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Point Cloud Mapping using Only Onboard Lidar in GNSS Denied and Dynamic Environments

Authors:
Misato Yamaji
Seiya Tanaka
Masafumi Hashimoto
Kazuhiko Takahashi

Keywords: point cloud map; simulatneous localization and mapping, distortion correction; NDT scan matching; graph SLAM; GNSS denied environment; dynamic environment

Abstract:
This paper presents a 3D point cloud mapping in Global Navigation Satellite Systems (GNSS) denied and dynamic outdoor environments using only a multilayer lidar (laser scanner) mounted on a vehicle. Distortion in scan data from the lidar is corrected by estimating the vehicle’s pose (3D positions and attitude angles) in a period shorter than the lidar scan period based on Normal Distributions Transform (NDT) scan matching and Extended Kalman Filter (EKF). The corrected scan data are mapped onto an elevation map; static and moving scan data, which are originated from static and moving objects, respectively, in the environments, are classified using the occupancy grid method. Only the static scan data are applied to generate a point cloud map using NDT-based Simultaneous Localization And Mapping (SLAM) and graph-based SLAM. Experimental results in a public road environment show the performance of the proposed method.

Pages: 43 to 49

Copyright: Copyright (c) IARIA, 2020

Publication date: February 23, 2020

Published in: conference

ISSN: 2308-4243

ISBN: 978-1-61208-771-9

Location: Lisbon, Portugal

Dates: from February 23, 2020 to February 27, 2020