Towards robust lidar-based 3D detection and tracking of UAVs

Tasnim Azad Abir; Endrowednes Kuantama; Richard Han; Judith Dawes; Rich Mildren; Phuc Nguyen

doi:10.1145/3597060.3597236

Towards robust lidar-based 3D detection and tracking of UAVs

Tasnim Azad Abir, Endrowednes Kuantama, Richard Han, Judith Dawes, Rich Mildren, Phuc Nguyen

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

3 Citations (Scopus)

59 Downloads (Pure)

Abstract

In this paper, we study the robustness of lidar-based 3D detection & tracking of UAVs. We investigate the effective detection ranges of different UAVs based on their construction materials and the effective range & 3D detection performance of a specific UAV at different atmospheric visibility conditions. Further, we examine to what extent lidar-based systems can track a drone’s trajectories via real-world experiments and point cloud data processing. Using a COTS lidar-based system (Livox Mid-40), we confirm that we can track UAVs in a fine-grained manner at up to 80m distance under various environmental conditions (i.e., morning, afternoon, and night).

Original language	English
Title of host publication	DroNet IX
Subtitle of host publication	proceedings of the DroNet IX Workshop 9th ACMWorkshop on Micro Aerial Vehicle Networks, Systems, and Applications
Place of Publication	New York
Publisher	Association for Computing Machinery (ACM)
Pages	1-7
Number of pages	7
ISBN (Electronic)	9798400702105
DOIs	https://doi.org/10.1145/3597060.3597236
Publication status	Published - 2023
Event	9th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications, DroNet 2023 - Helsinki, Finland Duration: 18 Jun 2023 → 18 Jun 2023

Conference

Conference	9th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications, DroNet 2023
Country/Territory	Finland
City	Helsinki
Period	18/06/23 → 18/06/23

Bibliographical note

Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

Lidar-based detection
UAV detection and tracking
Target reflectivity
Light robustness

Access to Document

10.1145/3597060.3597236Licence: CC BY

Publisher version (open access)Final published version, 1.18 MBLicence: CC BY

Cite this

@inproceedings{f3c6ed67893d48eabbe2b3e0ea36489d,

title = "Towards robust lidar-based 3D detection and tracking of UAVs",

abstract = "In this paper, we study the robustness of lidar-based 3D detection & tracking of UAVs. We investigate the effective detection ranges of different UAVs based on their construction materials and the effective range & 3D detection performance of a specific UAV at different atmospheric visibility conditions. Further, we examine to what extent lidar-based systems can track a drone{\textquoteright}s trajectories via real-world experiments and point cloud data processing. Using a COTS lidar-based system (Livox Mid-40), we confirm that we can track UAVs in a fine-grained manner at up to 80m distance under various environmental conditions (i.e., morning, afternoon, and night).",

keywords = "Lidar-based detection, UAV detection and tracking, Target reflectivity, Light robustness",

author = "Abir, {Tasnim Azad} and Endrowednes Kuantama and Richard Han and Judith Dawes and Rich Mildren and Phuc Nguyen",

note = "Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.; 9th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications, DroNet 2023 ; Conference date: 18-06-2023 Through 18-06-2023",

year = "2023",

doi = "10.1145/3597060.3597236",

language = "English",

pages = "1--7",

booktitle = "DroNet IX",

publisher = "Association for Computing Machinery (ACM)",

address = "United States",

}

Abir, TA, Kuantama, E , Han, R , Dawes, J , Mildren, R & Nguyen, P 2023, Towards robust lidar-based 3D detection and tracking of UAVs. in DroNet IX: proceedings of the DroNet IX Workshop 9th ACMWorkshop on Micro Aerial Vehicle Networks, Systems, and Applications. Association for Computing Machinery (ACM), New York, pp. 1-7, 9th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications, DroNet 2023, Helsinki, Finland, 18/06/23. https://doi.org/10.1145/3597060.3597236

Towards robust lidar-based 3D detection and tracking of UAVs. / Abir, Tasnim Azad; Kuantama, Endrowednes ; Han, Richard et al.
DroNet IX: proceedings of the DroNet IX Workshop 9th ACMWorkshop on Micro Aerial Vehicle Networks, Systems, and Applications. New York: Association for Computing Machinery (ACM), 2023. p. 1-7.

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

TY - GEN

T1 - Towards robust lidar-based 3D detection and tracking of UAVs

AU - Abir, Tasnim Azad

AU - Kuantama, Endrowednes

AU - Han, Richard

AU - Dawes, Judith

AU - Mildren, Rich

AU - Nguyen, Phuc

N1 - Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

PY - 2023

Y1 - 2023

N2 - In this paper, we study the robustness of lidar-based 3D detection & tracking of UAVs. We investigate the effective detection ranges of different UAVs based on their construction materials and the effective range & 3D detection performance of a specific UAV at different atmospheric visibility conditions. Further, we examine to what extent lidar-based systems can track a drone’s trajectories via real-world experiments and point cloud data processing. Using a COTS lidar-based system (Livox Mid-40), we confirm that we can track UAVs in a fine-grained manner at up to 80m distance under various environmental conditions (i.e., morning, afternoon, and night).

AB - In this paper, we study the robustness of lidar-based 3D detection & tracking of UAVs. We investigate the effective detection ranges of different UAVs based on their construction materials and the effective range & 3D detection performance of a specific UAV at different atmospheric visibility conditions. Further, we examine to what extent lidar-based systems can track a drone’s trajectories via real-world experiments and point cloud data processing. Using a COTS lidar-based system (Livox Mid-40), we confirm that we can track UAVs in a fine-grained manner at up to 80m distance under various environmental conditions (i.e., morning, afternoon, and night).

KW - Lidar-based detection

KW - UAV detection and tracking

KW - Target reflectivity

KW - Light robustness

UR - http://www.scopus.com/inward/record.url?scp=85163860095&partnerID=8YFLogxK

U2 - 10.1145/3597060.3597236

DO - 10.1145/3597060.3597236

M3 - Conference proceeding contribution

AN - SCOPUS:85163860095

SP - 1

EP - 7

BT - DroNet IX

PB - Association for Computing Machinery (ACM)

CY - New York

T2 - 9th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications, DroNet 2023

Y2 - 18 June 2023 through 18 June 2023

ER -

Towards robust lidar-based 3D detection and tracking of UAVs

Abstract

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this