City-Scale Grid-Topological Hybrid Maps for Autonomous Mobile Robot Navigation in Urban Area

被引:7
|
作者
Niijima, Shun [1 ,2 ]
Umeyama, Ryusuke [1 ,2 ]
Sasaki, Yoko [2 ]
Mizoguchi, Hiroshi [1 ,2 ]
机构
[1] Tokyo Univ Sci, Dept Mech Engn, 2641 Yamazaki, Noda, Chiba 2788510, Japan
[2] Natl Inst Adv Ind Sci & Technol, Koto Ku, 2-3-26 Aomi, Tokyo 1350064, Japan
关键词
OPENSTREETMAP; ENVIRONMENTS; ALGORITHM; SLAM;
D O I
10.1109/IROS45743.2020.9340990
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Extensive city navigation remains an unresolved problem for autonomous mobile robots that share space with pedestrians. This paper proposes a configuration for a navigation map that expresses urban structures and an autonomous navigation scheme that uses the configuration. The proposed map configuration is a hybrid structure of multiple 2D grid maps and a topological graph. The occupancy grids for path planning are automatically converted from a given 3D point cloud and publicly available maps. The topological graph enables the connections between the subdivisions of occupancy grids to be managed and are used for route planning. This hybrid configuration can embed various urban structures automatically and is applicable to a wide range of autonomous navigation tasks. We evaluated the map by generating the proposed navigation map in real city and performing path planning using on the hybrid map. Experimental results demonstrated that the hybrid map can reduce the planning time and memory usage compared to the conventional single 2D grid map based path planning.
引用
收藏
页码:2065 / 2071
页数:7
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    Shan, Yunxiao
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  • [27] Enhanced Geometric Map: a 2D&3D Hybrid City Model of Large Scale Urban Environment for Robot Navigation
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  • [29] Hybrid control for autonomous mobile robot navigation using neural network based behavior modules and environment classification
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