Aggregating swarms through morphology handling design contingencies: from the sweet spot to a rich expressivity

TL;DR

This study explores how physical design and policy choices in swarm robots influence collective behavior, demonstrating that tuning self-aligning strength around an optimal point enables effective phototaxis and diverse behaviors.

Contribution

It introduces a combined experimental and numerical analysis of morphological effects on swarm behavior, highlighting the importance of design contingencies and policy in collective robotics.

Findings

Optimal self-aligning strength is crucial for efficient phototaxis.

Physical morphology significantly impacts swarm success rates.

Exploring a range of parameters yields diverse collective behaviors.

Abstract

Morphological computing, the use of the physical design of a robot to ease the realization of a given task has been proven to be a relevant concept in the context of swarm robotics. Here we demonstrate both experimentally and numerically, that the success of such a strategy may heavily rely on the type of policy adopted by the robots, as well as on the details of the physical design. To do so, we consider a swarm of robots, composed of Kilobots embedded in an exoskeleton, the design of which controls the propensity of the robots to align or anti-align with the direction of the external force they experience. We find experimentally that the contrast that was observed between the two morphologies in the success rate of a simple phototactic task, where the robots were programmed to stop when entering a light region, becomes dramatic, if the robots are not allowed to stop, and can only slow down. Building on a faithful physical model of the self-aligning dynamics of the robots, we perform numerical simulations and demonstrate on one hand that a precise tuning of the self-aligning strength around a sweet spot is required to achieve an efficient phototactic behavior, on the other hand that exploring a range of self-alignment strength allows for a rich expressivity of collective behaviors.