As walking machines have big advantages in moving through rough and undiscovered terrains compared to wheeled vehicles, a new problem raised: different terrains require different gaits. Thus, terrain classification plays an important role in autonomous outdoor navigation. Since computer vision is a rapidly growing field and inspired by biology, this thesis presents a vision based terrain classi...

The paper presents a method of terrain classification and path planning for unmanned ground vehicles. The terrain classification is done on imagery that is acquired from UAV (unmanned aerial vehicle) or satellite and is used for UGV (unmanned ground vehicle) path planning thus introducing collaboration capabilities to the system of two. The system complements the UGV on-board navigation system ...

A stereo-based terrain classification for traversability estimation of all terrains in offroad mobile robots is presented. The proposed method defines the roughness of the surrounding terrain for every single pixel in the image or point in a point cloud using surface normals and also explains how this is applied to all terrain by knowing the kinematics capability, mechanical constraints and siz...

The terrain classification is a very important subject to the all-terrain robotics community. The knowledge of the type of terrain allows a rover to deal with its environment more efficiently. The work presented in this paper shows that it is possible to differentiate terrains based on their aspects, using exteroceptive sensors, as well as based on their influence on the rover’s behavior, using...

Terrain perception greatly enhances the performance of robots, providing them with essential information on the nature of terrain being traversed. Several living beings in nature offer interesting inspirations which adopt different gait patterns according to nature of terrain. In this paper, we present a novel terrain perception system for our bioinspired robot, Scorpio, to classify the terrain...

1 Abstract— In this paper the Modified Fractal Signature (MFS) method is applied to real Synthetic Aperture Radar (SAR) images provided to our research group by SET 163 Working Group on SAR radar techniques. This method uses the 'blanket' technique to provide useful information for SAR image classification. It is based on the calculation of the volume of a 'blanket', corresponding to the image ...

For Autonomous Ground Vehicles, modelling of the terrain is important for predicting future behaviours and control options. Current terrain modelling is able to identify geometric hazards but has a limited ability to identify complex terrain characteristics. This paper presents a method for segmenting and classifying terrain types based on range data to establish a geometric model of the terrai...

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In this thesis we present a comparison of multiple approaches to visual terrain classification for outdoor mobile robots based on local features. For this purpose, we put a camera on a mobile robot and use it to capture images which are then analyzed to recognize the terrains present in these images. There are two sets of approaches that we use to classify terrains. The first is based on greysc...