Difference between revisions of "2nd Level Theses"

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Here you can find proposals for master thesis (20 CFU for each student).  See [[Project Proposals]] for other kinds of projects and theses.
 
Here you can find proposals for master thesis (20 CFU for each student).  See [[Project Proposals]] for other kinds of projects and theses.
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Latest revision as of 15:06, 7 January 2015

Here you can find proposals for master thesis (20 CFU for each student). See Project Proposals for other kinds of projects and theses.

RoboCup Rescue

Computer Vision and Image Analysis

Wiki Page: Accurate AR Marker Location
ARTag.jpg
Title: C++ Library for accurate marker location based on subsequent pnp refinements
Description: ARTags, QR codes, Data Matrix, are visual landmark used for augmented reality, but they could be used for robotics as well. A thesis has already been done on using data matrix for robot localization and mapping, but improvements are required in terms generality, accuracy and robustness of the solution. The goal is thuss to:
  • increase the number of markers supported by the system (ARTag + QR codes)
  • increase the accuracy of the detection and localization of the marker
  • test different algorithms for the solution of the perspective from n points problem

Material:

  • papers on PnP algorithms, OpenCV,
  • Matlab code with three PnP algorithms implementations
  • C++ libraries for marker detection (to be found and evaluated)

Expected outcome:

  • C++ library to the robust localization of artificial markers
  • a ROS node performing accurate ARTag localization
  • a comparison of Tags and algorithms in a real world scenario
  • The use of this library in a SLAM framework (Thesis)

Required skills or skills to be acquired:

  • background on computer vision and image processing
  • C++ programming under Linux
Tutor: MatteoMatteucci (matteo.matteucci@polimi.it)
Start: 1 January 2015
Students: 1 - 2
CFU: 5 - 10
Research Area: Computer Vision and Image Analysis
Research Topic: None
Wiki Page: Comparison of State of the Art Visual Odometry Systems
VisualOdometry.jpg
Title: A Comparison of State of the Art Visual Odometry Systems (Monocular and Stereo)
Description: Visual odometry is the estimation of camera(s) movement from a sequence of images. In case we deal with a single camera system we have Monocular Visual Odometry; in case we have more cameras we have a Stero Visual Odometry. The goal of the thesis is to review the state of the art on in visual odometry, classify existing approaches and compare their implementations (many of the algorithms have online source code available).

Material

Expected outcome:

  • a set of running algorithms performing visual odometry

Required skills or skills to be acquired:

  • computer vision and 3D reconstruction
  • C++ programming under Linux
Tutor: MatteoMatteucci (matteo.matteucci@polimi.it)
Start: 1 January 2015
Students: 1 - 2
CFU: 10 - 20
Research Area: Computer Vision and Image Analysis
Research Topic: None
Wiki Page: Mesh Refinement with Deep Learning
Title: Mesh Refinement with Deep Learning
Description: Mesh Refinement with Deep Learning
Tutor: AndreaRomanoni (andrea.romanoni@polimi.it)
Start: October 2018
Students: 1
CFU: 5
Research Area: Computer Vision and Image Analysis
Wiki Page: Poit cloud SLAM with Microsoft Kinect
PointCloudKinect.jpg
Title: Point cloud SLAM with Microsoft Kinect
Description: Simultaneous Localization and Mapping (SLAM) is one of the basic functionalities required from an autonomous robot. In the past we have developed a framework for building SLAM algorithm based on the use of the Extended Kalman Filter and vision sensors. A recently available vision sensor which has tremendous potential for autonomous robots is the Microsoft Kinect RGB-D sensor. The thesis aims at the integration of the Kinect sensor in the framework developed for the development of a point cloud base system for SLAM.

