Forward Kinematics Algorithm for 6-DOF Parallel Platforms Combining Neural Networks and Iterative Methods

The field of automated assembly faces the challenge of precise component alignment. This study focuses on the assembly scenario where one component moves along the vertical axis for assembly, while the other component is positioned on a six-degree-of-freedom (6-DOF) parallel platform for adaptive pose adjustment. This paper proposes a new algorithm that combines neural networks with iterative computation to solve the forward kinematics of the parallel platform, achieving precise coordination with the Z-axis. Experiments have shown that the algorithm effectively plans the platform’s motion trajectory, with position accuracy reaching below 0.005 mm and pose error controlled within 0.003 radians. The new algorithm excels in improving assembly precision and is suitable for pre-planned motion trajectory scenarios, providing effective technical support for the field of automated assembly.