The need for spatial representations and spatial reasoning is ubiquitous in AI – from robot planning and navigation, to interpreting visual inputs, to understanding natural language – in all these cases the need to represent and reason about spatial aspects of the world is of key importance. Related fields of research, such as geographic information science

Abstract. This paper investigates the challenging problem of encoding the knowledge and reasoning processes involved in the common sense manipulation of physical objects. In particular we provide a formalisation of a domain involving rigid objects, holes and a string within a reasoning about actions and change framework. Therefore, this work investigates the formalisation and reasoning about flexible objects and void space (holes) in a single domain. Preliminary results of automated reasoning within this domain are also presented. 1

This thesis develops a logic-based method for constructing symbolic rep- resentations of moving objects (including the observer itself) given raw image data from a mobile robot's stereoscopic vision system. In order to accomplish this goal, we first define a qualitative spatial reasoning formalism based upon the sensor data of the robot. With this formal- ism a two-step method for image interpretation is proposed. The first step transforms sequences of raw images into descriptions of changes that occurred in consecutive frames. The second step uses abductive reasoning to infer real world events from these descriptions. Particular attention has been given to the interpretation of spatial occlusion within the proposed framework.

Our purpose in this work is to track agents' activities and to issue a report in terms of plans or procedures that are likely to be in progress, for applications such as surveillance, situation assessment, hazard detection.

In this paper we propose a spatial ontology for reasoning about holes, rigid objects and a string, taking a classical puzzle as a motivating example. In this ontology the domain is composed of spatial regions whereby a theory about holes is defined over a mereotopological basis. Within this theory we define a data structure, named chain, that facilitates a clear and efficient representation of the puzzle states and its solution. Qualitative Spatial Reasoning, Commonsense Reasoning 1

This paper addresses the problem of using logical deductions to find an explanation for changes occurred in image sequences from a mobile robot. The logic framework consists of a formalism for specifying changes in image sequences, a path-based semantics for interpreting such specifications, and an algorithm for constructing explanations for changes in image sequences from logical deductions. The main contribution of this approach is that it provides the theoretical foundations for symbolically interpreting long sequences of sensor data transitions. In practice, each snapshot taken by the robot camera represents a database state. Transitions between consecutive snapshots are modeled by changes in the database and interpreted by a state transition oracle encoding axioms about common-sense spatial reasoning. RESUMO Este artigo aborda o problema de aplicar deduções lógicas para encontrar uma explicação sobre mudanças ocorridas em sequências de imagens provenientes de um robô móvel. O formalismo lógico utilizado nesta tarefa consiste de um sistema axiomático que especifica mudanças em sequências de imagens, uma semântica baseada em caminhos para interpretar tais mudanças e um algoritmo cujo objetivo é construir explicações para mudanças em sequências de images a partir de deduções lógicas. A contribuição principal deste trabalho é o desenvolvimento de uma teoria rigorosa que fornece fundamentos precisos para interpretações simbólicas de sequências de transições em dados sensoriais. Na prática, cada cena obtida pela câmera do robô representa um estado de uma base de dados. As transições ocorridas em cenas cenas consecutivas são modeladas por mudanças na base de dados e interpretadas por um oráculo. Este oráculo implementa axiomas sobre uma teoria de raciocínio espacial qualitativo.

This paper investigates the automatic induction of spatial attention from the visual observation of objects manipulated on a table top. In this work, space is represented in terms of a novel observer-object relative reference system, named Local Cardinal System, defined upon the local neighbourhood of objects on the table. We present results of applying the proposed methodology on five distinct scenarios involving the construction of spatial patterns of coloured blocks.