Image-Based Visual Servoing of Micro Aerial Vehicles With Robust Observation and Output Feedback

An output feedback control method is proposed in the article with state observers for robust image-based visual servoing (IBVS) regarding micro aerial vehicles (MAVs). Specifically, image features are first selected from the perspective image moments and are projected onto a suitably defined image plane so as to provide decoupled kinematics for translational motion. In order to address the problem of low quality and even unavailability of linear velocity information, the image moment error observer is designed as a foundation based on an image filter, and then the MAV body velocities are estimated by designing a robust observer to obtain translational optical flow of virtual image features. An adaptive law is proposed for the unknown depth information of the visual target and is combined with observers in output feedback controller design to enhance system robustness. Stability analysis shows that all states of the system are uniformly ultimately bounded (UUB) and converge to zero asymptotically. Comparative simulation and experimental results demonstrate the performance of the proposed method.

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Publication Details

Journal
IEEE Transactions on Control Systems Technology
Published
2025-05-29
DOI
https://doi.org/10.1109/tcst.2025.3570243
Primary Topic
Advanced Vision and Imaging
Type
article
Field-Weighted Citation Impact
0.00

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article

Image-Based Visual Servoing of Micro Aerial Vehicles With Robust Observation and Output Feedback

Xuebo Zhang, Wuxi Shi, Yongcong Chen, Baoquan Li
1 links
IEEE Transactions on Control Systems Technology
Advanced Vision and Imaging
article

Image-Based Visual Servoing of Micro Aerial Vehicles With Robust Observation and Output Feedback

Xuebo Zhang, Wuxi Shi, Yongcong Chen, Baoquan Li
article en

Abstract

An output feedback control method is proposed in the article with state observers for robust image-based visual servoing (IBVS) regarding micro aerial vehicles (MAVs). Specifically, image features are first selected from the perspective image moments and are projected onto a suitably defined image plane so as to provide decoupled kinematics for translational motion. In order to address the problem of low quality and even unavailability of linear velocity information, the image moment error observer is designed as a foundation based on an image filter, and then the MAV body velocities are estimated by designing a robust observer to obtain translational optical flow of virtual image features. An adaptive law is proposed for the unknown depth information of the visual target and is combined with observers in output feedback controller design to enhance system robustness. Stability analysis shows that all states of the system are uniformly ultimately bounded (UUB) and converge to zero asymptotically. Comparative simulation and experimental results demonstrate the performance of the proposed method.

IEEE Transactions on Control Systems TechnologyVol. 33(6)
Tiangong University (CN), Nankai University (CN)
National Science Foundation, National Natural Science Foundation of China
Openalex Percentile: Top 90%
Advanced Vision and Imaging
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