An important challenge in outdoor mobile robotic perception is maintaining terrain classification performance throughout the extremely variable conditions that we may wish a robot to operate under. Outdoor robots operate in a series of “environments” that consist of diverse terrain, vegetation, weather, and lighting conditions. A physical robot does not randomly jump between environments; typic...

In this paper, techniques for an automated extraction, classification and modelling of 3D objects will be presented. They use solely laserscanning derived digital elevation models as data basis. Trees, buildings and terrain objects are detected and classified. Firstly, a special region growing algorithm segments 3D objects on the terrain surface. Object specific features are extracted inside th...

Autonomous robot navigation in unstructured outdoor environments is a challenging area of active research and is currently unsolved. The navigation task requires identifying safe, traversable paths that allow the robot to progress toward a goal while avoiding obstacles. Stereo is an effective tool in the near field, but used alone leads to a common failure mode in autonomous navigation in which...

Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with percepti...

We address the problem of learning to recognize traversable terrain in an unstructured outdoor environment a core functionality for autonomous robot navigation. The traversability learning problem is challenging for two reasons. First, while general-purpose sensing can be used to identify the existence of particular terrain features such as vegetation and sloping ground, the traversability of t...

For polarimetric SAR (PolSAR) image classification, it is a challenge to classify the aggregated terrain types, such as the urban area, into semantic homogenous regions due to sharp bright-dark variations in intensity. The aggregated terrain type is formulated by the similar ground objects aggregated together. In this paper, a polarimetric hierarchical semantic model (PHSM) is firstly proposed ...

Autonomous mobile robots need to adapt their behavior to the terrain over which they drive, and to predict the traversability of the terrain so that they can effectively plan their paths. Such robots usually make use of a set of sensors to investigate the terrain around them and build up an internal representation that enable them to navigate. This paper addresses the question of how to use sen...

Unmanned Ground Vehicle’s (UGV) have to cope with the most complex range of dynamic and variable obstacles and therefore need to be highly intelligent in order to cope with navigating in such a cluttered environment. When traversing over different terrains (whether it is a UGV or a commercial manned vehicle) different drive styles and configuration settings need to be selected in order to trave...