Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-14T15:16:35.406Z Has data issue: false hasContentIssue false
  • English
  • Français

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]
Get access Rights & Permissions [Opens in a new window]

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

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Shimizu, M., Kakuya, H., Yoon, W. K., Kitagaki, K. and Kosuge, K., “Analytical inverse kinematic computation for 7-DOF redundant manipulators with joint limits and its application to redundancy resolution,” IEEE Trans. Robot. 24(5), 1131–1142 (2008).10.1109/TRO.2008.2003266Google Scholar
Yu, C., Jin, M. and Liu, H., “An Analytical Solution for Inverse Kinematic of 7-DOF Redundant Manipulators with Offset-Wrist,” 2012 IEEE International Conference on Mechatronics and Automation (2012) pp. 92–97.Google Scholar
Jiang, L., Huo, X., Liu, Y. and Liu, H., “An Integrated Inverse Kinematic Approach for the 7-DOF Humanoid Arm with Offset Wrist,” 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO) (2013) pp. 2737–2742.Google Scholar
Mu, Z., Yuan, H., Xu, W., Liu, T. and Liang, B., “A segmented geometry method for kinematics and configuration planning of spatial hyper-redundant manipulators,” IEEE Trans. Syst. Man & Cybern. Syst. 50(5), 1746–1756 (2020).10.1109/TSMC.2017.2784828Google Scholar
Xiao, Y., Wang, X., Li, Z. and Zhao, Y., “A method of kinematic analysis and singularity elimination for upper-limb exoskeleton,” Robot. 38(1), 33–40 (2016).Google Scholar
Reiter, A., Müller, A. and Gattringer, H., “On higher order inverse kinematics methods in time-optimal trajectory planning for kinematically redundant manipulators,” IEEE Trans. Ind. Inform. 14(4), 1681–1690 (2018).Google Scholar
Amanpreet, S., Ekta, S., Sanjeev, S. and Ashish, S., “Kinematic modeling of a 7-degree of freedom spatial hybrid manipulator for medical surgery,” Proc. Inst. Mech. Eng. H J. Eng. Med. 232(1), 12–23 (2018).CrossRefGoogle Scholar
Donelan, P., “Singularity-theoretic methods in robot kinematics,” Robotica. 25(6), 19 (2007).CrossRefGoogle Scholar
Zhang, Z., Fu, T., Yan, Z., Jin, L., Xiao, L., Sun, Y. and Yu, Z., “A varying-parameter convergent-differential neural network for solving joint-angular-drift problems of redundant robot manipulators,” IEEE/ASME Trans. Mechatron. 23(2), 679–689 (2018).Google Scholar
Jiang, G., Luo, M., Bai, K. and Chen, S., “A precise positioning method for a puncture robot based on a PSO-optimized BP neural network algorithm,” Appl. Sci. 7(10), 969 (2017).10.3390/app7100969CrossRefGoogle Scholar
Carlos, L., Jesus, H., Alanis, A. Y. and Nancy, A., “A soft computing approach for inverse kinematics of robot manipulators,” Eng. Appl. Artif. Intell. 74, 104–120 (2018).Google Scholar
Huang, H., Chen, C. and Wang, P., “Particle Swarm Optimization for Solving the Inverse Kinematics of 7-DOF Robotic Manipulators,” 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), (2012) pp. 3105–3110.Google Scholar
Ding, Q., Zhao, X. and Han, J., “A general closed-loop framework for multi-dimensional sequence processing,” Intell. Auton. Syst. 194, 311–321 (2013).Google Scholar
Julier, S. J., Uhlmann, J. K. and Durrant-Whyte, H. F., “A New Approach for Filtering Nonlinear Systems,” Proceedings of 1995 American Control Conference - ACC’95, 3, (1995) pp. 1628–1632.Google Scholar
Wan, E. and Merwe, R., “The Unscented Kalman Filter for Nonlinear Estimation,” Proceeding of the Symposium 2000 on Adaptive System for Signal Processing, Communication and Control (AS-SPCC), (2000) pp. 153–158.Google Scholar
Joukhadar, A. and Hanna, D. K., “UKF-based enhancement and ROS implementation of 4-WDDMR localization with advanced control system,” Cogent Eng. 5(1), 1481561 (2018).CrossRefGoogle Scholar
Du, G., Shao, H., Chen, Y., Zhang, P. and Liu, X., “An online method for serial robot self-calibration with CMAC and UKF,” Robot. Comput. Integr. Manuf. 42, 39–48 (2016).10.1016/j.rcim.2016.05.006Google Scholar
Mazzoleni, M., Noh, S. J., Lee, H., Liu, Y., Seo, D. J., Amaranto, A., Alfonso, L. and Solomatine, D. P., “Real-time assimilation of streamflow observations into a hydrological routing model: Effects of model structures and updating methods,” Hydrolog. Sci. J. 63(3), 386–407 (2018).10.1080/02626667.2018.1430898Google Scholar
https://petercorke.com/toolboxes/robotics-toolbox/ (accessed on 3th Oct 2018).Google Scholar
https://www.kuka.com/en-us/products/mobility/mobile-robot-systems/kmr-iiwa (accessed on 3th Oct 2018).Google Scholar