Ballardini Augusto Luis

FileBallardiniaugustoluisHi everyone, I'm Augusto and from 2017 I am working at IRALAB as a Postdoctoral Research Fellow ūüôā





Università degli Studi di Milano - Bicocca Dipartimento di Informatica, Sistemistica e Comunicazione Viale Sarca 336, Building U14, 20126 Milano, Italy Informatics and Robotics for Automation Lab (IRALab) Location: Room 1020 Phone: +39 02 6448 7823 Email: ballardini at disco dot unimib dot it

Research Interests


  • A. L. Ballardini, A. Furlan, A. Galbiati, M. Matteucci, F. Sacchi, D. G. Sorrenti - 6DoF Monte Carlo Localization in a 3D world with Laser Range Finders. This is a research report of my master's thesis, written for the DISCO Dept. (93 downloads) [Other link¬†from Unimib]
    Abstract: In mobile robotics, localization plays a key role in every task assigned to a robot. This report describes the probabilistic module we developed to solve the localization problem in our autonomous driving vehicle. Our method uses a complete 6DoF approach within a 3D motion model, in order to correctly integrate the error caused by dead reckoning. Furthermore, the description of the environment is a 3D voxel representation. We base on particle filtering, in the localization process. An ad-hoc simulation environment has been developed, for testing the effectiveness of the motion model. Finally, we performed some field experiments, to demonstrate that our approach consistently locates the 6DoF position of the vehicle along the driven path on the test site.
  • A. L. Ballardini, A. Furlan, A. Galbiati, M. Matteucci, F. Sacchi, D. G. Sorrenti An effective 6DoF motion model for 3D-6DoF Monte Carlo Localization 4th Workshop on Planning, Perception and Navigation for Intelligent Vehicles, IROS, 2012 PDF available An effective 6DoF motion model for 3D-6DoF Monte Carlo Localization (650 downloads) .
    Abstract: This paper deals with the probabilistic 6DoF motion model of a wheeled road vehicle. It allows to correctly model the error introduced by dead reckoning. Furthermore, to stress the importance of an appropriate motion model, i.e., that different models are not equally good, we show that another model, which was previously developed, does not allow a correct representation of the uncertainty, therefore misguiding 3D-6DoF Monte Carlo Localization. We also present some field experiments to demonstrate that our model allow a consistent determination of the 6DoF vehicle pose
  • Augusto Luis Ballardini, Simone Fontana, Axel Furlan, Domenico G. Sorrenti - ira_laser_tools: a ROS LaserScan manipulation toolbox¬† ¬† or here
    Abstract: Laser scanners are sensors of widespread use in robotic applications. Under the Robot Operating System (ROS) the information generated by laser scanners can be conveyed by either LaserScan messages or in the form of PointClouds. Many publicly available algorithms (mapping, localization, navigation, etc.) rely on LaserScan messages, yet a tool for handling multiple lasers, merging their measurements, or to generate generic LaserScan messages from PointClouds, is not available. This report describes two tools, in the form of ROS nodes, which we release as open source under the BSD license, which allow to either merge multiple single-plane laser scans or to generate virtual laser scans from a point cloud. A short tutorial, along with the main advantages and limitations of these tools are presented.
  • Augusto Luis Ballardini, Simone Fontana, Axel Furlan, Dario Limongi, Domenico Giorgio Sorrenti - A framework for outdoor urban environment estimation, IEEE 18th International Conference on Intelligent Transportation Systems, ITSC2015, in ITSC2015 proceedings.
    Abstract: In this paper we present a general framework for urban road layout estimation, altogether with a specific application to the vehicle localization problem. The localization is performed by synergically exploiting data from different sensors, as well as map-matching with OpenStreetMap cartographic maps. The effectiveness is proven by achieving real-time computation with state-of-the-art results on a set of ten not trivial runs from the KITTI dataset, including both urban/residential and highway/road scenarios. Although this paper represents a first step implementation towards a more general urban scene understanding framework, here we prove its flexibility of application to different intelligent vehicles applications.
  • Simone Fontana, Lorenzo Ferretti, Augusto Luis Ballardini, Axel Furlan and Domenico Giorgio Sorrenti - An Indoor Localization System for Telehomecare Applications on IEEE Transactions on Systems, Man, and Cybernetics: Systems¬†-¬†In this paper, we present a novel probabilistic technique, based on the Bayes filter, able to estimate the user location, even with unreliable sensor data coming only from fixed sensors in the monitored environment. Our approach has been extensively tested in a home-like environment, as well as in a real home, and achieves very good results. We present results on two datasets, representative of real life conditions, collected during the testing phase. We detect the patient location with subroom accuracy, an improvement over the state of the art for localization using only environmental sensors. The main drawback is that it is only suitable for applications where a single person is present in the environment, like as with other approaches that do not use any mobile device. For this reason, we introduced the "telehomecare" term, therefore differentiating from generic telemedicine applications, where many people can be in the same environment at the same time.
  • Augusto Luis Ballardini, Daniele Cattaneo, Simone Fontana, Domenico Giorgio Sorrenti - Leveraging the OSM Building Data to Enhance Localization of an Urban Vehicle, IEEE ITSC 2016 Conference [link]. In this paper we present a technique that takes advantage of detected building fac Őßades and OpenStreetMaps data to im- prove the localization of an autonomous vehicle driving in a urban scenario. The proposed approach leverages images from a stereo rig mounted on the vehicle to produce a mathematical representation of the buildings‚Äô facades within the field of view. This representation is matched against the outlines of the surrounding buildings as they are available on OpenStreetMaps. The information is then fed into our probabilistic framework, called Road Layout Estimation, in order to produce an accurate lane-level localization of the vehicle. The experiments conducted on the well-known KITTI datasets prove the effectiveness of our approach
  • Augusto Luis Ballardini, Daniele Cattaneo, Simone Fontana, Domenico Giorgio Sorrenti - An Online Probabilistic Road Intersection Detector - Presented ad¬†ICRA 2017 Conference [link]
    In this paper we propose a probabilistic approach for detecting and classifying urban road intersections from a moving vehicle. The approach is based on images from an onboard stereo rig; it relies on the detection of the road ground plane on one side, and on a pixel-level classification of the road on the other. The two processing pipelines are then integrated and the parameters of the road components, i.e., the intersection geometry, are inferred. As opposed to other state-of-the-art offline methods, which require processing of the whole video sequence, our approach integrates the image data by means of an online procedure. The experiments have been performed on well-known KITTI datasets, allowing for future comparisons.  

