Visual collective behaviors on spherical robots

TL;DR

This paper demonstrates that a simple visual model using panoramic information enables spherical robots to exhibit complex collective behaviors like swarming and milling, bridging simulation and real-world experiments.

Contribution

It introduces a novel visual flocking model for spherical robots that reproduces multiple collective behaviors using only panoramic visual cues.

Findings

Successful implementation of visual flocking with 10 robots

Reproduction of swarming and milling behaviors

Close match between simulation and physical experiments

Abstract

The implementation of collective motion, traditionally, disregard the limited sensing capabilities of an individual, to instead assuming an omniscient perception of the environment. This study implements a visual flocking model in a ``robot-in-the-loop'' approach to reproduce these behaviors with a flock composed of 10 independent spherical robots. The model achieves robotic collective motion by only using panoramic visual information of each robot, such as retinal position, optical size and optic flow of the neighboring robots. We introduce a virtual anchor to confine the collective robotic movements so to avoid wall interactions. For the first time, a simple visual robot-in-the-loop approach succeed in reproducing several collective motion phases, in particular, swarming, and milling. Another milestone achieved with by this model is bridging the gap between simulation and physical experiments by demonstrating nearly identical behaviors in both environments with the same visual model. To conclude, we show that our minimal visual collective motion model is sufficient to recreate most collective behaviors on a robot-in-the-loop system that is scalable, behaves as numerical simulations predict and is easily comparable to traditional models.