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IEEE international symposium on Assembly and Manufacturing (ISAM)

作者： Caigong Qin S. Cameron A. McLean Computing Laboratory and Robotics Research Group Oxford University UK

Considers the issues involved in writing path planners that can work well with complex geometric models of robots and workspaces, and outline the authors' work in implementing a solution. The authors' claim that many path planning problems can be solved by a mixture of global and local planning. In turn, local planning can be usefully supported by the provision of efficient distance computations, and the authors describe a variation on the algorithm of Gilbert, Johnson and Keerthi (1988), that they have packaged together with a hierarchical decomposition of objects for added efficiency. Global planning requires more domain-dependent techniques, but the authors have been experimenting with approximations to the generalised Voronoi diagram, and results for this system are shown using a path planner based on the authors' method of virtual springs.

关键词： Path planning Motion planning robotics and automation Robots computational geometry Manipulators Solid modeling Laboratories Writing Packaging

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Petri net-based approach to intelligent control synthesis of FMS

Petri net-based approach to intelligent control synthesis of...

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international Conference on Emerging Technologies and Factory automation (ETFA)

作者： F. Capkovic Institute of Control Theory and Robotics Slovak Academy of Sciences Bratislava Slovakia

Because the classical control theory does not give satisfactory results in the DEDS (discrete event dynamic systems) control systems synthesis, especially in analytical terms, and because such systems are very important in human life-e.g. flexible manufacturing systems (FMS), transport systems, communications systems, etc.-another approaches are wanted. The main aim of this paper is to point out a simple approach leading to a very simple dealing with the FMS (as a kind of the DEDS) modelling and intelligent control problems solving. On that way imbedding some results of applied artificial intelligence, especially the rule-based knowledge representation and simple form of automatic reasoning, is used.

关键词： Intelligent control Flexible manufacturing systems Integrated circuit modeling Control system synthesis Analog integrated circuits Control theory Mathematical model Automatic control Vectors Robots

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A comparison of neural network controllers for a mobile robot with an on-board manipulator

A comparison of neural network controllers for a mobile robo...

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IEEE international symposium on Intelligent Control (ISIC)

作者： S. Jagannathan P.S. Shiakolas Systems and Controls Research Automated Analysis Corporation Peoria IL USA Mechanical and AeroSpace Engineering and The Automation & Robotics Research Institute University of Texas Arlington Arlington TX USA

A systematic approach for modeling and motion control of a mobile vehicle with on-board arm is presented. Two neural network based controllers which feedback linearize the composite system after the incorporation of non-holonomic constraints are considered. The feedback linearization provides an inner loop that accounts for possible motion of the on-board arm. These neural network controllers exhibit learning-while functioning features instead of the traditional learning-then-control training approach. Therefore, the control action is immediate with no off-line-learning phase needed. The case of maintaining a desired course and speed while the on-board arm is allowed to move to its desired orientation is considered. The two neural network algorithms used in designing the controller are backpropagation with e-mod and Hebbian learning with e-mod. computationally the Hebbian learning with e-mod outperforms the backpropagation with e-mod without any performance degradation. A computational comparison and simulation results are presented in order to justify the theoretical conclusion.

关键词： Neural networks Mobile robots Neurofeedback Backpropagation Hebbian theory Motion control Vehicles Linear feedback control systems Control systems Interconnected systems

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System architecture and edge tracking performance of an automated robotic deburring workcell

System architecture and edge tracking performance of an auto...

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IEEE international symposium on Intelligent Control (ISIC)

作者： R. Rajagopalan R.M.H. Cheng V.R. Ayyadevara G. Huard Centre for Industrial Control Department of Mechanical Engineering Concordia University Montreal QUE Canada

This paper presents the system architecture and performance of a robotic workcell capable of deburring used components. Such a workcell should possess the ability to automatically probe, reconstruct the surface geometry, determine the tool path for further machining, and finally carry out edge finishing. The robot chosen is YAMAHA Zeta-1 robot designed specifically for deburring. Probing is accomplished by means of a displacement sensor. This obviates the need for an additional probing stage in the process. The workcell controller has an information processing part consisting of a PC-parallel processor network, an interface to communicate with the controller of the deburring robot and a hardware interface for the probe. The surface of the workpiece is probed by the robot, directed along a path prescribed by the PC-parallel processor network, based on the original CAD database. The probed points, thus collected are used to reconstruct the surface probed and extrapolate to obtain the edge profile. The tool path constructed from the edge profile is then used to direct the robot during machining. Results of edge tracking of a saddle surface in three dimensions is presented. The geometric tacking error is found to be within the resolution of the command signals (0.063 mm).

关键词： Surface reconstruction robotics and automation Deburring Robot sensing systems Probes Machining Surface finishing computational geometry Process control Information processing

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PARAMETERIZATION AND ADAPTIVE-CONTROL OF SPACE ROBOT SYSTEMS

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 1994年第2期30卷 435-451页

作者： XU, YS SHUM, HY KANADE, T LEE, JJ KOREA ADV INST SCI & TECHNOL DEPT ELECT ENGNSEOUL 131SOUTH KOREA

In space application, robot systems are subject to unknown or unmodeled dynamics, for example, in the tasks of transporting an unknown payload or catching an unmodeled moving object. We discuss the parameterization problem in dynamic structure and adaptive control of a space robot system with an attitude-controlled base to which the robot is attached. We first derive the system kinematic and dynamic equations based on Lagrangian dynamics and the linear momentum conservation law. Based on the dynamic model developed, we discuss the problem of linear parameterization in terms of dynamic parameters, and find that, in joint space, the dynamics can be linearized by a set of combined dynamic parameters;however, in inertial space linear parameterization is impossible in general. Then we propose an adaptive control scheme in joint space, and present a simulation study to demonstrate its effectiveness and computational procedure. Because most takes are specified in inertial space instead of joint space, we discuss the issues associated to adaptive control in inertial space and identify two potential problems: unavailability of joint trajectory because the mapping from inertial space trajectory is dynamic-dependent and subject to uncertainty;and nonlinear parameterization in inertial space. We approach the problem by making use of the proposed joint space adaptive controller and updating the joint trajectory by the estimated dynamic parameters and given trajectory in inertial space.

