Dynamic Interception Image-Based Visual Servoing Under Gust Interference and Model Uncertainty

Hanyu Guo; Tao Song; Jianchuan Ye

doi:10.1007/978-981-95-3037-3_28

Dynamic Interception Image-Based Visual Servoing Under Gust Interference and Model Uncertainty

Hanyu Guo
, Tao Song
, Jianchuan Ye^*

^*Corresponding author for this work

Beijing Institute of Technology

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

Abstract

The existence of gust interference, sensor noise, model uncertainty, nonlinear and underactuated characteristics of quadrotor drones, and unknown target drone motion poses challenges to the existing UAV dynamic interception technology based on image visual servoing (IBVS). Based on the image dynamics model of the virtual image plane and velocity compensation, this study designs a finite-time convergence interception control method. The incremental nonlinear dynamic inversion (INDI) technology is used to improve the robustness of the quadrotor drone to gust interference, unknown target acceleration and model uncertainty. From the comparison of simulation results, it can be seen that under the above environmental conditions, compared with the existing methods, the proposed control method improves the interception accuracy by 45%, 21.3% and 49.2% in the head-on interception, pursuit and maneuvering target interception tasks, respectively.

Original language	English
Title of host publication	Proceedings of the 2nd Aerospace Frontiers Conference, AFC 2025 - Volume VI
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	410-420
Number of pages	11
ISBN (Print)	9789819530366
DOIs	https://doi.org/10.1007/978-981-95-3037-3_28
Publication status	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

Gust interference
Image-based visual servoing (IBVS)
Incremental nonlinear dynamic inversion (INDI)
Interception
Model uncertainty
Quadrotor

Access to Document

10.1007/978-981-95-3037-3_28

Cite this

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title = "Dynamic Interception Image-Based Visual Servoing Under Gust Interference and Model Uncertainty",

abstract = "The existence of gust interference, sensor noise, model uncertainty, nonlinear and underactuated characteristics of quadrotor drones, and unknown target drone motion poses challenges to the existing UAV dynamic interception technology based on image visual servoing (IBVS). Based on the image dynamics model of the virtual image plane and velocity compensation, this study designs a finite-time convergence interception control method. The incremental nonlinear dynamic inversion (INDI) technology is used to improve the robustness of the quadrotor drone to gust interference, unknown target acceleration and model uncertainty. From the comparison of simulation results, it can be seen that under the above environmental conditions, compared with the existing methods, the proposed control method improves the interception accuracy by 45\%, 21.3\% and 49.2\% in the head-on interception, pursuit and maneuvering target interception tasks, respectively.",

keywords = "Gust interference, Image-based visual servoing (IBVS), Incremental nonlinear dynamic inversion (INDI), Interception, Model uncertainty, Quadrotor",

author = "Hanyu Guo and Tao Song and Jianchuan Ye",

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 = "10.1007/978-981-95-3037-3\_28",

language = "English",

isbn = "9789819530366",

series = "Lecture Notes in Mechanical Engineering",

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

pages = "410--420",

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

address = "Germany",

}

Guo, H, Song, T & Ye, J 2026, Dynamic Interception Image-Based Visual Servoing Under Gust Interference and Model Uncertainty. in Proceedings of the 2nd Aerospace Frontiers Conference, AFC 2025 - Volume VI. Lecture Notes in Mechanical Engineering, Springer Science and Business Media Deutschland GmbH, pp. 410-420, 2nd Aerospace Frontiers Conference, AFC 2025, Beijing, China, 11/04/25. https://doi.org/10.1007/978-981-95-3037-3_28

Dynamic Interception Image-Based Visual Servoing Under Gust Interference and Model Uncertainty. / Guo, Hanyu; Song, Tao; Ye, Jianchuan.
Proceedings of the 2nd Aerospace Frontiers Conference, AFC 2025 - Volume VI. Springer Science and Business Media Deutschland GmbH, 2026. p. 410-420 (Lecture Notes in Mechanical Engineering).

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

TY - GEN

T1 - Dynamic Interception Image-Based Visual Servoing Under Gust Interference and Model Uncertainty

AU - Guo, Hanyu

AU - Song, Tao

AU - Ye, Jianchuan

N1 - Publisher Copyright: © Press of Acta Aeronautica et Astronautica Sinica 2026.

PY - 2026

Y1 - 2026

N2 - The existence of gust interference, sensor noise, model uncertainty, nonlinear and underactuated characteristics of quadrotor drones, and unknown target drone motion poses challenges to the existing UAV dynamic interception technology based on image visual servoing (IBVS). Based on the image dynamics model of the virtual image plane and velocity compensation, this study designs a finite-time convergence interception control method. The incremental nonlinear dynamic inversion (INDI) technology is used to improve the robustness of the quadrotor drone to gust interference, unknown target acceleration and model uncertainty. From the comparison of simulation results, it can be seen that under the above environmental conditions, compared with the existing methods, the proposed control method improves the interception accuracy by 45%, 21.3% and 49.2% in the head-on interception, pursuit and maneuvering target interception tasks, respectively.

AB - The existence of gust interference, sensor noise, model uncertainty, nonlinear and underactuated characteristics of quadrotor drones, and unknown target drone motion poses challenges to the existing UAV dynamic interception technology based on image visual servoing (IBVS). Based on the image dynamics model of the virtual image plane and velocity compensation, this study designs a finite-time convergence interception control method. The incremental nonlinear dynamic inversion (INDI) technology is used to improve the robustness of the quadrotor drone to gust interference, unknown target acceleration and model uncertainty. From the comparison of simulation results, it can be seen that under the above environmental conditions, compared with the existing methods, the proposed control method improves the interception accuracy by 45%, 21.3% and 49.2% in the head-on interception, pursuit and maneuvering target interception tasks, respectively.

KW - Gust interference

KW - Image-based visual servoing (IBVS)

KW - Incremental nonlinear dynamic inversion (INDI)

KW - Interception

KW - Model uncertainty

KW - Quadrotor

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DO - 10.1007/978-981-95-3037-3_28

M3 - Conference contribution

AN - SCOPUS:105028355845

SN - 9789819530366

T3 - Lecture Notes in Mechanical Engineering

SP - 410

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

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T2 - 2nd Aerospace Frontiers Conference, AFC 2025

Y2 - 11 April 2025 through 14 April 2025

ER -

Dynamic Interception Image-Based Visual Servoing Under Gust Interference and Model Uncertainty

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