control of autonomous vehicle at driving limits and experiment on an autonomous formula racing car

NASA Astrophysics Data System (ADS)

Ni, Jun; Hu, Jibin

2017-06-01

In this paper, a novel dynamics controller for autonomous vehicle to simultaneously control it to the driving limits and follow the desired path is proposed. The dynamics controller consists of longitudinal and lateral controllers. In longitudinal controller, the G-G diagram is utilized to describe the driving and handling limits of the vehicle. The accurate G-G diagram is obtained based on phase plane approach and a nonlinear vehicle dynamic model with accurate tyre model. In lateral controller, the tyre cornering stiffness is estimated to improve the robustness of the controller. The stability analysis of the closed-looped error dynamics shows that the controller remains stable against parameters uncertainties in extreme condition such as tyre saturation. Finally, an electric autonomous Formula race car developed by the authors is used to validate the proposed controller. The autonomous driving experiment on an oval race track shows the efficiency and robustness of the proposed controller.

Interactive multi-objective path planning through a palette-based user interface

NASA Astrophysics Data System (ADS)

Shaikh, Meher T.; Goodrich, Michael A.; Yi, Daqing; Hoehne, Joseph

2016-05-01

n a problem where a human uses supervisory control to manage robot path-planning, there are times when human does the path planning, and if satisfied commits those paths to be executed by the robot, and the robot executes that plan. In planning a path, the robot often uses an optimization algorithm that maximizes or minimizes an objective. When a human is assigned the task of path planning for robot, the human may care about multiple objectives. This work proposes a graphical user interface (GUI) designed for interactive robot path-planning when an operator may prefer one objective over others or care about how multiple objectives are traded off. The GUI represents multiple objectives using the metaphor of an artist's palette. A distinct color is used to represent each objective, and tradeoffs among objectives are balanced in a manner that an artist mixes colors to get the desired shade of color. Thus, human intent is analogous to the artist's shade of color. We call the GUI an "Adverb Palette" where the word "Adverb" represents a specific type of objective for the path, such as the adverbs "quickly" and "safely" in the commands: "travel the path quickly", "make the journey safely". The novel interactive interface provides the user an opportunity to evaluate various alternatives (that tradeoff between different objectives) by allowing her to visualize the instantaneous outcomes that result from her actions on the interface. In addition to assisting analysis of various solutions given by an optimization algorithm, the palette has additional feature of allowing the user to define and visualize her own paths, by means of waypoints (guiding locations) thereby spanning variety for planning. The goal of the Adverb Palette is thus to provide a way for the user and robot to find an acceptable solution even though they use very different representations of the problem. Subjective evaluations suggest that even non-experts in robotics can carry out the planning tasks with a great deal of flexibility using the adverb palette.

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.

Automated Planning and Scheduling for Planetary Rover Distributed Operations

NASA Technical Reports Server (NTRS)

Backes, Paul G.; Rabideau, Gregg; Tso, Kam S.; Chien, Steve

1999-01-01

Automated planning and Scheduling, including automated path planning, has been integrated with an Internet-based distributed operations system for planetary rover operations. The resulting prototype system enables faster generation of valid rover command sequences by a distributed planetary rover operations team. The Web Interface for Telescience (WITS) provides Internet-based distributed collaboration, the Automated Scheduling and Planning Environment (ASPEN) provides automated planning and scheduling, and an automated path planner provided path planning. The system was demonstrated on the Rocky 7 research rover at JPL.

Autonomous Instrument Placement for Mars Exploration Rovers

NASA Technical Reports Server (NTRS)

Leger, P. Chris; Maimone, Mark

2009-01-01

Autonomous Instrument Placement (AutoPlace) is onboard software that enables a Mars Exploration Rover to act autonomously in using its manipulator to place scientific instruments on or near designated rock and soil targets. Prior to the development of AutoPlace, it was necessary for human operators on Earth to plan every motion of the manipulator arm in a time-consuming process that included downlinking of images from the rover, analysis of images and creation of commands, and uplinking of commands to the rover. AutoPlace incorporates image analysis and planning algorithms into the onboard rover software, eliminating the need for the downlink/uplink command cycle. Many of these algorithms are derived from the existing groundbased image analysis and planning algorithms, with modifications and augmentations for onboard use.

Cooperative path planning for multi-USV based on improved artificial bee colony algorithm

NASA Astrophysics Data System (ADS)

Cao, Lu; Chen, Qiwei

2018-03-01

Due to the complex constraints, more uncertain factors and critical real-time demand of path planning for multiple unmanned surface vehicle (multi-USV), an improved artificial bee colony (I-ABC) algorithm were proposed to solve the model of cooperative path planning for multi-USV. First the Voronoi diagram of battle field space is conceived to generate the optimal area of USVs paths. Then the chaotic searching algorithm is used to initialize the collection of paths, which is regard as foods of the ABC algorithm. With the limited data, the initial collection can search the optimal area of paths perfectly. Finally simulations of the multi-USV path planning under various threats have been carried out. Simulation results verify that the I-ABC algorithm can improve the diversity of nectar source and the convergence rate of algorithm. It can increase the adaptability of dynamic battlefield and unexpected threats for USV.

Autonomous mobile robot for radiologic surveys

DOEpatents

Dudar, A.M.; Wagner, D.G.; Teese, G.D.

1994-06-28

An apparatus is described for conducting radiologic surveys. The apparatus comprises in the main a robot capable of following a preprogrammed path through an area, a radiation monitor adapted to receive input from a radiation detector assembly, ultrasonic transducers for navigation and collision avoidance, and an on-board computer system including an integrator for interfacing the radiation monitor and the robot. Front and rear bumpers are attached to the robot by bumper mounts. The robot may be equipped with memory boards for the collection and storage of radiation survey information. The on-board computer system is connected to a remote host computer via a UHF radio link. The apparatus is powered by a rechargeable 24-volt DC battery, and is stored at a docking station when not in use and/or for recharging. A remote host computer contains a stored database defining paths between points in the area where the robot is to operate, including but not limited to the locations of walls, doors, stationary furniture and equipment, and sonic markers if used. When a program consisting of a series of paths is downloaded to the on-board computer system, the robot conducts a floor survey autonomously at any preselected rate. When the radiation monitor detects contamination, the robot resurveys the area at reduced speed and resumes its preprogrammed path if the contamination is not confirmed. If the contamination is confirmed, the robot stops and sounds an alarm. 5 figures.

Autonomous mobile robot for radiologic surveys

DOEpatents

Dudar, Aed M.; Wagner, David G.; Teese, Gregory D.

1994-01-01

An apparatus for conducting radiologic surveys. The apparatus comprises in the main a robot capable of following a preprogrammed path through an area, a radiation monitor adapted to receive input from a radiation detector assembly, ultrasonic transducers for navigation and collision avoidance, and an on-board computer system including an integrator for interfacing the radiation monitor and the robot. Front and rear bumpers are attached to the robot by bumper mounts. The robot may be equipped with memory boards for the collection and storage of radiation survey information. The on-board computer system is connected to a remote host computer via a UHF radio link. The apparatus is powered by a rechargeable 24-volt DC battery, and is stored at a docking station when not in use and/or for recharging. A remote host computer contains a stored database defining paths between points in the area where the robot is to operate, including but not limited to the locations of walls, doors, stationary furniture and equipment, and sonic markers if used. When a program consisting of a series of paths is downloaded to the on-board computer system, the robot conducts a floor survey autonomously at any preselected rate. When the radiation monitor detects contamination, the robot resurveys the area at reduced speed and resumes its preprogrammed path if the contamination is not confirmed. If the contamination is confirmed, the robot stops and sounds an alarm.

Planning paths through a spatial hierarchy - Eliminating stair-stepping effects

NASA Technical Reports Server (NTRS)

Slack, Marc G.

1989-01-01

Stair-stepping effects are a result of the loss of spatial continuity resulting from the decomposition of space into a grid. This paper presents a path planning algorithm which eliminates stair-stepping effects induced by the grid-based spatial representation. The algorithm exploits a hierarchical spatial model to efficiently plan paths for a mobile robot operating in dynamic domains. The spatial model and path planning algorithm map to a parallel machine, allowing the system to operate incrementally, thereby accounting for unexpected events in the operating space.

Progress of Crew Autonomous Scheduling Test (CAST) On the ISS

NASA Technical Reports Server (NTRS)

Healy, Matthew; Marquez, Jessica; Hillenius, Steven; Korth, David; Bakalyar, Lauren Rush; Woodbury, Neil; Larsen, Crystal M.; Bates, Shelby; Kockler, Mikayla; Rhodes, Brooke;

SOLON: An autonomous vehicle mission planner

NASA Technical Reports Server (NTRS)

Dudziak, M. J.

1987-01-01

The State-Operator Logic Machine (SOLON) Planner provides an architecture for effective real-time planning and replanning for an autonomous vehicle. The highlights of the system, which distinguish it from other AI-based planners that have been designed previously, are its hybrid application of state-driven control architecture and the use of both schematic representations and logic programming for the management of its knowledge base. SOLON is designed to provide multiple levels of planning for a single autonomous vehicle which is supplied with a skeletal, partially-specified mission plan at the outset of the vehicle's operations. This mission plan consists of a set of objectives, each of which will be decomposable by the planner into tasks. These tasks are themselves comparatively complex sets of actions which are executable by a conventional real-time control system which does not perform planning but which is capable of making adjustments or modifications to the provided tasks according to constraints and tolerances provided by the Planner. The current implementation of the SOLON is in the form of a real-time simulation of the Planner module of an Intelligent Vehicle Controller (IVC) on-board an autonomous underwater vehicle (AUV). The simulation is embedded within a larger simulator environment known as ICDS (Intelligent Controller Development System) operating on a Symbolics 3645/75 computer.

Orbital Express Mission Operations Planning and Resource Management using ASPEN

NASA Technical Reports Server (NTRS)

Chouinard, Caroline; Knight, Russell; Jones, Grailing; Tran, Daniel

2008-01-01

As satellite equipment and mission operations become more costly, the drive to keep working equipment running with less man-power rises.Demonstrating the feasibility of autonomous satellite servicing was the main goal behind the Orbital Express (OE) mission. Planning the satellite mission operations for OE required the ability to create a plan which could be executed autonomously over variable conditions. The Automated-Scheduling and Planning Environment (ASPEN)tool, developed at the Jet Propulsion Laboratory, was used to create the schedule of events in each daily plan for the two satellites of the OE mission. This paper presents an introduction to the ASPEN tool, the constraints of the OE domain, the variable conditions that were presented within the mission, and the solution to operations that ASPEN provided. ASPEN has been used in several other domains, including research rovers, Deep Space Network scheduling research, and in flight operations for the ASE project's EO1 satellite. Related work is discussed, as are the future of ASPEN and the future of autonomous satellite servicing.

NASA's Autonomous Formation Flying Technology Demonstration, Earth Observing-1(EO-1)

NASA Technical Reports Server (NTRS)

Folta, David; Bristow, John; Hawkins, Albin; Dell, Greg

2002-01-01

NASA's first autonomous formation flying mission, the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft, recently completed its principal goal of demonstrating advanced formation control technology. This paper provides an overview of the evolution of an onboard system that was developed originally as a ground mission planning and operations tool. We discuss the Goddard Space Flight Center s formation flying algorithm, the onboard flight design and its implementation, the interface and functionality of the onboard system, and the implementation of a Kalman filter based GPS data smoother. A number of safeguards that allow the incremental phasing in of autonomy and alleviate the potential for mission-impacting anomalies from the on- board autonomous system are discussed. A comparison of the maneuvers planned onboard using the EO-1 autonomous control system to those from the operational ground-based maneuver planning system is presented to quantify our success. The maneuvers discussed encompass reactionary and routine formation maintenance. Definitive orbital data is presented that verifies all formation flying requirements.

Model-based Executive Control through Reactive Planning for Autonomous Rovers

NASA Technical Reports Server (NTRS)

Finzi, Alberto; Ingrand, Felix; Muscettola, Nicola

2004-01-01

This paper reports on the design and implementation of a real-time executive for a mobile rover that uses a model-based, declarative approach. The control system is based on the Intelligent Distributed Execution Architecture (IDEA), an approach to planning and execution that provides a unified representational and computational framework for an autonomous agent. The basic hypothesis of IDEA is that a large control system can be structured as a collection of interacting agents, each with the same fundamental structure. We show that planning and real-time response are compatible if the executive minimizes the size of the planning problem. We detail the implementation of this approach on an exploration rover (Gromit an RWI ATRV Junior at NASA Ames) presenting different IDEA controllers of the same domain and comparing them with more classical approaches. We demonstrate that the approach is scalable to complex coordination of functional modules needed for autonomous navigation and exploration.

IDEA: Planning at the Core of Autonomous Reactive Agents

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Dorais, Gregory A.; Fry, Chuck; Levinson, Richard; Plaunt, Christian; Clancy, Daniel (Technical Monitor)

2002-01-01

Several successful autonomous systems are separated into technologically diverse functional layers operating at different levels of abstraction. This diversity makes them difficult to implement and validate. In this paper, we present IDEA (Intelligent Distributed Execution Architecture), a unified planning and execution framework. In IDEA a layered system can be implemented as separate agents, one per layer, each representing its interactions with the world in a model. At all levels, the model representation primitives and their semantics is the same. Moreover, each agent relies on a single model, plan database, plan runner and on a variety of planners, both reactive and deliberative. The framework allows the specification of agents that operate, within a guaranteed reaction time and supports flexible specification of reactive vs. deliberative agent behavior. Within the IDEA framework we are working to fully duplicate the functionalities of the DS1 Remote Agent and extend it to domains of higher complexity than autonomous spacecraft control.

Autonomous surgical robotics using 3-D ultrasound guidance: feasibility study.

PubMed

Whitman, John; Fronheiser, Matthew P; Ivancevich, Nikolas M; Smith, Stephen W

2007-10-01

The goal of this study was to test the feasibility of using a real-time 3D (RT3D) ultrasound scanner with a transthoracic matrix array transducer probe to guide an autonomous surgical robot. Employing a fiducial alignment mark on the transducer to orient the robot's frame of reference and using simple thresholding algorithms to segment the 3D images, we tested the accuracy of using the scanner to automatically direct a robot arm that touched two needle tips together within a water tank. RMS measurement error was 3.8% or 1.58 mm for an average path length of 41 mm. Using these same techniques, the autonomous robot also performed simulated needle biopsies of a cyst-like lesion in a tissue phantom. This feasibility study shows the potential for 3D ultrasound guidance of an autonomous surgical robot for simple interventional tasks, including lesion biopsy and foreign body removal.

Defence R&D Canada's autonomous intelligent systems program

NASA Astrophysics Data System (ADS)

Digney, Bruce L.; Hubbard, Paul; Gagnon, Eric; Lauzon, Marc; Rabbath, Camille; Beckman, Blake; Collier, Jack A.; Penzes, Steven G.; Broten, Gregory S.; Monckton, Simon P.; Trentini, Michael; Kim, Bumsoo; Farell, Philip; Hopkin, Dave

2004-09-01

The Defence Research and Development Canada's (DRDC has been given strategic direction to pursue research to increase the independence and effectiveness of military vehicles and systems. This has led to the creation of the Autonomous Intelligent Systems (AIS) prgram and is notionally divide into air, land and marine vehicle systems as well as command, control and decision support systems. This paper presents an overarching description of AIS research issues, challenges and directions as well as a nominal path that vehicle intelligence will take. The AIS program requires a very close coordination between research and implementation on real vehicles. This paper briefly discusses the symbiotic relationship between intelligence algorithms and implementation mechanisms. Also presented are representative work from two vehicle specific research program programs. Work from the Autonomous Air Systems program discusses the development of effective cooperate control for multiple air vehicle. The Autonomous Land Systems program discusses its developments in platform and ground vehicle intelligence.

Rotational-path decomposition based recursive planning for spacecraft attitude reorientation

NASA Astrophysics Data System (ADS)

Xu, Rui; Wang, Hui; Xu, Wenming; Cui, Pingyuan; Zhu, Shengying

2018-02-01

The spacecraft reorientation is a common task in many space missions. With multiple pointing constraints, it is greatly difficult to solve the constrained spacecraft reorientation planning problem. To deal with this problem, an efficient rotational-path decomposition based recursive planning (RDRP) method is proposed in this paper. The uniform pointing-constraint-ignored attitude rotation planning process is designed to solve all rotations without considering pointing constraints. Then the whole path is checked node by node. If any pointing constraint is violated, the nearest critical increment approach will be used to generate feasible alternative nodes in the process of rotational-path decomposition. As the planning path of each subdivision may still violate pointing constraints, multiple decomposition is needed and the reorientation planning is designed as a recursive manner. Simulation results demonstrate the effectiveness of the proposed method. The proposed method has been successfully applied in two SPARK microsatellites to solve onboard constrained attitude reorientation planning problem, which were developed by the Shanghai Engineering Center for Microsatellites and launched on 22 December 2016.

Autonomous Spacecraft Communication Interface for Load Planning

NASA Technical Reports Server (NTRS)

Dever, Timothy P.; May, Ryan D.; Morris, Paul H.

2014-01-01

Ground-based controllers can remain in continuous communication with spacecraft in low Earth orbit (LEO) with near-instantaneous communication speeds. This permits near real-time control of all of the core spacecraft systems by ground personnel. However, as NASA missions move beyond LEO, light-time communication delay issues, such as time lag and low bandwidth, will prohibit this type of operation. As missions become more distant, autonomous control of manned spacecraft will be required. The focus of this paper is the power subsystem. For present missions, controllers on the ground develop a complete schedule of power usage for all spacecraft components. This paper presents work currently underway at NASA to develop an architecture for an autonomous spacecraft, and focuses on the development of communication between the Mission Manager and the Autonomous Power Controller. These two systems must work together in order to plan future load use and respond to unanticipated plan deviations. Using a nominal spacecraft architecture and prototype versions of these two key components, a number of simulations are run under a variety of operational conditions, enabling development of content and format of the messages necessary to achieve the desired goals. The goals include negotiation of a load schedule that meets the global requirements (contained in the Mission Manager) and local power system requirements (contained in the Autonomous Power Controller), and communication of off-plan disturbances that arise while executing a negotiated plan. The message content is developed in two steps: first, a set of rapid-prototyping "paper" simulations are preformed; then the resultant optimized messages are codified for computer communication for use in automated testing.

Ovis: A Framework for Visual Analysis of Ocean Forecast Ensembles.

PubMed

Höllt, Thomas; Magdy, Ahmed; Zhan, Peng; Chen, Guoning; Gopalakrishnan, Ganesh; Hoteit, Ibrahim; Hansen, Charles D; Hadwiger, Markus

2014-08-01

We present a novel integrated visualization system that enables interactive visual analysis of ensemble simulations of the sea surface height that is used in ocean forecasting. The position of eddies can be derived directly from the sea surface height and our visualization approach enables their interactive exploration and analysis.The behavior of eddies is important in different application settings of which we present two in this paper. First, we show an application for interactive planning of placement as well as operation of off-shore structures using real-world ensemble simulation data of the Gulf of Mexico. Off-shore structures, such as those used for oil exploration, are vulnerable to hazards caused by eddies, and the oil and gas industry relies on ocean forecasts for efficient operations. We enable analysis of the spatial domain, as well as the temporal evolution, for planning the placement and operation of structures.Eddies are also important for marine life. They transport water over large distances and with it also heat and other physical properties as well as biological organisms. In the second application we present the usefulness of our tool, which could be used for planning the paths of autonomous underwater vehicles, so called gliders, for marine scientists to study simulation data of the largely unexplored Red Sea.

An advanced terrain modeler for an autonomous planetary rover

NASA Technical Reports Server (NTRS)

Hunter, E. L.

1980-01-01

A roving vehicle capable of autonomously exploring the surface of an alien world is under development and an advanced terrain modeler to characterize the possible paths of the rover as hazardous or safe is presented. This advanced terrain modeler has several improvements over the Troiani modeler that include: a crosspath analysis, better determination of hazards on slopes, and methods for dealing with missing returns at the extremities of the sensor field. The results from a package of programs to simulate the roving vehicle are then examined and compared to results from the Troiani modeler.

Path Planning for Robot based on Chaotic Artificial Potential Field Method

NASA Astrophysics Data System (ADS)

Zhang, Cheng

2018-03-01

Robot path planning in unknown environments is one of the hot research topics in the field of robot control. Aiming at the shortcomings of traditional artificial potential field methods, we propose a new path planning for Robot based on chaotic artificial potential field method. The path planning adopts the potential function as the objective function and introduces the robot direction of movement as the control variables, which combines the improved artificial potential field method with chaotic optimization algorithm. Simulations have been carried out and the results demonstrate that the superior practicality and high efficiency of the proposed method.

Autonomous Control Modes and Optimized Path Guidance for Shipboard Landing in High Sea States

DTIC Science & Technology

2015-11-16

a degraded visual environment, workload during the landing task begins to approach the limits of a human pilot’s capability. It is a similarly...Figure 2. Approach Trajectory ±4 ft landing error ±8 ft landing error ±12 ft landing error Flight Path -3000...heave and yaw axes. Figure 5. Open loop system generation ±4 ft landing error ±8 ft landing error ±12 ft landing error -10 -8 -6 -4 -2 0 2 4

Computer-Aided Remote Driving

NASA Technical Reports Server (NTRS)

Wilcox, Brian H.

1994-01-01

System for remote control of robotic land vehicle requires only small radio-communication bandwidth. Twin video cameras on vehicle create stereoscopic images. Operator views cross-polarized images on two cathode-ray tubes through correspondingly polarized spectacles. By use of cursor on frozen image, remote operator designates path. Vehicle proceeds to follow path, by use of limited degree of autonomous control to cope with unexpected conditions. System concept, called "computer-aided remote driving" (CARD), potentially useful in exploration of other planets, military surveillance, firefighting, and clean-up of hazardous materials.

Exploiting map plans as resources for action

NASA Technical Reports Server (NTRS)

Payton, David

1989-01-01

When plans are used as programs for controlling the action of autonomous or teleoperated robots, their abstract representation can easily obscure a great deal of the critical knowledge that originally led to the planned course of action. An autonomous vehicle experiment is highlighted which illustrates how the information barriers created by abstraction can result in undesirable action. It is then shown how the same task can be performed correctly using plans as a resource for action. As a result of this simple change in outlook, problems requiring opportunistic reaction to unexpected changes in the environment can be solved.

The planning coordinator: A design architecture for autonomous error recovery and on-line planning of intelligent tasks

NASA Technical Reports Server (NTRS)

Farah, Jeffrey J.

1992-01-01

Developing a robust, task level, error recovery and on-line planning architecture is an open research area. There is previously published work on both error recovery and on-line planning; however, none incorporates error recovery and on-line planning into one integrated platform. The integration of these two functionalities requires an architecture that possesses the following characteristics. The architecture must provide for the inclusion of new information without the destruction of existing information. The architecture must provide for the relating of pieces of information, old and new, to one another in a non-trivial rather than trivial manner (e.g., object one is related to object two under the following constraints, versus, yes, they are related; no, they are not related). Finally, the architecture must be not only a stand alone architecture, but also one that can be easily integrated as a supplement to some existing architecture. This thesis proposal addresses architectural development. Its intent is to integrate error recovery and on-line planning onto a single, integrated, multi-processor platform. This intelligent x-autonomous platform, called the Planning Coordinator, will be used initially to supplement existing x-autonomous systems and eventually replace them.

Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning

PubMed Central

Kok, Kai Yit; Rajendran, Parvathy

2016-01-01

The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost. PMID:26943630

Planning and Execution: The Spirit of Opportunity for Robust Autonomous Systems

NASA Technical Reports Server (NTRS)

Muscettola, Nicola

2004-01-01

One of the most exciting endeavors pursued by human kind is the search for life in the Solar System and the Universe at large. NASA is leading this effort by designing, deploying and operating robotic systems that will reach planets, planet moons, asteroids and comets searching for water, organic building blocks and signs of past or present microbial life. None of these missions will be achievable without substantial advances in.the design, implementation and validation of autonomous control agents. These agents must be capable of robustly controlling a robotic explorer in a hostile environment with very limited or no communication with Earth. The talk focuses on work pursued at the NASA Ames Research center ranging from basic research on algorithm to deployed mission support systems. We will start by discussing how planning and scheduling technology derived from the Remote Agent experiment is being used daily in the operations of the Spirit and Opportunity rovers. Planning and scheduling is also used as the fundamental paradigm at the core of our research in real-time autonomous agents. In particular, we will describe our efforts in the Intelligent Distributed Execution Architecture (IDEA), a multi-agent real-time architecture that exploits artificial intelligence planning as the core reasoning engine of an autonomous agent. We will also describe how the issue of plan robustness at execution can be addressed by novel constraint propagation algorithms capable of giving the tightest exact bounds on resource consumption or all possible executions of a flexible plan.

Three-dimensional path planning software-assisted transjugular intrahepatic portosystemic shunt: a technical modification.

PubMed

Tsauo, Jiaywei; Luo, Xuefeng; Ye, Linchao; Li, Xiao

2015-06-01

This study was designed to report our results with a modified technique of three-dimensional (3D) path planning software assisted transjugular intrahepatic portosystemic shunt (TIPS). 3D path planning software was recently developed to facilitate TIPS creation by using two carbon dioxide portograms acquired at least 20° apart to generate a 3D path for overlay needle guidance. However, one shortcoming is that puncturing along the overlay would be technically impossible if the angle of the liver access set and the angle of the 3D path are not the same. To solve this problem, a prototype 3D path planning software was fitted with a utility to calculate the angle of the 3D path. Using this, we modified the angle of the liver access set accordingly during the procedure in ten patients. Failure for technical reasons occurred in three patients (unsuccessful wedged hepatic venography in two cases, software technical failure in one case). The procedure was successful in the remaining seven patients, and only one needle pass was required to obtain portal vein access in each case. The course of puncture was comparable to the 3D path in all patients. No procedure-related complication occurred following the procedures. Adjusting the angle of the liver access set to match the angle of the 3D path determined by the software appears to be a favorable modification to the technique of 3D path planning software assisted TIPS.

Astrobiology Science and Technology: A Path to Future Discovery

NASA Technical Reports Server (NTRS)

Meyer, M. A.; Lavaery, D. B.

2001-01-01

The Astrobiology Program is described. However, science-driven robotic exploration of extreme environments is needed for a new era of planetary exploration requiring biologically relevant instrumentation and extensive, autonomous operations on planetary surfaces. Additional information is contained in the original extended abstract.

Knowledge-Based Motion Control of AN Intelligent Mobile Autonomous System

NASA Astrophysics Data System (ADS)

Isik, Can

An Intelligent Mobile Autonomous System (IMAS), which is equipped with vision and low level sensors to cope with unknown obstacles, is modeled as a hierarchy of path planning and motion control. This dissertation concentrates on the lower level of this hierarchy (Pilot) with a knowledge-based controller. The basis of a theory of knowledge-based controllers is established, using the example of the Pilot level motion control of IMAS. In this context, the knowledge-based controller with a linguistic world concept is shown to be adequate for the minimum time control of an autonomous mobile robot motion. The Pilot level motion control of IMAS is approached in the framework of production systems. The three major components of the knowledge-based control that are included here are the hierarchies of the database, the rule base and the rule evaluator. The database, which is the representation of the state of the world, is organized as a semantic network, using a concept of minimal admissible vocabulary. The hierarchy of rule base is derived from the analytical formulation of minimum-time control of IMAS motion. The procedure introduced for rule derivation, which is called analytical model verbalization, utilizes the concept of causalities to describe the system behavior. A realistic analytical system model is developed and the minimum-time motion control in an obstacle strewn environment is decomposed to a hierarchy of motion planning and control. The conditions for the validity of the hierarchical problem decomposition are established, and the consistency of operation is maintained by detecting the long term conflicting decisions of the levels of the hierarchy. The imprecision in the world description is modeled using the theory of fuzzy sets. The method developed for the choice of the rule that prescribes the minimum-time motion control among the redundant set of applicable rules is explained and the usage of fuzzy set operators is justified. Also included in the dissertation are the description of the computer simulation of Pilot within the hierarchy of IMAS control and the simulated experiments that demonstrate the theoretical work.

