Implementing a Computer Vision-based Collision Avoidance System for a Collaborative Surgical Assistant Robot

This project aims to enhance the safety, precision, and efficiency of robotic surgical assistants — collaborative robots designed to work alongside surgeons — by developing a computer vision-based system that prevents collisions in real time. Using cameras and advanced image processing techniques, the system will monitor the operating room, detecting people and other obstacles. It will then use an adaptive decision-making to adjust the movements of the robot based on sensory information. By reducing risks for both patients and medical staff, this technology will make robotic assistance more reliable, reducing the physical strain on surgeons. In the long term, this will allow surgical teams to operate more efficiently, reducing the number of personnel needed per procedure, and thus improving accessibility to advanced surgeries in underserved regions. Participating institutions benefit by advancing their research in artificial intelligence, robotics, and healthcare technology while fostering interdisciplinary collaboration. This project will also contribute to the development of new safety policies for collaborative robots, bridging the gap between computer vision research and surgical robot safety, and paving the way for more intelligent, adaptive, and safer robotic assistants.

Faculty Supervisor:

Yue Hu

Student:

Partner:

National University of Kyiv-Mohyla Academy

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology; Information and Communications Technology; Artificial Intelligence

University:

University of Waterloo

Program: