Integrity Monitoring For Automated Aerial Refueling: A Stereo Vision Approach
Abstract
This paper develops two algorithms that provide relative navigation measurements for automated aerial refueling solely from a stereo image pair. Algorithms were analyzed in simulation and then in flight test using two C-12C aircraft. The first algorithm, the Vision and Bayesian Inference Based Integrity Monitor (V5), uses Bayesian inference and template matching to return a probability mass function (PMF) describing the position of an observed aircraft. This PMF provides a relative position estimate as well as a protection level, thus providing a degree of navigation integrity. Using both simulation and flight test data, mean V5 spherical error was less than one meter and protection levels reliably characterized algorithm uncertainty. The second algorithm, relative pose estimation with computer vision and iterative closest point (R7), uses stereo vision algorithms and the iterative closest point algorithm to return relative position and attitude estimates. Using both simulation and flight test data, mean R7 spherical error was less than 0.5 meters. Additionally, in flight test, mean R7 attitude errors were less than 3 in all axes.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 23, 2018
- Accession Number
- AD1056214
Entities
People
- Thomas R. Stuart
Organizations
- Air Force Institute of Technology