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robotics AND AUTONOMOUS SYSTEMS 1997年第1期21卷 37-50页

作者： Kosecka, J Robotics laboratory Department of Electrical Engineering and Computer Science 333 Cory Hall 98 UC Berkeley Berkeley CA 94720-1772 USA

Rich sensory information, robust control strategies and proper representation of the environment are crucial for successful navigation of the mobile robot. We propose a model of the environment which is suitable for global navigation using visual sensing. At the lowest level of interaction of the robot with the environment we employ visual servoing techniques which facilitate robust local navigation by means of relative positioning. Further we demonstrate how to use these local control strategies in a global setting. The environment is represented in terms of place graph, where the nodes correspond to places and arcs have associated servoing strategies for moving from one place to another. The global navigation is expressed as a sequence of relative positioning tasks obtainable from the search of a place graph. The proposed model facilitates generation of motion plans which can be executed in a robust manner thanks to the presence of the sensory information in the feedback loop.

关键词： visual servicing motion planning navigation

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Calibrating a multi-manipulator robotic system (vol 4, pg 20, 1997)

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IEEE robotics & AUTOMATION MAGAZINE 1997年第2期4卷 44-44页

作者： Bonitz, RG Hsia, TC Jet Propulation Laboratory Pasadena CA USA Systems.Control and Robotics Laboratory Department of Electrical and Computer Engineering University of California Davis CA USA

A simple, but effective, method of calibrating a multimanipulator robotic system is introduced. The algorithm uses precisely machined calibration plates which are inexpensive to manufacture and require no measuring instrumentation. The method is tested on a dual-arm system which resulted in an order of magnitude reduction in the pose error. Coordinated dual-arm manipulation experiments are conducted using the calibrated kinematic model to validate the usefulness of the calibration process.

关键词： Calibration Robot kinematics Manipulators robotics and automation Force control End effectors Acoustic measurements Testing Coordinate measuring machines Position measurement

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On an effective design approach of Cartesian space neural network control for robot manipulators

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ROBOTICA 1997年第3期15卷 305-312页

作者： Jung, S Hsia, TC Robotics Research Laboratory Department of Electrical and Computer Engineering University of California Davis CA 95616 USA. E-mail: hsia@ece.ucdavis.edu and jung@ece.ucdavis.edu

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 neural network (NN) as a compensator for the complex problem of Cartesian space control. In particular we examine the differences in system performance of accurate position control when the same NN compensator is applied at different locations in the controller structure. 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 control input or joint torque/force. To facilitate the analysis, new NN training signal is introduced and used for all cases. The study is also extended to non-model based Cartesian control problems. Simulation results with three-link rotary robot are presented and performances of different compensating locations are compared.

关键词： neural network robot control Cartesian space design

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Control of articulated vehicle for mining applications: modeling and laboratory experiments

Control of articulated vehicle for mining applications: mode...

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IEEE Conference on Control Technology and Applications (CCTA)

作者： V. Polotski A. Hemami Department of Electrical and Computer Engineering Perception and Robotics Laboratory Montreal QUE Canada

The paper presents the theoretical analysis and experimental results of path tracking control of a class of vehicles widely used in underground mining operations. A vehicle consists of the front and rear units hinged together, where each unit has only one pair of nonsteerable wheels. Steering is performed by changing the angle between the front and rear units by means of a (pair of) hydraulic cylinders (linear actuators). In operation this vehicle moves in either forward or backward directions. Path tracking control problem is of the main importance in order to follow the relatively narrow mining corridors. It consists of using the sensory information to measure the deviations in position and orientation from the path to be followed. Based upon these two tracking errors a feedback system must govern the appropriate steering action.

关键词： Laboratories Wheels Remotely operated vehicles Mobile robots Motion analysis Automation Vehicle dynamics Axles Application software Hydraulic actuators

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Bounded tracking for non-minimum phase nonlinear systems with fast zero dynamics

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INTERNATIONAL JOURNAL OF CONTROL 1997年第4期68卷 819-847页

作者： Tomlin, CJ Sastry, SS Department of Electrical Engineering and Computer Sciences Intelligent Machines and Robotics Laboratory University of California Berkeley CA 94720-1770 United States

In this paper, we derive tracking control laws for non-minimum phase nonlinear systems with both fast and slow, possibly unstable, zero dynamics. The fast zero dynamics arise from a perturbation of a nominal system. These fast zeros can be problematic in that they may be in the right half plane and may cause large magnitude tracking control inputs. In this paper, we combine the ideas from some recent work of Hunt, Meyer and Su with that of Devasia, Chen and Paden on an asymptotic tracking procedure for non-minimum phase nonlinear systems. We give (somewhat subtle) conditions under which the tracking control input is bounded as the magnitude of the perturbation of the nominal system becomes zero. Explicit bounds on the control inputs are calculated for both SISO and MIMO systems using some interesting non-standard singular perturbation techniques. The method is applied to a suite of examples, including the simplified planar dynamics of VTOL and CTOL aircraft.

