Design of Optimized Multiobjective Function for Bipedal Locomotion Based on Energy and Stability

Abstract

This paper presents a novel analytical method to develop the multiobjective function including energy and stability functions. The energy function has been developed by unique approach of orbital energy concept and the stability function obtained by modifying the pre-existing zero moment point (ZMP) trajectory. These functions are optimized using real coded genetic algorithm to produce an optimum set of walk parameters. The analytical results show that, when the energy function is optimized, the stability of the robot decreases. Similarly, if the stability function is optimized, the energy consumed by the robot increases. Thus, there is a clear trade-off between the stability and energy functions. Thus, we propose the multiobjective evolutionary algorithm to yield the optimum value of the walk parameters. The results are verified by Nao robot. This approach increases the energy efficiency of Nao robot by 67.05%, and stability increases by 75%. Furthermore, this method can be utilized on all ZMP classed bipeds.

Keywords

• zero moment point
• center of mass
• multiobjective optimization
• bipedal locomotion
• pareto-optimal front