Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/105707
Title: A vision-based navigation system for perching aircraft
Authors: Wu, Yanhua
Venkateswara Rao, D. M. K. K.
Keywords: Vision-based Navigation
Aircraft Perching
Engineering::Aeronautical engineering
Issue Date: 2018
Source: Venkateswara Rao, D. M. K. K., & Wu, Y. (2019). A vision-based navigation system for perching aircraft. Journal of Intelligent & Robotic Systems, 95(2), 555-566. doi:10.1007/s10846-018-0807-7
Series/Report no.: Journal of Intelligent & Robotic Systems
Abstract: This paper presents the investigation of the use of position-sensing diode (PSD) - a light source direction sensor - for designing a vision-based navigation system for a perching aircraft. Aircraft perching maneuvers mimic bird’s landing by climbing for touching down with low velocity or negligible impact. They are optimized to reduce their spatial requirements, like altitude gain or trajectory length. Due to disturbances and uncertainties, real-time perching is realized by tracking the optimal trajectories. As the performance of the controllers depends on the accuracy of estimated aircraft state, the use of PSD measurements as observations in the state estimation model is proposed to achieve precise landing. The performance and the suitability of this navigation system are investigated through numerical simulations. An optimal perching trajectory is computed by minimizing the trajectory length. Accelerations, angular-rates and PSD readings are determined from this trajectory and then added with experimentally obtained noise to create simulated sensor measurements. The initial state of the optimal perching trajectory is perturbed, and by assuming zero biases, extended Kalman filter is implemented for aircraft state estimation. It is shown that the errors between estimated and actual aircraft states reduce along the trajectory, validating the proposed navigation system.
URI: https://hdl.handle.net/10356/105707
http://hdl.handle.net/10220/49551
ISSN: 0921-0296
DOI: 10.1007/s10846-018-0807-7
Rights: © 2018 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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