The purpose of this project is to safely integrate robots and humans into industrial processes. The most prevalent current solution to the problem of safe integration of robots and humans is to place the robots in cages to separate the workspaces of humans and robots. The cages prevent humans from entering the robot’s workspace and prevent any contact between the two entities. However, cages present an inefficiency in the industrial process as they require additional space and do not allow a seamless integration of robots and humans. This paper proposes a multi-tiered safety system that combines vision and torque feedback safety measures that can stop robot movement. The vision safety system proposed detects foreign movement in the camera frame and stops the robot’s motion. The torque system proposed detects unexpected torques in the robot’s motors and stops the robot’s motion. The results show that both safety systems can effectively stop robot motion if an unsafe condition is detected. For the industrial process of interest, the multi-tiered safety system is expected to lay the foundation for future integration of humans and robots on the industrial process. Contributions to the academic community for this paper are a multi-tiered safety system for robots in industrial processes, a machine learning circle detection algorithm, and a novel end-of-arm-tooling (EOAT) for the industrial process of interest.
