# A Task Allocation Framework for Human Multi-Robot Collaborative Settings

arXiv: https://arxiv.org/abs/2210.14036 · HTML: https://mlsanity.com/paper/2210.14036/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Oct 2022.

## Built on by (most cited first, 2 of 2)

- [Intuitive Programming, Adaptive Task Planning, and Dynamic Role Allocation in Human-Robot Collaboration](https://mlsanity.com/paper/2511.08732/) (2025)
- [We Choose to Go to Space: Agent-driven Human and Multi-Robot Collaboration in Microgravity](https://mlsanity.com/paper/2402.14299/) (2024)

## Abstract (arXiv)

The requirements of modern production systems together with more advanced robotic technologies have fostered the integration of teams comprising humans and autonomous robots. However, along with the potential benefits also comes the question of how to effectively handle these teams considering the different characteristics of the involved agents. For this reason, this paper presents a framework for task allocation in a human multi-robot collaborative scenario. The proposed solution combines an optimal offline allocation with an online reallocation strategy which accounts for inaccuracies of the offline plan and/or unforeseen events, human subjective preferences and cost of switching from one task to another so as to increase human satisfaction and team efficiency. Experiments are presented for the case of two manipulators cooperating with a human operator for performing a box filling task.