Loading web-font TeX/Math/Italic
Dynamic Path Planning and Motion Control of Microrobotic Swarms for Mobile Target Tracking | IEEE Journals & Magazine | IEEE Xplore

Dynamic Path Planning and Motion Control of Microrobotic Swarms for Mobile Target Tracking


Abstract:

Magnetic field-driven microrobotic swarms have drawn extensive attention, especially in the field of automatic control. Realizing dynamic path planning and motion control...Show More

Abstract:

Magnetic field-driven microrobotic swarms have drawn extensive attention, especially in the field of automatic control. Realizing dynamic path planning and motion control of microrobotic swarms for mobile target tracking is one of the important tasks that still remains unsolved. In this paper, we firstly present an enhanced bidirectional rapidly-exploring random tree star (EB-RRT*) algorithm considering the physical size of the swarm to dynamically plan the optimal path for obstacle avoidance. An image-guided motion controller, which consists of a direction controller and a Genetic Algorithm based Linear Quadratic Regulator (GA-LQR) velocity controller, is then proposed to realize mobile target tracking using microrobotic swarms. Targeted bursting algorithm is subsequently developed to meet the requirement of tracking high-speed (i.e., 20 \mu m/s ) mobile targets. Simulations are performed to validate the proposed methods and obtain the proper ranges of the input parameters for the controllers. Finally, the control effectiveness of mobile target tracking in different conditions and environments is validated by experimental results. Note to Practitioners—The motivation of this work is to develop an effective control scheme for mobile target tracking using microrobotic swarms. Conventional control schemes mainly focus on the control of single microrobots to reach static targets, and thus the desired path is fixed once planned. In addition, the motion of single monolithic microrobots can be modelled precisely. However, in mobile target tracking using microrobotic swarms, dynamic planning algorithms are demanded to frequently update the desired path. Swarms consisting of millions of micro-agents are also difficult to be modelled due to the complex agent-agent interactions. In this work, an effective control scheme consisting of a dynamic path planner, a motion controller and a targeted bursting unit is developed. Real-time dynamic paths will be planned even though th...
Published in: IEEE Transactions on Automation Science and Engineering ( Volume: 20, Issue: 4, October 2023)
Page(s): 2454 - 2468
Date of Publication: 21 September 2022

ISSN Information:

Funding Agency:


I. Introduction

Milli/microrobots remotely navigated by magnetic fields have attracted extensive attention due to their potential biomedical applications [1], [2], [3], [4], [5], [6], [7], [8], [9]. Different types of milli/microrobots have been investigated, e.g., spherical [10], [11], [12], helical [13], [14], [15], and bio-hybrid milli/microrobots [16], [17], [18]. Meanwhile, milli/microrobots with different locomotion are also been reported, e.g., millirobots with a composited agglutinate magnetic spray are capable of crawling, walking and rolling [19], soft microrobots consisting of photoactive liquid-crystal elastomers can perform translation and rotation [20], and trimer-like microrobots is able to rolling and chiral rotating [21]. Although various kinds of milli/microrobots have been developed, microrobotic swarms are considered as potential candidates to tackle challenges encountered in low-invasive therapies, such as targeted drug delivery and in-situ sensing [22], [23]. Inspired by the living swarm behaviors in nature, various kinds of mirorobotic swarms have been reported, e.g., vortex-like swarms [24], ribbon-like swarms [25], elliptical swarms [26] and tornado-like swarms [27]. Since microrobotic swarms can hardly be equipped with onboard sensors and circuits, closed-loop control of them is significant for realizing navigated locomotion and pattern adaptive reconfiguration, especially in confined environments [26]. Moreover, tracking a mobile target using microrobotic swarms could be attached with further significances. In this case, dynamic path planning and motion control of the swarms are two important steps to realize the purpose.

References

References is not available for this document.