Haptic-based robot hand grasping technique using reinforcement learning

Do-Gyeong Yuk; Jung Woo Sohn

doi:10.1117/12.3010674

10 May 2024 Haptic-based robot hand grasping technique using reinforcement learning

Do-Gyeong Yuk, Jung Woo Sohn

Proceedings Volume PC12948, Soft Mechatronics and Wearable Systems; PC129480J (2024) https://doi.org/10.1117/12.3010674
Event: SPIE Smart Structures + Nondestructive Evaluation, 2024, Long Beach, California, United States

Abstract

Researchers are developing a master glove with haptic feedback to control robot hands for precise object manipulation. This technology ensures the robot applies the right amount of force when grasping objects, preventing damage or insufficient grip. A 3D-printed robot hand with DYNAMIXEL motors was used, and reinforcement learning determined the optimal grip force through grasping experiments with haptic feedback. The results demonstrate the successful and stable grasping of various objects, especially soft ones, by the robot hand using this method.

Conference Presentation

Citation Download Citation

Do-Gyeong Yuk and Jung Woo Sohn "Haptic-based robot hand grasping technique using reinforcement learning", Proc. SPIE PC12948, Soft Mechatronics and Wearable Systems, PC129480J (10 May 2024); https://doi.org/10.1117/12.3010674

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