Controlling Collision-Induced Aggregations in a Swarm of Micro Bristle-Robots

Systematically designing local interaction rules to achieve collective behaviors in robot swarms is a challenging endeavor, especially in micro-robots where size restrictions imply severe sensing, communication, and computation limitations. In such robot swarms, performing useful functions is often pre- conditioned on the formation of high-density aggregations which can facilitate collective signaling and information sharing. In this paper, we present a systematic approach to control aggregation behaviors by leveraging the physical interactions in a swarm of 300 3-mm vibration-driven micro bristle-robots that we designed and fabricated. We demonstrate the ability to control the degree of aggregation by varying the motility characteristics of the robots through global vibration frequency and amplitude inputs, after comprehensive characterization, modeling and simulation of the locomotion dynamics and robot interactions. To quantify the degree of aggregation, we also introduce a new metric, the MIPS index (Motility-Induced Phase Separation index), which unlike many existing methods does not require a scenario-specific tuning of parameters. Our investigations reveal how physics- driven interaction mechanisms can be exploited to achieve desired behaviors in minimally equipped robot swarms and highlight the specific ways in which hardware and software developments aid in the achievement of collision-induced aggregations.