A safe autonomous stacker in human shared workspaces

This paper proposes a solution for safe navigation of stacker vehicles in workspaces shared with people, with a focus on the docking manoeuvres for pallet picking and dropping. Behaviours for way-point and wall following are developed following the attractor dynamics approach. Then, these behaviours are orchestrated by state machines (that activate or deactivate them) depending on the specific task. Each of these states also defines different safe areas and maximum travel speeds, which is a requirement for safe operation. Results of real experiments are presented that show the standard operation and its robustness against perturbations (people in the way) and failure detection (missing pallets).