November 8, 2025Open Access

Learning Dual-Arm Coordination for Grasping Large Flat Objects

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Experimental results show improved grasping of large flat objects without additional maneuvers.
The reinforcement learning model effectively trains dual-arm coordination for robotic grasping tasks.
Training was conducted in Isaac Gym, leading to direct applications in real robot environments.
Strong generalization allows transfer of learned policies to unseen objects, indicating robust learning.

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Experiment demonstrates improved grasping efficiency in robotic systems, suggesting advances in dual-arm coordination and transfer learning.

Wang et al. (2025) studied this question.

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Experiment demonstrates improved grasping efficiency in robotic systems, suggesting advances in dual-arm coordination and transfer learning.