mlsanityData to 14 Oct 2026

A Scalable Multi-Robot Framework for Decentralized and Asynchronous Perception-Action-Communication Loops

arXiv 2309.10164 ↗First posted 18 Sep 2023cs.RO cs.AIcited by 1

Not on the map. Why?

Abstract (arXiv)

We develop a decentralized Perception-Action-Communication (PAC) system for multi-robot teams that enables them to collaborate in large scale, outdoor environments. Our system natively supports deployments at any scale by leveraging a graph neural network (GNN) to diffuse information hop-by-hop across the fleet's network. This achieves global collaboration from individual robots limited to local sensing and communication. Fully asynchronous, the core modules of PAC: perception, inter-robot communication, message aggregation and action are clocked at different frequencies with information flowing between them through buffers. We implement the PAC system as a series of highly extensible ROS2 nodes to serve as the foundational infrastructure for deployable swarm systems. PAC is validated in the real world with outdoor experiments with up to N=20 quadrotor robots and in simulations based on real-world data with up to N=100. These validations show that our system upholds crucial properties for field-deployable robot collectives: scalability, resiliency and repeatability.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 17 of its 36 references that are in the map. First posted on arXiv 18 Sep 2023.

Builds on

17 of 36 references.

References · 17

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
  2. 2017Inductive Representation Learning on Large Graphscited by 6,320
  3. 2016Convolutional Neural Networks on Graphs with Fast Localized Spectral Filteringcited by 2,089
  4. 2013Spectral Networks and Locally Connected Networks on Graphscited by 1,102
  5. 2022Robot Operating System 2: Design, Architecture, and Uses In The Wildcited by 199
  6. 2019Graph Neural Networks for Decentralized Multi-Robot Path Planningcited by 86
  7. 2020Graph Neural Networks: Architectures, Stability and Transferabilitycited by 80
  8. 2019Learning Decentralized Controllers for Robot Swarms with Graph Neural Networkscited by 62
  9. 2021TrackMPNN: A Message Passing Graph Neural Architecture for Multi-Object Trackingcited by 21
  10. 2020Multi-Robot Coverage and Exploration using Spatial Graph Neural Networkscited by 19
  11. 2021Graph Neural Networks for Decentralized Multi-Robot Submodular Action Selectioncited by 14
  12. 2021Coverage Control in Multi-Robot Systems via Graph Neural Networkscited by 13
5 more
  1. 2020Synthesizing Decentralized Controllers with Graph Neural Networks and Imitation Learningcited by 12
  2. 2022Graph Neural Networks for Multi-Robot Active Information Acquisitioncited by 12
  3. 2021A Framework for Real-World Multi-Robot Systems Running Decentralized GNN-Based Policiescited by 11
  4. 2021Scalable Perception-Action-Communication Loops with Convolutional and Graph Neural Networkscited by 7
  5. 2023Comparison of Middlewares in Edge-to-Edge and Edge-to-Cloud Communication for Distributed ROS2 Systemscited by 2

Built on by

Cited by year

Citing papers per year: 2024: 1.

1 paper.

  1. 2024LPAC: Learnable Perception-Action-Communication Loops with Applications to Coverage Controlcited by 3