Control of Magnetic Microrobot Teams for Temporal Micromanipulation Tasks

TL;DR

This paper introduces a novel control framework enabling magnetic microrobot teams to perform complex tasks specified by temporal logic, combining optimal control synthesis with sampling techniques for large-scale planning, validated through simulations and experiments.

Contribution

It presents the first control framework for independently controlling magnetic microrobot teams for temporal micromanipulation tasks, integrating optimal control and sampling-based methods.

Findings

Addresses large-scale planning problems beyond existing methods

Successfully demonstrates the approach through simulation studies

Provides experimental validation of the control framework

Abstract

In this paper, we present a control framework that allows magnetic microrobot teams to accomplish complex micromanipulation tasks captured by global Linear Temporal Logic (LTL) formulas. To address this problem, we propose an optimal control synthesis method that constructs discrete plans for the robots that satisfy both the assigned tasks as well as proximity constraints between the robots due to the physics of the problem. Our proposed algorithm relies on an existing optimal control synthesis approach combined with a novel sampling-based technique to reduce the state-space of the product automaton that is associated with the LTL specifications. The synthesized discrete plans are executed by the microrobots independently using local magnetic fields. Simulation studies show that the proposed algorithm can address large-scale planning problems that cannot be solved using existing optimal control synthesis approaches. Moreover, we present experimental results that also illustrate the potential of our method in practice. To the best of our knowledge, this is the first control framework that allows independent control of teams of magnetic microrobots for temporal micromanipulation tasks.