MOTION PLANNING OF AN INTELLIGENT ROBOT USING GA MOTIVATED TEMPORAL ASSOCIATIVE MEMORY

Abstract

ABSTRACT The paper discusses the concept of re-planning for a mobile robot in the presence of semidynamic obstacles. The navigational planning is done by employing genetic algorithm until it reaches the goal point. The path segments traversed by the mobile robot are stored by a simple matrix, employing temporal associative memory. During subsequent traversal, the robot utilizes the previously stored matrix to avoid an obstacle path. In case of deadlock, the robot back tracks using TAM and finds alternative paths to reach the goal. This algorithm has been realized on a Pioneer 2DX mobile robot of ActiveMedia Robotic LLC, USA, through client server architecture. The result shows that the robot reaches the goal within a vicinity of a 20 mm radius.