Open AccessProceedings Article
Large-scale map-making
Kurt Konolige
- 25 Jul 2004
- pp 457-463
178
TL;DR: This work presents an abstraction method for postponing the growth in computation of the computation to construct the map, and solves a much smaller problem in the space of the connection graph of the map.
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Abstract: Current mapping algorithms using Consistent Pose Estimation (CPE) algorithms can successfully map areas of 104 square meters, using thousands of poses. However, the computation to construct the map grows as O(n log n), so larger maps get increasingly difficult to build. We present an abstraction method for postponing the growth in computation. This method solves a much smaller problem in the space of the connection graph of the map.
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References
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Jens-Steffen Gutmann,Kurt Konolige +1 more
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•Book Chapter
Simultaneous mapping and localization with sparse extended information filters
Sebastian Thrun,Daphne Koller,Zoubin Ghahramani,H Durrant Whyte,Ay Ng +4 more
- 16 Sep 2004
TL;DR: The notion of sparse extended information filters (SEIFs), as a new method for solving the SLAM problem, is developed, and several original constant-time results of SEIFs are presented, showing the high accuracy of the resulting maps in comparison to the computationally more cumbersome EKF solution.
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