University of Twente Student Theses


Using a time-of-flight camera for autonomous indoor navigation

Kaspers, R. (2011) Using a time-of-flight camera for autonomous indoor navigation.

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Abstract:At Philips Floor Care autonomous vacuum cleaner robots are being developed. These robots autonomously find their way in unknown domestic environments. For such a robot to perform its job intelligently, it has to be able to observe its surroundings and process these observations into a map of the environment. A relatively new sensor for this task is the Time-of-Flight camera, which is capable of capturing a 3D image of its subject, multiple times a second. In this research the potential of the Time-of-Flight camera for autonomous indoor navigation is investigated. A characterization of the camera is made and algorithms are developed that extract relevant data from the 3D images (corners, jump edges and planes). These algorithms are evaluated with respect to speed, accuracy and robustness. Finally, a proof-of-principle setup is made using several orderings of typical pieces of furniture in a test room. The recorded 3D images are then processed using the developed feature extraction algorithms. The resulting features are fed to a Simultaneous Localization and Mapping (SLAM) algorithm, which estimates a map of the detected landmarks and the camera position within thismap. Based on the results it is concluded that the selected features are robustly detected, are abundant in the test setups and can be extracted and processed by the SLAMalgorithm in real time. The proof-of-principle shows that the features are accurate enough to result in stable SLAM within an average room. There are some issues identified that negatively affect accuracy, which require further research of both the camera and the algorithms. However, it can be concluded that the time-of-flight camera has good potential for autonomous indoor navigation and that the selected features can be considered good candidates for this purpose.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:53 electrotechnology
Programme:Electrical Engineering MSc (60353)
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