Advanced Bayesian Methods for Lunar Surface Navigation

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NNX10CC95P
Agency Tracking Number: 094663
Amount: $99,937.00
Phase: Phase I
Program: SBIR
Awards Year: 2010
Solicitation Year: 2009
Solicitation Topic Code: O4.03
Solicitation Number: N/A
Small Business Information
385 High Plain Road, Andover, MA, 01810-3234
DUNS: 961415887
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Julian Center
 Principal Investigator
 (978) 683-0290
 jcenter@ieee.org
Business Contact
 Julian Center
Title: CEO
Phone: (978) 269-4120
Email: jcenter@ieee.org
Research Institution
N/A
Abstract
The key innovation of this project will be the application of advanced Bayesian methods to integrate real-time dense stereo vision and high-speed optical flow with an Inertial Measurement Unit (IMU) to produce a highly accurate planetary rover navigation system. The software developed in this project will leverage current computing technology to implement advanced Visual Odometry (VO) methods that will accurately track much faster rover movements. Our fully Bayesian approach to VO will utilize more information from the images than previous methods are capable of using. Our Bayesian VO does not explicitly select features to track. Instead it implicitly determines what can be learned from each image pixel and weights the information accordingly. This means that our approach can work with images that have no distinct corners, which can be a significant advantage with low contrast images from permanently shadowed areas. We expect that the error characteristics of the visual processing with be complementary to the error characteristics of a low-cost IMU. Therefore, the combination of the two should provide highly accurate navigation.

* Information listed above is at the time of submission. *

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