Chapter 4 - Path planning and task assignment for multiple UAVs in dynamic environments

Abstract

This chapter presents an effective approach to path planning combined with task assignments for a group of unmanned aerial vehicles (UAVs). Path planning for a UAV is a challenging task. Handling multiple UAVs in dynamic environments makes planning more complicated. On the other hand, coordination and cooperation is very significant for multi-UAV planning. To find a collision-free optimal cost path, a particle swarm optimization-based algorithm is used here. The proposed path planning algorithm has the capability to replan the path to avoid collision with static and dynamic obstacles and with other UAVs as well. One of the main contributions of the proposed approach is that it can efficiently solve the task assignment problem for multiple UAVs in a distributed manner. A nearest neighbor search model is applied to decompose/divide a set of tasks into several subsets of tasks and distribute them among UAVs. Following this approach, UAVs can effectively perform their mission in complex environments. The simulation results, using different obstacle configurations and different task distributions, are presented and discussed to validate the proposed approach. The proposed approach is tested with multiple UAVs under various reality factors such as breakdown of UAVs and task switching between UAVs. The result shows that, even in the presence of such uncertainties, UAVs are able to successfully complete all of the given tasks without any collision with other UAVs or obstacles.