Study of follow-the-leader motion through multi-objective optimization of serpentine gait of a bio-inspired snake robot

Abstract

ABSTRACT This article presents multi-objective optimization for the efficient locomotion of the serpentine gait of a biologically inspired snake robot. The optimization problem is solved by using multi-objective genetic algorithm approach. The objective functions are the minimization of power consumption and the maximization of the forward propulsion velocity of the robot. The decision variables are the parameters of the serpentine gait, namely as amplitude, angular frequency and phase shift. The snake robot is modeled by using the Newton-Euler dynamic formulation related to locomotion robots. The wheel-ground contact is modeled by using the Coulomb’s law of dry friction. Optimization results are obtained and discussed for a number of coefficients of friction. The results depicted that for the pareto-optimal solutions, the lateral slide of the modules is negligibly small and the snake robot showed a follow-the-leader motion. These results justify the efficient utilization of energy in follow-the-leader approach. Finally, this study provides a useful basis for the selection of appropriate design parameters of snake robot under specified physical constraints and limitations.