Dynamic Modeling and Parameter Identification of Hybrid Bipedal Robotic Legs

doi:10.3901/JME.260237

Abstract

Abstract: To enhance the speed and accuracy of dynamic parameter identification for bipedal robotic legs based on hybrid mechanisms, an integrated parameter identification method is proposed, which combines an improved excitation trajectory optimization technique with the Ivy algorithm (IVYA). Initially, the parallel joints in the robotic leg are simplified into equivalent serial joints, and a linearized single-leg dynamic model is established using the Newton–Euler method. Compared with traditional methods, this research proposes the first integration of joint space utilization constraints into excitation trajectory optimization, addressing the optimization efficiency issues arising from the compact joint space of hybrid serial-parallel mechanisms, and successfully designs excitation trajectories. A dynamic parameter identification experiment is conducted on a 5-DOF robotic leg with a hybrid mechanism. Joint angle and current data are collected via sensors, and after filtering, the IVYA algorithm is employed for parameter estimation. The prediction results obtained using IVYA are compared with those derived from the least squares method. Experimental results indicate that the excitation trajectory optimized under joint space utilization constraints improves the optimization speed by 17% and exhibits negligible condition number error. Moreover, compared with the least squares method, the RMS errors between the actual torques and the predicted torques for the five joints obtained using the IVYA-based dynamic model are lower, with the average RMS error reduced by 13.42% and the maximum RMS error decreased by 2.68 N•m. These findings confirm the effectiveness of the proposed integrated identification method, providing a theoretical basis for precise model-based control of hybrid robots.

Key words: parameter identification, trajectory optimization, ivy algorithm, hybrid mechanism, bipedal robot

CLC Number:

TP242

SUN Peng, GE Menghu, RUI Chao, CAO Likang, CHEN Bo, WANG Jianbin, LI Yanbiao. Dynamic Modeling and Parameter Identification of Hybrid Bipedal Robotic Legs[J]. Journal of Mechanical Engineering, 2026, 62(5): 192-203.

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URL: http://www.cjmenet.com.cn/EN/10.3901/JME.260237

http://www.cjmenet.com.cn/EN/Y2026/V62/I5/192

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