Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/96462
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Aeronautical and Aviation Engineering | - |
dc.creator | Li, X | en_US |
dc.creator | Huang, H | en_US |
dc.creator | Savkin, AV | en_US |
dc.creator | Zhang, J | en_US |
dc.date.accessioned | 2022-12-07T02:55:02Z | - |
dc.date.available | 2022-12-07T02:55:02Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/96462 | - |
dc.language.iso | en | en_US |
dc.publisher | MDPI AG | en_US |
dc.rights | © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | en_US |
dc.rights | The following publication Li, X., Huang, H., Savkin, A. V., & Zhang, J. (2022). Robotic herding of farm animals using a network of barking aerial drones. Drones, 6(2), 29 is available at https://doi.org/10.3390/drones6020029. | en_US |
dc.subject | Autonomous drones | en_US |
dc.subject | Motion control | en_US |
dc.subject | Precision farming | en_US |
dc.subject | Robotic herding | en_US |
dc.subject | Shepherding | en_US |
dc.subject | Swarm guidance | en_US |
dc.subject | Unmanned aerial vehicles (UAVs) | en_US |
dc.title | Robotic herding of farm animals using a network of barking aerial drones | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 6 | en_US |
dc.identifier.issue | 2 | en_US |
dc.identifier.doi | 10.3390/drones6020029 | en_US |
dcterms.abstract | This paper proposes a novel robotic animal herding system based on a network of autonomous barking drones. The objective of such a system is to replace traditional herding methods (e.g., dogs) so that a large number (e.g., thousands) of farm animals such as sheep can be quickly collected from a sparse status and then driven to a designated location (e.g., a sheepfold). In this paper, we particularly focus on the motion control of the barking drones. To this end, a computationally efficient sliding mode based control algorithm is developed, which navigates the drones to track the moving boundary of the animals’ footprint and enables the drones to avoid collisions with others. Extensive computer simulations, where the dynamics of the animals follow Reynolds’ rules, show the effectiveness of the proposed approach. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Drones, Feb. 2022, v. 6, no. 2, 29 | en_US |
dcterms.isPartOf | Drones | en_US |
dcterms.issued | 2022-02 | - |
dc.identifier.scopus | 2-s2.0-85123793583 | - |
dc.identifier.eissn | 2504-446X | en_US |
dc.identifier.artn | 29 | en_US |
dc.description.validate | 202212 bckw | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | - |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | CC | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
drones-06-00029.pdf | 1.87 MB | Adobe PDF | View/Open |
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