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—Simultaneous Localization and Mapping (SLAM) consists in the concurrent construction of a representation of the environment (the map), and the estimation of the state of the robot moving within it. The SLAM community has made astonishing progress over the last 30 years, enabling large-scale real-world applications, and witnessing a steady transition of(More)
In this paper we show how to carry out robust place recognition using both near and far information provided by a stereo camera. Visual appearance is known to be very useful in place recognition tasks. In recent years, it has been shown that taking geometric information also into account further improves system robustness. Stereo visual systems provide 3D(More)
We report brain electrophysiological responses from 10- to 13-month-old Mexican infants while listening to native and foreign CV-syllable contrasts differing in Voice Onset Time (VOT). All infants showed normal auditory event-related potential (ERP) components. Our analyses showed ERP evidence that Mexican infants are capable of discriminating their native(More)
Odometry Semantic segm. Object 1 Object n. .. time Fig. 1: Proposed system in this paper. The semantic segmentation (SS) thread is used to improve the performance of any specific object detector which itself feedback to SS the detected object to improve the generic object class with this new evidence. Any number of different object detectors can be turned(More)
Vision-based localization on robots and vehicles remains unsolved when extreme appearance change and viewpoint change are present simultaneously. The current state of the art approaches to this challenge either deal with only one of these two problems; for example FAB-MAP (viewpoint invariance) or SeqSLAM (appearance-invariance), or use extensive training(More)
—We explore the capabilities of Auto-Encoders to fuse the information available from cameras and depth sensors, and to reconstruct missing data, for scene understanding tasks. In particular we consider three input modalities: RGB images; depth images; and semantic label information. We seek to generate complete scene segmentations and depth maps, given(More)
Advancements in robotic navigation, object search and exploration rest to a large extent on robust, efficient and more advanced semantic understanding of the surrounding environment. Since the choice of most relevant semantic information depends on the task, it is desirable to develop approaches which can be adopted for different tasks at hand and which(More)