Multi-objective optimization design method for the dimensions and control parameters of curling hexapod robot based on application performance

The curling hexapod robot is different from previous curling robots, which can mimic the throwing actions of curlers. To ensure its performance, the size and control parameters of the robot need to be optimized. However, there is still a lack of parameter design optimization methods for hexapod curling robots based on application performance and considering the coupling effects of size and control parameters. To meet this demand, this paper combines Simscape Multibody simulation modeling and genetic algorithm to propose a multi-objective optimization method for the dimensions and control parameters of curling hexapod robot based on application performance. This method uses Simscape Multibody to establish a parametric model of the curling robot, and proposes an optimization search method using genetic algorithms based on constraints and objective functions. Finally, the dimensions and control parameters of the curling robot that meet the application performance requirements are solved through the optimization method.