Structural optimization method of transport manipulator for the BEST tokamak

This study proposes a novel structural optimization framework integrating kinematic and static performance for the transport manipulator of China's Burning Plasma Experimental Superconducting Tokamak (BEST), outperforming traditional single-objective approaches. A 1T3R (one translational, three rotational degrees of freedom) configuration is selected based on task requirements and geometric constraints. Link lengths are optimized using Sequential Quadratic Programming (SQP), achieving a 3.43% workspace increase compared to the Lagrange multiplier method. Cross-sectional parameters are optimized using Non-dominated Sorting Genetic Algorithm II (NSGA-II), with hollow rectangular sections reducing deformation and weight, improving the payload-to-weight ratio. This scalable framework enhances kinematic performance and payload-to-weight ratio, offering a robust solution for fusion reactor maintenance.