Dynamic Walking and Stepping over Large Obstacles of Biped Robots: A Poincaré Map Approach

Abstract

This paper considers dynamic stepping of biped robots when walking through a big obstacle, which is a great problem for these kinds of robots, using nonlinear model predictive control technique. No need for trajectory planning is one of the key advantages of this method. Hence, the gait length is not predefined and the controller determines it on the basis of the physical restraints and dynamic constancy conditions for approaching the obstacle and stepping over it. The stability and good performance for stepping over large obstacles are guaranteed by the definition of appropriate linear and nonlinear constraints and cost functions. Furthermore, to solve the uncertainty problem corresponding to the biped dynamic model, neural networks are used to identify the model of robot. For stability analysis, the Poincar map with the fixed-point technique is utilized to guarantee the robot stability. Simulation outcomes indicate excellent efficiency of the suggested technique used to a five-link biped robot crossing over a 4015 cm obstacle in sagittal plane when preserving a safety clearance from it with no need to a predefined trajectory.