Abstract
In emergency scenarios, such as a terrorist attack or a building on fire, it is desirable to track first responders in order to coordinate the operation. Pedestrian tracking methods solely based on inertial measurement units in indoor environments are candidates for such operations since they do not depend on pre-installed infrastructure. A very powerful indoor navigation method represents collaborative simultaneous localization and mapping (collaborative SLAM), where the learned maps of several users can be combined in order to help indoor positioning. In this paper, maps are estimated from several similar trajectories (multiple users) or one user wearing multiple sensors. They are combined successively in order to obtain a precise map and positioning. For reducing complexity, the trajectories are divided into small portions (sliding window technique) and are partly successively applied to the collaborative SLAM algorithm. We investigate successive combinations of the map portions of several pedestrians and analyze the resulting position accuracy. The results depend on several parameters, e.g., the number of users or sensors, the sensor drifts, the amount of revisited area, the number of iterations, and the windows size. We provide a discussion about the choice of the parameters. The results show that the mean position error can be reduced to ≈0.5 m when applying partly successive collaborative SLAM.
Highlights
IntroductionThe first responders usually arrive by emergency vehicles and small teams of them enter a building without knowing the floorplan
In indoor emergency scenarios, the first responders usually arrive by emergency vehicles and small teams of them enter a building without knowing the floorplan
We investigate collaborative simultaneous localization and mapping (SLAM) solely based on inertial data either resulting from a number of pedestrians that are entering an unknown building and that are following similar paths—or resulting from one pedestrian wearing multiple sensors
Summary
The first responders usually arrive by emergency vehicles and small teams of them enter a building without knowing the floorplan. The commander of the first responders on sight needs to know the positions of the first responders inside the building to coordinate their actions. Examples for such scenarios are a building on fire or policemen operations in the case of a hostage-taken, a rampage, or a terror attack. In addition to the coordination of the team members, the knowledge of the positions and the activities of the first responders are desired for the case that a first responder needs help or needs to be rescued. In the case of a fire, this information would help if an injured firefighter in operation needs assistance. For the above-mentioned applications in professional use cases, an infrastructure-less, ad-hoc applicable indoor navigation system has to be developed
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