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.
This work seeks to incorporate existing methodologies for controlling and localizing robotic hardware of different capabilities in order to create an autonomous system of robots to move deliverables within an established environment. The system utilizes modular designs to employ rapid prototyping of different robotic capabilities highlighting the adaptability of this methodology. A high-level task manager centrally assigns priorities to each deliverable, and, through decentralized planning, the robots deconflict with one another during execution. Through the adoption of reinforcement learning techniques, our robots create individual path plans that adapt to both static and dynamic obstacles in real time. Contrasting other works that manage robotic systems in a predetermined and fixed environment, we demonstrate a single, simplified approach that can control and localize modular robots simultaneously in any given setting, to include warehouses and factories. This work utilizes the Robotic Operating System (ROS) to communicate between multiple robots of various capabilities and a single task manager, synchronizing autonomous movement and avoiding other tracked objects.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.