Adaptive neural-network control for redundant nonholonomic mobile modular manipulators

Authors:
Yangmin Li;Yugang Liu;Shaoze Yan
Affiliations:
Faculty of Science and Technology, University of Macau, Taipa, Macao S.A.R., P.R. China;Faculty of Science and Technology, University of Macau, Taipa, Macao S.A.R., P.R. China;Department of Precision Instruments and Mechanology, Tsinghua University, Beijing, P.R. China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
Year:
2005

Citing 3
Cited 1

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Theory of Robot Control

Theory of Robot Control
Multilayer neural-net robot controller with guaranteed tracking performance

IEEE Transactions on Neural Networks

Sliding Mode Adaptive Neural-Network Control for Nonholonomic Mobile Modular Manipulators

Journal of Intelligent and Robotic Systems

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Abstract

This paper discusses the trajectory following issue for redundant nonholonomic mobile modular manipulators. Dynamic model is established and an adaptive neural-network controller is developed to control the end-effector to follow a desired spacial trajectory. The proposed algorithm doesn't need any priori dynamics and provides a new solution for stabilization of redundant robotic self-motions. Simulation results for a real robot demonstrate the proposed algorithm is effective.