View source for Poit cloud SLAM with Microsoft Kinect

{{ProjectProposal
|title=Point 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:'''
*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
|start=2015/01/01
|studmin=1
|studmax=2
|cfumin=10
|cfumax=20
|resarea=Computer Vision and Image Analysis
|restopic=none
|level=Ms
|type=Thesis
|status=Active
}}