A Geometric Approach for Real-Time Forward Kinematics of the General Stewart Platform

作者：Fangfang Yang, Xiaojun Tan, Zhe Wang, LU Zhen-feng, Tao He · 发表于：Sensors · 年份：2022 · DOI：10.3390/s22134829 · 被引用次数：15 · 研究领域：Robotic Mechanisms and Dynamics、Soft Robotics and Applications、Iterative Learning Control Systems

This paper presents a geometric approach for real-time forward kinematics of the general Stewart platform, which consists of two rigid bodies connected by six general serial manipulators. By describing the rigid-body motion as exponential of twist, and taking advantage of the product of exponentials formula, a step-by-step derivation of the proposed algorithm is presented. As the algorithm naturally solves all passive joint displacements, the correctness is then verified by comparing the forward-kinematic solutions from all chains. The convergence ability and robustness of the proposed algorithm are demonstrated with large amounts of numerical simulations. In all test cases, the proposed algorithm terminates within four iterations, converging with near-quadratic speed. Finally, the proposed algorithm is also implemented on a mainstream embedded motion controller. Compared with the incremental method, the proposed algorithm is more robust, with an average execution time of 0.48 ms, meeting the requirements of most applications, such as kinematic calibration, motion simulation, and real-time control.