Abstract
High-speed navigation of autonomous Unmanned Ground Vehicles (UGVs) in rough unknown terrains requires the detection and identification of the terrain in order to make effective navigation decisions. This paper investigates a geometrical approach to identifying terrain based on its roughness using the terrain elevations from a point cloud generated using a 3D camera. This roughness, called the Roughness Index (RI), is used to identify different terrains by overlaying the terrain with a grid map and using the standard deviation of the point cloud elevations in each grid cell. The experimental testing and results of this terrain identification technique are presented as determined from field experiments using an experimental UGV test platform on rough outdoor terrains.
Highlights
Unmanned Ground Vehicles (UGVs) are becoming increasingly prevalent in everyday life as these complex systems are being used in applications including surveillance, military, law enforcement, industrial hauling, and search and rescue
This paper investigates the challenge of predictive terrain identification to perform navigation decisions for high-speed UGVs
This paper presented a geometrical terrain identification approach, the Roughness Index (RI), that identified terrain based on the roughness of the terrain using the point cloud of a 3D camera sensor
Summary
Unmanned Ground Vehicles (UGVs) are becoming increasingly prevalent in everyday life as these complex systems are being used in applications including surveillance, military, law enforcement, industrial hauling, and search and rescue. In order for these systems to navigate effectively in any environment they must be able to detect the terrain and react . In order to avoid such occurrences techniques for predicting the terrain the UGV will encounter are essential to allow for navigation decisions to be made in advance of the vehicle physically encountering the terrain. This paper investigates the challenge of predictive terrain identification to perform navigation decisions for high-speed UGVs
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