Heterogeneous Multi-robot Task Allocation for Long-Endurance Missions in Dynamic Scenarios

We present a framework for Multi-Robot Task Allocation (MRTA) in heterogeneous teams performing long-endurance missions in dynamic scenarios. Given the limited battery of robots, especially for aerial vehicles, we allow for robot recharges and the possibility of fragmenting and/or relaying certain tasks. We also address tasks that must be performed by a coalition of robots in a coordinated manner. Given these features, we introduce a new class of heterogeneous MRTA problems which we analyze theoretically and optimally formulate as a Mixed-Integer Linear Program. We then contribute a heuristic algorithm to compute approximate solutions and integrate it into a mission planning and execution architecture capable of reacting to unexpected events by repairing or recomputing plans online. Our experimental results show the relevance of our newly formulated problem in a realistic use case for inspection with aerial robots. We assess the performance of our heuristic solver in comparison with other variants and with exact optimal solutions in small-scale scenarios. In addition, we evaluate the ability of our replanning framework to repair plans online.

@article{calvo2025_2411.02062,
  title={ Heterogeneous Multi-robot Task Allocation for Long-Endurance Missions in Dynamic Scenarios },
  author={ Alvaro Calvo and Jesus Capitan },
  journal={arXiv preprint arXiv:2411.02062},
  year={ 2025 }
}