We present a novel method for visual mapping and localization autonomous vehicles, by extracting, modeling, optimizing semantic road elements. Specifically, our integrates cascaded deep models to detect standardized elements instead of traditional point features, seek improved pose accuracy map representation compactness. To utilize the structural we model lights signs their representative keyp...

Many works in the recent literature introduce semantic mapping methods that use CNNs (Convolutional Neural Networks) to recognize properties images. The types of (eg.: room size, place category, and objects) their classes kitchen bathroom, for category) are usually predefined restricted a specific task. Thus, all visual data acquired processed during construction maps lost only recognized remai...

In an endeavor to study natural systems at multiple spatial and taxonomic resolutions, there is urgent need for automated, high-throughput frameworks that can handle plethora of information. The coalescence remote-sensing, computer-vision, deep-learning elicits a new era in ecological research. However, complex systems, such as marine-benthic habitats, key processes still remain enigmatic due t...

In the current COVID-19 pandemic, people expect to use robots replace humans complete disinfection work in public places. Since different regions environment have risks, addition conventional SLAM capability, robot also needs be able recognize and distinguish objects scene customizable tasks. this paper, we propose a LiDAR-based semantic mapping system that can used for robotic By using prior i...

Performing collaborative semantic mapping is a critical challenge for cooperative robots to enhance their comprehensive contextual understanding of the surroundings. This article bridges gap between advances in geometry that relies on pure information fusion, and single robot focuses integrating continuous raw sensor data. In this article, novel hierarchical probabilistic framework proposed, wh...

Modeling domain knowledge as Linked Data is not straightforward for data publishers, because they are domain experts and not Semantic Web specialists. Most approaches that map data to its semantic representation still require users to have knowledge of the underlying implementations, as the mapping definitions remained, so far, tight to their execution. Defining mapping languages enables to dec...