Robust Vision-Based Autonomous Navigation, Mapping and Landing for MAVs at Night
Conference Paper, Proceedings of International Symposium on Experimental Robotics (ISER '18), pp. 232 - 242, November, 2018
Abstract
This paper is about vision-based autonomous flight of MAVs at night. Despite it being dark almost half of the time, most of the work to date has addressed only daytime operations. Enabling autonomous night-time operation of MAVs with low SWaP on-board sensing capabilities is still an open problem in current robotics research. In this paper, we take a step in this direction and introduce a robust vision-based perception system using thermal-infrared cameras. We present this in the context of safe autonomous landing on rooftop-like structures, and demonstrate the efficacy of our proposed system through extensive real-world flight experiments in outdoor environments at night.
Notes
The research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.
The research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.
BibTeX
@conference{Daftry-2018-126835,author = {Shreyansh Daftry and Manash Das and Jeff Delaune and Cristina Sorice and Robert Hewitt and Shreetej Reddy and Daniel Lytle and Elvin Gu and Larry Matthies},
title = {Robust Vision-Based Autonomous Navigation, Mapping and Landing for MAVs at Night},
booktitle = {Proceedings of International Symposium on Experimental Robotics (ISER '18)},
year = {2018},
month = {November},
pages = {232 - 242},
}
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