Session A1a: Navigation and Positioning Using AI

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Date: Wednesday, September 16, 2026
Time: 8:30 a.m. - 10:05 a.m.
Location: Windsong 1-2
In-Person presenters in this session provide pre-recorded presentations for viewing by registered attendees on Wednesday, September 16.

In-Person Presentations These presentations will be given in-person at the conference. Presenters will provide a pre-recorded presentation for on-demand viewing by all registered attendees.
8:35	Actuation-Aware Quadrotor Navigation: A Learned Dynamics Factor for Robust Visual-Inertial Estimation Yu Feng, Dept. of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, & Nankai University; Yingying Wang, Dept. of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University; Fuyong Wang, College of Artificial Intelligence, Nankai University; Haoming Zhang, Learning Systems and Robotics Lab, Technical University of Munich; Weisong Wen, Dept. of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University
8:57	Bird’s-Eye-View Mapping from Vehicle Cameras via 3D Foundation Models Mira Partha, Daniel Neamati, Dev Jayram, and Grace Gao, Stanford University
9:20	Design and Performance Analysis of a ConvNeXt-Based Positioning System Using 5G-Integrated Multi-Radio Matching-Map Images Juil Jeon, Jung Ho Lee, Youngsu Cho, Mobility and Navigation Research Section, Electronics and Telecommunications Research Institute
9:43	Wheel-Mounted/GNSS Fusion with AI-Aided Position Updates Gal Versano and Itzik Klein, The Autonomous Navigation and Sensor Fusion Lab (ANSFL) The Hatter Department of Marine Technologies Charney School of Marine Sciences, University of Haifa
10:05-10:35, Break. Refreshments in Exhibit Hall
Alternate Presentation Alternate presentations may be given in-person at the conference if other authors are unable to present. Alternate Presenters will provide a pre-recorded presentation for on-demand viewing by all registered attendees.
1.	Efficient Satellite Acquisition for Initial Positioning Using Deep Learning - Graph Convolutional Networks Li-Hsiang Chu, Yin-Lien Lo, Yao-Cheng Lin, Shi-Xian Yang, AIROHA

On-Demand Presentation Pre-recorded presentations will become available for viewing by registered attendees on Wednesday, September 16.
	Set Transformer–Based GNSS Position Correction in Urban Environments Zhonghua Li, Xiaopeng Hou, Kun Fang, Jinxiang Wang, Beihang University; Jichao Dong, Aviation Data Communication Corporation

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