A Heuristic for Multiple Heterogeneous Mobile Robots Task Assignment under Various Loading Conditions considering Workload Balance

This paper proposes a heuristic that optimizes the task completion time for heterogeneous multi-robot systems operating in various real-world applications such as transportation, surveillance, and monitoring. Focusing on transportation missions in manufacturing or warehouse environments, the heuristic aims to find a tour for each robot that departs from distinctive depots completes all assigned tasks, and returns to the depot while minimizing the last task completion time. Building on previous work, the newly developed algorithm can solve more generalized problems, which involve required minimum payload restrictions on each task. The heterogeneous multi-robot systems consist of robots with different average running speeds and maximum payloads. The proposed heuristic considers workload balancing between the robots to provide a feasible solution satisfying all constraints. To validate the approach, the algorithm is tested repeatedly in simulation, varying problem sizes. The results show that the heuristic produces good-quality solutions within a reasonable computation time, demonstrating the potential for real-time implementation. Performance metrics used for evaluation include the objective function value and computation time.