2 code implementations • 6 Nov 2021 • Nicola A. Piga, Yuriy Onyshchuk, Giulia Pasquale, Ugo Pattacini, Lorenzo Natale
In this work, we introduce ROFT, a Kalman filtering approach for 6D object pose and velocity tracking from a stream of RGB-D images.
1 code implementation • 12 Feb 2020 • Fabrizio Bottarel, Giulia Vezzani, Ugo Pattacini, Lorenzo Natale
In this paper, we present version 1. 0 of GRASPA, a benchmark to test effectiveness of grasping pipelines on physical robot setups.
Robotics
no code implementations • 9 Jul 2019 • Jennifer J. Gago, Valentina Vasco, Bartek Łukawski, Ugo Pattacini, Vadim Tikhanoff, Juan G. Victores, Carlos Balaguer
Natural language to sign language translation presents several challenges to developers, such as the discordance between the length of input and output data and the use of non-manual markers.
1 code implementation • 12 Oct 2017 • Claudio Fantacci, Giulia Vezzani, Ugo Pattacini, Vadim Tikhanoff, Lorenzo Natale
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.
Robotics Systems and Control Computation
1 code implementation • 12 Jun 2017 • Clément Moulin-Frier, Tobias Fischer, Maxime Petit, Grégoire Pointeau, Jordi-Ysard Puigbo, Ugo Pattacini, Sock Ching Low, Daniel Camilleri, Phuong Nguyen, Matej Hoffmann, Hyung Jin Chang, Martina Zambelli, Anne-Laure Mealier, Andreas Damianou, Giorgio Metta, Tony J. Prescott, Yiannis Demiris, Peter Ford Dominey, Paul F. M. J. Verschure
This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot.
1 code implementation • 14 Mar 2017 • Claudio Fantacci, Ugo Pattacini, Vadim Tikhanoff, Lorenzo Natale
This paper addresses recursive markerless estimation of a robot's end-effector using visual observations from its cameras.
Robotics
no code implementations • 13 Nov 2014 • Alessandro Roncone, Ugo Pattacini, Giorgio Metta, Lorenzo Natale
In this work we propose a comprehensive framework for gaze stabilization in a humanoid robot.
no code implementations • CVPR 2014 • Sean Ryan Fanello, Cem Keskin, Pushmeet Kohli, Shahram Izadi, Jamie Shotton, Antonio Criminisi, Ugo Pattacini, Tim Paek
We propose 'filter forests' (FF), an efficient new discriminative approach for predicting continuous variables given a signal and its context.