Real-time classification of ground from lidar data for helicopter navigation

Ferdinand Eisenkeil; Tobias Schafhitzel; Uwe Kühne; Oliver Deussen

doi:10.1117/12.2015681

23 May 2013 Real-time classification of ground from lidar data for helicopter navigation

Ferdinand Eisenkeil, Tobias Schafhitzel, Uwe Kühne, Oliver Deussen

Proceedings Volume 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII; 874512 (2013) https://doi.org/10.1117/12.2015681
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

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.

Citation Download Citation

Ferdinand Eisenkeil, Tobias Schafhitzel, Uwe Kühne, and Oliver Deussen "Real-time classification of ground from lidar data for helicopter navigation", Proc. SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, 874512 (23 May 2013); https://doi.org/10.1117/12.2015681

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KEYWORDS

Sensors

LIDAR

Visualization

Data modeling

Clouds

Image segmentation

Neodymium

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