mlsanityData to 14 Oct 2026

A Framework for Real-World Multi-Robot Systems Running Decentralized GNN-Based Policies

arXiv 2111.01777 ↗First posted 2 Nov 2021cs.RO cs.LG cs.MAcited by 11

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Abstract (arXiv)

GNNs are a paradigm-shifting neural architecture to facilitate the learning of complex multi-agent behaviors. Recent work has demonstrated remarkable performance in tasks such as flocking, multi-agent path planning and cooperative coverage. However, the policies derived through GNN-based learning schemes have not yet been deployed to the real-world on physical multi-robot systems. In this work, we present the design of a system that allows for fully decentralized execution of GNN-based policies. We create a framework based on ROS2 and elaborate its details in this paper. We demonstrate our framework on a case-study that requires tight coordination between robots, and present first-of-a-kind results that show successful real-world deployment of GNN-based policies on a decentralized multi-robot system relying on Adhoc communication. A video demonstration of this case-study, as well as the accompanying source code repository, can be found online. https://www.youtube.com/watch?v=COh-WLn4iO4 https://github.com/proroklab/ros2_multi_agent_passage https://github.com/proroklab/rl_multi_agent_passage

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 18 of its 39 references that are in the map. First posted on arXiv 2 Nov 2021.

Builds on

18 of 39 references.

References · 18

  1. 2017Neural Message Passing for Quantum Chemistrycited by 3,487
  2. 2016Learning to Communicate with Deep Multi-Agent Reinforcement Learningcited by 575
  3. 2020SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Drivingcited by 121
  4. 2018PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learningcited by 90
  5. 2019Graph Neural Networks for Decentralized Multi-Robot Path Planningcited by 86
  6. 2019Learning Decentralized Controllers for Robot Swarms with Graph Neural Networkscited by 62
  7. 2020Message-Aware Graph Attention Networks for Large-Scale Multi-Robot Path Planningcited by 43
  8. 2020Mobile Robot Path Planning in Dynamic Environments through Globally Guided Reinforcement Learningcited by 37
  9. 2019Graph Policy Gradients for Large Scale Robot Controlcited by 28
  10. 2020The Emergence of Adversarial Communication in Multi-Agent Reinforcement Learningcited by 28
  11. 2016The Robotarium: A remotely accessible swarm robotics research testbedcited by 24
  12. 2021Decentralized Inference with Graph Neural Networks in Wireless Communication Systemscited by 18
6 more
  1. 2021Graph Neural Networks for Decentralized Multi-Robot Submodular Action Selectioncited by 14
  2. 2021ModGNN: Expert Policy Approximation in Multi-Agent Systems with a Modular Graph Neural Network Architecturecited by 9
  3. 2019Multi-Robot Path Deconfliction through Prioritization by Path Prospectscited by 8
  4. 2021ROS-NetSim: A Framework for the Integration of Robotic and Network Simulatorscited by 4
  5. 2021The Holy Grail of Multi-Robot Planning: Learning to Generate Online-Scalable Solutions from Offline-Optimal Expertscited by 4
  6. 2021Latency Analysis of ROS2 Multi-Node Systemscited by 2

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Cited by year

Citing papers per year: 2022: 2; 2023: 2; 2024: 4; 2025: 3.

11 papers.

  1. 2022VMAS: A Vectorized Multi-Agent Simulator for Collective Robot Learningcited by 68
  2. 2024Language-Conditioned Offline RL for Multi-Robot Navigationcited by 9
  3. 2025MAGNNET: Multi-Agent Graph Neural Network-based Efficient Task Allocation for Autonomous Vehicles with Deep Reinforcement Learningcited by 4
  4. 2023Learning to Navigate in Turbulent Flows with Aerial Robot Swarms: A Cooperative Deep Reinforcement Learning Approachcited by 3
  5. 2024LPAC: Learnable Perception-Action-Communication Loops with Applications to Coverage Controlcited by 3
  6. 2024Graph Neural Networks Gone Hogwildcited by 2
  7. 2025Hierarchical Message-Passing Policies for Multi-Agent Reinforcement Learningcited by 2
  8. 2023A Scalable Multi-Robot Framework for Decentralized and Asynchronous Perception-Action-Communication Loopscited by 1
  9. 2024A finite time analysis of distributed Q-learningcited by 1
  10. 2025Multi-Robot Collaboration through Reinforcement Learning and Abstract Simulationcited by 1
  11. 2022See What the Robot Can't See: Learning Cooperative Perception for Visual Navigationcited by 0