Generation of optimal trajectories for ascending and descending a stair of a humanoid based on uDEAS

In this paper, a humanoid is simulated and implemented to walk up and down a staircase using the blending polynomial and univariate dynamic encoding algorithm for searches (uDEAS). The motivation of this paper is to divide efficient walking step for a commercial humanoid when ascending and descending a stair. Therefore ascending and descending a staircase are each scheduled by four steps. Each step mimics natural gait of human being and is easy to analyze and implement. Optimal trajectories of ten motors in a lower extremity of a humanoid are rigorously computed to simultaneously satisfy stability condition, walking constraints, and energy efficiency requirements. As an optimization method, uDEAS is applied to search optimal trajectory parameters in blending polynomials. The feasibility of this approach will be validated by simulation with a commercial humanoid robot.