A Modified Artificial Potential Field Method Based on Subgoal Points for Mobile Robot

Jixue Mo; Changqing Gao; Fei Liu; Qingkai Yang; Hao Fang

doi:10.1007/978-981-99-6483-3_26

A Modified Artificial Potential Field Method Based on Subgoal Points for Mobile Robot

Jixue Mo, Changqing Gao, Fei Liu, Qingkai Yang, Hao Fang^*

^*此作品的通讯作者

自动化学院

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

In this paper, a modified artificial potential field (MAPF) method was proposed for general mobile robot navigation system. This MAPF method can effectively solve the unreachable goal problem and the local minima problem of traditional APF method. The first key idea of MAPF method is to modify the repulsive force function and thus optimize the direction of total repulsive force; the second key idea is to generate a serials of subgoal points around obstacles with specific method, so as to help the robot escape from or keep away from local minima area. By comparing with other similar algorithms in simulation environment, the MAPF algorithm can generate shorter paths efficiently. More importantly, it also can generate effective paths in multi-obstacle environment where other algorithms cannot. Finally the simulation results verified the reasonability and practicability of the proposed MAPF method.

源语言	英语
主期刊名	Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings
编辑	Huayong Yang, Jun Zou, Geng Yang, Xiaoping Ouyang, Honghai Liu, Zhiyong Wang, Zhouping Yin, Lianqing Liu
出版商	Springer Science and Business Media Deutschland GmbH
页	296-307
页数	12
ISBN（印刷版）	9789819964826
DOI	https://doi.org/10.1007/978-981-99-6483-3_26
出版状态	已出版 - 2023
活动	16th International Conference on Intelligent Robotics and Applications, ICIRA 2023 - Hangzhou, 中国期限: 5 7月 2023 → 7 7月 2023

出版系列

姓名	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	14267 LNAI
ISSN（印刷版）	0302-9743
ISSN（电子版）	1611-3349

会议

会议	16th International Conference on Intelligent Robotics and Applications, ICIRA 2023
国家/地区	中国
市	Hangzhou
时期	5/07/23 → 7/07/23

访问文件

10.1007/978-981-99-6483-3_26

其它文件与链接

链接到 Scopus 的出版物

引用此

Mo, J., Gao, C., Liu, F., Yang, Q., & Fang, H. (2023). A Modified Artificial Potential Field Method Based on Subgoal Points for Mobile Robot. 在 H. Yang, J. Zou, G. Yang, X. Ouyang, H. Liu, Z. Wang, Z. Yin, & L. Liu (编辑), Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings (页码 296-307). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 14267 LNAI). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-99-6483-3_26

Mo, Jixue ; Gao, Changqing ; Liu, Fei 等. / A Modified Artificial Potential Field Method Based on Subgoal Points for Mobile Robot. Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings. 编辑 / Huayong Yang ; Jun Zou ; Geng Yang ; Xiaoping Ouyang ; Honghai Liu ; Zhiyong Wang ; Zhouping Yin ; Lianqing Liu. Springer Science and Business Media Deutschland GmbH, 2023. 页码 296-307 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{58bd3222a3af4cafa47cb3e76f93ffd6,

title = "A Modified Artificial Potential Field Method Based on Subgoal Points for Mobile Robot",

abstract = "In this paper, a modified artificial potential field (MAPF) method was proposed for general mobile robot navigation system. This MAPF method can effectively solve the unreachable goal problem and the local minima problem of traditional APF method. The first key idea of MAPF method is to modify the repulsive force function and thus optimize the direction of total repulsive force; the second key idea is to generate a serials of subgoal points around obstacles with specific method, so as to help the robot escape from or keep away from local minima area. By comparing with other similar algorithms in simulation environment, the MAPF algorithm can generate shorter paths efficiently. More importantly, it also can generate effective paths in multi-obstacle environment where other algorithms cannot. Finally the simulation results verified the reasonability and practicability of the proposed MAPF method.",

keywords = "Artificial potential field, Mobile robot, Path planning, Subgoal points",

author = "Jixue Mo and Changqing Gao and Fei Liu and Qingkai Yang and Hao Fang",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023 ; Conference date: 05-07-2023 Through 07-07-2023",

year = "2023",

doi = "10.1007/978-981-99-6483-3_26",

language = "English",

isbn = "9789819964826",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "296--307",

