Multi-Objective Optimization Of Snake Robot In Serpentine Locomotion

This paper presents multi-objective optimization for a snake robot with serpentine locomotion. Genetic algorithm (GA) is used to achieve two objectives: minimizing the total travelling time and minimizing the total energy consumption. The effect of initial values of winding angle and acceleration on energy consumption and average speed is depicted. The simulation results show a periodic pattern of the joint torques when the robot maintains a serpenoid curve during travel. Moreover, a Pareto-optimal front was generated for optimal solutions of both of the objectives, while the weighted sum method was used for selecting the best solution. Finally, the simulation results were verified experimentally on an eight-link snake robot considering the limitations of the servomotors used in the experiment. The experimental results with the winding angle of 30 degrees was found as the optimum winding angle that can achieve both objectives of minimizing the energy consumption and the travelling time.