An Optimal Task Allocation Strategy for Heterogeneous Multi-Robot Systems
This addresses the need for efficient task allocation in multi-robot systems for applications requiring long-term operation, though it appears incremental.
The paper tackled the problem of optimally allocating tasks to heterogeneous robots by proposing a novel algorithm that accounts for robot capabilities and energy consumption, demonstrating efficacy in simulation and on real robots.
For a team of heterogeneous robots executing multiple tasks, we propose a novel algorithm to optimally allocate tasks to robots while accounting for their different capabilities. Motivated by the need that robot teams have in many real-world applications of remaining operational for long periods of time, we allow each robot to choose tasks taking into account the energy consumed by executing them, besides the global specifications on the task allocation. The tasks are encoded as constraints in an energy minimization problem solved at each point in time by each robot. The prioritization of a task over others -- effectively signifying the allocation of the task to that particular robot -- occurs via the introduction of slack variables in the task constraints. Moreover, the suitabilities of certain robots towards certain tasks are also taken into account to generate a task allocation algorithm for a team of robots with heterogeneous capabilities. The efficacy of the developed approach is demonstrated both in simulation and on a team of real robots.