A Metaheuristic Artificial Immune System Algorithm for Mobile Robot Navigation

Abstract

This paper presents a metaheuristic artificial immune system (AIS) algorithm for mobile robot navigation in a structured environment with obstacles. The generated collision-free path is optimal in the sense of the shortest distance by defining the performance index. The initial feasible path generated from the AIS planner is then smoothed using the cubic B-spline technique, in order to construct a near-optimal collision-free continuous path. Simulations results are conducted to show the merit of the proposed AIS path planner and smoother for global path planning of autonomous robot navigation.