Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/96462
PIRA download icon_1.1View/Download Full Text
Title: Robotic herding of farm animals using a network of barking aerial drones
Authors: Li, X
Huang, H 
Savkin, AV
Zhang, J
Issue Date: Feb-2022
Source: Drones, Feb. 2022, v. 6, no. 2, 29
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.
Keywords: Autonomous drones
Motion control
Precision farming
Robotic herding
Shepherding
Swarm guidance
Unmanned aerial vehicles (UAVs)
Publisher: MDPI AG
Journal: Drones 
EISSN: 2504-446X
DOI: 10.3390/drones6020029
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/).
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.
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
drones-06-00029.pdf1.87 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

75
Last Week
2
Last month
Citations as of Sep 22, 2024

Downloads

37
Citations as of Sep 22, 2024

SCOPUSTM   
Citations

28
Citations as of Sep 26, 2024

WEB OF SCIENCETM
Citations

25
Citations as of Sep 26, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.