Building an Autonomous Indoor Visual SLAM System using an iRobot - PowerPoint PPT Presentation

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Building an Autonomous Indoor Visual SLAM System using an iRobot and Kinect Chase Lewis Mentor: Xin Li, Kang Zhang Kinect and iRobot System Simultaneous Localization and Mapping Creating a 3d map while tracking the location of the robot

Building an Autonomous Indoor Visual SLAM System using an iRobot and Kinect Chase Lewis Mentor: Xin Li, Kang Zhang
Kinect and iRobot System
Simultaneous Localization and Mapping Creating a 3d map while tracking the location of the robot in said map Algorithms and image processing techniques S.L.A.M
Point Cloud Conversion
Algorithms Speeded Up Robust Feature (SURF) Random Sample Consensus (RANSAC) Feature Detection
Stitching
Self-Driving Cars
Remote Exploration
Questions?
This material is based upon work supported by the National Science Foundation under award OCI-1560410 with additional support from the Center for Computation & Technology at Louisiana State University. Acknowledgements
OpenCV: http://opencv.org/ References Kinect Image Library: http://vision.in.tum.de/ Feature Detection Support: http://pyimagesearch.com/

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