Collective perception for tracking people with a robot swarm

TL;DR

This paper explores how robot swarms can collectively track people in dynamic environments, demonstrating promising results in simulation across various office settings.

Contribution

It introduces a preliminary simulation-based experiment on collective person tracking using robot swarms in different office environments.

Findings

Swarm perception enables continuous environment monitoring.

Detection and information propagation times vary with swarm size.

Robot swarms show potential for dynamic environment monitoring.

Abstract

Swarm perception refers to the ability of a robot swarm to utilize the perception capabilities of each individual robot, forming a collective understanding of the environment. Their distributed nature enables robot swarms to continuously monitor dynamic environments by maintaining a constant presence throughout the space.In this study, we present a preliminary experiment on the collective tracking of people using a robot swarm. The experiment was conducted in simulation across four different office environments, with swarms of varying sizes. The robots were provided with images sampled from a dataset of real-world office environment pictures.We measured the time distribution required for a robot to detect a person changing location and to propagate this information to increasing fractions of the swarm. The results indicate that robot swarms show significant promise in monitoring dynamic environments.