Truly autonomous robot navigation requires an accurate map of the environment, which can for example be generated from lidar measurements or images (either monocular or stereo). Whereas in office-like environments SLAM is considered to be almost solved, the ambiguities and the irregularities that might be present in harsh and unstructured domains make SLAM still an open challenge. While numerous online state estimation approaches have been presented in the past, graph-based SLAM methods are currently undergoing a renaissance due to recent insights into the structure of the SLAM problem resulting in very efficient implementations. Graph-based solutions are typically composed of a front-end and back-end part. The front-end extracts a graph representation from sensor readings, where edges are constraints representing both the estimated trajectory of the robot from pose tracking as well as loop-closures detected by the sensors. Constraints in the graph can be contradictory since observations are always affected by noise. The challenging task of the back-end is the computation of a globally consistent arrangement of the poses given all the constraints.

This tutorial will concentrate on the essential theoretical and practical aspects of graph-based SLAM in harsh environments with emphasis on data sets generated in harsh environments, such as during RobCup Rescue and Disaster City events. The tutorial will be divided into two main sections:

Date and Format

Full day tutorial on Tuesday, October 4, 2011 at KI 2011 in Berlin.


Please go to the webpage of the KI'11 http://ki2011.de/ and go to "Partcipation --> Registration". You will find the tutorial under the workshops. Please send also an email to: alexander DOT kleiner AT liu DOT se
The registration / participation is FREE OF CHARGE!


Giorgio Dr. Giorgio Grisetti
Dept. of Systems and Computer Science
La Sapienza University of Rome
Via Ariosto 25
I-00185 Rome, Italy
grisetti AT informatik DOT uni-freiburg DOT de
Nuechti Prof. Dr. Andreas Nuechter
School of Engineering and Science
Jacobs University Bremen
Campus Ring 12
28759 Bremen, Germany
a.nuechter AT jacobs-university DOT de
A. Kleiner Dr. Alexander Kleiner
Dept. of Computer and Information Science
Linköping University
SE-581 83 Linköping, Sweden
alexander DOT kleiner AT liu DOT se

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