Least-Squares Fitting of Two 3-D Point Sets
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
A comparison of four algorithms for estimating 3-D rigid transformations
BMVC '95 Proceedings of the 1995 British conference on Machine vision (Vol. 1)
An Algorithm for Finding Best Matches in Logarithmic Expected Time
ACM Transactions on Mathematical Software (TOMS)
Multidimensional binary search trees used for associative searching
Communications of the ACM
Exploring artificial intelligence in the new millennium
Multiview registration for large data sets
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
Heuristic-based laser scan matching for outdoor 6d SLAM
KI'05 Proceedings of the 28th annual German conference on Advances in Artificial Intelligence
Localization methods for a mobile robot in urban environments
IEEE Transactions on Robotics
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6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six degrees of freedom for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. In previous work we presented our scan matching based 6D SLAM approach [10--12, 16], where scan matching is based on the well known iterative closest point (ICP) algorithm [3]. Efficient implementations of this algorithm are a result of a fast computation of closest points. The usual approach, i.e., using k-d trees is extended in this paper. We describe a novel search strategy, that leads to significant speed-ups. Our mapping system is real-time capable, i.e., 3D maps are computed using the resources of the used Kurt3D robotic hardware.