Distributed Spatial Awareness for Robot Swarms

TL;DR

This paper presents a method for robot swarms to develop a shared spatial awareness using local sensing, message passing, and movement, enabling new algorithms with low resource requirements.

Contribution

It introduces a distributed approach combining Gaussian Belief Propagation and continuous movement to establish a global reference frame in robot swarms.

Findings

System characterized successfully in simulation

Demonstrated two new swarm algorithms using shared reference frame

Achieved low bandwidth and computation requirements

Abstract

Building a distributed spatial awareness within a swarm of locally sensing and communicating robots enables new swarm algorithms. We use local observations by robots of each other and Gaussian Belief Propagation message passing combined with continuous swarm movement to build a global and distributed swarm-centric frame of reference. With low bandwidth and computation requirements, this shared reference frame allows new swarm algorithms. We characterise the system in simulation and demonstrate two example algorithms.