A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sum and Difference Histograms for Texture Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimating uncertain spatial relationships in robotics
Autonomous robot vehicles
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
The 4th International Symposium on Experimental Robotics IV
A color projection for fast generic target tracking
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 1 - Volume 1
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Introduction to mathematical techniques in pattern recognition
Introduction to mathematical techniques in pattern recognition
A Vision System for Environment Representation: From Landscapes to Landmarks
MICAI '02 Proceedings of the Second Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Three-dimensional iterative closest point-based outdoor SLAM using terrain classification
Intelligent Service Robotics
A hybrid segmentation method applied to color images and 3d information
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
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This paper concerns the exploration of a natural environment by a mobile robot equipped with both a video camera and a range sensor (stereo or laser range finder); we focus on the interest of such a multisensory system to deal with the incremental construction of a global model of the environment and with the 3-D localization of the mobile robot. The 3-D segmentation of the range data provides a geometrical scene description: the regions issued from the segmentation step correspond either to the ground or to objects emerging from this ground (e.g. rocks, vegetations). The 3D boundaries of these regions can be projected on the video image, so that each one can be characterized and afterwards identified, by a probabilistic method, to obtain its nature (e.g. soil, rocks ...); the ground region can be over-segmented, adding visual information, such as the texture. During the robot motions, a slow and a fast processes are simultaneously executed; in the modelling process (currently 0.1Hz), a global landmark-based model is incrementally built and the robot situation can be estimated if some discriminant landmarks are selected from the detected objects in the range data; in the tracking process (currently 1Hz), selected landmarks are tracked in the visual data. The tracking results are used to simplify the matching between landmarks in the modelling process.