Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Theory of Robot Control
A neuro-fuzzy controller for mobile robot navigation and multirobotconvoying
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Obstacle avoidance for kinematically redundant manipulators using a dual neural network
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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This paper addresses an obstacle avoidance issue for redundant nonholonomic mobile modular manipulators. On the basis of modular robot concept, an integrated dynamic modeling method is proposed, which takes both the mobile platform and the onboard modular manipulator as an integrated structure. A new obstacle avoidance algorithm is proposed which is mainly composed of two parts: a self-motion planner (SMP) and a robust adaptive neural fuzzy controller (RANFC). One important feature of this algorithm lies in that obstacles are avoided by online adjusting self-motions so that the end-effector task will not be affected unless the obstacles are just on the desired trajectory. The RANFC does not rely on exact aprior dynamic parameters and can suppress bounded external disturbance effectively. The effectiveness of the proposed algorithm is verified by simulations.