Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Ignacio Vizzo"'
Publikováno v:
Sensors, Vol 22, Iss 3, p 1296 (2022)
Mapping is a crucial task in robotics and a fundamental building block of most mobile systems deployed in the real world. Robots use different environment representations depending on their task and sensor setup. This paper showcases a practical appr
Externí odkaz:
https://doaj.org/article/d38fa5945ba34bf78e2861ebbcd58af6
Autor:
Federico Magistri, Elias Marks, Sumanth Nagulavancha, Ignacio Vizzo, Thomas Labe, Jens Behley, Michael Halstead, Chris McCool, Cyrill Stachniss
Publikováno v:
IEEE Robotics and Automation Letters. 7:10120-10127
Autor:
Ignacio Vizzo Vizzo, Benedikt Mersch, Rodrigo Marcuzzi, Louis Wiesmann, Jens Behley, Cyrill Stachniss
Publikováno v:
IEEE Robotics and Automation Letters. 7:8534-8541
Autor:
Louis Wiesmann, Tiziano Guadagnino, Ignacio Vizzo, Giorgio Grisetti, Jens Behley, Cyrill Stachniss
Publikováno v:
IEEE Robotics and Automation Letters. 7:6327-6334
Autor:
Xieyuanli Chen, Benedikt Mersch, Lucas Nunes, Rodrigo Marcuzzi, Ignacio Vizzo, Jens Behley, Cyrill Stachniss
Publikováno v:
IEEE Robotics and Automation Letters. 7:6107-6114
Understanding the scene is key for autonomously navigating vehicles and the ability to segment the surroundings online into moving and non-moving objects is a central ingredient for this task. Often, deep learning-based methods are used to perform mo
Publikováno v:
IEEE Robotics and Automation Letters. 7:1550-1557
A key challenge for autonomous vehicles is to navigate in unseen dynamic environments. Separating moving objects from static ones is essential for navigation, pose estimation, and understanding how other traffic participants are likely to move in the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7dafce4e87ce335c13301c473493fec8
http://arxiv.org/abs/2206.04129
http://arxiv.org/abs/2206.04129
Akademický článek
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Publikováno v:
ICRA
Robust and accurate, map-based localization is crucial for autonomous mobile systems. In this paper, we exploit range images generated from 3D LiDAR scans to address the problem of localizing mobile robots or autonomous cars in a map of a large-scale
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1c6a94674c3b3d6e18c3b9780a65769
Publikováno v:
IROS
Perception in autonomous vehicles is often carried out through a suite of different sensing modalities. Given the massive amount of openly available labeled RGB data and the advent of high-quality deep learning algorithms for image-based recognition,