Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Tiberiu T. Cocias"'
Autor:
Andrea Margheri, Federico Lombardi, Sorin Mihai Grigorescu, Bogdan Trasnea, Tiberiu T. Cocias, Leonardo Aniello
Publikováno v:
Sensors, Vol 20, Iss 5450, p 5450 (2020)
Sensors
Volume 20
Issue 19
Sensors (Basel, Switzerland)
Sensors
Volume 20
Issue 19
Sensors (Basel, Switzerland)
Self-driving cars and autonomous vehicles are revolutionizing the automotive sector, shaping the future of mobility altogether. Although the integration of novel technologies such as Artificial Intelligence (AI) and Cloud/Edge computing provides gold
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee88c94821acc9a834ee86785dde9a2c
http://arxiv.org/abs/2009.11722
http://arxiv.org/abs/2009.11722
In this paper, we propose an object reconstruction apparatus that uses the so-called Generic Primitives (GP) to complete shapes. A GP is a 3D point cloud depicting a generalized shape of a class of objects. To reconstruct the objects in a scene we fi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b80707187a2d315992952ee371dd7b2
http://arxiv.org/abs/2006.02098
http://arxiv.org/abs/2006.02098
Autonomous vehicles are controlled today either based on sequences of decoupled perception-planning-action operations, either based on End2End or Deep Reinforcement Learning (DRL) systems. Current deep learning solutions for autonomous driving are su
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3d765fe3e973c86dec56cfabb5e33439
http://arxiv.org/abs/1906.10971
http://arxiv.org/abs/1906.10971
Autor:
Sorin Mihai Grigorescu, Andrei Vasilcoi, Bogdan Trasnea, Tiberiu T. Cocias, Liviu A. Marina, Florin Moldoveanu
Publikováno v:
IRC
Grid maps obtained from fused sensory information are nowadays among the most popular approaches for motion planning for autonomous driving cars. In this paper, we introduce Deep Grid Net (DGN), a deep learning (DL) system designed for understanding
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6c5ab000a6fb8baaac582de1f3cfe072
https://doi.org/10.1109/irc.2019.00073
https://doi.org/10.1109/irc.2019.00073
The last decade witnessed increasingly rapid progress in self-driving vehicle technology, mainly backed up by advances in the area of deep learning and artificial intelligence. The objective of this paper is to survey the current state-of-the-art on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::678b66128b3b533c94e3becbc4e211c2
Publikováno v:
Robotics and Autonomous Systems. 61:960-972
In this paper, a simultaneous 3D volumetric segmentation and reconstruction method, based on the so-called Generic Fitted Shapes (GFS) is proposed. The aim of this work is to cope with the lack of volumetric information encountered in visually contro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a12f5b0106af75ace1784c3d6d3697c4
https://doi.org/10.1016/j.robot.2013.04.020
https://doi.org/10.1016/j.robot.2013.04.020
Publikováno v:
Robotics and Autonomous Systems. 59:899-909
Successful path planning and object manipulation in service robotics applications rely both on a good estimation of the robot's position and orientation (pose) in the environment, as well as on a reliable understanding of the visualized scene. In thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e32a4d64016eff32d8381fb40946e48d
https://doi.org/10.1016/j.robot.2011.07.005
https://doi.org/10.1016/j.robot.2011.07.005
Publikováno v:
Studies in Computational Intelligence ISBN: 9783319032054
In this paper, a markerless approach for estimating the pose of a robot using only 3D visual information is presented. As opposite to traditional methods, our approach makes use of 3D features solely for determining a relative position between the im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d8aa6cdedab30ac8030ec26715939e3f
https://doi.org/10.1007/978-3-319-03206-1_15
https://doi.org/10.1007/978-3-319-03206-1_15
Publikováno v:
Communications in Computer and Information Science ISBN: 9783642382406
VISIGRAPP (Selected Papers)
VISIGRAPP (Selected Papers)
This paper presents a method for surface estimation applied on single viewed objects. Its goal is to deliver reliable 3D scene information to service robotics application for appropriate grasp and manipulation actions. The core of the approach is to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77805c570cad5358aa62a2114ae239ca
https://doi.org/10.1007/978-3-642-38241-3_25
https://doi.org/10.1007/978-3-642-38241-3_25
Publikováno v:
2012 13th International Conference on Optimization of Electrical and Electronic Equipment (OPTIM).
A method for approximating an object's surface defined by 2.5D data is presented. The goal is to determine a compact volume which may be subjected to manipulation actions under a proper grasp planning. The object volume is obtained based on a union o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9c8ade537f554023f4afd14e3f4bde0
https://doi.org/10.1109/optim.2012.6231780
https://doi.org/10.1109/optim.2012.6231780