This book demonstrates bene?ts of abstract and qualitative reasoning that have not received much attention in the context of autonomous robotics before. Bremen, Christian Freksa December 2007 Director of the SFB/TR 8 Spatial Cognition Preface This book addresses spatial representations and reasoning techniques for - bile robot mapping, providing an analysis of fundamental representations and processes involved. A spatial representation based on shape information is p- posed and shape analysis techniques are developed to tackle the correspondence problem in robot mapping. A general mathematical formulation is presented to provide the formal ground for an e?cient matching of con?gurations of objects. This book is a slightly revised version of my doctoral thesis submitted to the Faculty of Mathematics and Computer Science of the University of Bremen, Germany. Manycontributeto the developmentofa dissertation,butsomeofthemstand out. Christian Freksa, I thank you for supporting and encouraging my work, for introducing me to interdisciplinary work, for giving me the freedom to develop this dissertation, and for providing an enjoyable atmosphere to work in. Longin Jan Latecki, thank you for countless in-depth discussions helping me to develop andtopositionmywork,forthefruitfulcollaboration,andformakingaresearch stay possible that has been very valuable to me. I thank the research groups in Bremen and Philadelphia for helpful discussions and feedback, in particular Jan Oliver Wallgrun. ̈ I also thank Kai-Florian Richter, Sven Bertel, and Lutz Frommberger for feedback on this work. Robert Ross, thank you for helping to proof-read this dissertation.

This important work is an attempt to synthesize two areas that need to be treated in tandem. The book brings together the fields of robot spatial mapping and cognitive spatial mapping, which share some common core problems. One would expect some cross-fertilization of research between the two areas to have occurred, yet this has begun only recently. There are now signs that some synthesis is happening, so this work is a timely one for students and engineers in robotics.

What is space? Is there space when there are objects to occupy it or is there space only when there are no objects to occupy it? Can there be space without objects? These are old philosophical questions that concern the ontology of space in the philosophical sense of ‘ontology’ – what is the nature of space? Cognitive science in general and arti?cial intelligence in particular are less c- cerned with the nature of things than with their mental conceptualizations. In spatial cognition research we address questions like What do we know about space? How is space represented? What are the representational entities? What are the rep- sentational structures? Answers to these questions are described in what is called ontologies in arti?cial intelligence. Different tasks require different knowledge, and different representations of knowledge facilitate different ways of solving problems. In this book, Jan Oliver Wallgrün develops and investigates representational structures to support tasks of autonomous mobile robots, from the acquisition of knowledge to the use of this knowledge for navigation. The research presented is concerned with the robot mapping problem, the pr- lem of building a spatial representation of an environment that is perceived by s- sors that only provide incomplete and uncertain information; this information usually needs to be related to other imprecise or uncertain information. The routes a robot can take can be abstractly described in terms of graphs where alternative routes are represented by alternative branches in these route graphs.

How should a robot represent and reason about spatial information when it needs to collaborate effectively with a human? The form of spatial representation that is useful for robot navigation may not be useful in higher-level reasoning or working with humans as a team member. To explore this question, we have extended previous work on how children and robots learn to play hide and seek to a human-robot team covertly approaching a moving target. We used the cognitive modeling system, ACT-R, with an added spatial module to support the robot's spatial reasoning. The robot interacted with a team member through voice, gestures, and movement during the team's covert approach of a moving target. This paper describes the new robotic system and its integration of metric, symbolic, and cognitive layers of spatial representation and reasoning for its individual and team behavior.

Space and time are inextricably linked. Reasoning about space often involves reasoning about change in spatial configurations. Qualitative spatial information theory encompasses spatial as well as temporal representation and reasoning. Qualitative Spatio-Temporal Representation and Reasoning: Trends and Future Directions is a contribution to the emerging discipline of qualitative spatial information theory within artificial intelligence. This collection of research covers both theory and application-centric research and provides a comprehensive perspective on the emerging area of qualitative spatio-temporal representation and reasoning. This revolutionary new field is increasingly becoming a core issue within mobile computing, GIS/spatial information systems, databases, computer vision as well as knowledge discovery and data mining.

This book is devoted to the development of adequate spatial representations for robot motion planning. Drawing upon advanced heuristic techniques from AI and computational geometry, the authors introduce a general model for spatial representation of physical objects. This model is then applied to two key problems in intelligent robotics: collision detection and motion planning. In addition, the application to actual robot arms is kept always in mind, instead of dealing with simplified models. This monograph is built upon Angel del Pobil's PhD thesis which was selected as the winner of the 1992 Award of the Spanish Royal Academy of Doctors.

This book constitutes the thoroughly refereed postproceedings of the International Conference on Spatial Cognition 2004 held in Fauenchiemsee, Germany in October 2004. The 27 revised full papers presented were carefully reviewed and selected from 50 submissions. The papers are organized in topical sections on route directions, wayfinding, and spatial behaviour; description of space, prepositions and reference; meta-models, diagrams, and maps; spatial-temporal representation and reasoning; and robot mapping and piloting.

Developments in technologies have evolved in a much wider use of technology throughout science, government, and business; resulting in the expansion of geographic information systems. GIS is the academic study and practice of presenting geographical data through a system designed to capture, store, analyze, and manage geographic information. Geographic Information Systems: Concepts, Methodologies, Tools, and Applications is a collection of knowledge on the latest advancements and research of geographic information systems. This book aims to be useful for academics and practitioners involved in geographical data.

This third volume documents the results achieved within a priority program on spatial cognition funded by the German Science Foundation (DFG). The 23 revised full papers presented went through two rounds of reviewing and improvement and reflect the increased interdisciplinary cooperation in the area. The papers are organized in topical sections on routes and navigation, human memory and learning, spatial representation, and spatial reasoning.