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Categorical color projection for robot road following

Categorical color projection for robot road following

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Nan Zeng J.D. Crisman Robotics & Vision Systems Laboratory Department of Electrical and Computer Engineering Northeastern University Boston MA USA

This paper shows that categorical color developed in Yue Du (1994) is a good representation of color space for some robot vision tasks. The authors use SCARF as a test case to compare 'equivalent' RGB, categorical color, and intensity robot vision algorithms on a difficult robot road following task. SCARF uses a full three-dimensional representation of color space to formulate road and off-road colors. Performing categorical color or intensity projection, the authors can model the road and off-road colors as single dimensional probability density functions. This greatly reduces the time to process the color image. Moreover, the authors show that categorical color is a good representation in that it outperforms an equivalent intensity algorithm on the robot tasks. Categorical color, while it cannot outperform the original RGB algorithm, performs well enough to be used in this particular robot application. Its effectiveness is verified by many experiments on difficult road image sequences.

关键词： Roads Robot vision systems Orbital robotics Color Machine vision Mobile robots Image segmentation Layout Image edge detection Degradation

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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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New neural network control technique for non-model based robot manipulator control

New neural network control technique for non-model based rob...

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IEEE International Conference on Systems, Man and Cybernetics

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

In this paper a new neural network (NN) control technique for non-model based PD control of robot manipulators are proposed. The main difference between the proposed technique and the existing feedback error learning (FEL) technique of Kawato et al. is that compensation of robot dynamics uncertainties is done outside the control loop by modifying the desired input trajectory. By using different NN training signals, two NN control algorithms are developed. One is comparable to that in the FEL technique and the another involves the Jacobian of the PD controlled robot dynamic system. Performances of both controllers with different trajectories and PD controller gains are examined and compared with that of the FEL controller. It is shown that the new control technique is superior.

关键词： Neural networks Manipulators Robot control PD control Robot kinematics Uncertainty Control systems Motion control Trajectory Nonlinear control systems

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Depth extraction using lateral or axial camera motion: an integration of depth from motion and stereo

Depth extraction using lateral or axial camera motion: an in...

引用

IEEE International Conference on Image Processing

作者： A.K. Dalmia M.M. Trivedi Web Systems Group Datacube Inc. Danvers MA USA Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

We present an integrated methodology that can be used to extract the depth from a sequence of images. The method combines the ability of stereo processing to acquire highly accurate depth measurements and the efficiency of spatial and temporal gradient analysis. As a result of this integration, depth measurements of a high quality are obtained at a speed approximately ten-times higher than that of stereo processing. Without any a priori information of the locations of the points in the scene, the correspondence problem in stereo processing is computationally expensive. In our approach, we use the spatial and temporal gradient analysis, which has been shown to provide the depth with a high efficiency but limited accuracy, to guide the stereo matching process. Experiments for lateral and axial camera translations have acquired depth results with a mean error of less than 3 percent.

关键词： Cameras Displacement measurement Robot vision systems computer vision Equations Laboratories Data engineering Velocity measurement Layout Energy resolution

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On reference trajectory modification approach for Cartesian space neural network control of robot manipulators

On reference trajectory modification approach for Cartesian ...

引用

IEEE International Conference on robotics and Automation (ICRA)

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

It is well known that computed torque robot control is subjected to performance degradation due to uncertainties in robot model, and application of neural network (NN) compensation techniques are promising. In this paper we examine the effectiveness of NN as a compensator for the complex problem of Cartesian space control. In particular we examine the differences in system performance when the same NN compensator is applied at different locations in the controller. It is found that using NN to modify the reference trajectory to compensate for model uncertainties is much more effective than the traditional approach of modifying joint torque/force. To facilitate the analysis, a new NN training signal is introduced. The study is extended to non-model based Cartesian control problem. Simulation results are also presented.

关键词： Neural networks Uncertainty computer networks Robot control Degradation Orbital robotics System performance Control systems Torque Signal analysis

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On neural network application to robust impedance control of robot manipulators

On neural network application to robust impedance control of...

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IEEE International Conference on robotics and Automation (ICRA)

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

Performance of impedance controller for robot force tracking is affected by the uncertainties in the robot model and environment stiffness. The purpose of the paper is to improve the controller robustness by applying the neural network technique to compensate for the uncertainties in the robot model. A novel error signal is proposed for the neural network training. In addition, an algorithm is developed to determine the reference trajectory when the environment stiffness is unknown. Simulations show that highly robust position/force tracking by a three degrees-of-freedom robot can be achieved under large uncertainties.

