Session D5: AI/Machine Learning (ML) for PNT Determination

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Date: Wednesday, June 14, 2023
Time: 8:30 a.m. - 10:00 a.m.

Session Chairs:

Dr. David Woodburn AFIT	Dr. Rebecca Russell Draper

8:35 a.m.	“Surepoints” – Deep Learning for custom Vision Aided Navigation Descriptors: Dylan Bowald - AFRL Positioning, Navigation, & Timing branch
8:55 a.m.	Increasing CNN Findable Features in Imagery via Labeling Obscured Features: Jeffrey Choate, Scott Nykl, Air Force Institute of Technology
9:15 a.m.	Landmark NAV: Vision-Only Robust 6-D.O.F. Aircraft Localization: Jack Tsai, Zachary Fisher, Honeywell Aerospace; Nikhil Gupta, Qualcomm; Justin Syrstad, The Toro Company; Vegnesh Jayaraman, Annis Nusseibeh, Andrew Stewart, Gregg Swenson, Thandava Edara, Honeywell Aerospace; Vijay Venkataraman, Cirrus Aircraft, *Work performed during employment with Honeywell
9:35 a.m.	Machine Learning for the Characterization of Seabed Topography for Bathymetric Fixing: Simran Shinh and Jonathan Thomas, JHU/APL
Alternates
1.	GNSS Machine Learning Toolset (MLT): Luis Hernandez, Clarizza Morales, Jim Aarestad, Brian Zufelt, Cosmiac, UNM; Renee Yazdi, Kevin Slimak, Canyon Consulting; Madeleine Nadeau, David Choi, Colton Mott, AFRL
2.	Transformer networks for robust, cross-modal visual terrain relative navigation: Eric Amoroso, Curtis Boirum, Andrew Ashley, Fraser Kitchell, Kerry Snyder, KEF Robotics
3.	Sensor-actuated Deep-learning Neural-network to Estimate Geo-location: Qirfiraz Siddiqui, NOGPS Technologies, Inc.

Break: 10:00 a.m. – 10:45 a.m., Exhibit Hall - Sponsored by L3Harris

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