Liu Jiaxin, Wang Huaping, Liu Menghua, Zhao Ran, Zhao Yanfeng, Sun Tao, Shi Qing
Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology), Ministry of Education, Beijing 100081, China.
Cyborg Bionic Syst. 2022 Nov 2;2022:9890607. doi: 10.34133/2022/9890607. eCollection 2022.
With high throughput and high flexibility, optoelectronic tweezers (OETs) hold huge potential for massively parallel micromanipulation. However, the trajectory of the virtual electrode has been planned in advance in most synchronous manipulations for multiple targets based on an optically induced dielectrophoresis (ODEP) mechanism, which is insufficient to ensure the stability and efficiency in an environment with potential collision risk. In this paper, a synchronously discretized manipulation method based on a centralized and decoupled path planner is proposed for transporting microparticles of different types with an OET platform. An approach based on the Kuhn-Munkres algorithm is utilized to achieve the goal assignment between target microparticles and goal positions. With the assistance of a visual feedback module, a path planning approach based on the POMDP algorithm dynamically determines the motion strategies of the particle movement to avoid potential collisions. The geometrical parameters of the virtual electrodes are optimized for different types of particles with the goal of maximum transport speed. The experiments of micropatterning with different morphologies and transporting multiple microparticles (e.g., polystyrene microspheres and 3T3 cells) to goal positions are performed. These results demonstrate that the proposed manipulation method based on optoelectronic tweezers is effective for multicell transport and promises to be used in biomedical manipulation tasks with high flexibility and efficiency.
光电镊子(OETs)具有高通量和高灵活性,在大规模并行微操纵方面具有巨大潜力。然而,在基于光诱导介电泳(ODEP)机制的多目标同步操纵中,大多数情况下虚拟电极的轨迹是预先规划的,这不足以确保在存在潜在碰撞风险的环境中的稳定性和效率。本文针对基于OET平台的不同类型微粒传输,提出了一种基于集中解耦路径规划器的同步离散操纵方法。利用基于匈牙利算法的方法实现目标微粒与目标位置之间的目标分配。在视觉反馈模块的辅助下,基于部分可观测马尔可夫决策过程(POMDP)算法的路径规划方法动态确定微粒运动的策略,以避免潜在碰撞。针对不同类型的微粒,以最大传输速度为目标对虚拟电极的几何参数进行了优化。进行了不同形态的微图案化以及将多个微粒(如聚苯乙烯微球和3T3细胞)传输到目标位置的实验。这些结果表明,所提出的基于光电镊子的操纵方法对于多细胞运输是有效的,有望以高灵活性和效率应用于生物医学操纵任务。
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