Micro Unmanned Surface Vehicle for Shallow Littoral Data Sampling

NASA Astrophysics Data System (ADS)

Murphy, R. R.; Wilde, G.

2016-02-01

This paper describes the creation of an autonomous air boat that can be carried by one person, called a micro unmanned surface vehicle (USV), for sensor sampling in shallow littoral areas such as inlets and creeks. A USV offers advantages over other types of unmanned marine vehicles. Unlike an autonomous underwater vehicle, the Challenge 1.0 air boat can operate in shallow water of less than 15 cm depth and maintain network connectivity for control and data sampling. A USV does not require a tether, like a remotely operated marine vehicle (ROV), which would limit the distance and mobility. However, a USV operating in shallow littoral areas poses several challenges. Navigation is a challenge since rivers and bays may have semi-submerged obstacles and there may be no depth maps; the approach taken in the Challenge 1.0 project is to let the operator specify a safe area of the water by visual inspection and then the USV autonomously creates a path to optimally sample the collision free area. Navigation is also a challenge because of platform dynamics-the USV we describe is a non-holonomic vehicle; this paper explores spiral paths rather than boustrophedon paths. Another challenge is the quality of sensing. Water-based sensing is noisy and thus a reading at a single point may not reflect the overall value. In practice, areas are sampled rather than a single point, but the noise in the point values within the sampled area produce a survey with widely varying numbers and are difficult for humans to interpret. This paper implements an inverse distance weighting interpolation algorithm to produce a visual "heatmap" that reliably portrays the smoothed data.

A novel representation for planning 3-D collision-free paths

NASA Technical Reports Server (NTRS)

Bonner, Susan; Kelley, Robert B.

1990-01-01

A new scheme for the representation of objects, the successive spherical approximation (SSA), facilitates the rapid planning of collision-free paths in a dynamic three-dimensional environment. The hierarchical nature of the SSA allows collisions to be determined efficiently while still providing an exact representation of objects. The rapidity with which collisions can be detected, less than 1 sec per environment object per path, makes it possible to use a generate-and-test path-planning strategy driven by human conceptual knowledge to determine collision-free paths in a matter of seconds on a Sun 3/180 computer. A hierarchy of rules, based on the concept of a free space cell, is used to find heuristically satisfying collision-free paths in a structured environment.

Robust and Opportunistic Autonomous Science for a Potential Titan Aerobot

NASA Technical Reports Server (NTRS)

Gaines, Daniel M.; Estlin, Tara; Schaffer, Steve; Castano, Rebecca; Elfes, Alberto

2010-01-01

We are developing onboard planning and execution technologies to provide robust and opportunistic mission operations for a potential Titan aerobot. Aerobot have the potential for collecting a vast amount of high priority science data. However, to be effective, an aerobot must address several challenges including communication constraints, extended periods without contact with Earth, uncertain and changing environmental conditions, maneuverability constraints and potentially short-lived science opportunities. We are developing the AerOASIS system to develop and test technology to support autonomous science operations for a potential Titan Aerobot. The planning and execution component of AerOASIS is able to generate mission operations plans that achieve science and engineering objectives while respecting mission and resource constraints as well as adapting the plan to respond to new science opportunities. Our technology leverages prior work on the OASIS system for autonomous rover exploration. In this paper we describe how the OASIS planning component was adapted to address the unique challenges of a Titan Aerobot and we describe a field demonstration of the system with the JPL prototype aerobot.

Study and development of techniques for automatic control of remote manipulators

NASA Technical Reports Server (NTRS)

Shaket, E.; Leal, A.

1976-01-01

An overall conceptual design for an autonomous control system of remote manipulators which utilizes feedback was constructed. The system consists of a description of the high-level capabilities of a model from which design algorithms are constructed. The autonomous capability is achieved through automatic planning and locally controlled execution of the plans. The operator gives his commands in high level task-oriented terms. The system transforms these commands into a plan. It uses built-in procedural knowledge of the problem domain and an internal model of the current state of the world.

A bat algorithm with mutation for UCAV path planning.

PubMed

Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi

2012-01-01

Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models.

A Feedforward Control Approach to the Local Navigation Problem for Autonomous Vehicles

DTIC Science & Technology

1994-05-02

AD-A282 787 " A Feedforward Control Approach to the Local Navigation Problem for Autonomous Vehicles Alonzo Kelly CMU-RI-TR-94-17 The Robotics...follow, or a direction to prefer, it cannot generate its own strategic goals. Therefore, it solves the local planning problem for autonomous vehicles . The... autonomous vehicles . It is intelligent because it uses range images that are generated from either a laser rangefinder or a stereo triangulation

Three-Dimensional Path Planning Software-Assisted Transjugular Intrahepatic Portosystemic Shunt: A Technical Modification

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

Tsauo, Jiaywei, E-mail: 80732059@qq.com; Luo, Xuefeng, E-mail: luobo-913@126.com; Ye, Linchao, E-mail: linchao.ye@siemens.com

2015-06-15

PurposeThis study was designed to report our results with a modified technique of three-dimensional (3D) path planning software assisted transjugular intrahepatic portosystemic shunt (TIPS).Methods3D path planning software was recently developed to facilitate TIPS creation by using two carbon dioxide portograms acquired at least 20° apart to generate a 3D path for overlay needle guidance. However, one shortcoming is that puncturing along the overlay would be technically impossible if the angle of the liver access set and the angle of the 3D path are not the same. To solve this problem, a prototype 3D path planning software was fitted with a utility to calculate themore » angle of the 3D path. Using this, we modified the angle of the liver access set accordingly during the procedure in ten patients.ResultsFailure for technical reasons occurred in three patients (unsuccessful wedged hepatic venography in two cases, software technical failure in one case). The procedure was successful in the remaining seven patients, and only one needle pass was required to obtain portal vein access in each case. The course of puncture was comparable to the 3D path in all patients. No procedure-related complication occurred following the procedures.ConclusionsAdjusting the angle of the liver access set to match the angle of the 3D path determined by the software appears to be a favorable modification to the technique of 3D path planning software assisted TIPS.« less

Research and application of genetic algorithm in path planning of logistics distribution vehicle

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

The core of the logistics distribution system is the vehicle routing planning, research path planning problem, provide a better solution has become an important issue. In order to provide the decision support for logistics and distribution operations, this paper studies the problem of vehicle routing with capacity constraints (CVRP). By establishing a mathematical model, the genetic algorithm is used to plan the path of the logistics vehicle to meet the minimum logistics and transportation costs.

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.

UAV Research at NASA Langley: Towards Safe, Reliable, and Autonomous Operations

NASA Technical Reports Server (NTRS)

Davila, Carlos G.

2016-01-01

Unmanned Aerial Vehicles (UAV) are fundamental components in several aspects of research at NASA Langley, such as flight dynamics, mission-driven airframe design, airspace integration demonstrations, atmospheric science projects, and more. In particular, NASA Langley Research Center (Langley) is using UAVs to develop and demonstrate innovative capabilities that meet the autonomy and robotics challenges that are anticipated in science, space exploration, and aeronautics. These capabilities will enable new NASA missions such as asteroid rendezvous and retrieval (ARRM), Mars exploration, in-situ resource utilization (ISRU), pollution measurements in historically inaccessible areas, and the integration of UAVs into our everyday lives all missions of increasing complexity, distance, pace, and/or accessibility. Building on decades of NASA experience and success in the design, fabrication, and integration of robust and reliable automated systems for space and aeronautics, Langley Autonomy Incubator seeks to bridge the gap between automation and autonomy by enabling safe autonomous operations via onboard sensing and perception systems in both data-rich and data-deprived environments. The Autonomy Incubator is focused on the challenge of mobility and manipulation in dynamic and unstructured environments by integrating technologies such as computer vision, visual odometry, real-time mapping, path planning, object detection and avoidance, object classification, adaptive control, sensor fusion, machine learning, and natural human-machine teaming. These technologies are implemented in an architectural framework developed in-house for easy integration and interoperability of cutting-edge hardware and software.

Initial Results from an Energy-Aware Airborne Dynamic, Data-Driven Application System Performing Sampling in Coherent Boundary-Layer Structures

NASA Astrophysics Data System (ADS)

Frew, E.; Argrow, B. M.; Houston, A. L.; Weiss, C.

2014-12-01

The energy-aware airborne dynamic, data-driven application system (EA-DDDAS) performs persistent sampling in complex atmospheric conditions by exploiting wind energy using the dynamic data-driven application system paradigm. The main challenge for future airborne sampling missions is operation with tight integration of physical and computational resources over wireless communication networks, in complex atmospheric conditions. The physical resources considered here include sensor platforms, particularly mobile Doppler radar and unmanned aircraft, the complex conditions in which they operate, and the region of interest. Autonomous operation requires distributed computational effort connected by layered wireless communication. Onboard decision-making and coordination algorithms can be enhanced by atmospheric models that assimilate input from physics-based models and wind fields derived from multiple sources. These models are generally too complex to be run onboard the aircraft, so they need to be executed in ground vehicles in the field, and connected over broadband or other wireless links back to the field. Finally, the wind field environment drives strong interaction between the computational and physical systems, both as a challenge to autonomous path planning algorithms and as a novel energy source that can be exploited to improve system range and endurance. Implementation details of a complete EA-DDDAS will be provided, along with preliminary flight test results targeting coherent boundary-layer structures.

Path planning algorithms for assembly sequence planning. [in robot kinematics

NASA Technical Reports Server (NTRS)

Krishnan, S. S.; Sanderson, Arthur C.

1991-01-01

Planning for manipulation in complex environments often requires reasoning about the geometric and mechanical constraints which are posed by the task. In planning assembly operations, the automatic generation of operations sequences depends on the geometric feasibility of paths which permit parts to be joined into subassemblies. Feasible locations and collision-free paths must be present for part motions, robot and grasping motions, and fixtures. This paper describes an approach to reasoning about the feasibility of straight-line paths among three-dimensional polyhedral parts using an algebra of polyhedral cones. A second method recasts the feasibility conditions as constraints in a nonlinear optimization framework. Both algorithms have been implemented and results are presented.

The NASA/Army Autonomous Rotorcraft Project

NASA Technical Reports Server (NTRS)

Whalley, M.; Freed, M.; Takahashi, M.; Christian, D.; Patterson-Hine, A.; Schulein, G.; Harris, R.

2002-01-01

An overview of the NASA Ames Research Center Autonomous Rotorcraft Project (ARP) is presented. The project brings together several technologies to address NASA and US Army autonomous vehicle needs, including a reactive planner for mission planning and execution, control system design incorporating a detailed understanding of the platform dynamics, and health monitoring and diagnostics. A candidate reconnaissance and surveillance mission is described. The autonomous agent architecture and its application to the candidate mission are presented. Details of the vehicle hardware and software development are provided.

Vehicle Guidance and Control Along Circular Trajectories

DTIC Science & Technology

1992-09-01

the line of sight, while Chism [2] studied a cross track error based control law. Hawkinson [3] extended the results to the multiple input case when...Thesis, Naval Postgraduate School, Monterey, California, June. 2. Chism , S., (1990) "Robust path tracking of autonomous underwater vehicles using sliding

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.

MO-F-CAMPUS-T-05: SQL Database Queries to Determine Treatment Planning Resource Usage

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

Fox, C; Gladstone, D

2015-06-15

Purpose: A radiation oncology clinic’s treatment capacity is traditionally thought to be limited by the number of machines in the clinic. As the number of fractions per course decrease and the number of adaptive plans increase, the question of how many treatment plans a clinic can plan becomes increasingly important. This work seeks to lay the ground work for assessing treatment planning resource usage. Methods: Care path templates were created using the Aria 11 care path interface. Care path tasks included key steps in the treatment planning process from the completion of CT simulation through the first radiation treatment. SQLmore » Server Management Studio was used to run SQL queries to extract task completion time stamps along with care path template information and diagnosis codes from the Aria database. 6 months of planning cycles were evaluated. Elapsed time was evaluated in terms of work hours within Monday – Friday, 7am to 5pm. Results: For the 195 validated treatment planning cycles, the average time for planning and MD review was 22.8 hours. Of those cases 33 were categorized as urgent. The average planning time for urgent plans was 5 hours. A strong correlation between diagnosis code and range of elapsed planning time was as well as between elapsed time and select diagnosis codes was observed. It was also observed that tasks were more likely to be completed on the date due than the time that they were due. Follow-up confirmed that most users did not look at the due time. Conclusion: Evaluation of elapsed planning time and other tasks suggest that care paths should be adjusted to allow for different contouring and planning times for certain diagnosis codes and urgent cases. Additional clinic training around task due times vs dates or a structuring of care paths around due dates is also needed.« less

Autonomous Mission Manager for Rendezvous, Inspection and Mating

NASA Technical Reports Server (NTRS)

Zimpfer, Douglas J.

2003-01-01

To meet cost and safety objectives, space missions that involve proximity operations between two vehicles require a high level of autonomy to successfully complete their missions. The need for autonomy is primarily driven by the need to conduct complex operations outside of communication windows, and the communication time delays inherent in space missions. Autonomy also supports the goals of both NASA and the DOD to make space operations more routine, and lower operational costs by reducing the requirement for ground personnel. NASA and the DoD have several programs underway that require a much higher level of autonomy for space vehicles. NASA's Space Launch Initiative (SLI) program has ambitious goals of reducing costs by a factor or 10 and improving safety by a factor of 100. DARPA has recently begun its Orbital Express to demonstrate key technologies to make satellite servicing routine. The Air Force's XSS-ll program is developing a protoflight demonstration of an autonomous satellite inspector. A common element in space operations for many NASA and DOD missions is the ability to rendezvous, inspect anclJor dock with another spacecraft. For DARPA, this is required to service or refuel military satellites. For the Air Force, this is required to inspect un-cooperative resident space objects. For NASA, this is needed to meet the primary SLI design reference mission of International Space Station re-supply. A common aspect for each of these programs is an Autonomous Mission Manager that provides highly autonomous planning, execution and monitoring of the rendezvous, inspection and docking operations. This paper provides an overview of the Autonomous Mission Manager (AMM) design being incorporated into many of these technology programs. This AMM provides a highly scalable level of autonomous operations, ranging from automatic execution of ground-derived plans to highly autonomous onboard planning to meet ground developed mission goals. The AMM provides the capability to automatically execute the plans and monitor the system performance. In the event of system dispersions or failures the AMM can modify plans or abort to assure overall system safety. This paper describes the design and functionality of Draper's AMM framework, presents concept of operations associated with the use of the AMM, and outlines the relevant features of the flight demonstrations.

Getting the Most from the Twin Mars Rovers

NASA Technical Reports Server (NTRS)

Laufenberg, Larry

2003-01-01

The report discusses the Mixed-initiative Activity Planning GENerator (MARGEN) automatically generates activity plans for rovers. Decision support system mixes autonomous planning/scheduling with user modifications. Accommodating change. Technology spotlight

A Bat Algorithm with Mutation for UCAV Path Planning

PubMed Central

Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi

2012-01-01

Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models. PMID:23365518

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs

PubMed Central

Jiang, Peng; Li, Deshi; Sun, Tao

2017-01-01

Unmanned Aerial Vehicles (UAVs) play an important role in applications such as data collection and target reconnaissance. An accurate and optimal path can effectively increase the mission success rate in the case of small UAVs. Although path planning for UAVs is similar to that for traditional mobile robots, the special kinematic characteristics of UAVs (such as their minimum turning radius) have not been taken into account in previous studies. In this paper, we propose a locally-adjustable, continuous-curvature, bounded path-planning algorithm for fixed-wing UAVs. To deal with the curvature discontinuity problem, an optimal interpolation algorithm and a key-point shift algorithm are proposed based on the derivation of a curvature continuity condition. To meet the upper bound for curvature and to render the curvature extrema controllable, a local replanning scheme is designed by combining arcs and Bezier curves with monotonic curvature. In particular, a path transition mechanism is built for the replanning phase using minimum curvature circles for a planning philosophy. Numerical results demonstrate that the analytical planning algorithm can effectively generate continuous-curvature paths, while satisfying the curvature upper bound constraint and allowing UAVs to pass through all predefined waypoints in the desired mission region. PMID:28925960

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs.

PubMed

Wang, Xiaoliang; Jiang, Peng; Li, Deshi; Sun, Tao

2017-09-19

Unmanned Aerial Vehicles (UAVs) play an important role in applications such as data collection and target reconnaissance. An accurate and optimal path can effectively increase the mission success rate in the case of small UAVs. Although path planning for UAVs is similar to that for traditional mobile robots, the special kinematic characteristics of UAVs (such as their minimum turning radius) have not been taken into account in previous studies. In this paper, we propose a locally-adjustable, continuous-curvature, bounded path-planning algorithm for fixed-wing UAVs. To deal with the curvature discontinuity problem, an optimal interpolation algorithm and a key-point shift algorithm are proposed based on the derivation of a curvature continuity condition. To meet the upper bound for curvature and to render the curvature extrema controllable, a local replanning scheme is designed by combining arcs and Bezier curves with monotonic curvature. In particular, a path transition mechanism is built for the replanning phase using minimum curvature circles for a planning philosophy. Numerical results demonstrate that the analytical planning algorithm can effectively generate continuous-curvature paths, while satisfying the curvature upper bound constraint and allowing UAVs to pass through all predefined waypoints in the desired mission region.

Constrained VPH+: a local path planning algorithm for a bio-inspired crawling robot with customized ultrasonic scanning sensor.

PubMed

Rao, Akshay; Elara, Mohan Rajesh; Elangovan, Karthikeyan

This paper aims to develop a local path planning algorithm for a bio-inspired, reconfigurable crawling robot. A detailed description of the robotic platform is first provided, and the suitability for deployment of each of the current state-of-the-art local path planners is analyzed after an extensive literature review. The Enhanced Vector Polar Histogram algorithm is described and reformulated to better fit the requirements of the platform. The algorithm is deployed on the robotic platform in crawling configuration and favorably compared with other state-of-the-art local path planning algorithms.

Need satisfaction, motivational regulations and exercise: moderation and mediation effects.

PubMed

Weman-Josefsson, Karin; Lindwall, Magnus; Ivarsson, Andreas

2015-05-20

Based on the Self-determination theory process model, this study aimed to explore relationships between the latent constructs of psychological need satisfaction, autonomous motivation and exercise behaviour; the mediational role of autonomous motivation in the association of psychological need satisfaction with exercise behaviour; as well as gender and age differences in the aforementioned associations. Adult active members of an Internet-based exercise program (n = 1091) between 18 and 78 years of age completed a test battery on motivational aspects based on Self-determination theory. The Basic Psychological Needs in Exercise Scale and the Behavioural Regulation in Exercise Questionnaire-2 were used to measure need satisfaction and type of motivation and the Leisure Time Exercise Questionnaire to measure self-reported exercise. Need satisfaction predicted autonomous motivation, which in turn predicted exercise, especially for women. Autonomous motivation was found to mediate the association between need satisfaction and exercise. Age and gender moderated several of the paths in the model linking need satisfaction with motivation and exercise. The results demonstrated gender and age differences in the proposed sequential mechanisms between autonomous motivation and exercise in the process model. This study thus highlights a potential value in considering moderating factors and the need to further examine the underlying mechanisms between needs, autonomous motivation, and exercise behaviour.

Autonomous Planning and Replanning for Mine-Sweeping Unmanned Underwater Vehicles

NASA Technical Reports Server (NTRS)

Gaines, Daniel M.

2010-01-01

This software generates high-quality plans for carrying out mine-sweeping activities under resource constraints. The autonomous planning and replanning system for unmanned underwater vehicles (UUVs) takes as input a set of prioritized mine-sweep regions, and a specification of available UUV resources including available battery energy, data storage, and time available for accomplishing the mission. Mine-sweep areas vary in location, size of area to be swept, and importance of the region. The planner also works with a model of the UUV, as well as a model of the power consumption of the vehicle when idle and when moving.

Path Searching Based Fault Automated Recovery Scheme for Distribution Grid with DG

NASA Astrophysics Data System (ADS)

Xia, Lin; Qun, Wang; Hui, Xue; Simeng, Zhu

2016-12-01

Applying the method of path searching based on distribution network topology in setting software has a good effect, and the path searching method containing DG power source is also applicable to the automatic generation and division of planned islands after the fault. This paper applies path searching algorithm in the automatic division of planned islands after faults: starting from the switch of fault isolation, ending in each power source, and according to the line load that the searching path traverses and the load integrated by important optimized searching path, forming optimized division scheme of planned islands that uses each DG as power source and is balanced to local important load. Finally, COBASE software and distribution network automation software applied are used to illustrate the effectiveness of the realization of such automatic restoration program.

Demonstration of a Spoken Dialogue Interface for Planning Activities of a Semi-autonomous Robot

NASA Technical Reports Server (NTRS)

Dowding, John; Frank, Jeremy; Hockey, Beth Ann; Jonsson, Ari; Aist, Gregory

2002-01-01

Planning and scheduling in the face of uncertainty and change pushes the capabilities of both planning and dialogue technologies by requiring complex negotiation to arrive at a workable plan. Planning for use of semi-autonomous robots involves negotiation among multiple participants with competing scientific and engineering goals to co-construct a complex plan. In NASA applications this plan construction is done under severe time pressure so having a dialogue interface to the plan construction tools can aid rapid completion of the process. But, this will put significant demands on spoken dialogue technology, particularly in the areas of dialogue management and generation. The dialogue interface will need to be able to handle the complex dialogue strategies that occur in negotiation dialogues, including hypotheticals and revisions, and the generation component will require an ability to summarize complex plans. This demonstration will describe a work in progress towards building a spoken dialogue interface to the EUROPA planner for the purposes of planning and scheduling the activities of a semi-autonomous robot. A prototype interface has been built for planning the schedule of the Personal Satellite Assistant (PSA), a mobile robot designed for micro-gravity environments that is intended for use on the Space Shuttle and International Space Station. The spoken dialogue interface gives the user the capability to ask for a description of the plan, ask specific questions about the plan, and update or modify the plan. We anticipate that a spoken dialogue interface to the planner will provide a natural augmentation or alternative to the visualization interface, in situations in which the user needs very targeted information about the plan, in situations where natural language can express complex ideas more concisely than GUI actions, or in situations in which a graphical user interface is not appropriate.

Assessing the Performance of Human-Automation Collaborative Planning Systems

DTIC Science & Technology

2011-06-01

process- ing and incorporating vast amounts of incoming information into their solutions. How- ever, these algorithms are brittle and unable to account for...planning system, a descriptive Mission Performance measure may address the total travel time on the path or the cost of the path (e.g. total work...minimizing costs or collisions [4, 32, 33]. Error measures for such a path planning system may track how many collisions occur or how much threat

Towards an Autonomous Space In-Situ Marine Sensorweb

NASA Technical Reports Server (NTRS)

Chien, S.; Doubleday, J.; Tran, D.; Thompson, D.; Mahoney, G.; Chao, Y.; Castano, R.; Ryan, J.; Kudela, R.; Palacios, S.;

Mediated Paths to Overreactive Discipline: Mothers' Experienced Emotion, Appraisals, and Physiological Responses

ERIC Educational Resources Information Center

Lorber, Michael F.; O'Leary, Susan G.

2005-01-01

The present investigation was designed to evaluate whether mothers' emotion experience, autonomic reactivity, and negatively biased appraisals of their toddlers' behavior and toddlers' rates of misbehavior predicted overreactive discipline in a mediated fashion. Ninety-three community mother-toddler dyads were observed in a laboratory interaction,…

Application of Grazing-Inspired Guidance Laws to Autonomous Information Gathering

DTIC Science & Technology

2014-09-01

paths by expressing it as the Selective Traveling Salesman Problem subject to dynamic constraints. Tisdale et al. [11] utilized a receding horizon ap...vehicle failures by halving the initial fuel level on selected agents. Note that simulations start with agents 50s travel time away from where they

Causal modeling of self-concept, job satisfaction, and retention of nurses.

PubMed

Cowin, Leanne S; Johnson, Maree; Craven, Rhonda G; Marsh, Herbert W

2008-10-01

The critical shortage of nurses experienced throughout the western world has prompted researchers to examine one major component of this complex problem - the impact of nurses' professional identity and job satisfaction on retention. A descriptive correlational design with a longitudinal element was used to examine a causal model of nurses' self-concept, job satisfaction, and retention plans in 2002. A random sample of 2000 registered nurses was selected from the state registering authority listing. A postal survey assessing multiple dimensions of nurses' self-concept (measured by the nurse self-concept questionnaire), job satisfaction (measured by the index of work satisfaction) was undertaken at Time 1 (n=528) and 8 months later at Time 2 (n=332) (including retention plans (measured by the Nurse Retention Index). Using confirmatory factor analysis, correlation matrices and path analysis, measurement and structural models were examined on matching pairs of data from T1 and T2 (total sample N=332). Nurses' self-concept was found to have a stronger association with nurses' retention plans (B=.45) than job satisfaction (B=.28). Aspects of pay and task were not significantly related to retention plans, however, professional status (r=.51), and to a lesser extent, organizational policies (r=.27) were significant factors. Nurses' general self-concept was strongly related (r=.57) to retention plans. Strategies or interventions requiring implementation and evaluation include: counseling to improve nurse general self-concept, education programs and competencies in health communication between health professionals, reporting of nurse-initiated programs with substantial patient benefit, nurse-friendly organizational policies, common health team learning opportunities, and autonomous practice models.

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.

Automatic Parking of Self-Driving CAR Based on LIDAR

NASA Astrophysics Data System (ADS)

Lee, B.; Wei, Y.; Guo, I. Y.

2017-09-01

To overcome the deficiency of ultrasonic sensor and camera, this paper proposed a method of autonomous parking based on the self-driving car, using HDL-32E LiDAR. First the 3-D point cloud data was preprocessed. Then we calculated the minimum size of parking space according to the dynamic theories of vehicle. Second the rapidly-exploring random tree algorithm (RRT) algorithm was improved in two aspects based on the moving characteristic of autonomous car. And we calculated the parking path on the basis of the vehicle's dynamics and collision constraints. Besides, we used the fuzzy logic controller to control the brake and accelerator in order to realize the stably of speed. At last the experiments were conducted in an autonomous car, and the results show that the proposed automatic parking system is feasible and effective.

Optimal Paths in Gliding Flight

NASA Astrophysics Data System (ADS)

Wolek, Artur

Underwater gliders are robust and long endurance ocean sampling platforms that are increasingly being deployed in coastal regions. This new environment is characterized by shallow waters and significant currents that can challenge the mobility of these efficient (but traditionally slow moving) vehicles. This dissertation aims to improve the performance of shallow water underwater gliders through path planning. The path planning problem is formulated for a dynamic particle (or "kinematic car") model. The objective is to identify the path which satisfies specified boundary conditions and minimizes a particular cost. Several cost functions are considered. The problem is addressed using optimal control theory. The length scales of interest for path planning are within a few turn radii. First, an approach is developed for planning minimum-time paths, for a fixed speed glider, that are sub-optimal but are guaranteed to be feasible in the presence of unknown time-varying currents. Next the minimum-time problem for a glider with speed controls, that may vary between the stall speed and the maximum speed, is solved. Last, optimal paths that minimize change in depth (equivalently, maximize range) are investigated. Recognizing that path planning alone cannot overcome all of the challenges associated with significant currents and shallow waters, the design of a novel underwater glider with improved capabilities is explored. A glider with a pneumatic buoyancy engine (allowing large, rapid buoyancy changes) and a cylindrical moving mass mechanism (generating large pitch and roll moments) is designed, manufactured, and tested to demonstrate potential improvements in speed and maneuverability.

A Hybrid Metaheuristic DE/CS Algorithm for UCAV Three-Dimension Path Planning

PubMed Central

Wang, Gaige; Guo, Lihong; Duan, Hong; Wang, Heqi; Liu, Luo; Shao, Mingzhen

2012-01-01

Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model. PMID:23193383

A hybrid metaheuristic DE/CS algorithm for UCAV three-dimension path planning.

PubMed

Wang, Gaige; Guo, Lihong; Duan, Hong; Wang, Heqi; Liu, Luo; Shao, Mingzhen

2012-01-01

Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model.

Spacecraft Attitude Maneuver Planning Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Kornfeld, Richard P.

