Conference paper
Terrain Mapping and Obstacle Detection Using Gaussian Processes
Automation and Control, Department of Electrical Engineering, Technical University of Denmark1
Department of Electrical Engineering, Technical University of Denmark2
Measurement and Instrumentation Systems, National Space Institute, Technical University of Denmark3
National Space Institute, Technical University of Denmark4
University of Southern Denmark5
In this paper we consider a probabilistic method for extracting terrain maps from a scene and use the information to detect potential navigation obstacles within it. The method uses Gaussian process regression (GPR) to predict an estimate function and its relative uncertainty. To test the new methods, we have arranged two setups: an artificial flat surface with an object in front of the sensors and an outdoor unstructured terrain.
Two sensor types have been used to determine the point cloud fed to the system: a 3D laser scanner and a stereo camera pair. The results from both sensor systems show that the estimated maps follow the terrain shape, while protrusions are identified and may be isolated as potential obstacles. Representing the data with a covariance function allows a dramatic reduction of the amount of data to process, while maintaining the statistical properties of the measured and interpolated features.
Language: | English |
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Year: | 2011 |
Pages: | 118-123 |
Proceedings: | 10th International Conference on Machine Learning and Applications (ICMLA 2011) |
ISBN: | 0769546072 , 1457721341 , 9780769546070 and 9781457721342 |
Types: | Conference paper |
DOI: | 10.1109/ICMLA.2011.137 |
3D laser scanner Cameras Estimation Gaussian Processes Gaussian process regression Gaussian processes Lasers Object detection Obstacle Detection Robotics Sensors Terrain Mapping Three dimensional displays artificial flat surface collision avoidance covariance analysis covariance function geophysical image processing navigation obstacle obstacle detection probabilistic method probability sensor system statistical properties stereo camera pair stereo image processing terrain mapping terrain shape