Material:

  • Kinect sensor and libraries
  • A framework for multisensor SLAM
  • PCL2.0 library for dealing with point clouds

Expected outcome:

  • Algorithm able to build 3D point cloud representation of the observed scene
  • Point clouds processing could be used to improve the accuracy of the filter as well

Required skills or skills to be acquired:

  • Basic background in computer vision
  • Basic background in Kalman filtering
  • C++ programming under Linux
Tutor: MatteoMatteucci (matteo.matteucci@polimi.it)
Start: 1 January 2015
Students: 1 - 2
CFU: 10 - 20
Research Area: Computer Vision and Image Analysis
Research Topic: None


Robotics

Wiki Page: 3D Scene Understanding
FreeCamera.png
Title: 3D Indoor scene understanding and layout reconstruction for a mobile robot in collaboration with UnimiB
Description: The proposed project aims to reconstruct the 3D structural layout of an indoor environment perceived by a mobile robot. From the sensorial data, the robot should be able to reconstruct a geometrical structure of an indoor environment (e.g., an office).

Methods for indoor layout reconstruction must be significantly more tolerant to missing data than their outdoor counterparts, since environments such as offices and apartments exhibit extremely high levels of clutter, which typically results in heavy occlusions of walls and other structures of interest, large-scale artifacts, noise and missing data. The proposed work will be developed in collaboration with IRALAB, the Robotics Lab of University of Milano Bicocca.

The work will be based on an existing project, Free Your Camera (http://www.ira.disco.unimib.it/research/robotic-perception-research/free-your-camera-3d-indoor-scene-understanding-from-arbitrary-camera-motion/) and will be part of a robotic framework based on with ROS and in development at IRALAB.

Tutor: FrancescoAmigoni (francesco.amigoni@polimi.it), MatteoLuperto (matteo.luperto@polimi.com)
Start: 1 February 2015
Students: 1 - 2
CFU: 10 - 20
Research Area: Robotics
Research Topic: Robotics
Wiki Page: Automatic Differentiation Techniques for Real Time Kalman Filtering
Autodiff.png
Title: Evaluation of Automatic Differentiation Techniques for Gauss-Newton based Simultaneous Localization and Mapping
Description: In Gauss-Newton non linear optimization one of the most tedious part is computing Jacobians. At the AIRLab we have developed a framework for non linear Simultaneous Localization and Mapping suitable for different motion models and measurement equations, but any time you need to change something you need to recompute the required Jacobian. Automatic differentiation is a tool for the automatic differentiation of source code either at compiling time or at runtime; we are interested in testing these techniques in the software we have developed and compare their performance with respect to (cumbersome) optimized computation.

Material

Expected outcome: New modules implementations based on automatic differentiation A comparison between the old stuff and new approach

Required skills or skills to be acquired:

  • C++ programming under Linux
Tutor: MatteoMatteucci (matteo.matteucci@polimi.it)
Start: 1 January 2015
Students: 1 - 2
CFU: 10 - 20
Research Area: Robotics
Research Topic: None
Wiki Page: Cognitive SLAM
C SLAM Recognition2.png
Title: Cognitive SLAM
Description: We have developed a system that is able to detect, recognize and track objects in an image taken from a low cost robot equipped with a IMU and a low cost camera. The system is capable to detect and recognize objects using a user defined fuzzy tree classifier. However the system performance is heavily dependent on high level feature extraction, such as geometric features. The problem is non trivial due to noisy low cost camera and changes in the light conditions. The aim of this project is to improve the feature extraction and description process, both in performance and quality, possible adding a more complete description or others type of features. The long term aim of the research is to have an autonomuos robot capable to create a semantic map of the envirorment, localize himself , make inference on the map, navigate into the envirorment using the objects as landmarks.

No special skills are required, except basic c and object oriented programming.

