Sensor-Based Path Planning and Tracking Control Scheme for Nonholonornic Wheeled Mobile Robots

Abstract

This paper presents a control scheme for intelligent motion control of nonholonomic wheeled mobile robots under unstructured environments. First, using a simple genetic algorithm, the path planning module calculates an obstacle-free path as a sequence of control vectors of orientation, considering kinematic constraints in steering control. Then, the tracking control module calculates the references for motion control of the mobile robot using a sensor fusion neural network. Preliminary experiments for teaching the neural network with internal and external sensors are presented to show the effectiveness of the proposed control scheme.