Vincenzo Caglioti

Prof. Vincenzo Caglioti


Research Focus & Metrics

Academic Career Length

34Years (1993-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2010 in Robotics and Autonomous Systems
Verified
Journal Article
Closed access
FAFrancesco Amigoni
Francesco Amigoni
VCVincenzo Caglioti
Vincenzo Caglioti

1 September 2014
Verified
Conference Paper
Closed access
FGFabrizio Ghiringhelli
Fabrizio Ghiringhelli
JGJerome Guzzi
Jerome Guzzi
GCGianni A. Di Caro
Gianni A. Di Caro
VCVincenzo Caglioti
Vincenzo Caglioti
LGLuca M. Gambardella
Luca M. Gambardella
AGAlessandro Giusti
Alessandro Giusti
Once a multi-robot system is implemented on real hardware and tested in the real world, analyzing its evolution and debugging unexpected behaviors is often a very difficult task. We present a tool for aiding this activity, by visualizing an Augmented Reality overlay on a live video feed acquired by a fixed camera overlooking the robot environment. Such overlay displays live information exposed by each robot, which may be textual (state messages), symbolic (graphs, charts), or, most importantly, spatially-situated; spatially-situated information is related to the environment surrounding the robot itself, such as for example the perceived position of neighboring robots, the perceived extent of obstacles, the path the robot plans to follow. We show that, by directly representing such information on the environment it refers to, our proposal removes a layer of indirection and significantly eases the process of understanding complex multi-robot systems. We describe how the system is implemented, discuss application examples in different scenarios, and provide supplementary material including demonstration videos and a functional implementation.

1 September 2014
Verified
Conference Paper
Closed access
AGArmando Pesenti Gritti
Armando Pesenti Gritti
OTOscar Tarabini
Oscar Tarabini
JGJerome Guzzi
Jerome Guzzi
GCGianni A. Di Caro
Gianni A. Di Caro
VCVincenzo Caglioti
Vincenzo Caglioti
AGAlessandro Giusti
Alessandro Giusti
Small-footprint mobile ground robots, such as the popular Turtlebot and Kobuki platforms, are by necessity equipped with sensors which lie close to the ground. Reliably detecting and tracking people from this viewpoint is a challenging problem, whose solution is a key requirement for many applications involving sharing of common spaces and close human-robot interaction. We present a robust solution for cluttered indoor environments, using an inexpensive RGB-D sensor such as the Microsoft Kinect or Asus Xtion. Even in challenging scenarios with multiple people in view at once and occluding each other, our system solves the person detection problem significantly better than alternative approaches, reaching a precision, recall and F1-score of 0.85, 0.81 and 0.83, respectively. Evaluation datasets, a real-time ROS-enabled implementation and demonstration videos are provided as supplementary material.

1 January 1998 in IEEE Transactions on Robotics and Automation
Verified
Journal Article
Closed access
GBG. Borghi
G. Borghi
VCVincenzo Caglioti
Vincenzo Caglioti

10 July 2006
Verified
Conference Paper
Closed access
VCVincenzo Caglioti
Vincenzo Caglioti
ACA. Citterio
A. Citterio
AFA. Fossati
A. Fossati

31 March 2011 in International Journal of Computer Vision
Verified
Journal Article
Closed access
PDF file
SGSimone Gasparini
Simone Gasparini
VCVincenzo Caglioti
Vincenzo Caglioti