A flexible and scalable SLAM system with full 3D motion estimation

Abstract

Abstract-For many applications in Urban Search and Rescue (USAR) scenarios robots need to learn a map of unknown environments. We present a system for fast online learning of occupancy grid maps requiring low computational resources. It combines a robust scan matching approach using a LIDAR system with a 3D attitude estimation system based on inertial sensing. By using a fast approximation of map gradients and a multi-resolution grid, reliable localization and mapping capabilities in a variety of challenging environments are realized. Multiple datasets showing the applicability in an embedded handheld mapping system are provided. We show that the system is sufficiently accurate as to not require explicit loop closing techniques in the considered scenarios. The software is available as an open source package for ROS.

A Sensor Fusion Layer to Cope with Reduced Visibility in SLAM

“…These methods rely heavily on scan matching of consecutive sensor readings, with combination of other techniques, like multi-resolution occupancy grid maps [13], or dynamic likelihood field models for measurement [14]. Despite the evident advances in research on SLAM, most approaches do not consider environments disturbed by smoke, dust, or steam.…”

“…However, a study of the current available algorithms was required in order to investigate which algorithm best fits our needs. Five 2D laser-based SLAM algorithms available in ROS were reviewed and evaluated, namely: HectorSLAM [13], GMapping [10], CoreSLAM [23], LagoSLAM [24] and KartoSLAM [25].…”

“…HectorSLAM 3 combines a 2D SLAM system based on robust scan matching and 3D navigation technique using an inertial sensing system [13]. The authors make use of the high update rate and the low distance measurement noise from modern LIDARs.…”

“…To overcome this issue, two stages are identified: increasing and decreasing smoke concentration. According to these stages, smoke 13 A "zero-crossing" is a point where the sign of a function changes (e.g. from positive to negative).…”

Automated indoor RFID inventorying using a self-guided micro-aerial vehicle

“…The laser scans are processed onboard using the HectorSLAM method [13]. This method constructs a pixelated representation of a two-dimensional floor plan by assigning each pixel to either a filled space, an empty space, or an unobserved space.…”