Spider robot walking gait optimization using Jaya multi-objective optimization algorithm

Abstract

The legs must move in a pattern to ensure that a four-legged robot walks organically and uses less energy. This is still a challenging issue today since four-legged creatures with incredibly complicated structures and precise motions are beyond the reach of current technology. This paper proposes a gait generation model for a spider robot that examines the guarantee between stability and speed. First, the robot spider’s movement rules are initiatively determined via four gait parameters—vertical step length, horizontal step length, leg lift, and knee bend. Meanwhile, the 3rd-order interpolation function determines the trajectory of the hips and feet at each leg. By applying analytical methods to solve the inverse kinematics issue, the orbits of the hips and feet at the four legs of the spider robot will be used to deduce twelve joint angle orbits at those locations. Then, a multi-objective function is proposed regarding both speed and stability based on the gait characteristics (gait parameters, CoP/ZMP trajectory) of the spider robot as to train the gait generation model by addressing the forward kinematics issue analytically. Finally, the multi-object MO-Jaya optimization technique is used to find four optimal gait parameters so that the spider robot performs a stable walking gait at the fastest speed. This proposal is implemented for the experiment B3-SBOT spider robot, simulation/experiment outcomes show that B3-SBOT moves at its fastest feasible speed while walking stably.