Under-actuated hand grasping classification method based on pneumatic tactile sensation

被引：0

作者：

Cong M. ^{[1
]}

Miao Y. ^{[1
]}

Li Y. ^{[1
]}

Liu D. ^{[1
]}

机构：

[1] School of Mechanical Engineering, Dalian University of Technology, Dalian

来源：

Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2021年 / 49卷 / 09期

关键词：

Classification and identification; Discrete Kalman filtering; Pneumatic tactile sensor; Random forest classifier; Under-actuated hand;

D O I：

10.13245/j.hust.210908

中图分类号：

学科分类号：

摘要：

Pneumatic tactile array sensors were used to pick up tactile feature information. The palm and fingertips were equipped with tactile sensors, and their sensitivity and maximum repeatability error are 13.73, 10.85 kPa/N and 3.54% and 2.73%, respectively. Tactile feature data sets which were built by under-actuated used discrete Kalman filtering method to reduce noise, and were classified by random forest algorithm. Experiment results indicate that the pneumatic tactile sensor has high sensitivity and small repeatability error, and can effectively sense the changes of tactile information during the capture and classification process, relying on the under-actuated hand, avoiding the impact of speed collision on the classification results during grasping, and without complicated grasping control methods. The random forest classification method combined with discrete Kalman filtering can effectively complete the recognition and classification of objects. The recognition accuracy of this method is 93.2%. © 2021, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.

引用

页码：41 / 46

页数：5

共 15 条

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