A New Solving Method Based on Simulated Annealing Particle Swarm Optimization for the Forward Kinematic Problem of the Stewart–Gough Platform

The forward kinematics of the Stewart–Gough platform is vital for high-precision positioning and sensing in six degrees freedom. In this paper, solving converted to searching best posture corresponding input outrigger length vectors by inverse kinematic calculation. simulated annealing (SA) process embedded into particle swarm optimization (PSO) improve convergence speed overcome local convergence. proposed SA–PSO algorithm not only accelerates but also improves reliability success rate. After parameters, rate random vector steadily above 99.9% while results PSO between 93% 100%. workspace simulation, average iteration number reduced from 146.6 122.7, meanwhile, 99.992%, much higher than 93.805% PSO. Compared with traditional Newton–Raphson method, method has a less time consuming. Finally, physical experiment conducted on six-degree-of-freedom platform, revealing that given reliable accurate.