LAPSE:2023.4196
Published Article
LAPSE:2023.4196
Adaptive Visual Servoing for Obstacle Avoidance of Micro Unmanned Aerial Vehicle with Optical Flow and Switched System Model
Ming-Li Chiang, Shun-Hung Tsai, Cheng-Ming Huang, Kuang-Tin Tao
February 22, 2023
Abstract
A vision-based adaptive switching controller that uses optical flow information to avoid obstacles for micro unmanned aerial vehicles (MUAV) is proposed in this paper. To use the optical flow to indicate the distance between the MUAV and the environment, we propose an algorithm with multi-thread processing such that the optical flow information is obtained reliably and continuously in the entire camera field of view. The flying behavior of considered MUAV is regarded as a switching system when considering different flying modes during the mission of obstacle avoidance. By the required flight direction for obstacle avoidance specified by the detected optical flow, an adaptive control scheme is designed to track the required trajectory in switching modes. The simulation result shows the tracking performances of the adaptive control with the switching system. The experiment of the whole system is completed to verify the obstacle avoidance capability of our system.
Keywords
MUAV, optical flow, switched systems, visual servoing
Suggested Citation
Chiang ML, Tsai SH, Huang CM, Tao KT. Adaptive Visual Servoing for Obstacle Avoidance of Micro Unmanned Aerial Vehicle with Optical Flow and Switched System Model. (2023). LAPSE:2023.4196
Author Affiliations
Chiang ML: Department of Applied Mathematics, Tung Hai University, Taichung 407224, Taiwan
Tsai SH: Department of Electrical Engineering, National Sun Yet-Sen University, Kaohsiung 804, Taiwan
Huang CM: Departments of Electrical Engineering, National Taipei University of Technology, Taipei 106, Taiwan
Tao KT: R&D Department II, Wistron Corporation, Neihu 11469, Taiwan
Journal Name
Processes
Volume
9
Issue
12
First Page
2126
Year
2021
Publication Date
2021-11-25
ISSN
2227-9717
Version Comments
Original Submission
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PII: pr9122126, Publication Type: Journal Article
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LAPSE:2023.4196
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https://doi.org/10.3390/pr9122126
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Feb 22, 2023
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