JRM Vol.29 No.4 pp. 639-648
doi: 10.20965/jrm.2017.p0639


Development of Autonomous Navigation System Using 3D Map with Geometric and Semantic Information

Yoshihiro Aotani, Takashi Ienaga, Noriaki Machinaka, Yudai Sadakuni, Ryota Yamazaki, Yuki Hosoda, Ryota Sawahashi, and Yoji Kuroda

Meiji University
1-1-1 Higashimita, Tama-ku, Kawasaki, Kanagawa 214-8571, Japan

March 1, 2017
June 22, 2017
August 20, 2017
autonomous navigation robot, 3D semantic map, localization

This paper presents an autonomous navigation system. Our system is based on an accurate 3D map, which includes “geometric information” (e.g., curb, wall, street tree) and “semantic information” (e.g., sidewalk, roadway, crosswalk) extracted by environmental recognition. By using the semantic map, we can obtain the suitable area to keep away from undesired places. Furthermore, by comparing the map with real-time 3D geometric information from LIDAR, we obtain the robot position. To show the effectiveness of our system, we conduct a 3D semantic map construction experiment and driving test. The experiment results show that the proposed system enables accurate and highly reproducible localization and stable autonomous mobility.

3D map with geometric and semantic information

3D map with geometric and semantic information

Cite this article as:
Y. Aotani, T. Ienaga, N. Machinaka, Y. Sadakuni, R. Yamazaki, Y. Hosoda, R. Sawahashi, and Y. Kuroda, “Development of Autonomous Navigation System Using 3D Map with Geometric and Semantic Information,” J. Robot. Mechatron., Vol.29 No.4, pp. 639-648, 2017.
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