A Herd Foraging-Based Adaptive Coverage Path Planning in Unbounded Environments

Jun Qi Zhang; Peng Zu; Meng Chu Zhou

doi:10.1109/SMC53654.2022.9945206

A Herd Foraging-Based Adaptive Coverage Path Planning in Unbounded Environments

Jun Qi Zhang, Peng Zu, Meng Chu Zhou

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

Coverage path planning is important in helping us perform such tasks as map construction and criminal capture. As an outstanding method, predator-prey coverage path planning employs a predator-prey mechanism to enable a robot to adaptively cover an arbitrary 2-D surface with dynamic obastacles. However, it is designed for bounded environments only and cannot work in unbounded environments. Inspired by the foraging behavior of herds in nature, this work proposes an adaptive coverage path planning algorithm suitable for unbounded environments, called herd foraging-based coverage path planning. It employs a virtual herd to control the overall coverage direction of a robot, allowing it to be applied in unbounded environments. The experimental results demonstrate its effectiveness in unbounded environments.

Original language	English (US)
Title of host publication	2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2062-2066
Number of pages	5
ISBN (Electronic)	9781665452588
DOIs	https://doi.org/10.1109/SMC53654.2022.9945206
State	Published - 2022
Event	2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022 - Prague, Czech Republic Duration: Oct 9 2022 → Oct 12 2022

Publication series

Name	Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume	2022-October
ISSN (Print)	1062-922X

Conference

Conference	2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022
Country/Territory	Czech Republic
City	Prague
Period	10/9/22 → 10/12/22

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering
Control and Systems Engineering
Human-Computer Interaction

Keywords

Coverage path planning (CPP)
artificial intelligence
herd foraging-based coverage path planning (HFCPP)
unbounded environments

Access to Document

10.1109/SMC53654.2022.9945206

Cite this

Zhang, J. Q., Zu, P., & Zhou, M. C. (2022). A Herd Foraging-Based Adaptive Coverage Path Planning in Unbounded Environments. In 2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022 - Proceedings (pp. 2062-2066). (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics; Vol. 2022-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC53654.2022.9945206

Zhang, Jun Qi ; Zu, Peng ; Zhou, Meng Chu. / A Herd Foraging-Based Adaptive Coverage Path Planning in Unbounded Environments. 2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 2062-2066 (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics).

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abstract = "Coverage path planning is important in helping us perform such tasks as map construction and criminal capture. As an outstanding method, predator-prey coverage path planning employs a predator-prey mechanism to enable a robot to adaptively cover an arbitrary 2-D surface with dynamic obastacles. However, it is designed for bounded environments only and cannot work in unbounded environments. Inspired by the foraging behavior of herds in nature, this work proposes an adaptive coverage path planning algorithm suitable for unbounded environments, called herd foraging-based coverage path planning. It employs a virtual herd to control the overall coverage direction of a robot, allowing it to be applied in unbounded environments. The experimental results demonstrate its effectiveness in unbounded environments.",

keywords = "Coverage path planning (CPP), artificial intelligence, herd foraging-based coverage path planning (HFCPP), unbounded environments",

author = "Zhang, {Jun Qi} and Peng Zu and Zhou, {Meng Chu}",

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language = "English (US)",

series = "Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics",

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Zhang, JQ, Zu, P & Zhou, MC 2022, A Herd Foraging-Based Adaptive Coverage Path Planning in Unbounded Environments. in 2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022 - Proceedings. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, vol. 2022-October, Institute of Electrical and Electronics Engineers Inc., pp. 2062-2066, 2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022, Prague, Czech Republic, 10/9/22. https://doi.org/10.1109/SMC53654.2022.9945206

A Herd Foraging-Based Adaptive Coverage Path Planning in Unbounded Environments. / Zhang, Jun Qi; Zu, Peng; Zhou, Meng Chu.
2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. p. 2062-2066 (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics; Vol. 2022-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Zu, Peng

AU - Zhou, Meng Chu

PY - 2022

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N2 - Coverage path planning is important in helping us perform such tasks as map construction and criminal capture. As an outstanding method, predator-prey coverage path planning employs a predator-prey mechanism to enable a robot to adaptively cover an arbitrary 2-D surface with dynamic obastacles. However, it is designed for bounded environments only and cannot work in unbounded environments. Inspired by the foraging behavior of herds in nature, this work proposes an adaptive coverage path planning algorithm suitable for unbounded environments, called herd foraging-based coverage path planning. It employs a virtual herd to control the overall coverage direction of a robot, allowing it to be applied in unbounded environments. The experimental results demonstrate its effectiveness in unbounded environments.

AB - Coverage path planning is important in helping us perform such tasks as map construction and criminal capture. As an outstanding method, predator-prey coverage path planning employs a predator-prey mechanism to enable a robot to adaptively cover an arbitrary 2-D surface with dynamic obastacles. However, it is designed for bounded environments only and cannot work in unbounded environments. Inspired by the foraging behavior of herds in nature, this work proposes an adaptive coverage path planning algorithm suitable for unbounded environments, called herd foraging-based coverage path planning. It employs a virtual herd to control the overall coverage direction of a robot, allowing it to be applied in unbounded environments. The experimental results demonstrate its effectiveness in unbounded environments.

KW - Coverage path planning (CPP)

KW - artificial intelligence

KW - herd foraging-based coverage path planning (HFCPP)

KW - unbounded environments

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Zhang JQ, Zu P, Zhou MC. A Herd Foraging-Based Adaptive Coverage Path Planning in Unbounded Environments. In 2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2022. p. 2062-2066. (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics). doi: 10.1109/SMC53654.2022.9945206

A Herd Foraging-Based Adaptive Coverage Path Planning in Unbounded Environments

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