Mosquito pick-and-place: Automating a key step in PfSPZ-based Malaria vaccine production

Henry Phalen, Prasad Vagdargi, Michael Pozin, Sumana Chakravarty, Gregory S. Chirikjian, Iulian Iordachita, Russell H Taylor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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 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 from a mesh platform 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. An analysis of the failure cases provides insights for improvements to be implemented as this robotic pick-and-place system is integrated into a larger automated mosquito dissection system under development.

Original languageEnglish (US)
Title of host publication2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019
PublisherIEEE Computer Society
Pages12-17
Number of pages6
ISBN (Electronic)9781728103556
DOIs
StatePublished - Aug 1 2019
Event15th IEEE International Conference on Automation Science and Engineering, CASE 2019 - Vancouver, Canada
Duration: Aug 22 2019Aug 26 2019

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2019-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference15th IEEE International Conference on Automation Science and Engineering, CASE 2019
CountryCanada
CityVancouver
Period8/22/198/26/19

Fingerprint

Dissection
Vaccines
Computer vision
Robotics
Grippers
Automation
Health
Robots

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Phalen, H., Vagdargi, P., Pozin, M., Chakravarty, S., Chirikjian, G. S., Iordachita, I., & Taylor, R. H. (2019). Mosquito pick-and-place: Automating a key step in PfSPZ-based Malaria vaccine production. In 2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019 (pp. 12-17). [8842860] (IEEE International Conference on Automation Science and Engineering; Vol. 2019-August). IEEE Computer Society. https://doi.org/10.1109/COASE.2019.8842860

Mosquito pick-and-place : Automating a key step in PfSPZ-based Malaria vaccine production. / Phalen, Henry; Vagdargi, Prasad; Pozin, Michael; Chakravarty, Sumana; Chirikjian, Gregory S.; Iordachita, Iulian; Taylor, Russell H.

2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019. IEEE Computer Society, 2019. p. 12-17 8842860 (IEEE International Conference on Automation Science and Engineering; Vol. 2019-August).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Phalen, H, Vagdargi, P, Pozin, M, Chakravarty, S, Chirikjian, GS, Iordachita, I & Taylor, RH 2019, Mosquito pick-and-place: Automating a key step in PfSPZ-based Malaria vaccine production. in 2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019., 8842860, IEEE International Conference on Automation Science and Engineering, vol. 2019-August, IEEE Computer Society, pp. 12-17, 15th IEEE International Conference on Automation Science and Engineering, CASE 2019, Vancouver, Canada, 8/22/19. https://doi.org/10.1109/COASE.2019.8842860
Phalen H, Vagdargi P, Pozin M, Chakravarty S, Chirikjian GS, Iordachita I et al. Mosquito pick-and-place: Automating a key step in PfSPZ-based Malaria vaccine production. In 2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019. IEEE Computer Society. 2019. p. 12-17. 8842860. (IEEE International Conference on Automation Science and Engineering). https://doi.org/10.1109/COASE.2019.8842860
Phalen, Henry ; Vagdargi, Prasad ; Pozin, Michael ; Chakravarty, Sumana ; Chirikjian, Gregory S. ; Iordachita, Iulian ; Taylor, Russell H. / Mosquito pick-and-place : Automating a key step in PfSPZ-based Malaria vaccine production. 2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019. IEEE Computer Society, 2019. pp. 12-17 (IEEE International Conference on Automation Science and Engineering).
@inproceedings{55e2311a7cda484e8eadf2ab51842ccc,
title = "Mosquito pick-and-place: Automating a key step in PfSPZ-based Malaria vaccine production",
abstract = "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 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 from a mesh platform 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. An analysis of the failure cases provides insights for improvements to be implemented as this robotic pick-and-place system is integrated into a larger automated mosquito dissection system under development.",
author = "Henry Phalen and Prasad Vagdargi and Michael Pozin and Sumana Chakravarty and Chirikjian, {Gregory S.} and Iulian Iordachita and Taylor, {Russell H}",
year = "2019",
month = "8",
day = "1",
doi = "10.1109/COASE.2019.8842860",
language = "English (US)",
series = "IEEE International Conference on Automation Science and Engineering",
publisher = "IEEE Computer Society",
pages = "12--17",
booktitle = "2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019",

}

TY - GEN

T1 - Mosquito pick-and-place

T2 - Automating a key step in PfSPZ-based Malaria vaccine production

AU - Phalen, Henry

AU - Vagdargi, Prasad

AU - Pozin, Michael

AU - Chakravarty, Sumana

AU - Chirikjian, Gregory S.

AU - Iordachita, Iulian

AU - Taylor, Russell H

PY - 2019/8/1

Y1 - 2019/8/1

N2 - 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 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 from a mesh platform 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. An analysis of the failure cases provides insights for improvements to be implemented as this robotic pick-and-place system is integrated into a larger automated mosquito dissection system under development.

AB - 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 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 from a mesh platform 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. An analysis of the failure cases provides insights for improvements to be implemented as this robotic pick-and-place system is integrated into a larger automated mosquito dissection system under development.

UR - http://www.scopus.com/inward/record.url?scp=85072947971&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85072947971&partnerID=8YFLogxK

U2 - 10.1109/COASE.2019.8842860

DO - 10.1109/COASE.2019.8842860

M3 - Conference contribution

AN - SCOPUS:85072947971

T3 - IEEE International Conference on Automation Science and Engineering

SP - 12

EP - 17

BT - 2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019

PB - IEEE Computer Society

ER -