关键词： Neural networks Robust control Impedance Robot control Force control Uncertainty Manipulator dynamics Robot sensing systems Orbital robotics robotics and automation

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Design of a structured light sensor for in situ calibration

Design of a structured light sensor for in situ calibration

引用

IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： F.W. DePiero R.L. Kress Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA Roboticsand Process Systems Division Oak Ridge National Laboratory Oak Ridge TN USA

This paper highlights a ranging sensor that can be calibrated at standoffs of 1 to 3 feet with a depth of field of /spl ap/1 ft. Tests at a 16" standoff have produced a 0.004 inch standard deviation in height measurement errors. The data density and field of view are programmable. The sensor is positioned robotically, allowing it to provide accurate, shed-range measurements prior to manipulation tasks. The sensor head is relatively inexpensive (/spl ap/$10 k) and is designed for in situ calibration. This approach is intended to allow replacement components to be installed, calibrated, and validated without decontamination. Calibration, validation and data acquisition are all designed to be performed remotely and in a highly automated fashion. These in situ features of the design are targeted for the interest of industry with the aim of producing a sensor having a longer lifetime and a lower maintenance cost.

关键词： Calibration Testing Measurement standards Measurement errors Robot sensing systems Position measurement Decontamination Data acquisition Sensor phenomena and characterization Costs

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Fuzzy perceptual grouping in image understanding

Fuzzy perceptual grouping in image understanding

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： A.L. Ralescu J.G. Shanahan Department of Electrical & Computer Engineering University of Cincinnati USA Laboratory for lnternational Fuzzy Engineering Research Yokohama Japan

The image understanding work we present is part of a navigation support system. We explore the use of fuzzy techniques for image understanding via perceptual organization. A brief review of previous work on perceptual organization introduces our motivation for using fuzzy techniques for representation which in turns entails their use for reasoning about the result of the organization. The approach is supported by experimental results obtained for an office scene environment.< >

关键词： computer vision Humans Psychology Neuroscience Machine vision Visual perception Bayesian methods Laboratories Fuzzy systems Floors

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Adaptive visual tracking algorithm and real-time implementation

Adaptive visual tracking algorithm and real-time implementat...

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IEEE International Conference on robotics and Automation (ICRA)

作者： M.W. Eklund G. Ravichandran M.M. Trivedi S.B. Marapane Computer Vision and Robotics Research Laboratory Electrical and Colmputer Engineerirrg Department University of Tennessee Knoxville TN USA University of Tennessee Knoxville Knoxville TN US Dept. of Electr. & Comput. Eng. Tennessee Univ. Knoxville TN USA

A real-time correspondence based tracking algorithm is detailed. The system uses a pipeline processor, a general purpose processor, a camera and a display. The minimum noise and correlation energy (MINACE) filter is used in the tracking algorithm as it provides a good combination of speed, accuracy and flexibility for the targeted hardware system. The system designed is fast and tracking is accomplished at a rate of 15 Hz. The system is adaptive and does not rely on a previous model of the object; the training image for filter synthesis is acquired from previous image frames and the filter is synthesized online to accommodate 3D variations of the target being tracked. The system tracks an object consistently as is demonstrated by the low deviation of the results in the evaluation.

关键词： Target tracking Cameras Robot vision systems Filters Visual servoing Image motion analysis computer vision Laboratories Power engineering and energy Pipelines

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A robotic system to locate hazardous chemical leaks

A robotic system to locate hazardous chemical leaks

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IEEE International Conference on robotics and Automation (ICRA)

作者： R.A. Russell D. Thiel R. Deveza A. Mackay-Sim Intelligent Robotics Research Centre Department of Electrical&Computer Systems Engineering Monash University Clavton VIC Australia School of Microelectronic Engineering Griffith University Brisbane QLD Australia School of Science Griffith University Brisbane QLD Australia

Tracing leaks of airborne radioactive, poisonous or flammable materials is a potentially dangerous activity that could be undertaken by robotic systems. This paper describes a practical investigation of the possibility of developing simple, low cost, autonomous robots to perform this task. It is envisaged that these robots would be used in large numbers. This would improve reliability through redundancy and provide large area coverage from a wide distribution of robots. Failure of a single unit would not jeopardise the overall sensing operation. Sensing and control techniques developed to perform leak location in a simplified laboratory environment are described and experimental results are presented.

关键词： Chemical hazards Robot sensing systems Mobile robots Chemical sensors Wheels Intelligent robots Chemical technology Orbital robotics Computational geometry Vehicles

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