Machine vision for autonomous small body navigation
- 7 November 2002
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 7, 661-671
- https://doi.org/10.1109/aero.2000.879333
Abstract
This paper describes machine vision algorithms that enable precision guidance and hazard avoidance during small body exploration through onboard visual feature tracking and landmark recognition. These algorithms provide estimates of spacecraft relative motion and absolute position used to guide the spacecraft during autonomous landing and exploration. They also enable hazard avoidance by providing estimates of 3-D surface topography through processing of monocular image streams. This form of onboard autonomy is a critical enabling technology for multiple future missions including Comet Nucleus Sample Return, Large Asteroid Sample Return, Titan Organics Explorer and Europa Lander and Mars lander missions.Keywords
This publication has 7 references indexed in Scilit:
- Real-time 2-D feature detection on a reconfigurable computerPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Error analysis of a real-time stereo systemPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Crater detection for autonomous landing on asteroidsImage and Vision Computing, 2001
- Surface matching for object recognition in complex three-dimensional scenesImage and Vision Computing, 1998
- Iterative point matching for registration of free-form curves and surfacesInternational Journal of Computer Vision, 1994
- Optimal motion and structure estimationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1993
- A computer algorithm for reconstructing a scene from two projectionsNature, 1981