Researchers propose GOPT, a generalizable online 3D Bin Packing approach via Transformer-based deep reinforcement learning (DRL), for robotic object packing.
GOPT consists of a Placement Generator module and a Packing Transformer, enabling generalization across multiple environments with different bin dimensions.
Extensive experiments demonstrate that GOPT outperforms baselines and exhibits excellent generalization capabilities.
The practical applicability of GOPT is showcased through deployment with a robot.