面向显微操作的生物自动化捕捉系统研究

在生物显微操作实验中，安全稳定地捕捉生物目标具有极其重要的意义。针对传统人工操作效率低、可重复性差等问题，提出了一套面向显微操作的生物自动化捕捉系统，通过视觉反馈以及闭环控制，使用微移液管自动化抽吸在液体生长介质中的生物对象。首先采用粒子群算法对传统图像分割算法进行优化，以实现视野中生物目标与移液管位置的同步实时跟踪；然后建立了微移液管捕捉过程的动力学模型，采用非线性干扰观测器来抑制模型参数的不确定性及环境干扰，并建立了闭环控制系统；最后通过实验验证系统性能。实验测得系统的图像平均分割时间为81.05 ms,捕捉平均所需时间1.85 s,捕捉平均最大误差0.34 mm,捕捉成功率94%。实验表明，系统可以在不同光源及视野中存在微量干扰的环境下实现准确、快速、无损捕捉生物对象，并具有良好的鲁棒性。该方法的潜在应用包括胚胎玻璃化冷冻、胚胎干细胞移植、卵裂球活检、细胞力学性质检测等。

Research on the biological automatic capture system for micromanipulation

In the biological micromanipulation experiment, it is of great significance to capture biological targets safely and stably. The traditional manual operation has problems of low efficiency and poor repeatability. To address these issues, a set of biological automatic capture system for micromanipulation is proposed. Through visual feedback and closed-loop control, the micropipette is used to automatically aspirate biological objects in a liquid growth medium. Firstly, the particle swarm optimization algorithm is used to optimize the traditional image segmentation algorithm to realize the synchronous real-time tracking of the biological target in the field of view and the position of the pipette. Then, the dynamic model of micropipette capture process is formulated, the nonlinear disturbance observer is used to suppress the uncertainty of model parameters and environmental disturbance, and the closed-loop control system is established. Finally, the performance of the system is evaluated by experiments. Results show that the average image segmentation time of the system is 81. 05 ms, the average capture time is 1. 85 s, the average maximum error of capture is 0. 34 mm, and the capture success rate is 94% . The experiments show that the system can accurately, quickly and undamaged capture biological objects in the environment with trace interference in different light sources and visual fields, which has good robustness. The potential applications of this method include vitrification of embryos, embryonic stem cell transplantation, blastomere biopsy, cell mechanical property detection, etc.