6 accepted papers
Global localization is an essential ingredient for autonomous mobile robots. However, existing global localization systems primarily rely on Global Navigation Satellite System (GNSS), infrastructures, or visual/LiDAR-based place recognition, which suffer from enclosed/semi-enclosed GNSS-denied envir
In recent years, infrastructure-based localization methods have achieved significant progress thanks to their reliable and drift-free localization capability. However, the preinstalled infrastructures suffer from inflexibilities and high maintenance costs. This poses an interesting problem of how to…
As a new sensor, 4D radar (x, y, z, velocity) has great potential for V2X, due to its 3D point cloud, direct doppler velocity output, long distance ranging, low-cost, and more importantly, robust perception in all weathers. However, the extrinsic calibration of multiple long baseline 4D radars is ra…
Accurate global localization is an essential ingredient for autonomous mobile robots (AMRs) operating in enclosed or partially enclosed repetitive environments (e.g., office corridors, industrial warehouses, transportation centers). In such environments, the Global Navigation Satellite System (GNSS)…
In V2X (Vehicle-to-Everything), one important work is to extrinsically calibrate multiple 3D LiDARs, which are mounted with a long baseline and large viewpoint-difference at the road-side. Current solutions either require a specific target being set up (e.g., a sphere), or require specific features…
Multi-LiDAR system is an important part of V2X (Vehicle to Everything) to enhance the perception information for unmanned vehicles. To fuse the information from multiple 3D LiDARs, accurate extrinsic calibration between the LiDARs is essential. However, the existing multi-LiDAR calibration methods m…