2004-01-01

A key enabling technology that leads to greater spacecraft autonomy is the capability to autonomously and optimally slew the spacecraft from and to different attitudes while operating under a number of celestial and dynamic constraints. The task of finding an attitude trajectory that meets all the constraints is a formidable one, in particular for orbiting or fly-by spacecraft where the constraints and initial and final conditions are of time-varying nature. This approach for attitude path planning makes full use of a priori constraint knowledge and is computationally tractable enough to be executed onboard a spacecraft. The approach is based on incorporating the constraints into a cost function and using a Genetic Algorithm to iteratively search for and optimize the solution. This results in a directed random search that explores a large part of the solution space while maintaining the knowledge of good solutions from iteration to iteration. A solution obtained this way may be used as is or as an initial solution to initialize additional deterministic optimization algorithms. A number of representative case examples for time-fixed and time-varying conditions yielded search times that are typically on the order of minutes, thus demonstrating the viability of this method. This approach is applicable to all deep space and planet Earth missions requiring greater spacecraft autonomy, and greatly facilitates navigation and science observation planning.

Information for Successful Interaction with Autonomous Systems

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Johnson, Kathy A.

2003-01-01

Interaction in heterogeneous mission operations teams is not well matched to classical models of coordination with autonomous systems. We describe methods of loose coordination and information management in mission operations. We describe an information agent and information management tool suite for managing information from many sources, including autonomous agents. We present an integrated model of levels of complexity of agent and human behavior, which shows types of information processing and points of potential error in agent activities. We discuss the types of information needed for diagnosing problems and planning interactions with an autonomous system. We discuss types of coordination for which designs are needed for autonomous system functions.

Evolutionistic or revolutionary paths? A PACS maturity model for strategic situational planning.

PubMed

van de Wetering, Rogier; Batenburg, Ronald; Lederman, Reeva

2010-07-01

While many hospitals are re-evaluating their current Picture Archiving and Communication System (PACS), few have a mature strategy for PACS deployment. Furthermore, strategies for implementation, strategic and situational planning methods for the evolution of PACS maturity are scarce in the scientific literature. Consequently, in this paper we propose a strategic planning method for PACS deployment. This method builds upon a PACS maturity model (PMM), based on the elaboration of the strategic alignment concept and the maturity growth path concept previously developed in the PACS domain. First, we review the literature on strategic planning for information systems and information technology and PACS maturity. Secondly, the PMM is extended by applying four different strategic perspectives of the Strategic Alignment Framework whereupon two types of growth paths (evolutionistic and revolutionary) are applied that focus on a roadmap for PMM. This roadmap builds a path to get from one level of maturity and evolve to the next. An extended method for PACS strategic planning is developed. This method defines eight distinctive strategies for PACS strategic situational planning that allow decision-makers in hospitals to decide which approach best suits their hospitals' current situation and future ambition and what in principle is needed to evolve through the different maturity levels. The proposed method allows hospitals to strategically plan for PACS maturation. It is situational in that the required investments and activities depend on the alignment between the hospital strategy and the selected growth path. The inclusion of both strategic alignment and maturity growth path concepts make the planning method rigorous, and provide a framework for further empirical research and clinical practice.

Escalator: An Autonomous Scheduling Scheme for Convergecast in TSCH

PubMed Central

Oh, Sukho; Hwang, DongYeop; Kim, Ki-Hyung; Kim, Kangseok

2018-01-01

Time Slotted Channel Hopping (TSCH) is widely used in the industrial wireless sensor networks due to its high reliability and energy efficiency. Various timeslot and channel scheduling schemes have been proposed for achieving high reliability and energy efficiency for TSCH networks. Recently proposed autonomous scheduling schemes provide flexible timeslot scheduling based on the routing topology, but do not take into account the network traffic and packet forwarding delays. In this paper, we propose an autonomous scheduling scheme for convergecast in TSCH networks with RPL as a routing protocol, named Escalator. Escalator generates a consecutive timeslot schedule along the packet forwarding path to minimize the packet transmission delay. The schedule is generated autonomously by utilizing only the local routing topology information without any additional signaling with other nodes. The generated schedule is guaranteed to be conflict-free, in that all nodes in the network could transmit packets to the sink in every slotframe cycle. We implement Escalator and evaluate its performance with existing autonomous scheduling schemes through a testbed and simulation. Experimental results show that the proposed Escalator has lower end-to-end delay and higher packet delivery ratio compared to the existing schemes regardless of the network topology. PMID:29659508

Escalator: An Autonomous Scheduling Scheme for Convergecast in TSCH.

PubMed

Oh, Sukho; Hwang, DongYeop; Kim, Ki-Hyung; Kim, Kangseok

2018-04-16

Time Slotted Channel Hopping (TSCH) is widely used in the industrial wireless sensor networks due to its high reliability and energy efficiency. Various timeslot and channel scheduling schemes have been proposed for achieving high reliability and energy efficiency for TSCH networks. Recently proposed autonomous scheduling schemes provide flexible timeslot scheduling based on the routing topology, but do not take into account the network traffic and packet forwarding delays. In this paper, we propose an autonomous scheduling scheme for convergecast in TSCH networks with RPL as a routing protocol, named Escalator. Escalator generates a consecutive timeslot schedule along the packet forwarding path to minimize the packet transmission delay. The schedule is generated autonomously by utilizing only the local routing topology information without any additional signaling with other nodes. The generated schedule is guaranteed to be conflict-free, in that all nodes in the network could transmit packets to the sink in every slotframe cycle. We implement Escalator and evaluate its performance with existing autonomous scheduling schemes through a testbed and simulation. Experimental results show that the proposed Escalator has lower end-to-end delay and higher packet delivery ratio compared to the existing schemes regardless of the network topology.

A path planning method used in fluid jet polishing eliminating lightweight mirror imprinting effect

NASA Astrophysics Data System (ADS)

Li, Wenzong; Fan, Bin; Shi, Chunyan; Wang, Jia; Zhuo, Bin

2014-08-01

With the development of space technology, the design of optical system tends to large aperture lightweight mirror with high dimension-thickness ratio. However, when the lightweight mirror PV value is less than λ/10 , the surface will show wavy imprinting effect obviously. Imprinting effect introduced by head-tool pressure has become a technological barrier in high-precision lightweight mirror manufacturing. Fluid jet polishing can exclude outside pressure. Presently, machining tracks often used are grating type path, screw type path and pseudo-random path. On the edge of imprinting error, the speed of adjacent path points changes too fast, which causes the machine hard to reflect quickly, brings about new path error, and increases the polishing time due to superfluous path. This paper presents a new planning path method to eliminate imprinting effect. Simulation results show that the path of the improved grating path can better eliminate imprinting effect compared to the general path.

Stochastic Evolutionary Algorithms for Planning Robot Paths

NASA Technical Reports Server (NTRS)

Fink, Wolfgang; Aghazarian, Hrand; Huntsberger, Terrance; Terrile, Richard

2006-01-01

A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.

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.

Origami-inspired, on-demand deployable and collapsible mechanical metamaterials with tunable stiffness

NASA Astrophysics Data System (ADS)

Zhai, Zirui; Wang, Yong; Jiang, Hanqing

2018-03-01

Origami has been employed to build deployable mechanical metamaterials through folding and unfolding along the crease lines. Deployable metamaterials are usually flexible, particularly along their deploying and collapsing directions, which unfortunately in many cases leads to an unstable deployed state, i.e., small perturbations may collapse the structure along the same deployment path. Here we create an origami-inspired mechanical metamaterial with on-demand deployability and selective collapsibility through energy analysis. This metamaterial has autonomous deployability from the collapsed state and can be selectively collapsed along two different paths, embodying low stiffness for one path and substantially high stiffness for another path. The created mechanical metamaterial yields load-bearing capability in the deployed direction while possessing great deployability and collapsibility. The principle in this work can be utilized to design and create versatile origami-inspired mechanical metamaterials that can find many applications.

Origami-inspired, on-demand deployable and collapsible mechanical metamaterials with tunable stiffness.

PubMed

Zhai, Zirui; Wang, Yong; Jiang, Hanqing

2018-02-27

Origami has been employed to build deployable mechanical metamaterials through folding and unfolding along the crease lines. Deployable metamaterials are usually flexible, particularly along their deploying and collapsing directions, which unfortunately in many cases leads to an unstable deployed state, i.e., small perturbations may collapse the structure along the same deployment path. Here we create an origami-inspired mechanical metamaterial with on-demand deployability and selective collapsibility through energy analysis. This metamaterial has autonomous deployability from the collapsed state and can be selectively collapsed along two different paths, embodying low stiffness for one path and substantially high stiffness for another path. The created mechanical metamaterial yields load-bearing capability in the deployed direction while possessing great deployability and collapsibility. The principle in this work can be utilized to design and create versatile origami-inspired mechanical metamaterials that can find many applications. Copyright © 2018 the Author(s). Published by PNAS.

Origami-inspired, on-demand deployable and collapsible mechanical metamaterials with tunable stiffness

PubMed Central

Zhai, Zirui; Wang, Yong

2018-01-01

Origami has been employed to build deployable mechanical metamaterials through folding and unfolding along the crease lines. Deployable metamaterials are usually flexible, particularly along their deploying and collapsing directions, which unfortunately in many cases leads to an unstable deployed state, i.e., small perturbations may collapse the structure along the same deployment path. Here we create an origami-inspired mechanical metamaterial with on-demand deployability and selective collapsibility through energy analysis. This metamaterial has autonomous deployability from the collapsed state and can be selectively collapsed along two different paths, embodying low stiffness for one path and substantially high stiffness for another path. The created mechanical metamaterial yields load-bearing capability in the deployed direction while possessing great deployability and collapsibility. The principle in this work can be utilized to design and create versatile origami-inspired mechanical metamaterials that can find many applications. PMID:29440441

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.

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.

Autonomous Object Manipulation Using a Soft Planar Grasping Manipulator

PubMed Central

Katzschmann, Robert K.; Marchese, Andrew D.

2015-01-01

Abstract This article presents the development of an autonomous motion planning algorithm for a soft planar grasping manipulator capable of grasp-and-place operations by encapsulation with uncertainty in the position and shape of the object. The end effector of the soft manipulator is fabricated in one piece without weakening seams using lost-wax casting instead of the commonly used multilayer lamination process. The soft manipulation system can grasp randomly positioned objects within its reachable envelope and move them to a desired location without human intervention. The autonomous planning system leverages the compliance and continuum bending of the soft grasping manipulator to achieve repeatable grasps in the presence of uncertainty. A suite of experiments is presented that demonstrates the system's capabilities. PMID:27625916

Artificial Neural Network Based Mission Planning Mechanism for Spacecraft

NASA Astrophysics Data System (ADS)

Li, Zhaoyu; Xu, Rui; Cui, Pingyuan; Zhu, Shengying

2018-04-01

The ability to plan and react fast in dynamic space environments is central to intelligent behavior of spacecraft. For space and robotic applications, many planners have been used. But it is difficult to encode the domain knowledge and directly use existing techniques such as heuristic to improve the performance of the application systems. Therefore, regarding planning as an advanced control problem, this paper first proposes an autonomous mission planning and action selection mechanism through a multiple layer perceptron neural network approach to select actions in planning process and improve efficiency. To prove the availability and effectiveness, we use autonomous mission planning problems of the spacecraft, which is a sophisticated system with complex subsystems and constraints as an example. Simulation results have shown that artificial neural networks (ANNs) are usable for planning problems. Compared with the existing planning method in EUROPA, the mechanism using ANNs is more efficient and can guarantee stable performance. Therefore, the mechanism proposed in this paper is more suitable for planning problems of spacecraft that require real time and stability.

MO-F-CAMPUS-T-03: Continuous Dose Delivery with Gamma Knife Perfexion

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

Ghobadi,; Li, W; Chung, C

2015-06-15

Purpose: We propose continuous dose delivery techniques for stereotactic treatments delivered by Gamma Knife Perfexion using inverse treatment planning system that can be applied to various tumour sites in the brain. We test the accuracy of the plans on Perfexion’s planning system (GammaPlan) to ensure the obtained plans are viable. This approach introduces continuous dose delivery for Perefxion, as opposed to the currently employed step-and-shoot approaches, for different tumour sites. Additionally, this is the first realization of automated inverse planning on GammaPlan. Methods: The inverse planning approach is divided into two steps of identifying a quality path inside the target,more » and finding the best collimator composition for the path. To find a path, we select strategic regions inside the target volume and find a path that visits each region exactly once. This path is then passed to a mathematical model which finds the best combination of collimators and their durations. The mathematical model minimizes the dose spillage to the surrounding tissues while ensuring the prescribed dose is delivered to the target(s). Organs-at-risk and their corresponding allowable doses can also be added to the model to protect adjacent organs. Results: We test this approach on various tumour sizes and sites. The quality of the obtained treatment plans are comparable or better than forward plans and inverse plans that use step- and-shoot technique. The conformity indices in the obtained continuous dose delivery plans are similar to those of forward plans while the beam-on time is improved on average (see Table 1 in supporting document). Conclusion: We employ inverse planning for continuous dose delivery in Perfexion for brain tumours. The quality of the obtained plans is similar to forward and inverse plans that use conventional step-and-shoot technique. We tested the inverse plans on GammaPlan to verify clinical relevance. This research was partially supported by Elekta, Sweden (vendor of Gamma Knife Perfexion)« less

Orbital Express Mission Operations Planning and Resource Management using ASPEN

NASA Technical Reports Server (NTRS)

Chouinard, Caroline; Knight, Russell; Jones, Grailing; Tran, Danny

2008-01-01

The Orbital Express satellite servicing demonstrator program is a DARPA program aimed at developing "a safe and cost-effective approach to autonomously service satellites in orbit". The system consists of: a) the Autonomous Space Transport Robotic Operations (ASTRO) vehicle, under development by Boeing Integrated Defense Systems, and b) a prototype modular next-generation serviceable satellite, NEXTSat, being developed by Ball Aerospace. Flexibility of ASPEN: a) Accommodate changes to procedures; b) Accommodate changes to daily losses and gains; c) Responsive re-planning; and d) Critical to success of mission planning Auto-Generation of activity models: a) Created plans quickly; b) Repetition/Re-use of models each day; and c) Guarantees the AML syntax. One SRP per day vs. Tactical team

Autonomous Navigation Using Celestial Objects

NASA Technical Reports Server (NTRS)

Folta, David; Gramling, Cheryl; Leung, Dominic; Belur, Sheela; Long, Anne

1999-01-01

In the twenty-first century, National Aeronautics and Space Administration (NASA) Enterprises envision frequent low-cost missions to explore the solar system, observe the universe, and study our planet. Satellite autonomy is a key technology required to reduce satellite operating costs. The Guidance, Navigation, and Control Center (GNCC) at the Goddard Space Flight Center (GSFC) currently sponsors several initiatives associated with the development of advanced spacecraft systems to provide autonomous navigation and control. Autonomous navigation has the potential both to increase spacecraft navigation system performance and to reduce total mission cost. By eliminating the need for routine ground-based orbit determination and special tracking services, autonomous navigation can streamline spacecraft ground systems. Autonomous navigation products can be included in the science telemetry and forwarded directly to the scientific investigators. In addition, autonomous navigation products are available onboard to enable other autonomous capabilities, such as attitude control, maneuver planning and orbit control, and communications signal acquisition. Autonomous navigation is required to support advanced mission concepts such as satellite formation flying. GNCC has successfully developed high-accuracy autonomous navigation systems for near-Earth spacecraft using NASA's space and ground communications systems and the Global Positioning System (GPS). Recently, GNCC has expanded its autonomous navigation initiative to include satellite orbits that are beyond the regime in which use of GPS is possible. Currently, GNCC is assessing the feasibility of using standard spacecraft attitude sensors and communication components to provide autonomous navigation for missions including: libration point, gravity assist, high-Earth, and interplanetary orbits. The concept being evaluated uses a combination of star, Sun, and Earth sensor measurements along with forward-link Doppler measurements from the command link carrier to autonomously estimate the spacecraft's orbit and reference oscillator's frequency. To support autonomous attitude determination and control and maneuver planning and control, the orbit determination accuracy should be on the order of kilometers in position and centimeters per second in velocity. A less accurate solution (one hundred kilometers in position) could be used for acquisition purposes for command and science downloads. This paper provides performance results for both libration point orbiting and high Earth orbiting satellites as a function of sensor measurement accuracy, measurement types, measurement frequency, initial state errors, and dynamic modeling errors.

Mobile robot navigation modulated by artificial emotions.

PubMed

Lee-Johnson, C P; Carnegie, D A

2010-04-01

For artificial intelligence research to progress beyond the highly specialized task-dependent implementations achievable today, researchers may need to incorporate aspects of biological behavior that have not traditionally been associated with intelligence. Affective processes such as emotions may be crucial to the generalized intelligence possessed by humans and animals. A number of robots and autonomous agents have been created that can emulate human emotions, but the majority of this research focuses on the social domain. In contrast, we have developed a hybrid reactive/deliberative architecture that incorporates artificial emotions to improve the general adaptive performance of a mobile robot for a navigation task. Emotions are active on multiple architectural levels, modulating the robot's decisions and actions to suit the context of its situation. Reactive emotions interact with the robot's control system, altering its parameters in response to appraisals from short-term sensor data. Deliberative emotions are learned associations that bias path planning in response to eliciting objects or events. Quantitative results are presented that demonstrate situations in which each artificial emotion can be beneficial to performance.

Optimizing a mobile robot control system using GPU acceleration

NASA Astrophysics Data System (ADS)

Tuck, Nat; McGuinness, Michael; Martin, Fred

2012-01-01

This paper describes our attempt to optimize a robot control program for the Intelligent Ground Vehicle Competition (IGVC) by running computationally intensive portions of the system on a commodity graphics processing unit (GPU). The IGVC Autonomous Challenge requires a control program that performs a number of different computationally intensive tasks ranging from computer vision to path planning. For the 2011 competition our Robot Operating System (ROS) based control system would not run comfortably on the multicore CPU on our custom robot platform. The process of profiling the ROS control program and selecting appropriate modules for porting to run on a GPU is described. A GPU-targeting compiler, Bacon, is used to speed up development and help optimize the ported modules. The impact of the ported modules on overall performance is discussed. We conclude that GPU optimization can free a significant amount of CPU resources with minimal effort for expensive user-written code, but that replacing heavily-optimized library functions is more difficult, and a much less efficient use of time.

Image-based tracking and sensor resource management for UAVs in an urban environment

NASA Astrophysics Data System (ADS)

Samant, Ashwin; Chang, K. C.

2010-04-01

Coordination and deployment of multiple unmanned air vehicles (UAVs) requires a lot of human resources in order to carry out a successful mission. The complexity of such a surveillance mission is significantly increased in the case of an urban environment where targets can easily escape from the UAV's field of view (FOV) due to intervening building and line-of-sight obstruction. In the proposed methodology, we focus on the control and coordination of multiple UAVs having gimbaled video sensor onboard for tracking multiple targets in an urban environment. We developed optimal path planning algorithms with emphasis on dynamic target prioritizations and persistent target updates. The command center is responsible for target prioritization and autonomous control of multiple UAVs, enabling a single operator to monitor and control a team of UAVs from a remote location. The results are obtained using extensive 3D simulations in Google Earth using Tangent plus Lyapunov vector field guidance for target tracking.

InPRO: Automated Indoor Construction Progress Monitoring Using Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Hamledari, Hesam

In this research, an envisioned automated intelligent robotic solution for automated indoor data collection and inspection that employs a series of unmanned aerial vehicles (UAV), entitled "InPRO", is presented. InPRO consists of four stages, namely: 1) automated path planning; 2) autonomous UAV-based indoor inspection; 3) automated computer vision-based assessment of progress; and, 4) automated updating of 4D building information models (BIM). The works presented in this thesis address the third stage of InPRO. A series of computer vision-based methods that automate the assessment of construction progress using images captured at indoor sites are introduced. The proposed methods employ computer vision and machine learning techniques to detect the components of under-construction indoor partitions. In particular, framing (studs), insulation, electrical outlets, and different states of drywall sheets (installing, plastering, and painting) are automatically detected using digital images. High accuracy rates, real-time performance, and operation without a priori information are indicators of the methods' promising performance.

Spline Trajectory Algorithm Development: Bezier Curve Control Point Generation for UAVs

NASA Technical Reports Server (NTRS)

Howell, Lauren R.; Allen, B. Danette

2016-01-01

A greater need for sophisticated autonomous piloting systems has risen in direct correlation with the ubiquity of Unmanned Aerial Vehicle (UAV) technology. Whether surveying unknown or unexplored areas of the world, collecting scientific data from regions in which humans are typically incapable of entering, locating lost or wanted persons, or delivering emergency supplies, an unmanned vehicle moving in close proximity to people and other vehicles, should fly smoothly and predictably. The mathematical application of spline interpolation can play an important role in autopilots' on-board trajectory planning. Spline interpolation allows for the connection of Three-Dimensional Euclidean Space coordinates through a continuous set of smooth curves. This paper explores the motivation, application, and methodology used to compute the spline control points, which shape the curves in such a way that the autopilot trajectory is able to meet vehicle-dynamics limitations. The spline algorithms developed used to generate these curves supply autopilots with the information necessary to compute vehicle paths through a set of coordinate waypoints.

Three-Dimensional Path Planning for Uninhabited Combat Aerial Vehicle Based on Predator-Prey Pigeon-Inspired Optimization in Dynamic Environment.

PubMed

Zhang, Bo; Duan, Haibin

2017-01-01

Three-dimension path planning of uninhabited combat aerial vehicle (UCAV) is a complicated optimal problem, which mainly focused on optimizing the flight route considering the different types of constrains under complex combating environment. A novel predator-prey pigeon-inspired optimization (PPPIO) is proposed to solve the UCAV three-dimension path planning problem in dynamic environment. Pigeon-inspired optimization (PIO) is a new bio-inspired optimization algorithm. In this algorithm, map and compass operator model and landmark operator model are used to search the best result of a function. The prey-predator concept is adopted to improve global best properties and enhance the convergence speed. The characteristics of the optimal path are presented in the form of a cost function. The comparative simulation results show that our proposed PPPIO algorithm is more efficient than the basic PIO, particle swarm optimization (PSO), and different evolution (DE) in solving UCAV three-dimensional path planning problems.

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

Hybrid Learning: An Effective Resource in University Education?

ERIC Educational Resources Information Center

Alducin-Ochoa, Juan Manuel; Vázquez-Martínez, Ana Isabel

2016-01-01

The organisation of university education in Europe is undergoing profound changes as a consequence of the establishment of the European Higher Education Area (EHEA). This transformation entails methodological changes that are focused on student work. The student is now considered to be an autonomous individual who is able to choose a path of study…

A nonlinear strategy for sensor based vehicle path control

NASA Technical Reports Server (NTRS)

Mayr, R.

1994-01-01

A method of transverse control which makes use of nonlinear formulations is presented. The strategy is utilized to stabilize a vehicle. The vehicle is autonomously guided and takes its control inputs from an optical sensing system. Additionally, the velocity of the vehicle is dictated by a longitudinal controller, which is also discussed.

Autonomous Laser-Powered Vehicle

NASA Technical Reports Server (NTRS)

Stone, William C. (Inventor); Hogan, Bartholomew P. (Inventor)

2017-01-01

An autonomous laser-powered vehicle designed to autonomously penetrate through ice caps of substantial (e.g., kilometers) thickness by melting a path ahead of the vehicle as it descends. A high powered laser beam is transmitted to the vehicle via an onboard bare fiber spooler. After the beam enters through the dispersion optics, the beam expands into a cavity. A radiation shield limits backscatter radiation from heating the optics. The expanded beam enters the heat exchanger and is reflected by a dispersion mirror. Forward-facing beveled circular grooves absorb the reflected radiant energy preventing the energy from being reflected back towards the optics. Microchannels along the inner circumference of the beam dump heat exchanger maximize heat transfer. Sufficient amount of fiber is wound on the fiber spooler to permit not only a descent but also to permit a sample return mission by inverting the vehicle and melting its way back to the surface.

Stereo Image Ranging For An Autonomous Robot Vision System

NASA Astrophysics Data System (ADS)

Holten, James R.; Rogers, Steven K.; Kabrisky, Matthew; Cross, Steven

1985-12-01

The principles of stereo vision for three-dimensional data acquisition are well-known and can be applied to the problem of an autonomous robot vehicle. Coincidental points in the two images are located and then the location of that point in a three-dimensional space can be calculated using the offset of the points and knowledge of the camera positions and geometry. This research investigates the application of artificial intelligence knowledge representation techniques as a means to apply heuristics to relieve the computational intensity of the low level image processing tasks. Specifically a new technique for image feature extraction is presented. This technique, the Queen Victoria Algorithm, uses formal language productions to process the image and characterize its features. These characterized features are then used for stereo image feature registration to obtain the required ranging information. The results can be used by an autonomous robot vision system for environmental modeling and path finding.

HERMIES-3: A step toward autonomous mobility, manipulation, and perception

NASA Technical Reports Server (NTRS)

Weisbin, C. R.; Burks, B. L.; Einstein, J. R.; Feezell, R. R.; Manges, W. W.; Thompson, D. H.

1989-01-01

HERMIES-III is an autonomous robot comprised of a seven degree-of-freedom (DOF) manipulator designed for human scale tasks, a laser range finder, a sonar array, an omni-directional wheel-driven chassis, multiple cameras, and a dual computer system containing a 16-node hypercube expandable to 128 nodes. The current experimental program involves performance of human-scale tasks (e.g., valve manipulation, use of tools), integration of a dexterous manipulator and platform motion in geometrically complex environments, and effective use of multiple cooperating robots (HERMIES-IIB and HERMIES-III). The environment in which the robots operate has been designed to include multiple valves, pipes, meters, obstacles on the floor, valves occluded from view, and multiple paths of differing navigation complexity. The ongoing research program supports the development of autonomous capability for HERMIES-IIB and III to perform complex navigation and manipulation under time constraints, while dealing with imprecise sensory information.

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR

PubMed Central

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-01-01

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner. PMID:29439447

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR.

PubMed

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-02-11

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.

An Application of Self-Organizing Map for Multirobot Multigoal Path Planning with Minmax Objective.

PubMed

Faigl, Jan

2016-01-01

In this paper, Self-Organizing Map (SOM) for the Multiple Traveling Salesman Problem (MTSP) with minmax objective is applied to the robotic problem of multigoal path planning in the polygonal domain. The main difficulty of such SOM deployment is determination of collision-free paths among obstacles that is required to evaluate the neuron-city distances in the winner selection phase of unsupervised learning. Moreover, a collision-free path is also needed in the adaptation phase, where neurons are adapted towards the presented input signal (city) to the network. Simple approximations of the shortest path are utilized to address this issue and solve the robotic MTSP by SOM. Suitability of the proposed approximations is verified in the context of cooperative inspection, where cities represent sensing locations that guarantee to "see" the whole robots' workspace. The inspection task formulated as the MTSP-Minmax is solved by the proposed SOM approach and compared with the combinatorial heuristic GENIUS. The results indicate that the proposed approach provides competitive results to GENIUS and support applicability of SOM for robotic multigoal path planning with a group of cooperating mobile robots. The proposed combination of approximate shortest paths with unsupervised learning opens further applications of SOM in the field of robotic planning.

