介电泳
计算机科学
职位(财务)
PID控制器
解耦(概率)
控制理论(社会学)
运动规划
控制器(灌溉)
路径(计算)
控制工程
微流控
人工智能
控制(管理)
工程类
纳米技术
机器人
材料科学
温度控制
农学
经济
程序设计语言
生物
财务
作者
Jiaxin Liu,Huaping Wang,Qing Shi,Xinyi Dong,Kaijun Lin,Tao Sun,Marco Ceccarelli,Toshio Fukuda
标识
DOI:10.1109/rcar54675.2022.9872252
摘要
As a high-throughput and highly flexible technique, optically induced dielectrophoresis (ODEP) is one of the most promising micromanipulation techniques applied for biomedical studies. However, most ODEP-based manipulation methods have not been explored deeply in terms of accurate control under unstructured environments with multiple interference. This paper reports a dynamic control framework for automatically transporting single particle to goal position in a complex environment with an optically induced dielectrophoresis platform. The POMDP-based path planner periodically provides the optimal motion strategy based on the real-time environmental information and current position of the particle to avoid collisions with randomly moving obstacles. The optimal motion strategies are smoothly expanded to short-distance trajectories, which are dynamically followed by the target particle with proxy-based sliding mode control (PSMC) closed-loop controller. Experimental results indicated that compared with traditional controllers such as PID, our control method possesses higher accuracy and stability in path following. In addition, the performance of the path planner was demonstrated by transporting a NIH/3T3 cell to the desired position within a relatively crowded environment.
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