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

Henry PhalenPrasad VagdargiMariah L SchrumSumana ChakravartyAmanda CanezinMichael PozinSuat CoemertIulian IordachitaStephen L HoffmanGregory S ChirikjianRussell H Taylor
Published in: IEEE transactions on automation science and engineering : a publication of the IEEE Robotics and Automation Society (2020)
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.
Keyphrases
  • aedes aegypti
  • dengue virus
  • minimally invasive
  • deep learning
  • plasmodium falciparum
  • primary care
  • zika virus
  • virtual reality
  • machine learning
  • single cell