SCARA based peg-in-hole assembly using compliant IPMC micro gripper

被引：77

作者：

Jain, R. K. ^{[1
]}

Majumder, S. ^{[1
]}

Dutta, A. ^{[2
]}

机构：

[1] CMERI, CSIR, Design Mech Syst Grp, Micro Robot Lab, Durgapur 713209, WB, India

[2] Indian Inst Technol, Dept Mech Engn, Kanpur 208016, Uttar Pradesh, India

来源：

ROBOTICS AND AUTONOMOUS SYSTEMS | 2013年 / 61卷 / 03期

关键词：

Peg-in-hole assembly; SCARA; IPMC micro gripper; Compliant assembly; ELECTRIC CONNECTORS; FAULT-DETECTION;

D O I：

10.1016/j.robot.2012.12.001

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Robotic assembly is difficult as there always exist position errors between two mating parts. Compliance is added in a selective compliant assembly robot arm (SCARA) in the form of a two ionic polymer metal composite (IPMC) fingers based micro gripper. This micro gripper is integrated at the end effector position of a SCARA robot. Peg-hole interaction is analytically modeled and based on it the force required to correct the lateral and angular errors by IPMC is calculated. A proportional-derivative (PD) controller is designed to actuate the IPMC to get the desired force for correcting the peg position before assembly. Simulations and experiments were carried out by developing an IPMC micro gripper and using it to analyze various cases of peg in hole assembly. The experimental results prove that adding compliance through IPMC helps in peg-in-hole assembly. (c) 2012 Elsevier B.V. All rights reserved.

引用

页码：297 / 311

页数：15

共 48 条

[41] A Noncontact Control Strategy for Circular Peg-in-Hole Assembly Guided by the 6-DOF Robot Based on Hybrid Vision [J].

Xu, Jingjing ;

Liu, Kang ;

Pei, Yanhu ;

Yang, Congbin ;

Cheng, Yanhong ;

Liu, Zhifeng .

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 71

[42] Sample-Efficiency, Stability and Generalization Analysis for Deep Reinforcement Learning on Robotic Peg-in-Hole Assembly [J].

Deng, Yuelin ;

Hou, Zhimin ;

Yang, Wenhao ;

Xu, Jing .

INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2021, PT II, 2021, 13014 :393-403

[43] Cross-Shaped Peg-in-Hole Autonomous Assembly System via BP Neural Network Based on Force/Moment and Visual Information [J].

Ma, Zheng ;

Hu, Xiaoguang ;

Zhou, Yulin .

MACHINES, 2024, 12 (12)

[44] A Novel Delta-Like Parallel Robot With Three Translations and Two Pitch Rotations for Peg-in-Hole Assembly [J].

Cheng, Peng ;

Cao, Wen-ao ;

Liu, Degang ;

Cui, Jun ;

Lai, Jingpei .

JOURNAL OF MECHANISMS AND ROBOTICS-TRANSACTIONS OF THE ASME, 2025, 17 (02)

[45] Posture estimation and adjustment for robotic precise peg-in-hole based on fuzzy variable admittance control [J].

Ning, Rui ;

Liu, Yi ;

We, Jinbo ;

Yu, Shuanghe .

2024 14TH ASIAN CONTROL CONFERENCE, ASCC 2024, 2024, :2237-2242

[46] Integrating Vision Localization and Deep Reinforcement Learning for High-Precision, Low-Cost Peg-in-Hole Assembly [J].

Lin, Ze ;

Wang, Chuang ;

Xie, Longhan ;

Zeng, Miaosheng ;

Wu, Sihan .

2024 IEEE INTERNATIONAL CONFERENCE ON CYBERNETICS AND INTELLIGENT SYSTEMS, CIS AND IEEE INTERNATIONAL CONFERENCE ON ROBOTICS, AUTOMATION AND MECHATRONICS, RAM, CIS-RAM 2024, 2024, :138-143

[47] Vision-based robotic peg-in-hole research: integrating object recognition, positioning, and reinforcement learning [J].

Chen, Chengjun ;

Wang, Hao ;

Pan, Yong ;

Li, Dongnian .

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2024, 135 (3-4) :1119-1129

[48] Online Action Learning using Kernel Density Estimation for Quick Discovery of Good Parameters for Peg-in-Hole Insertion [J].

Sorensen, Lars Caroe ;

Buch, Jacob Porksen ;

Petersen, Henrik Gordon ;

Kraft, Dirk .

ICINCO: PROCEEDINGS OF THE 13TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, VOL 2, 2016, :166-177

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