Abstract
Simultaneous localization and mapping (SLAM) is the essential technique in mapping environments that are denied to the global navigation satellite systems (GNSSs), such as indoor spaces. In this article, we present a loop-closing continuous-time LIDAR-IMU SLAM for indoor environments. The design of the proposed SLAM is based on arbitrarily-oriented planar features that allow for point to plane matching for local but also global optimization. Moreover, to update the SLAM graph during the optimization, we propose a simple yet elegant loop closure method in the form of merging the planes together. Representing the SLAM map by planes is advantageous due to the abundant existence of planar structures in indoor built environments. The proposed method was validated on a specific configuration of three 2D LIDAR scanners mounted on a wearable platform (backpack). Scanned point clouds were compared against ones obtained from a commercial mobile mapping system (Viametris iMS3D) and a terrestrial laser scanner (RIEGL VZ-400). The experimental results demonstrate that our SLAM system is capable of mapping multi-storey buildings, staircases, cluttered areas and areas with curved walls. Furthermore, our SLAM system offers comparable performance to that of the commercial system as shown by the low deviation between the point clouds generated by both systems. The majority of the cloud-to-cloud absolute distances – about 92% – are less than 3 cm.
Highlights
Three-dimensional (3D) digital models of indoor environments can be advantageous to professionals from various disciplines such as en gineering, architecture and archaeology
The Indoor mobile mapping sys tems (IMMSs) rely on simultaneous localization and mapping (SLAM) algorithm for positioning in spaces and environ ments inaccessible to the global navigation satellite systems (GNSSs)
We propose a loop-closing SLAM system that is capable of producing plane-based maps of various indoor environments in the real world
Summary
Three-dimensional (3D) digital models of indoor environments can be advantageous to professionals from various disciplines such as en gineering, architecture and archaeology. Indoor mobile mapping sys tems (IMMSs) digitize indoor environments quickly and at high levels of detail (Lehtola et al, 2017; Maboudi et al, 2017) Such systems have advantages over terrestrial laser scanners (TLS) in terms of timeconsumption and labour. The core idea of SLAM (Cadena et al, 2016) is to map unknown environments In this task, problems arise from that these environments may contain pathological geometries and from that the platform motion may be erratic (Yu and Zhang, 2019) light detection and ranging (LIDAR) SLAM degenerates in those pose configurations where the geometry of LIDAR observations is insufficient to estimate the 3D pose of the mapping system. The IMU sensor provides good short-term motion estimates (Yang et al, 2019; Karam et al, 2019), it suffers from accumulated er rors over time due to the dead reckoning-based positioning, and there fore obviously is undesirable as a stand-alone sensor for positioning purposes
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: ISPRS Journal of Photogrammetry and Remote Sensing
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
