Robust location using system dynamics and motion constraints

To our knowledge, the indoor location system which currently achieves the best performance using inexpensive off-the-shelf equipment locates a mobile within 1.5 meters with probability 77% in hallways. Even while maintaining this accuracy, the system often reports logical errors such as the mobile in the wrong cubicle of an office or even on the wrong side of a wall when broadening the domain of application to within rooms. We propose an extension of the work using the same Markov localization framework, however incorporating system dynamics (necessitating no post-processing of the output) and motion constraints which implicitly encode the physical properties of the survey area. Our system retains the advantages of its predecessor of low cost, wireless LAN connectivity and security, and large-scale deployment, however extending the survey area from simple hallways to the whole office environment, while maintaining the same precision without logical errors.

[1]  Stephen A. Dyer,et al.  Digital signal processing , 2018, 8th International Multitopic Conference, 2004. Proceedings of INMIC 2004..

[2]  R.J. Fontana,et al.  Ultra-wideband precision asset location system , 2002, 2002 IEEE Conference on Ultra Wideband Systems and Technologies (IEEE Cat. No.02EX580).

[3]  Wolfram Burgard,et al.  Estimating the Absolute Position of a Mobile Robot Using Position Probability Grids , 1996, AAAI/IAAI, Vol. 2.

[4]  Gaetano Borriello,et al.  Location Systems for Ubiquitous Computing , 2001, Computer.

[5]  W. Burgard,et al.  Markov Localization for Mobile Robots in Dynamic Environments , 1999, J. Artif. Intell. Res..

[6]  H. Hashemi,et al.  The indoor radio propagation channel , 1993, Proc. IEEE.

[7]  Kostas E. Bekris,et al.  Robotics-Based Location Sensing Using Wireless Ethernet , 2002, MobiCom '02.

[8]  F. Raab,et al.  Magnetic Position and Orientation Tracking System , 1979, IEEE Transactions on Aerospace and Electronic Systems.

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

[10]  Michael Isard,et al.  CONDENSATION—Conditional Density Propagation for Visual Tracking , 1998, International Journal of Computer Vision.

[11]  Andy Hopper,et al.  The Anatomy of a Context-Aware Application , 1999, Wirel. Networks.