Motion planning for multi-link robots using Artificial Potential Fields and modified Simulated Annealing

Abstract

In this paper, we present a hybrid control methodology using Artificial Potential Fields (APF) integrated with a modified Simulated Annealing (SA) optimization algorithm for motion planning of a team of multi-link snake robots. The principle of this work is based on the locomotion of a snake where subsequent links follow the trace of the head. We developed an algorithm where the APF method provides simple, efficient and effective path planning and the modified SA is applied in order for the robots to recover from a local minima. Modifications to the SA algorithm improve the performance of the algorithm and reduce convergence time. Validation on a three-link snake robot shows that the derived control laws from the combined APF and SA motion planning algorithm can successfully navigate the robot to reach its destination, while avoiding collisions with multiple obstacles and other robots in its path as well as recover from local minima.