An Autonomous and Hardware-Agnostic Vision-Servoed System for Microdevice Injection
Yumin Zheng, Runjia Tan, Rui Jiao, Sunwoo Lee
AI summary
Problem
Automated insertion of nanoliter-scale implantable microdevices currently depends on complex, custom-built robotic setups that are difficult to reproduce and require extensive manual calibration.
Approach
The system uses standard commercial devices and a multi-camera vision pipeline to automatically handle coarse positioning, autofocus, marker-aided centering, and non-contact guidance without manual alignment.
Key results
- Hardware-agnostic, plug-and-play platform built from commercial devices
- Multi-camera vision pipeline enabling closed-loop automated injection
- 47.2% reduction in operating time compared to manual injection
- High procedural reproducibility validated on tissue-mimicking agarose with a MOTE
Why it matters
Lowers the technical and financial barriers for biomedical researchers to adopt automated, high-throughput microdevice implantation in vitro and in vivo.
Abstract
Automated manipulation of nanoliter-scale im- plantable microdevices (IMDs) typically relies on complex, custom-built robotic setups that are difficult to reproduce and require extensive manual calibration. To address this challenge, this paper proposes an easily deployable and highly repro- ducible vision-servoed manipulation system for IMDs. Based on standard commercial off-the-shelf devices, the proposed platform is hardware-agnostic and eliminates the need for tedious manual calibration. The automated workflow seamlessly integrates coarse positioning, auto-focus, and marker-aided cen- tering to achieve robust precision. The system is validated using a sub-nanoliter IMD, the microscale optoelectronic tetherless electrode (MOTE). Experimental results demonstrate that the proposed framework requires minimal manual intervention and significantly reduces operating time by 47.2 % compared to manual injection performed by an experienced user. These results pave the way for economical, high-throughput, and automated IMD-based in vitro and in vivo experiments, and beyond.