From Pixels to Shelf: An Integrated Robotic System for Autonomous Supermarket Stocking with a Mobile Manipulator
The research developed an efficient modular robotic system for autonomous shelf stocking in supermarkets. It integrates off-the-shelf hardware with ROS2 and uses Behavior Trees for planning, YOLO/SAM2 for vision, and Model Predictive Control (MPC) for precise navigation. Experiments showed over 98% success rate in pick-and-place tasks, though performance still lags behind human workers.