Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Claudio Fantacci"'
Autor:
Nicola A. Piga, Fabrizio Bottarel, Claudio Fantacci, Giulia Vezzani, Ugo Pattacini, Lorenzo Natale
Publikováno v:
Frontiers in Robotics and AI, Vol 8 (2021)
Tracking the 6D pose and velocity of objects represents a fundamental requirement for modern robotics manipulation tasks. This paper proposes a 6D object pose tracking algorithm, called MaskUKF, that combines deep object segmentation networks and dep
Externí odkaz:
https://doaj.org/article/b9c3c1d57a4f434b8b795326a9fa5fda
Autor:
Enrico Villagrossi, Alessandro Ardesi, Claudio Fantacci, Marco Maggiali, Daniele Pucci, Silvio Traversaro, Ines Sorrentino, Andrea Polo, Angelo Rendiniello, Lorenzo Natale, Prajval Kumar Murali
Publikováno v:
ICRA
Hand-eye calibration of laser profile sensors is the process of extracting the homogeneous transformation between the laser profile sensor frame and the end-effector frame of a robot in order to express the data extracted by the sensor in the robot's
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13d6cc27bb69ccc9f7eeef28669149fb
http://arxiv.org/abs/2103.11981
http://arxiv.org/abs/2103.11981
Publikováno v:
IEEE Signal Processing Letters. 25:640-644
This letter proposes analytical expressions for the fusion of certain classes of labeled multiobject densities via Kullback–Leibler averaging. Specifically, we provide analytical fusion rules for the labeled multi-Bernoulli and marginalized $\delta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::069554916c21d6c66ef7f1ace9abf804
https://doi.org/10.1109/lsp.2018.2811750
https://doi.org/10.1109/lsp.2018.2811750
Autor:
Benedetto Allotta, Riccardo Costanzi, Claudio Fantacci, F. Di Corato, Enrico Meli, Luigi Chisci, Alessandro Ridolfi, Davide Fenucci, Andrea Caiti
Publikováno v:
Mechatronics. 39:185-195
Robust and performing navigation systems for Autonomous Underwater Vehicles (AUVs) play a discriminant role towards the success of complex underwater missions involving one or more AUVs. The quality of the filtering algorithm for the estimation of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::618e787366c909f466740d277a29f7e3
https://doi.org/10.1016/j.mechatronics.2016.05.007
https://doi.org/10.1016/j.mechatronics.2016.05.007
Publikováno v:
Information Fusion. 31:110-126
This overview paper describes the particle methods developed for the implementation of the a class of Bayes filters formulated using the random finite set formalism. It is primarily intended for the readership already familiar with the particle metho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44c9b7672a2c78ac380be385d76f7fc6
https://doi.org/10.1016/j.inffus.2016.02.004
https://doi.org/10.1016/j.inffus.2016.02.004
Autor:
Francesco Papi, Claudio Fantacci
Publikováno v:
IEEE Signal Processing Letters. 23:863-867
Existing multisensor multitarget tracking solutions have complexities that grow super-exponentially w.r.t. the number of sensors. In this letter, we propose a novel algorithm for multisensor multitarget tracking that is scalable w.r.t. the number of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ded29f6a99d23243a25cd0d95187fd51
https://doi.org/10.1109/lsp.2016.2557078
https://doi.org/10.1109/lsp.2016.2557078
Publikováno v:
IEEE Transactions on Aerospace and Electronic Systems. 51:3294-3306
This paper deals with the problem of tracking a moving target by means of a network of geographically dispersed nodes with Doppler sensing, communication, and processing capabilities. The problem is addressed both in a hierarchical setting, i.e., in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::40a0e5f42527abc0171248946bc824da
https://doi.org/10.1109/taes.2015.140340
https://doi.org/10.1109/taes.2015.140340
Publikováno v:
IET Radar, Sonar & Navigation. 9:401-410
This study addresses distributed state estimation of jump Markovian systems and its application to tracking of a manoeuvring target by means of a network of heterogeneous sensors and communication nodes. Two novel consensus-based multiple-model filte
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d011c0956a7728cab6cac61b718d7f2c
https://doi.org/10.1049/iet-rsn.2014.0071
https://doi.org/10.1049/iet-rsn.2014.0071
This paper addresses recursive markerless estimation of a robot's end-effector using visual observations from its cameras. The problem is formulated into the Bayesian framework and addressed using Sequential Monte Carlo (SMC) filtering. We use a 3D r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4c9f43cbde4fd954b349de182242421
http://arxiv.org/abs/1703.04771
http://arxiv.org/abs/1703.04771
Publikováno v:
ICRA
To precisely reach for an object with a humanoid robot, it is of central importance to have good knowledge of both end-effector, object pose and shape. In this work we propose a framework for markerless visual servoing on unknown objects, which is di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2dbe882acbbcfd0581568375aaa57500