MIT Talk: Information Gain-based Exploration for Mobile Robots Using Rao-Blackwellized Particle Filters

Speaker: Cyrill Stachniss , University of Freiburg
Date: Friday, December 16 2005
Time: 1:00PM to 2:00PM
Location: 32-397
Host: Nick Roy
Contact: Nicholas Roy, x3-2517, nickroy@mit.edu

Abstract:
This talk presents an integrated approach to exploration, mapping, and localization. Our algorithm uses a highly efficient Rao-Blackwellized particle filter to represent the posterior about maps and poses. It applies a decision-theoretic framework which simultaneously considers the uncertainty in the map and in the pose of the vehicle to evaluate potential actions. It trades off the cost of executing an action with the expected information gain and takes into account possible sensor measurements gathered along the path taken by the robot. We furthermore describe how to utilize the properties of the Rao-Blackwellization to efficiently compute the expected information gain. We present experimental results obtained in the real world and in simulation to demonstrate the effectiveness of our approach.

Cyrill Stachniss studied computer science at the University of Freiburg and received his MSc in 2002. Currently he is a PhD student in the research lab for autonomous intelligent systems headed by Wolfram Burgard at the University of Freiburg. His research interests lie in the areas of mobile robot exploration, SLAM, and collision avoidance. He submitted his PhD thesis titled "Exploration and Mapping with Mobile Robots" in December 2005.

Link:
http://www.informatik.uni-freiburg.de/~stachnis/pdf/stachniss05rss.pdf