An Improved Algorithm of Multi-robot Task Assignment and Path Planning

For robots to operate effectively and swiftly in complicated environments, task assignment and path planning must be reasonable. However, many of the present algorithms distribute tasks to many robots without considering the surroundings, which results in arbitrary task allocations and interferes with path planning. To address the multi-robot task allocation and path planning (MRTA-PP) issue in complicated environments, this paper proposes an enhanced algorithm of the MRTA-PP based on the integration of the improved genetic algorithm (IGA) and the improved A* algorithm (IA*). First, the multi-robot task assignment (MRTA) problem was transformed into the multiple traveling salesman problem (MTSP) in this paper. Secondly, the IA* was proposed and used to solve the distance matrix consisting of the distances between task points. Then, the IGA was proposed, and the MTSP was solved based on the distance matrix using the IGA. Finally, the overall route of each robot was planned according to the solution using the IA*. The results demonstrate the efficacy of the enhanced algorithm of the MRTA-PP based on the integration of the IGA and the IA* (IGA-IA*), as proposed in this paper, in solving the MRTA-PP issue in complex environments.