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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： A.C. Sanderson Center for Advanced Technology in Robotics and Automation and Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute RPI Troy NY USA Intellignet robotics Laboratory Institute for Information Science and Electronics University of Tsukuba Tsukuba Japan

An object-oriented modular approach to the engineering of complex robotic systems emphasizes reliability, reusability, ease of development, and user and network interfaces. This modular approach integrates many architectural principles and computational techniques which support adaptive and learning capability at the local, modular level. The TETROBOT is a modular and reconfigurable robotic system which was developed to demonstrate the reliable performance in a wide variety of task domains through reconfiguration of the same fundamental hardware and software components. Such a modular approach emphasizes the synthesis and integration of engineering modules and takes advantage of object-oriented engineering principles to design for a family of tasks. This paper provides an overview of the TETROBOT modular system and describes three modular systems in other applications domains.

关键词： Robots Hardware Robustness Humans Indium phosphide Utility programs

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What programmable vector fields can (and cannot) do: force field algorithms for MEMS and vibratory plate parts feeders

What programmable vector fields can (and cannot) do: force f...

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IEEE International Conference on robotics and Automation (ICRA)

作者： K.-F. Bohringer B.R. Donald N.C. MacDonald Robotics & Vision Lab. Cornell Univ. Ithaca NY USA Robotics & Vision Laboratory Department of Computer Science Cornell University Ithaca NY USA School of Electrical Engineering and Cornell Nanofabrication Facility Cornell University Ithaca NY USA

Programmable vector fields can be used to control a variety of flexible planar parts feeders. When a part is placed on our devices, the programmed vector field induces a force and moment upon it. Over time, the part may come to rest in a dynamic equilibrium state. We demonstrate lower bounds on what the devices cannot do, and results on a classification of control strategies. We suggest sufficient conditions for programmable fields to induce well-behaved equilibria on every part placed on our devices. We define composition operators to build complex strategies from simple ones, and show the resulting fields are also well-behaved. We discuss whether fields outside this class can be useful and free of pathology. Using these tools, we describe new manipulation algorithms, and improve existing planning algorithms by a quadratic factor, and the plan-length by a linear factor. We relax earlier dynamic and mechanical assumptions to obtain more robust and flexible strategies. Finally, we consider parts feeders that can only implement a very limited "vocabulary" of vector fields. We discuss the trade-off between mechanical complexity and planning complexity.

关键词： Micromechanical devices Automatic control Force control Feeds Assembly Robot vision systems Laboratories computer science Nanofabrication Uniform resource locators

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Stability analysis of a robust PD control law for robot manipulators

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Journal of Field robotics 1996年第6期13卷

作者： T. C. Hsia Z. Mao Robotics Research Laboratory Department of Electrical and Computer Engineering University of California Davis CA 95616 Intel Corporation 2200 Mission College Blvd. Santa Clara CA 95052

The purpose of this article is to examine the stability of a robust and decentralized PD control law for robot manipulator control. The control law, which was developed by the authors, has been shown experimentally to be extremely simple to implement and highly accurate for position and force tracking in the presence of robot model uncertainty and payload variation. However, stability analysis has been difficult due to the nonlinearity of robot dynamics and the use of time-delayed measurements of joint torques and joint accelerations in the control law. A rigorous stability analysis is presented in this article using Popov's hyperstability theory. A sufficient condition for global stability is obtained that supports previous theoretical and experimental results. © 1996 John Wiley & Sons, Inc.

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EXPERIMENTS IN ACTIVE VISION WITH REAL AND VIRTUAL ROBOT HEADS

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APPLIED INTELLIGENCE 1995年第3期5卷 237-250页

作者： MARAPANE, SB TRIVEDI, MM Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department The University of Tennessee Knoxville

In the emerging paradigm of animate vision, the visual processes are not thought of as being independent of cognitive or motor processing, but as an integrated system within the context of visual behavior. Intimate coupling of sensory and motor systems have found to improve significantly the performance of behavior based vision systems. In order to study active vision systems one requires sensory-motor systems. Designing, building, and operating such a test bed is a challenging task. In this paper we describe the status of on-going work in developing a sensory-motor robotic system, R2H, with ten degrees of freedoms (DOF) for research in active vision. To complement the R2H system a Graphical Simulation and Animation (GSA) environment is also developed. The objective of building the GSA system is to create a comprehensive design tool to design and study the behavior of active systems and their interactions with the environment. GSA system aids the researchers to develop high performance and reliable software and hardware in a most effective manner. The GSA environment integrates sensing and motor actions and features complete kinematic simulation of the R2H system, it's sensors and it's workspace. With the aid of the GSA environment a Depth from Focus (DFF), Depth from Vergence, and Depth from Stereo modules are implemented and tested. The power and usefulness of the GSA system as a research tool is demonstrated by acquiring and analyzing images in the real and virtual worlds using the same software implemented and tested in the virtual world.

