Pallet Detection

Pallet detection research focuses on accurately locating and orienting pallets within warehouse environments, primarily to automate tasks like forklift operation and inventory management. Current methods leverage computer vision techniques, employing 360-degree cameras and algorithms like Mask R-CNN and YOLOv8, often enhanced by synthetic data generation using game engines or domain randomization to improve model robustness and reduce annotation costs. This work is crucial for advancing autonomous warehousing systems and optimizing logistics efficiency by improving the speed and accuracy of pallet handling.