Closing a Million-Landmarks Loop

We present an improved version of the treemap SLAM algorithm which uses Cholesky factors for representing Gaussians and a hierarchical tree partitioning algorithm derived from the established Kernighan-Lin heuristic for graph bisection. We demonstrate the algorithm's efficiency by mapping a simulated building with 1032271 landmarks. In the end, we close a million-landmarks loop in 21 ms, providing an estimate for ap10000 selected landmarks close to the robot, or in 442 ms for computing a full estimate

[1]  R. M. Mattheyses,et al.  A Linear-Time Heuristic for Improving Network Partitions , 1982, 19th Design Automation Conference.

[2]  Peter C. Cheeseman,et al.  Estimating uncertain spatial relationships in robotics , 1986, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[3]  Bruce Hendrickson,et al.  A Multi-Level Algorithm For Partitioning Graphs , 1995, Proceedings of the IEEE/ACM SC95 Conference.

[4]  Günther Schmidt,et al.  Building a global map of the environment of a mobile robot: the importance of correlations , 1997, Proceedings of International Conference on Robotics and Automation.

[5]  Jack Dongarra,et al.  LAPACK Users' Guide, 3rd ed. , 1999 .

[6]  Stephen R. Marsland,et al.  Learning globally consistent maps by relaxation , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[7]  Udo Frese,et al.  Simultaneous Localization and Mapping - A Discussion , 2001 .

[8]  Jeffrey K. Uhlmann,et al.  Building a million beacon map , 2001, SPIE Optics East.

[9]  Sebastian Thrun,et al.  Probabilistic robotics , 2002, CACM.

[10]  Sebastian Thrun,et al.  FastSLAM: a factored solution to the simultaneous localization and mapping problem , 2002, AAAI/IAAI.

[11]  Mark A. Paskin,et al.  Thin Junction Tree Filters for Simultaneous Localization and Mapping , 2002, IJCAI.

[12]  P. Newman,et al.  SLAM in large-scale cyclic environments using the Atlas framework , 2003 .

[13]  Eduardo Mario Nebot,et al.  Solving computational and memory requirements of feature-based simultaneous localization and mapping algorithms , 2003, IEEE Trans. Robotics Autom..

[14]  Michael Bosse,et al.  Simultaneous Localization and Map Building in Large-Scale Cyclic Environments Using the Atlas Framework , 2004, Int. J. Robotics Res..

[15]  Hugh F. Durrant-Whyte,et al.  Simultaneous Localization and Mapping with Sparse Extended Information Filters , 2004, Int. J. Robotics Res..

[16]  Udo Frese.  An O(log n) algorithm for simultaneous localization and mapping of mobile robots in indoor environments , 2004 .

[17]  Tom Duckett,et al.  A multilevel relaxation algorithm for simultaneous localization and mapping , 2005, IEEE Transactions on Robotics.

[18]  Frank Dellaert,et al.  A Multifrontal QR Factorization Approach to Distributed Inference Applied to Multirobot Localization and Mapping , 2005, AAAI.

[19]  Matthew R. Walter,et al.  A Provably Consistent Method for Imposing Sparsity in Feature-Based SLAM Information Filters , 2007, ISRR.

[20]  Edwin Olson,et al.  Fast iterative alignment of pose graphs with poor initial estimates , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[21]  Udo Frese.  Treemap: An O(log n) algorithm for indoor simultaneous localization and mapping , 2006, Auton. Robots.

[22]  Udo Frese,et al.  A Discussion of Simultaneous Localization and Mapping , 2006, Auton. Robots.