High Definition Mapping for Inland Waterways: Fusing Precise GNSS and LiDAR

Abstract

Inland waterways transport (IWT) offers an eco-friendly and cost-effective alternative for transporting heavy and bulky shipments. However, navigation in waterways presents challenges due to limited maneuverability, shallow depths, and the need for accurate data. This seminar presents how to obtain High Definition (HD) maps for inland waterways with LiDAR (Light Detection and Ranging) technology. HD mapping combines satellite-based navigation with the SLAM (Simultaneous Localization and Mapping, a well-known problem in robotics) to provide precise mapping. Dr Medina will discuss the navigational and mapping requirements for waterborne applications and the methodology needed to succeed on this task. Then, the  proposed FAST-GLIO solution is introduced. FAST-GLIO extends the state-of-the-art FAST-LIO2 solution and combines it with Multi-GNSS antenna data to obtain a SLAM solution with sub-decimeter accuracy. Finally, the process of extracting bridge-related information from LiDAR-based HD maps will be showcased as exemplary application.

Speaker

Dr Daniel Medina, a member of the Institute of Electrical and Electronics Engineers (IEEE), received the PhD degree in Computer Sciences from Universidad Carlos III de Madrid (UC3M) in 2022. He is currently a research fellow at the Institute of Communications and Navigation of the German Aerospace Center (DLR), where he leads the Multi Sensor Systems research group, dedicated to the provision of perception and navigation solutions for waterborne transport applications. His research interests include statistical signal processing at large, robust filtering and estimation theory with applications to LiDAR perception and high precision satellite-based navigation. He is currently the elected Vice-Chair for the IEEE ITSS German Chapter. He is actively involved in the editorial and organizational processes of a number of conferences, such as IEEE ITSC 2019--2023, IV 2022, IEEE/ION PLANS 2023 or the ITSS R8 Chapters Meeting 2023.