editor = "Huayong Yang and Jun Zou and Geng Yang and Xiaoping Ouyang and Honghai Liu and Zhiyong Wang and Zhouping Yin and Lianqing Liu",

booktitle = "Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings",

address = "Germany",

}

Mo, J, Gao, C, Liu, F, Yang, Q & Fang, H 2023, A Modified Artificial Potential Field Method Based on Subgoal Points for Mobile Robot. 在 H Yang, J Zou, G Yang, X Ouyang, H Liu, Z Wang, Z Yin & L Liu (编辑), Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 14267 LNAI, Springer Science and Business Media Deutschland GmbH, 页码 296-307, 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023, Hangzhou, 中国, 5/07/23. https://doi.org/10.1007/978-981-99-6483-3_26

A Modified Artificial Potential Field Method Based on Subgoal Points for Mobile Robot. / Mo, Jixue; Gao, Changqing; Liu, Fei 等.
Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings. 编辑 / Huayong Yang; Jun Zou; Geng Yang; Xiaoping Ouyang; Honghai Liu; Zhiyong Wang; Zhouping Yin; Lianqing Liu. Springer Science and Business Media Deutschland GmbH, 2023. 页码 296-307 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 14267 LNAI).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - A Modified Artificial Potential Field Method Based on Subgoal Points for Mobile Robot

AU - Mo, Jixue

AU - Gao, Changqing

AU - Liu, Fei

AU - Yang, Qingkai

AU - Fang, Hao

PY - 2023

Y1 - 2023

N2 - In this paper, a modified artificial potential field (MAPF) method was proposed for general mobile robot navigation system. This MAPF method can effectively solve the unreachable goal problem and the local minima problem of traditional APF method. The first key idea of MAPF method is to modify the repulsive force function and thus optimize the direction of total repulsive force; the second key idea is to generate a serials of subgoal points around obstacles with specific method, so as to help the robot escape from or keep away from local minima area. By comparing with other similar algorithms in simulation environment, the MAPF algorithm can generate shorter paths efficiently. More importantly, it also can generate effective paths in multi-obstacle environment where other algorithms cannot. Finally the simulation results verified the reasonability and practicability of the proposed MAPF method.

AB - In this paper, a modified artificial potential field (MAPF) method was proposed for general mobile robot navigation system. This MAPF method can effectively solve the unreachable goal problem and the local minima problem of traditional APF method. The first key idea of MAPF method is to modify the repulsive force function and thus optimize the direction of total repulsive force; the second key idea is to generate a serials of subgoal points around obstacles with specific method, so as to help the robot escape from or keep away from local minima area. By comparing with other similar algorithms in simulation environment, the MAPF algorithm can generate shorter paths efficiently. More importantly, it also can generate effective paths in multi-obstacle environment where other algorithms cannot. Finally the simulation results verified the reasonability and practicability of the proposed MAPF method.

KW - Artificial potential field

KW - Mobile robot

KW - Path planning

KW - Subgoal points

UR - http://www.scopus.com/inward/record.url?scp=85175995482&partnerID=8YFLogxK

U2 - 10.1007/978-981-99-6483-3_26

DO - 10.1007/978-981-99-6483-3_26

M3 - Conference contribution

AN - SCOPUS:85175995482

SN - 9789819964826

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 296

EP - 307

BT - Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings

A2 - Yang, Huayong

A2 - Zou, Jun

A2 - Yang, Geng

A2 - Ouyang, Xiaoping

A2 - Liu, Honghai

A2 - Wang, Zhiyong

A2 - Yin, Zhouping

A2 - Liu, Lianqing

PB - Springer Science and Business Media Deutschland GmbH

T2 - 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023

Y2 - 5 July 2023 through 7 July 2023

ER -

Mo J, Gao C, Liu F, Yang Q , Fang H. A Modified Artificial Potential Field Method Based on Subgoal Points for Mobile Robot. 在 Yang H, Zou J, Yang G, Ouyang X, Liu H, Wang Z, Yin Z, Liu L, 编辑, Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings. Springer Science and Business Media Deutschland GmbH. 2023. 页码 296-307. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-981-99-6483-3_26

A Modified Artificial Potential Field Method Based on Subgoal Points for Mobile Robot

摘要

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