Development of Edge-Node Map Based Navigation System Without Requirement of Prior Sensor Data Collection
Author(s) -
Kazuki Takahashi,
Jumpei Arima,
Toshihiro Hayata,
Yoshitaka Nagai,
Naoya Sugiura,
Ren Fukatsu,
Wataru Yoshiuchi,
Yoji KURODA
Publication year - 2020
Publication title -
journal of robotics and mechatronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.257
H-Index - 19
eISSN - 1883-8049
pISSN - 0915-3942
DOI - 10.20965/jrm.2020.p1112
Subject(s) - map matching , computer science , computer vision , occupancy grid mapping , robot , point cloud , enhanced data rates for gsm evolution , artificial intelligence , navigation system , grid reference , mobile robot , node (physics) , mobile robot navigation , trajectory , dead reckoning , real time computing , global positioning system , robot control , engineering , telecommunications , physics , structural engineering , astronomy
In this study, a novel framework for autonomous robot navigation system is proposed. The navigation system uses an edge-node map, which is easily created from electronic maps. Unlike a general self-localization method using an occupancy grid map or a 3D point cloud map, there is no need to run the robot in the target environment in advance to collect sensor data. In this system, the internal sensor is mainly used for self-localization. Assuming that the robot is running on the road, the position of the robot is estimated by associating the robot’s travel trajectory with the edge. In addition, node arrival determination is performed using branch point information obtained from the edge-node map. Because this system does not use map matching, robust self-localization is possible, even in a dynamic environment.
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