Thesis - Open Access
Master of Science (MS)
Collaboration, Computer vision, Robotics
The number of robotic systems in the world is growing rapidly. However, most industrial robots are isolated in caged environments for the safety of users. There is an urgent need for human-in-the-loop collaborative robotic systems since robots are very good at performing precise and repetitive tasks but lack the cognitive ability and soft skills of humans. To fill this need, a key challenge is how to enable a robot to interpret its human co-worker’s motion and intention. This research addresses this challenge by developing a collaborative human-robot interface via innovations in computer vision, robotics, and system integration techniques. Specifically, this work integrates a holistic framework of cameras, motion sensors, and a 7-degree-of-freedom robotic manipulator controlled by vision data processing and motion planning algorithms implemented in the open-source robotics middleware Robot Operating System (ROS).
Library of Congress Subject Headings
Number of Pages
South Dakota State University
Deegan, Travis, "Human-Robot Collaboration Enabled By Real-Time Vision Tracking" (2021). Electronic Theses and Dissertations. 5249.