An Application of Self-Organizing Map for Multirobot Multigoal Path Planning with Minmax Objective

PubMed Central

Faigl, Jan

2016-01-01

In this paper, Self-Organizing Map (SOM) for the Multiple Traveling Salesman Problem (MTSP) with minmax objective is applied to the robotic problem of multigoal path planning in the polygonal domain. The main difficulty of such SOM deployment is determination of collision-free paths among obstacles that is required to evaluate the neuron-city distances in the winner selection phase of unsupervised learning. Moreover, a collision-free path is also needed in the adaptation phase, where neurons are adapted towards the presented input signal (city) to the network. Simple approximations of the shortest path are utilized to address this issue and solve the robotic MTSP by SOM. Suitability of the proposed approximations is verified in the context of cooperative inspection, where cities represent sensing locations that guarantee to “see” the whole robots' workspace. The inspection task formulated as the MTSP-Minmax is solved by the proposed SOM approach and compared with the combinatorial heuristic GENIUS. The results indicate that the proposed approach provides competitive results to GENIUS and support applicability of SOM for robotic multigoal path planning with a group of cooperating mobile robots. The proposed combination of approximate shortest paths with unsupervised learning opens further applications of SOM in the field of robotic planning. PMID:27340395

Control technique for planetary rover

NASA Technical Reports Server (NTRS)

Nakatani, Ichiro; Kubota, Takashi; Adachi, Tadashi; Saitou, Hiroaki; Okamoto, Sinya

1994-01-01

Beginning next century, several schemes for sending a planetary rover to the moon or Mars are being planned. As part of the development program, autonomous navigation technology is being studied to allow the rover the ability to move autonomously over a long range of unknown planetary surface. In the previous study, we ran the autonomous navigation experiment on an outdoor test terrain by using a rover test-bed that was controlled by a conventional sense-plan-act method. In some cases during the experiment, a problem occurred with the rover moving into untraversable areas. To improve this situation, a new control technique has been developed that gives the rover the ability of reacting to the outputs of the proximity sensors, a reaction behavior if you will. We have developed a new rover test-bed system on which an autonomous navigation experiment was performed using the newly developed control technique. In this outdoor experiment, the new control technique effectively produced the control command for the rover to avoid obstacles and be guided to the goal point safely.

Plan demographics, participants' saving behavior, and target-date fund investments.

PubMed

Park, Youngkyun

2009-05-01

This analysis explores (1) whether plan demographic characteristics would affect individual participant contribution rates and target-date fund investments and (2) equity glide paths for participants in relation to plan demographics by considering target replacement income and its success rate. PLAN DEMOGRAPHIC CHARACTERISTICS IN PARTICIPANT CONTRIBUTION RATES: This study finds empirical evidence that 401(k) plan participants' contribution rates differ by plan demographics based on participants' income and/or tenure. In particular, participants in 401(k) plans dominated by those with low income and short tenure tend to contribute less than those in plans dominated by participants with high income and long tenure. Future research will explore how participant contribution behavior may also be influenced by incentives provided by employers through matching formulae. PLAN DEMOGRAPHIC CHARACTERISTICS IN TARGET-DATE FUND INVESTMENTS: The study also finds empirical evidence that participants' investments in target-date funds with different equity allocations differ by plan demographics based on participants' income and/or tenure. In particular, target-date fund users with 90 percent or more of their account balances in target-date funds who are in 401(k) plans dominated by low-income and short-tenure participants tend to hold target-date funds with lower equity allocations, compared with their counterparts in plans dominated by high-income and long-tenure participants. Future research will focus on the extent to which these characteristics might influence the selection of target-date funds by plan sponsors. EQUITY GLIDE PATHS: Several stylized equity glide paths as well as alternative asset allocations are compared for participants at various starting ages to demonstrate the interaction between plan demographics and equity glide paths/asset allocations in terms of success rates in meeting various replacement income targets. The equity glide path/asset allocation providing the highest success rate at a particular replacement rate target will vary with the assumed starting date of the participant (see Figure 17). Given the highly stylized nature of the simulations in this Issue Brief it is important to note that the results are not intended to provide a single equity glide path solution in relation to plan demographics. Instead, they serve as a framework to be considered when plan sponsors make a selection concerning which target-date funds to include in their plan. IMPORTANCE OF PARTICIPANT CONTRIBUTION RATES: This analysis finds that although target-date funds with different equity glide paths affect the retirement income replacement success rate, participant contribution rates corresponding to different plan demographic characteristics have a stronger impact. AUTO FEATURES OF THE PPA: This Issue Brief provides a stylized study using observed contribution rates as of the 2007 plan year. However, with the passage of the Pension Protection Act of 2006 and its likely impact on plan design in the future (increased utilization of automatic enrollment and automatic contribution escalations), it is likely that contribution rates among the participants may become more homogenous. In such a scenario, it may be more likely that a single equity glide path would meet a wide range of demographic profiles.

Prediction of intention to continue sport in athlete students: A self-determination theory approach

PubMed Central

Keshtidar, Mohammad; Behzadnia, Behzad

2017-01-01

Grounded on the self-determination theory (Deci & Ryan, 1985, 2000) and achievement goals theory (Ames, 1992; Nicholls, 1989), this study via structural equation modelling, predicted intention to continue in sport from goal orientations and motivations among athlete students. 268 athlete students (Mage = 21.9), in Iranian universities completed a multi-section questionnaire tapping the targeted variables. Structural equation modelling (SEM) offered an overall support for the proposed model. The results showed that there are positive relationships between intention to continue in sport and both orientations as well as both motivations. A task-involving orientation emerged as a positive predictor of the autonomous motivation, while an ego-involving orientation was a positive predictor controlled motivation as well as autonomous motivation. The results also support positive paths between autonomous motivation and future intention to participate in sport. Autonomous motivation also was a positive mediator in relationship between task orientation and the intentions. As a conclusion, the implications of the task-involving orientation are discussabled in the light of its importance for the quality and potential maintenance of sport involvement among athlete students. PMID:28178308

Prediction of intention to continue sport in athlete students: A self-determination theory approach.

PubMed

Keshtidar, Mohammad; Behzadnia, Behzad

2017-01-01

Grounded on the self-determination theory (Deci & Ryan, 1985, 2000) and achievement goals theory (Ames, 1992; Nicholls, 1989), this study via structural equation modelling, predicted intention to continue in sport from goal orientations and motivations among athlete students. 268 athlete students (Mage = 21.9), in Iranian universities completed a multi-section questionnaire tapping the targeted variables. Structural equation modelling (SEM) offered an overall support for the proposed model. The results showed that there are positive relationships between intention to continue in sport and both orientations as well as both motivations. A task-involving orientation emerged as a positive predictor of the autonomous motivation, while an ego-involving orientation was a positive predictor controlled motivation as well as autonomous motivation. The results also support positive paths between autonomous motivation and future intention to participate in sport. Autonomous motivation also was a positive mediator in relationship between task orientation and the intentions. As a conclusion, the implications of the task-involving orientation are discussabled in the light of its importance for the quality and potential maintenance of sport involvement among athlete students.

Enriching the hierarchical model of achievement motivation: autonomous and controlling reasons underlying achievement goals.

PubMed

Michou, Aikaterini; Vansteenkiste, Maarten; Mouratidis, Athanasios; Lens, Willy

2014-12-01

The hierarchical model of achievement motivation presumes that achievement goals channel the achievement motives of need for achievement and fear of failure towards motivational outcomes. Yet, less is known whether autonomous and controlling reasons underlying the pursuit of achievement goals can serve as additional pathways between achievement motives and outcomes. We tested whether mastery approach, performance approach, and performance avoidance goals and their underlying autonomous and controlling reasons would jointly explain the relation between achievement motives (i.e., fear of failure and need for achievement) and learning strategies (Study 1). Additionally, we examined whether the autonomous and controlling reasons underlying learners' dominant achievement goal would account for the link between achievement motives and the educational outcomes of learning strategies and cheating (Study 2). Six hundred and six Greek adolescent students (Mage = 15.05, SD = 1.43) and 435 university students (Mage M = 20.51, SD = 2.80) participated in studies 1 and 2, respectively. In both studies, a correlational design was used and the hypotheses were tested via path modelling. Autonomous and controlling reasons underlying the pursuit of achievement goals mediated, respectively, the relation of need for achievement and fear of failure to aspects of learning outcomes. Autonomous and controlling reasons underlying achievement goals could further explain learners' functioning in achievement settings. © 2014 The British Psychological Society.

Development of an autonomous treatment planning strategy for radiation therapy with effective use of population-based prior data.

PubMed

Wang, Huan; Dong, Peng; Liu, Hongcheng; Xing, Lei

2017-02-01

Current treatment planning remains a costly and labor intensive procedure and requires multiple trial-and-error adjustments of system parameters such as the weighting factors and prescriptions. The purpose of this work is to develop an autonomous treatment planning strategy with effective use of prior knowledge and in a clinically realistic treatment planning platform to facilitate radiation therapy workflow. Our technique consists of three major components: (i) a clinical treatment planning system (TPS); (ii) a formulation of decision-function constructed using an assemble of prior treatment plans; (iii) a plan evaluator or decision-function and an outer-loop optimization independent of the clinical TPS to assess the TPS-generated plan and to drive the search toward a solution optimizing the decision-function. Microsoft (MS) Visual Studio Coded UI is applied to record some common planner-TPS interactions as subroutines for querying and interacting with the TPS. These subroutines are called back in the outer-loop optimization program to navigate the plan selection process through the solution space iteratively. The utility of the approach is demonstrated by using clinical prostate and head-and-neck cases. An autonomous treatment planning technique with effective use of an assemble of prior treatment plans is developed to automatically maneuver the clinical treatment planning process in the platform of a commercial TPS. The process mimics the decision-making process of a human planner and provides a clinically sensible treatment plan automatically, thus reducing/eliminating the tedious manual trial-and-errors of treatment planning. It is found that the prostate and head-and-neck treatment plans generated using the approach compare favorably with that used for the patients' actual treatments. Clinical inverse treatment planning process can be automated effectively with the guidance of an assemble of prior treatment plans. The approach has the potential to significantly improve the radiation therapy workflow. © 2016 American Association of Physicists in Medicine.

Path planning and Ground Control Station simulator for UAV

NASA Astrophysics Data System (ADS)

Ajami, A.; Balmat, J.; Gauthier, J.-P.; Maillot, T.

In this paper we present a Universal and Interoperable Ground Control Station (UIGCS) simulator for fixed and rotary wing Unmanned Aerial Vehicles (UAVs), and all types of payloads. One of the major constraints is to operate and manage multiple legacy and future UAVs, taking into account the compliance with NATO Combined/Joint Services Operational Environment (STANAG 4586). Another purpose of the station is to assign the UAV a certain degree of autonomy, via autonomous planification/replanification strategies. The paper is organized as follows. In Section 2, we describe the non-linear models of the fixed and rotary wing UAVs that we use in the simulator. In Section 3, we describe the simulator architecture, which is based upon interacting modules programmed independently. This simulator is linked with an open source flight simulator, to simulate the video flow and the moving target in 3D. To conclude this part, we tackle briefly the problem of the Matlab/Simulink software connection (used to model the UAV's dynamic) with the simulation of the virtual environment. Section 5 deals with the control module of a flight path of the UAV. The control system is divided into four distinct hierarchical layers: flight path, navigation controller, autopilot and flight control surfaces controller. In the Section 6, we focus on the trajectory planification/replanification question for fixed wing UAV. Indeed, one of the goals of this work is to increase the autonomy of the UAV. We propose two types of algorithms, based upon 1) the methods of the tangent and 2) an original Lyapunov-type method. These algorithms allow either to join a fixed pattern or to track a moving target. Finally, Section 7 presents simulation results obtained on our simulator, concerning a rather complicated scenario of mission.

The process by which perceived autonomy support predicts motivation, intention, and behavior for seasonal influenza prevention in Hong Kong older adults.

PubMed

Chung, Pak-Kwong; Zhang, Chun-Qing; Liu, Jing-Dong; Chan, Derwin King-Chung; Si, Gangyan; Hagger, Martin S

2017-07-28

This study examined the effectiveness of a theoretical framework that integrates self-determination theory (SDT) and the theory of planned behavior (TPB) in explaining the use of facemasks to prevent seasonal influenza among Hong Kong older adults. Data were collected at two time points in the winter in Hong Kong, during which influenza is most prevalent. At Time 1, older adults (N = 141) completed self-report measures of SDT (perceived autonomy support from senior center staff, autonomous motivation for influenza prevention) and TPB (attitude, subjective norm, perceived behavioral control, and intention for influenza prevention) constructs with respect to facemask used to prevent infection. Two weeks later, at Time 2, participants' acceptance of a facemask to prevent influenza in the presence of an experimenter with flu-like symptoms was recorded. Path analysis found that perceived autonomy support of senior center staff was positively and significantly linked to autonomous motivation for facemask use, which, in turn, was positively related to intentions to wear facemasks through the mediation of attitude, subjective norm, and perceived behavioral control. However, the effect of intention on facemask use was not significant. Results generally support the proposed framework and the findings of previous studies with respect to intention, but the non-significant intention-behavior relationship may warrant future research to examine the reasons for older adults not to wear facemasks to prevent seasonal influenza despite having positive intentions to do so.

Autonomous Mars ascent and orbit rendezvous for earth return missions

NASA Technical Reports Server (NTRS)

Edwards, H. C.; Balmanno, W. F.; Cruz, Manuel I.; Ilgen, Marc R.

1991-01-01

The details of tha assessment of autonomous Mars ascent and orbit rendezvous for earth return missions are presented. Analyses addressing navigation system assessments, trajectory planning, targeting approaches, flight control guidance strategies, and performance sensitivities are included. Tradeoffs in the analysis and design process are discussed.

A Comparison of Risk Sensitive Path Planning Methods for Aircraft Emergency Landing

NASA Technical Reports Server (NTRS)

Meuleau, Nicolas; Plaunt, Christian; Smith, David E.; Smith, Tristan

2009-01-01

Determining the best site to land a damaged aircraft presents some interesting challenges for standard path planning techniques. There are multiple possible locations to consider, the space is 3-dimensional with dynamics, the criteria for a good path is determined by overall risk rather than distance or time, and optimization really matters, since an improved path corresponds to greater expected survival rate. We have investigated a number of different path planning methods for solving this problem, including cell decomposition, visibility graphs, probabilistic road maps (PRMs), and local search techniques. In their pure form, none of these techniques have proven to be entirely satisfactory - some are too slow or unpredictable, some produce highly non-optimal paths or do not find certain types of paths, and some do not cope well with the dynamic constraints when controllability is limited. In the end, we are converging towards a hybrid technique that involves seeding a roadmap with a layered visibility graph, using PRM to extend that roadmap, and using local search to further optimize the resulting paths. We describe the techniques we have investigated, report on our experiments with these techniques, and discuss when and why various techniques were unsatisfactory.

FTS evolution

NASA Technical Reports Server (NTRS)

Provost, David E.

1990-01-01

Viewgraphs on flight telerobotic servicer evolution are presented. Topics covered include: paths for FTS evolution; frequently performed actions; primary task states; EPS radiator panel installation; generic task definitions; path planning; non-contact alignment; contact planning and control; and human operator interface.

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.

Development of preoperative planning software for transforaminal endoscopic surgery and the guidance for clinical applications.

PubMed

Chen, Xiaojun; Cheng, Jun; Gu, Xin; Sun, Yi; Politis, Constantinus

2016-04-01

Preoperative planning is of great importance for transforaminal endoscopic techniques applied in percutaneous endoscopic lumbar discectomy. In this study, a modular preoperative planning software for transforaminal endoscopic surgery was developed and demonstrated. The path searching method is based on collision detection, and the oriented bounding box was constructed for the anatomical models. Then, image reformatting algorithms were developed for multiplanar reconstruction which provides detailed anatomical information surrounding the virtual planned path. Finally, multithread technique was implemented to realize the steady-state condition of the software. A preoperative planning software for transforaminal endoscopic surgery (TE-Guider) was developed; seven cases of patients with symptomatic lumbar disc herniations were planned preoperatively using TE-Guider. The distances to the midlines and the direction of the optimal paths were exported, and each result was in line with the empirical value. TE-Guider provides an efficient and cost-effective way to search the ideal path and entry point for the puncture. However, more clinical cases will be conducted to demonstrate its feasibility and reliability.

Scalable autonomous operations of unmanned assets

NASA Astrophysics Data System (ADS)

Jung, Sunghun

Although there have been great theoretical advances in the region of Unmanned Aerial Vehicle (UAV) autonomy, applications of those theories into real world are still hesitated due to unexpected disturbances. Most of UAVs which are currently used are mainly, strictly speaking, Remotely Piloted Vehicles (RPA) since most works related with the flight control, sensor data analysis, and decision makings are done by human operators. To increase the degree of autonomy, many researches are focused on developing Unmanned Autonomous Aerial Vehicle (UAAV) which can takeoff, fly to the interested area by avoiding unexpected obstacles, perform various missions with decision makings, come back to the base station, and land on by itself without any human operators. To improve the performance of UAVs, the accuracies of position and orientation sensors are enhanced by integrating a Unmanned Ground Vehicle (UGV) or a solar compass to a UAV; Position sensor accuracy of a GPS sensor on a UAV is improved by referencing the position of a UGV which is calculated by using three GPS sensors and Weighted Centroid Localization (WCL) method; Orientation sensor accuracy is improved as well by using Three Pixel Theorem (TPT) and integrating a solar compass which composed of nine light sensors to a magnetic compass. Also, improved health management of a UAV is fulfilled by developing a wireless autonomous charging station which uses four pairs of transmitter and receiver magnetic loops with four robotic arms. For the software aspect, I also analyze the error propagation of the proposed mission planning hierarchy to achieve the safest size of the buffer zone. In addition, among seven future research areas regarding UAV, this paper mainly focuses on developing algorithms of path planning, trajectory generation, and cooperative tactics for the operations of multiple UAVs using GA based multiple Traveling Salesman Problem (mTSP) which is solved by dividing into m number of Traveling Salesman Problems (TSP) using two region division methods such as Uniform Region Division (URD) and K-means Voronoi Region Division (KVRD). The topic of the maximum fuel efficiency is also dealt to ensure the minimum amount fuel consumption to perform surveillance on a given region using multiple UAVs. Last but not least, I present an application example of cattle roundup with two UAVs and two animals using the feedback linearization controller.

Visually based path-planning by Japanese monkeys.

PubMed

Mushiake, H; Saito, N; Sakamoto, K; Sato, Y; Tanji, J

2001-03-01

To construct an animal model of strategy formation, we designed a maze path-finding task. First, we asked monkeys to capture a goal in the maze by moving a cursor on the screen. Cursor movement was linked to movements of each wrist. When the animals learned the association between cursor movement and wrist movement, we established a start and a goal in the maze, and asked them to find a path between them. We found that the animals took the shortest pathway, rather than approaching the goal randomly. We further found that the animals adopted a strategy of selecting a fixed intermediate point in the visually presented maze to select one of the shortest pathways, suggesting a visually based path planning. To examine their capacity to use that strategy flexibly, we transformed the task by blocking pathways in the maze, providing a problem to solve. The animals then developed a strategy of solving the problem by planning a novel shortest path from the start to the goal and rerouting the path to bypass the obstacle.

Model-Unified Planning and Execution for Distributed Autonomous System Control

NASA Technical Reports Server (NTRS)

Aschwanden, Pascal; Baskaran, Vijay; Bernardini, Sara; Fry, Chuck; Moreno, Maria; Muscettola, Nicola; Plaunt, Chris; Rijsman, David; Tompkins, Paul

2006-01-01

The Intelligent Distributed Execution Architecture (IDEA) is a real-time architecture that exploits artificial intelligence planning as the core reasoning engine for interacting autonomous agents. Rather than enforcing separate deliberation and execution layers, IDEA unifies them under a single planning technology. Deliberative and reactive planners reason about and act according to a single representation of the past, present and future domain state. The domain state behaves the rules dictated by a declarative model of the subsystem to be controlled, internal processes of the IDEA controller, and interactions with other agents. We present IDEA concepts - modeling, the IDEA core architecture, the unification of deliberation and reaction under planning - and illustrate its use in a simple example. Finally, we present several real-world applications of IDEA, and compare IDEA to other high-level control approaches.

Using Iterative Repair to Increase the Responsiveness of Planning and Scheduling for Autonomous Spacecraft

NASA Technical Reports Server (NTRS)

Chien, Steve; Knight, Russell; Stechert, Andre; Sherwood, Rob; Rabideau, Gregg

1998-01-01

An autonomous spacecraft must balance long-term and short-term considerations. It must perform purposeful activities that ensure long-term science and engineering goals are achieved and ensure that it maintains positive resource margins. This requires planning in advance to avoid a series of shortsighted decisions that can lead to failure, However, it must also respond in a timely fashion to a somewhat dynamic and unpredictable environment. Thus, spacecraft plans must often be modified due to fortuitous events such as early completion of observations and setbacks such as failure to acquire a guidestar for a science observation. This paper describes the use of iterative repair to support continuous modification and updating of a current working plan in light of changing operating context.

Intelligent robots for planetary exploration and construction

NASA Technical Reports Server (NTRS)

Albus, James S.

1992-01-01

Robots capable of practical applications in planetary exploration and construction will require realtime sensory-interactive goal-directed control systems. A reference model architecture based on the NIST Real-time Control System (RCS) for real-time intelligent control systems is suggested. RCS partitions the control problem into four basic elements: behavior generation (or task decomposition), world modeling, sensory processing, and value judgment. It clusters these elements into computational nodes that have responsibility for specific subsystems, and arranges these nodes in hierarchical layers such that each layer has characteristic functionality and timing. Planetary exploration robots should have mobility systems that can safely maneuver over rough surfaces at high speeds. Walking machines and wheeled vehicles with dynamic suspensions are candidates. The technology of sensing and sensory processing has progressed to the point where real-time autonomous path planning and obstacle avoidance behavior is feasible. Map-based navigation systems will support long-range mobility goals and plans. Planetary construction robots must have high strength-to-weight ratios for lifting and positioning tools and materials in six degrees-of-freedom over large working volumes. A new generation of cable-suspended Stewart platform devices and inflatable structures are suggested for lifting and positioning materials and structures, as well as for excavation, grading, and manipulating a variety of tools and construction machinery.

Fusing terrain and goals: agent control in urban environments

NASA Astrophysics Data System (ADS)

Kaptan, Varol; Gelenbe, Erol

2006-04-01

The changing face of contemporary military conflicts has forced a major shift of focus in tactical planning and evaluation from the classical Cold War battlefield to an asymmetric guerrilla-type warfare in densely populated urban areas. The new arena of conflict presents unique operational difficulties due to factors like complex mobility restrictions and the necessity to preserve civilian lives and infrastructure. In this paper we present a novel method for autonomous agent control in an urban environment. Our approach is based on fusing terrain information and agent goals for the purpose of transforming the problem of navigation in a complex environment with many obstacles into the easier problem of navigation in a virtual obstacle-free space. The main advantage of our approach is its ability to act as an adapter layer for a number of efficient agent control techniques which normally show poor performance when applied to an environment with many complex obstacles. Because of the very low computational and space complexity at runtime, our method is also particularly well suited for simulation or control of a huge number of agents (military as well as civilian) in a complex urban environment where traditional path-planning may be too expensive or where a just-in-time decision with hard real-time constraints is required.

An Algorithm for Autonomous Formation Obstacle Avoidance

NASA Astrophysics Data System (ADS)

Cruz, Yunior I.

The level of human interaction with Unmanned Aerial Systems varies greatly from remotely piloted aircraft to fully autonomous systems. In the latter end of the spectrum, the challenge lies in designing effective algorithms to dictate the behavior of the autonomous agents. A swarm of autonomous Unmanned Aerial Vehicles requires collision avoidance and formation flight algorithms to negotiate environmental challenges it may encounter during the execution of its mission, which may include obstacles and chokepoints. In this work, a simple algorithm is developed to allow a formation of autonomous vehicles to perform point to point navigation while avoiding obstacles and navigating through chokepoints. Emphasis is placed on maintaining formation structures. Rather than breaking formation and individually navigating around the obstacle or through the chokepoint, vehicles are required to assemble into appropriately sized/shaped sub-formations, bifurcate around the obstacle or negotiate the chokepoint, and reassemble into the original formation at the far side of the obstruction. The algorithm receives vehicle and environmental properties as inputs and outputs trajectories for each vehicle from start to the desired ending location. Simulation results show that the algorithm safely routes all vehicles past the obstruction while adhering to the aforementioned requirements. The formation adapts and successfully negotiates the obstacles and chokepoints in its path while maintaining proper vehicle separation.

Trait Mindfulness Predicts Attentional and Autonomic Regulation of Alcohol Cue-Reactivity

PubMed Central

Garland, Eric L.

2013-01-01

Background The trait of mindfulness varies among meditation-naïve individuals and is associated with attentional and autonomic regulation, two neurocognitive functions that become impaired in addiction. It was hypothesized that alcohol dependent inpatients with comparatively high levels of trait mindfulness would exhibit significant autonomic recovery from stress-primed alcohol cues mediated by greater attentional disengagement from such cues. Methods 58 alcohol dependent inpatients participated in affect-modulated psychophysiological cue-reactivity protocol and a spatial cueing task designed to assess alcohol attentional bias (AB). Associations between trait mindfulness, alcohol AB, and an index of autonomic activity, high-frequency heart rate variability (HFHRV), were examined via multivariate path analysis. Results Higher trait mindfulness was significantly associated with less difficulty resisting the urge to drink and greater HFHRV recovery from stress-primed alcohol cues. After statistically controlling for the correlation of mindfulness and perceived difficulty resisting drinking urges, the association between mindfulness and HFHRV recovery was partially mediated by attentional disengagement from alcohol cues (model R2 = .30). Discussion Alcohol dependent inpatients higher in mindfulness are better able to disengage attention from alcohol cues, which in turn predicts the degree of HFHRV recovery from such cues. Trait mindfulness may index cognitive control over appetitive responses reflected in superior attentional and autonomic regulation of stress-primed alcohol cue-reactivity. PMID:23976814

Global Positioning System (GPS) Receiver Autonomous Integrity Monitoring (RAIM) web service to support Area Navigation (RNAV) flight planning

DOT National Transportation Integrated Search

2008-01-28

The Volpe Center designed, implemented, and deployed a Global Positioning System (GPS) Receiver Autonomous Integrity Monitoring (RAIM) prediction system in the mid 1990s to support both Air Force and Federal Aviation Administration (FAA) use of TSO C...

A science-based executive for autonomous planetary vehicles

NASA Technical Reports Server (NTRS)

Peters, S.

2001-01-01

If requests for scientific observations, rather than specific plans, are uplinked to an autonomous execution system on the vehicle, it would be able to adjust its execution based upon actual performance. Such a science-based executive control system had been developed and demonstrated for the Rocky7 research rover.

Spatial Coverage Planning for a Planetary Rover

NASA Technical Reports Server (NTRS)

Gaines, Daniel M.; Estlin, Tara; Chouinard, Caroline

2008-01-01

We are developing onboard planning and execution technologies to support the exploration and characterization of geological features by autonomous rovers. In order to generate high quality mission plans, an autonomous rover must reason about the relative importance of the observations it can perform. In this paper we look at the scientific criteria of selecting observations that improve the quality of the area covered by samples. Our approach makes use of a priori information, if available, and allows scientists to mark sub-regions of the area with relative priorities for exploration. We use an efficient algorithm for prioritizing observations based on spatial coverage that allows the system to update observation rankings as new information is gained during execution.

Autonomous Power System intelligent diagnosis and control

NASA Technical Reports Server (NTRS)

Ringer, Mark J.; Quinn, Todd M.; Merolla, Anthony

1991-01-01

The Autonomous Power System (APS) project at NASA Lewis Research Center is designed to demonstrate the abilities of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution hardware. Knowledge-based software provides a robust method of control for highly complex space-based power systems that conventional methods do not allow. The project consists of three elements: the Autonomous Power Expert System (APEX) for fault diagnosis and control, the Autonomous Intelligent Power Scheduler (AIPS) to determine system configuration, and power hardware (Brassboard) to simulate a space based power system. The operation of the Autonomous Power System as a whole is described and the responsibilities of the three elements - APEX, AIPS, and Brassboard - are characterized. A discussion of the methodologies used in each element is provided. Future plans are discussed for the growth of the Autonomous Power System.

Autonomous power system intelligent diagnosis and control

NASA Technical Reports Server (NTRS)

Ringer, Mark J.; Quinn, Todd M.; Merolla, Anthony

1991-01-01

The Autonomous Power System (APS) project at NASA Lewis Research Center is designed to demonstrate the abilities of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution hardware. Knowledge-based software provides a robust method of control for highly complex space-based power systems that conventional methods do not allow. The project consists of three elements: the Autonomous Power Expert System (APEX) for fault diagnosis and control, the Autonomous Intelligent Power Scheduler (AIPS) to determine system configuration, and power hardware (Brassboard) to simulate a space based power system. The operation of the Autonomous Power System as a whole is described and the responsibilities of the three elements - APEX, AIPS, and Brassboard - are characterized. A discussion of the methodologies used in each element is provided. Future plans are discussed for the growth of the Autonomous Power System.

