Image-Based Lunar Terrain Relative Navigation Without a Map: Measurements
Abstract
Image-based terrain relative navigation is expected to play an important role in the safe operation of upcoming lunar exploration missions. This work provides a detailed treatment of how visual odometry direction-of-motion measurements may be constructed using images from a monocular camera and without the need of an onboard map of the lunar surface. Substantial care is required to achieve best-possible navigation performance, which numerical studies indicate is sufficient to enable many types of autonomous navigation. Results are shown for historical Apollo images and for synthetic images. While visual odometry alone may not meet every mission’s needs, it is a powerful technique that should be a part of every professional spacecraft navigator’s toolkit.
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Visual odometry paradigms do not require extensive cataloging for TRN and have advanced the capabilities of autonomous systems and improved robustness to prevalent sources of error.
“On the other hand, Visual Odometry (VO) paradigms which do not require extensive cataloging for TRN have also majorly advanced the capabilities of autonomous systems and vastly improved robustness to the prevalent sources of error17,18.”
From Probabilistic regression for autonomous terrain relative navigation via multi-modal feature learning (2024) · cites this paper as [17]
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- Authors
- Christian, J. A., Hong, L., McKee, P., Christensen, R., & Crain, T. P.
- Affiliations
- Rensselaer Polytechnic Institute (US)
- Utah State University (US)
- Intuitive Machines, LLC, Houston, Texas 77058
- Venue
- Journal of Spacecraft and Rockets
- Published
- 2021-01
- Volume
- 58
- Issue
- 1
- Pages
- 164-181
- ISSN
- 0022-4650 (ISSN-L)
- 1533-6794
- OpenAlex
- W3097586409
- Cited by
- 31
- References
- 46
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 6 · 2023: 5 · 2022: 2 · 2021: 4
- FWCI
- 1.65
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Spacecraft and Rockets (publishedVersion)
- Funders
- Intuitive Machines
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
- Physical Sciences › Engineering › Aerospace Engineering › Spacecraft Dynamics and Control
- Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
- Keywords
- image-based navigation, visual odometry, monocular camera, mapless navigation, lunar exploration, autonomous spacecraft navigation, spacecraft navigation
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