Difference between revisions of "Poit cloud SLAM with Microsoft Kinect"
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− | |tutor=MatteoMatteucci | + | |tutor=MatteoMatteucci |
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|type=Thesis | |type=Thesis | ||
|status=Active | |status=Active | ||
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Revision as of 00:40, 22 December 2014
Title: | Poit cloud SLAM with Microsoft Kinect |
Image:PointCloudKinect.jpg |
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:
Expected outcome:
Required skills or skills to be acquired:
| |
Tutor: | MatteoMatteucci (matteo.matteucci@polimi.it) | |
Start: | 2015/01/01 | |
Students: | 1 - 2 | |
CFU: | 10 - 20 | |
Research Area: | Computer Vision and Image Analysis | |
Research Topic: | none | |
Level: | Ms | |
Type: | Thesis | |
Status: | Active |