关键词： Nonlinear control systems

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On robust impedance force control of robot manipulators

On robust impedance force control of robot manipulators

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IEEE International Conference on robotics and Automation (ICRA)

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

An impedance function is proposed to achieve accurate force tracking under the presence of uncertainties in robot dynamics and environment models. The new impedance function is formulated on the basis of PID control of the force tracking error which compensates for the unknown environment stiffness and position. The robot dynamics uncertainties are compensated by a simple time-delayed robust control algorithm. Stability and convergence of the control scheme are analyzed. Simulation studies with a three link rotary robot manipulator are shown. Furthermore, experimental results on a PUMA 560 arm are carried out to confirm the proposed impedance controller's performance.

关键词： Robust control Impedance Force control Robots Manipulator dynamics Uncertainty Three-term control Error correction Stability analysis Convergence

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GMA Welding Process Regulation via Hierarchical GPC with Assured Stability

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IFAC Proceedings Volumes 1997年第3期30卷 221-226页

作者： S.G. Tzafestas E.J. Kyriannakis Intelligent Robotics and Automation Laboratory National Technical University of Athens Department of Electrical and Computer Engineering 15773 Zografou Campus Athens Greece

This paper deals with the regulation of the thermal characteristics of Gas Metal Arc (GMA) welding. A previously developed model is used for the open loop predictions. At the first level of the hierarchy, a parameterized Generalized Predictive Control (GPC) algorithm is selected among other control techniques, due to its robustness against modeling errors and parameter variations. A coordinator, at the second level of the hierarchy, specifies a set of reliable values for the parameters of GPC, so that stability is assured. A representative set of simulation results is included, along an evaluation of the advantages and limitations of the proposed hierarchical GPC technique.

关键词： Predictive control Hierarchical structures Regulation Stabilization Arc welding

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Robust telemanipulator control using a partitioned neural network architecture

Robust telemanipulator control using a partitioned neural ne...

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1997 IEEE International Conference on Neural Networks (ICNN 97)

作者： Tzafestas, SG Prokopiou, PA Tzafestas, CS Intelligent Robotics and Automation Laboratory Department of Electrical and Computer Engineering National Technical Unhersity of Athens Zografou 15773 Athens Greece Laboratoire de Robotique de Paris CNRS UPMC-UVSQ 78140 Velizy 10-12 AV. de 1' Europe France

ISBN: (纸本)0780341236

In this paper the control problem of telemanipulators is considered under the condition that they are subject to modeling and other uncertainties of considerable levels. The design is based on the S. Lee and H. S. Lee teleoperator control scheme, which is modified so as to be able to compensate the uncertainties, and is implemented using a partitioned multilayer perceptron neural network. Several subnetworks are used each one identifying a term of the manipulator's dynamic model. A new learning algorithm is proposed which distributes the learning error to each subnetwork and enables online training Several simulation results are provided which show the robustness ability by the partitioned neurocontroller, and compare it with the results obtained through sliding mode control.

关键词： Sliding mode control

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Introducing the theory of fuzzy cognitive maps in distributed systems

Introducing the theory of fuzzy cognitive maps in distribute...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： C.D. Stylios V.C. Georgopoulos P.P. Groumpos Laboratory for Automation and Robotics Department of Electrical and Computer Engineering University of Patras Rio Greece School of Electrical Engineering and Computer Science Ohio University Athens OH USA

This paper investigates a novel hybrid fuzzy neural system, fuzzy cognitive map (FCM), and its implementation in distributed systems and control problems. The description and the methodology of this system will be examined and then it will be shown the application of FCM in a process control problem, which will reveal the characteristics and qualities of FCM. There is an oncoming need for more autonomous and intelligent systems, which could be satisfied with the application of FCM in the field of systems and control.

关键词： Fuzzy cognitive maps Fuzzy systems Fuzzy logic Intelligent systems robotics and automation Fuzzy control Control systems Control system synthesis Neural networks Humans

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MoNiF: a modular neuro-fuzzy controller for race car navigation

MoNiF: a modular neuro-fuzzy controller for race car navigat...

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IEEE International Symposium on Computational Intelligence in robotics and Automation (CIRA)

作者： K.C. Ng R. Scorcioni M.M. Trivedi N. Lassiter Computer Vision and Robotics Research Laboratory Electrical anad Computer Engineering Department University of California San Diego CA USA

This paper characterizes how well the modular neuro-fuzzy controller, MoNiF, can perform in robotic applications by testing it in a race-car simulator. The performance of this controller is compared with that of a neural network controller (NNC) and the best programmed car (the ideal car). During the phase of learning from the ideal car, MoNiF reaches its stable performance (when it demonstrates good control) at lap 300; while the NNC requires 700 laps. Without further learning and when competing in the same learning track, MoNiF completes 20 laps of the track about 24 seconds later than the ideal car but 29 second ahead of the NNC car. However, when they all are competing in different unfamiliar tracks, MoNiF performs comparably to the ideal car, while NNC has completely lost its ability to drive. Observing the behaviors of NNC and MoNiF, we conclude that MoNiF learns to refine the output of expert rules and thus can drive in most tracks. Meanwhile NNC learns to drive in a particular track but loses its generality for other tracks. It is shown that this modular control method, equipped with the pretrained knowledge of only few simple expert rules, learns much faster than a NNC without any apriori knowledge.

关键词： Navigation Neural networks computer vision Robot vision systems Application software computer simulation Target tracking Laboratories Performance evaluation Testing

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