A hierarchical spatial-aware algorithm with efficient reinforcement learning for human-robot task planning and allocation in production

ArXi:2604.12669v1 Announce Type: new In advanced manufacturing systems, humans and robots collaborate to conduct the production process. Effective task planning and allocation (TPA) is crucial for achieving high production efficiency, yet it remains challenging in complex and dynamic manufacturing environments. The dynamic nature of humans and robots, particularly the need to consider spatial information (e.g., humans' real-time position and the distance they need to move to complete a task), substantially complicates.