Tutor: AndreaBonarini (andrea.bonarini@polimi.it), DavideTateo (davide.tateo@polimi.it)
Start: 1 January 2015
Students: 1 - 2
CFU: 5 - 20
Research Area: Robotics
Research Topic: SLAM, Feature Extraction
Wiki Page: Designing Living Objects
EmotionalTrashBin.jpg
Title: Designing Living Objects
Description: The aim of this activity is to investigate how one or more objects in an antropic environment (home, office, hospital) can be designed and implemented to have a character and to move, having nice interactions with people. The work to be done concerns the analysis, definition, design and implementation of at least one of these objects.
Tutor: AndreaBonarini (andrea.bonarini@polimi.it)
Start: 15 October 2017
Students: 1 - 2
CFU: 5 - 20
Research Area: Robotics
Research Topic: Living Objects
Wiki Page: MoonSLAM Reengineering
SofwareEingineer.jpg
Title: Reengineering of a flexible framework for simultaneous localization and mapping
Description: In the last three years a general framework for the implementation of EKF-SLAM algorithm has been developed at the AIRLab. After several improvements it is now time to redesign it based on the experience cumulated. The goal is to have an international reference framework for the development of EKF based SLAM algorithms with multiple sensors (e.g., lasers, odometers, inertial measurement ) and different motion models (e.g., free 6DoF motion, planar motion, ackerman kinematic, and do on). The basic idea is to implement it by using C++ templates, numerically stable techniques for Kalman filtering and investigation the use of automatic differentiation. It should be possible to seamlessly exchange motion model and sensor model without having to write code beside the motion model and the measurement equation.

Material

  • lots of theoretical background and material
  • an existing (and working) C++ implementation of the framework

Expected outcome:

  • a C++ library for the implementation of generic EKF-SLAM algorithms

Required skills:

  • Experienced C++ programming under Linux
Tutor: MatteoMatteucci (matteo.matteucci@polimi.it)
Start: 1 January 2015
Students: 1 - 2
CFU: 20 - 20
Research Area: Robotics
Research Topic: None
Wiki Page: ROS navigation local planner
300px
Title: ROS_navigation_local_planner
Description: The project will be focused on the implementation of a planner and tracking algorithms for Ackermann vehicles
Tutor: MatteoMatteucci (matteo.matteucci@polimi.it)
Start: October 2017
Students: 1 - 3
CFU: 2 - 20
Research Area: Robotics
Research Topic: Local Planner
Wiki Page: Robot Games
Spykeecontorri.jpg
Title: Robot Games
Description: Projects may include the design of an interactive game on an existing or a new robot, and its evaluation. These projects allow to experiment with real mobile robots and interaction devices. Some games may be designed for disabled children. The project can be considered a MS thesis if it can produce a new game and, possibly, a new robot, and includes adapting the behavior of the robot to the player.
Tutor: AndreaBonarini (andrea.bonarini@polimi.it)
Start:
Students: 1 - 2
CFU: 2 - 20
Research Area: Robotics
Research Topic: Robogames
Wiki Page: Unmanned Aerial Vehicles Visual Navigation
Quadrotor.jpg
Title: A critical review on the state of the art in visual navigation for unmanned aerial vehicles
Description: Visual navigation is becoming more and more important in the development of unmanned aerial vehicles (UAV). The goal of this thesis/tesina is to review in a structured way the current state of art in the field from different perspective: research teams, projects, platforms, tasks, algorithms. The latter is the most important aspect obviously and the project should provide a clear view on what is done today, and obtaining which results. Two kind of operations are of most interest: tracking of fixed and mobile targets (and how this impact on the UAV path), navigation on a geo-referenced map. Implementing one of the standard approaches on a mini unmanned aerial vehicle would be the ideal ending of the work to turn it into a thesis.

Material:

  • papers from major journals and conferences
  • reports from research projects

Expected outcome:

  • a report with a detailed review of the state of the art organized according to the main relevant aspects (to be identified during the work)
  • an implementation of some state of the art algorithms for tracking or navigation

Required skills or skills to be acquired:

  • proficiency in english
  • basic understanding of computer vision
  • basic understanding of filtering techniques
Tutor: MatteoMatteucci (matteo.matteucci@polimi.it)
Start: 1 January 2015
Students: 1 - 2
CFU: 10 - 20
Research Area: Robotics
Research Topic: None
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