Thermal Stability of Al2O3/Silicone Composites as High-Temperature Encapsulants

NASA Astrophysics Data System (ADS)

Yao, Yiying

Underwater gliders are robust and long endurance ocean sampling platforms that are increasingly being deployed in coastal regions. This new environment is characterized by shallow waters and significant currents that can challenge the mobility of these efficient (but traditionally slow moving) vehicles. This dissertation aims to improve the performance of shallow water underwater gliders through path planning. The path planning problem is formulated for a dynamic particle (or "kinematic car") model. The objective is to identify the path which satisfies specified boundary conditions and minimizes a particular cost. Several cost functions are considered. The problem is addressed using optimal control theory. The length scales of interest for path planning are within a few turn radii. First, an approach is developed for planning minimum-time paths, for a fixed speed glider, that are sub-optimal but are guaranteed to be feasible in the presence of unknown time-varying currents. Next the minimum-time problem for a glider with speed controls, that may vary between the stall speed and the maximum speed, is solved. Last, optimal paths that minimize change in depth (equivalently, maximize range) are investigated. Recognizing that path planning alone cannot overcome all of the challenges associated with significant currents and shallow waters, the design of a novel underwater glider with improved capabilities is explored. A glider with a pneumatic buoyancy engine (allowing large, rapid buoyancy changes) and a cylindrical moving mass mechanism (generating large pitch and roll moments) is designed, manufactured, and tested to demonstrate potential improvements in speed and maneuverability.

A Primer on Autonomous Aerial Vehicle Design

PubMed Central

Coppejans, Hugo H. G.; Myburgh, Herman C.

2015-01-01

There is a large amount of research currently being done on autonomous micro-aerial vehicles (MAV), such as quadrotor helicopters or quadcopters. The ability to create a working autonomous MAV depends mainly on integrating a simultaneous localization and mapping (SLAM) solution with the rest of the system. This paper provides an introduction for creating an autonomous MAV for enclosed environments, aimed at students and professionals alike. The standard autonomous system and MAV automation are discussed, while we focus on the core concepts of SLAM systems and trajectory planning algorithms. The advantages and disadvantages of using remote processing are evaluated, and recommendations are made regarding the viability of on-board processing. Recommendations are made regarding best practices to serve as a guideline for aspirant MAV designers. PMID:26633410

A Primer on Autonomous Aerial Vehicle Design.

PubMed

Coppejans, Hugo H G; Myburgh, Herman C

2015-12-02

There is a large amount of research currently being done on autonomous micro-aerial vehicles (MAV), such as quadrotor helicopters or quadcopters. The ability to create a working autonomous MAV depends mainly on integrating a simultaneous localization and mapping (SLAM) solution with the rest of the system. This paper provides an introduction for creating an autonomous MAV for enclosed environments, aimed at students and professionals alike. The standard autonomous system and MAV automation are discussed, while we focus on the core concepts of SLAM systems and trajectory planning algorithms. The advantages and disadvantages of using remote processing are evaluated, and recommendations are made regarding the viability of on-board processing. Recommendations are made regarding best practices to serve as a guideline for aspirant MAV designers.

Sequential quadratic programming-based fast path planning algorithm subject to no-fly zone constraints

NASA Astrophysics Data System (ADS)

Liu, Wei; Ma, Shunjian; Sun, Mingwei; Yi, Haidong; Wang, Zenghui; Chen, Zengqiang

2016-08-01

Path planning plays an important role in aircraft guided systems. Multiple no-fly zones in the flight area make path planning a constrained nonlinear optimization problem. It is necessary to obtain a feasible optimal solution in real time. In this article, the flight path is specified to be composed of alternate line segments and circular arcs, in order to reformulate the problem into a static optimization one in terms of the waypoints. For the commonly used circular and polygonal no-fly zones, geometric conditions are established to determine whether or not the path intersects with them, and these can be readily programmed. Then, the original problem is transformed into a form that can be solved by the sequential quadratic programming method. The solution can be obtained quickly using the Sparse Nonlinear OPTimizer (SNOPT) package. Mathematical simulations are used to verify the effectiveness and rapidity of the proposed algorithm.

The Relationships between Perceived Teaching Behaviors and Motivation in Physical Education: A One-Year Longitudinal Study

ERIC Educational Resources Information Center

Koka, Andre

2013-01-01

This study aimed to examine the direction of relationships between specific dimensions of perceived teaching behaviors and motivation in physical education over time among 330 secondary school students. Cross-lagged path-analytic models revealed that autonomous motivation was reciprocally related over time with perceived decision-making style, and…

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.

Project Scheduling Based on Risk of Gas Transmission Pipe

NASA Astrophysics Data System (ADS)

Silvianita; Nurbaity, A.; Mulyadi, Y.; Suntoyo; Chamelia, D. M.

2018-03-01

The planning of a project has a time limit on which must be completed before or right at a predetermined time. Thus, in a project planning, it is necessary to have scheduling management that is useful for completing a project to achieve maximum results by considering the constraints that will exists. Scheduling management is undertaken to deal with uncertainties and negative impacts of time and cost in project completion. This paper explains about scheduling management in gas transmission pipeline project Gresik-Semarang to find out which scheduling plan is most effectively used in accordance with its risk value. Scheduling management in this paper is assissted by Microsoft Project software to find the critical path of existing project scheduling planning data. Critical path is the longest scheduling path with the fastest completion time. The result is found a critical path on project scheduling with completion time is 152 days. Furthermore, the calculation of risk is done by using House of Risk (HOR) method and it is found that the critical path has a share of 40.98 percent of all causes of the occurence of risk events that will be experienced.

Advanced Communication Architectures and Technologies for Missions to the Outer Planets

NASA Technical Reports Server (NTRS)

Bhasin, K.; Hayden, J. L.

2001-01-01

Missions to the outer planets would be considerably enhanced by the implementation of a future space communication infrastructure that utilizes relay stations placed at strategic locations in the solar system. These relay stations would operate autonomously and handle remote mission command and data traffic on a prioritized demand access basis. Such a system would enhance communications from that of the current direct communications between the planet and Earth. The system would also provide high rate data communications to outer planet missions, clear communications paths during times when the sun occults the mission spacecraft as viewed from Earth, and navigational "lighthouses" for missions utilizing onboard autonomous operations. Additional information is contained in the original extended abstract.

UAVSAR Flight-Planning System

NASA Technical Reports Server (NTRS)

2008-01-01

A system of software partly automates planning of a flight of the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) -- a polarimetric synthetic-aperture radar system aboard an unpiloted or minimally piloted airplane. The software constructs a flight plan that specifies not only the intended flight path but also the setup of the radar system at each point along the path.

Planification de trajectoires pour une flotte d'UAVs

NASA Astrophysics Data System (ADS)

Ait El Cadi, Abdessamad

In this thesis we address the problem of coordinating and controlling a fleet of Unmanned Aerial Vehicles (UAVs) during a surveillance mission in a dynamic context. The problem is vast and is related to several scientific domains. We have studied three important parts of this problem: • modeling the ground with all its constraints; • computing a shortest non-holonomic continuous path in a risky environment with a presence of obstacles; • planning a surveillance mission for a fleet of UAVs in a real context. While investigating the scientific literature related to these topics, we have detected deficiencies in the modeling of the ground and in the computation of the shortest continuous path, two critical aspects for the planning of a mission. So after the literature review, we have proposed answers to these two aspects and have applied our developments to the planning of a mission of a fleet of UAVs in a risky environment with the presence of obstacles. Obstacles could be natural like mountain or any non flyable zone. We have first modeled the ground as a directed graph. However, instead of using a classic mesh, we opted for an intelligent modeling that reduces the computing time on the graph without losing accuracy. The proposed model is based on the concept of visibility graph, and it also takes into account the obstacles, the danger areas and the constraint of non-holonomy of the UAVs- the kinematic constraint of the planes that imposes a maximum steering angle. The graph is then cleaned to keep only the minimum information needed for the calculation of trajectories. The generation of this graph possibly requires a lot of computation time, but it is done only once before the planning and will not affect the performance of trajectory calculations. We have also developed another simpler graph that does not take into account the constraint of non-holonomy. The advantage of this second graph is that it reduces the computation time. However, it requires the use of a correction procedure to make the resulting trajectory non-holonomic. This correction is possible within the context of our missions, but not for all types of autonomous vehicles. Once the directed graph is generated, we propose the use of a procedure for calculating the shortest continuous non-holonomic path in a risky environment with the presence of obstacles. The directed graph already incorporates all the constraints, which makes it possible to model the problem as a shortest path problem with resource a resource constraint (the resource here is the amount of permitted risk). The results are very satisfactory since the resulting routes are non-holonomic paths that meet all constraints. Moreover, the computing time is very short. For cases based on the simpler graph, we have created a procedure for correcting the trajectory to make it non-holonomic. All calculations of non-holonomy are based on Dubins curves (1957). We have finally applied our results to the planning of a mission of a fleet of UAVs in a risky environment with the presence of obstacles. For this purpose, we have developed a directed multi-graph where, for each pair of targets (points of departure and return of the mission included), we calculate a series of shorter trajectories with different limits of risk -- from the risk-free path to the riskiest path. We then use a Tabu Search with two tabu lists. Using these procedures, we have been able to produce routes for a fleet of UAVs that minimize the cost of the mission while respecting the limit of risk and avoiding obstacles. Tests are conducted on examples created on the basis of descriptions given by the Canadian Defense and, also on some instances of the CVRP (Capacitated Vehicle Routing Problem), those described by Christofides et Elion and those described by Christofides, Mingozzi et Toth. The results are of very satisfactory since all trajectories are non-holonomic and the improvement of the objective, when compared to a simple constructive method, achieves in some cases between 10 % and 43 %. We have even obtained an improvement of 69 %, but on a poor solution generated by a greedy algorithm. (Abstract shortened by UMI.)

Grasp planning under uncertainty

NASA Technical Reports Server (NTRS)

Erkmen, A. M.; Stephanou, H. E.

1989-01-01

The planning of dexterous grasps for multifingered robot hands operating in uncertain environments is covered. A sensor-based approach to the planning of a reach path prior to grasping is first described. An on-line, joint space finger path planning algorithm for the enclose phase of grasping was then developed. The algorithm minimizes the impact momentum of the hand. It uses a Preshape Jacobian matrix to map task-level hand preshape requirements into kinematic constraints. A master slave scheme avoids inter-finger collisions and reduces the dimensionality of the planning problem.

Planning paths to multiple targets: memory involvement and planning heuristics in spatial problem solving.

PubMed

Wiener, J M; Ehbauer, N N; Mallot, H A

2009-09-01

For large numbers of targets, path planning is a complex and computationally expensive task. Humans, however, usually solve such tasks quickly and efficiently. We present experiments studying human path planning performance and the cognitive processes and heuristics involved. Twenty-five places were arranged on a regular grid in a large room. Participants were repeatedly asked to solve traveling salesman problems (TSP), i.e., to find the shortest closed loop connecting a start location with multiple target locations. In Experiment 1, we tested whether humans employed the nearest neighbor (NN) strategy when solving the TSP. Results showed that subjects outperform the NN-strategy, suggesting that it is not sufficient to explain human route planning behavior. As a second possible strategy we tested a hierarchical planning heuristic in Experiment 2, demonstrating that participants first plan a coarse route on the region level that is refined during navigation. To test for the relevance of spatial working memory (SWM) and spatial long-term memory (LTM) for planning performance and the planning heuristics applied, we varied the memory demands between conditions in Experiment 2. In one condition the target locations were directly marked, such that no memory was required; a second condition required participants to memorize the target locations during path planning (SWM); in a third condition, additionally, the locations of targets had to retrieved from LTM (SWM and LTM). Results showed that navigation performance decreased with increasing memory demands while the dependence on the hierarchical planning heuristic increased.

Autonomous operations through onboard artificial intelligence

NASA Technical Reports Server (NTRS)

Sherwood, R. L.; Chien, S.; Castano, R.; Rabideau, G.

2002-01-01

The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.

Lane identification and path planning for autonomous mobile robots

NASA Astrophysics Data System (ADS)

McKeon, Robert T.; Paulik, Mark; Krishnan, Mohan

2006-10-01

This work has been performed in conjunction with the University of Detroit Mercy's (UDM) ECE Department autonomous vehicle entry in the 2006 Intelligent Ground Vehicle Competition (www.igvc.org). The IGVC challenges engineering students to design autonomous vehicles and compete in a variety of unmanned mobility competitions. The course to be traversed in the competition consists of a lane demarcated by painted lines on grass with the possibility of one of the two lines being deliberately left out over segments of the course. The course also consists of other challenging artifacts such as sandpits, ramps, potholes, and colored tarps that alter the color composition of scenes, and obstacles set up using orange and white construction barrels. This paper describes a composite lane edge detection approach that uses three algorithms to implement noise filters enabling increased removal of noise prior to the application of image thresholding. The first algorithm uses a row-adaptive statistical filter to establish an intensity floor followed by a global threshold based on a reverse cumulative intensity histogram and a priori knowledge about lane thickness and separation. The second method first improves the contrast of the image by implementing an arithmetic combination of the blue plane (RGB format) and a modified saturation plane (HSI format). A global threshold is then applied based on the mean of the intensity image and a user-defined offset. The third method applies the horizontal component of the Sobel mask to a modified gray scale of the image, followed by a thresholding method similar to the one used in the second method. The Hough transform is applied to each of the resulting binary images to select the most probable line candidates. Finally, a heuristics-based confidence interval is determined, and the results sent on to a separate fuzzy polar-based navigation algorithm, which fuses the image data with that produced by a laser scanner (for obstacle detection).

Cooperative mission execution and planning

NASA Astrophysics Data System (ADS)

Flann, Nicholas S.; Saunders, Kevin S.; Pells, Larry

1998-08-01

Utilizing multiple cooperating autonomous vehicles to perform tasks enhances robustness and efficiency over the use of a single vehicle. Furthermore, because autonomous vehicles can be controlled precisely and their status known accurately in real time, new types of cooperative behaviors are possible. This paper presents a working system called MEPS that plans and executes missions for multiple autonomous vehicles in large structured environments. Two generic spatial tasks are supported, to sweep an area and to visit a location while activating on-board equipment. Tasks can be entered both initially by the user and dynamically during mission execution by both users and vehicles. Sensor data and task achievement data is shared among the vehicles enabling them to cooperatively adapt to changing environmental, vehicle and tasks conditions. The system has been successfully applied to control ATV and micro-robotic vehicles in precision agriculture and waste-site characterization environments.

System and Method for Aiding Pilot Preview, Rehearsal, Review, and Real-Time Visual Acquisition of Flight Mission Progress

NASA Technical Reports Server (NTRS)

Prinzel, III, Lawrence J. (Inventor); Pope, Alan T. (Inventor); Williams, Steven P. (Inventor); Bailey, Randall E. (Inventor); Arthur, Jarvis J. (Inventor); Kramer, Lynda J. (Inventor); Schutte, Paul C. (Inventor)

2012-01-01

Embodiments of the invention permit flight paths (current and planned) to be viewed from various orientations to provide improved path and terrain awareness via graphical two-dimensional or three-dimensional perspective display formats. By coupling the flight path information with a terrain database, uncompromising terrain awareness relative to the path and ownship is provided. In addition, missed approaches, path deviations, and any navigational path can be reviewed and rehearsed before performing the actual task. By rehearsing a particular mission, check list items can be reviewed, terrain awareness can be highlighted, and missed approach procedures can be discussed by the flight crew. Further, the use of Controller Pilot Datalink Communications enables data-linked path, flight plan changes, and Air Traffic Control requests to be integrated into the flight display of the present invention.

Integrated Demonstration of Instrument Placement , Robust Execution and Contingent Planning

NASA Technical Reports Server (NTRS)

Pedersen, L.; Bualat, M.; Lees, D.; Smith, D. E.; Korsmeyer, David (Technical Monitor); Washington, R.

2003-01-01

This paper describes an integrated demonstration of ground-based contingent planning, robust execution and autonomous instrument placement for the efficient exploration of a site by a prototype Mars rover.

Sampling-Based Coverage Path Planning for Complex 3D Structures

DTIC Science & Technology

2012-09-01

one such task, in which a single robot must sweep its end effector over the entirety of a known workspace. For two-dimensional environments, optimal...structures. First, we introduce a new algorithm for planning feasible coverage paths. It is more computationally efficient in problems of complex geometry...iteratively shortens and smooths a feasible coverage path; robot configurations are adjusted without violating any coverage con- straints. Third, we propose

Automated and Adaptive Mission Planning for Orbital Express

NASA Technical Reports Server (NTRS)

Chouinard, Caroline; Knight, Russell; Jones, Grailing; Tran, Daniel; Koblick, Darin

2008-01-01

The Orbital Express space mission was a Defense Advanced Research Projects Agency (DARPA) lead demonstration of on-orbit satellite servicing scenarios, autonomous rendezvous, fluid transfers of hydrazine propellant, and robotic arm transfers of Orbital Replacement Unit (ORU) components. Boeing's Autonomous Space Transport Robotic Operations (ASTRO) vehicle provided the servicing to the Ball Aerospace's Next Generation Serviceable Satellite (NextSat) client. For communication opportunities, operations used the high-bandwidth ground-based Air Force Satellite Control Network (AFSCN) along with the relatively low-bandwidth GEO-Synchronous space-borne Tracking and Data Relay Satellite System (TDRSS) network. Mission operations were conducted out of the RDT&E Support Complex (RSC) at the Kirtland Air Force Base in New Mexico. All mission objectives were met successfully: The first of several autonomous rendezvous was demonstrated on May 5, 2007; autonomous free-flyer capture was demonstrated on June 22, 2007; the fluid and ORU transfers throughout the mission were successful. Planning operations for the mission were conducted by a team of personnel including Flight Directors, who were responsible for verifying the steps and contacts within the procedures, the Rendezvous Planners who would compute the locations and visibilities of the spacecraft, the Scenario Resource Planners (SRPs), who were concerned with assignment of communications windows, monitoring of resources, and sending commands to the ASTRO spacecraft, and the Mission planners who would interface with the real-time operations environment, process planning products and coordinate activities with the SRP. The SRP position was staffed by JPL personnel who used the Automated Scheduling and Planning ENvironment (ASPEN) to model and enforce mission and satellite constraints. The lifecycle of a plan began three weeks outside its execution on-board. During the planning timeframe, many aspects could change the plan, causing the need for re-planning. These variable factors, ranging from shifting contact times to ground-station closures and required maintenance times, are discussed along with the flexibility of the ASPEN tool to accommodate changes to procedures and the daily or long-range plan, which contributed to the success of the mission. This paper will present an introduction to ASPEN, a more in-depth discussion on its use on the Orbital Express mission, and other relative work. A description of ground operations after the SRP deliveries were made is included, and we briefly discuss lessons learned from the planning perspective and future work.

Growing Up of Autonomous Agents: an Emergent Phenomenon

NASA Astrophysics Data System (ADS)

Morgavi, Giovanna; Marconi, Lucia

2008-10-01

A fundamental research challenge is the design of robust artifacts that are capable of operating under changing environments and noisy input, and yet exhibit the desired behavior and response time. These systems should be able to adapt and learn how to react to unforeseen scenarios as well as to display properties comparable to biological entities. The turn to nature has brought us many unforeseen great concepts. Biological systems are able to handle many of these challenges with an elegance and efficiency still far beyond current human artifacts. A living artifact grows up when its capabilities, abilities/knowledge, shift to a further level of complexity, i.e. the complexity rank of its internal capabilities performs a step forward. In the attempt to define an architecture for autonomous growing up agents [1]. We conducted an experiment on the abstraction process in children as natural parts of a cognitive system. We found that linguistic growing up involve a number of different trial processes. We identified a fixed number of distinct paths that were crossed by children. Once a given interpretation paths was discovered useless, they tried to follow another path, until the new meaning was emerging. This study generates suggestion about the evolutionary conditions conducive to the emergence of growing up in robots and provides guidelines for designing artificial evolutionary systems displaying spontaneous adaptation abilities. The importance of multi-sensor perception, motivation and emotional drives are underlined and, above all, the growing up insights shows similarities to emergent self-organized behaviors.

Robot path planning algorithm based on symbolic tags in dynamic environment

NASA Astrophysics Data System (ADS)

Vokhmintsev, A.; Timchenko, M.; Melnikov, A.; Kozko, A.; Makovetskii, A.

2017-09-01

The present work will propose a new heuristic algorithms for path planning of a mobile robot in an unknown dynamic space that have theoretically approved estimates of computational complexity and are approbated for solving specific applied problems.

Temporal and Resource Reasoning for Planning, Scheduling and Execution in Autonomous Agents

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Hunsberger, Luke; Tsamardinos, Ioannis

2005-01-01

This viewgraph slide tutorial reviews methods for planning and scheduling events. The presentation reviews several methods and uses several examples of scheduling events for the successful and timely completion of the overall plan. Using constraint based models the presentation reviews planning with time, time representations in problem solving and resource reasoning.

RoBlock: a prototype autonomous manufacturing cell

NASA Astrophysics Data System (ADS)

Baekdal, Lars K.; Balslev, Ivar; Eriksen, Rene D.; Jensen, Soren P.; Jorgensen, Bo N.; Kirstein, Brian; Kristensen, Bent B.; Olsen, Martin M.; Perram, John W.; Petersen, Henrik G.; Petersen, Morten L.; Ruhoff, Peter T.; Skjolstrup, Carl E.; Sorensen, Anders S.; Wagenaar, Jeroen M.

2000-10-01

RoBlock is the first phase of an internally financed project at the Institute aimed at building a system in which two industrial robots suspended from a gantry, as shown below, cooperate to perform a task specified by an external user, in this case, assembling an unstructured collection of colored wooden blocks into a specified 3D pattern. The blocks are identified and localized using computer vision and grasped with a suction cup mechanism. Future phases of the project will involve other processes such as grasping and lifting, as well as other types of robot such as autonomous vehicles or variable geometry trusses. Innovative features of the control software system include: The use of an advanced trajectory planning system which ensures collision avoidance based on a generalization of the method of artificial potential fields, the use of a generic model-based controller which learns the values of parameters, including static and kinetic friction, of a detailed mechanical model of itself by comparing actual with planned movements, the use of fast, flexible, and robust pattern recognition and 3D-interpretation strategies, integration of trajectory planning and control with the sensor systems in a distributed Java application running on a network of PC's attached to the individual physical components. In designing this first stage, the aim was to build in the minimum complexity necessary to make the system non-trivially autonomous and to minimize the technological risks. The aims of this project, which is planned to be operational during 2000, are as follows: To provide a platform for carrying out experimental research in multi-agent systems and autonomous manufacturing systems, to test the interdisciplinary cooperation architecture of the Maersk Institute, in which researchers in the fields of applied mathematics (modeling the physical world), software engineering (modeling the system) and sensor/actuator technology (relating the virtual and real worlds) could collaborate with systems integrators to construct intelligent, autonomous systems, and to provide a showpiece demonstrator in the entrance hall of the Institute's new building.

Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment

PubMed Central

Zhang, Rubo; Yang, Yu

2017-01-01

Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling time domain control is one of the better task planning techniques, which can greatly reduce the computational workload and realize the tradeoff between AUV dynamics, environment and cost. Finally, a simulation experiment was performed to evaluate the distributed task planning performance of the scroll time domain quantum bee colony optimization algorithm. The simulation results demonstrate that the STDQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The STDQABC algorithm can effectively improve MAUV distributed tasking planning performance, complete the task goal and get the approximate optimal solution. PMID:29186166

Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment.

PubMed

Li, Jianjun; Zhang, Rubo; Yang, Yu

2017-01-01

Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling time domain control is one of the better task planning techniques, which can greatly reduce the computational workload and realize the tradeoff between AUV dynamics, environment and cost. Finally, a simulation experiment was performed to evaluate the distributed task planning performance of the scroll time domain quantum bee colony optimization algorithm. The simulation results demonstrate that the STDQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The STDQABC algorithm can effectively improve MAUV distributed tasking planning performance, complete the task goal and get the approximate optimal solution.

Research on Taxiway Path Optimization Based on Conflict Detection

PubMed Central

Zhou, Hang; Jiang, Xinxin

2015-01-01

Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency. PMID:26226485

Expert system for neurosurgical treatment planning

NASA Astrophysics Data System (ADS)

Cheng, Andrew Y. S.; Chung, Sally S. Y.; Kwok, John C. K.

1996-04-01

A specially designed expert system is in development for neurosurgical treatment planning. The knowledge base contains knowledge and experiences on neurosurgical treatment planning from neurosurgeon consultants, who also determine the risks of different regions in human brains. When completed, the system can simulate the decision making process of neurosurgeons to determine the safest probing path for operation. The Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) scan images for each patient are grabbed as the input. The system also allows neurosurgeons to include for any particular patient the additional information, such as how the tumor affects its neighboring functional regions, which is also important for calculating the safest probing path. It can then consider all the relevant information and find the most suitable probing path on the patient's brain. A 3D brain model is constructed for each set of the CT/MRI scan images and is displayed real-time together with the possible probing paths found. The precise risk value of each path is shown as a number between 0 and 1, together with its possible damages in text. Neurosurgeons can view more than one possible path simultaneously, and make the final decision on the selected path for operation.

Research on Taxiway Path Optimization Based on Conflict Detection.

PubMed

Zhou, Hang; Jiang, Xinxin

2015-01-01

Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency.

Automation and robotics

NASA Technical Reports Server (NTRS)

Montemerlo, Melvin

1988-01-01

The Autonomous Systems focus on the automation of control systems for the Space Station and mission operations. Telerobotics focuses on automation for in-space servicing, assembly, and repair. The Autonomous Systems and Telerobotics each have a planned sequence of integrated demonstrations showing the evolutionary advance of the state-of-the-art. Progress is briefly described for each area of concern.

Autonomous Student Experiences in Outdoor and Adventure Education

ERIC Educational Resources Information Center

Daniel, Brad; Bobilya, Andrew J.; Kalisch, Kenneth R.; McAvoy, Leo H.

2014-01-01

This article explores the current state of knowledge regarding the use of autonomous student experiences (ASE) in outdoor and adventure education (OAE) programs. ASE are defined as components (e.g., solo, final expedition) in which participants have a greater measure of choice and control over the planning, execution, and outcomes of their…

Study of Double-Weighted Graph Model and Optimal Path Planning for Tourist Scenic Area Oriented Intelligent Tour Guide

NASA Astrophysics Data System (ADS)

Shi, Y.; Long, Y.; Wi, X. L.

2014-04-01

When tourists visiting multiple tourist scenic spots, the travel line is usually the most effective road network according to the actual tour process, and maybe the travel line is different from planned travel line. For in the field of navigation, a proposed travel line is normally generated automatically by path planning algorithm, considering the scenic spots' positions and road networks. But when a scenic spot have a certain area and have multiple entrances or exits, the traditional described mechanism of single point coordinates is difficult to reflect these own structural features. In order to solve this problem, this paper focuses on the influence on the process of path planning caused by scenic spots' own structural features such as multiple entrances or exits, and then proposes a doubleweighted Graph Model, for the weight of both vertexes and edges of proposed Model can be selected dynamically. And then discusses the model building method, and the optimal path planning algorithm based on Dijkstra algorithm and Prim algorithm. Experimental results show that the optimal planned travel line derived from the proposed model and algorithm is more reasonable, and the travelling order and distance would be further optimized.

Path planning for planetary rover using extended elevation map

NASA Technical Reports Server (NTRS)

Nakatani, Ichiro; Kubota, Takashi; Yoshimitsu, Tetsuo

1994-01-01

This paper describes a path planning method for planetary rovers to search for paths on planetary surfaces. The planetary rover is required to travel safely over a long distance for many days over unfamiliar terrain. Hence it is very important how planetary rovers process sensory information in order to understand the planetary environment and to make decisions based on that information. As a new data structure for informational mapping, an extended elevation map (EEM) has been introduced, which includes the effect of the size of the rover. The proposed path planning can be conducted in such a way as if the rover were a point while the size of the rover is automatically taken into account. The validity of the proposed methods is verified by computer simulations.