关键词： ACTIVE VISION ROBOT HEADS ROBOT SIMULATION DEPTH EXTRACTION

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LOCALIZED RADON TRANSFORM-BASED DETECTION OF SHIP WAKES IN SAR IMAGES

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1995年第1期33卷 35-45页

作者： COPELAND, AC RAVICHANDRAN, G TRIVEDI, MM Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

This paper presents a Radon transform-based approach to the detection of ship wakes in Synthetic Aperture Radar (SAR) images, The key element of this technique is a localization of the Radon transform, whereby the intensity integration is performed over short line segments rather than across the entire image. A linear feature detection algorithm, which utilizes this localized Radon transform, is then developed, In this algorithm, referred to as the feature space line detector (FSLD) algorithm, the transform space is subjected to processing which server to isolate and locate the response of linear features and suppress the responses of false alarms, This algorithm is tested on both synthetic images corrupted by various levels of Weibull multiplicative noise and on actual SAR images of ship wakes. The results of this testing demonstrate the algorithm's robustness in the presence of noise, as well as its ability to detect and localize linear features that are significantly shorter than the image dimensions,

关键词： Marine vehicles Radar detection computer vision Testing Synthetic aperture radar Image segmentation Detection algorithms Detectors Noise level Noise robustness

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A NEW NEURAL-NETWORK CONTROL TECHNIQUE FOR ROBOT MANIPULATORS

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ROBOTICA 1995年第5期13卷 477-484页

作者： JUNG, S HSIA, TC [a1 ]Robotics Research Laboratory Department of Electrical and Computer Engineering University of California Davis CA 95616 (USA)

A new neural network (NN) control technique for robot manipulators is introduced in this paper. The fundamental robot control technique is the model-based computed-torque control which is subjected to performance degradation due, to model uncertainty. NN controllers have been traditionally used to generate a compensating joint torque to account for the effects of the uncertainties. The proposed NN control approach is conceptually different in that it is aimed at prefiltering the desired joint trajectories before they are used to command the computed-torque-controlled robot system (the plant) to counteract performance degradation due to plant uncertainties. In this framework, the NN controller serves as the inverse model of the plant, which can be trained on-line using joint tracking error. Several variations of this technique introduced. Back-propagation algorithms the NN controller have been developed. Simulation results have demonstrated the excellent tracking performance of the proposed control technique.

关键词： NEURAL NETWORK CONTROL ROBOTS COMPUTED TORQUE

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RESIDUAL UNCERTAINTY IN 3-DIMENSIONAL RECONSTRUCTION USING 2-PLANES CALIBRATION AND STEREO METHODS

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PATTERN RECOGNITION 1995年第7期28卷 1073-1082页

作者： THAYER, S TRIVEDI, M Electrical and Computer Engineering Department Computer Vision and Robotics Research Laboratory The University of Tennessee Knoxville TN 37996-2100 U.S.A.

A necessary goal in the calibration of any instrument is an indication of how well the particular device performs. In the specific case where a camera system is used in the process of three-dimensional reconstruction or stereopsis, geometric measures of the accuracy, precision, and repeatability of 3-D point measurements give a quantitative evaluation of the success of that algorithm. This paper presents an experimental performance analysis of a traditional calibration algorithm as applied to the problem of three-dimensional vision. The study begins with an analysis of the algorithm in a single camera or monocular system. Monocular analysis concludes with a derivation of error boundaries under different. geometric constraints. Showing how this residual error propagates from the component monocular systems into a three-dimensional reconstruction, a binocular analysis derives the desired performance monitors. The paper concludes with a geometric interpretation of the results.