Public Datasets

Intersection Detector & Ground Truth

The following datasets are related to paper An Online Probabilistic Road Intersection Detector  presented in the IEEE ICRA 2017 Conference [link]

Projects and Presentations

Courses and Schools attended during the PhD Years

  • Parallel Computing Using MPI and OpenMP - Cineca 17-25 June 2013
  • 1st Summer School on Critical Embedded Systems, 2-11 July 2013, Toulouse - France [link]
  • 4th PAVIS School on Computer Vision, Pattern Recognition, and Image Processing,¬†September 18-20, 2013 - Sestri Levante (GE), Italy
  • V-Charge Summer School on Perception and Planning for Autonomous Driving - July 7-10 2014, ETH Zurich, Switzerland
  • Computational approaches to Physical and Virtual Crowd Phenomena - DISCO PhD Course [link]
  • Clustering Analysis - DISCO PhD Course
  • Advanced Techniques for Combinatorial Algorithms - DISCO PhD Course
  • Paradigms and Approaches to Computer Security - DISCO PhD Course [link]

Teaching assistance

  • Computer Architecture (Architettura modulo Elaboratori)
  • Robotics:
    • Robot motion (Probabilistic Robotics Ch.6): 3DoF and 6DoF odometry model, sampling algorithm, beam model
    • Robot Localization, Monte Carlo (Probabilistic Robotics, Ch.8): MCL, Augmented MCL, KLD-Sampling
    • Camera Calibration DLT - Lab Practice
    • Camera Calibration using Matlab Toolbox and OpenCV / ROS Tools - Mono & Stereo configuration - Lab Practice


During the last few years 2012-2017 I have had the opportunity to supervise the works of:

Daniele Cattaneo - A probabilistic intersection detector for the Road Layout Estimation Framework
Sergio Cattaneo - Leveraging the OSM building data in the Road Layout Estimation Framework
Dario Limongi - Road Layout Estimation - A probabilistic framework for autonomous driving Cars
Francesco Sacchi - 3D slam for autonomous vehicle

Matteo Vaghi - USAD GUI: progettazione ed implementazione di una interfaccia grafica per veicolo a guida autonoma
Alessandro Pagani - Trajectory Recorder and Player for Mobile Robots
Fabrizio Bianchini - A robotic mapping platform based on laser scanner
Alfredo De Santis - 3D Mapping with laser scanners
Daniele Fiorenti - 3D Mapping Ground Truth
Elio Salanitri - A laser device and its calibration for the 3D Mapping Ground Truth project

Old Projects

Electronics Related Projects (developed during the master degree) - SPI Accelerometers