Tang Xiaoqing, Li Yuke, Liu Xiaoming, Liu Dan, Chen Zhuo, Arai Tatsuo
Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, State Key Laboratory of Intelligent Control and Decision of Complex System, Beijing Advanced Innovation Center for Intelligent Robots and Systems, and School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Center for Neuroscience and Biomedical Engineering, The University of Electro-Communications, Tokyo 182-8585, Japan.
Micromachines (Basel). 2022 Feb 21;13(2):337. doi: 10.3390/mi13020337.
Magnetic microrobots are vital tools for targeted therapy, drug delivery, and micromanipulation on cells in the biomedical field. In this paper, we report an automated control and path planning method of magnetic microrobots based on computer vision. Spherical microrobots can be driven in the rotating magnetic field generated by electromagnetic coils. Under microscopic visual navigation, robust target tracking is achieved using PID-based closed-loop control combined with the Kalman filter, and intelligent obstacle avoidance control can be achieved based on the dynamic window algorithm (DWA) implementation strategy. To improve the performance of magnetic microrobots in trajectory tracking and movement in complicated environments, the magnetic microrobot motion in the flow field at different velocities and different distribution obstacles was investigated. The experimental results showed that the vision-based controller had an excellent performance in a complex environment and that magnetic microrobots could be controlled to move to the target position smoothly and accurately. We envision that the proposed method is a promising opportunity for targeted drug delivery in biological research.
磁性微型机器人是生物医学领域中用于靶向治疗、药物递送和细胞微操作的重要工具。在本文中，我们报告了一种基于计算机视觉的磁性微型机器人自动控制和路径规划方法。球形微型机器人可以在电磁线圈产生的旋转磁场中驱动。在微观视觉导航下，使用基于PID的闭环控制结合卡尔曼滤波器实现了稳健的目标跟踪，并基于动态窗口算法（DWA）实现策略实现了智能避障控制。为了提高磁性微型机器人在复杂环境中的轨迹跟踪和运动性能，研究了不同速度和不同分布障碍物的流场中磁性微型机器人的运动。实验结果表明，基于视觉的控制器在复杂环境中具有优异的性能，并且可以控制磁性微型机器人平稳、准确地移动到目标位置。我们设想，所提出的方法为生物研究中的靶向药物递送提供了一个有前景的机会。
