An adaptive framework for mobile robot navigation

Abstract

Collective behaviours observed in nature bring new methodologies in proposing control algorithms for robot groups to perform a variety of complex tasks. In this article, an adaptive algorithm, allowing the safe navigation of a group of robots in a collective manner, is proposed. The algorithm, inspired from the adaptive particle swarm optimization technique, proposes an efficient control approach to overcome both static and moving obstacles. Accordingly, compared to the conventional particle swarm optimization algorithm, the proposed system allows a robot or group of robots (swarm) to complete the goal while avoiding static and moving obstacles as well as dynamic targets in a safe and collective manner. The simulation results verify the overall performance and reliability of the proposed system.