Research on target recognition in the end effector of mechanical gripper

Yungao Yang; Xiaoqing Chen; Yongyi Yuan; Hanyu Lu

doi:10.1117/12.3025702

28 February 2024 Research on target recognition in the end effector of mechanical gripper

Yungao Yang, Xiaoqing Chen, Yongyi Yuan, Hanyu Lu

Proceedings Volume 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023); 130712H (2024) https://doi.org/10.1117/12.3025702
Event: International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 2023, Shenyang, China

Abstract

To address the problem of excessive dependence on the main control unit and poor adaptability of the mechanical claw movement, the paper proposes a feasible solution to the end-point visual perception of the mechanical arm, which improves the adaptability and intelligence of the robot. Based on the AI terminal Kendryte K210 module, the paper constructed an image sample training set, completed model training, and then integrated the module into the mechanical arm endpoint to achieve target recognition and synchronous mechanical arm movements. The experiments show that the mechanical claw designed with this solution can perceive the spatial position of the target object based on target recognition, achieving the goal of "not dropping heavy objects and not breaking fragile objects," making target recognition more flexible in the mechanical hand.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yungao Yang, Xiaoqing Chen, Yongyi Yuan, and Hanyu Lu "Research on target recognition in the end effector of mechanical gripper", Proc. SPIE 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 130712H (28 February 2024); https://doi.org/10.1117/12.3025702

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