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A Closed-Loop Framework for the Inverse Kinematics of the 7 Degrees of Freedom Manipulator

Published online by Cambridge University Press:  13 August 2020

Guoli Song Open the ORCID record for Guoli Song [Opens in a new window] ,
Shun Su ,
Yingli Li ,
Xingang Zhao ,
Huibin Du ,
Jianda Han  and
Yiwen Zhao Open the ORCID record for Yiwen Zhao [Opens in a new window]
Guoli Song
Affiliation:
State Key Laboratory of Rdobotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China. E-mails: [email protected], [email protected], [email protected], [email protected] Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China Liaoning Medical Surgery and Rehabilitation Robot Engineering Research Center, Shenyang 110134, China Department of Orthopaedics, Affifiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou 646000, China
Shun Su
Affiliation:
State Key Laboratory of Rdobotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China. E-mails: [email protected], [email protected], [email protected], [email protected] Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China University of Chinese Academy of Sciences, Beijing 100049, China. E-mail: [email protected]
Yingli Li
Affiliation:
State Key Laboratory of Rdobotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China. E-mails: [email protected], [email protected], [email protected], [email protected] Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China University of Chinese Academy of Sciences, Beijing 100049, China. E-mail: [email protected]
Xingang Zhao
Affiliation:
State Key Laboratory of Rdobotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China. E-mails: [email protected], [email protected], [email protected], [email protected] Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
Huibin Du
Affiliation:
State Key Laboratory of Rdobotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China. E-mails: [email protected], [email protected], [email protected], [email protected] Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
Jianda Han
Affiliation:
State Key Laboratory of Rdobotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China. E-mails: [email protected], [email protected], [email protected], [email protected] Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China College of Artificial Intelligence, Nankai University, Tianjing 300071, China. E-mail: [email protected]
Yiwen Zhao*
Affiliation:
State Key Laboratory of Rdobotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China. E-mails: [email protected], [email protected], [email protected], [email protected] Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
*
*Corresponding author. E-mail: [email protected]
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Summary

The 7 degrees of freedom (DOF) redundant manipulator greatly improves obstacle/singularity avoidance capability and operational flexibility. However, the inverse kinematics problem of this manipulator is very difficult to solve because it has an infinite number of solutions. This paper uses a new numerical sequence processing method with a closed-loop framework to solve the inverse kinematics of the 7-DOF redundant manipulator. Simulation and experiment show that this method has high commonality. No special structure of the robot is required, and this method has improved computational efficiency and reliability.

Keywords

7-DOF manipulatorRedundant manipulatorUKFInverse kinematicsClosed-loop framework
Type
Articles
Information
Robotica , Volume 39 , Issue 4 , April 2021 , pp. 572 - 581
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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