Abstract:
Systems, methods and instructions for creating building models of physical structures is disclosed. The building model may be a collection of floors defined by outlines containing regions that may be offset relative to a main region, and a collection of connectors. Connectors may have connection points for tracking, routing and sizing. Connectors may indicate elevation changes through georeferenced structural features. Signal elements may also be features that provide corrections when tracking. Feature descriptors are data that describes the structural configuration and signal elements enabling them to be matched to previously collected data in a database. User interface elements assist a user of a tracking device in collecting floor information, structural features and signal features and validating certain collected information based on previously known information. The height of floors may also be inferred based on sensor data from the tracking device.
Abstract:
Methods and systems are described for determining the elevation of tracked personnel or assets (trackees) that can take input from mounted sensors on each trackee (including barometric, inertial, magnetometer, radio frequency ranging and signal strength, light and GPS sensors), external constraints (including ranging constraints, feature constraints, and user corrections), and terrain elevation data. An example implementation of this method for determining elevation of persons on foot is described. But this method is not limited to computing elevation of personnel or to on foot movements.
Abstract:
Methods for calibrating a body-worn magnetic sensor by spinning the magnetic sensor 360 degrees to capture magnetic data; if the spin failed to produce a circle contained in an x-y plane fit a sphere to the captured data; determining offsets based on the center of the sphere; and removing the offsets that are in the z-direction. Computing a magnetic heading reliability of a magnetic sensor by determining an orientation of the sensor at one location; transforming the orientation between two reference frames; measuring a first vector associated with the magnetic field of Earth at the location; processing the first vector to generate a virtual vector when a second location is detected; measuring a second vector associated with the magnetic field of Earth at the second location; and calculating the magnetic heading reliability at the second location based on a comparison of the virtual vector and the second vector.
Abstract:
Methods for calibrating a body-worn magnetic sensor by spinning the magnetic sensor 360 degrees to capture magnetic data; if the spin failed to produce a circle contained in an x-y plane fit a sphere to the captured data; determining offsets based on the center of the sphere; and removing the offsets that are in the z-direction. Computing a magnetic heading reliability of a magnetic sensor by determining an orientation of the sensor at one location; transforming the orientation between two reference frames; measuring a first vector associated with the magnetic field of Earth at the location; processing the first vector to generate a virtual vector when a second location is detected; measuring a second vector associated with the magnetic field of Earth at the second location; and calculating the magnetic heading reliability at the second location based on a comparison of the virtual vector and the second vector.
Abstract:
Methods for calibrating a body-worn magnetic sensor by spinning the magnetic sensor 360 degrees to capture magnetic data; if the spin failed to produce a circle contained in an x-y plane fit a sphere to the captured data; determining offsets based on the center of the sphere; and removing the offsets that are in the z-direction. Computing a magnetic heading reliability of a magnetic sensor by determining an orientation of the sensor at one location; transforming the orientation between two reference frames; measuring a first vector associated with the magnetic field of Earth at the location; processing the first vector to generate a virtual vector when a second location is detected; measuring a second vector associated with the magnetic field of Earth at the second location; and calculating the magnetic heading reliability at the second location based on a comparison of the virtual vector and the second vector.
Abstract:
Disclosed herein are methods and systems for mapping irregular features. In an embodiment, a computer-implemented method may include obtaining tracking data that has dead reckoning tracking data for a tracked subject along a path and performing shape correction on the tracking data to provide a first estimate of the path.
Abstract:
Methods and systems are described for determining the elevation of tracked personnel or assets (trackees) that can take input from mounted sensors on each trackee (including barometric, inertial, magnetometer, radio frequency ranging and signal strength, light and GPS sensors), external constraints (including ranging constraints, feature constraints, and user corrections), and terrain elevation data. An example implementation of this method for determining elevation of persons on foot is described. But this method is not limited to computing elevation of personnel or to on foot movements.
Abstract:
Disclosed herein are methods and systems for mapping irregular features. In an embodiment, a computer-implemented method may include obtaining tracking data that has dead reckoning tracking data for a tracked subject along a path and performing shape correction on the tracking data to provide a first estimate of the path.
Abstract:
Methods, systems, and computer readable storage media are presented for directional scaling of inertial path data to satisfy ranging constraints. The presented techniques take into account scaling confidence information. In addition to bounding potential scale corrections based on the reliability of the inertial path and the magnetic heading confidence, the techniques bound potential scale parameters based on constraints and solve for directional scale parameters.
Abstract:
This disclosure provides techniques for the creation of maps of indoor spaces. In these techniques, an individual or a team with no mapping or cartography expertise can contribute to the creation of maps of buildings, campuses or cities. An indoor location system can track the location of contributors in the building. As they walk through indoor spaces, an application may automatically create a map based on data from motion sensors by both tracking the location of the contributors and also inferring building features such as hallways, stairways, and elevators based on the tracked contributors' motions as they move through a structure. With these techniques, the process of mapping buildings can be crowd sourced to a large number of contributors, making the indoor mapping process efficient and easy to scale up.