CS&E Seminar Fri. 17 Dec. 2010, 12.00 -- Bernhard Nebel; 12:45 Alexander Kleiner @ Aula Magna
On December, 17th there will be two seminars of the Computer Science and Engineering Series
TITLE: Coming Up with Good Excuses: What To Do When No Plan Can be Found
SPEAKER: Prof. Bernhard Nebel, Institut fur Informatik, Albert-Ludwigs-Universitaet Freiburg, Germany
TIME AND LOCATION: 17 December 2010, 12.00 -- Aula Magna
When using a planner-based agent architecture, many things can go wrong. First and foremost, an agent might fail to execute one of the planned actions for some reasons. Even more annoying, however, is a situation where the agent is incompetent, i.e., unable to come up with a plan. This might be due to the fact that there are principal reasons that prohibit a successful plan or simply because the task's description is incomplete or incorrect. In either case, an explanation for such a failure would be very helpful. We will address this problem and provide a formalization of coming up with excuses for not being able to find a plan. Based on that, we will present an algorithm that is able to find excuses and demonstrate that such excuses can be found in practical settings in reasonable time.
TITLE: Hierarchical Visibility for Guaranteed Search in Large-Scale Outdoor Terrain
SPEAKER: Dr. Alexander Kleiner, Albert-Ludwigs-Universitaet Freiburg, Germany
TIME AND LOCATION: 17 December 2010, 12.45 -- Aula Magna
In this talk I present a novel approach for guaranteed search that considers a 2.5d environment represented by elevation maps. Such a representation is particularly suitable for large-scale outdoor scenarios capturing some aspects of 3d visibility and can include target heights.
In our approach we construct a graph representation of the environment by sampling strategic locations and computing their detection sets, an extended notion of visibility. From the graph we compute strategies using previous work on graph-searching. These strategies are used to coordinate a team of searchers (humans or robots) and to generate trajectories for the searchers using an appropriate classification of the terrain. In experiments we investigate the performance of our approach and provide examples including real world data sets, e.g. from Haiti, with multiple loops and elevation plateaus. Furthermore, I present results from a large-scale experiment conducted with ten participants in the wild (the Gascola robot training site near by Pittsburgh, US).
home page of the Seminars in Computer Science and Engineering Series: www.dis.uniroma1.it/~seminf