1 citations · 1 across the 4 of their papers we have counts for
5 papers
Learning passive policies with virtual energy tanks in robotics
Riccardo Zanella, Gianluca Palli, Stefano Stramigioli +1
Within a robotic context, we merge the techniques of passivity-based control (PBC) and reinforcement learning (RL) with the goal of eliminating some of their reciprocal weaknesses,…
Symplectic Integration for Multivariate Dynamic Spline-Based Model of Deformable Linear Objects
Alaa Khalifa, Gianluca Palli
Deformable Linear Objects (DLOs) such as ropes, cables, and surgical sutures have a wide variety of uses in automotive engineering, surgery, and electromechanical industries. There…
Effective Deployment of CNNs for 3DoF Pose Estimation and Grasping in Industrial Settings
Daniele De Gregorio, Riccardo Zanella, Gianluca Palli +1
In this paper we investigate how to effectively deploy deep learning in practical industrial settings, such as robotic grasping applications. When a deep-learning based solution is…
Semi-Automatic Labeling for Deep Learning in Robotics
Daniele De Gregorio, Alessio Tonioni, Gianluca Palli +1
In this paper, we propose Augmented Reality Semi-automatic labeling (ARS), a semi-automatic method which leverages on moving a 2D camera by means of a robot, proving precise camera…
Let's take a Walk on Superpixels Graphs: Deformable Linear Objects Segmentation and Model Estimation
Daniele De Gregorio, Gianluca Palli, Luigi Di Stefano
While robotic manipulation of rigid objects is quite straightforward, coping with deformable objects is an open issue. More specifically, tasks like tying a knot, wiring a connecto…