Decentralized Fusion with Finite Set Statistics for Landing Navigation
The simultaneous localization and mapping (SLAM) problem is one that utilizes a vehicle's observations of its environment to refine an estimate of that environment while improving understanding of its own state. This paper proposes the use of SLAM tools formulated using finite set statistics to perform terrain-aided navigation for planetary landers. Further, the methodology is designed to augment, rather than replace, standard extended Kalman filter-based navigation architectures via decentralized fusion with feedback, enabling a SLAM-Fusion procedure with substantially lower development costs than replacing existing approaches altogether. The resulting approach enables significant performance improvements in existing navigation filters with little to no modification of the existing scheme. The theoretical results are supported via simulation of a lunar descent trajectory and the proposed SLAM-Fusion procedure.
J. S. McCabe and K. J. DeMars, "Decentralized Fusion with Finite Set Statistics for Landing Navigation," Advances in the Astronautical Sciences, vol. 162, pp. 2937-2961, Univelt Inc., Aug 2018.
AAS/AIAA Astrodynamics Specialist Conference, 2017 (2017: Aug. 20-24, Stevenson, WA)
Mechanical and Aerospace Engineering
Keywords and Phrases
Astrophysics; Kalman filters; Navigation; Planetary landers; Robotics; Set theory, Decentralized fusions; Descent trajectories; Finite set statistics; Navigation architectures; Navigation filters; Performance improvements; Simultaneous localization and mapping problems; Terrain aided navigation, Air navigation
International Standard Book Number (ISBN)
International Standard Serial Number (ISSN)
Article - Conference proceedings
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