activity
20192026
most citedFeature-Based Transfer Learning for Robotic Push Manipulation

19 citations · 52 across the 15 of their papers we have counts for

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13 papers · 1 filter

cs.RO2026

LiZIP: An Auto-Regressive Compression Framework for LiDAR Point Clouds

Aditya Shibu, Kayvan Karim, Claudio Zito

The massive volume of data generated by LiDAR sensors in autonomous vehicles creates a bottleneck for real-time processing and vehicle-to-everything (V2X) transmission. Existing lo…

cs.RO20231 cited

Robot Grasping and Manipulation: A Prospective

Claudio Zito

``A simple handshake would give them away''. This is how Anthony Hopkins' fictional character, Dr Robert Ford, summarises a particular flaw of the 2016 science-fiction \emph{Westwo…

cs.RO2022

Multi-Hypothesis Scan Matching through Clustering

Giorgio Iavicoli, Claudio Zito

Graph-SLAM is a well-established algorithm for constructing a topological map of the environment while simultaneously attempting the localisation of the robot. It relies on scan ma…

cs.RO2020

Aging Touch: Systematic and Unbiased Presentation of Tactile Stimuli

Claudio Zito

This report presents the experimental methodology and a step-by-step guide for gathering data on how aging influences tactile surface perception in decision and action. The experim…

cs.RO20194 cited

Multisensory Learning Framework for Robot Drumming

A. Barsky, C. Zito, H. Mori +2

The hype about sensorimotor learning is currently reaching high fever, thanks to the latest advancement in deep learning. In this paper, we present an open-source framework for col…

cs.RO20192 cited

Robust and fast generation of top and side grasps for unknown objects

Brice Denoun, Beatriz Leon, Claudio Zito +3

In this work, we present a geometry-based grasping algorithm that is capable of efficiently generating both top and side grasps for unknown objects, using a single view RGB-D camer…