3D LIDAR Based Vehicle Localization using Vertical Structure Landmark in Urban Road

Im, Jun-Hyuck; Kim, Kyu‐Won; Jee, Gyu-In

doi:10.33012/2017.15156

Cited by 1 publication

(1 citation statement)

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“…Soloviev has demonstrated that 2D line LIDAR scan matching can be paired with GPS for navigating in environments where GPS navigation alone can be difficult . More recently, these sensors have been combined in Simultaneous Localization and Mapping (SLAM) approaches, most commonly developed for indoor and GPS‐denied navigation. While SLAM techniques alone have the capability of allowing users to navigate by observing environmental changes, long term positioning often suffers from drift and biases.…”

Section: Related Workmentioning

confidence: 99%

Probabilistic graphical fusion of LiDAR, GPS, and 3D building maps for urban UAV navigation

Chen

Gao

2019

NAVIGATION

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Because of the recent interest in unmanned air vehicle (UAV) commercialization, there is a great need for navigation algorithms that provide accurate and robust positioning in urban environments that are often Global Positioning Systems (GPS) challenged or denied. In this paper, we present a probabilistic graph-based navigation algorithm resilient to GPS errors. Fusing GPS pseudorange and Light Detection and Ranging (LiDAR) odometry measurements with 3D building maps, we apply a batch estimation approach to generate a robust trajectory estimate and maps of the surrounding environment. We then leverage the maps to locate potential sources of GPS multipath and mitigate the effects of degraded pseudorange measurements on the trajectory estimate. We experimentally validate our results with flight tests conducted in GPS-challenged and GPS-denied environments.

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Section: Related Workmentioning

confidence: 99%