31.01.2012 ob 15:00 / P4
Prof. Wolfram Burgard
Univerza v Freiburgu
Povzetek predavanja
Probabilistic approaches have been discovered as one of the most powerful approaches to highly relevant problems in mobile robotics including robot state estimation and localization. Major challenges in the context of probabilistic algorithms for mobile robot navigation lie in the questions of how to deal with highly complex state estimation problems and how to control the robot so that it efficiently carries out its task. In this talk, I will discuss both aspects and present recently developed techniques for efficiently learning a map of an unknown environment with a mobile robot using particle filters. I will also describe how the complexity of this state estimation problem can be reduced by actively controlling the vehicle. For all algorithms I will present experimental results that have been obtained with mobile robots in real-world environments using range sensors and cameras. I will conclude the presentation with a discussion of open issues and potential directions for future research.
O predavatelju
Prof. Burgard is a professor for computer science and head of the research lab for Autonomous Intelligent Systems, Institut für Informatik, Faculty for Applied Sciences, Albert-Ludwigs-Universität Freiburg, Germany. His areas of interest lie in artificial intelligence and mobile robots. His research mainly focuses on the development of robust and adaptive techniques for state estimation and control. Over the past years he and his group have developed a series of innovative probabilistic techniques for robot navigation and control. They cover different aspects such as localization, map-building, SLAM, path-planning, exploration, and several other aspects. He was involved in deployment of several interactive mobile tour-guide robots that operated autonomously in museums and trade shows, including the first of its kind in 1997. In 2008 he and his group developed an approach that allowed a car to autonomously navigate and park itself. Prof. Burgard has published over 250 papers and articles in robotic conferences and journals. He co-authored two books in 2005, Principles of Robot Motion – Theory, Algorithms, and Implementations, and Probabilistic Robotics, that deal with topics such as robot-oriented planning and robot sensory perception in face of uncertainty.