Environment-based measurement planning for autonomous RTLS configuration

We present a novel approach for selecting measurement points online to determine the pose (position and orientation) of an Real-Time Location System's (RTLS) receiving element. In combination with the RANdom Sample And Consensus (RANSAC) algorithm, we generate a selection of measurement points excluding bad measurements to get the right estimation of the pose. The proposed algorithm considers obstacles and boundaries, which are previously unknown. On the basis of an Angle of Arrival (AoA) system, we demonstrate the applicability and accuracy gain of our algorithm in simulation and real experiment.

[1]  Thorsten Edelh.  Autonomous Configuration Method for Real-Time Location Systems , 2009 .

[2]  J. Kemper,et al.  Human-Assisted Calibration of an Angulation Based Indoor Location System , 2008, 2008 Second International Conference on Sensor Technologies and Applications (sensorcomm 2008).

[3]  Agus Budiyono,et al.  Principles of GNSS, Inertial, and Multi-sensor Integrated Navigation Systems , 2012 .

[4]  Thia Kirubarajan,et al.  Estimation with Applications to Tracking and Navigation: Theory, Algorithms and Software , 2001 .

[5]  Randolph L. Moses,et al.  An auto-calibration method for Unattended Ground Sensors , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[6]  Fredrik Gustafsson,et al.  Adaptive filtering and change detection , 2000 .

[7]  Dan Wang,et al.  Land vehicle navigation using odometry/INS/vision integrated system , 2008, 2008 IEEE Conference on Cybernetics and Intelligent Systems.

[8]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[9]  Erik D. Demaine,et al.  Mobile-assisted localization in wireless sensor networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..