# A Unified Architecture for Dynamic Role Allocation and Collaborative Task Planning in Mixed Human-Robot Teams

arXiv: https://arxiv.org/abs/2301.08038 · HTML: https://mlsanity.com/paper/2301.08038/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 54 references that are in the map.
- First posted on arXiv 19 Jan 2023.

## Builds on (most cited first, 11 of 11)

- [Behavior Trees in Robotics and AI: An Introduction](https://mlsanity.com/paper/1709.00084/) (2017)
- [CoSTAR: Instructing Collaborative Robots with Behavior Trees and Vision](https://mlsanity.com/paper/1611.06145/) (2016)
- [A Hierarchical Architecture for Human-Robot Cooperation Processes](https://mlsanity.com/paper/2009.02807/) (2020)
- [On modularity in reactive control architectures, with an application to formal verification](https://mlsanity.com/paper/2008.12515/) (2020)
- [Flexible human-robot cooperation models for assisted shop-floor tasks](https://mlsanity.com/paper/1707.02591/) (2017)
- [A Resilient and Energy-Aware Task Allocation Framework for Heterogeneous Multi-Robot Systems](https://mlsanity.com/paper/2105.05586/) (2021)
- [Evaluating Methods for End-User Creation of Robot Task Plans](https://mlsanity.com/paper/1811.02690/) (2018)
- [A Human-Centered Dynamic Scheduling Architecture for Collaborative Application](https://mlsanity.com/paper/2103.01831/) (2021)
- [An Integrated Dynamic Method for Allocating Roles and Planning Tasks for Mixed Human-Robot Teams](https://mlsanity.com/paper/2105.12031/) (2021)
- [Robot Trajectory Adaptation to Optimise the Trade-off between Human Cognitive Ergonomics and Workplace Productivity in Collaborative Tasks](https://mlsanity.com/paper/2207.03739/) (2022)
- [Dynamic Human-Robot Role Allocation based on Human Ergonomics Risk Prediction and Robot Actions Adaptation](https://mlsanity.com/paper/2111.03630/) (2021)

## Built on by (most cited first, 1 of 1)

- [Intelligent Framework for Human-Robot Collaboration: Dynamic Ergonomics and Adaptive Decision-Making](https://mlsanity.com/paper/2503.07901/) (2025)

## Abstract (arXiv)

The growing deployment of human-robot collaborative processes in several industrial applications, such as handling, welding, and assembly, unfolds the pursuit of systems which are able to manage large heterogeneous teams and, at the same time, monitor the execution of complex tasks. In this paper, we present a novel architecture for dynamic role allocation and collaborative task planning in a mixed human-robot team of arbitrary size. The architecture capitalizes on a centralized reactive and modular task-agnostic planning method based on Behavior Trees (BTs), in charge of actions scheduling, while the allocation problem is formulated through a Mixed-Integer Linear Program (MILP), that assigns dynamically individual roles or collaborations to the agents of the team. Different metrics used as MILP cost allow the architecture to favor various aspects of the collaboration (e.g. makespan, ergonomics, human preferences). Human preference are identified through a negotiation phase, in which, an human agent can accept/refuse to execute the assigned task.In addition, bilateral communication between humans and the system is achieved through an Augmented Reality (AR) custom user interface that provides intuitive functionalities to assist and coordinate workers in different action phases. The computational complexity of the proposed methodology outperforms literature approaches in industrial sized jobs and teams (problems up to 50 actions and 20 agents in the team with collaborations are solved within 1 s). The different allocated roles, as the cost functions change, highlights the flexibility of the architecture to several production requirements. Finally, the subjective evaluation demonstrating the high usability level and the suitability for the targeted scenario.