2009
DOI: 10.1002/rob.20314
|View full text |Cite
|
Sign up to set email alerts
|

Automatic appearance‐based loop detection from three‐dimensional laser data using the normal distributions transform

Abstract: We propose a new approach to appearance-based loop detection for mobile robots, using three-dimensional (3D) laser scans. Loop detection is an important problem in the simultaneous localization and mapping (SLAM) domain, and, because it can be seen as the problem of recognizing previously visited places, it is an example of the data association problem. Without a flat-floor assumption, two-dimensional laser-based approaches are bound to fail in many cases. Two of the problems with 3D approaches that we address… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
91
0

Year Published

2012
2012
2022
2022

Publication Types

Select...
5
3

Relationship

1
7

Authors

Journals

citations
Cited by 120 publications
(112 citation statements)
references
References 22 publications
(47 reference statements)
0
91
0
Order By: Relevance
“…Using global descriptors of the local point cloud for place recognition is also proposed [13][14][15]. Rohling et al [13] propose to describe each local point cloud with a 1D histogram of point heights, assuming that the sensor keeps a constant height above the ground.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Using global descriptors of the local point cloud for place recognition is also proposed [13][14][15]. Rohling et al [13] propose to describe each local point cloud with a 1D histogram of point heights, assuming that the sensor keeps a constant height above the ground.…”
Section: Related Workmentioning
confidence: 99%
“…Finally, Iterative Closest Point (ICP) is used for computing the relative pose between point clouds. In another approach, Magnusson et al [15] split the cloud into overlapping grids and compute shape properties (spherical, linear, and several type of planar) of each cell and combine them into a matrix of surface shape histograms. Similar to other works, these descriptors are compared for recognizing places.…”
Section: Related Workmentioning
confidence: 99%
“…Alternative scan representations used for pairwise alignment include the normalized distributions transform (NDT) (Magnusson, Lilienthal, Andreasson, & Duckett, 2007), which provides a reduced representation of the scan by discretizing the scan volume. Although this scan representation was later extended to provide loop closure detection (Magnusson, Andreasson, Nüchter, & Lilienthal, 2009), these approaches were designed for localization in underground mines, where the wall structure can be exploited. Similarly, the use of planar surface patches (Pathak et al, 2010) for 3D mapping of urban disaster sites still utilized some structure inherent in the environment.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In the point-to-distribution (P2D) variant, the registration of a new scan then becomes a problem of fitting its points to the distribution, and is solved as a least-squares problem. Several proposals have been made regarding the segmentation of space [2], the representation of orientation [7], its use in loop closure [8], and the use of features instead of the full point cloud [9]. Important extensions include the distribution to distribution registration (D2D-NDT) presented in [10], the fusion of NDT with occupancy maps [11]- [14] its use with Monte-Carlo localization [15], [16], and the integration of color information in the registration [17].…”
Section: D-ndtmentioning
confidence: 99%