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

Persson, Martin and Duckett, Tom and Lilienthal, Achim (2008) Fusion of aerial images and sensor data from a ground vehicle for improved semantic mapping. Robotics and autonomous systems, 56 (6). pp. 483-492. ISSN 0921-8890

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Fusion of Aerial Images and Sensor Data from a Ground Vehicle for Improved Semantic Mapping
journal article on semantic mapping by fusing information from ground and aerial images
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Full text URL: http://dx.doi.org/10.1016/j.robot.2008.03.002

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 omnidirectional 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.

Item Type:Article
Additional Information: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 omnidirectional 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.
Keywords:mobile robot, semantic mapping, aerial images
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
ID Code:1682
Deposited By: Tom Duckett
Deposited On:20 Nov 2008 16:33
Last Modified:13 Mar 2013 08:30

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