Paper Info
Title
Outdoor Autonomous Navigation Utilizing Proximity Points Of 3d Pointcloud
Abstract
In this paper, an autonomous navigation method that utilizes proximity points of 3D range data is proposed for use in mobile robots. Some useful geometric properties of proximity points are derived, and a computationally efficient algorithm for extracting such points from 3D pointclouds is presented. Unlike previously proposed keypoints, the proximity point does not require any computationally expensive analysis of the local curvature, and is useful for detecting reliable keypoints in an environment where objects with definite curvatures such as edges and flat surfaces are scarce. Moreover, a particle-filter-based self-localization method that uses proximity points for a similarity measure of observation is presented. The proposed method was implemented in a real mobile robot system, and its performance was tested in an outdoor experiment conducted during Nakanoshima Challenge 2019.
Year
DOI
Venue
2020
10.20965/jrm.2020.p1183
JOURNAL OF ROBOTICS AND MECHATRONICS
Keywords
DocType
Volume
mobile robot, proximal points, 3D LiDAR, self-localization
Journal
32
Issue
ISSN
Citations 
6
0915-3942
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Yuichi Tazaki17610.74
Yasuyoshi Yokokohji2847109.34