The Efficient Extension of Globally Consistent Scan Matching to 6 DoF
نویسندگان
چکیده
Over ten years ago, Lu and Milios presented a probabilistic scan matching algorithm for solving the simultaneous localization and mapping (SLAM) problem with 2D laser range scans, a standard in robotics. This paper presents an extension to this GraphSLAM method. Our iterative algorithm uses a sparse network to represent the relations between several overlapping 3D scans, computes in every step the 6 degrees of freedom (DoF) transformation in closed form and exploits efficient data association with cached k-d trees. Our approach leads to globally consistent 3D maps, precise 6D pose and covariance estimates, as demonstrated by various experimental results.
منابع مشابه
Globally consistent 3D mapping with scan matching
A globally consistent solution to the simultaneous localization and mapping (SLAM) problem in 2D with three degrees of freedom (DoF) poses was presented by Lu and Milios [20]. To create maps suitable for natural environments it is however necessary to consider the 6 DoF case, namely the three Cartesian coordinates and the roll, pitch and yaw angles. This article describes the extension of the p...
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