Robust neuro-fuzzy navigation of mobile manipulator among dynamic obstacles

Abstract

To fit well the needs of autonomous mobile manipulator, two robust adaptive Neuro-Fuzzy motion controllers are developed. The first controller, based on a computational efficient processing scheme for fuzzy reactive navigation, is used to generate the commands for the servo-systems of robot arm so that, locally, it may choose its way to its goal autonomously. The second fuzzy reactive navigation is implemented in mobile platform so that it maintains a permanent flexible path between two nodes in network generated by a probabilistic roadmap approach. In order to consider the compatibility of stabilisation, mobilisation and manipulation, we derive a coordinated fuzzy local planner algorithm so that the mobile manipulator can avoid stably unknown and/or dynamic obstacles The purpose of an integration of robust controller and Modified Elman Neural Network is to deal with unmodeled bounded disturbances and/or unstructured unmodeled dynamics.