Collaborative Mapping for Pedestrian Navigation in Security Applications

Abstract

In rescue missions or law enforcement applications, accurate determination of every team member's position and providing this information on a map may signi�cantly improve mutual situation awareness and potentially reduce the risk of accidentally harming a team member. Furthermore, it could help keep track of the areas that have been already visited, helping the coordination of the mission at hand. Whereas in outdoors environments accurate positioning information can be obtained using a GNSS receivers, in indoor or underground environments GNSS signals are strongly disturbed and other means of localization must be called into play. Foot mounted inertial sensors or IMUs have been one of the proposed solutions, but their performance is prone to errors that grow over time. Only when the map of the environment is provided, can these IMUs perform with high accuracy. But building plans or maps of indoor and underground areas are often unavailable, outdated, incomplete and do not re ect furniture or other obstacles that also constraint the pedestrian's motion. How can a reliable map of an indoor environment be generated? FootSLAM - Simultaneous Localization and Mapping for pedestrians - is a novel technique based on foot mounted IMUs that measure the pedestrian's steps while walking. These measurements can be used to generate a map of an environment while determining the pedestrian's location within that map. FootSLAM was recently extended to FeetSLAM, the multiuser scenario in which the maps obtained by two or more pedestrians are combined to generate a more extensive and accurate map of the environment. In this paper we elaborate on di�erent deployment scenarios for Foot- SLAM and its collaborative counterpart in security and emergency applications, yet to be experimentally validated.