A Method for Situation Awareness of Unmanned Aerial Vehicle Based on Octree Map

Zhen Wang; Yihuan Zhang; Yuhao Shi; Xiang Chang; Borui Yao; Yiyang Wu; Bin Wu; Mingying Huo; Naiming Qi

doi:10.1007/978-981-95-3007-6_4

A Method for Situation Awareness of Unmanned Aerial Vehicle Based on Octree Map

Zhen Wang
, Yihuan Zhang
, Yuhao Shi
, Xiang Chang
, Borui Yao
, Yiyang Wu
, Bin Wu
, Mingying Huo^*
, Naiming Qi^*

^*Corresponding author for this work

School of Astronautics, Harbin Institute of Technology

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

Abstract

The situation awareness capability of Unmanned Aerial Vehicles (UAVs) is a critical technology for ensuring successful mission execution and flight safety, playing an indispensable role in the development and application of UAVs. To enhance the situation awareness capabilities of UAVs while reducing the volume of mapping data, this paper proposes a situation awareness method for UAVs based on octree map. Initially, the motion trajectory of the UAV is determined using Kalman filtering for its pose information. Subsequently, feature extraction is performed using FAST key points and BRIEF descriptors, and feature points from adjacent frames are matched using a Fast Library for Approximate Nearest Neighbors algorithm to integrate image information. Finally, the octree map is constructed to enable effective situation awareness by combining the UAV's motion trajectory with image matching information. Simulation results demonstrate that this method not only achieves superior situation awareness for UAVs but also exhibits better data compression characteristics compared with point cloud maps.

Original language	English
Title of host publication	Proceedings of the 2nd Aerospace Frontiers Conference, AFC 2025 - Volume II
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	54-65
Number of pages	12
ISBN (Print)	9789819530069
DOIs	https://doi.org/10.1007/978-981-95-3007-6_4
State	Published - 2026
Externally published	Yes
Event	2nd Aerospace Frontiers Conference, AFC 2025 - Beijing, China Duration: 11 Apr 2025 → 14 Apr 2025

Publication series

Name	Lecture Notes in Mechanical Engineering
ISSN (Print)	2195-4356
ISSN (Electronic)	2195-4364

Conference

Conference	2nd Aerospace Frontiers Conference, AFC 2025
Country/Territory	China
City	Beijing
Period	11/04/25 → 14/04/25

Keywords

Fast library for approximate nearest neighbors
Feature extraction
Octree map
Pose calculation
Situation awareness

Access to Document

10.1007/978-981-95-3007-6_4

Cite this

Wang, Z., Zhang, Y., Shi, Y., Chang, X., Yao, B., Wu, Y., Wu, B., Huo, M., & Qi, N. (2026). A Method for Situation Awareness of Unmanned Aerial Vehicle Based on Octree Map. In Proceedings of the 2nd Aerospace Frontiers Conference, AFC 2025 - Volume II (pp. 54-65). (Lecture Notes in Mechanical Engineering). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-95-3007-6_4

@inproceedings{ded831de6c1445638125b55c3306c917,

title = "A Method for Situation Awareness of Unmanned Aerial Vehicle Based on Octree Map",

abstract = "The situation awareness capability of Unmanned Aerial Vehicles (UAVs) is a critical technology for ensuring successful mission execution and flight safety, playing an indispensable role in the development and application of UAVs. To enhance the situation awareness capabilities of UAVs while reducing the volume of mapping data, this paper proposes a situation awareness method for UAVs based on octree map. Initially, the motion trajectory of the UAV is determined using Kalman filtering for its pose information. Subsequently, feature extraction is performed using FAST key points and BRIEF descriptors, and feature points from adjacent frames are matched using a Fast Library for Approximate Nearest Neighbors algorithm to integrate image information. Finally, the octree map is constructed to enable effective situation awareness by combining the UAV's motion trajectory with image matching information. Simulation results demonstrate that this method not only achieves superior situation awareness for UAVs but also exhibits better data compression characteristics compared with point cloud maps.",

keywords = "Fast library for approximate nearest neighbors, Feature extraction, Octree map, Pose calculation, Situation awareness",

author = "Zhen Wang and Yihuan Zhang and Yuhao Shi and Xiang Chang and Borui Yao and Yiyang Wu and Bin Wu and Mingying Huo and Naiming Qi",

