Task allocation and coordinated motion planning for autonomous multi-robot optical inspection systems

Autonomous multi-robot optical inspection systems are increasingly applied for obtaining inline measurements in process monitoring and quality control. Numerous methods path planning robotic coordination have been developed static dynamic environments to different fields. However, these approaches may not work the autonomous system due fast computation requirements of optimization, unique characteristics on end-effector orientations, complex large-scale free-form product surfaces. This paper proposes a novel task allocation methodology coordinated motion inspection. Specifically, (1) local robust is proposed achieve efficient well-balanced measurement assignment among robots; (2) collision-free via searching coordinate space perturbation probe poses or paths conflicting robots. A case study shows that approach can mitigate risk collisions between robots environments, resolve conflicts robots, reduce cycle time significantly consistently.