Practical Framework for Path Representation and Following Control in Mobile Industrial Robots

This paper presents a practical framework for path representation and following control for mobile industrial robots. Mobile industrial robots perform various missions, such as navigating predefined routes and transporting cargo in industrial environments. Unlike traditional AGVs that rely on physical tapes installed densely along routes, our framework supports the generation of drivable paths by connecting waypoints specified by users. The proposed framework generates drivable work paths while considering the permissible deviation between waypoints and the path, as well as the maximum curvature, without nonlinear optimization techniques. Additionally, we introduce a "stopover" attribute for each waypoint to enhance usability in narrow workspaces. Furthermore, we have developed a practical path following control system that takes into account real-world challenges such as actuation delay and computational efficiency. The proposed speed planner incorporates predictive information without relying on optimization techniques, and supports robust following performance by braking intervention if path deviation increases. The effectiveness of the proposed framework has been validated through robot tests, demonstrating accurate path following performance and efficient computation.