Abstract
Legged robots are constantly evolving, and energy efficiency is a major driving factor in their design. However, combining mechanism efficiency and trajectory planning can be challenging. This work proposes a computational optimization framework for optimizing leg design during basic walking while maximizing energy efficiency. We generalize the robotic limb design as a four-bar linkage-based design pool and optimize the leg using an evolutionary algorithm. The leg configuration and design parameters are optimized based on user-defined objective functions. Our framework was validated by comparing it to measured data on our prototype quadruped robot for forward trotting. The Bennett robotic leg was advantageous for omni-directional locomotion with enhanced energy efficiency.
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@article{Gu2023ComputationalDesign,
title = {Computational Design Towards Energy Efficient Optimization in Overconstrained Robotic Limbs},
author = {Yuping Gu and Ziqian Wang and Shihao Feng and Haoran Sun and Haibo Lu and Jia Pan and Fang Wan and Chaoyang Song},
doi = {10.1093/jcde/qwad083},
year = {2023},
date = {2023-08-22},
urldate = {2023-08-22},
journal = {Journal of Computational Design and Engineering},
volume = {10},
number = {5},
issue = {October},
pages = {1941–1956},
abstract = {Legged robots are constantly evolving, and energy efficiency is a major driving factor in their design. However, combining mechanism efficiency and trajectory planning can be challenging. This work proposes a computational optimization framework for optimizing leg design during basic walking while maximizing energy efficiency. We generalize the robotic limb design as a four-bar linkage-based design pool and optimize the leg using an evolutionary algorithm. The leg configuration and design parameters are optimized based on user-defined objective functions. Our framework was validated by comparing it to measured data on our prototype quadruped robot for forward trotting. The Bennett robotic leg was advantageous for omni-directional locomotion with enhanced energy efficiency.},
keywords = {Corresponding Author, Editor's Choice, J. Comput. Des. Eng. (JCDE), JCR Q1},
pubstate = {published},
tppubtype = {article}
}