关键词： STEREOPSIS ACCURACY PRECISION REPEATABILITY MONOCULAR BINOCULAR 2-PLANES CALIBRATION

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ROBOT PERFORMANCE-MEASUREMENT AND CALIBRATION USING A 3D computer VISION SYSTEM

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ROBOTICA 1995年第pt 4期13卷 327-337页

作者： PREISING, B HSIA, TC [a1 ]Robotics Research Laboratory Department of Electrical and Computer Engineering University of California Davis Davis California 95616 (USA)

Present day robot systems are manufactured to perform within industry accepted tolerances. However, to use such systems for tasks requiring high precision, various methods of robot calibration are generally required. These procedures can improve the accuracy of a robot within a small volume of the robot's workspace. The objective of this paper is to demonstrate the use of a single camera 3D computer vision system as a position sensor in order to perform robot calibration. A vision feedback scheme, termed Vision-guided Robot Control (VRC), is described which can improve the accuracy of a robot in an on-line iterative manner. This system demonstrates the advantage that can be achieved by a Cartesian space robot control scheme when end effector position/orientation are actually sensed instead of calculated from the kinematic equations. The degree of accuracy is determined by setting a tolerance level for each of the six robot Cartesian space coordinates. In general, a small tolerance level requires a large number of iterations in order to position the end effector, and a large tolerance level requires fewer iterations. The viability of using a vision system for robot calibration is demonstrated by experimentally showing that the accuracy of a robot can be drastically improved. In addition, the vision system can also be used to determine the repeatability and accuracy of a robot in a simple, efficient, and quick manner. Experimental work with an IBM Electric Drive Robot (EDR) and the proposed vision system produced a 97 and a 145 fold improvement in the position and orientation accuracy of the robot, respectively.

关键词： 3D VISION ROBOT PERFORMANCE CALIBRATION POSITION SENSOR

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EXPERIMENTAL RESULTS ON ADAPTIVE NONLINEAR CONTROL AND INPUT PRESHAPING FOR MULTILINK FLEXIBLE MANIPULATORS

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AUTOMATICA 1995年第1期31卷 83-97页

作者： KHORRAMI, F JAIN, S TZES, A School of Electrical Engineering and Computer Science Control/Robotics Research Laboratory (CRRL) Polytechnic University Brooklyn NY 11201 United States Department of Mechanical Engineering Control/Robotics Research Laboratory (CRRL) Polytechnic University Brooklyn NY 11201 United States

Adaptive input precompensators in conjunction with nonlinear controllers for multi-link flexible manipulators are considered in this paper. In an earlier paper, we had shown that application of a nonlinear inner-loop control reduces the variations in frequencies due to the geometrical configuration for multi-link flexible manipulators. This results in a better performance when input preshaping or any other controller based on a linear model is designed. To improve the performance of the system to parameter variations (e.g. changes in payload), an adaptive version of the advocated controller is utilized. This is achieved by estimating the time of application of the impulses for on-line preshaping and in the case of payload uncertainty, estimation of the payload and real-time adjustment of the nonlinear inner-loop based controller. Frequency domain Time-Varying Transfer Function Estimate (TTFE) and Empirical Transfer Function Estimate (ETFE) system identification algorithms are proposed for estimation of vibrational modes and unknown payload. Experimental results on a two-link flexible manipulator with adaptive nonlinear control and preshaping are provided to show the effectiveness of the advocated controllers. Overall, the present paper completely generalizes the adaptive input preshaping technique for multi-link flexible manipulators.

关键词： FLEXIBLE MANIPULATORS VIBRATION DAMPING NONLINEAR CONTROL INPUT PRESHAPING IDENTIFICATION ADAPTIVE CONTROL

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A new neural network control technique for robot manipulators

A new neural network control technique for robot manipulator...

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American Control Conference (ACC)

作者： Seul Jung T.C. Hsia Robotics Research Laboratory Department of Electrical and Computer Engineering University of California Davis CA USA

A neural network (NN) control technique for robot manipulators is introduced in this paper. The fundamental robot control technique is the model-based computed-torque control which is subjected to performance degradation due to model uncertainty. NN controllers have been traditionally used to generate a compensating joint torque to account for the effects of the uncertainties. The proposed NN control approach is conceptually different in that it is aimed at prefiltering the desired joint trajectories before they are used to command the computed-torque-controlled robot system (the plant) to counteract performance degradation due to plant uncertainties. In this framework, the NN controller serves as the inverse model of the plant, which can be trained online using joint tracking error. Several variations of this basic technique are introduced. Backpropagation training algorithms for the NN controller have been developed. Simulation results have demonstrated the excellent tracking performance of the proposed control technique.

关键词： Neural networks Robot control Manipulators Uncertainty Degradation Torque control Control systems Inverse problems Error correction Backpropagation

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