Abstract
In this paper, we present a novel pedestrian indoor positioning system that uses sensor fusion between a foot-mounted inertial measurement unit (IMU) and a vision-based fiducial marker tracking system. The goal is to provide an after-action review for first responders during training exercises. The main contribution of this work comes from the observation that different walking types (e.g., forward walking, sideways walking, backward walking) lead to different levels of position and heading error. Our approach takes this into account when accumulating the error, thereby leading to more-accurate estimations. Through experimentation, we show the variation in error accumulation and the improvement in accuracy alter when and how often to activate the camera tracking system, leading to better balance between accuracy and power consumption overall. The IMU and vision-based systems are loosely coupled using an extended Kalman filter (EKF) to ensure accurate and unobstructed positioning computation. The motion model of the EKF is derived from the foot-mounted IMU data and the measurement model from the vision system. Existing indoor positioning systems for training exercises require extensive active infrastructure installation, which is not viable for exercises taking place in a remote area. With the use of passive infrastructure (i.e., fiducial markers), the positioning system can accurately track user position over a longer duration of time and can be easily integrated into the environment. We evaluated our system on an indoor trajectory of 250 m. Results show that even with discrete corrections, near a meter level of accuracy can be achieved. Our proposed system attains the positioning accuracy of 0.55 m for a forward walk, 1.05 m for a backward walk, and 1.68 m for a sideways walk with a 90% confidence level.
Highlights
And reliably determining the position and heading of first responders undertaking training exercises can give valuable insight into their situational awareness of the current scenario and provide the context of the decisions made
The proposed distance-based correction was done for all three walking motion types, forward walk, sideways walk, and backward walk at 25 m, 50 m, 75 m and 100 m intervals
The appropriate distance to achieve near sub-meter accuracy for forward walking motion type is 100 m as 90% of the Euclidean distance error was 0.55 m
Summary
And reliably determining the position and heading of first responders undertaking training exercises can give valuable insight into their situational awareness of the current scenario and provide the context of the decisions made. Measuring movement requires an accurate positioning system. Various indoor positioning systems have been proposed in the past, often using technologies such as wireless infrastructure, inertial and magnetic sensing, ultrasound, and computer vision. These methods either utilise an internal mechanism to measure the change in position and orientation (known as relative positioning systems) or require an external frame of reference to localise (absolute positioning systems) [1].
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