Proactive Guidance for Accurate UAV Landing on a Dynamic Platform: A Visual-inertial Approach

Ching-Wei Chang; Li-Yu Lo; Hiu Ching Cheung; Yurong Feng; An-Shik Yang; Chih-Yung Wen; Weifeng Zhou

doi:10.20944/preprints202112.0012.v1

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preprints.org > engineering > control and systems engineering > doi: 10.20944/preprints202112.0012.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Proactive Guidance for Accurate UAV Landing on a Dynamic Platform: A Visual-inertial Approach

Version 1 : Received: 30 November 2021 / Approved: 1 December 2021 / Online: 1 December 2021 (11:58:13 CET)

How to cite: Chang, C.; Lo, L.; Cheung, H.C.; Feng, Y.; Yang, A.; Wen, C.; Zhou, W. Proactive Guidance for Accurate UAV Landing on a Dynamic Platform: A Visual-inertial Approach. Preprints 2021, 2021120012. https://doi.org/10.20944/preprints202112.0012.v1 Chang, C.; Lo, L.; Cheung, H.C.; Feng, Y.; Yang, A.; Wen, C.; Zhou, W. Proactive Guidance for Accurate UAV Landing on a Dynamic Platform: A Visual-inertial Approach. Preprints 2021, 2021120012. https://doi.org/10.20944/preprints202112.0012.v1

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MDPI and ACS Style

Chang, C.; Lo, L.; Cheung, H.C.; Feng, Y.; Yang, A.; Wen, C.; Zhou, W. Proactive Guidance for Accurate UAV Landing on a Dynamic Platform: A Visual-inertial Approach. Preprints 2021, 2021120012. https://doi.org/10.20944/preprints202112.0012.v1

APA Style

Chang, C., Lo, L., Cheung, H.C., Feng, Y., Yang, A., Wen, C., & Zhou, W. (2021). Proactive Guidance for Accurate UAV Landing on a Dynamic Platform: A Visual-inertial Approach. Preprints. https://doi.org/10.20944/preprints202112.0012.v1

Chicago/Turabian Style

Chang, C., Chih-Yung Wen and Weifeng Zhou. 2021 "Proactive Guidance for Accurate UAV Landing on a Dynamic Platform: A Visual-inertial Approach" Preprints. https://doi.org/10.20944/preprints202112.0012.v1

Abstract

This work aims to develop an autonomous system for the unmanned aerial vehicle (UAV) to land on a moving platform such as the automobile or marine vessels, providing a promising solution for a long-endurance flight operation, a large mission coverage range, and a convenient recharging ground station. Different from most state-of-the-art UAV landing frameworks which rely on UAV’s onboard computers and sensors, the proposed system fully depends on the computation unit situated on the ground vehicle/marine vessel to serve as a landing guidance system. Such novel configuration can therefore lighten the burden of the UAV and computation power on the ground vehicle/marine vessel could be enhanced. In particular, we exploit a sensor fusion-based algorithm for the guidance system to perform UAV localization, whilst a control method based upon trajectory optimization is integrated. Indoor and outdoor experiments are conducted and the result shows that a precise autonomous landing on a 43 X 43 cm platform could be performed.

Keywords

UAV; VTOL; Object Tracking; Deep Learning; Sensor fusion; Kalman Filter; Autonomous Landing; Optimal Trajectory

Subject

Engineering, Control and Systems Engineering

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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