Autonomous Robotic SLAM-based Indoor Navigation for High Resolution Sampling with Complete Coverage

I. Wieser, A. Viseras Ruiz, M. Frassl, M. Angermann, J. Mueller, M. Lichtenstern

Abstract: Recent work has shown the feasibility of pedestrian and robotic indoor localization based only on maps of the magnetic field. To obtain a complete representation of the magnetic field without initial knowledge of the environment or any existing infrastructure, we consider an autonomous robotic platform to reduce limitations of economic or operational feasibility. Therefore we present a novel robotic system that autonomously samples any measurable physical processes at high spatial resolution in buildings without any prior knowledge of the building’s structure. In particular we focus on adaptable robotic shapes, kinematics and sensor placements to both achieve complete coverage in hardly accessible areas and not be limited to round shaped robots. We propose a grid based representation of the robot’s configuration space and graph search algorithms, such as Best-First-Search and an adaption of Dijkstra’s algorithm, to guarantee complete path coverage. In combination with an optical simultaneous localization and mapping (SLAM) algorithm, we present experimental results by sampling the magnetic field in an a priori unknown office with a robotic platform autonomously and completely.
Published in: Proceedings of IEEE/ION PLANS 2014
May 5 - 8, 2014
Hyatt Regency Hotel
Monterey, CA
Pages: 945 - 951
Cite this article: Wieser, I., Ruiz, A. Viseras, Frassl, M., Angermann, M., Mueller, J., Lichtenstern, M., "Autonomous Robotic SLAM-based Indoor Navigation for High Resolution Sampling with Complete Coverage," Proceedings of IEEE/ION PLANS 2014, Monterey, CA, May 2014, pp. 945-951.
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