211 citations · 311 across the 12 of their papers we have counts for
12 papers
RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation
Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao +36
The ability to leverage heterogeneous robotic experience from different robots and tasks to quickly master novel skills and embodiments has the potential to transform robot learnin…
: Policy Representations with Successor Features
Gianluca Scarpellini, Ksenia Konyushkova, Claudio Fantacci +3
This paper describes , a method for representing behaviors of black box policies as feature vectors. The policy representations capture how the statistics of founda…
Lossless Adaptation of Pretrained Vision Models For Robotic Manipulation
Mohit Sharma, Claudio Fantacci, Yuxiang Zhou +4
Recent works have shown that large models pretrained on common visual learning tasks can provide useful representations for a wide range of specialized perception problems, as well…
SkillS: Adaptive Skill Sequencing for Efficient Temporally-Extended Exploration
Giulia Vezzani, Dhruva Tirumala, Markus Wulfmeier +13
The ability to effectively reuse prior knowledge is a key requirement when building general and flexible Reinforcement Learning (RL) agents. Skill reuse is one of the most common a…
Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes
Alex X. Lee, Coline Devin, Yuxiang Zhou +18
We study the problem of robotic stacking with objects of complex geometry. We propose a challenging and diverse set of such objects that was carefully designed to require strategie…
In Situ Translational Hand-Eye Calibration of Laser Profile Sensors using Arbitrary Objects
Prajval Kumar Murali, Ines Sorrentino, Angelo Rendiniello +8
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 rob…
Markerless visual servoing on unknown objects for humanoid robot platforms
Claudio Fantacci, Giulia Vezzani, Ugo Pattacini +2
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 fr…
Visual end-effector tracking using a 3D model-aided particle filter for humanoid robot platforms
Claudio Fantacci, Ugo Pattacini, Vadim Tikhanoff +1
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…
An Overview of Particle Methods for Random Finite Set Models
Branko Ristic, Michael Beard, Claudio Fantacci
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 primaril…
Distributed multi-object tracking over sensor networks: a random finite set approach
Claudio Fantacci
The aim of the present dissertation is to address distributed tracking over a network of heterogeneous and geographically dispersed nodes (or agents) with sensing, communication an…
Consensus Labeled Random Finite Set Filtering for Distributed Multi-Object Tracking
C. Fantacci, B. -N. Vo, B. -T. Vo +2
This paper addresses distributed multi-object tracking over a network of heterogeneous and geographically dispersed nodes with sensing, communication and processing capabilities. T…
Generalized Labeled Multi-Bernoulli Approximation of Multi-Object Densities
Francesco Papi, Ba-Ngu Vo, Ba-Tuong Vo +2
In multi-object inference, the multi-object probability density captures the uncertainty in the number and the states of the objects as well as the statistical dependence between t…