Vision-Guided Closed-Loop Autonomous Navigation of Light-Driven Janus Microbots
Abstract
Artificial microbots capable of precise and autonomous navigation could provide versatile platforms for microscale transport, manipulation, and task execution in complex environments. However, reliable navigation becomes increasingly challenging at the micrometre scale, particularly when the surrounding environment changes dynamically. Here, we develop a vision-guided closed-loop navigation framework for light-driven cube-shaped hematite/TiO2 Janus microbots with a characteristic size of approximately 3 μm. Real-time visual localization using a custom-trained YOLOv11 object-detection model is integrated with discretized waypoint-based magnetic steering to enable precise navigation along complex prescribed trajectories, with more than 90% of the measured trajectory deviations remaining below 6 μm across the tested path geometries. The framework further enables arbitrary user-defined free-hand trajectories and autonomous navigation through a physically confined maze. In dynamically changing environments, A* path planning enables real-time path replanning while avoiding multiple independently swimming 5 μm spherical Janus micromotors. Finally, the microbot selectively captures multiple cargo particles and autonomously transports and delivers them to a predefined location while simultaneously avoiding dynamic obstacles. These results establish an integrated platform combining programmable trajectory control, autonomous path planning, real-time environmental adaptation, and task execution within a single light-driven Janus microbot system.
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BibTeX
@misc{andia2026visionguided,
title = {{Vision-Guided Closed-Loop Autonomous Navigation of Light-Driven Janus Microbots}},
author = {Kanhu Charan Andia and Harsh Prashant Katole and Parth Nitinkumar Bhosale and Hemant Kumar and Dhruv Pratap Singh},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.21222},
eprint = {2610.21222},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.21222},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - Vision-Guided Closed-Loop Autonomous Navigation of Light-Driven Janus Microbots
AU - Kanhu Charan Andia
AU - Harsh Prashant Katole
AU - Parth Nitinkumar Bhosale
AU - Hemant Kumar
AU - Dhruv Pratap Singh
PY - 2026
DA - 2026/10/15
PB - arXiv
DO - 10.48550/arxiv.2610.21222
UR - https://arxiv.org/abs/2610.21222
AB - Artificial microbots capable of precise and autonomous navigation could provide versatile platforms for microscale transport, manipulation, and task execution in complex environments. However, reliable navigation becomes increasingly challenging at the micrometre scale, particularly when the surrounding environment changes dynamically. Here, we develop a vision-guided closed-loop navigation framework for light-driven cube-shaped hematite/TiO2 Janus microbots with a characteristic size of approximately 3 μm. Real-time visual localization using a custom-trained YOLOv11 object-detection model is integrated with discretized waypoint-based magnetic steering to enable precise navigation along complex prescribed trajectories, with more than 90% of the measured trajectory deviations remaining below 6 μm across the tested path geometries. The framework further enables arbitrary user-defined free-hand trajectories and autonomous navigation through a physically confined maze. In dynamically changing environments, A* path planning enables real-time path replanning while avoiding multiple independently swimming 5 μm spherical Janus micromotors. Finally, the microbot selectively captures multiple cargo particles and autonomously transports and delivers them to a predefined location while simultaneously avoiding dynamic obstacles. These results establish an integrated platform combining programmable trajectory control, autonomous path planning, real-time environmental adaptation, and task execution within a single light-driven Janus microbot system.
ER -