241 citations · 750 across the 37 of their papers we have counts for
29 papers · 1 filter
Handling Concurrency in Behavior Trees
Michele Colledanchise, Lorenzo Natale
This paper addresses the concurrency issues affecting Behavior Trees (BTs), a popular tool to model the behaviors of autonomous agents in the video game and the robotics industry.…
Weakly-Supervised Object Detection Learning through Human-Robot Interaction
Elisa Maiettini, Vadim Tikhanoff, Lorenzo Natale
Reliable perception and efficient adaptation to novel conditions are priority skills for humanoids that function in dynamic environments. The vast advancements in latest computer v…
On the Implementation of Behavior Trees in Robotics
Michele Colledanchise, Lorenzo Natale
There is a growing interest in Behavior Trees (BTs) as a tool to describe and implement robot behaviors. BTs were devised in the video game industry and their adoption in robotics…
A Toolchain to Design, Execute, and Monitor Robots Behaviors
Michele Colledanchise, Giuseppe Cicala, Daniele E. Domenichelli +2
In this paper, we present a toolchain to design, execute, and verify robot behaviors. The toolchain follows the guidelines defined by the EU H2020 project RobMoSys and encodes the…
Formalizing the Execution Context of Behavior Trees for Runtime Verification of Deliberative Policies
Michele Colledanchise, Giuseppe Cicala, Daniele E. Domenichelli +2
In this paper, we enable automated property verification of deliberative components in robot control architectures. We focus on formalizing the execution context of Behavior Trees…
iCub
Lorenzo Natale, Chiara Bartolozzi, Francesco Nori +2
In this chapter we describe the history and evolution of the iCub humanoid platform. We start by describing the first version as it was designed during the RobotCub EU project and…
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…
Task Planning with Belief Behavior Trees
Evgenii Safronov, Michele Colledanchise, Lorenzo Natale
In this paper, we propose Belief Behavior Trees (BBTs), an extension to Behavior Trees (BTs) that allows to automatically create a policy that controls a robot in partially observa…
Act, Perceive, and Plan in Belief Space for Robot Localization
Michele Colledanchise, Damiano Malafronte, Lorenzo Natale
In this paper, we outline an interleaved acting and planning technique to rapidly reduce the uncertainty of the estimated robot's pose by perceiving relevant information from the e…
GRASPA 1.0: GRASPA is a Robot Arm graSping Performance benchmArk
Fabrizio Bottarel, Giulia Vezzani, Ugo Pattacini +1
The use of benchmarks is a widespread and scientifically meaningful practice to validate performance of different approaches to the same task. In the context of robot grasping the…
Analysis and Exploitation of Synchronized Parallel Executions in Behavior Trees
Michele Colledanchise, Lorenzo Natale
Behavior Trees (BTs) are becoming a popular tool to model the behaviors of autonomous agents in the computer game and the robotics industry. One of the key advantages of BTs lies i…
Improving the Parallel Execution of Behavior Trees
Michele Colledanchise, Lorenzo Natale
Behavior Trees (BTs) have become a popular framework for designing controllers of autonomous agents in the computer game and in the robotics industry. One of the key advantages of…
Speeding-up Object Detection Training for Robotics with FALKON
Elisa Maiettini, Giulia Pasquale, Lorenzo Rosasco +1
Latest deep learning methods for object detection provide remarkable performance, but have limits when used in robotic applications. One of the most relevant issues is the long tra…
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…
Are we done with object recognition? The iCub robot's perspective
Giulia Pasquale, Carlo Ciliberto, Francesca Odone +2
We report on an extensive study of the benefits and limitations of current deep learning approaches to object recognition in robot vision scenarios, introducing a novel dataset use…
Controlled Tactile Exploration and Haptic Object Recognition
Massimo Regoli, Nawid Jamali, Giorgio Metta +1
In this paper we propose a novel method for in-hand object recognition. The method is composed of a grasp stabilization controller and two exploratory behaviours to capture the sha…
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…
Memory Unscented Particle Filter for 6-DOF Tactile Localization
Giulia Vezzani, Ugo Pattacini, Giorgio Battistelli +2
This paper addresses 6-DOF (degree-of-freedom) tactile localization, i.e. the pose estimation of tridimensional objects given tactile measurements. This estimation problem is funda…
Enabling Depth-driven Visual Attention on the iCub Humanoid Robot: Instructions for Use and New Perspectives
Giulia Pasquale, Tanis Mar, Carlo Ciliberto +2
The importance of depth perception in the interactions that humans have within their nearby space is a well established fact. Consequently, it is also well known that the possibili…
Real-world Object Recognition with Off-the-shelf Deep Conv Nets: How Many Objects can iCub Learn?
Giulia Pasquale, Carlo Ciliberto, Francesca Odone +2
The ability to visually recognize objects is a fundamental skill for robotics systems. Indeed, a large variety of tasks involving manipulation, navigation or interaction with other…
A representation of robotic behaviors using component port arbitration
Ali Paikan, Giorgio Metta, Lorenzo Natale
Developing applications considering reactiveness, scalability and re-usability has always been at the center of attention of robotic researchers. Behavior-based architectures have…
A Flexible and Robust Large Scale Capacitive Tactile System for Robots
Perla Maiolino, Marco Maggiali, Giorgio Cannata +2
Capacitive technology allows building sensors that are small, compact and have high sensitivity. For this reason it has been widely adopted in robotics. In a previous work we prese…
Gaze Stabilization for Humanoid Robots: a Comprehensive Framework
Alessandro Roncone, Ugo Pattacini, Giorgio Metta +1
Gaze stabilization is an important requisite for humanoid robots. Previous work on this topic has focused on the integration of inertial and visual information. Little attention ha…
Reverse Engineering of Middleware for Verification of Robot Control Architectures
Ali Khalili, Lorenzo Natale, Armando Tacchella
We consider the problem of automating the verification of distributed control software relying on publish-subscribe middleware. In this scenario, the main challenge is that softwar…