Group-based control of large-scale micro-robot swarms with on-board Physical Finite-State Machines

TL;DR

This paper presents a scalable group-based control approach for large micro-robot swarms using on-board finite-state machines, demonstrating local accessibility, hypothesized global controllability, and efficient collision avoidance.

Contribution

It introduces a novel group-based control framework for micro-robot swarms with on-board finite-state machines, enhancing scalability and control simplicity.

Findings

Proves local accessibility of the control system.

Hypothesizes global controllability based on simulations.

Develops a collision avoidance method suitable for online use.

Abstract

An important problem in microrobotics is how to control a large group of microrobots with a global control signal. This paper focuses on controlling a large-scale swarm of MicroStressBots with on-board physical finite-state machines. We introduce the concept of group-based control, which makes it possible to scale up the swarm size while reducing the complexity both of robot fabrication as well as swarm control. We prove that the group-based control system is locally accessible in terms of the robot positions. We further hypothesize based on extensive simulations that the system is globally controllable. A nonlinear optimization strategy is proposed to control the swarm by minimizing control effort. We also propose a probabilistically complete collision avoidance method that is suitable for online use. The paper concludes with an evaluation of the proposed methods in simulations.