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Bibliographic Details
Main Authors: Ibrayeva, Arman, Omarov, Batyrkhan
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2505.00923
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author Ibrayeva, Arman
Omarov, Batyrkhan
author_facet Ibrayeva, Arman
Omarov, Batyrkhan
contents This paper addresses several critical stages of designing a walking robot, including optimal structural synthesis, introducing a novel 'rational' mechanical structure aimed at enhancing efficiency and simplifying control system, while addressing practical limitations observed in existing designs. The study includes development of novel multicriteria synthesis methods for achieving optimal leg design, integrating analytical and numerical methods. In addition, a method based on Non-dominated Sorting Genetic Algorithm II is presented. Turning modes are investigated, and for the first time, the isotropy criterion, typically applied to parallel manipulators, is used for optimizing walking robot parameters to ensure optimal force and motion transfer in all directions. Several physical prototypes are developed to experimentally validate the functionality of different mechanisms of the robot, including adaptation to the surface irregularities and navigation using LiDAR.
format Preprint
id arxiv_https___arxiv_org_abs_2505_00923
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Optimal Design of a Walking Robot: Analytical, Numerical, and Machine Learning Methods for Multicriteria Synthesis
Ibrayeva, Arman
Omarov, Batyrkhan
Robotics
This paper addresses several critical stages of designing a walking robot, including optimal structural synthesis, introducing a novel 'rational' mechanical structure aimed at enhancing efficiency and simplifying control system, while addressing practical limitations observed in existing designs. The study includes development of novel multicriteria synthesis methods for achieving optimal leg design, integrating analytical and numerical methods. In addition, a method based on Non-dominated Sorting Genetic Algorithm II is presented. Turning modes are investigated, and for the first time, the isotropy criterion, typically applied to parallel manipulators, is used for optimizing walking robot parameters to ensure optimal force and motion transfer in all directions. Several physical prototypes are developed to experimentally validate the functionality of different mechanisms of the robot, including adaptation to the surface irregularities and navigation using LiDAR.
title Optimal Design of a Walking Robot: Analytical, Numerical, and Machine Learning Methods for Multicriteria Synthesis
topic Robotics
url https://arxiv.org/abs/2505.00923