Autonomous robot navigation with the capability to perceive the surrounding environment of the robot enhances the efficiency and safety of the robot. A technique for terrain classification for traversability assessment of mobile robot navigating in natural terrain by extracting the textural features from visual sensing of terrain data using co-occurrence matrix is presented in this paper. The a...

Photogrammetric UAV sees a surge in use for high-resolution mapping, but its use to map terrain under dense vegetation cover remains challenging due to a lack of exposed ground surfaces. This paper presents a novel object-oriented classification ensemble algorithm to leverage height, texture and contextual information of UAV data to improve landscape classification and terrain estimation. Its i...

The ability to recognize the encountered terrain is an essential part of any terrain-dependent control system designed for mobile robots. Terrains such as sand and gravel make vehicle mobility more difficult and thus reduce vehicle performance. To alleviate this problem the vehicle control system can be tuned for maximum speeds, turning angles, accelerations and other conditions to help adapt t...

This paper presents two techniques to detect and classify navigable terrain in complex 3D environments. The first method is a low level on-line mechanism aimed at detecting obstacles and holes at a fast frame rate using a time-of-flight camera as the main sensor. The second technique is a high-level off-line classification mechanism that learns traversable regions from larger 3D point clouds ac...

Automated terrain classification for electric powered wheelchairs (EPWs) has two primary motivations. First, certain terrains (e.g., sand and gravel) make wheelchair mobility more difficult. To alleviate this problem the wheelchair control system can be manually tuned for maximum speeds and/or accelerations to help adapt to various terrains. Terrain classification can then be used to automate t...

The Demo III program has as its primary focus the development of autonomous mobility for a small rugged cross country vehicle. Enabling vision based terrain perception technology for classification of scene geometry and material is currently under development at JPL. In this paper we report recent progress on both stereo-based obstacle detection and terrain cover colorbased classification. Our ...

Todays unmanned ground vehicles (UGV) must operate in and increasingly general set of circumstances. These UGV’s must be able to provide stable controlability on whatever terrain they may encounter. A UGV might begin a assignment on asphalt but quickly be required to negotiate sand, mud, or even snow. Traversing these terrains can affect the performance and controllability of the vehicle. Like ...

Terrain detection and classification are critical elements for NASA mission preparations and landing site selection. In this paper, we have investigated several image features and classifiers for lunar terrain classification. The proposed histogram of gradient orientation effectively discerns the characteristics of various terrain types. We further develop an open-source Lunar Image Labeling To...

Due to the varying terrain conditions in outdoor scenarios the kinematics of mobile robots is much more complex compared to indoor environments. In this paper we present an approach to predict future positions of mobile robots which considers the current terrain. Our approach uses Gaussian process regression (GPR) models to estimate future robot positions. An unscented Kalman filter (UKF) is us...

Terrain physical characteristics can have a significant impact on passenger vehicle handling, ride quality, and stability. Here, an algorithm is presented to classify terrain using a single suspensionmounted accelerometer. The algorithm passes a measured acceleration signal through a dynamic vehicle model to estimate the terrain profile, and then extracts spatial frequency components of this es...