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Probabilistic terrain classification in unstructured environments
Robotics and Autonomous Systems, 2013Autonomous navigation in unstructured environments is a complex task and an active area of research in mobile robotics. Unlike urban areas with lanes, road signs, and maps, the environment around our robot is unknown and unstructured. Such an environment requires careful examination as it is random, continuous, and the number of perceptions and ...
Marcel Häselich +4 more
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Terrain Classification from an Aerial Perspective
2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2020Terrain knowledge around unmanned ground vehicles (UGVs) is vital for autonomous navigation. Having global understanding of the surroundings of UGVs is important, although the field of view from UGVs is very limited. Thus, we utilize an aerial vehicle to provide a large terrain map from sequential aerial images.
Sivert Frang Lunsaeter +3 more
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Terrain Image Classification with SVM
2013Remote sensing is an important tool in a variety of scientific researches which can help to study and solve many practical environmental problems. Classification of remote sensing image, however, is usually complex in many respects that a lot of different ground objects show mixture distributions in space and change with temporal variations. Therefore,
Mu-Song Chen, Chi-Pan Hwang, Tze-Yee Ho
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Terrain Classification by Sequential Algorithms
1991This paper presents several strategies developed for classification of terrain regions, based on the SPRT algorithm (Sequential Probability Ratio Test [1]). The SPRT algorithm is considered to be appropriate to two-class-classification and will be extended by the introduced strategies for resolution of multi-class-classification problems.
Y. Huang, Piero Zamperoni
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Terrain contact modeling and classification for ATVs
2016 IEEE International Conference on Robotics and Automation (ICRA), 2016We present a method for estimating the contact event between sensor-free active subtracks, named flippers, of an articulated tracked vehicle (ATV) and the terrain surface. The main idea is to consider both the moving base link and unexpected collisions dynamics as disturbances of the flipper dynamics.
GIANNI, Mario +3 more
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Terrain Classification Using Clustering Algorithms
Third International Conference on Natural Computation (ICNC 2007), 2007Texture analysis has been efficiently utilized in the area of terrain classification. The widely used co-occurrence features have been reported most effective for this application. Since the number of co-occurrence features is very high, a terrain classifier based on co-occurrence features should deal with high dimensionality problem.
Dong-Min Woo +4 more
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Single-parameter terrain classification for terrain following
Journal of Aircraft, 1980To avoid excessive simulation of terrain following flights, it is desirable to have a method to classify terrain with regard to its suitability for terrain following. Analytical expressions for the probability of crashing (Pc) for a terrain-following missile indicate that the variances oe and ae, of missile altitude error and error rate, respectively ...
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Speed Independent Terrain Classification
2006 Proceeding of the Thrity-Eighth Southeastern Symposium on System Theory, 2006Today's autonomous vehicles operate within an increasingly larger set of environments compared to earlier research in which environments were more controlled. In particular, unmanned ground vehicles (UGVs) must be able to travel on whatever terrain the mission offers, including sand, mud, or even snow.
E.M. DuPont, R.G. Roberts, C.A. Moore
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Performance analysis and terrain classification for a legged robot over rough terrain
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012Minimally actuated millirobotic crawlers navigate unreliably over uneven terrain-even when designed with inherent stability-mostly because of manufacturing variabilities and a lack of good models for ground interaction. In this paper, we investigate the performance of a legged robot as it traverses three distinct rough terrains: tile, carpet, and ...
Fernando Garcia Bermudez +4 more
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SVMs for Vibration-Based Terrain Classification
2007When an outdoor mobile robot traverses different types of ground surfaces, different types of vibrations are induced in the body of the robot. These vibrations can be used to learn a discrimination between different surfaces and to classify the current terrain. Recently, we presented a method that uses Support Vector Machines for classification, and we
Christian Weiss +2 more
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