Fine-grained Qualitative Spatial Reasoning about Point Positions
The ability to persist in the spacial environment is, not only in the robotic context, an essential feature. Positional knowledge is one of the most important aspects of space and a number of methods to represent these information have been developed in the in the research area of spatial cognition. The basic qualitative spatial representation and reasoning techniques are presented in this thesis and several calculi are briefly reviewed. Features and applications of qualitative calculi are summarized. A new calculus for representing and reasoning about qualitative spatial orientation and distances is being designed. It supports an arbitrary level of granularity over ternary relations of points. Ways of improving the complexity of the composition are shown and an implementation of the calculus demonstrates its capabilities. Existing qualitative spatial calculi of positional information are compared to the new approach and possibilities for future research are outlined.
Code (0)
등록된 구현이 없습니다.
Tasks
Spatial ReasoningSimilar Papers 제목 키워드 기반
Towards Grounded Visual Spatial Reasoning in Multi-Modal Vision Language Models
Large vision-and-language models (VLMs) trained to match images with text on large-scale datasets of image-text pairs have shown impressive generalization ability on several vision and language tasks. Several recent work…
Image-text matchingObject LocalizationQuestion AnsweringSpatial Reasoning+3FoundationMotion: Auto-Labeling and Reasoning about Spatial Movement in Videos
Motion understanding is fundamental to physical reasoning, enabling models to infer dynamics and predict future states. However, state-of-the-art models still struggle on recent motion benchmarks, primarily due to the sc…
Spatial ReasoningBilateral Spatial Reasoning about Street Networks: Graph-based RAG with Qualitative Spatial Representations
This paper deals with improving the capabilities of Large Language Models (LLM) to provide route instructions for pedestrian wayfinders by means of qualitative spatial relations.
Spatial ReasoningESPRIT: Explaining Solutions to Physical Reasoning Tasks
Neural networks lack the ability to reason about qualitative physics and so cannot generalize to scenarios and tasks unseen during training. We propose ESPRIT, a framework for commonsense reasoning about qualitative phys…
Geospatial Narratives and their Spatio-Temporal Dynamics: Commonsense Reasoning for High-level Analyses in Geographic Information Systems
The modelling, analysis, and visualisation of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged par…
Data Integration