Personal and Ubiquitous Computing

, Volume 15, Issue 1, pp 61–74

An embedded system for real-time navigation and remote command of a trained canine

  • Winard R. Britt
  • Jeffrey Miller
  • Paul Waggoner
  • David M. Bevly
  • John A. HamiltonJr
Original Article

DOI: 10.1007/s00779-010-0298-4

Cite this article as:
Britt, W.R., Miller, J., Waggoner, P. et al. Pers Ubiquit Comput (2011) 15: 61. doi:10.1007/s00779-010-0298-4

Abstract

This paper demonstrates a capability to use a developed embedded sensor suite to consistently track the position, motion behavior, and orientation of a canine. Quantifying and recording canine position and motion in real time provides a useful mechanism for objective analysis of canine trials and missions. We provide a detailed description of the sensor equipment, including the global position satellite (GPS) receiver and antenna, accelerometers, gyroscopes, and magnetometers. Sensors beyond GPS provide for higher frequency readings, a tolerance to GPS loss, and the ability to characterize canine orientation. We demonstrate integrating sensor measurements using an Extended Kalman Filter (EKF) to estimate the canine position and velocity during temporary GPS loss. The system supports the remote actuation of tone and vibration commands and reports commands in real time alongside sensor data. This extends the range at which a handler could monitor a canine and allows enhanced trial analysis using raw sensor data and visualizations. To illustrate the system capabilities, we performed a case study in the remote command and navigation of a trained canine by a professional trainer. The results of this case study are analyzed in terms of canine trial success, motion behavior analysis, and in the context of simulated GPS losses. We discuss other potential applications of the system in autonomous canine command, canine motion analysis, and non-canine applications.

Keywords

Canine augmentation technologySensor navigationSensor aggregationEmbedded systemsCanine guidance

Copyright information

© Springer-Verlag London Limited 2010

Authors and Affiliations

  • Winard R. Britt
    • 1
  • Jeffrey Miller
    • 2
  • Paul Waggoner
    • 3
  • David M. Bevly
    • 2
  • John A. HamiltonJr
    • 1
  1. 1.Department of Computer Science and Software Engineering Shelby CenterAuburn UniversityAuburnUSA
  2. 2.Department of Mechanical Engineering Ross HallAuburn UniversityAuburnUSA
  3. 3.Canine and Detection Research InstituteMcClellanUSA