Imagine a scenario in which you arrive at a client’s site for the first time. Within five minutes you have your gear unpacked and ready to scan. The client shows you around offices and meeting rooms, up and down stairways to access multiple floors, through their warehouse and unstructured outdoor areas. After forty minutes, you arrive in the cafeteria, where you instantly present a high-resolution 3D model of the site on your tablet to your guide over a cup of coffee. You hand over a USB stick with the data, shake hands, and head over to an industrial site across town for your next data acquisition session. Rather than spending days with a team of people moving heavy equipment around a building, a 3D point cloud is now generated in the same time it takes a single person to walk through a building.
How is this scenario possible without the use of high grade positioning from GPS/INS or the time consuming setup and surveying of target markers? While there has been rapid progress in the development of commercial outdoor mobile mapping solutions, transition to indoor environments has proven to be a far more challenging problem. Central to the development of mobile mapping solutions is the ability to determine the trajectory of the LiDAR sensor in order to project range measurements to a common coordinate frame. In outdoor systems, this trajectory can be determined directly from GPS/GNSS measurements, where short periods of no or poor GPS/GNSS information can generally be handled by the use of local inertial measurements to estimate location.
In the case of indoor environments however, there is typically either no or very poor positioning information available. While technologies for indoor location using RF or radar information are emerging, these typically have fairly poor precision (>1m error) and require significant additional infrastructure to be placed within buildings. Likewise, where inertial measurements are effective for estimating position over short time periods, the error drift over longer durations indicates that this is not a satisfactory means to obtain accurate trajectory information indoors.
Researchers at the CSIRO ICT Centre in Australia have been tackling this very problem of achieving accurate 3D-mapping in environments where GPS is unreliable or unavailable over extended time periods. Not only is the challenge to derive maps without the aid of additional external infrastructure for localization, it is also to acquire the required measurements via a hardware platform that is lightweight and portable–enabling a user to map while walking through any indoor environment.
The CSIRO solution that enables this vision is a handheld 3D mapping system called Zebedee. Zebedee consists of a lightweight LiDAR scanner with 30m (100ft) maximum range and an industrial-grade MEMS inertial measurement unit (IMU) mounted on a simple spring mechanism
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