Dynamic formation control for autonomous underwater vehicles

Abstract

Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles (AUVs) to collaborate with each other. In this work, a dynamic formation model was proposed, in which several algorithms were developed for the complex underwater environment. Dimension changeable particle swarm algorithm was used to find an optimized path by dynamically adjusting the number and the distribution of the path nodes. Position relationship based obstacle avoidance algorithm was designed to detour along the edges of obstacles. Virtual potential point based formation-keeping algorithm was employed by incorporating dynamic strategies which were decided by the current states of the formation. The virtual potential point was used to keep the formation structure when the AUV or the formation was deviated. Simulation results show that an optimal path can be dynamically planned with fewer path nodes and smaller fitness, even with a concave obstacle. It has been also proven that different formation-keeping strategies can be adaptively selected and the formation can change its structure in a narrow area and restore back after passing the obstacle.