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

arXiv: https://arxiv.org/abs/1903.08641 · HTML: https://mlsanity.com/paper/1903.08641/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Mar 2019.

## Built on by (most cited first, 6 of 6)

- [Heterogeneous Multi-Robot Reinforcement Learning](https://mlsanity.com/paper/2301.07137/) (2023)
- [Hierarchical Language Models for Semantic Navigation and Manipulation in an Aerial-Ground Robotic System](https://mlsanity.com/paper/2506.05020/) (2025)
- [A Constrained-Optimization Approach to the Execution of Prioritized Stacks of Learned Multi-Robot Tasks](https://mlsanity.com/paper/2301.05346/) (2023)
- [JaxRobotarium: Training and Deploying Multi-Robot Policies in 10 Minutes](https://mlsanity.com/paper/2505.06771/) (2025)
- [Acting on the Unseen: Communication-Free Collaborative Filtering for Decentralized Multi-Robot Task Allocation](https://mlsanity.com/paper/2605.25584/) (2026)
- [Embodied Semantic Communication for Collective Autonomous Agents: A Tutorial on Representation, Wireless Delivery, and Closed-Loop Coordination](https://mlsanity.com/paper/2609.35936/) (2026)

## Abstract (arXiv)

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.