Long‐Distance Autonomous Navigation of Optical Microrobotic Swarms in Complex Environments

The local force field generated by light endows optical microrobots with remarkable flexibility and adaptivity, promising significant advancements in precise medicine and cell transport. Nevertheless, the automated navigation of multiple optical microrobots in intricate, dynamic environments over extended distances remains a challenge. In this study, we introduce a versatile control strategy aimed at navigating optical microrobotic swarms to distant targets under obstacles of varying sizes, shapes, and velocities. By confining all microrobots within a manipulation domain, we ensure swarm integrity while mitigating the effects of Brownian motion. Obstacle's elliptical approximation is developed to facilitate efficient obstacle avoidance for microrobotic swarms. Additionally, we integrate several supplementary functions to enhance swarm robustness and intelligence, addressing uncertainties such as swarm collapse, particle immobilization, and anomalous laser-obstacle interactions in real microscopic environments. We further demonstrate the efficacy and versatility of our proposed strategy by achieving autonomous long-distance navigation to a series of targets. This strategy is compatible with both optical trapping- and nudging-based microrobotic swarms, representing a significant advancement in enabling optical microrobots to undertake complex tasks such as drug delivery and nanosurgery and understanding collective motions.

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Publication Details

Journal
Advanced Intelligent Systems
Published
2024-09-19
DOI
https://doi.org/10.1002/aisy.202400409
Primary Topic
Micro and Nano Robotics
Type
article
Field-Weighted Citation Impact
0.00

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article

Long‐Distance Autonomous Navigation of Optical Microrobotic Swarms in Complex Environments

Yuebing Zheng, Zhihan Chen, Siyuan Huang
Advanced Intelligent Systems
Micro and Nano Robotics
article

Long‐Distance Autonomous Navigation of Optical Microrobotic Swarms in Complex Environments

Yuebing Zheng, Zhihan Chen, Siyuan Huang
article en

Abstract

The local force field generated by light endows optical microrobots with remarkable flexibility and adaptivity, promising significant advancements in precise medicine and cell transport. Nevertheless, the automated navigation of multiple optical microrobots in intricate, dynamic environments over extended distances remains a challenge. In this study, we introduce a versatile control strategy aimed at navigating optical microrobotic swarms to distant targets under obstacles of varying sizes, shapes, and velocities. By confining all microrobots within a manipulation domain, we ensure swarm integrity while mitigating the effects of Brownian motion. Obstacle's elliptical approximation is developed to facilitate efficient obstacle avoidance for microrobotic swarms. Additionally, we integrate several supplementary functions to enhance swarm robustness and intelligence, addressing uncertainties such as swarm collapse, particle immobilization, and anomalous laser-obstacle interactions in real microscopic environments. We further demonstrate the efficacy and versatility of our proposed strategy by achieving autonomous long-distance navigation to a series of targets. This strategy is compatible with both optical trapping- and nudging-based microrobotic swarms, representing a significant advancement in enabling optical microrobots to undertake complex tasks such as drug delivery and nanosurgery and understanding collective motions.

Advanced Intelligent SystemsVol. 6(12)
Walker (United States) (US), The University of Texas at Austin (US)
National Science Foundation, National Institutes of Health, National Institute of General Medical Sciences, Division of Electrical, Communications and Cyber Systems
Good health and well-being
Openalex Percentile: Top 85%
Micro and Nano Robotics
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Long‐Distance Autonomous Navigation of Optical Microrobotic Swarms in Complex Environments — Yuebing Zheng, Zhihan Chen, et al. · Advanced Intelligent Systems (2024) | TGRS Research Map | TGRS