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Trex : taxonomy-based robot-control expert-system Miljanovic, Dejan Milan

Abstract

This work presents the basis for an expert system design for robot control. The system is based on a new taxonomy for robot control. This taxonomy identifies the main issues in the design and selection of robot controllers and categorizes and relates these issues. A clear distinction is drawn between the selection of robot control architectures and the controller algorithms that are utilized within these architectures. In both cases a wide variety of approaches are examined and evaluated based on characteristics such as disturbance rejection, effective stiffness, allowable planing task error, dynamic motion characteristics, sensor information, hardware requirements and model accuracy. Based on these characteristics the controller architectures and controller algorithms are categorized and evaluated using these major criteria: reliability, complexity and robustness. This review and categorization gives rise to a taxonomy based on desired task, imposed criteria, and the distinctive characteristics of various controller architectures and controllers described in the taxonomy. Based on this taxonomy an open expert system for selecting suitable control architectures and algorithms is developed. The appropriateness of the rules embedded in expert system's inference engine as well as the correctness of the decisions made by the expert system is verified via simulations and experiments. Simulation results are obtained by applying selected control architectures and controllers on a two-link manipulator both for free robot motion and constrained robot motion. Experiments are performed both for constrained and unconstrained motion on a five-axis industrial robot. This system is designed for implementation on a new real-time open architecture controller system. This system has potential applications for industrial robots that are currendy limited to either very restrictive proprietary controllers, or complex and specialized controller designs.

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