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Estimation of scale and slope information for structure from motion-based 3D map

Yuyang Shao, Yonghoon Ji, Hiromitsu Fujii, Keiji Nagatani, Atsushi Yamashita, Hajime Asama

Year
2017
Citations
3

Abstract

Dealing with natural disasters, such as debris flow, typically involves teleoperation of an unmanned robot. Three-dimensional (3D) map information of an environment is especially useful for teleoperating the unmanned robot system to perform unmanned construction and auto-investigation. Recently, structure from motion (SfM) using an unmanned aerial vehicle (UAV) equipped with monocular cameras has been proposed as a general method to build 3D map information. However, absolute slope and scale information for the built 3D map cannot be obtained when applying general SfM technology without the deployment of ground control points (GCPs). Therefore, we propose a method that can recover absolute slope and scale information for a 3D map. To this end, we apply sensor fusion technology that combines inertial measurement unit (IMU) data from an unmanned ground vehicle (UGV) and image data from the camera mounted on a UAV. Experimental results show that our estimation scheme is able to successfully represent the slope and scale information along with the 3D map.

Keywords

Inertial measurement unitComputer visionArtificial intelligenceComputer scienceStructure from motionTeleoperationRobotScale (ratio)MonocularMotion estimation

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