← Search

Ugo Pattacini

12 accepted papers

2026

Multifingered Force-Aware Control for Humanoid Robots

ICRA 2026poster

In this paper, we address force-aware control and force distribution in robotic platforms with multi-fingered hands. Given a target goal and force estimates from tactile sensors, we design a controller that adapts the motion of the torso, arm, wrist, and fingers, redistributing forces to maintain st…

2022

ROFT: Real-Time Optical Flow-Aided 6D Object Pose and Velocity Tracking

RA-L 2022

6D object pose tracking has been extensively studied in the robotics and computer vision communities. The most promising solutions, leveraging on deep neural networks and/or filtering and optimization, exhibit notable performance on standard benchmarks. However, to our best knowledge, these have not

Cited by 26SourceScholar
2020

GRASPA 1.0: GRASPA is a Robot Arm graSping Performance BenchmArk

RA-L 2020

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 use of common object sets has emerged in recent years, however no dominant protocols and metrics to test grasping pipeli

Cited by 36SourcecodeScholar
2018

Improving Superquadric Modeling and Grasping with Prior on Object Shapes

ICRA 2018poster

This paper proposes an object modeling and grasping pipeline for humanoid robots. This work improves our previous approach based on superquadric functions. In particular, we speed up and refine the modeling process by using prior information on the object shape provided by an object classifier. We u…

Cited by 23SourceScholar
2018

Markerless Visual Servoing on Unknown Objects for Humanoid Robot Platforms

ICRA 2018poster

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 divided in four main parts: I) a leastsquares minimi…

Cited by 10SourcecodeScholar
2018

Transferring Visuomotor Learning from Simulation to the Real World for Robotics Manipulation Tasks

IROS 2018poster

Hand-eye coordination is a requirement for many manipulation tasks including grasping and reaching. However, accurate hand-eye coordination has shown to be especially difficult to achieve in complex robots like the iCub humanoid. In this work, we solve the hand-eye coordination task using a visuomot…

Cited by 19SourceScholar
2017

The design and validation of the R1 personal humanoid

IROS 2017poster

In recent years the robotics field has witnessed an interesting new trend. Several companies started the production of service robots whose aim is to cooperate with humans. The robots developed so far are either rather expensive or unsuitable for manipulation tasks. This article presents the result…

Cited by 50SourceScholar
2017

Visual end-effector tracking using a 3D model-aided particle filter for humanoid robot platforms

IROS 2017poster

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 rendering engine and Computer Aided Design (CAD) sc…

Cited by 16SourceScholar
2016

A Cartesian 6-DoF Gaze Controller for Humanoid Robots

RSS 2016poster

In robotic systems with moving cameras control of gaze allows for image stabilization, tracking and attention switching. Proper integration of these capabilities lets the robot exploit the kinematic redundancy of the oculomotor system to improve tracking performance and extend the field of view, whi…

2015

A best-effort approach for run-time channel prioritization in real-time robotic application

IROS 2015poster

Application domains of robotic systems are growing in complexity. It seems therefore plausible that robotic software will continue to be designed to be executed on distributed computer architectures interconnected through a network. It is a common practice today to rely on best-effort performance an…

Cited by 11SourceScholar
2015

Learning peripersonal space representation through artificial skin for avoidance and reaching with whole body surface

IROS 2015poster

With robots leaving factory environments and entering less controlled domains, possibly sharing living space with humans, safety needs to be guaranteed. To this end, some form of awareness of their body surface and the space surrounding it is desirable. In this work, we present a unique method that…

Cited by 26SourceScholar