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Multiobjective optimized bipedal locomotion

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Abstract

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).

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Notes

  1. To understand the difference between the energy consumed, try walking with bent knees for about 5 m. Then, walk back to the starting point normally (knees not bent). The difference between the energy consumed can be clearly understood.

  2. The x-component of ZMP trajectory does not account much for ensuring the stability of the bipedal robots. This is because, the x-component of ZMP gives information only about the distance travelled by the bipedal robot and depicts nothing about its stability.

  3. obtain the motor current readings of NaO robot, the joint current sensor keys were selected in Choregraphe simulation software. When the robot walks, the current readings of the corresponding joints are stored in a *.csv file.

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Authors and Affiliations

  1. Indian Institute of Information Technology, Allahabad, India

    Manish Raj, Vijay Bhaskar Semwal & G C Nandi

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  1. Manish Raj
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  2. Vijay Bhaskar Semwal
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  3. G C Nandi
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Correspondence to Manish Raj.

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Raj, M., Semwal, V.B. & Nandi, G.C. Multiobjective optimized bipedal locomotion. Int. J. Mach. Learn. & Cyber. 10, 1997–2013 (2019). https://doi.org/10.1007/s13042-017-0660-1

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  • DOI: https://doi.org/10.1007/s13042-017-0660-1

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