A Novel Version of Sampling-based Motion Planner for Manipulation with Faster Initial Solution and Convergence

Guoqiang Zhao; Xiangzhou Wang; Shuhua Zheng; Qian Han

doi:10.1109/CCDC55256.2022.10033427

A Novel Version of Sampling-based Motion Planner for Manipulation with Faster Initial Solution and Convergence

Guoqiang Zhao^*, Xiangzhou Wang, Shuhua Zheng, Qian Han

^*此作品的通讯作者

Beijing Institute of Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

1 引用（Scopus）

摘要

This paper presents, Anytime Fast-BIT∗ (AFBIT∗), a sampling based, asymptotically optimal manipulation motion planner which quickly finds an initial feasible path and rapidly improves the path quality toward optimality. AFBIT∗ is guided by modified heuristics in task space for faster first solution. A local optimization method is adopted at the end of every round to optimize the current best path and generate the next vertex and edge for the global path while a new round begins to improve the quality of the remaining path. Simulation results suggest AFBIT∗ is more efficient and effective on manipulation problems than BIT∗ and Fast-BIT∗.

源语言	英语
主期刊名	Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022
出版商	Institute of Electrical and Electronics Engineers Inc.
页	357-363
页数	7
ISBN（电子版）	9781665478960
DOI	https://doi.org/10.1109/CCDC55256.2022.10033427
出版状态	已出版 - 2022
活动	34th Chinese Control and Decision Conference, CCDC 2022 - Hefei, 中国期限: 15 8月 2022 → 17 8月 2022

出版系列

姓名	Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022

会议

会议	34th Chinese Control and Decision Conference, CCDC 2022
国家/地区	中国
市	Hefei
时期	15/08/22 → 17/08/22

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10.1109/CCDC55256.2022.10033427

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链接到 Scopus 的出版物

引用此

Zhao, G., Wang, X., Zheng, S., & Han, Q. (2022). A Novel Version of Sampling-based Motion Planner for Manipulation with Faster Initial Solution and Convergence. 在 Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022 (页码 357-363). (Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCDC55256.2022.10033427

Zhao, Guoqiang ; Wang, Xiangzhou ; Zheng, Shuhua 等. / A Novel Version of Sampling-based Motion Planner for Manipulation with Faster Initial Solution and Convergence. Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022. Institute of Electrical and Electronics Engineers Inc., 2022. 页码 357-363 (Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022).

@inproceedings{d7eb1afb670b48b9b70c75b5de2ccc36,

title = "A Novel Version of Sampling-based Motion Planner for Manipulation with Faster Initial Solution and Convergence",

abstract = "This paper presents, Anytime Fast-BIT∗ (AFBIT∗), a sampling based, asymptotically optimal manipulation motion planner which quickly finds an initial feasible path and rapidly improves the path quality toward optimality. AFBIT∗ is guided by modified heuristics in task space for faster first solution. A local optimization method is adopted at the end of every round to optimize the current best path and generate the next vertex and edge for the global path while a new round begins to improve the quality of the remaining path. Simulation results suggest AFBIT∗ is more efficient and effective on manipulation problems than BIT∗ and Fast-BIT∗.",

keywords = "Industrial robots, Manipulation motion planning, Sampling-Based Algorithm",

author = "Guoqiang Zhao and Xiangzhou Wang and Shuhua Zheng and Qian Han",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 34th Chinese Control and Decision Conference, CCDC 2022 ; Conference date: 15-08-2022 Through 17-08-2022",

year = "2022",

doi = "10.1109/CCDC55256.2022.10033427",

language = "English",

series = "Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "357--363",

booktitle = "Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022",

address = "United States",

}

Zhao, G , Wang, X , Zheng, S & Han, Q 2022, A Novel Version of Sampling-based Motion Planner for Manipulation with Faster Initial Solution and Convergence. 在 Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022. Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022, Institute of Electrical and Electronics Engineers Inc., 页码 357-363, 34th Chinese Control and Decision Conference, CCDC 2022, Hefei, 中国, 15/08/22. https://doi.org/10.1109/CCDC55256.2022.10033427

A Novel Version of Sampling-based Motion Planner for Manipulation with Faster Initial Solution and Convergence. / Zhao, Guoqiang ; Wang, Xiangzhou ; Zheng, Shuhua 等.
Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022. Institute of Electrical and Electronics Engineers Inc., 2022. 页码 357-363 (Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022).

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 Novel Version of Sampling-based Motion Planner for Manipulation with Faster Initial Solution and Convergence

AU - Zhao, Guoqiang

AU - Wang, Xiangzhou

AU - Zheng, Shuhua

AU - Han, Qian

PY - 2022

Y1 - 2022

N2 - This paper presents, Anytime Fast-BIT∗ (AFBIT∗), a sampling based, asymptotically optimal manipulation motion planner which quickly finds an initial feasible path and rapidly improves the path quality toward optimality. AFBIT∗ is guided by modified heuristics in task space for faster first solution. A local optimization method is adopted at the end of every round to optimize the current best path and generate the next vertex and edge for the global path while a new round begins to improve the quality of the remaining path. Simulation results suggest AFBIT∗ is more efficient and effective on manipulation problems than BIT∗ and Fast-BIT∗.

AB - This paper presents, Anytime Fast-BIT∗ (AFBIT∗), a sampling based, asymptotically optimal manipulation motion planner which quickly finds an initial feasible path and rapidly improves the path quality toward optimality. AFBIT∗ is guided by modified heuristics in task space for faster first solution. A local optimization method is adopted at the end of every round to optimize the current best path and generate the next vertex and edge for the global path while a new round begins to improve the quality of the remaining path. Simulation results suggest AFBIT∗ is more efficient and effective on manipulation problems than BIT∗ and Fast-BIT∗.

KW - Industrial robots

KW - Manipulation motion planning

KW - Sampling-Based Algorithm

UR - http://www.scopus.com/inward/record.url?scp=85149530852&partnerID=8YFLogxK

U2 - 10.1109/CCDC55256.2022.10033427

DO - 10.1109/CCDC55256.2022.10033427

M3 - Conference contribution

AN - SCOPUS:85149530852

T3 - Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022

SP - 357

EP - 363

BT - Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 34th Chinese Control and Decision Conference, CCDC 2022

Y2 - 15 August 2022 through 17 August 2022

ER -

Zhao G , Wang X , Zheng S, Han Q. A Novel Version of Sampling-based Motion Planner for Manipulation with Faster Initial Solution and Convergence. 在 Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022. Institute of Electrical and Electronics Engineers Inc. 2022. 页码 357-363. (Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022). doi: 10.1109/CCDC55256.2022.10033427

A Novel Version of Sampling-based Motion Planner for Manipulation with Faster Initial Solution and Convergence

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