Robust Neuro-fuzzy Feedback Control for Mobile Manipulator

Two robust Neuro-Fuzzy feedback controllers for autonomous and intelligent electrically driven mobile manipulator in dynamic and partially known environments containing moving obstacles are presented. The first one 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. And the second controller 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 results from the simulation are demonstrated and evaluated the effectiveness of the proposed control algorithms.