An Architecture to Enable Autonomous Control of Spacecraft

NASA Technical Reports Server (NTRS)

May, Ryan D.; Dever, Timothy P.; Soeder, James F.; George, Patrick J.; Morris, Paul H.; Colombano, Silvano P.; Frank, Jeremy D.; Schwabacher, Mark A.; Wang, Liu; LawLer, Dennis

2014-01-01

Autonomy is required for manned spacecraft missions distant enough that light-time communication delays make ground-based mission control infeasible. Presently, ground controllers develop a complete schedule of power modes for all spacecraft components based on a large number of factors. The proposed architecture is an early attempt to formalize and automate this process using on-vehicle computation resources. In order to demonstrate this architecture, an autonomous electrical power system controller and vehicle Mission Manager are constructed. These two components are designed to work together in order to plan upcoming load use as well as respond to unanticipated deviations from the plan. The communication protocol was developed using "paper" simulations prior to formally encoding the messages and developing software to implement the required functionality. These software routines exchange data via TCP/IP sockets with the Mission Manager operating at NASA Ames Research Center and the autonomous power controller running at NASA Glenn Research Center. The interconnected systems are tested and shown to be effective at planning the operation of a simulated quasi-steady state spacecraft power system and responding to unexpected disturbances.

A Sampling Based Approach to Spacecraft Autonomous Maneuvering with Safety Specifications

NASA Technical Reports Server (NTRS)

Starek, Joseph A.; Barbee, Brent W.; Pavone, Marco

2015-01-01

This paper presents a methods for safe spacecraft autonomous maneuvering that leverages robotic motion-planning techniques to spacecraft control. Specifically the scenario we consider is an in-plan rendezvous of a chaser spacecraft in proximity to a target spacecraft at the origin of the Clohessy Wiltshire Hill frame. The trajectory for the chaser spacecraft is generated in a receding horizon fashion by executing a sampling based robotic motion planning algorithm name Fast Marching Trees (FMT) which efficiently grows a tree of trajectories over a set of probabillistically drawn samples in the state space. To enforce safety the tree is only grown over actively safe samples for which there exists a one-burn collision avoidance maneuver that circularizes the spacecraft orbit along a collision-free coasting arc and that can be executed under potential thrusters failures. The overall approach establishes a provably correct framework for the systematic encoding of safety specifications into the spacecraft trajectory generations process and appears amenable to real time implementation on orbit. Simulation results are presented for a two-fault tolerant spacecraft during autonomous approach to a single client in Low Earth Orbit.

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.

Visual environment recognition for robot path planning using template matched filters

NASA Astrophysics Data System (ADS)

Orozco-Rosas, Ulises; Picos, Kenia; Díaz-Ramírez, Víctor H.; Montiel, Oscar; Sepúlveda, Roberto

2017-08-01

A visual approach in environment recognition for robot navigation is proposed. This work includes a template matching filtering technique to detect obstacles and feasible paths using a single camera to sense a cluttered environment. In this problem statement, a robot can move from the start to the goal by choosing a single path between multiple possible ways. In order to generate an efficient and safe path for mobile robot navigation, the proposal employs a pseudo-bacterial potential field algorithm to derive optimal potential field functions using evolutionary computation. Simulation results are evaluated in synthetic and real scenes in terms of accuracy of environment recognition and efficiency of path planning computation.

New Polyazine-Bridged RuII,RhIII and RuII,RhI Supramolecular Photocatalysts for Water Reduction to Hydrogen Applicable for Solar Energy Conversion and Mechanistic Investigation of the Photocatalytic Cycle

NASA Astrophysics Data System (ADS)

Zhou, Rongwei

Underwater gliders are robust and long endurance ocean sampling platforms that are increasingly being deployed in coastal regions. This new environment is characterized by shallow waters and significant currents that can challenge the mobility of these efficient (but traditionally slow moving) vehicles. This dissertation aims to improve the performance of shallow water underwater gliders through path planning. The path planning problem is formulated for a dynamic particle (or "kinematic car") model. The objective is to identify the path which satisfies specified boundary conditions and minimizes a particular cost. Several cost functions are considered. The problem is addressed using optimal control theory. The length scales of interest for path planning are within a few turn radii. First, an approach is developed for planning minimum-time paths, for a fixed speed glider, that are sub-optimal but are guaranteed to be feasible in the presence of unknown time-varying currents. Next the minimum-time problem for a glider with speed controls, that may vary between the stall speed and the maximum speed, is solved. Last, optimal paths that minimize change in depth (equivalently, maximize range) are investigated. Recognizing that path planning alone cannot overcome all of the challenges associated with significant currents and shallow waters, the design of a novel underwater glider with improved capabilities is explored. A glider with a pneumatic buoyancy engine (allowing large, rapid buoyancy changes) and a cylindrical moving mass mechanism (generating large pitch and roll moments) is designed, manufactured, and tested to demonstrate potential improvements in speed and maneuverability.

Path-following control of wheeled planetary exploration robots moving on deformable rough terrain.

PubMed

Ding, Liang; Gao, Hai-bo; Deng, Zong-quan; Li, Zhijun; Xia, Ke-rui; Duan, Guang-ren

2014-01-01

The control of planetary rovers, which are high performance mobile robots that move on deformable rough terrain, is a challenging problem. Taking lateral skid into account, this paper presents a rough terrain model and nonholonomic kinematics model for planetary rovers. An approach is proposed in which the reference path is generated according to the planned path by combining look-ahead distance and path updating distance on the basis of the carrot following method. A path-following strategy for wheeled planetary exploration robots incorporating slip compensation is designed. Simulation results of a four-wheeled robot on deformable rough terrain verify that it can be controlled to follow a planned path with good precision, despite the fact that the wheels will obviously skid and slip.

Path-Following Control of Wheeled Planetary Exploration Robots Moving on Deformable Rough Terrain

PubMed Central

Ding, Liang; Gao, Hai-bo; Deng, Zong-quan; Li, Zhijun; Xia, Ke-rui; Duan, Guang-ren

2014-01-01

The control of planetary rovers, which are high performance mobile robots that move on deformable rough terrain, is a challenging problem. Taking lateral skid into account, this paper presents a rough terrain model and nonholonomic kinematics model for planetary rovers. An approach is proposed in which the reference path is generated according to the planned path by combining look-ahead distance and path updating distance on the basis of the carrot following method. A path-following strategy for wheeled planetary exploration robots incorporating slip compensation is designed. Simulation results of a four-wheeled robot on deformable rough terrain verify that it can be controlled to follow a planned path with good precision, despite the fact that the wheels will obviously skid and slip. PMID:24790582

Software Testbed for Developing and Evaluating Integrated Autonomous Systems

DTIC Science & Technology

2015-03-01

EUROPA planning system for plan generation. The adaptive controller executes the new plan, using augmented, hierarchical finite state machines to...using the Internet Communications Engine ( ICE ), an object-oriented toolkit for building distributed applications. TABLE OF CONTENTS 1...ANML model is translated into the New Domain Definition Language (NDDL) and sent to NASA???s EUROPA planning system for plan generation. The adaptive

Aircraft path planning for optimal imaging using dynamic cost functions

NASA Astrophysics Data System (ADS)

Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin

2015-05-01

Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.

Short Range Planning for Educational Management.

ERIC Educational Resources Information Center

Turksen, I. B.; Holzman, A. G.

A planning cycle for any autonomous university entity contains five basic processes: information storage and retrieval forecasting, resource allocation, scheduling, and a term of study with a feedback loop. The resource allocation process is investigated for the development of shortrange planning models. Dynamic models wth linear and quadratic…

The Basis for Integrating Local Knowledge into the School Curriculum for Tibetans in Southern Gansu

ERIC Educational Resources Information Center

Fuhai, An

2017-01-01

The school curriculum in Gannan Tibetan Autonomous Prefecture (Gannan) does not adequately consider the interests and needs of Tibetan students or the life options of those who fail to be chosen for a path to "legitimization." Such a curriculum is not only incompatible with what should be the objectives and requirements for transmitting…

The Path Forward: School Autonomy and Its Implications for the Future of Boston's Public Schools

ERIC Educational Resources Information Center

French, Dan; Miles, Karen Hawley; Nathan, Linda

2014-01-01

This study explores the question of how Boston Public Schools (BPS) can strengthen and support autonomy and accountability across its portfolio to promote innovation and expand access to equity and high performance. Some of the specific questions guiding this work are: (1) Should all schools within BPS operate within autonomous structures? (2) Is…

One or Multiple Paths to Quality Assurance of Higher Education Institutions in the United Arab Emirates

ERIC Educational Resources Information Center

Ashour, Sanaa

2017-01-01

The United Arab Emirates (UAE) is a federation of seven autonomous emirates that follow different economic models. There is a process for quality assurance at the federal level, however, each emirate takes its own approach to assure the quality of its institutions. This has resulted in different procedures and varying levels of oversight and…

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

NASA Technical Reports Server (NTRS)

1974-01-01

A number of problems related to the design, construction and evaluation of an autonomous roving planetary vehicle and its control and operating systems intended for an unmanned exploration of Mars are studied. Vehicle configuration, dynamics, control, systems and propulsion; systems analysis; terrain sensing and modeling and path selection; and chemical analysis of samples are included.

Leader-follower function for autonomous military convoys

NASA Astrophysics Data System (ADS)

Vasseur, Laurent; Lecointe, Olivier; Dento, Jerome; Cherfaoui, Nourrdine; Marion, Vincent; Morillon, Joel G.

2004-09-01

The French Military Robotic Study Program (introduced in Aerosense 2003), sponsored by the French Defense Procurement Agency and managed by Thales Airborne Systems as the prime contractor, focuses on about 15 robotic themes which can provide an immediate "operational added value." The paper details the "robotic convoy" theme (named TEL1), which main purpose is to develop a robotic leader-follower function so that several unmanned vehicles can autonomously follow teleoperated, autonomous or on-board driven leader. Two modes have been implemented: Perceptive follower: each autonomous follower anticipates the trajectory of the vehicle in front of it, thanks to a dedicated perception equipment. This mode is mainly based on the use of perceptive data, without any communication link between leader and follower (to lower the cost of future mass development and extend the operational capabilities). Delayed follower: the leader records its path and transmits it to the follower; the follower is able to follow the recorded trajectory again at any delayed time. This mode uses localization data got from inertial measurements. The paper presents both modes with detailed algorithms and the results got from the military acceptance tests performed on wheeled 4x4 vehicles (DARDS French ATD).

Autonomous power expert system

NASA Technical Reports Server (NTRS)

Ringer, Mark J.; Quinn, Todd M.

1990-01-01

The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control technologies to the Space Station Freedom Electrical Power Systems (SSF/EPS). The objectives of the program are to establish artificial intelligence/expert system technology paths, to create knowledge based tools with advanced human-operator interfaces, and to integrate and interface knowledge-based and conventional control schemes. This program is being developed at the NASA-Lewis. The APS Brassboard represents a subset of a 20 KHz Space Station Power Management And Distribution (PMAD) testbed. A distributed control scheme is used to manage multiple levels of computers and switchgear. The brassboard is comprised of a set of intelligent switchgear used to effectively switch power from the sources to the loads. The Autonomous Power Expert System (APEX) portion of the APS program integrates a knowledge based fault diagnostic system, a power resource scheduler, and an interface to the APS Brassboard. The system includes knowledge bases for system diagnostics, fault detection and isolation, and recommended actions. The scheduler autonomously assigns start times to the attached loads based on temporal and power constraints. The scheduler is able to work in a near real time environment for both scheduling and dynamic replanning.

Autonomous power expert system

NASA Technical Reports Server (NTRS)

Ringer, Mark J.; Quinn, Todd M.

1990-01-01

The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control technologies to the Space Station Freedom Electrical Power Systems (SSF/EPS). The objectives of the program are to establish artificial intelligence/expert system technology paths, to create knowledge based tools with advanced human-operator interfaces, and to integrate and interface knowledge-based and conventional control schemes. This program is being developed at the NASA-Lewis. The APS Brassboard represents a subset of a 20 KHz Space Station Power Management And Distribution (PMAD) testbed. A distributed control scheme is used to manage multiple levels of computers and switchgear. The brassboard is comprised of a set of intelligent switchgear used to effectively switch power from the sources to the loads. The Autonomous Power Expert System (APEX) portion of the APS program integrates a knowledge based fault diagnostic system, a power resource scheduler, and an interface to the APS Brassboard. The system includes knowledge bases for system diagnostics, fault detection and isolation, and recommended actions. The scheduler autonomously assigns start times to the attached loads based on temporal and power constraints. The scheduler is able to work in a near real time environment for both scheduling an dynamic replanning.

Autonomous motivation is not enough: the role of compensatory health beliefs for the readiness to change stair and elevator use.

PubMed

Radtke, Theda; Rackow, Pamela

2014-11-28

Compensatory health beliefs (CHBs) are beliefs that an unhealthy behavior can be compensated with a healthy behavior. In line with the CHBs model, the aim of this study was twofold. First, the study investigated the relationship between autonomous motivation and CHBs that physical inactivity can be compensated by taking the stairs instead of the elevator. Second, the study focused on the associations between CHBs and readiness to use the stairs more often and stair and elevator use. Thus, a cross-sectional online questionnaire was designed that was filled out by 135 participants. Path analysis showed that individuals with stronger autonomous motivation to use the stairs strongly agreed that sedentary behavior could be compensated by taking the stairs instead of the elevator. Moreover, CHBs were positively related to readiness to change behavior, but not to self-reported stair and elevator use. Even though future research is necessary to replicate these findings, autonomous motivation seems to have a positive impact on CHBs which, in turn, might boost an intended behavior change. Thus, promoting possible compensation of physical inactivity might foster the readiness to change the unhealthy behavior.

Augmented Reality: Sustaining Autonomous Way-Finding in the Community for Older Persons with Cognitive Impairment.

PubMed

Sejunaite, K; Lanza, C; Ganders, S; Iljaitsch, A; Riepe, M W

2017-01-01

Impairment of autonomous way-finding subsequent to a multitude of neurodegenerative and other diseases impedes independence of older persons and their everyday activities. It was the goal to use augmented reality to aid autonomous way-finding in a community setting. A spatial map and directional information were shown via head-up display to guide patients from the start zone on the hospital campus to a bakery in the nearby community. Hospital campus and nearby community. Patients with mild cognitive impairment (age 63 to 89). A head-up display was used to help patients find their way. Time needed to reach goal and number of assists needed. With use of augmented reality device, patients preceded along the correct path in 113 out of 120 intersections. Intermittent reassurance was needed for most patients. Patients affirmed willingness to use such an augmented reality device in everyday life if needed or even pay for it. Augmented reality guided navigation is a promising means to sustain autonomous way-finding as a prerequisite for autonomy of older persons in everyday activities. Thus, this study lays ground for a field trial in the community using assistive technology for older persons with cognitive impairment.

Autonomous Motivation Is Not Enough: The Role of Compensatory Health Beliefs for the Readiness to Change Stair and Elevator Use

PubMed Central

Radtke, Theda; Rackow, Pamela

2014-01-01

Compensatory health beliefs (CHBs) are beliefs that an unhealthy behavior can be compensated with a healthy behavior. In line with the CHBs model, the aim of this study was twofold. First, the study investigated the relationship between autonomous motivation and CHBs that physical inactivity can be compensated by taking the stairs instead of the elevator. Second, the study focused on the associations between CHBs and readiness to use the stairs more often and stair and elevator use. Thus, a cross-sectional online questionnaire was designed that was filled out by 135 participants. Path analysis showed that individuals with stronger autonomous motivation to use the stairs strongly agreed that sedentary behavior could be compensated by taking the stairs instead of the elevator. Moreover, CHBs were positively related to readiness to change behavior, but not to self-reported stair and elevator use. Even though future research is necessary to replicate these findings, autonomous motivation seems to have a positive impact on CHBs which, in turn, might boost an intended behavior change. Thus, promoting possible compensation of physical inactivity might foster the readiness to change the unhealthy behavior. PMID:25464134

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration. [performance tests of remote control equipment for roving vehicles

NASA Technical Reports Server (NTRS)

Gisser, D. G.; Frederick, D. K.; Sandor, G. N.; Shen, C. N.; Yerazunis, S. W.

1976-01-01

Problems related to the design and control of an autonomous rover for the purpose of unmanned exploration of the planets were considered. Building on the basis of prior studies, a four wheeled rover of unusual mobility and maneuverability was further refined and tested under both laboratory and field conditions. A second major effort was made to develop autonomous guidance. Path selection systems capable of dealing with relatively formidable hazard and terrains involving various short range (1.0-3.0 meters), hazard detection systems using a triangulation detection concept were simulated and evaluated. The mechanical/electronic systems required to implement such a scheme were constructed and tested. These systems include: laser transmitter, photodetectors, the necessary data handling/controlling systems and a scanning mast. In addition, a telemetry system to interface the vehicle, the off-board computer and a remote control module for operator intervention were developed. Software for the autonomous control concept was written. All of the systems required for complete autonomous control were shown to be satisfactory except for that portion of the software relating to the handling of interrupt commands.

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.

Robot Path Planning in Uncertain Environments: A Language-Measure-Theoretic Approach

DTIC Science & Technology

2015-03-01

in the framework of probabilistic finite state automata (PFSA) and language measure from a control-theoretic perspective. The proposed concept has been...DOI: 10.1115/1.4027876] Keywords: path planning, language measure, probabilistic finite state automata 1 Motivation and Introduction In general

A Unified Approach to Model-Based Planning and Execution

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Dorais, Gregory A.; Fry, Chuck; Levinson, Richard; Plaunt, Christian; Norvig, Peter (Technical Monitor)

2000-01-01

Writing autonomous software is complex, requiring the coordination of functionally and technologically diverse software modules. System and mission engineers must rely on specialists familiar with the different software modules to translate requirements into application software. Also, each module often encodes the same requirement in different forms. The results are high costs and reduced reliability due to the difficulty of tracking discrepancies in these encodings. In this paper we describe a unified approach to planning and execution that we believe provides a unified representational and computational framework for an autonomous agent. We identify the four main components whose interplay provides the basis for the agent's autonomous behavior: the domain model, the plan database, the plan running module, and the planner modules. This representational and problem solving approach can be applied at all levels of the architecture of a complex agent, such as Remote Agent. In the rest of the paper we briefly describe the Remote Agent architecture. The new agent architecture proposed here aims at achieving the full Remote Agent functionality. We then give the fundamental ideas behind the new agent architecture and point out some implication of the structure of the architecture, mainly in the area of reactivity and interaction between reactive and deliberative decision making. We conclude with related work and current status.

Mission planning for autonomous systems

NASA Technical Reports Server (NTRS)

Pearson, G.

1987-01-01

Planning is a necessary task for intelligent, adaptive systems operating independently of human controllers. A mission planning system that performs task planning by decomposing a high-level mission objective into subtasks and synthesizing a plan for those tasks at varying levels of abstraction is discussed. Researchers use a blackboard architecture to partition the search space and direct the focus of attention of the planner. Using advanced planning techniques, they can control plan synthesis for the complex planning tasks involved in mission planning.

Intelligent unmanned vehicle systems suitable for individual or cooperative missions

NASA Astrophysics Data System (ADS)

Anderson, Matthew O.; McKay, Mark D.; Wadsworth, Derek C.

2007-04-01

The Department of Energy's Idaho National Laboratory (INL) has been researching autonomous unmanned vehicle systems for over fifteen years. Areas of research have included unmanned ground and aerial vehicles used for hazardous and remote operations as well as teamed together for advanced payloads and mission execution. Areas of application include aerial particulate sampling, cooperative remote radiological sampling, and persistent surveillance including real-time mosaic and geo-referenced imagery in addition to high-resolution still imagery. Both fixed-wing and rotary airframes are used possessing capabilities spanning remote control to fully autonomous operation. Patented INL-developed auto steering technology is taken advantage of to provide autonomous parallel path swathing with either manned or unmanned ground vehicles. Aerial look-ahead imagery is utilized to provide a common operating picture for the ground and air vehicles during cooperative missions. This paper will discuss the various robotic vehicles, including sensor integration, used to achieve these missions and anticipated cost and labor savings.

Navigation of autonomous vehicles for oil spill cleaning in dynamic and uncertain environments

NASA Astrophysics Data System (ADS)

Jin, Xin; Ray, Asok

2014-04-01

In the context of oil spill cleaning by autonomous vehicles in dynamic and uncertain environments, this paper presents a multi-resolution algorithm that seamlessly integrates the concepts of local navigation and global navigation based on the sensory information; the objective here is to enable adaptive decision making and online replanning of vehicle paths. The proposed algorithm provides a complete coverage of the search area for clean-up of the oil spills and does not suffer from the problem of having local minima, which is commonly encountered in potential-field-based methods. The efficacy of the algorithm is tested on a high-fidelity player/stage simulator for oil spill cleaning in a harbour, where the underlying oil weathering process is modelled as 2D random-walk particle tracking. A preliminary version of this paper was presented by X. Jin and A. Ray as 'Coverage Control of Autonomous Vehicles for Oil Spill Cleaning in Dynamic and Uncertain Environments', Proceedings of the American Control Conference, Washington, DC, June 2013, pp. 2600-2605.

The Trans-Contextual Model of Autonomous Motivation in Education

PubMed Central

Hagger, Martin S.; Chatzisarantis, Nikos L. D.

2015-01-01

The trans-contextual model outlines the processes by which autonomous motivation toward activities in a physical education context predicts autonomous motivation toward physical activity outside of school, and beliefs about, intentions toward, and actual engagement in, out-of-school physical activity. In the present article, we clarify the fundamental propositions of the model and resolve some outstanding conceptual issues, including its generalizability across multiple educational domains, criteria for its rejection or failed replication, the role of belief-based antecedents of intentions, and the causal ordering of its constructs. We also evaluate the consistency of model relationships in previous tests of the model using path-analytic meta-analysis. The analysis supported model hypotheses but identified substantial heterogeneity in the hypothesized relationships across studies unattributed to sampling and measurement error. Based on our meta-analysis, future research needs to provide further replications of the model in diverse educational settings beyond physical education and test model hypotheses using experimental methods. PMID:27274585

Real-Time Hazard Detection and Avoidance Demonstration for a Planetary Lander

NASA Technical Reports Server (NTRS)

Epp, Chirold D.; Robertson, Edward A.; Carson, John M., III

2014-01-01

The Autonomous Landing Hazard Avoidance Technology (ALHAT) Project is chartered to develop and mature to a Technology Readiness Level (TRL) of six an autonomous system combining guidance, navigation and control with terrain sensing and recognition functions for crewed, cargo, and robotic planetary landing vehicles. In addition to precision landing close to a pre-mission defined landing location, the ALHAT System must be capable of autonomously identifying and avoiding surface hazards in real-time to enable a safe landing under any lighting conditions. This paper provides an overview of the recent results of the ALHAT closed loop hazard detection and avoidance flight demonstrations on the Morpheus Vertical Testbed (VTB) at the Kennedy Space Center, including results and lessons learned. This effort is also described in the context of a technology path in support of future crewed and robotic planetary exploration missions based upon the core sensing functions of the ALHAT system: Terrain Relative Navigation (TRN), Hazard Detection and Avoidance (HDA), and Hazard Relative Navigation (HRN).

Reactive navigation for autonomous guided vehicle using neuro-fuzzy techniques

NASA Astrophysics Data System (ADS)

Cao, Jin; Liao, Xiaoqun; Hall, Ernest L.

1999-08-01

A Neuro-fuzzy control method for navigation of an Autonomous Guided Vehicle robot is described. Robot navigation is defined as the guiding of a mobile robot to a desired destination or along a desired path in an environment characterized by as terrain and a set of distinct objects, such as obstacles and landmarks. The autonomous navigate ability and road following precision are mainly influenced by its control strategy and real-time control performance. Neural network and fuzzy logic control techniques can improve real-time control performance for mobile robot due to its high robustness and error-tolerance ability. For a mobile robot to navigate automatically and rapidly, an important factor is to identify and classify mobile robots' currently perceptual environment. In this paper, a new approach of the current perceptual environment feature identification and classification, which are based on the analysis of the classifying neural network and the Neuro- fuzzy algorithm, is presented. The significance of this work lies in the development of a new method for mobile robot navigation.

Autonomous Navigation for Deep Space Missions

NASA Technical Reports Server (NTRS)

Bhaskaran, Shyam

2012-01-01

Navigation (determining where the spacecraft is at any given time, controlling its path to achieve desired targets), performed using ground-in- the-loop techniques: (1) Data includes 2-way radiometric (Doppler, range), interferometric (Delta- Differential One-way Range), and optical (images of natural bodies taken by onboard camera) (2) Data received on the ground, processed to determine orbit, commands sent to execute maneuvers to control orbit. A self-contained, onboard, autonomous navigation system can: (1) Eliminate delays due to round-trip light time (2) Eliminate the human factors in ground-based processing (3) Reduce turnaround time from navigation update to minutes, down to seconds (4) React to late-breaking data. At JPL, we have developed the framework and computational elements of an autonomous navigation system, called AutoNav. It was originally developed as one of the technologies for the Deep Space 1 mission, launched in 1998; subsequently used on three other spacecraft, for four different missions. The primary use has been on comet missions to track comets during flybys, and impact one comet.

The Trans-Contextual Model of Autonomous Motivation in Education: Conceptual and Empirical Issues and Meta-Analysis.

PubMed

Hagger, Martin S; Chatzisarantis, Nikos L D

2016-06-01

The trans-contextual model outlines the processes by which autonomous motivation toward activities in a physical education context predicts autonomous motivation toward physical activity outside of school, and beliefs about, intentions toward, and actual engagement in, out-of-school physical activity. In the present article, we clarify the fundamental propositions of the model and resolve some outstanding conceptual issues, including its generalizability across multiple educational domains, criteria for its rejection or failed replication, the role of belief-based antecedents of intentions, and the causal ordering of its constructs. We also evaluate the consistency of model relationships in previous tests of the model using path-analytic meta-analysis. The analysis supported model hypotheses but identified substantial heterogeneity in the hypothesized relationships across studies unattributed to sampling and measurement error. Based on our meta-analysis, future research needs to provide further replications of the model in diverse educational settings beyond physical education and test model hypotheses using experimental methods.

Terrain discovery and navigation of a multi-articulated linear robot using map-seeking circuits

NASA Astrophysics Data System (ADS)

Snider, Ross K.; Arathorn, David W.

2006-05-01

A significant challenge in robotics is providing a robot with the ability to sense its environment and then autonomously move while accommodating obstacles. The DARPA Grand Challenge, one of the most visible examples, set the goal of driving a vehicle autonomously for over a hundred miles avoiding obstacles along a predetermined path. Map-Seeking Circuits have shown their biomimetic capability in both vision and inverse kinematics and here we demonstrate their potential usefulness for intelligent exploration of unknown terrain using a multi-articulated linear robot. A robot that could handle any degree of terrain complexity would be useful for exploring inaccessible crowded spaces such as rubble piles in emergency situations, patrolling/intelligence gathering in tough terrain, tunnel exploration, and possibly even planetary exploration. Here we simulate autonomous exploratory navigation by an interaction of terrain discovery using the multi-articulated linear robot to build a local terrain map and exploitation of that growing terrain map to solve the propulsion problem of the robot.

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.

Automated flight path planning for virtual endoscopy.

PubMed

Paik, D S; Beaulieu, C F; Jeffrey, R B; Rubin, G D; Napel, S

1998-05-01

In this paper, a novel technique for rapid and automatic computation of flight paths for guiding virtual endoscopic exploration of three-dimensional medical images is described. While manually planning flight paths is a tedious and time consuming task, our algorithm is automated and fast. Our method for positioning the virtual camera is based on the medial axis transform but is much more computationally efficient. By iteratively correcting a path toward the medial axis, the necessity of evaluating simple point criteria during morphological thinning is eliminated. The virtual camera is also oriented in a stable viewing direction, avoiding sudden twists and turns. We tested our algorithm on volumetric data sets of eight colons, one aorta and one bronchial tree. The algorithm computed the flight paths in several minutes per volume on an inexpensive workstation with minimal computation time added for multiple paths through branching structures (10%-13% per extra path). The results of our algorithm are smooth, centralized paths that aid in the task of navigation in virtual endoscopic exploration of three-dimensional medical images.

