A Hybrid MCIWO-NN Forward Kinematics Estimator for the Stewart Platform
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2022
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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. � 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Forward kinematics; Modified chaotic invasive weed optimization; Neural networks; Stewart platform
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