# Hierarchical Needs Based Self-Adaptive Framework For Cooperative Multi-Robot System

arXiv: https://arxiv.org/abs/2004.10920 · HTML: https://mlsanity.com/paper/2004.10920/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Apr 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)
- [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 Cooperative Multi-Agent Cognitive Modeling](https://mlsanity.com/paper/2401.05572/) (2024)
- [Innate-Values-driven Reinforcement Learning based Cognitive Modeling](https://mlsanity.com/paper/2411.09160/) (2024)

## Abstract (arXiv)

Research in multi-robot and swarm systems has seen significant interest in cooperation of agents in complex and dynamic environments. To effectively adapt to unknown environments and maximize the utility of the group, robots need to cooperate, share information, and make a suitable plan according to the specific scenario. Inspired by Maslow's hierarchy of human needs and systems theory, we introduce Robot's Need Hierarchy and propose a new solution called Self-Adaptive Swarm System (SASS). It combines multi-robot perception, communication, planning, and execution with the cooperative management of conflicts through a distributed Negotiation-Agreement Mechanism that prioritizes robot's needs. We also decompose the complex tasks into simple executable behaviors through several Atomic Operations, such as selection, formation, and routing. We evaluate SASS through simulating static and dynamic tasks and comparing them with the state-of-the-art collision-aware task assignment method integrated into our framework.