Collective perception for tracking people with a robot swarm

TL;DR

A preliminary experiment on the collective tracking of people using a robot swarm is presented, showing significant promise in monitoring dynamic environments.

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.

Figures (2)

• Figure 1: Simulated environments with a 12.0-robot swarm.
• Figure 2: Empirical cumulative distribution of the time required to a) detect an event, and propagate it to b) 25% of the swarm, c) 50% of the swarm, and d) 75% of the swarm, for the three different swarm sizes.