机器人辅助生物细胞光学操作中运动规划
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摘要
分子和细胞生物学是生命科学中发展最迅速且最具广泛影响力的前沿学科之一。光镊建立在光的辐射压基础上,通过激光形成的三维全光学势阱,产生pN量级的微小操作力,可对生命状态下微米到纳米量级的生物细胞、大分子及基因等活体物质进行无伤精确操作。光镊用于操控和研究微小活体单位的行为,在细胞分类,细胞特性检测,细胞融合,胚胎干细胞培养、生物蛋白肌动力测量及DNA显微解剖等问题上,取得了开创性成果。最近,越来越多的研究热点集中在将机器人技术和生物工程技术与先进的光镊系统融合。感兴趣的生物细胞经过捕获,移动到用户指定的目标位置,而且在此过程中如何避开存在于工作区域内的障碍细胞或其他障碍颗粒,这恰恰是一个典型的机器人运动控制课题。如何拓展机器人运动规划应用到微观领域,找出一条到目标点的路径显得尤为重要。而且在细胞运送过程中,细胞所吸收的激光能量也需要特别注意。
本论文基于光镊应用的背景,建立了台式光镊生物细胞操作系统,利用机器人自动化相关技术,针对细胞移动和运送,提出一种机器人运动规划方法,实现了生物细胞在运送过程中细胞的自动壁障功能和功率吸收的最小化。本研究主要有以下三个方面组成：
首先,我们通过机器人路径规划技术与光镊操作系统的融合,提出了一种实现活体细胞自动运送的新型方法,首次将基于快速搜索随机树的路径规划方法应用到生物活体细胞的运输中。通过在稳定的酵母菌细胞水溶液中自动运输选定酵母菌细胞的实验,阐述了这种方法的实效性。
其次,考虑到生物细胞在水溶液中的布朗运动特性对细胞环境的影响,我们提出一种基于实时在线监测的动态路径规划方法,来躲避复杂环境中因布朗运动导致的动态障碍。通过在不同溶液环境中的酵母菌细胞运输实验,验证了这种方法在复杂动态溶液环境中的实效性。此外,通过将三维细胞运输拆分为两个二维细胞运输过程的方法,我们将这种应用于二维空间的路径规划方法,拓展到三维细胞运输的应用中。
最后,我们对细胞运输过程中的细胞光学能量吸收问题进行了初步的研究。通过对光镊捕获的细胞建立能量吸收模型,实现运输过程中细胞所受的光学损伤的最小化。细胞运输的路径由A星路径规划算法产生。基于提出的能量吸收模型,通过对产生路径的轨迹平滑设计,达到细胞运输吸收功率最小化的目标。
本毕业论文的主要贡献在于,利用机器人路径规划的研究方法来实现生物学细胞在简单稳定和复杂动态环境中的自动运输问题,更进一步实现细胞在运输过程中光学损伤的最小化。本课题符合当前微观生物医药学的发展趋势,对细胞生物学各个领域应用有着重要的战略发展意义。
Optical tweezers exhibits high accuracy in flexible and noninvasive manipulation of microparticles. Increasing demand for both efficiency and productivity in the manipulation of biological cells highlights the need for the advanced use of optical tweezers. Recent efforts in integrating robotics into optical tweezers to create a new cell manipulation tool have drawn considerable attention in the fields of robotics and bioengineering. Transporting the trapped cells to the user-defined goal region while avoiding collisions with other cells and obstacles present in the workspace, is a typical motion-planning problem. How to extend a robotic motion planner is important in finding a collision-free path/trajectory for transferring the trapped cells to the desired goal location, in which minimizing optical damage to the trapped cells should also be considered. This thesis aims to develop a motion planning method for cell transportation with collision avoidance and minimum optical damage to the trapped cells. The research is carried out in the following three perspectives.
First, a new approach to integrating a robotic path planner into an optical tweezers manipulation system is developed in order to achieve automated transportation of live cells. A Rapidly Exploring Random Tree (RRT) based path planner is applied for the first time to the cell transportation application. Experiments on transferring the yeast cells are performed to demonstrate the effectiveness of RRT-based path planning especially in stable aqueous solution.
Second, a dynamic path planner with an online monitoring strategy is further developed in dynamic solution to avoid collisions dynamically, in which the environmental influence caused by the Brownian movement of the other cells is particularly taken into account. The proposed dynamic path planner can successfully deal with the complex dynamic environments. Furthermore, the proposed path planner shows potential for application in3D cell transportation by dividing3D cell transportation tasks into two sub-tasks in two orthogonal2D planes.
