CoLoSSI: Multi-Robot Task Allocation in Spatially-Distributed and Communication Restricted Environments

In our research, we address the problem of coordination and planning in heterogeneous multi-robot systems for missions that consist of spatially localized tasks. Conventionally, this problem has been framed as a task allocation problem that maps tasks to robots. However, all previous work assumes that tasks are atomic procedures. In this work, we relax this assumption and adopt a non-atomic model of tasks that enables robots to accomplish mission tasks incrementally over disjoint periods, precisely to account for the possibility of having a task serviced by numerous individual contributions over time. We propose a cooperative, load-balancing task allocation and scheduling algorithm based on sequential single-item auctions (CoLoSSI) that explicitly considers the non-atomicity of tasks, promotes synergies between agents, and enables cooperation while maintaining computational tractability. We also propose a fully distributed variant of CoLoSSI that tackles sparse, communication-restricted scenarios. Computational and simulation results confirm the efficacy of the proposed approaches for generating good-quality mission plans with low computational effort.