# Needs-driven Heterogeneous Multi-Robot Cooperation in Rescue Missions

arXiv: https://arxiv.org/abs/2009.00288 · HTML: https://mlsanity.com/paper/2009.00288/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Sep 2020.

## Built on by (most cited first, 10 of 10)

- [How Can Robots Trust Each Other For Better Cooperation? A Relative Needs Entropy Based Robot-Robot Trust Assessment Model](https://mlsanity.com/paper/2105.07443/) (2021)
- [KT-BT: A Framework for Knowledge Transfer Through Behavior Trees in Multi-Robot Systems](https://mlsanity.com/paper/2209.02886/) (2022)
- [A Hierarchical Game-Theoretic Decision-Making for Cooperative Multi-Agent Systems Under the Presence of Adversarial Agents](https://mlsanity.com/paper/2303.16641/) (2023)
- [Utility Theory based Cognitive Modeling in the Application of Robotics: A Survey](https://mlsanity.com/paper/2306.09445/) (2023)
- [Bayesian Soft Actor-Critic: A Directed Acyclic Strategy Graph Based Deep Reinforcement Learning](https://mlsanity.com/paper/2208.06033/) (2022)
- [Hierarchical Needs-driven Agent Learning Systems: From Deep Reinforcement Learning To Diverse Strategies](https://mlsanity.com/paper/2302.13132/) (2023)
- [A Strategy-Oriented Bayesian Soft Actor-Critic Model](https://mlsanity.com/paper/2303.04193/) (2023)
- [Self-Adaptive Swarm System (SASS)](https://mlsanity.com/paper/2106.04679/) (2021)
- [Edge Computing based Human-Robot Cognitive Fusion: A Medical Case Study in the Autism Spectrum Disorder Therapy](https://mlsanity.com/paper/2401.00776/) (2024)
- [Innate-Values-driven Reinforcement Learning based Cognitive Modeling](https://mlsanity.com/paper/2411.09160/) (2024)

## Abstract (arXiv)

This paper focuses on the teaming aspects and the role of heterogeneity in a multi-robot system applied to robot-aided urban search and rescue (USAR) missions. We propose a needs-driven multi-robot cooperation mechanism represented through a Behavior Tree structure and evaluate the system's performance in terms of the group utility and energy cost to achieve the rescue mission in a limited time. From the theoretical analysis, we prove that the needs-driven cooperation in a heterogeneous robot system enables higher group utility than a homogeneous robot system. We also perform simulation experiments to verify the proposed needs-driven collaboration and show that the heterogeneous multi-robot cooperation can achieve better performance and increase system robustness by reducing uncertainty in task execution. Finally, we discuss the application to human-robot teaming.