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Advanced Bayesian Methods for Lunar Surface Navigation

Award Information

Agency:
National Aeronautics and Space Administration
Branch:
N/A
Award ID:
Program Year/Program:
2011 / SBIR
Agency Tracking Number:
094663
Solicitation Year:
2009
Solicitation Topic Code:
O4.03
Solicitation Number:
Small Business Information
Autonomous Exploration, Inc.
385 High Plain Road Andover, MA 01810-3234
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 2
Fiscal Year: 2011
Title: Advanced Bayesian Methods for Lunar Surface Navigation
Agency: NASA
Contract: NNX11CA57C
Award Amount: $599,999.00
 

Abstract:

The key innovation of this project is 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 leverages 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 utilizes 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 have shown that the error characteristics of the visual processing are complementary to the error characteristics of a low-cost IMU. Therefore, the combination of the two can provide highly accurate navigation.

Principal Investigator:

Julian Center
Principal Investigator
9782694120
jcenter@ieee.org

Business Contact:

Julian Center
Business Official
9782694120
jcenter@ieee.org
Small Business Information at Submission:

Autonomous Exploration, Inc.
385 High Plain Road Andover, MA 01810-3234

EIN/Tax ID: 262686819
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No