Third, an energy model for optically trapped cells is established for the objective of minimizing the optical damage of trapped cells during the cell transportation. In path planning, an A*based path planner is used to design a collision-free path. In trajectory smoothing along the generated path, the trajectory is further optimized through parameter optimization with a new objective function that considers the minimum optical damage of trapped cell based on the established energy model.
This thesis study makes an important contribution to the illustration of using a robotic path planner to address the automated transportation of biological cells with laser setup in both stable and dynamic aqueous solutions. The issue of minimizing optical damage to the trapped cell caused by laser radiation is also considered in the path planning.
本论文基于光镊应用的背景,建立了台式光镊生物细胞操作系统,利用机器人自动化相关技术,针对细胞移动和运送,提出一种机器人运动规划方法,实现了生物细胞在运送过程中细胞的自动壁障功能和功率吸收的最小化。本研究主要有以下三个方面组成：
首先,我们通过机器人路径规划技术与光镊操作系统的融合,提出了一种实现活体细胞自动运送的新型方法,首次将基于快速搜索随机树的路径规划方法应用到生物活体细胞的运输中。通过在稳定的酵母菌细胞水溶液中自动运输选定酵母菌细胞的实验,阐述了这种方法的实效性。
其次,考虑到生物细胞在水溶液中的布朗运动特性对细胞环境的影响,我们提出一种基于实时在线监测的动态路径规划方法,来躲避复杂环境中因布朗运动导致的动态障碍。通过在不同溶液环境中的酵母菌细胞运输实验,验证了这种方法在复杂动态溶液环境中的实效性。此外,通过将三维细胞运输拆分为两个二维细胞运输过程的方法,我们将这种应用于二维空间的路径规划方法,拓展到三维细胞运输的应用中。
最后,我们对细胞运输过程中的细胞光学能量吸收问题进行了初步的研究。通过对光镊捕获的细胞建立能量吸收模型,实现运输过程中细胞所受的光学损伤的最小化。细胞运输的路径由A星路径规划算法产生。基于提出的能量吸收模型,通过对产生路径的轨迹平滑设计,达到细胞运输吸收功率最小化的目标。
本毕业论文的主要贡献在于,利用机器人路径规划的研究方法来实现生物学细胞在简单稳定和复杂动态环境中的自动运输问题,更进一步实现细胞在运输过程中光学损伤的最小化。本课题符合当前微观生物医药学的发展趋势,对细胞生物学各个领域应用有着重要的战略发展意义。
Optical tweezers exhibits high accuracy in flexible and noninvasive manipulation of microparticles. Increasing demand for both efficiency and productivity in the manipulation of biological cells highlights the need for the advanced use of optical tweezers. Recent efforts in integrating robotics into optical tweezers to create a new cell manipulation tool have drawn considerable attention in the fields of robotics and bioengineering. Transporting the trapped cells to the user-defined goal region while avoiding collisions with other cells and obstacles present in the workspace, is a typical motion-planning problem. How to extend a robotic motion planner is important in finding a collision-free path/trajectory for transferring the trapped cells to the desired goal location, in which minimizing optical damage to the trapped cells should also be considered. This thesis aims to develop a motion planning method for cell transportation with collision avoidance and minimum optical damage to the trapped cells. The research is carried out in the following three perspectives.
First, a new approach to integrating a robotic path planner into an optical tweezers manipulation system is developed in order to achieve automated transportation of live cells. A Rapidly Exploring Random Tree (RRT) based path planner is applied for the first time to the cell transportation application. Experiments on transferring the yeast cells are performed to demonstrate the effectiveness of RRT-based path planning especially in stable aqueous solution.
Second, a dynamic path planner with an online monitoring strategy is further developed in dynamic solution to avoid collisions dynamically, in which the environmental influence caused by the Brownian movement of the other cells is particularly taken into account. The proposed dynamic path planner can successfully deal with the complex dynamic environments. Furthermore, the proposed path planner shows potential for application in3D cell transportation by dividing3D cell transportation tasks into two sub-tasks in two orthogonal2D planes.
Third, an energy model for optically trapped cells is established for the objective of minimizing the optical damage of trapped cells during the cell transportation. In path planning, an A*based path planner is used to design a collision-free path. In trajectory smoothing along the generated path, the trajectory is further optimized through parameter optimization with a new objective function that considers the minimum optical damage of trapped cell based on the established energy model.
This thesis study makes an important contribution to the illustration of using a robotic path planner to address the automated transportation of biological cells with laser setup in both stable and dynamic aqueous solutions. The issue of minimizing optical damage to the trapped cell caused by laser radiation is also considered in the path planning.
引文
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