TY - GEN
T1 - Design a Pneumatic-Driven Sorting Modular Soft Hand Based on Visual Object Detection
AU - Zhang, Yu
AU - Zhou, Jiangyu
AU - Li, Yu
AU - Zheng, Tianjiao
AU - Zhao, Sikai
AU - Zhu, Yanhe
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - Bionic soft hands have attracted extensive attention due to their high flexibility, safety, and adaptability, enabling them to mimic human hand movements such as grasping. This paper presents the design a pneumatic-driven sorting modular soft hand based on visual object detection. Additionally, a comprehensive sorting system control platform was constructed, integrating vision sensor, the modular soft hand, object detection, drive units, and mobile sorting strategies. To verify the system's performance, we established datasets for three types of objects: Lightweight building blocks, fragile eggs, and fresh oranges, and utilized the YOLOv8 algorithm to train the object detection model, thus accurately identifying the type of objects to be sorted and the three-dimensional coordinates of their grasping points. The experimental results demonstrate that this control platform is efficient, stable, and non-destructive in both single-target and multi-target mixed sorting, fully verifying the system's practicality and reliability.
AB - Bionic soft hands have attracted extensive attention due to their high flexibility, safety, and adaptability, enabling them to mimic human hand movements such as grasping. This paper presents the design a pneumatic-driven sorting modular soft hand based on visual object detection. Additionally, a comprehensive sorting system control platform was constructed, integrating vision sensor, the modular soft hand, object detection, drive units, and mobile sorting strategies. To verify the system's performance, we established datasets for three types of objects: Lightweight building blocks, fragile eggs, and fresh oranges, and utilized the YOLOv8 algorithm to train the object detection model, thus accurately identifying the type of objects to be sorted and the three-dimensional coordinates of their grasping points. The experimental results demonstrate that this control platform is efficient, stable, and non-destructive in both single-target and multi-target mixed sorting, fully verifying the system's practicality and reliability.
KW - Modular Soft Hand
KW - Object Detection
KW - Sorting System
UR - https://www.scopus.com/pages/publications/85218499595
U2 - 10.1007/978-981-96-0798-3_24
DO - 10.1007/978-981-96-0798-3_24
M3 - 会议稿件
AN - SCOPUS:85218499595
SN - 9789819607976
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 316
EP - 330
BT - Intelligent Robotics and Applications - 17th International Conference, ICIRA 2024, Proceedings
A2 - Lan, Xuguang
A2 - Mei, Xuesong
A2 - Jiang, Caigui
A2 - Zhao, Fei
A2 - Tian, Zhiqiang
PB - Springer Science and Business Media Deutschland GmbH
T2 - 17th International Conference on Intelligent Robotics and Applications, ICIRA 2024
Y2 - 31 July 2024 through 2 August 2024
ER -