An Atlas framework for scalable mapping

This paper describes Atlas, a hybrid metrical/topological approach to SLAM that achieves efficient mapping of large-scale environments. The representation is a graph of coordinate frames, with each vertex in the graph representing a local frame, and each edge representing the transformation between adjacent frames. In each frame, we build a map that captures the local environment and the current robot pose along with the uncertainties of each. Each map's uncertainties are modeled with respect to its own frame. Probabilities of entities with respect to arbitrary frames are generated by following a path formed by the edges between adjacent frames, computed via Dijkstra's shortest path algorithm. Loop closing is achieved via an efficient map matching algorithm. We demonstrate the technique running in real-time in a large indoor structured environment (2.2 km path length) with multiple nested loops using laser or ultrasonic ranging sensors.

[1]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[2]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[3]  Karsten P. Ulland,et al.  Vii. References , 2022 .

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

[5]  Y. Bar-Shalom.  Tracking and data association , 1988 .

[6]  Yoram Koren,et al.  Real-time obstacle avoidance for fact mobile robots , 1989, IEEE Trans. Syst. Man Cybern..

[7]  조동우.  A Bayesian Method for Certainty Grids , 1989 .

[8]  John J. Leonard,et al.  Directed Sonar Sensing for Mobile Robot Navigation , 1992 .

[9]  O. Faugeras.  Three-dimensional computer vision: a geometric viewpoint , 1993 .

[10]  Marc Levoy,et al.  Feature-based volume metamorphosis , 1995, SIGGRAPH.

[11]  Jeffrey K. Uhlmann,et al.  A non-divergent estimation algorithm in the presence of unknown correlations , 1997, Proceedings of the 1997 American Control Conference (Cat. No.97CH36041).

[12]  Andrew J. Davison,et al.  Mobile Robot Navigation Using Active Vision , 1998 .

[13]  J. C. BurgesChristopher.  A Tutorial on Support Vector Machines for Pattern Recognition , 1998 .

[14]  Lindsay Kleeman,et al.  Large Scale Sonarray Mapping using Multiple Connected Local Maps , 1998 .

[15]  Roberto Manduchi,et al.  Bilateral filtering for gray and color images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[16]  Kurt Konolige,et al.  Incremental mapping of large cyclic environments , 1999, Proceedings 1999 IEEE International Symposium on Computational Intelligence in Robotics and Automation. CIRA'99 (Cat. No.99EX375).

[17]  Andrew Zisserman,et al.  Automatic reconstruction of piecewise planar models from multiple views , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[18]  Alexei A. Efros,et al.  Texture synthesis by non-parametric sampling , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[19]  Wolfram Burgard,et al.  Monte Carlo localization for mobile robots , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[20]  James F. O'Brien,et al.  Shape transformation using variational implicit functions , 1999, SIGGRAPH Courses.

[21]  Steven M. Seitz,et al.  Interactive manipulation of rigid body simulations , 2000, SIGGRAPH.

[22]  Hiromasa Suzuki,et al.  Metamorphosis of Arbitrary Triangular Meshes , 2000, IEEE Computer Graphics and Applications.

[23]  J. Tenenbaum,et al.  A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.

[24]  Benjamin Kuipers,et al.  The Spatial Semantic Hierarchy , 2000, Artif. Intell..

[25]  Henrik I. Christensen,et al.  Triangulation-based fusion of sonar data with application in robot pose tracking , 2000, IEEE Trans. Robotics Autom..

[26]  S T Roweis,et al.  Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.

[27]  Reinhard Koch,et al.  Automated reconstruction of 3D scenes from sequences of images , 2000 .

[28]  Steven J. Gortler,et al.  Feature-based cellular texturing for architectural models , 2001, SIGGRAPH.

[29]  Denis Zorin,et al.  A simple algorithm for surface denoising , 2001, Proceedings Visualization, 2001. VIS '01..

[30]  Eduardo Mario Nebot,et al.  Optimization of the simultaneous localization and map-building algorithm for real-time implementation , 2001, IEEE Trans. Robotics Autom..

[31]  Rob Miller,et al.  Outlier finding: focusing user attention on possible errors , 2001, UIST '01.

[32]  Sebastian Thrun,et al.  A Probabilistic On-Line Mapping Algorithm for Teams of Mobile Robots , 2001, Int. J. Robotics Res..

[33]  Steven M. Seitz,et al.  Interactive design of rigid-body simulations for computer animation , 2001 .

[34]  Rob Miller,et al.  Interactive Simultaneous Editing of Multiple Text Regions , 2001, USENIX ATC, General Track.

[35]  Jagnow Robert Carl,et al.  Real-time simulation of deformation and fracture of stiff materials , 2001 .

[36]  J. Leonard,et al.  Decoupled Stochastic Mapping , 2001 .

[37]  John J. Leonard,et al.  Decoupled stochastic mapping [for mobile robot & AUV navigation] , 2001 .

[38]  Patric Jensfelt,et al.  Approaches to Mobile Robot Localization in Indoor Environments , 2001 .

[39]  Juan D. Tardós,et al.  Data association in stochastic mapping using the joint compatibility test , 2001, IEEE Trans. Robotics Autom..

[40]  Hugh F. Durrant-Whyte,et al.  A solution to the simultaneous localization and map building (SLAM) problem , 2001, IEEE Trans. Robotics Autom..

[41]  Eduardo Mario Nebot,et al.  Localisation in large-scale environments , 2001, Robotics Auton. Syst..

[42]  Hugh F. Durrant-Whyte,et al.  A Bayesian Algorithm for Simultaneous Localisation and Map Building , 2001, ISRR.

[43]  Michael Bosse,et al.  Calibrated, Registered Images of an Extended Urban Area , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[44]  John J. Leonard,et al.  Robust Mapping and Localization in Indoor Environments Using Sonar Data , 2002, Int. J. Robotics Res..

[45]  Rob Miller,et al.  Multiple selections in smart text editing , 2002, IUI '02.

[46]  Michael Bosse,et al.  Mapping Partially Observable Features from Multiple Uncertain Vantage Points , 2002, Int. J. Robotics Res..

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

[48]  Alexei A. Efros,et al.  Fast bilateral filtering for the display of high-dynamic-range images , 2002 .

[49]  Hugh F. Durrant-Whyte,et al.  Simultaneous Mapping and Localization with Sparse Extended Information Filters: Theory and Initial Results , 2004, WAFR.

[50]  Leonard McMillan,et al.  A procedural approach to authoring solid models , 2002, SIGGRAPH.

[51]  Stefan B. Williams,et al.  An efficient approach to the simultaneous localisation and mapping problem , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[52]  Michael Bosse,et al.  Autonomous feature-based exploration , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[53]  Steven M. Seitz,et al.  Motion sketching for control of rigid-body simulations , 2003, TOGS.

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