Adaptive legged manipulation: Versatile disturbance predictive control for quadruped robots with robotic arms

被引：4

作者：

Yao, Qingfeng ^{[1
,2
,3
]}

Wang, Cong ^{[1
,2
,3
]}

Wang, Jilong ^{[4
]}

Meng, Linghan ^{[1
,2
,3
]}

Yang, Shuyu ^{[4
]}

Zhang, Qifeng ^{[1
,2
,5
]}

Wang, Donglin ^{[4
]}

机构：

[1] Chinese Acad Sci, Shenyang Inst Automat, State Key Lab Robot, Shenyang 110016, Peoples R China

[2] Inst Robot & Intelligent Mfg, Shenyang 110169, Peoples R China

[3] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

[4] Westlake Univ, Sch Engn, Hangzhou 310024, Peoples R China

[5] 114 Nanta St, Shenyang, Peoples R China

来源：

ROBOTICS AND AUTONOMOUS SYSTEMS | 2023年 / 167卷

关键词：

Reinforcement learning; Quadruped robot; Forward model; LOCOMOTION; TERRAIN;

D O I：

10.1016/j.robot.2023.104468

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Equipping a legged robot with a manipulator enables versatile mobile manipulation, significantly improving its performance in various tasks. However, developing a unified framework for diverse robotic arms and legged robots presents a challenge. This study proposes a disturbance predictive control framework where a high-level estimator cooperates with a disturbance-based low-level controller. Further, a transportable latent dynamic adapter is introduced to enable the model to migrate rapidly to different robotic arms. Our method can adapt well to other manipulators with a few samples. Further, the effectiveness of our method was demonstrated via simulation and real experiments. & COPY; 2023 Elsevier B.V. All rights reserved.

引用

页数：9

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