Relative Navigation and Terrain-based Path Planning using Flash LiDAR based Surfel Grid Map for Asteroid Exploration
Open accessAbstract
Due to lack of spacecraft's global position and attitude information on small solar system bodies (SSSBs) like asteroids, only relative state measurements are available for navigation. Therefore, relative navigation with respect to a local reference frame is the basis for in-situ autonomous exploration on the asteroids. The relative navigation changes a local reference frame during the flight, which guarantees local accuracy of state estimation and mapping. We present the relative navigation framework using surfel grid map-based scan-to-map matching for localization and mapping on asteroid surface. We also propose a terrain-based path planning that makes use of inherent terrain surface properties of surfel grid maps. A thorough validation of our navigation approach and comparison to a global flash LiDAR-based navigation in different flight scenarios and in both MIL (model-in-the-loop) and real-time PIL (processor-in-the-loop) tests show the viability of this novel navigation framework.
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Real and simulated LiDAR data has proven efficient and robust data for neural network training in many applications, such as obstacle detection, path planning, and TRN even in the case of uncooperative operations.
“Real and simulated LiDAR data has proven efficient and robust data for neural network training in many applications, such as obstacle detection20, path planning21, and TRN even in the case of uncooperative operations22.”
From Probabilistic regression for autonomous terrain relative navigation via multi-modal feature learning (2024) · cites this paper as [21]
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Probabilistic regression for autonomous terrain relative navigation via multi-modal feature learning
Kim, I., & Singh, S. (2024) · Scientific Reports · doi:10.1038/s41598-024-81377-z · Cited by 6 · see citing works
“Real and simulated LiDAR data has proven efficient and robust data for neural network training in many applications, such as obstacle detection 20 , path planning 21 , and TRN even in the case of uncooperative operations 22 .”
Optimization-based Local Relative Navigation for Exploration on Asteroid Surface
Liu, B., Liu, J., & Janschek, K. (2023) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2023.10.1098
Self-citation
- Authors
- Liu, B., & Janschek, K.
- Affiliations
- Institute of Automation (DE)
- Corresponding author
- Liu, B.
- ORCID
- Venue
- IFAC-PapersOnLine
- Publisher
- Elsevier BV
- Published
- 2022
- Volume
- 55
- Issue
- 22
- Pages
- 85-90
- ISSN
- 2405-8963 (ISSN-L)
- OpenAlex
- W4366153709
- Cited by
- 2
- References
- 17
- Citations by year
- 2024: 1 · 2023: 1
- FWCI
- 0.22
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- IFAC-PapersOnLine (publishedVersion)
- Funders
- Bundesministerium für Wirtschaft und Energie (50 RA 1841)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
- Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Robotic Path Planning Algorithms
- Keywords
- relative navigation, asteroid exploration, flash lidar, localization and mapping, small bodies, autonomous spacecraft navigation, processor-in-the-loop testing, model-in-the-loop testing
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