Depth camera SLAM on a low-cost WiFi mapping robot

Piotr Mirowski, Ravishankar Palaniappan, Tin Kam Ho
<span title="">2012</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="" style="color: black;">2012 IEEE International Conference on Technologies for Practical Robot Applications (TePRA)</a> </i> &nbsp;
Radio-Frequency fingerprinting is an interesting solution for indoor localization. It exploits existing telecommunication infrastructure, such as WiFi routers, along with a database of signal strengths at different locations, but requires manually collecting signal measurements along with precise position information. To automatically build signal maps, we use an autonomous, self-localizing, low-cost mobile robotic platform. Our robot relies on the Kinect depth camera that is limited by a
more &raquo; ... field of view and short range. Our two-stage localization architecture first performs real-time obstacle-avoidance-based navigation and visual-based odometry correction for bearing angles. It then uses RGB-D images for Simultaneous Localization and Mapping. We compare the applicability of 6-degrees-offreedom RGB-D SLAM, and of particle filtering 2D SLAM algorithms and present novel ideas for loop closures. Finally, we demonstrate the use of the robot for WiFi localization in an office space.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1109/tepra.2012.6215673</a> <a target="_blank" rel="external noopener" href="">dblp:conf/tepra/MirowskiPH12</a> <a target="_blank" rel="external noopener" href="">fatcat:sad2wrcvn5gwjo5jqov6dluvyy</a> </span>
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