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.

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.

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.

Focuses on acquiring spatial models of physical environments through mobile robots The robotic mapping problem is commonly referred to as SLAM (simultaneous localization and mapping). 3D maps are necessary to avoid collisions with complex obstacles and to self-localize in six degrees of freedom (x-, y-, z-position, roll, yaw and pitch angle) New solutions to the 6D SLAM problem for 3D laser scans are proposed and a wide variety of applications are presented

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.

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.

Starting with an updated description of Allen's calculus, the book proceeds with a description of the main qualitative calculi which have been developed over the last two decades. It describes the connection of complexity issues to geometric properties. Models of the formalisms are described using the algebraic notion of weak representations of the associated algebras. The book also includes a presentation of fuzzy extensions of qualitative calculi, and a description of the study of complexity in terms of clones of operations.

This book constitutes the second volume documenting the results achieved within a priority program on spatial cognition by the German Science Foundation (DFG).The 28 revised full papers presented were carefully reviewed and reflect the increased interdisciplinary cooperation in the area. The book is divided into sections on maps and diagrams, motion and spatial reference, spatial relations and spatial inference, navigation in real and virtual spaces, and spatial memory.

Spatial reasoning and planning is a core constituent in robotics, graphics, computer-aided design, and geographic information systems. After a review of previous work in the related areas, Liu and Daneshmend present a unified framework for qualitative spatial representation and reasoning. This paves the way for a generation of solutions to spatial problems where the geometric knowledge is imprecise. Many graphical illustrations and detailed algorithm descriptions help the reader to comprehend the solution paths and to develop their own applications. The book is written as a self-contained text for researchers and graduate students. The methodologies, algorithmic details, and case studies presented can be used as course material as well as a convenient reference.

Probabilistic Reasoning and Decision Making in Sensory-Motor Systems by Pierre Bessiere, Christian Laugier and Roland Siegwart provides a unique collection of a sizable segment of the cognitive systems research community in Europe. It reports on contributions from leading academic institutions brought together within the European projects Bayesian Inspired Brain and Artifact (BIBA) and Bayesian Approach to Cognitive Systems (BACS). This fourteen-chapter volume covers important research along two main lines: new probabilistic models and algorithms for perception and action, new probabilistic methodology and techniques for artefact conception and development. The work addresses key issues concerned with Bayesian programming, navigation, filtering, modelling and mapping, with applications in a number of different contexts.