Human navigation and mapping with a 6DOF IMU and a laser scanner

This article focuses on human navigation, by proposing a system for mapping and self-localization based on wearable sensors, i.e., a laser scanner and a 6 Degree-of-Freedom Inertial Measurement Unit (6DOF IMU) fixed on a helmet worn by the user. The sensor data are fed to a Simultaneous Localization And Mapping (SLAM) algorithm based on particle filtering, an approach commonly used for mapping and self-localization in mobile robotics. Given the specific scenario considered, some operational hypotheses are introduced in order to reduce the effect of a well-known problem in IMU-based localization, i.e., position drift. Experimental results show that the proposed solution leads to improvements in the quality of the generated map with respect to existing approaches.

► We developed a system for human localization and mapping, suitable for first responders in search and rescue operations. ► The system is based on wearable sensors (e.g., a Inertial Measurement Unit and a laser scanner). ► We propose an original solution to reduce position drifting, a well-known problem with IMU-based dead reckoning. ► We analyse the approach theoretically, and we validate theoretical results through real-world experiments.