[Summary Week4] Pedestrian tracking with Shoe Mounted Inertial sensors – Eric Foxlin
In this paper, the author describes NavShoe, a novel shoe-mounted inertial sensor system that is capable of tracking 6-DOF in an un-instrumented environment. The proposed system builds on the prevalent MEMS gyroscopes that report 3-DOF (orientation in space) by also providing highly accurate position estimates.
Un-instrumented inertial tracking is made feasible by the identification of alternating stationary and moving stride phases of human locomotion. The inertial sensors, being shoe-mounted, can detect this pattern. The stationary phases are used to apply zero-velocity updates (ZUPTs), to ensure that the inertial integrator’s velocity is set to zero intermittently. Another novel aspect is the feeding of ZUPTs to an Extended Kalhman Filter(EKF) to correct velocity errors, leading to error accumulation that is linear in strides as opposed to cubic. The ZUPT feedback to the EKF is able to correct for all drifts, barring yaw drift. The author minimizes this heading drift using corrective measurements obtained from a magnetic compass.
To realize the proposed system, the author employs triaxialrate-gyroscopes, accelerometers and magnetometers. To drive real-world consumption, the system is also provided with a RF transceiver that receives sensor information which is then processed by a host of stochastic prediction/correlation algorithms which yield the corrected position and orientation.
The author describes how compensating for magnetic interference was a major problem for him to solve, and discusses a scheme that allows the system to be calibrated initially and thus be subsequently free of magnetic-field distortions created by metal in shoe-soles. He also elaborates on the technique that he uses for modeling the magnetic compass output that accounts for noise as well as spatial magnetic field variations due to declination and deviation.
Finally, the author present his results of the tracking system in an indoor and an outdoor setting. The results are quite impressive, and there is only a 0.3% heading error in both settings. The author also describes a possible hybrid system that could incorporate GPS data as a position-correction term, thus making the system viable even for long treks. As extensions to his work, the author describes the possibility of using additional spatial information for improving accuracy (much akin to the GeoSpots of Argon), and also the potential to use the system for driving a HMD.
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