Adaptive Autonomous Navigation of Multiple Optoelectronic Microrobots in Dynamic Environments
Laurent Mennillo, Christopher Bendkowski, Mohamed Elsayed, Harrison Edwards, Shuailong Zhang, Vijay Pawar, Aaron R. Wheeler, Danail Stoyanov
Abstract
The optoelectronic microrobot is an advanced light-controlled micromanipulation technology which has particular promise for collecting and transporting sensitive microscopic objects such as biological cells. However, wider application of the technology is currently limited by a reliance on manual control and a lack of methods for simultaneous manipulation of multiple microrobotic actuators. In this letter, we present a computational framework for autonomous navigation of multiple optoelectronic microrobots in dynamic environments. Combining closed-loop visual-servoing, SLAM, real-time visual detection of microrobots and obstacles, dynamic path-finding and adaptive motion behaviors, this approach allows microrobots to avoid static and moving obstacles, and perform a range of tasks in real-world dynamic environments. The capabilities of the system are demonstrated through micromanipulation experiments in simulation and in real conditions using a custom built optoelectronic tweezer system.
BibTeX
@inproceedings{ral2022_adaptiveautonomo,
title = {Adaptive Autonomous Navigation of Multiple Optoelectronic Microrobots in Dynamic Environments},
author = {Laurent Mennillo and Christopher Bendkowski and Mohamed Elsayed and Harrison Edwards and Shuailong Zhang and Vijay Pawar and Aaron R. Wheeler and Danail Stoyanov and Michael J. Shaw},
booktitle = {RA-L 2022},
year = {2022}
}