Natural Residual Reinforcement Learning for Bicycle Robot Control

被引：4

作者：

Zhu, Xianjin ^{[1
]}

Zheng, Xudong ^{[3
]}

Zhang, Qiyuan ^{[1
]}

Chen, Zhang ^{[2
]}

Liu, Yu ^{[1
]}

Liang, Bin ^{[2
]}

机构：

[1] Harbin Inst Technol, Dept Mech & Elect Engn, 92 Xidazhi St, Harbin, Heilongjiang, Peoples R China

[2] Tsinghua Univ, Dept Automat, 30 Shuangqing Rd, Beijing, Peoples R China

[3] Tsinghua Univ, Tsinghua Shenzhen Int Grad Sch, 2279 Lishui Rd, Shenzhen, Peoples R China

来源：

2021 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (IEEE ICMA 2021) | 2021年

基金：

中国国家自然科学基金;

关键词：

NRRL algorithm; bicycle robot; balance control; path tracking;

D O I：

10.1109/ICMA52036.2021.9512587

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This work focuses on motion control of the bicycle robot by using the proposed NRRL algorithm. Unlike the traditional RL algorithm, decomposing the main tasks into subtasks manually and introducing qualitative prior knowledge to the agent have been applied in the NRRL algorithm. Simulation results show that better performance and better sample efficiency of the proposed NRRL algorithm have been achieved in terms of balance control and path tracking of bicycle robot. It's believed that the NRRL algorithm is available on the real physical bicycle robot, and the deployment of the algorithm will be realized soon, as the real physical bicycle robot has been constructed currently.

引用

页码：1201 / 1206

页数：6

共 50 条

[21] Hierarchical reinforcement learning with adaptive scheduling for robot control
Huang, Zhigang
Liu, Quan
Zhu, Fei
[J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2023, 126
[22] Falling avoidance control of acrobat robot by reinforcement learning
Kochiya, T.
Yamakita, M.
[J]. PROCEEDINGS OF SICE ANNUAL CONFERENCE, VOLS 1-8, 2007, : 319 - 323
[23] Analysis of Mobile Robot Control by Reinforcement Learning Algorithm
Bernat, Jakub
Czopek, Pawel
Bartosik, Szymon
[J]. ELECTRONICS, 2022, 11 (11)
[24] A Fuzzy Reinforcement Learning Approach for Continuum Robot Control
Goharimanesh, M.
Mehrkish, A.
Janabi-Sharifi, F.
[J]. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2020, 100 (3-4) : 809 - 826
[25] Reinforcement Learning Control of Robot Manipulators in Uncertain Environments
Shah, Hitesh
Gopal, M.
[J]. 2009 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY, VOLS 1-3, 2009, : 120 - 125
[26] A reinforcement learning approach for robot control in an unknown environment
Xiao, NF
Nahavandi, S
[J]. IEEE ICIT' 02: 2002 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY, VOLS I AND II, PROCEEDINGS, 2002, : 1096 - 1099
[27] Model-Based Reinforcement Learning For Robot Control
Li, Xiang
Shang, Weiwei
Cong, Shuang
[J]. 2020 5TH INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS AND MECHATRONICS (ICARM 2020), 2020, : 300 - 305
[28] Reinforcement learning and robust control for robot compliance tasks
Kuan, CP
Young, KY
[J]. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 1998, 23 (2-4) : 165 - 182
[29] Reinforcement learning for human-robot shared control
Li, Yanan
Tee, Keng Peng
Yan, Rui
Ge, Shuzhi Sam
[J]. ASSEMBLY AUTOMATION, 2020, 40 (01) : 105 - 117
[30] Path Generation with Reinforcement Learning for Surgical Robot Control
Chen, Junhong
Wang, Zeyu
Zhu, Ruiqi
Zhang, Ruiyang
Bai, Weibang
Lo, Benny
[J]. 2022 IEEE-EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH INFORMATICS (BHI) JOINTLY ORGANISED WITH THE IEEE-EMBS INTERNATIONAL CONFERENCE ON WEARABLE AND IMPLANTABLE BODY SENSOR NETWORKS (BSN'22), 2022,

← 1 2 3 4 5 →