Near-Optimal Trajectory Generation of a Two-Legged Robot with Soft Sole on Staircase using PSO and ABC

During biped locomotion the foot ground interaction plays an important role, as it takes the reaction force acting on the foot and allows stable walking of the biped robot. Generally, the foot is considered to be hard to solve the gait generation problem and dynamic balance aspects of the two-legged robot. However, a layer of rubber is placed on the sole of the robot to act as a shock absorber for all practical purposes. It is important to note that the soft sole gets deformed during walking of the robot and allows the limbs of the robot to bend that influences the dynamic balance of the walking machine. The aim of this study is to use two different non-traditional optimization algorithms, such as particle swarm optimization (PSO) and artificial bee colony (ABC) algorithms to obtain the optimal hip trajectory, damping coefficient and position of the lumped masses for a 7-DOF biped robot ascending the staircase. The dynamic balance of the gaits generated with soft sole is verified using the concept of zero moment point (ZMP). Further, the energy consumed in ascending the staircase with and without soft sole has been computed. The results of this study proved that, least energy is consumed with soft sole having correction for the deformation. Near-Optimal Trajectory Generation of a Two-Legged Robot with Soft Sole on Staircase using PSO and ABC