关键词： trajectory unmodeled dynamics computational procedure adaptive control Robot System Joint space Inertial parameterization dynamic parameter aerospace robotics

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The design of shape interactions using motion constraints

The design of shape interactions using motion constraints

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IEEE international Conference on robotics and automation (ICRA)

作者： M. Caine MIT Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA

In this paper we examine an approach to the visualization, analysis and design of functional shape interactions represented as motion constraints in configuration space. A graphical constraint representation, together with a set of computational tools we have developed, permits a designer to visualize and directly manipulate motion constraints in order to achieve desired functional properties. The resulting system has been implemented and applied to the analysis and design of a set of orienting, fixturing and assembly devices for the automated assembly of planar parts.< >

关键词： Shape Motion analysis Motion planning Algorithm design and analysis Performance analysis Assembly systems robotics and automation Laboratories Space technology Visualization

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Hierarchical reinforcement learning and decision making for intelligent machines

Hierarchical reinforcement learning and decision making for ...

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IEEE international Conference on robotics and automation (ICRA)

作者： P. Lima G. Saridis Electrical Computer and Systems Engineering Department Rensselaer Polytechnic Institute Troy NY USA

A methodology for performance improvement of intelligent machines based on hierarchical reinforcement learning is introduced. Machine decision making and learning are based on a cost function which includes reliability and a computational cost of algorithms at the three levels of the hierarchy proposed by Saridis. Despite this particular formalization, the methodology intends to be sufficiently general to encompass different types of architectures and applications. Novel contributions of this work include the definition of a cost function combining reliability and complexity, recursively improved through feedback, a hierarchical reinforcement learning and decision making algorithm which uses that cost function, and a methodology supported on information-based complexity for joint measure of algorithm cost and reliability. Results of simulations show the application of the formalism to intelligent robotic systems.< >

关键词： Decision making Cost function Intelligent robots computational intelligence Learning systems Machine learning computational efficiency Computer architecture Feedback Intelligent systems

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A novel cognitive architecture for simulated robots in an artificial world

A novel cognitive architecture for simulated robots in an ar...

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IEEE international Conference on robotics and automation (ICRA)

作者： A. Agah G.A. Bekey Institute for Robotics and Intelligent Systems Computer Science Department University of Southern California Los Angeles CA USA

This paper presents a novel cognitive architecture for simulated autonomous robots in an artificial world. The design principle of the architecture enables the robotic system to both react to the world and perform premeditated actions. The cognitive architecture is a modular structure composed of a number of multilevel interconnected components, each with distributed, module-specific memory. The modular structure allows for simple portability of the architecture across a variety of robotic platforms. The behavior of the robot is based on the automatic creation of composite behavior from a set of predefined atomic behaviors. Facts about the world are discovered as the robot performs its tasks. An autonomous robot embedded within an artificial world (named Machina Cogitans) is equipped with this architecture, and a number of experiments are presented.< >

关键词： Cognitive robotics Intelligent robots Computer architecture robotics and automation computational modeling Robot sensing systems Robotic assembly Intelligent systems Biological system modeling Artificial intelligence

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QMTOOL-a qualitative modelling and simulation CAD system for designing automated workcells

QMTOOL-a qualitative modelling and simulation CAD system for...

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IEEE international Conference on robotics and automation (ICRA)

作者： G.K. Adam E. Grant Department of Computer Science University of Strathclyde Glasgow UK

This paper describes a qualitative modelling and simulation approach to designing and developing application independent control architectures for automated workcells. A qualitative modelling toolbox, called QMTOOL, was constructed using AI and object-oriented software to achieve this specification. QMTOOL models are built and simulated through interactive dialogue with the user. A model encapsulates the high-level knowledge of the human expert, and a simulation run can verify the design at the specification level. With QMTOOL, visual interaction, direct manipulation of objects, and symbolic computing mechanisms, are all available to the designer.< >

关键词： Design automation Object oriented modeling computational modeling Artificial intelligence Humans Communication system control Power system modeling Control systems Buildings Automatic control

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A reinforcement-learning approach to reactive control policy design for autonomous robots

A reinforcement-learning approach to reactive control policy...

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IEEE international Conference on robotics and automation (ICRA)

作者： A.H. Fagg D. Lotspeich G.A. Bekey Center for Neural Engineering University of Southern California Los Angeles CA USA

Within the field of robotics, much recent attention has been given to control techniques that have been termed reactive or behavior-based. The design of such control systems for even a remotely interesting task is typically a laborious effort, requiring many hours of experimental "tweaking" as the actual behavior of the system is observed by the system designer. In this paper, the authors present a neural-based reinforcement learning approach to the design of reactive control policies in which the designer specifies the the desired behavior of the system, rather than the control program that produces the desired behavior.< >

关键词： Control systems Intelligent robots Robot sensing systems Service robots Robot control Intelligent systems computational and artificial intelligence Optimal control Application specific integrated circuits Data mining

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