Adaptive Autonomous Navigation of Multiple Optoelectronic Microrobots in Dynamic Environments
Adaptive Autonomous Navigation of Multiple Optoelectronic Microrobots in Dynamic Environments
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DOI：
10.1109/lra.2022.3194308
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发表时间：
2022-10
影响因子：
5.2
通讯作者：
Laurent Mennillo;Christopher Bendkowski;M. Elsayed;Harrison Edwards;Shuailong Zhang;Vijay M. Pawar;A. R. Wheeler;D. Stoyanov;M. Shaw
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文献类型：
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作者：
Laurent Mennillo;Christopher Bendkowski;M. Elsayed;Harrison Edwards;Shuailong Zhang;Vijay M. Pawar;A. R. Wheeler;D. Stoyanov;M. Shaw
光电子微机器人是一种先进的光控微操作技术，在采集和运输生物细胞等敏感微观物体方面具有特殊的前景。然而，目前该技术的广泛应用受到对手动控制的依赖以及缺乏同时操纵多个微型机器人执行器的方法的限制。在这封信中，我们提出了一种动态环境中多个光电微型机器人自主导航的计算框架。该方法结合了闭环视觉伺服、SLAM、微型机器人和障碍物的实时视觉检测、动态路径搜索和自适应运动行为，使微型机器人能够避开静止和运动的障碍物，并在现实世界的动态环境中执行一系列任务。通过使用定制的光电镊子系统的模拟和真实条件下的微操作实验，验证了该系统的能力。
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.