Outdoor Autonomous Navigation Utilizing Proximity Points of 3D Pointcloud-Reference-Cited by-同舟云学术

Outdoor Autonomous Navigation Utilizing Proximity Points of 3D Pointcloud

Published:2020-12-20 Issue:6 Volume:32 Page:1183-1192
ISSN:1883-8049
Container-title:Journal of Robotics and Mechatronics
language:en
Short-container-title:J. Robot. Mechatron.

Author:

Tazaki Yuichi, ,Yokokohji Yasuyoshi

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.

Funder

Japan Society for the Promotion of Science

Publisher

Fuji Technology Press Ltd.

Subject

Electrical and Electronic Engineering,General Computer Science

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