Abstract
In this paper, a new dynamics modeling approach is proposed by using the Newton-Euler equation in screw form. The momentum screw equations of multi-rigid bodies are derived in an absolute coordinate system, which systematically demonstrates the theorem of momentum and the theorem of moment of momentum of a multi-rigid body system in the screw coordinate system. At the same time, this also provides a new approach for the study of velocity screw (twist) and force screw (wrench). The twist is utilized as a variable to associate the screw displacement with the acceleration of the rigid body. On the basis, of the dynamics equation upper limb of a humanoid robot was formed, which was solved by the numerical method. The results show that compared with the common Lagrange equation, the method proposed in this paper requires less mathematical computation and is more convenient for computer programming. In addition, unlike the common Newton-Euler method in Cartesian coordinates, the method proposed by the author has fewer algebraic volumes and fewer computational procedures.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hicks, J.L., Uchida, T.K., Seth, A., Rajagopal, A., Delp, S.L.: Is my model good enough? best practices for verification and validation of musculoskeletal models and simulations of movement. ASME. J. Biomech. Eng. 137, 020905 (2015)
Manns, P., Sreenivasa, M., Millard, M., Mombaur, K.: Motion optimization and parameter identification for a human and lower back exoskeleton model. IEEE Robot. Autom. Let. 2, 1564–1570 (2017)
Lamas, M., Mouzo, F., Michaud, F., Lugris, U., Cuadrado, J.: Comparison of several muscle modeling alternatives for computationally intensive algorithms in human motion dynamics. Multibody Sys. Dyn. 54, 415–442 (2022)
Liu, X.H., Zheng, X.H., Li, S.P., Chen, X.H., Wang, Z.B.: Improved adaptive neural network control for humanoid robot hand in workspace, Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci. 229, 869–881 (2014)
Zhao, J.S., Sun, H.L.: Kinetostatics of a serial robot in screw form. Adv. Mech. Eng. 15, 1–12 (2023)
Qu, J.D., Zhang, F.H., Wang, Y., Fu, Y.L.L: Human-like coordination motion learning for a redundant dual-arm robot. Robot. Comput. Integrat. Manufac. 57 (2019)
Shimizu, M.: Analytical inverse kinematics for 5-DOF humanoid manipulator under arbitrarily specified unconstrained orientation of end-effector. Robotica 33, 1–21 (2015)
Paparisabet, M.A., Dehghani, R., Ahmadi, A.R.: Knee and torso kinematics in generation of optimum gait pattern based on human-like motion for a seven-link biped robot. Multibody Sys. Dyn. 47, 117–136 (2019)
Coronel-Escamilla, A., Torres, F., Gómez-Aguilar, J.F., Escobar-Jiménez, R.F., Guerrero-RamÃrez, G.V.: On the trajectory tracking control for an SCARA robot manipulator in a fractional model driven by induction motors with PSO tuning. Multibody Sys. Dyn. 43, 257–277 (2018)
Hashemi, E., Khajepour, A.: Kinematic and three-dimensional dynamic modeling of a biped robot. Proc. Inst. Mech. Eng, Part K: J. Multi-body Dyn. 231, 57–73 (2016)
Fang, Y., Wang, S., Cui, D., Bi, Q.S., Yan, C.L.: Multi-body dynamics model of crawler wall-climbing robot. Proc. Inst. Mech. Eng, Part K: J. Multi-body Dyn. 236, 535–553 (2022)
Dimeas, F., Avendaño-Valencia, L.D., Aspragathos, N.: Human - robot collision detection and identification based on fuzzy and time series modelling. Robotica 33, 1886–1898 (2015)
Zhao, J.S., Feng, Z.J., Chu, F.L., Ma, N.: Advanced Theory of Constraint and Motion Analysis for Robot Mechanisms, 1st edn. Academic Press, Florida (2013)
Acknowledgments
This work was supported in part by the Basic Research Project Group of China under Grant 514010305-301-3, in part by the National Natural Science Foundation of China under Grant 51575291, in part by the National Major Science and Technology Project of China under Grant 2015ZX04002101, in part by the State Key Laboratory of Tribology, Tsinghua University, and part by the 221 Program of Tsinghua University.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sun, HL., Zhao, DJ., Zhao, JS. (2023). Screw Dynamics of the Upper Limb of a Humanoid Robot. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14274. Springer, Singapore. https://doi.org/10.1007/978-981-99-6501-4_48
Download citation
DOI: https://doi.org/10.1007/978-981-99-6501-4_48
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-6500-7
Online ISBN: 978-981-99-6501-4
eBook Packages: Computer ScienceComputer Science (R0)