Virtual Occupancy Grid Map for Submap-based Pose Graph SLAM and Planning in 3D Environments

被引：0

作者：

Ho, Bing-Jui ^{[1
]}

Sodhi, Paloma ^{[1
]}

Teixeira, Pedro ^{[2
]}

Hsiao, Ming ^{[1
]}

Kusnur, Tushar ^{[3
]}

Kaess, Michael ^{[1
]}

机构：

[1] Carnegie Mellon Univ, Inst Robot, Pittsburgh, PA 15213 USA

[2] MIT, Comp Sci & Artificial Intelligence Lab, 77 Massachusetts Ave, Cambridge, MA 02139 USA

[3] BITS Pilani KK Birla Goa Campus, Dept Elect & Elect Engn, Sancoale, Goa, India

来源：

2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) | 2018年

基金：

美国国家科学基金会;

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we propose a mapping approach that constructs a globally deformable virtual occupancy grid map (VOG-map) based on local submaps. Such a representation allows pose graph SLAM systems to correct globally accumulated drift via loop closures while maintaining free space information for the purpose of path planning. We demonstrate use of such a representation for implementing an underwater SLAM system in which the robot actively plans paths to generate accurate 3D scene reconstructions. We evaluate performance on simulated as well as real-world experiments. Our work furthers capabilities of mobile robots actively mapping and exploring unstructured, three dimensional environments.

引用

页码：2175 / 2182

页数：8

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