Using Intensity and Geometric Models of 3-D Point Cloud for Landmark Detection and Vehicle Localization
碩士 === 國立臺灣大學 === 電機工程學研究所 === 106 === In order to achieve full self-driving capability, localization is one of the basic function of future autonomous vehicle. Although GPS is widely used for localization, it suffers from bias generally. To reduce the bias, landmarks around the ego-vehicle can be u...
Main Authors: | Ti Lan, 藍迪 |
---|---|
Other Authors: | 連豊力 |
Format: | Others |
Language: | en_US |
Published: |
2018
|
Online Access: | http://ndltd.ncl.edu.tw/handle/857x48 |
Similar Items
-
Geometric Measurement Based on 3D Point Cloud
by: Sakontanut Srijan, et al.
Published: (2019) -
A Novel Simplification Method for 3D Geometric Point Cloud Based on the Importance of Point
by: Chunyang Ji, et al.
Published: (2019-01-01) -
Map-Matching-Based Cascade Landmark Detection and Vehicle Localization
by: Kyoungtaek Choi, et al.
Published: (2019-01-01) -
Rotation-Aware 3D Vehicle Detection From Point Cloud
by: Hyunjun Choi, et al.
Published: (2021-01-01) -
GEOMETRIC FEATURES AND THEIR RELEVANCE FOR 3D POINT CLOUD CLASSIFICATION
by: M. Weinmann, et al.
Published: (2017-05-01)