City Research Online

Abstract

Current light detection and ranging (LIDAR) based odometry solutions that are used for spacecraft relative navigation suffer from quite a few deficiencies. These include an off-line training requirement and relying on the iterative closest point (ICP) that does not guarantee a globally optimum solution. To encounter this, the authors suggest a robust architecture that overcomes the problems of current proposals by combining the concepts of 3D local feature matching with an adaptive variant of the H∞ recursive filtering process. Trials on real laser scans of an EnviSat model demonstrate that the proposed architecture affords at least one order of magnitude better accuracy compared to ICP.

Publication Type:	Article
Additional Information:	This paper is a postprint of a paper submitted to and accepted for publication in IET Radar, Sonar & Navigation and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library (https://doi.org/10.1049/iet-rsn.2018.5354). ©Institution of Engineering and Technology, 2019.
Subjects:	T Technology > TL Motor vehicles. Aeronautics. Astronautics
Departments:	School of Science & Technology > Department of Engineering
SWORD Depositor:	Symplectic Administrator

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