# An Optimal Task Allocation Strategy for Heterogeneous Multi-Robot Systems

## TL;DR

This paper introduces an energy-aware, optimal task allocation algorithm for heterogeneous multi-robot systems, balancing capabilities and energy consumption to enhance operational longevity.

## Contribution

It presents a novel energy minimization-based task allocation method that considers robot heterogeneity and task prioritization in real-time.

## Key findings

- Effective in simulations and real-robot experiments
- Balances energy consumption with task priorities
- Improves operational longevity of robot teams

## Abstract

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.