Robot path planning based on artificial immune network

Abstract

Path planning is an important issue in mobile robotics and many methods have been developed to tackle this problem, such as the grid algorithms, potential field methods, neural network methods and genetic algorithm approaches, each method has its own strength over others in certain aspects. In this paper, mobile robot path planning based on artificial immune network (AIN) is proposed. Simulations show that the proposed method is same capable of obtaining an optimal or near-optimal collision free path planning as knowledge-based genetic algorithm (KGA) method propopsed in [1], but in the complex environment, mobile robot path planning based on AIN has more advantage.