Autonomous Drone Landing: Marked Landing Pads and Solidified Lava Flows
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Published:2024-01-30
Issue:
Volume:
Page:1-17
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ISSN:1793-351X
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Container-title:International Journal of Semantic Computing
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language:en
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Short-container-title:Int. J. Semantic Computing
Author:
Springer Joshua1ORCID,
Kyas Marcel1ORCID
Affiliation:
1. Department of Computer Science, Reykjavik University, Menntavegur 1, 101 Reykjavik, Iceland
Abstract
Landing is the most challenging and risky aspect of basic multirotor drone flight, and only simple landing methods exist for autonomous drones. We explore methods for autonomous drone landing in two scenarios. In the first scenario, we examine methods for landing on known landing pads using fiducial markers and a gimbal-mounted monocular camera. This method has potential in drone applications where a drone must land more accurately than global positioning system (GPS) can provide (e.g. package delivery in an urban canyon). We expand on previous methods by actuating the drone’s camera to track the marker over time, and we address the complexities of pose estimation caused by fiducial marker orientation ambiguity. In the second scenario, and in collaboration with the Rover-Aerial Vehicle Exploration Network (RAVEN) project, we explore methods for landing on solidified lava flows in Iceland, which serves as an analog environment for Mars and provides insight into the effectiveness of drone-rover exploration teams. Our drone uses a depth camera to visualize the terrain, and we are developing methods to analyze the terrain data for viable landing sites in real time with minimal sensors and external infrastructure requirements, so that the solution does not heavily influence the drone’s behavior, mission structure, or operational environments.
Publisher
World Scientific Pub Co Pte Ltd
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Linguistics and Language,Information Systems,Software
Cited by
1 articles.
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