A Mosquito Pick-and-Place System for PfSPZ-based Malaria Vaccine Production.

A Mosquito Pick-and-Place System for PfSPZ-based Malaria Vaccine Production.
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DOI:
10.1109/tase.2020.2992131
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发表时间:
2021-01
期刊:
IEEE transactions on automation science and engineering : a publication of the IEEE Robotics and Automation Society
影响因子:
--
通讯作者:
Taylor RH
Taylor RH
中科院分区:
其他
文献类型:
--
作者:
Phalen H;Vagdargi P;Schrum ML;Chakravarty S;Canezin A;Pozin M;Coemert S;Iordachita I;Hoffman SL;Chirikjian GS;Taylor RH

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疟疾的治疗是一项全球性的健康挑战,广泛采用该疾病的疫苗将使其受益。已经开发了一种使用寄生虫恶性疟原虫(Pf)的子孢子(SPZ)来产生活生物体疫苗的方法,所述子孢子(SPZ)集中在受感染蚊子的唾液腺中。目前获得这些PfSPZ的手动解剖方法对于大规模疫苗生产不是最佳有效的。我们提出了一个改进的解剖程序和机械夹具,提高蚊子解剖的速度,并有助于deskill这一阶段的生产过程。我们进一步展示了在这个生产过程中的一个关键步骤的自动化,从一个分段设备到解剖组件中的蚊子的采摘和放置。这个单元测试的机器人蚊子拾放系统进行使用定制设计的微夹附到一个四自由度(4-DOF)的机器人在计算机视觉系统的指导下。蚊子被自动抓住并拉到一对有缺口的解剖刀片上,以去除蚊子的头部,从而允许进入唾液腺。根据计算机视觉的输出调整这些刀片的位置,以适应每个被抓住的蚊子的独特解剖结构和方向。在该系统对50只蚊子进行的试验性测试中,我们证明了100%的抓取准确度和90%的准确度,将蚊子的颈部放置在刀片凹口内,以便可以移除头部。对于这种困难且非标准的拾取和放置任务来说,这是一个有希望的结果。自动化过程可以帮助在全球范围内增加疟疾疫苗的生产。目前,生产需要技术人员手动解剖蚊子,这是一个缓慢,繁琐的过程,需要漫长的培训方案。本文提出了一种改进的手动夹具和程序,减少技术人员的培训时间。此外,提出了一种自动化的解剖过程的方法,并证明了机器人操作的蚊子与计算机视觉的帮助下的关键步骤。我们的方法可以作为一个有用的例子,系统设计和集成的从业者,寻求执行新的和具有挑战性的拾取和放置任务的小,不均匀,高度可变形的对象。
The treatment of malaria is a global health challenge that stands to benefit from the widespread introduction of a vaccine for the disease. A method has been developed to create a live organism vaccine using the sporozoites (SPZ) of the parasite Plasmodium falciparum (Pf), which are concentrated in the salivary glands of infected mosquitoes. Current manual dissection methods to obtain these PfSPZ are not optimally efficient for large-scale vaccine production. We propose an improved dissection procedure and a mechanical fixture that increases the rate of mosquito dissection and helps to deskill this stage of the production process. We further demonstrate the automation of a key step in this production process, the picking and placing of mosquitoes from a staging apparatus into a dissection assembly. This unit test of a robotic mosquito pick-and-place system is performed using a custom-designed micro-gripper attached to a four degree of freedom (4-DOF) robot under the guidance of a computer vision system. Mosquitoes are autonomously grasped and pulled to a pair of notched dissection blades to remove the head of the mosquito, allowing access to the salivary glands. Placement into these blades is adapted based on output from computer vision to accommodate for the unique anatomy and orientation of each grasped mosquito. In this pilot test of the system on 50 mosquitoes, we demonstrate a 100% grasping accuracy and a 90% accuracy in placing the mosquito with its neck within the blade notches such that the head can be removed. This is a promising result for this difficult and non-standard pick-and-place task. Automated processes could help increase malaria vaccine production to global scale. Currently, production requires technicians to manually dissect mosquitoes, a process that is slow, tedious, and requires a lengthy training regimen. This paper presents an an improved manual fixture and procedure that reduces technician training time. Further, an approach to automate this dissection process is proposed and the critical step of robotic manipulation of the mosquito with the aid of computer vision is demonstrated. Our approach may serve as a useful example of system design and integration for practitioners that seek to perform new and challenging pick-and-place tasks with small, non-uniform, and highly deformable objects.
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