Autonomous Navigation through Data Association of Cadastral Map and Sensor Information for Personal Mobility Robot

Abstract

For autonomous navigation of so-called personal mobility robots, we have proposed a localization method using an existing cadastral map. As a result, a personal mobility robot was enabled to move toward a destination autonomously without building the environmental map beforehand through SLAM. However, obstacles in the environment are not included in the map. Therefore, the robot can not avoid obstacles ahead. For this problem, we allow the robot to reflect the obstacles observed by 3D LiDAR in the map through data association. Through the data association of the cadastral map and sensor information, the robot avoids the obstacles by repeatedly planning the path in the map. In the experiments, we show that the robot is able to move toward a goal destination autonomously by avoiding obstacles.