Optimum Hip Trajectory Generation of a Biped Robot during Single Support Phase Using Genetic Algorithm

Stability of Biped walking has been an area of interest for researchers since decades. In this work an optimum hip trajectory is generated, taking its swinging foot trajectory that is a B-Spline path and physical parameters of the robot as input parameters. The objective is to minimize the deviation of zero moment point (ZMP) from the geometrical centre of supporting foot area. Genetic algorithm (GA) has emerged as a significant tool for ill faced engineering problems and can be utilized when the redundancy in solutions is exhibited. The process involves here real coded genetic algorithm (RCGA), which uses progressive search technique to find optimum hip location, for ZMP to be within certain tolerance around the most stable point. The results are simulated with a biped having 10 degrees of freedom (DOF) comprising of kinematic chain of 11 links. The variation of various joint angles can be used as reference for dynamic control of any actual robot during single support phase which is the most critical of state biped walking. The output is a more anthropomorphic and stable robot with inherent flexibility offered by a B-Spline trajectory for its modification.