Fusion of aerial images and sensor data from a ground vehicle for improved semantic mapping

Authors:
Martin Persson;Tom Duckett;Achim J. Lilienthal
Affiliations:
Center for Applied Autonomous Sensor Systems, Department of Technology, Örebro University, Örebro, Sweden;Department of Computing and Informatics, University of Lincoln, Lincoln, UK;Center for Applied Autonomous Sensor Systems, Department of Technology, Örebro University, Örebro, Sweden
Venue:
Robotics and Autonomous Systems
Year:
2008

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Abstract

This work investigates the use of semantic information to link ground level occupancy maps and aerial images. A ground level semantic map, which shows open ground and indicates the probability of cells being occupied by walls of buildings, is obtained by a mobile robot equipped with an omni-directional camera, GPS and a laser range finder. This semantic information is used for local and global segmentation of an aerial image. The result is a map where the semantic information has been extended beyond the range of the robot sensors and predicts where the mobile robot can find buildings and potentially driveable ground.