Comparison of tablet-based strategies for incision planning in laser microsurgery

NASA Astrophysics Data System (ADS)

Schoob, Andreas; Lekon, Stefan; Kundrat, Dennis; Kahrs, Lüder A.; Mattos, Leonardo S.; Ortmaier, Tobias

2015-03-01

Recent research has revealed that incision planning in laser surgery deploying stylus and tablet outperforms state-of-the-art micro-manipulator-based laser control. Providing more detailed quantitation regarding that approach, a comparative study of six tablet-based strategies for laser path planning is presented. Reference strategy is defined by monoscopic visualization and continuous path drawing on a graphics tablet. Further concepts deploying stereoscopic or a synthesized laser view, point-based path definition, real-time teleoperation or a pen display are compared with the reference scenario. Volunteers were asked to redraw and ablate stamped lines on a sample. Performance is assessed by measuring planning accuracy, completion time and ease of use. Results demonstrate that significant differences exist between proposed concepts. The reference strategy provides more accurate incision planning than the stereo or laser view scenario. Real-time teleoperation performs best with respect to completion time without indicating any significant deviation in accuracy and usability. Point-based planning as well as the pen display provide most accurate planning and increased ease of use compared to the reference strategy. As a result, combining the pen display approach with point-based planning has potential to become a powerful strategy because of benefiting from improved hand-eye-coordination on the one hand and from a simple but accurate technique for path definition on the other hand. These findings as well as the overall usability scale indicating high acceptance and consistence of proposed strategies motivate further advanced tablet-based planning in laser microsurgery.

The antecedents and consequences of autonomous self-regulation for college: a self-determination theory perspective on socialization.

PubMed

Niemiec, Christopher P; Lynch, Martin F; Vansteenkiste, Maarten; Bernstein, Jessey; Deci, Edward L; Ryan, Richard M

2006-10-01

Using self-determination theory, two studies investigated the relations among perceived need support from parents, their adolescents' autonomous self-regulation for academics, and the adolescents' well-being. Study 1 indicated that perceived need support from parents independently predicted adolescents' well-being, although when mothers' and fathers' data were examined separately, the relation was stronger for mothers than for fathers. In Study 2, autonomous self-regulation for planning to attend college was a significant partial mediator of the relation of adolescents' perceived need support to well-being. Thus, perceived need support from parents does seem important for the development of adolescents' autonomous self-regulation and well-being.

Implementation and Simulation Results using Autonomous Aerobraking Development Software

NASA Technical Reports Server (NTRS)

Maddock, Robert W.; DwyerCianciolo, Alicia M.; Bowes, Angela; Prince, Jill L. H.; Powell, Richard W.

2011-01-01

An Autonomous Aerobraking software system is currently under development with support from the NASA Engineering and Safety Center (NESC) that would move typically ground-based operations functions to onboard an aerobraking spacecraft, reducing mission risk and mission cost. The suite of software that will enable autonomous aerobraking is the Autonomous Aerobraking Development Software (AADS) and consists of an ephemeris model, onboard atmosphere estimator, temperature and loads prediction, and a maneuver calculation. The software calculates the maneuver time, magnitude and direction commands to maintain the spacecraft periapsis parameters within design structural load and/or thermal constraints. The AADS is currently tested in simulations at Mars, with plans to also evaluate feasibility and performance at Venus and Titan.

Automatic Operation For A Robot Lawn Mower

NASA Astrophysics Data System (ADS)

Huang, Y. Y.; Cao, Z. L.; Oh, S. J.; Kattan, E. U.; Hall, E. L.

1987-02-01

A domestic mobile robot, lawn mower, which performs the automatic operation mode, has been built up in the Center of Robotics Research, University of Cincinnati. The robot lawn mower automatically completes its work with the region filling operation, a new kind of path planning for mobile robots. Some strategies for region filling of path planning have been developed for a partly-known or a unknown environment. Also, an advanced omnidirectional navigation system and a multisensor-based control system are used in the automatic operation. Research on the robot lawn mower, especially on the region filling of path planning, is significant in industrial and agricultural applications.

Multi Robot Path Planning for Budgeted Active Perception with Self-Organising Maps

DTIC Science & Technology

2016-10-04

Multi- Robot Path Planning for Budgeted Active Perception with Self-Organising Maps Graeme Best1, Jan Faigl2 and Robert Fitch1 Abstract— We propose a...optimise paths for a multi- robot team that aims to maximally observe a set of nodes in the environment. The selected nodes are observed by visiting...regions, each node has an observation reward, and the robots are constrained by travel budgets. The SOM algorithm jointly selects and allocates nodes

Autonomous navigation - The ARMMS concept. [Autonomous Redundancy and Maintenance Management Subsystem

NASA Technical Reports Server (NTRS)

Wood, L. J.; Jones, J. B.; Mease, K. D.; Kwok, J. H.; Goltz, G. L.; Kechichian, J. A.

1984-01-01

A conceptual design is outlined for the navigation subsystem of the Autonomous Redundancy and Maintenance Management Subsystem (ARMMS). The principal function of this navigation subsystem is to maintain the spacecraft over a specified equatorial longitude to within + or - 3 deg. In addition, the navigation subsystem must detect and correct internal faults. It comprises elements for a navigation executive and for orbit determination, trajectory, maneuver planning, and maneuver command. Each of these elements is described. The navigation subsystem is to be used in the DSCS III spacecraft.

Planning collision free paths for two cooperating robots using a divide-and-conquer C-space traversal heuristic

NASA Technical Reports Server (NTRS)

Weaver, Johnathan M.

1993-01-01

A method was developed to plan feasible and obstacle-avoiding paths for two spatial robots working cooperatively in a known static environment. Cooperating spatial robots as referred to herein are robots which work in 6D task space while simultaneously grasping and manipulating a common, rigid payload. The approach is configuration space (c-space) based and performs selective rather than exhaustive c-space mapping. No expensive precomputations are required. A novel, divide-and-conquer type of heuristic is used to guide the selective mapping process. The heuristic does not involve any robot, environment, or task specific assumptions. A technique was also developed which enables solution of the cooperating redundant robot path planning problem without requiring the use of inverse kinematics for a redundant robot. The path planning strategy involves first attempting to traverse along the configuration space vector from the start point towards the goal point. If an unsafe region is encountered, an intermediate via point is identified by conducting a systematic search in the hyperplane orthogonal to and bisecting the unsafe region of the vector. This process is repeatedly applied until a solution to the global path planning problem is obtained. The basic concept behind this strategy is that better local decisions at the beginning of the trouble region may be made if a possible way around the 'center' of the trouble region is known. Thus, rather than attempting paths which look promising locally (at the beginning of a trouble region) but which may not yield overall results, the heuristic attempts local strategies that appear promising for circumventing the unsafe region.

Planning minimum-energy paths in an off-road environment with anisotropic traversal costs and motion constraints. Doctoral thesis

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

Ross, R.S.

1989-06-01

For a vehicle operating across arbitrarily-contoured terrain, finding the most fuel-efficient route between two points can be viewed as a high-level global path-planning problem with traversal costs and stability dependent on the direction of travel (anisotropic). The problem assumes a two-dimensional polygonal map of homogeneous cost regions for terrain representation constructed from elevation information. The anisotropic energy cost of vehicle motion has a non-braking component dependent on horizontal distance, a braking component dependent on vertical distance, and a constant path-independent component. The behavior of minimum-energy paths is then proved to be restricted to a small, but optimal set of traversalmore » types. An optimal-path-planning algorithm, using a heuristic search technique, reduces the infinite number of paths between the start and goal points to a finite number by generating sequences of goal-feasible window lists from analyzing the polygonal map and applying pruning criteria. The pruning criteria consist of visibility analysis, heading analysis, and region-boundary constraints. Each goal-feasible window lists specifies an associated convex optimization problem, and the best of all locally-optimal paths through the goal-feasible window lists is the globally-optimal path. These ideas have been implemented in a computer program, with results showing considerably better performance than the exponential average-case behavior predicted.« less

Path planning of decentralized multi-quadrotor based on fuzzy-cell decomposition algorithm

NASA Astrophysics Data System (ADS)

Iswanto, Wahyunggoro, Oyas; Cahyadi, Adha Imam

2017-04-01

The paper aims to present a design algorithm for multi quadrotor lanes in order to move towards the goal quickly and avoid obstacles in an area with obstacles. There are several problems in path planning including how to get to the goal position quickly and avoid static and dynamic obstacles. To overcome the problem, therefore, the paper presents fuzzy logic algorithm and fuzzy cell decomposition algorithm. Fuzzy logic algorithm is one of the artificial intelligence algorithms which can be applied to robot path planning that is able to detect static and dynamic obstacles. Cell decomposition algorithm is an algorithm of graph theory used to make a robot path map. By using the two algorithms the robot is able to get to the goal position and avoid obstacles but it takes a considerable time because they are able to find the shortest path. Therefore, this paper describes a modification of the algorithms by adding a potential field algorithm used to provide weight values on the map applied for each quadrotor by using decentralized controlled, so that the quadrotor is able to move to the goal position quickly by finding the shortest path. The simulations conducted have shown that multi-quadrotor can avoid various obstacles and find the shortest path by using the proposed algorithms.

A Spatial Cognitive Map and a Human-Like Memory Model Dedicated to Pedestrian Navigation in Virtual Urban Environments

NASA Astrophysics Data System (ADS)

Thomas, Romain; Donikian, Stéphane

Many articles dealing with agent navigation in an urban environment involve the use of various heuristics. Among them, one is prevalent: the search of the shortest path between two points. This strategy impairs the realism of the resulting behaviour. Indeed, psychological studies state that such a navigation behaviour is conditioned by the knowledge the subject has of its environment. Furthermore, the path a city dweller can follow may be influenced by many factors like his daily habits, or the path simplicity in term of minimum of direction changes. It appeared interesting to us to investigate how to mimic human navigation behavior with an autonomous agent. The solution we propose relies on an architecture based on a generic model of informed environment, a spatial cognitive map model merged with a human-like memory model, representing the agent's temporal knowledge of the environment, it gained along its experiences of navigation.

A DNA-based molecular motor that can navigate a network of tracks

NASA Astrophysics Data System (ADS)

Wickham, Shelley F. J.; Bath, Jonathan; Katsuda, Yousuke; Endo, Masayuki; Hidaka, Kumi; Sugiyama, Hiroshi; Turberfield, Andrew J.

2012-03-01

Synthetic molecular motors can be fuelled by the hydrolysis or hybridization of DNA. Such motors can move autonomously and programmably, and long-range transport has been observed on linear tracks. It has also been shown that DNA systems can compute. Here, we report a synthetic DNA-based system that integrates long-range transport and information processing. We show that the path of a motor through a network of tracks containing four possible routes can be programmed using instructions that are added externally or carried by the motor itself. When external control is used we find that 87% of the motors follow the correct path, and when internal control is used 71% of the motors follow the correct path. Programmable motion will allow the development of computing networks, molecular systems that can sort and process cargoes according to instructions that they carry, and assembly lines that can be reconfigured dynamically in response to changing demands.

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.

GPU: the biggest key processor for AI and parallel processing

NASA Astrophysics Data System (ADS)

Baji, Toru

2017-07-01

Two types of processors exist in the market. One is the conventional CPU and the other is Graphic Processor Unit (GPU). Typical CPU is composed of 1 to 8 cores while GPU has thousands of cores. CPU is good for sequential processing, while GPU is good to accelerate software with heavy parallel executions. GPU was initially dedicated for 3D graphics. However from 2006, when GPU started to apply general-purpose cores, it was noticed that this architecture can be used as a general purpose massive-parallel processor. NVIDIA developed a software framework Compute Unified Device Architecture (CUDA) that make it possible to easily program the GPU for these application. With CUDA, GPU started to be used in workstations and supercomputers widely. Recently two key technologies are highlighted in the industry. The Artificial Intelligence (AI) and Autonomous Driving Cars. AI requires a massive parallel operation to train many-layers of neural networks. With CPU alone, it was impossible to finish the training in a practical time. The latest multi-GPU system with P100 makes it possible to finish the training in a few hours. For the autonomous driving cars, TOPS class of performance is required to implement perception, localization, path planning processing and again SoC with integrated GPU will play a key role there. In this paper, the evolution of the GPU which is one of the biggest commercial devices requiring state-of-the-art fabrication technology will be introduced. Also overview of the GPU demanding key application like the ones described above will be introduced.

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.

[Sustainability focus in the health plans of the autonomous communities: sustainable development as an opportunity].

PubMed

Moyano-Santiago, Miguel A; Rivera-Lirio, Juana M

2016-01-01

To determine the degree to which the health plans of the autonomous communities focus on the usual three dimensions of sustainability: economic, social and environmental, both in the general level of discourse and in the different areas of intervention. A qualitative study was conducted through content analysis of a large sample of documents. The specific methodology was analysis of symbolic and operational sensitivity in a sample of eleven health plans of the Spanish state. Social aspects, such as social determinants or vulnerable groups, are receiving increasing attention from the health planner, although there is room to strengthen attention to environmental issues and to provide specific interventions in economic terms. The analysis demonstrates the incipient state of health plans as strategic planning documents that integrate economic, social and environmental aspects and contribute to the sustainability of the different health systems of the country. Copyright © 2016 SESPAS. Published by Elsevier Espana. All rights reserved.

The Next Generation of Mars-GRAM and Its Role in the Autonomous Aerobraking Development Plan

NASA Technical Reports Server (NTRS)

Justh, Hilary L.; Justus, Carl G.; Ramey, Holly S.

2011-01-01

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission applications. Mars-GRAM 2010 is currently being used to develop the onboard atmospheric density estimator that is part of the Autonomous Aerobraking Development Plan. In previous versions, Mars-GRAM was less than realistic when used for sensitivity studies for Thermal Emission Spectrometer (TES) MapYear=0 and large optical depth values, such as tau=3. A comparison analysis has been completed between Mars-GRAM, TES and data from the Planetary Data System (PDS) resulting in updated coefficients for the functions relating density, latitude, and longitude of the sun. The adjustment factors are expressed as a function of height (z), Latitude (Lat) and areocentric solar longitude (Ls). The latest release of Mars-GRAM 2010 includes these adjustment factors that alter the in-put data from MGCM and MTGCM for the Mapping Year 0 (user-controlled dust) case. The greatest adjustment occurs at large optical depths such as tau greater than 1. The addition of the adjustment factors has led to better correspondence to TES Limb data from 0-60 km as well as better agreement with MGS, ODY and MRO data at approximately 90-135 km. Improved simulations utilizing Mars-GRAM 2010 are vital to developing the onboard atmospheric density estimator for the Autonomous Aerobraking Development Plan. Mars-GRAM 2010 was not the only planetary GRAM utilized during phase 1 of this plan; Titan-GRAM and Venus-GRAM were used to generate density data sets for Aerobraking Design Reference Missions. These data sets included altitude profiles (both vertical and along a trajectory), GRAM perturbations (tides, gravity waves, etc.) and provided density and scale height values for analysis by other Autonomous Aero-braking team members.

The intertwining paths of the density managment and riparian buffer study and the Northwest Forest Plan

Treesearch

Kenneth J. Ruzicka; Deanna H. Olson; Klaus J. Puettmann

2013-01-01

Initiated simultaneously, the Density Management and Riparian Buff er Study of western Oregon and the Northwest Forest Plan have had intertwining paths related to federal forest management and policy changes in the Pacifi c Northwest over the last 15 to 20 years. We briefl y discuss the development of the Northwest Forest Plan and how it changed the way forest policy...

The Integrated Curriculum of "Planned Approach to Healthier Schools"

ERIC Educational Resources Information Center

Lounsbery, Monica; Gast, Julie; Smith, Nicole

2005-01-01

Planned Approach to Healthier Schools (PATHS) is a multicomponent school program that aims to establish and sustain a social norm consistent with physical activity and healthy nutrition in the school community. The PATHS components include: (1) a professional development and wellness program for faculty and staff; (2) ongoing social-marketing…

32. ISOMETRIC VIEW OF PIPING PLAN, SHOWING PATH OF CONDUIT ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

32. ISOMETRIC VIEW OF PIPING PLAN, SHOWING PATH OF CONDUIT FROM CONTROL BUNKER TO SHIELDING TANK. F.C. TORKELSON DRAWING NUMBER 842-ARVFS-701-P-1. INEL INDEX CODE NUMBER: 075 0701 60 851 151977. - Idaho National Engineering Laboratory, Advanced Reentry Vehicle Fusing System, Scoville, Butte County, ID

EPA Critical Path Science Plan Projects 19, 20 and 21: Human and Bovine Source Detection

EPA Science Inventory

The U.S. EPA Critical Path Science Plan Projects are: Project 19: develop novel bovine and human host-specific PCR assays and complete performance evaluation with other published methods. Project 20: Evaluate human-specific assays with water samples impacted with different lev...

Energy-Aware Multipath Routing Scheme Based on Particle Swarm Optimization in Mobile Ad Hoc Networks

PubMed Central

Robinson, Y. Harold; Rajaram, M.

2015-01-01

Mobile ad hoc network (MANET) is a collection of autonomous mobile nodes forming an ad hoc network without fixed infrastructure. Dynamic topology property of MANET may degrade the performance of the network. However, multipath selection is a great challenging task to improve the network lifetime. We proposed an energy-aware multipath routing scheme based on particle swarm optimization (EMPSO) that uses continuous time recurrent neural network (CTRNN) to solve optimization problems. CTRNN finds the optimal loop-free paths to solve link disjoint paths in a MANET. The CTRNN is used as an optimum path selection technique that produces a set of optimal paths between source and destination. In CTRNN, particle swarm optimization (PSO) method is primly used for training the RNN. The proposed scheme uses the reliability measures such as transmission cost, energy factor, and the optimal traffic ratio between source and destination to increase routing performance. In this scheme, optimal loop-free paths can be found using PSO to seek better link quality nodes in route discovery phase. PSO optimizes a problem by iteratively trying to get a better solution with regard to a measure of quality. The proposed scheme discovers multiple loop-free paths by using PSO technique. PMID:26819966

Task-level control for autonomous robots

NASA Technical Reports Server (NTRS)

Simmons, Reid

1994-01-01

Task-level control refers to the integration and coordination of planning, perception, and real-time control to achieve given high-level goals. Autonomous mobile robots need task-level control to effectively achieve complex tasks in uncertain, dynamic environments. This paper describes the Task Control Architecture (TCA), an implemented system that provides commonly needed constructs for task-level control. Facilities provided by TCA include distributed communication, task decomposition and sequencing, resource management, monitoring and exception handling. TCA supports a design methodology in which robot systems are developed incrementally, starting first with deliberative plans that work in nominal situations, and then layering them with reactive behaviors that monitor plan execution and handle exceptions. To further support this approach, design and analysis tools are under development to provide ways of graphically viewing the system and validating its behavior.

In-Space Networking On NASA's SCaN Testbed

NASA Technical Reports Server (NTRS)

Brooks, David; Eddy, Wesley M.; Clark, Gilbert J., III; Johnson, Sandra K.

2016-01-01

The NASA Space Communications and Navigation (SCaN) Testbed, an external payload onboard the International Space Station, is equipped with three software defined radios (SDRs) and a programmable flight computer. The purpose of the Testbed is to conduct inspace research in the areas of communication, navigation, and networking in support of NASA missions and communication infrastructure. Multiple reprogrammable elements in the end to end system, along with several communication paths and a semi-operational environment, provides a unique opportunity to explore networking concepts and protocols envisioned for the future Solar System Internet (SSI). This paper will provide a general description of the system's design and the networking protocols implemented and characterized on the testbed, including Encapsulation, IP over CCSDS, and Delay-Tolerant Networking (DTN). Due to the research nature of the implementation, flexibility and robustness are considered in the design to enable expansion for future adaptive and cognitive techniques. Following a detailed design discussion, lessons learned and suggestions for future missions and communication infrastructure elements will be provided. Plans for the evolving research on SCaN Testbed as it moves towards a more adaptive, autonomous system will be discussed.

Full practice authority--effecting change and improving access to care: the Nevada journey.

PubMed

VanBeuge, Susan S; Walker, Tomas

2014-06-01

In 2013, Nevada shifted from a collaborative practice model to full practice authority. Given the challenges many states still face, this article provides an outline of the evolution of the "nurse practitioner" (NP) in Nevada. Reviewing the path Nevada took toward full practice authority, we hope to provide insight including lessons learned and opposition encountered to assist other states working toward full practice authority. Literature searches were conducted on PubMed and MEDLINE. Search terms included "autonomous practice," "nurse practitioner," and "full practice authority." Healthcare reform will require nurse practitioners committed to legislative change. Nurse practitioners have the knowledge and ability to affect the legislative process and improve patients' access to care. With careful planning, full engagement, and team building, making a statute change is possible and should be seriously considered in states still struggling with collaborative relationships. Nurse practitioners are well situated to provide primary care in the United States. Removing barriers to practice through statute change will empower NPs to effect positive change in our struggling healthcare system. ©2014 The Author(s) ©2014 American Association of Nurse Practitioners.

Path Finding for Maximum Value of Information in Multi-Modal Underwater Wireless Sensor Networks

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

Gjanci, Petrika; Petrioli, Chiara; Basagni, Stefano

Here, we consider underwater multi-modal wireless sensor networks (UWSNs) suitable for applications on submarine surveillance and monitoring, where nodes offload data to a mobile autonomous underwater vehicle (AUV) via optical technology, and coordinate using acoustic communication. Sensed data are associated with a value, decaying in time. In this scenario, we address the problem of finding the path of the AUV so that the Value of Information (VoI) of the data delivered to a sink on the surface is maximized. We define a Greedy and Adaptive AUV Path-finding (GAAP) heuristic that drives the AUV to collect data from nodes depending onmore » the VoI of their data. For benchmarking the performance of AUV path-finding heuristics, we define an integer linear programming (ILP) formulation that accurately models the considered scenario, deriving a path that drives the AUV to collect and deliver data with the maximum VoI. In our experiments GAAP consistently delivers more than 80 percent of the theoretical maximum VoI determined by the ILP model. We also compare the performance of GAAP with that of other strategies for driving the AUV among sensing nodes, namely, random paths, TSP-based paths and a “lawn mower”-like strategy. Our results show that GAAP always outperforms every other heuristic in terms of delivered VoI, also obtaining higher energy efficiency.« less

Path Finding for Maximum Value of Information in Multi-Modal Underwater Wireless Sensor Networks

DOE PAGES

Gjanci, Petrika; Petrioli, Chiara; Basagni, Stefano; ...

2017-05-19

Here, we consider underwater multi-modal wireless sensor networks (UWSNs) suitable for applications on submarine surveillance and monitoring, where nodes offload data to a mobile autonomous underwater vehicle (AUV) via optical technology, and coordinate using acoustic communication. Sensed data are associated with a value, decaying in time. In this scenario, we address the problem of finding the path of the AUV so that the Value of Information (VoI) of the data delivered to a sink on the surface is maximized. We define a Greedy and Adaptive AUV Path-finding (GAAP) heuristic that drives the AUV to collect data from nodes depending onmore » the VoI of their data. For benchmarking the performance of AUV path-finding heuristics, we define an integer linear programming (ILP) formulation that accurately models the considered scenario, deriving a path that drives the AUV to collect and deliver data with the maximum VoI. In our experiments GAAP consistently delivers more than 80 percent of the theoretical maximum VoI determined by the ILP model. We also compare the performance of GAAP with that of other strategies for driving the AUV among sensing nodes, namely, random paths, TSP-based paths and a “lawn mower”-like strategy. Our results show that GAAP always outperforms every other heuristic in terms of delivered VoI, also obtaining higher energy efficiency.« less

Interactions of information transfer along separable causal paths

NASA Astrophysics Data System (ADS)

Jiang, Peishi; Kumar, Praveen

2018-04-01

Complex systems arise as a result of interdependences between multiple variables, whose causal interactions can be visualized in a time-series graph. Transfer entropy and information partitioning approaches have been used to characterize such dependences. However, these approaches capture net information transfer occurring through a multitude of pathways involved in the interaction and as a result mask our ability to discern the causal interaction within a subgraph of interest through specific pathways. We build on recent developments of momentary information transfer along causal paths proposed by Runge [Phys. Rev. E 92, 062829 (2015), 10.1103/PhysRevE.92.062829] to develop a framework for quantifying information partitioning along separable causal paths. Momentary information transfer along causal paths captures the amount of information transfer between any two variables lagged at two specific points in time. Our approach expands this concept to characterize the causal interaction in terms of synergistic, unique, and redundant information transfer through separable causal paths. Through a graphical model, we analyze the impact of the separable and nonseparable causal paths and the causality structure embedded in the graph as well as the noise effect on information partitioning by using synthetic data generated from two coupled logistic equation models. Our approach can provide a valuable reference for an autonomous information partitioning along separable causal paths which form a causal subgraph influencing a target.

Planning for the V&V of infused software technologies for the Mars Science Laboratory Mission

NASA Technical Reports Server (NTRS)

Feather, Martin S.; Fesq, Lorraine M.; Ingham, Michel D.; Klein, Suzanne L.; Nelson, Stacy D.

2004-01-01

NASA's Mars Science Laboratory (MSL) rover mission is planning to make use of advanced software technologies in order to support fulfillment of its ambitious science objectives. The mission plans to adopt the Mission Data System (MDS) as the mission software architecture, and plans to make significant use of on-board autonomous capabilities for the rover software.

Automation Improvements for Synchrotron Based Small Angle Scattering Using an Inexpensive Robotics Platform

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

Quintana, John P.

This paper reports on the progress toward creating semi-autonomous motion control platforms for beamline applications using the iRobot Create registered platform. The goal is to create beamline research instrumentation where the motion paths are based on the local environment rather than position commanded from a control system, have low integration costs and also be scalable and easily maintainable.

Integrated mobile robot control

NASA Technical Reports Server (NTRS)

Amidi, Omead; Thorpe, Charles

1991-01-01

This paper describes the structure, implementation, and operation of a real-time mobile robot controller which integrates capabilities such as: position estimation, path specification and tracking, human interfaces, fast communication, and multiple client support. The benefits of such high-level capabilities in a low-level controller was shown by its implementation for the Navlab autonomous vehicle. In addition, performance results from positioning and tracking systems are reported and analyzed.

Hierarchical Control of Semi-Autonomous Teams Under Uncertainty (HICST)

DTIC Science & Technology

2004-05-01

17 2.4 Module 4: Database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.5... Database SoW 1 2 34 5 Txt file: paths Figure 3: Integration of modules 1-5. The modules make provision for human intervention, not indicated in the...figure. SoW is ‘state of the world’. 3. Task execution; 4. Database for state estimation; 5. Java interface to OEP; 6. Robust dynamic programming for

Integrated mobile robot control

NASA Astrophysics Data System (ADS)

Amidi, Omead; Thorpe, Chuck E.

1991-03-01

This paper describes the strucwre implementation and operation of a real-time mobile robot controller which integrates capabilities such as: position estimation path specification and hacking human interfaces fast communication and multiple client support The benefits of such high-level capabilities in a low-level controller was shown by its implementation for the Naviab autonomous vehicle. In addition performance results from positioning and tracking systems are reported and analyzed.

Preliminary Design of an Autonomous Amphibious System

DTIC Science & Technology

2016-09-01

changing vehicle dynamics will require innovative new autonomy algorithms. The developed software architecture, drive-by- wire kit, and supporting...COMMUNICATIONS ARCHITECTURE .................................................12 3.3 DRIVE-BY- WIRE DESIGN...SOFTWARE MATURATION PLANS ......................................................17 4.2 DRIVE-BY- WIRE PLANNED REFINEMENT

Distributed autonomous systems: resource management, planning, and control algorithms

NASA Astrophysics Data System (ADS)

Smith, James F., III; Nguyen, ThanhVu H.

