Towards Robust Data Association and Feature Modeling for Concurrent Mapping and Localization

One of the most challenging aspects of concurrent mapping and localization (CML) is the problem of data association. Because of uncertainty in the origins of sensor measurements, it is difficult to determine the correspondence between measured data and features of the scene or object being observed, while rejecting spurious measurements. This paper reviews several new approaches to data association and feature modeling for CML that share the common theme of combining information from multiple uncertain vantage points while rejecting spurious data. Our results include: (1) feature-based mapping from laser data using robust segmentation, (2) map-building with sonar data using a novel application of the Hough transform for perception grouping, and (3) a new stochastic framework for making delayed decisions for combination of data from multiple uncertain vantage points. Experimental results are shown for CML using laser and sonar data from a B21 mobile robot.

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

[2]  Dana H. Ballard,et al.  Computer Vision , 1982 .

[3]  Raja Chatila,et al.  Stochastic multisensory data fusion for mobile robot location and environment modeling , 1989 .

[4]  John J. Leonard,et al.  A Computationally Efficient Method for Large-Scale Concurrent Mapping and Localization , 2000 .

[5]  Ingemar J. Cox,et al.  Modeling a Dynamic Environment Using a Bayesian Multiple Hypothesis Approach , 1994, Artif. Intell..

[6]  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).

[7]  Raja Chatila,et al.  An Experimental System for Incremental Environment Modelling by an Autonomous Mobile Robot , 1989, ISER.

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

[9]  J. M. M. Montiel,et al.  The SPmap: a probabilistic framework for simultaneous localization and map building , 1999, IEEE Trans. Robotics Autom..

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

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

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

[13]  Peter Cheeseman,et al.  On the Representation and Estimation of Spatial Uncertainty , 1986 .

[14]  Daniel E. Koditschek,et al.  Robotics Research : the ninth International Symposium , 2000 .

[15]  Petros G. Voulgaris,et al.  On optimal ℓ∞ to ℓ∞ filtering , 1995, Autom..

[16]  José A. Castellanos,et al.  Mobile Robot Localization and Map Building: A Multisensor Fusion Approach , 2000 .

[17]  Sebastian Thrun,et al.  An Online Mapping Algorithm for Teams of Mobile Robots , 2000 .

[18]  John J. Leonard,et al.  Incorporation of Delayed Decision Making into Stochastic Mapping , 2000, ISER.

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

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

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

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

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

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

[25]  Hugh F. Durrant-Whyte,et al.  An Experimental and Theoretical Investigation into Simultaneous Localisation and Map Building , 1999, ISER.

[26]  David W. Murray,et al.  Mobile Robot Localisation Using Active Vision , 1998, ECCV.

[27]  Randall Smith,et al.  Estimating Uncertain Spatial Relationships in Robotics , 1987, Autonomous Robot Vehicles.

[28]  John J. Leonard,et al.  Adaptive Mobile Robot Navigation and Mapping , 1999, Int. J. Robotics Res..