Dynamic Parameters Identification of Serial Robot Based on Dual Quaternion
Source abstract
Abstract
This paper studies the dynamic parameters identification problem of load and linkages of a serial robot in the presence of model uncertainty. The dynamic parameters of load and linkages of a serial robot have been identified through a combination procedure, which is useful for different platforms of serial robot systems. The purpose of this paper is to propose a dynamic parameter identification method for a serial robot based on a dual quaternion. Using the information of the force and torque of the load obtained by the six-dimensional force sensor installed on the end-effector of the robot, the dynamics parameter identification matrix of the load is derived, which also uses the information of motion speed and acceleration of the end-effector. On the other hand, the analysis of the dynamic relationship between adjacent linkages and the joints is based on dual quaternion algebra, and the identification matrix for the dynamic parameters and the difference values of associated linkages are derived, as well. The combination procedure of the method is flexible in the application of dynamic parameters identification for a serial robot using a dual quaternion. Furthermore, the proposed DQ (dual quaternion)-based method in this paper has the advantage of lower cost compared with the RBFNN (radial basis function neural network)-based method. The effectiveness of the proposed dynamic parameter identification method for a serial robot has been verified by relevant experiments.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Robotic Mechanisms and Dynamics · Image and Video Stabilization · Robot Manipulation and Learning
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Artificial Intelligence, Guilin University of Electronic Technology, Guilin 541104, China
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China
Funding
Guangxi Science and Technology Base and Talent Project of China · Project of Improving Scientific Research Basic Ability of Young and Middle-aged Teachers in Guangxi Universities
References (27)
Show source-provided references
1. System identification and a model-based control strategy of motor driven system with high order flexible manipulator10.1108/IR-01-2019-0012 ↗
2. Multi-objective optimal trajectory planning of customized industrial robot based on reliable dynamic identification for improving control accuracy10.1108/IR-12-2021-0301 ↗
3. Weon, I., Lee, S., and Yoo, J. (2024). Real-Time Semantic Segmentation of 3D LiDAR Point Clouds for Aircraft Engine Detection in Autonomous Jetbridge Operations. Appl. Sci., 14.10.3390/app14219685 ↗
4. Han, X., Wu, K., and Hui, N. (2025). Co-Optimization of Vibration Suppression and Data Efficiency in Robotic Manipulator Dynamic Modeling. Appl. Sci., 15.10.3390/app15147679 ↗
5. daVinci Research Kit Patient Side Manipulator Dynamic Model Using Augmented Lagrangian Particle Swarm Optimization10.1109/TMRB.2024.3387070 ↗
6. A Dynamic Resistive Force Model for Designing Mobile Robot in Granular Media10.1109/LRA.2022.3156636 ↗
7. Kinodynamic Model Identification: A Unified Geometric Approach10.1109/TRO.2020.3047515 ↗
8. Yang, X., Zhou, L., Zhang, C., Tian, X., and Li, Y. (2024, January 28–31). Cooperative Localization in Unknown Environment towards Multi-Robot Systems. Proceedings of the 2024 43rd Chinese Control Conference (CCC), Kunming, China.10.23919/CCC63176.2024.10661940 ↗
9. Dedicated Dynamic Parameter Identification for Delta-Like Robots10.1109/LRA.2024.3380924 ↗
10. Integrated Dimensional and Drive-train Design Optimization of a Light-weight Anthropomorphic Arm10.1016/j.robot.2011.09.004 ↗
11. Locomotion Control of Quadruped Robots With Online Center of Mass Adaptation and Payload Identification10.1109/ACCESS.2020.3044933 ↗
12. Research on the Forcefree Control of Cooperative Robots Based on Dynamic Parameters Identification10.1108/IR-01-2019-0007 ↗
13. Non-Redundant Inertial Parameters Determination for Dynamic Identification of Branched Articulated Robots10.1108/IR-12-2021-0296 ↗
14. Lei, L., Tang, Y., Zhang, W., Tang, Q., and Hao, H. (2025). YOLO-PWSL-Enhanced Robotic Fish: An Integrated Object Detection System for Underwater Monitoring. Appl. Sci., 15.10.3390/app15137052 ↗
15. An Integrated Kinematic Calibration and Dynamic Identification Method with Only Static Measurements for Serial Robot10.1109/TMECH.2023.3241302 ↗
16. Chen, Z., Wang, L., Zhang, H., Liu, J., and Wang, Q. (2022, January 2–4). Research on Dynamic Parameter Identification of Large Inertia Industrial Robot Based on RBFNNs. Proceedings of the 2022 4th International Conference on Control and Robotics (ICCR), Guangzhou, China.10.1109/ICCR55715.2022.10053871 ↗
17. A Semilinearized Approach for Dynamic Identification of Manipulator Based on Nonlinear Friction Model
18. Bazzi, D., Messeri, C., Zanchettin, A.M., and Rocco, P. (2020, January 11–13). Identification of Robot Forward Dynamics via Neural Network. Proceedings of the 2020 4th International Conference on Automation, Control and Robots (ICACR), Rome, Italy.10.1109/ICACR51161.2020.9265515 ↗
19. A dynamic parameter identification method for the 5-DOF hybrid robot based on sensitivity analysis10.1108/IR-08-2023-0178 ↗
20. The Dynamic Model of the UR10 Robot and Its ROS2 Integration10.1109/TII.2025.3534415 ↗
21. An Online Dynamic Parameter Identification Approach for Robotic Manipulator With Reformulated Physical Feasibility
22. Ni, H., Xu, C., Ye, Y., Chen, B., Luo, S., and Ji, S. (2025). Hybrid-Driven Dynamic Position Prediction of Robot End-Effector Integrating Parametric Dynamic Model and Machine Learning. Appl. Sci., 15.10.3390/app15020895 ↗
23. Zhang, G., Xu, Z., Hou, Z., Yang, W., Liang, J., Yang, G., Wang, J., Wang, H., and Han, C. (2020). A Systematic Error Compensation Strategy Based on an Optimized Recurrent Neural Network for Collaborative Robot Dynamics. Appl. Sci., 10.10.3390/app10196743 ↗
24. An Iterative Approach for Accurate Dynamic Model Identification of Industrial Robots10.1109/TRO.2020.2990368 ↗
25. A New Closed-Loop Input Error Approach for Industrial Robot Manipulator Identification Based on Evolutionary Algorithms10.1109/TCST.2024.3356391 ↗
26. Efficient Kinematic Calibration for Articulated Robot Based on Unit Dual Quaternion10.1109/TII.2023.3254666 ↗
27. Implementation and improvement of Integrated Management Systems: Recommendations for their adaptation to the ISO High-Level structure10.1016/j.cesys.2024.100227 ↗