Autonomous Quadrotor Landing on Inclined Surfaces in High Particle Environments Using Radar Sensor Perception
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Authors
Lesak, Mark C.
Taylor, Dylan
Kim, Jinho
Korpela, Christopher M.
Issue Date
2022
Type
proceedings-article
Language
Keywords
Point cloud compression , Propellers , Land surface , Radar , Cameras , Sensor Systems , Sensors
Alternative Title
Abstract
This paper presents an autonomous approach for landing a quadrotor on inclined surfaces up to 40 degrees using radar perception in a high particle environment, such as dust, rain, or fog. This system uses five radar sensors to determine the direction, angle, and smoothness of a slope through eigenvalue decomposition of a point cloud covariance matrix. The point cloud itself is generated using a FIFO queue with the radar sensors after their points are transformed to a common frame. Then, two asymmetric landing skids of different lengths actively conform to a slope in order to maintain level body attitude upon landing. For perception error tolerance, a study to understand the distance between the propeller and slope surface with respect to slope angles was developed. We evaluate the accuracy and consistency of radar sensors in accomplishing these tasks, to include a comparison of the results with a depth camera while in a high particle environment. Finally, the experimental result shows that the detected slope angle and direction were within 2.2 and 2.4 degrees of ground, and the proposed system is viable and robust for use in real-world applications.
Description
Citation
M. C. Lesak, D. Taylor, J. Kim and C. Korpela, "Autonomous Quadrotor Landing on Inclined Surfaces in High Particle Environments Using Radar Sensor Perception," 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Kyoto, Japan, 2022, pp. 12352-12358, doi: 10.1109/IROS47612.2022.9981929.
Publisher
IEEE