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Impedance Control Using Anisotropic Fuzzy Environment Models
Fusaomi Nagata*, Keigo Watanabe**, Kazuya Sato** and Kiyotaka Izumi***
*Interior Design Research Institute, Fukuoka Industrial Technology Center, Agemaki-405-3, Ohkawa, Fukuoka 831-0031, Japan
**Department of Advanced Systems Control Engineering, Graduate School of Science and Engineering, Saga University, Honjomachi-1, Saga 840-8502, Japan
***Department of Mechanical Engineering, Faculty of Science and Engineering, Saga University, Honjomachi-1, Saga 840, Japan
Received:August 26, 1998Accepted:November 19, 1998Published:February 20, 1999
Keywords:robot, compliance, impedance control, force control, learning control, fuzzy environment models, genetic algorithms, polishing
Abstract
We describe impedance control for force control in unknown environments, proposing anisotropic fuzzy environment models that estimate environmental stiffness using fuzzy reasoning and generate time-varying damping for stable force control. Each model is automatically taught with genetic algorithms (GAs), in which evaluation is made for force control in several known environments. Taught models are integrated for generalization. We apply models to tasks in which an industrial robot sands or polishes wood is differently stiff in different direction. Numerical simulations demonstrate the effectiveness of our method.
Cite this article as:F. Nagata, K. Watanabe, K. Sato, and K. Izumi, “Impedance Control Using Anisotropic Fuzzy Environment Models,” J. Robot. Mechatron., Vol.11 No.1, pp. 60-66, 1999.Data files:
