RoboCam: A Flexible High-Throughput Platform for Biological Research

Authors: Sergio Gonzalez, Jr., Alexandria Nesbeth, Keith Curry, Jacob Vazquez, Diana Carolina Ceron, Kimi Lee, Peter Chudinov

Faculty Supervisor: Raymond Esquerra

Department: Chemistry & Biochemistry

Scientific research often involves repeating methods and protocols to produce data for analysis. Recent technological advancements have led to the development of instruments that aid biologists by automating time-consuming tasks like liquid transfer, cell culturing, and microscopy. However, these systems tend to be large, expensive, and rigid, limited to specific functions, making them inaccessible to many researchers. To overcome these limitations, we developed an affordable and flexible robotic and vision system, RoboCaM, designed to automate repetitive lab procedures and adapt to the specific needs of different experiments. Leveraging the precision of inexpensive 3D printers, the cost-effectiveness of Raspberry Pi computers, affordable digital cameras, and open-source resources like OpenCV and Python, RoboCaM introduces a new level of versatility and accessibility. We showcase its application in two projects: FlyCaM and StentorCaM. In FlyCaM, we have successfully automated fly embryos' imaging, collection, detection, and counting in high-throughput 48-well plates. In StentorCaM, we showcase an infrared (IR) microscope capable of imaging photosensitive organisms without the interference typically caused by visible light. This enables the measurement of Stentor photophobia and phototaxis following exposure to external light stimuli. The RoboCaM platform presents a cost-effective solution for laboratories, enhancing their research efficiency by automating repetitive tasks.