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Poit cloud SLAM with Microsoft Kinect - Revision history
2024-03-28T11:44:19Z
Revision history for this page on the wiki
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https://airwiki.elet.polimi.it/index.php?title=Poit_cloud_SLAM_with_Microsoft_Kinect&diff=17368&oldid=prev
AndreaBonarini at 15:32, 31 December 2014
2014-12-31T15:32:32Z
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AndreaBonarini
https://airwiki.elet.polimi.it/index.php?title=Poit_cloud_SLAM_with_Microsoft_Kinect&diff=17324&oldid=prev
MatteoMatteucci at 23:40, 21 December 2014
2014-12-21T23:40:04Z
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MatteoMatteucci
https://airwiki.elet.polimi.it/index.php?title=Poit_cloud_SLAM_with_Microsoft_Kinect&diff=14953&oldid=prev
MatteoMatteucci at 16:04, 16 April 2012
2012-04-16T16:04:15Z
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MatteoMatteucci
https://airwiki.elet.polimi.it/index.php?title=Poit_cloud_SLAM_with_Microsoft_Kinect&diff=14934&oldid=prev
MatteoMatteucci: Created page with "{{ProjectProposal |title=Poit cloud SLAM with Microsoft Kinect |image=PointCloudKinect.jpg |description=Simultaneous Localization and Mapping (SLAM) is one of the basic functi..."
2012-04-16T15:23:13Z
<p>Created page with "{{ProjectProposal |title=Poit cloud SLAM with Microsoft Kinect |image=PointCloudKinect.jpg |description=Simultaneous Localization and Mapping (SLAM) is one of the basic functi..."</p>
<p><b>New page</b></p><div>{{ProjectProposal<br />
|title=Poit cloud SLAM with Microsoft Kinect<br />
|image=PointCloudKinect.jpg<br />
|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.<br />
<br />
'''Material:'''<br />
*Kinect sensor and libraries<br />
*A framework for multisensor SLAM<br />
*PCL2.0 library for dealing with point clouds<br />
<br />
'''Expected outcome:'''<br />
*Algorithm able to build 3D point cloud representation of the observed scene<br />
*Point clouds processing could be used to improve the accuracy of the filter as well<br />
<br />
'''Required skills or skills to be acquired:'''<br />
*Basic background in computer vision<br />
*Basic background in Kalman filtering<br />
*C++ programming under Linux <br />
<br />
|tutor=MatteoMatteucci<br />
|start=2012/04/01<br />
|studmin=1<br />
|studmax=2<br />
|cfumin=10<br />
|cfumax=20<br />
|resarea=Computer Vision and Image Analysis<br />
|restopic=none<br />
|level=Bs;Ms<br />
|type=Thesis<br />
|status=Active<br />
}}</div>
MatteoMatteucci