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IEEE ICRA 2012: Workshop on Stochastic Geometry in SLAM

Meeting Room 6, Saint Paul River Center,

175 West Kellogg Blvd, Saint Paul, Minnesota 55102, USA.

Friday 18. May 08.45 - 17.15.




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autonomous kayak
RFS GM
Coastal SLAM

Workshop Aims

Recent techniques from the field of Stochastic Geometry have introduced the concept of a Random Finite Set (RFS) representation of a multi target state, in multi-target tracking. Representing the feature based SLAM map state as an RFS, rather than the conventionally used random vector, is not merely a triviality of representation. Recent research has shown that Finite Set Statistics (FISST), developed for data fusion and estimation with RFSs, when applied to SLAM, eliminates the necessity of fragile map management and feature association algorithms. The RFS map concept therefore provides a robust paradigm under which the true number of features, which have entered the field(s) of view of an autonomous vehicle’s sensor(s), as well as their locations, can be jointly estimated in a Bayes optimal manner, while taking into account feature detection and false alarm probabilities. Further, estimation has little meaning without a concise notion of estimation error. Performance error metrics for SLAM will therefore be introduced, which allow SLAM map estimation error to be evaluated in its entirety.

The workshop will encompass presentations on the direct application of FISST to SLAM with an introduction to FISST, SLAM solutions in the presence of high levels of clutter in complex environments, multi-vehicle SLAM, extended target tracking and adaptive information retrieval based on visual sensors.



Tentative Schedule


08.45 Martin Adams & Ba-Ngu-Vo, Welcome and Workshop Introduction

09.00 Ronald P. Mahler, "Finite-Set Statistics and SLAM" (Slides Presented at Workshop)

10.00 Coffee Break

10.30 Ba-Ngu Vo, "Stochastic Geometry and Bayesian SLAM"
11.10 Daniel E. Clark, Chee S. Lee and Sharad Nagappa, "Single-Cluster PHD Filtering and Smoothing for SLAM Applications"
11.50 Karl Granström, Christian Lundquist, Fredrik Gustafsson and Umut Orguner, "On Extended Target Tracking Using PHD Filters"

12.30 Lunch

14.00 John Mullane, Samuel Keller and Martin Adams "Random Set Versus Vector Based SLAM in the Presence of High Clutter"
14.40
Diluka Moratuwage, Ba-Ngu Vo, Sardha Wijesoma and Danwei Wang, "Extending the Bayesian RFS SLAM Framework to Multi-Vehicle SLAM"
15.20
Philip Dames, Dinesh Thakur, Mac Schwager and Vijay Kumar, "Adaptive Information Gathering Using Visual Sensors"

16.00
Coffee Break

16.30
Panel Discussion, "The Future of Stochastic Geometry in Robotic Navigation"

17.15
End Workshop.