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In this paper, an algorithm to segment 3D points in dense range maps generated from the fusion of a single optical camera and a multiple emitter/detector laser range finder is presented. The camera image and laser range data are fused using a Markov Random Field to estimate a 3D point corresponding to each image pixel. The textured 3D dense point cloud is segmented based on evidence of a boundary...
This paper addresses the problem of map matching for robot navigation. We propose 3D map matching by a modified RANSAC algorithm for line edges acquired by a stereo camera. 3D map-matching has proven to be successful in indoor and outdoor environments.
Accurate localization of landmarks in the vicinity of a robot is a first step towards solving the SLAM problem. In this work, we propose algorithms to accurately estimate the 3D location of the landmarks from the robot only from a single image taken from its on board camera. Our approach differs from previous efforts in this domain in that it first reconstructs accurately the 3D environment from a...
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