DYNAMIC PATH PLANNING FOR ROBOT NAVIGATION USING SONOR MAPPING AND NEURAL NETWORKS

This paper presents a new path planning algorithm for safe navigation of a mobile robot in dynamic as well as static environments. The certa inty grid concept is adopted to represent the robot's surroundings and a simple sensor model is developed for fast acquisition of environmen tal information. The proposed system integrates global and local path planning and has been implemented in a partially known structured envi ronment without loss of generality for an indoor mobile robot. The glo bal planner finds the initial path based on Dijkstra's algorithm, whil e the local planning scheme uses three neural networks to follow the i nitial global path and avoid colliding with static and moving obstacle s. Effectiveness of these algorithms is illustrated through simulation and experiment using a real robot. The results show that the proposed algorithm can be efficiently implemented in a time varying environmen t.