Teaching-Playback Navigation Without a Consistent Map
Naoki Akai*, Luis Yoichi Morales*, and Hiroshi Murase**
*Institute of Innovation for Future Society (MIRAI), Nagoya University
Furo-cho, Chikusa, Nagoya 464-8601, Japan
**Graduate School of Information Science, Nagoya University
Furo-cho, Chikusa, Nagoya 464-8603, Japan
This paper presents a teaching-playback navigation method that does not require a consistent map built using simultaneous localization and mapping (SLAM). Many open source projects related to autonomous navigation including SLAM have been made available recently; however, autonomous mobile robot navigation in large-scale environments is still difficult because it is difficult to build a consistent map. The navigation method presented in this paper uses several partial maps to represent an environment map. In other words, the complex mapping process is not necessary to begin autonomous navigation. In addition, the trajectory that the robot travels in the mapping phase can be directly used as a target path. As a result, teaching-playback autonomous navigation can be achieved without any off-line processes. We tested the navigation method using log data taken in the environment of the Tsukuba Challenge and the testing results show its performance. We provide source code for the navigation method, which includes modules required for autonomous navigation (https://github.com/NaokiAkai/AutoNavi).
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