Optimization of fracture reduction robot controller based on improved sparrow algorithm

The accuracy of a fracture reduction robot (FRR) is critical for ensuring the safety of surgery. Improving the repositioning accuracy of a FRR, reducing the error, and realizing a safer and more stable folding motion is critical. To achieve this, a sparrow search algorithm (SSA) based on the Levy flight operator was proposed in this study for self-tuning the robot controller parameters. An inverse kinematic analysis of the FRR was also performed. The robot dynamics model was established using Simulink, and the inverse dynamics controller for the fracture reduction mechanism was designed using the computed torque control method. Both simulation and physical experiments were also performed. The actual motion trajectory of the actuator drive rod and its error with a desired trajectory was obtained through simulation. An optimized Levy-sparrow search algorithm (Levy-SSA) crack reduction robot controller demonstrated an overall reduction of two orders of magnitude in the reduction error, with an average error reduction of 98.74% compared with the traditional unoptimized controller. The Levy-SSA increased the convergence of the crack reduction robot control system to the optimal solution, improved the accuracy of the motion trajectory, and exhibited important implications for robot controller optimization.