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CLC number: TP242.6;TP18
On-line Access: 2025-10-13
Received: 2024-12-16
Revision Accepted: 2025-05-12
Crosschecked: 2025-10-13
Cited: 0
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Efficient learning of robust multigait quadruped locomotion for minimizing the cost of transport
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Zhicheng WANG, Xin ZHAO, Meng Yee (Michael) CHUAH, Zhibin LI, Jun WU, Qiuguo ZHU. Efficient learning of robust multigait quadruped locomotion for minimizing the cost of transport[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(9): 1679-1691.
@article{title="Efficient learning of robust multigait quadruped locomotion for minimizing the cost of transport",
author="Zhicheng WANG, Xin ZHAO, Meng Yee (Michael) CHUAH, Zhibin LI, Jun WU, Qiuguo ZHU",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="26",
number="9",
pages="1679-1691",
year="2025",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2401070"
}
%0 Journal Article
%T Efficient learning of robust multigait quadruped locomotion for minimizing the cost of transport
%A Zhicheng WANG
%A Xin ZHAO
%A Meng Yee (Michael) CHUAH
%A Zhibin LI
%A Jun WU
%A Qiuguo ZHU
%J Frontiers of Information Technology & Electronic Engineering
%V 26
%N 9
%P 1679-1691
%@ 2095-9184
%D 2025
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2401070
TY - JOUR
T1 - Efficient learning of robust multigait quadruped locomotion for minimizing the cost of transport
A1 - Zhicheng WANG
A1 - Xin ZHAO
A1 - Meng Yee (Michael) CHUAH
A1 - Zhibin LI
A1 - Jun WU
A1 - Qiuguo ZHU
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 26
IS - 9
SP - 1679
EP - 1691
%@ 2095-9184
Y1 - 2025
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2401070
Abstract: Quadruped robots are able to exhibit a range of gaits, each with its own traversability and energy efficiency characteristics. By actively coordinating between gaits in different scenarios, energy-efficient and adaptive locomotion can be achieved. This study investigates the performances of learned energy-efficient policies for quadrupedal gaits under different commands. We propose a training–synthesizing framework that integrates learned gait-conditioned locomotion policies into an efficient multiskill locomotion policy. The resulting control policy achieves low-cost smooth switching and controllable gaits. Our results of the learned multiskill policy demonstrate seamless gait transitions while maintaining energy optimality across all commands.
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