Publication Type : Conference Paper
Publisher : Springer Nature Singapore
Source : Lecture Notes in Networks and Systems
Url : https://doi.org/10.1007/978-981-19-0707-4_35
Campus : Chennai
School : School of Engineering
Department : Mechanical Engineering
Year : 2022
Abstract : The Stewart platform (SP) is the most popular form of a manipulator of all the classes of parallel manipulators. It is a widely used robot in various applications in the last decades. The mechanism of the Stewart platform (SP) has a complex closed kinematics structure with six degree-of-freedoms constraint motion and has the capability to solve the mappings. Inverse kinematics (IK) of the Stewart platform (SP) is easy to solve analytically, whereas evaluating its direct kinematics analytically is complex. Therefore, in this work, authors have attempted to estimate the forward kinematics (FK) of the 6–6 type Stewart platform using a soft-computing-based hybrid methodology. A combination of neural networks (NN) and Modified Chaotic Invasive Weed Optimization (MCIWO) is proposed to solve the said problem.
Cite this Research Publication : Dev Kunwar Singh Chauhan, Pandu R. Vundavilli, A Hybrid MCIWO-NN Forward Kinematics Estimator for the Stewart Platform, Lecture Notes in Networks and Systems, Springer Nature Singapore, 2022, https://doi.org/10.1007/978-981-19-0707-4_35