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Conference on sensor fusion amd decentralized control in robotic systems

作者： Wong, LM Dumont, C Abidi, MA Univ Tennessee Dept Elect Engn IRIS Lab Knoxville TN 37996 USA

ISBN: (纸本)0819429848

The goal of sensor planning in 3-D object reconstruction is to acquire enough 2-D information about an object to create a 3-D model of that object. This requires the acquisition of images from different viewpoints, the registration of each view, and the integration of all acquired information into a single model. Our focus is on the acquisition stage;we want to determine sensor poses or viewpoints that provide the next best view in an object reconstruction task. The Next Best View (NBV) is the determination of a new sensor position that reveals an optimal amount of unknown information about the object being modeled. The goal of a NBV reconstruction system is usually to model an object using the smallest number of views. Our approach to complete this task is to study a volumetric representation of the model after a new view is obtained. Since the volumetric model consists of known and unknown information, we want to find the viewpoint from which the largest amount of unknown data can be acquired. The NBV algorithm is integrated into a system that acquires synthetic range data from a computer object model, calculates new viewpoints according to an objective function, and reconstructs a complete volumetric model of the object of interest. The NBV algorithm is described in depth and experimental results are given. Also included is a review of related work.

关键词： next best view sensor planning 3-D reconstruction

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Learning manipulation skills by combining PCA technique and adaptive interpolation

Learning manipulation skills by combining PCA technique and ...

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Zhang, JW Knoll, A Univ Bielefeld Fac Technol D-33501 Bielefeld Germany

ISBN: (纸本)0819429848

We propose an approach for learning manipulation skills of robot arms based on complex sensor data. The first component of the used model serves as a projection of high-dimensional input data into an eigenspace by using Principal Component Analysis (PCA). Complex sensor data can be efficiently compressed if robot movements achieving optimal manipulation tasks are constrained to a local scenario. The second component is an adaptive B-spline model whose input space is the eigenspace and whose outputs are robot motion parameters. In the offline learning phase, an appropriate eigenspace can be built by extracting eigenvectors from a sequence of sampling sensor patterns. The B-spline model is then trained for smooth and correct interpolation. In the online application phase, through the cascaded two components, a sensor pattern can be mapped into robot action for performing the specified task. This approach makes tasks such as visually guided positioning much easier to implement. Instead of undergoing cumbersome hand-eye calibration processes, our system is trained in a supervised learning procedure using systematical perturbation motion around the optimal manipulation pose. If more sensors or some robust geometric features from the image processing are available, they can also be added to the input vector. Therefore, the proposed model can integrate multiple sensors and multiple modalities. Our experimental setup is a two-arm robotic system with "self-viewing" hand-eyes and force/torque sensors mounted on each parallel jaw gripper. Implementations with one-hand grasping and two-hand assembly based on visual and force sensors show that the method works even when no robust geometric features can be extracted from the sensor pattern.

关键词： sensor-based skills hand-eye task based mapping learning

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Resource-based action planning for multi-agent systems

Resource-based action planning for multi-agent systems

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Freund, E Hoffmann, K Rossmann, J Univ Dortmund Inst Robot Res D-44227 Dortmund Germany

ISBN: (纸本)0819429848

With the use of multi-robot-systems new chances and perspectives are revealed for industrial, space- and underwater-applications. At the IRF, a versatile multi-robot-control, which fully exploits the inherent flexibility of a multi-robot-system, has been developed. In order to guarantee optimized system-throughput and increased autonomy, the system builds on a new resource-based action planning approach to coordinate the different robot manipulators and other automation components in the workcell. An important issue of the realized action planning component to be applicable to real world problems is that it is realized as an integral part of the hierarchical multi-robot control structure IRCS (Intelligent Robot control System). The IRCS is the multi-robot control that was chosen by the German Space Agency (DLR) for major space automation projects. In this structure the resource-based action planning component is tightly integrated with components for coordinated task execution and collision avoidance to guarantee save operation of all agents in the multi-robot system. As the action planning component "understands" task descriptions on a high level of abstraction it is also the perfect counterpart for a Projective Virtual Reality (VR) system. The paper will describe the mechanism of resource based action planning, the practical experiences gained from the implementation for the IRCS as well as its services to support VR-based man machine interfaces.

