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

Abstract: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.

Robotics (cs.RO); Artificial Intelligence (cs.AI)

arXiv:2309.10164 [cs.RO]

(or arXiv:2309.10164v3 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2309.10164 Focus to learn more arXiv-issued DOI via DataCite

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