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Multiobjective optimized bipedal locomotion
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DOI：10.1007/s13042-017-0660-1.png)
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Abstract
En 中文
To develop the general analytical model for the optimization of trade-off Stability and Energy functions for biped humanoid robot is very tedious work. This paper presents a novel analytical method to develop the multiobjective function includes energy and stability functions. The challenge was to develop analytical model for stability and energy for the single support phase (SSP), double support phase (DSP) and the transition to SSP-DSP and vice versa. 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 (the trajectories which generated by the mathematical equations of ZMP). 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 Multi-Objective 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(HOAP, Honda robots).
Keywords:
Zero moment point
Center of mass
Multi-objective optimization
Bipedal locomotion
Pareto-optimal front
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