Single Reflection Spatial Voting: A Novel Method for Discovering Reflective Surfaces Using Indoor Positioning Systems

We present a novel method of using reflected pulses in indoor ultrasonic positioning systems to infer the details of reflective objects in the environment. The method is termed Single Reflection Spatial Voting (SRSV), and we perceive its major use to be in the field of pervasive computing, where automated object and surface discovery is emerging as an important feature. We demonstrate use of the method in the case of searching for vertical walls using an existing ultrasonic position sensor system (the Bat system). We find that valuable information can be extracted from reflection data using SRSV, and are able to construct a model of the room using a simple algorithm. We conclude that this method can be used to extract base data upon which to build hypotheses about the environment, given further sensor analysis. We also briefly address the potential uses of SRSV in Ultra-Wideband positioning, autonomous navigation, and map building.

[1]  Richard M. Murray,et al.  A Mathematical Introduction to Robotic Manipulation , 1994 .

[2]  Dennis A. Bohn.  Environmental Effects on the Speed of Sound , 1988 .

[3]  Gaetano Borriello.  Location Sensing Techniques , 2001 .

[4]  Andrew Martin Robert Ward,et al.  Sensor-driven computing , 1999 .

[5]  Billur Barshan,et al.  Ultrasonic surface profile determination by spatial voting , 1999 .

[6]  Richard O. Duda,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972, CACM.

[7]  Sebastian Thrun,et al.  Learning Maps for Indoor Mobile Robot Navigation. , 1996 .

[8]  O DudaRichard,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972 .

[9]  William H. Press,et al.  Numerical recipes in C , 2002 .

[10]  Andy Hopper,et al.  Using personnel movements for indoor autonomous environment discovery , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[11]  Sebastian Thrun,et al.  Learning Metric-Topological Maps for Indoor Mobile Robot Navigation , 1998, Artif. Intell..

[12]  Hari Balakrishnan,et al.  6th ACM/IEEE International Conference on on Mobile Computing and Networking (ACM MOBICOM ’00) The Cricket Location-Support System , 2022 .

[13]  Seth J. Teller,et al.  The cricket compass for context-aware mobile applications , 2001, MobiCom '01.

[14]  Andy Hopper,et al.  Implementing a Sentient Computing System , 2001, Computer.

[15]  Billur Barshan,et al.  Comparison of two methods of surface profile extraction from multiple ultrasonic range measurements , 2000 .

[16]  V. Padmanabhan,et al.  Enhancements to the RADAR User Location and Tracking System , 2000 .

[17]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).