note = "Publisher Copyright: {\textcopyright} Press of Acta Aeronautica et Astronautica Sinica 2026.; 2nd Aerospace Frontiers Conference, AFC 2025 ; Conference date: 11-04-2025 Through 14-04-2025",

year = "2026",

doi = "10.1007/978-981-95-3007-6\_4",

language = "英语",

isbn = "9789819530069",

series = "Lecture Notes in Mechanical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "54--65",

booktitle = "Proceedings of the 2nd Aerospace Frontiers Conference, AFC 2025 - Volume II",

address = "德国",

}

Wang, Z, Zhang, Y, Shi, Y, Chang, X, Yao, B, Wu, Y, Wu, B, Huo, M & Qi, N 2026, A Method for Situation Awareness of Unmanned Aerial Vehicle Based on Octree Map. in Proceedings of the 2nd Aerospace Frontiers Conference, AFC 2025 - Volume II. Lecture Notes in Mechanical Engineering, Springer Science and Business Media Deutschland GmbH, pp. 54-65, 2nd Aerospace Frontiers Conference, AFC 2025, Beijing, China, 11/04/25. https://doi.org/10.1007/978-981-95-3007-6_4

A Method for Situation Awareness of Unmanned Aerial Vehicle Based on Octree Map. / Wang, Zhen; Zhang, Yihuan; Shi, Yuhao et al.
Proceedings of the 2nd Aerospace Frontiers Conference, AFC 2025 - Volume II. Springer Science and Business Media Deutschland GmbH, 2026. p. 54-65 (Lecture Notes in Mechanical Engineering).

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

TY - GEN

T1 - A Method for Situation Awareness of Unmanned Aerial Vehicle Based on Octree Map

AU - Wang, Zhen

AU - Zhang, Yihuan

AU - Shi, Yuhao

AU - Chang, Xiang

AU - Yao, Borui

AU - Wu, Yiyang

AU - Wu, Bin

AU - Huo, Mingying

AU - Qi, Naiming

PY - 2026

Y1 - 2026

N2 - The situation awareness capability of Unmanned Aerial Vehicles (UAVs) is a critical technology for ensuring successful mission execution and flight safety, playing an indispensable role in the development and application of UAVs. To enhance the situation awareness capabilities of UAVs while reducing the volume of mapping data, this paper proposes a situation awareness method for UAVs based on octree map. Initially, the motion trajectory of the UAV is determined using Kalman filtering for its pose information. Subsequently, feature extraction is performed using FAST key points and BRIEF descriptors, and feature points from adjacent frames are matched using a Fast Library for Approximate Nearest Neighbors algorithm to integrate image information. Finally, the octree map is constructed to enable effective situation awareness by combining the UAV's motion trajectory with image matching information. Simulation results demonstrate that this method not only achieves superior situation awareness for UAVs but also exhibits better data compression characteristics compared with point cloud maps.

AB - The situation awareness capability of Unmanned Aerial Vehicles (UAVs) is a critical technology for ensuring successful mission execution and flight safety, playing an indispensable role in the development and application of UAVs. To enhance the situation awareness capabilities of UAVs while reducing the volume of mapping data, this paper proposes a situation awareness method for UAVs based on octree map. Initially, the motion trajectory of the UAV is determined using Kalman filtering for its pose information. Subsequently, feature extraction is performed using FAST key points and BRIEF descriptors, and feature points from adjacent frames are matched using a Fast Library for Approximate Nearest Neighbors algorithm to integrate image information. Finally, the octree map is constructed to enable effective situation awareness by combining the UAV's motion trajectory with image matching information. Simulation results demonstrate that this method not only achieves superior situation awareness for UAVs but also exhibits better data compression characteristics compared with point cloud maps.

KW - Fast library for approximate nearest neighbors

KW - Feature extraction

KW - Octree map

KW - Pose calculation

KW - Situation awareness

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SN - 9789819530069

T3 - Lecture Notes in Mechanical Engineering

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BT - Proceedings of the 2nd Aerospace Frontiers Conference, AFC 2025 - Volume II

PB - Springer Science and Business Media Deutschland GmbH

T2 - 2nd Aerospace Frontiers Conference, AFC 2025

Y2 - 11 April 2025 through 14 April 2025

ER -

A Method for Situation Awareness of Unmanned Aerial Vehicle Based on Octree Map

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