关键词： resource-based action planning action pattern net multistage action planning online model expansion intelligent multi-robot-control exploitation of flexibility virtual reality user friendliness increased autonomy and safety

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New approach for motion coordination of a mobile manipulator using fuzzy behavioral algorithms

New approach for motion coordination of a mobile manipulator...

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sensor fusion and decentralized control in robotic systems IV

作者： Häusler, Kurt Klement, Erich P. Zeichen, Gerfried Profactor Research GmbH Wehrgrabengasse 1-5 4400 Steyr Austria Fuzzy Logic Lab. Linz-Hagenberg University of Linz Hauptstraße 99 4232 Hagenberg Austria Institute of Flexible Automation Technical University of Vienna Gußhausstraße 27-29 1040 Vienna Austria

In this paper a new approach for the coordination of the motion axes of a mobile manipulator based on fuzzy behavioral algorithms and its implementation on a physical demonstrator is presented. The kinematic redundancy of the overall system (consisting of a 7 DOF manipulator and a 3 DOF mobile robot) will be used for autonomous and reactive motion of the mobile manipulator within poorely structured and even dynamically changing surroundings. sensors around the mobile and along the manipulator will provide the necessary information for navigation purposes and perception of the environment.

关键词： control system analysis

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Auto-agent: A behavior-based architecture for mobile navigation

Auto-agent: A behavior-based architecture for mobile navigat...

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Hwang, KS Lu, MY Natl Chung Cheng Univ Dept Elect Engn Chai Yi Taiwan

ISBN: (纸本)0819429848

The design and construction of mobile robots is as much an art as a science. Ire hardware architecture, researchers tend to construct a low-cost and reliable platform which equips with various sensory system for sensing the change of the environment to offer useful information to the navigation system. An autonomous navigation system plays a role in an mobile robot as the brain in human being, It generates action command according to those sensory data from the perception system to direct the mobile robot to go to desired positions or accomplish useful tasks without human intervention in real-world, An important problem hi autonomous navigation is the need to cope with the large amount of uncertainty that is inherent of natural environment. Therefore the development of techniques for autonomous navigation in real-world environments constitutes one uf the major trends in the current research on robotics. Inspired with the concept of software agents, reactive control and behavior-based control a modular architecture called Ante-agent, for mobile navigation is proposed, The main characteristic of Auto-agent is as following: Behavioral agents cooperate by means of communicating with other behavioral agents intermittently to achieve their local goal and the goals of the community as a whole because nea one individually has sufficient competence, resources and information to solve the entire probit nl. Auto-agent gains advantages from the characteristics of distributed system, it offers the possibility to find an acceptable solution with a reasonable time and complexity range, Besides, the modular structure iu convenient nt for an engineer to construct a new behavioral agent and to add it into Auto-agent.

关键词： behavior-based navigation system reactive control mobile robot

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Analysis of decentralized variable structure control for collective search by mobile robots

Analysis of decentralized variable structure control for col...

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sensor fusion and decentralized control in robotic systems IV

作者： Goldsmith, Steven Feddema, John Robinett, Rush Sandia National Laboratories Albuquerque NM 87185-8926 United States

This paper presents an analysis of a decentralized coordination strategy for organizing and controlling a team of mobile robots performing collective search. The alpha-beta coordination strategy is a family of collective search algorithms that allow teams of communicating robots to implicitly coordinate their search activities through a division of labor based on self-selected roles. In an alpha-beta team, alpha agents are motivated to improve their status by exploring new regions of the search space. Beta agents are conservative, and rely on the alpha agents to provide advanced information on favorable regions of the search space. An agent selects its current role dynamically based on its current status value relative to the current status values of the other team members. Status is determined by some function of the agent's sensor readings, and is generally a measurement of source intensity at the agent's current location. Variations on the decision rules determining alpha and beta behavior produce different versions of the algorithm that lead to different global properties. The alpha-beta strategy is based on a simple finite-state machine that implements a form of Variable Structure control (VSC). The VSC system changes the dynamics of the collective system by abruptly switching at defined states to alternative control laws. In VSC, Lyapunov's direct method is often used to design control surfaces which guide the system to a given goal. We introduce the alpha-beta algorithm and present an analysis of the equilibrium point and the global stability of the alpha-beta algorithm based on Lyapunov's method.

