Share Email Print

Proceedings Paper

Real-time classification of ground from lidar data for helicopter navigation
Author(s): Ferdinand Eisenkeil; Tobias Schafhitzel; Uwe Kühne; Oliver Deussen
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Helicopter pilots often have to deal with bad weather conditions and degraded views. Such situations may decrease the pilots' situational awareness significantly. The worst-case scenario would be a complete loss of visual reference during an off-field landing due to brownout or white out. In order to increase the pilots' situational awareness, helicopters nowadays are equipped with different sensors that are used to gather information about the terrain ahead of the helicopter. Synthetic vision systems are used to capture and classify sensor data and to visualize them on multifunctional displays or pilot's head up displays. This requires the input data to be a reliably classified into obstacles and ground. In this paper, we present a regularization-based terrain classifier. Regularization is a popular segmentation method in computer vision and used in active contours. For a real-time application scenario with LIDAR data, we developed an optimization that uses different levels of detail depending on the accuracy of the sensor. After a preprocessing step where points are removed that cannot be ground, the method fits a shape underneath the recorded point cloud. Once this shape is calculated, the points below this shape can be distinguished from elevated objects and are classified as ground. Finally, we demonstrate the quality of our segmentation approach by its application on operational flight recordings. This method builds a part of an entire synthetic vision processing chain, where the classified points are used to support the generation of a real-time synthetic view of the terrain as an assistance tool for the helicopter pilot.

Paper Details

Date Published: 23 May 2013
PDF: 14 pages
Proc. SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, 874512 (23 May 2013); doi: 10.1117/12.2015681
Show Author Affiliations
Ferdinand Eisenkeil, Univ. Konstanz (Germany)
Tobias Schafhitzel, Cassidian (Germany)
Uwe Kühne, Cassidian (Germany)
Oliver Deussen, Univ. Konstanz (Germany)

Published in SPIE Proceedings Vol. 8745:
Signal Processing, Sensor Fusion, and Target Recognition XXII
Ivan Kadar, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?