Decentralized Multi-agent Task Planning for Heterogeneous UAV Swarm

A decentralized task planning algorithm is proposed for heterogeneous unmanned aerial vehicle (UAV) swarm with different capabilities. The algorithm extends the consensus-based bundle algorithm (CBBA) to account for a more realistic and complex environment. The extension of the algorithm includes handling multi-agent task that requires multiple UAVs collaboratively completed in coordination, and consideration of avoiding obstacles in task scenarios. We propose a new consensus algorithm to solve the multi-agent task allocation problem and use the Dubins algorithm to design feasible paths for UAVs to avoid obstacles and consider motion constraints. Experimental results show that the CBBA extension algorithm can converge to a conflict-free and feasible solution for multi-agent task planning problems. © 2020, Editorial Department of Transactions of NUAA. All right reserved.