2005-05-01

Distributed autonomous systems, i.e., systems that have separated distributed components, each of which, exhibit some degree of autonomy are increasingly providing solutions to naval and other DoD problems. Recently developed control, planning and resource allocation algorithms for two types of distributed autonomous systems will be discussed. The first distributed autonomous system (DAS) to be discussed consists of a collection of unmanned aerial vehicles (UAVs) that are under fuzzy logic control. The UAVs fly and conduct meteorological sampling in a coordinated fashion determined by their fuzzy logic controllers to determine the atmospheric index of refraction. Once in flight no human intervention is required. A fuzzy planning algorithm determines the optimal trajectory, sampling rate and pattern for the UAVs and an interferometer platform while taking into account risk, reliability, priority for sampling in certain regions, fuel limitations, mission cost, and related uncertainties. The real-time fuzzy control algorithm running on each UAV will give the UAV limited autonomy allowing it to change course immediately without consulting with any commander, request other UAVs to help it, alter its sampling pattern and rate when observing interesting phenomena, or to terminate the mission and return to base. The algorithms developed will be compared to a resource manager (RM) developed for another DAS problem related to electronic attack (EA). This RM is based on fuzzy logic and optimized by evolutionary algorithms. It allows a group of dissimilar platforms to use EA resources distributed throughout the group. For both DAS types significant theoretical and simulation results will be presented.

Autonomous control systems - Architecture and fundamental issues

NASA Technical Reports Server (NTRS)

Antsaklis, P. J.; Passino, K. M.; Wang, S. J.

1988-01-01

A hierarchical functional autonomous controller architecture is introduced. In particular, the architecture for the control of future space vehicles is described in detail; it is designed to ensure the autonomous operation of the control system and it allows interaction with the pilot and crew/ground station, and the systems on board the autonomous vehicle. The fundamental issues in autonomous control system modeling and analysis are discussed. It is proposed to utilize a hybrid approach to modeling and analysis of autonomous systems. This will incorporate conventional control methods based on differential equations and techniques for the analysis of systems described with a symbolic formalism. In this way, the theory of conventional control can be fully utilized. It is stressed that autonomy is the design requirement and intelligent control methods appear at present, to offer some of the necessary tools to achieve autonomy. A conventional approach may evolve and replace some or all of the `intelligent' functions. It is shown that in addition to conventional controllers, the autonomous control system incorporates planning, learning, and FDI (fault detection and identification).

Remote mission specialist - A study in real-time, adaptive planning

NASA Technical Reports Server (NTRS)

Rokey, Mark J.

1990-01-01

A high-level planning architecture for robotic operations is presented. The remote mission specialist integrates high-level directives with low-level primitives executable by a run-time controller for command of autonomous servicing activities. The planner has been designed to address such issues as adaptive plan generation, real-time performance, and operator intervention.

Current-Sensitive Path Planning for an Underactuated Free-Floating Ocean Sensorweb

NASA Technical Reports Server (NTRS)

Dahl, Kristen P.; Thompson, David R.; McLaren, David; Chao, Yi; Chien, Steve

2011-01-01

This work investigates multi-agent path planning in strong, dynamic currents using thousands of highly under-actuated vehicles. We address the specific task of path planning for a global network of ocean-observing floats. These submersibles are typified by the Argo global network consisting of over 3000 sensor platforms. They can control their buoyancy to float at depth for data collection or rise to the surface for satellite communications. Currently, floats drift at a constant depth regardless of the local currents. However, accurate current forecasts have become available which present the possibility of intentionally controlling floats' motion by dynamically commanding them to linger at different depths. This project explores the use of these current predictions to direct float networks to some desired final formation or position. It presents multiple algorithms for such path optimization and demonstrates their advantage over the standard approach of constant-depth drifting.

[Gender and career paths of female primary care physicians in Andalusia, Spain, at the beginning of 21st century].

PubMed

Saletti-Cuesta, Lorena; Delgado, Ana; Ortiz-Gómez, Teresa

2014-12-01

The purpose of this article was to study, from a feminist perspective, the diversity and homogeneity in the career paths of female primary care physicians from Andalusia, Spain in the early 21st century, by analyzing the meanings they give to their careers and the influence of personal, family and professional factors. We conducted a qualitative study with six discussion groups. Thirty-two female primary care physicians working in urban health centers of the public health system of Andalusia participated in the study. The discourse analysis revealed that most of the female physicians did not plan for professional goals and, when they did plan for them, the goals were intertwined with family needs. Consequently, their career paths were discontinuous. In contrast, career paths oriented towards professional development and the conscious planning of goals were more common among the female doctors acting as directors of health care centers.

Simultaneous Planning and Control for Autonomous Ground Vehicles

DTIC Science & Technology

2009-02-01

these applications is called A * ( A -star), and it was originally developed by Hart, Nilsson, and Raphael [HAR68]. Their research presented the formal...sequence, rather than a dynamic programming approach. A * search is a technique originally developed for Artificial Intelligence 43 applications ... developed at the Center for Intelligent Machines and Robotics, serves as a platform for the implementation and testing discussed. autonomous

Perception, planning, and control for walking on rugged terrain

NASA Technical Reports Server (NTRS)

Simmons, Reid; Krotkov, Eric

1991-01-01

The CMU Planetary Rover project is developing a six-legged walking robot capable of autonomously navigating, exploring, and acquiring samples in rugged, unknown environments. To gain experience with the problems involved in walking on rugged terrain, a full-scale prototype leg was built and mounted on a carriage that rolls along overhead rails. Issues addressed in developing the software system to autonomously walk the leg through rugged terrain are described. In particular, the insights gained into perceiving and modeling rugged terrain, controlling the legged mechanism, interacting with the ground, choosing safe yet effective footfalls, and planning efficient leg moves through space are described.

A Forest Fire Sensor Web Concept with UAVSAR

NASA Astrophysics Data System (ADS)

Lou, Y.; Chien, S.; Clark, D.; Doubleday, J.; Muellerschoen, R.; Zheng, Y.

2008-12-01

We developed a forest fire sensor web concept with a UAVSAR-based smart sensor and onboard automated response capability that will allow us to monitor fire progression based on coarse initial information provided by an external source. This autonomous disturbance detection and monitoring system combines the unique capabilities of imaging radar with high throughput onboard processing technology and onboard automated response capability based on specific science algorithms. In this forest fire sensor web scenario, a fire is initially located by MODIS/RapidFire or a ground-based fire observer. This information is transmitted to the UAVSAR onboard automated response system (CASPER). CASPER generates a flight plan to cover the alerted fire area and executes the flight plan. The onboard processor generates the fuel load map from raw radar data, used with wind and elevation information, predicts the likely fire progression. CASPER then autonomously alters the flight plan to track the fire progression, providing this information to the fire fighting team on the ground. We can also relay the precise fire location to other remote sensing assets with autonomous response capability such as Earth Observation-1 (EO-1)'s hyper-spectral imager to acquire the fire data.

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

The navigation system of the JPL robot

NASA Technical Reports Server (NTRS)

Thompson, A. M.

1977-01-01

The control structure of the JPL research robot and the operations of the navigation subsystem are discussed. The robot functions as a network of interacting concurrent processes distributed among several computers and coordinated by a central executive. The results of scene analysis are used to create a segmented terrain model in which surface regions are classified by traversibility. The model is used by a path planning algorithm, PATH, which uses tree search methods to find the optimal path to a goal. In PATH, the search space is defined dynamically as a consequence of node testing. Maze-solving and the use of an associative data base for context dependent node generation are also discussed. Execution of a planned path is accomplished by a feedback guidance process with automatic error recovery.

Interactive Learning Environment for Bio-Inspired Optimization Algorithms for UAV Path Planning

ERIC Educational Resources Information Center

Duan, Haibin; Li, Pei; Shi, Yuhui; Zhang, Xiangyin; Sun, Changhao

2015-01-01

This paper describes the development of BOLE, a MATLAB-based interactive learning environment, that facilitates the process of learning bio-inspired optimization algorithms, and that is dedicated exclusively to unmanned aerial vehicle path planning. As a complement to conventional teaching methods, BOLE is designed to help students consolidate the…

The force control and path planning of electromagnetic induction-based massage robot.

PubMed

Wang, Wendong; Zhang, Lei; Li, Jinzhe; Yuan, Xiaoqing; Shi, Yikai; Jiang, Qinqin; He, Lijing

2017-07-20

Massage robot is considered as an effective physiological treatment to relieve fatigue, improve blood circulation, relax muscle tone, etc. The simple massage equipment quickly spread into market due to low cost, but they are not widely accepted due to restricted massage function. Complicated structure and high cost caused difficulties for developing multi-function massage equipment. This paper presents a novel massage robot which can achieve tapping, rolling, kneading and other massage operations, and proposes an improved reciprocating path planning algorithm to improve massage effect. The number of coil turns, the coil current and the distance between massage head and yoke were chosen to investigate the influence on massage force by finite element method. The control system model of the wheeled massage robot was established, including control subsystem of the motor, path algorithm control subsystem, parameter module of the massage robot and virtual reality interface module. The improved reciprocating path planning algorithm was proposed to improve regional coverage rate and massage effect. The influence caused by coil current, the number of coil turns and the distance between massage head and yoke were simulated in Maxwell. It indicated that coil current has more important influence compared to the other two factors. The path planning simulation of the massage robot was completed in Matlab, and the results show that the improved reciprocating path planning algorithm achieved higher coverage rate than the traditional algorithm. With the analysis of simulation results, it can be concluded that the number of coil turns and the distance between the moving iron core and the yoke could be determined prior to coil current, and the force can be controllable by optimizing structure parameters of massage head and adjusting coil current. Meanwhile, it demonstrates that the proposed algorithm could effectively improve path coverage rate during massage operations, therefore the massage effect can be improved.

An Autonomous Control System for an Intra-Vehicular Spacecraft Mobile Monitor Prototype

NASA Technical Reports Server (NTRS)

Dorais, Gregory A.; Desiano, Salvatore D.; Gawdiak, Yuri; Nicewarner, Keith

2003-01-01

This paper presents an overview of an ongoing research and development effort at the NASA Ames Research Center to create an autonomous control system for an internal spacecraft autonomous mobile monitor. It primary functions are to provide crew support and perform intra- vehicular sensing activities by autonomously navigating onboard the International Space Station. We describe the mission roles and high-level functional requirements for an autonomous mobile monitor. The mobile monitor prototypes, of which two are operational and one is actively being designed, physical test facilities used to perform ground testing, including a 3D micro-gravity test facility, and simulators are briefly described. We provide an overview of the autonomy framework and describe each of its components, including those used for automated planning, goal-oriented task execution, diagnosis, and fault recovery. A sample mission test scenario is also described.

Lessons Learned from Autonomous Sciencecraft Experiment

NASA Technical Reports Server (NTRS)

Chien, Steve A.; Sherwood, Rob; Tran, Daniel; Cichy, Benjamin; Rabideau, Gregg; Castano, Rebecca; Davies, Ashley; Mandl, Dan; Frye, Stuart; Trout, Bruce;

An Analytical Thermal Model for Autonomous Soaring Research

NASA Technical Reports Server (NTRS)

Allen, Michael

2006-01-01

A viewgraph presentation describing an analytical thermal model used to enable research on autonomous soaring for a small UAV aircraft is given. The topics include: 1) Purpose; 2) Approach; 3) SURFRAD Data; 4) Convective Layer Thickness; 5) Surface Heat Budget; 6) Surface Virtual Potential Temperature Flux; 7) Convective Scaling Velocity; 8) Other Calculations; 9) Yearly trends; 10) Scale Factors; 11) Scale Factor Test Matrix; 12) Statistical Model; 13) Updraft Strength Calculation; 14) Updraft Diameter; 15) Updraft Shape; 16) Smoothed Updraft Shape; 17) Updraft Spacing; 18) Environment Sink; 19) Updraft Lifespan; 20) Autonomous Soaring Research; 21) Planned Flight Test; and 22) Mixing Ratio.

Acoustic window planning for ultrasound acquisition.

PubMed

Göbl, Rüdiger; Virga, Salvatore; Rackerseder, Julia; Frisch, Benjamin; Navab, Nassir; Hennersperger, Christoph

2017-06-01

Autonomous robotic ultrasound has recently gained considerable interest, especially for collaborative applications. Existing methods for acquisition trajectory planning are solely based on geometrical considerations, such as the pose of the transducer with respect to the patient surface. This work aims at establishing acoustic window planning to enable autonomous ultrasound acquisitions of anatomies with restricted acoustic windows, such as the liver or the heart. We propose a fully automatic approach for the planning of acquisition trajectories, which only requires information about the target region as well as existing tomographic imaging data, such as X-ray computed tomography. The framework integrates both geometrical and physics-based constraints to estimate the best ultrasound acquisition trajectories with respect to the available acoustic windows. We evaluate the developed method using virtual planning scenarios based on real patient data as well as for real robotic ultrasound acquisitions on a tissue-mimicking phantom. The proposed method yields superior image quality in comparison with a naive planning approach, while maintaining the necessary coverage of the target. We demonstrate that by taking image formation properties into account acquisition planning methods can outperform naive plannings. Furthermore, we show the need for such planning techniques, since naive approaches are not sufficient as they do not take the expected image quality into account.

Mediated Paths to Overreactive Discipline: Mothers’ Experienced Emotion, Appraisals, and Physiological Responses

PubMed Central

Lorber, Michael F.; O’Leary, Susan G.

2015-01-01

The present investigation was designed to evaluate whether mothers’ emotion experience, autonomic reactivity, and negatively biased appraisals of their toddlers’ behavior and toddlers’ rates of misbehavior predicted overreactive discipline in a mediated fashion. Ninety-three community mother–toddler dyads were observed in a laboratory interaction, after which mothers’ emotion experience and appraisals of their toddler’s behavior were measured via a video-recall procedure. Autonomic physiology and overreactive discipline were measured during the interactions. Mothers’ negatively biased appraisals mediated the relation between emotion experience and overreactive discipline. Heart rate reactivity predicted discipline independent of this mediation. Toddler misbehavior appeared to be an entry point into the above process. Interventions that more actively target physiological and experiential components of mothers’ emotion may further reduce their overreactive discipline. PMID:16287397

Ribbon networks for modeling navigable paths of autonomous agents in virtual environments.

PubMed

Willemsen, Peter; Kearney, Joseph K; Wang, Hongling

2006-01-01

This paper presents the Environment Description Framework (EDF) for modeling complex networks of intersecting roads and pathways in virtual environments. EDF represents information about the layout of streets and sidewalks, the rules that govern behavior on roads and walkways, and the locations of agents with respect to navigable structures. The framework serves as the substrate on which behavior programs for autonomous vehicles and pedestrians are built. Pathways are modeled as ribbons in space. The ribbon structure provides a natural coordinate frame for defining the local geometry of navigable surfaces. EDF includes a powerful runtime interface supported by robust and efficient code for locating objects on the ribbon network, for mapping between Cartesian and ribbon coordinates, and for determining behavioral constraints imposed by the environment.

Data acquisition and path selection decision making for an autonomous roving vehicle. [laser pointing control system for vehicle guidance

NASA Technical Reports Server (NTRS)

Shen, C. N.; YERAZUNIS

1979-01-01

The feasibility of using range/pointing angle data such as might be obtained by a laser rangefinder for the purpose of terrain evaluation in the 10-40 meter range on which to base the guidance of an autonomous rover was investigated. The decision procedure of the rapid estimation scheme for the detection of discrete obstacles has been modified to reinforce the detection ability. With the introduction of the logarithmic scanning scheme and obstacle identification scheme, previously developed algorithms are combined to demonstrate the overall performance of the intergrated route designation system using laser rangefinder. In an attempt to cover a greater range, 30 m to 100 mm, the problem estimating gradients in the presence of positioning angle noise at middle range is investigated.

Ground vehicle control at NIST: From teleoperation to autonomy

NASA Technical Reports Server (NTRS)

Murphy, Karl N.; Juberts, Maris; Legowik, Steven A.; Nashman, Marilyn; Schneiderman, Henry; Scott, Harry A.; Szabo, Sandor

1994-01-01

NIST is applying their Real-time Control System (RCS) methodology for control of ground vehicles for both the U.S. Army Researh Lab, as part of the DOD's Unmanned Ground Vehicles program, and for the Department of Transportation's Intelligent Vehicle/Highway Systems (IVHS) program. The actuated vehicle, a military HMMWV, has motors for steering, brake, throttle, etc. and sensors for the dashboard gauges. For military operations, the vehicle has two modes of operation: a teleoperation mode--where an operator remotely controls the vehicle over an RF communications network; and a semi-autonomous mode called retro-traverse--where the control system uses an inertial navigation system to steer the vehicle along a prerecorded path. For the IVHS work, intelligent vision processing elements replace the human teleoperator to achieve autonomous, visually guided road following.

Status of DoD Robotic Programs

DTIC Science & Technology

1985-03-01

planning or adhere to previously planned routes. 0 Control. Controls are micro electronics based which provide means of autonomous action directly...KEY No: I 11 1181 1431 OROJECT Titloi ISMART TERRAIN ANALYSIS FOR ROBOTIC SYSTEMS (STARS) PROJECT Not I I CLASSIFICATION: IUCI TASK Titles IAUTOMATIC

On-board emergent scheduling of autonomous spacecraft payload operations

NASA Technical Reports Server (NTRS)

Lindley, Craig A.

1994-01-01

This paper describes a behavioral competency level concerned with emergent scheduling of spacecraft payload operations. The level is part of a multi-level subsumption architecture model for autonomous spacecraft, and it functions as an action selection system for processing a spacecraft commands that can be considered as 'plans-as-communication'. Several versions of the selection mechanism are described, and their robustness is qualitatively compared.

Space station automation study. Volume 1: Executive summary. Autonomous systems and assembly

NASA Technical Reports Server (NTRS)

1984-01-01

The space station automation study (SSAS) was to develop informed technical guidance for NASA personnel in the use of autonomy and autonomous systems to implement space station functions. The initial step taken by NASA in organizing the SSAS was to form and convene a panel of recognized expert technologists in automation, space sciences and aerospace engineering to produce a space station automation plan.

Task path planning, scheduling and learning for free-ranging robot systems

NASA Technical Reports Server (NTRS)

Wakefield, G. Steve

1987-01-01

The development of robotics applications for space operations is often restricted by the limited movement available to guided robots. Free ranging robots can offer greater flexibility than physically guided robots in these applications. Presented here is an object oriented approach to path planning and task scheduling for free-ranging robots that allows the dynamic determination of paths based on the current environment. The system also provides task learning for repetitive jobs. This approach provides a basis for the design of free-ranging robot systems which are adaptable to various environments and tasks.

Path Planning Based on Ply Orientation Information for Automatic Fiber Placement on Mesh Surface

NASA Astrophysics Data System (ADS)

Pei, Jiazhi; Wang, Xiaoping; Pei, Jingyu; Yang, Yang

2018-03-01

This article introduces an investigation of path planning with ply orientation information for automatic fiber placement (AFP) on open-contoured mesh surface. The new method makes use of the ply orientation information generated by loading characteristics on surface, divides the surface into several zones according to the ply orientation information and then designs different fiber paths in different zones. This article also gives new idea of up-layer design in order to make up for defects between parts and improve product's strength.

Predicting dental attendance from dental hygienists' autonomy support and patients' autonomous motivation: A randomised clinical trial.

PubMed

Halvari, Anne E Münster; Halvari, Hallgeir; Williams, Geoffrey C; Deci, Edward L

2017-02-01

To test the hypothesis that a Self-Determination Theory (SDT) intervention designed to promote oral health care competence in an autonomy-supportive way would predict change in caries competence relative to standard care. Further, to test the SDT process path-model hypotheses with: (1) the intervention and individual differences in relative autonomous locus of causality (RALOC) predicting increases in caries competence, which in turn would positively predict dental attendance; (2) RALOC negatively predicting dental anxiety, which would negatively predict dental attendance; (3) RALOC and caries disease referred to the dentist after an autonomy-supportive clinical exam directly positively predicting dental attendance; and (4) the intervention moderating the link between RALOC and dental attendance. A randomised two-group experiment was conducted at a dental clinic with 138 patients (M age  = 23.31 yr., SD = 3.5), with pre- and post-measures in a period of 5.5 months. The experimental model was supported. The SDT path model fit the data well and supported the hypotheses explaining 63% of the variance in dental attendance. Patients personality (RALOC) and hygienists promoting oral health care competence in an autonomy-supportive way, performance of autonomy-supportive clinical exams and reductions of anxiety for dental treatment have important practical implications for patients' dental attendance.

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.

The flight planning - flight management connection

NASA Technical Reports Server (NTRS)

Sorensen, J. A.

1984-01-01

Airborne flight management systems are currently being implemented to minimize direct operating costs when flying over a fixed route between a given city pair. Inherent in the design of these systems is that the horizontal flight path and wind and temperature models be defined and input into the airborne computer before flight. The wind/temperature model and horizontal path are products of the flight planning process. Flight planning consists of generating 3-D reference trajectories through a forecast wind field subject to certain ATC and transport operator constraints. The interrelationships between flight management and flight planning are reviewed, and the steps taken during the flight planning process are summarized.

From perceived autonomy support to intentional behaviour: Testing an integrated model in three healthy-eating behaviours.

PubMed

Girelli, Laura; Hagger, Martin; Mallia, Luca; Lucidi, Fabio

2016-01-01

A motivational model integrating self-determination theory, the theory of planned behaviour, and the health action process approach was tested in three samples in three behavioural contexts: fruit and vegetable, breakfast, and snack consumption. Perceived support for autonomous (self-determined) forms of motivation from parents and autonomous motivation from self-determination theory were hypothesised to predict intention and behaviour indirectly via the mediation of attitude and perceived behavioural control from the theory of planned behaviour. It was also expected that planning strategies would mediate the effect of intention on behaviour. Relations in the proposed models were expected to be similar across the behaviours. A two-wave prospective design was adopted. Three samples of high-school students (total N = 1041; 59.60% female; M age = 17.13 years ± 1.57) completed measures of perceived autonomy support, autonomous motivation, theory of planned behaviour constructs, planning strategies and behaviour for each of the three behavioural contexts. Three months later, 816 participants (62,24% female; M age: 17.13 years, SD = 1.58) of the initial sample self-reported their behaviour referred to the previous three months. Structural equation models provided support for the key hypothesised effects of the proposed model for the three health-related behaviours. Two direct effects were significantly different across the three behaviours: the effect of perceived autonomy support on perceived behavioural control and the effect of attitude on intention. In addition, planning strategies mediated the effect of intention on behaviour in fruit and vegetable sample only. Findings extend knowledge of the processes by which psychological antecedents from the theories affect energy-balance related behaviours. Copyright © 2015 Elsevier Ltd. All rights reserved.

Autonomous Formation Flying from Ground to Flight

NASA Technical Reports Server (NTRS)

Chapman, Keith B.; Dell, Gregory T.; Rosenberg, Duane L.; Bristow, John

1999-01-01

The cost of on-orbit operations remains a significant and increasingly visible concern in the support of satellite missions. Headway has been made in automating some ground operations; however, increased mission complexity and more precise orbital constraints have compelled continuing human involvement in mission design and maneuver planning operations. AI Solutions, Inc. in cooperation with the National Aeronautics and Space Administration's (NASA) Goddard Space Flight Center (GSFC) has tackled these more complex problems through the development of AutoCon as a tool for an automated solution. NASA is using AutoCon to automate the maneuver planning for the Earth Orbiter-1 (EO-1) mission. AutoCon was developed originally as a ground system tool. The EO-1 mission will be using a scaled version of AutoCon on-board the EO-1 satellite to command orbit adjustment maneuvers. The flight version of AutoCon plans maneuvers based on formation flying algorithms developed by GSFC, JPL, and other industry partners. In its fully autonomous mode, an AutoCon planned maneuver will be executed on-board the satellite without intervention from the ground. This paper describes how AutoCon automates maneuver planning for the formation flying constraints of the EO-1 mission. AutoCon was modified in a number of ways to automate the maneuver planning on-board the satellite. This paper describes how the interface and functionality of AutoCon were modified to support the on-board system. A significant component of this modification was the implementation of a data smoother, based on a Kalman filter, that ensures that the spacecraft states estimated by an on-board GPS receiver are as accurate as possible for maneuver planning. This paper also presents the methodology use to scale the AutoCon functionality to fit and execute on the flight hardware. This paper also presents the modes built that allow the incremental phasing in of autonomy. New technologies for autonomous operations are usually received with significant, and probably appropriate trepidation. A number of safeguards have been designed in both AutoCon and the interfacing systems to alleviate the potential of mission-impacting anomalies from the on-board autonomous system. This paper describes the error checking, input data integrity validation and limits set on maneuvers in AutoCon and the on-board system.

Autonomous Formation Flying from the Ground to Flight

NASA Technical Reports Server (NTRS)

Chapman, Keith B.; Dell, Gregory T.; Rosenberg, Duane L.; Bristow, John

1999-01-01

The cost of on-orbit operations remains a significant and increasingly visible concern in the support of satellite missions. Headway has been made in automating some ground operations; however, increased mission complexity and more precise orbital constraints have compelled continuing human involvement in mission design and maneuver planning operations. AI Solutions, Inc. in cooperation with the National Aeronautics and Space Administration's (NASA) Goddard Space Flight Center (GSFC) has tackled these more complex problems through the development of AutoCon(TM) as a tool for an automated solution. NASA is using AutoCon(TM) to automate the maneuver planning for the Earth Orbiter-1 (EO-1) mission. AutoCon(TM) was developed originally as a ground system tool. The EO-1 mission will be using a scaled version of AutoCon(TM) on-board the EO-1 satellite to command orbit adjustment maneuvers. The flight version of AutoCon(TM) plans maneuvers based on formation flying algorithms developed by GSFC, JPL, and other industry partners. In its fully autonomous mode, an AutoCon(TM) planned maneuver will be executed on-board the satellite without intervention from the ground. This paper describes how AutoCon(TM) automates maneuver planning for the formation flying constraints of the EO-1 mission. AutoCon(TM) was modified in a number of ways to automate the maneuver planning on-board the satellite. This paper describes how the interface and functionality of AutoCon(TM) were modified to support the on-board system. A significant component of this modification was the implementation of a data smoother, based on a Kalman filter, that ensures that the spacecraft states estimated by an on-board GPS receiver are as accurate as possible for maneuver planning. This paper also presents the methodology used to scale the AutoCon(TM) functionality to fit and execute on the flight hardware. This paper also presents the modes built into the system that allow the incremental phasing in of autonomy. New technologies for autonomous operations are usually received with significant, and probably appropriate, trepidation. A number of safeguards have been designed in both AutoCon(TM) and the interfacing systems to alleviate the potential of mission-impacting anomalies from the on-board autonomous system. This paper describes the error checking, input data integrity validation, and limits set on maneuvers in AutoCon(TM) and the on-board system.

Real-time path planning in dynamic virtual environments using multiagent navigation graphs.

PubMed

Sud, Avneesh; Andersen, Erik; Curtis, Sean; Lin, Ming C; Manocha, Dinesh

2008-01-01

We present a novel approach for efficient path planning and navigation of multiple virtual agents in complex dynamic scenes. We introduce a new data structure, Multi-agent Navigation Graph (MaNG), which is constructed using first- and second-order Voronoi diagrams. The MaNG is used to perform route planning and proximity computations for each agent in real time. Moreover, we use the path information and proximity relationships for local dynamics computation of each agent by extending a social force model [Helbing05]. We compute the MaNG using graphics hardware and present culling techniques to accelerate the computation. We also address undersampling issues and present techniques to improve the accuracy of our algorithm. Our algorithm is used for real-time multi-agent planning in pursuit-evasion, terrain exploration and crowd simulation scenarios consisting of hundreds of moving agents, each with a distinct goal.

UAS Conflict-Avoidance Using Multiagent RL with Abstract Strategy Type Communication

NASA Technical Reports Server (NTRS)

Rebhuhn, Carrie; Knudson, Matt; Tumer, Kagan

2014-01-01

The use of unmanned aerial systems (UAS) in the national airspace is of growing interest to the research community. Safety and scalability of control algorithms are key to the successful integration of autonomous system into a human-populated airspace. In order to ensure safety while still maintaining efficient paths of travel, these algorithms must also accommodate heterogeneity of path strategies of its neighbors. We show that, using multiagent RL, we can improve the speed with which conflicts are resolved in cases with up to 80 aircraft within a section of the airspace. In addition, we show that the introduction of abstract agent strategy types to partition the state space is helpful in resolving conflicts, particularly in high congestion.