关键词： Mobile robots

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BISMARC: a biologically inspired system for map-based autonomous rover control

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NEURAL NETWORKS 1998年第7-8期11卷 1497-1510页

作者： Huntsberger, T Rose, J Univ S Carolina Dept Comp Sci Intelligent Syst Lab Columbia SC 29208 USA

As the complexity of the missions to planetary surfaces increases, so too does the need for autonomous rover systems. This need is complicated by the power, mass and computer storage restrictions on such systems (Miller, proceedings SPIE Conference on Cooperative Intelligent robotics in Space iiI, 1829, pp. 472-475, 1992). To address these problems, we have recently developed a system called BISMARC (Biologically Inspired System for Map-based Autonomous Rover control) for planetary missions involving multiple small, lightweight surface revers (Huntsberger, proceedings SPIE Symposium on sensor fusion and decentralized control in Autonomous robotic systems, pp. 221-227, 1997). BISMARC is capable of cooperative planetary surface retrieval operations such as a multiple cache recovery mission to Mars. The system employs autonomous navigation techniques, behavior-based control for surface retrieval operations, and an action selection mechanism based on a modified form of free flow hierarchy (Rosenblatt and Payton, proceedings IEEE/INNS Joint Conference on Neural Networks, pp. 317-324, 1989). This paper primarily describes the navigation and map-mapping subsystems of BISMARC. They are inspired by some recent studies of London taxi drivers indicating that the right hippocampal region of the brain is activated for path planning but not for landmark identification (Maguire et al., Journal of Neuroscience, 17, 7103-7110, 1997). We also report the results of some experimental studies of simulated navigation in planetary environments. (C) 1998 Elsevier Science Ltd. All rights reserved.

关键词： robot navigation hippocampal maps wavelets neural networks

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Fully connected decentralized estimation

Fully connected decentralized estimation

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Conference on sensor fusion and decentralized control in Autonomous robotic systems

作者： Mutambara, AGO Florida State Univ. (United States)

ISBN: (纸本)0819426415

This paper addresses the multisensor estimation problem for both linear and nonlinear systems in a fully connected decentralized sensing architecture. The sensor data fusion problem is identified and the case for decentralized arhitectures, rather than hierarchical or centralized ones, is made. Fully connected decentralized estimation algorithms in both state and information spaces are then developed. The intent is to show that decentralized estimation is feasible and to demonstrate the advantages of information space over state space. The decentralization procedure is then repeated for the extended Kalman filter and extended information filter to produce decentralized filters for nonlinear systems. The four filters are compared and contrasted. In appraising the algorithms the problems associated with the requirement for a fully connected topology are identified.

关键词： estimation information filter decentralized multisensor data fusion

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Explaining finite state machine characteristics using variable structure control

Explaining finite state machine characteristics using variab...

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Conference on sensor fusion and decentralized control in Autonomous robotic systems

作者： Feddema, JT Robinett, RD Driessen, BJ Sandia National Labs. (United States)

ISBN: (纸本)0819426415

This paper describes how variable structure control can be used to describe the overall behavior of multiple autonomous robotic vehicles with simple finite state machine rules. The importance of this result is that we can then begin to design provably asymptotically stable group behaviors from a set of simple control laws and appropriate switching points with variable structure control. The ability to prove convergence to a god is especially important for applications such as locating military targets or land mines.

关键词： finite state machine cooperative behavior robotics variable structure control sliding mode control

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Self-calibration of eye-hand coordination system with decentralized data fusion

Self-calibration of eye-hand coordination system with decent...

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Conference on sensor fusion and decentralized control in Autonomous robotic systems

作者： Lee, S Ro, S Schenker, P Univ. of Southern Californai and Jet Propulsion Lab. (United States) Univ. of Southern California (United States) Jet Propulsion Lab. (United States)

ISBN: (纸本)0819426415

A method of automatically reducing uncertainties and calibrating possible biases involved in sensed data and extracted features by a system based on the geometric data fusion is presented. The perception net, as a structural representation of the sensing capabilities of a system, connects features of various levels of abstraction, referred to here as logical sensors, with their functional relationships such as feature transformations, data fusions, and constraints to be satisfied. The net maintains the consistency of logical sensors based on the forward propagation of uncertainties as well as the backward propagation of constraint errors. A novel geometric data fusion algorithm is presented as a unified framework for computing forward and backward propagations through which the net achieves the self-reduction of uncertainties and self-calibration of biases. The effectiveness of the proposed method is validated through simulation.

关键词： perception net intelligent robotic architecture eye-hand system decentralized data fusion self-calibration goal-oriented behaviors planetary sampling

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