Lauro Jose Lyrio Junior

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Mapping and localization are fundamental problems in autonomous robotics. Autonomous robots need to know where they are in their area of operation to navigate through it and to perform activities of interest. In this paper, we propose an Image-Based Global Localization (VibGL) system that uses Virtual Generalizing Random Access Memory Weightless Neural(More)
Humans can easily memorize images of places and labels (road names, addresses, etc.) associated with them, as well as trajectories defined by sequences of images and corresponding positions. Later, they are able to remember places' labels and relative positions when seeing the same images again. In this work, we present an image-based mapping, global(More)
Virtual Generalizing Random Access Memory Weightless Neural Networks (VG-RAM WNN) is an effective machine learning technique that offers simple implementation and fast training and test. We examined the performance of VG-RAM WNN on binocular dense stereo matching using the Middlebury Stereo Datasets. Our experimental results showed that, even without(More)
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