Reasoning about Qualitative Direction and Distance between Extended Objects using Answer Set Programming
This work addresses spatial reasoning challenges in domains like robotics or GIS, but it appears incremental as it builds upon existing calculi with extensions.
The authors tackled the problem of representing and reasoning about qualitative direction and distance between extended objects by introducing a formal framework using Answer Set Programming (ASP), extending Cardinal Directional Calculus with constraints like defaults and preferences, and developing methods for consistency checking and relation inference.
In this thesis, we introduce a novel formal framework to represent and reason about qualitative direction and distance relations between extended objects using Answer Set Programming (ASP). We take Cardinal Directional Calculus (CDC) as a starting point and extend CDC with new sorts of constraints which involve defaults, preferences and negation. We call this extended version as nCDC. Then we further extend nCDC by augmenting qualitative distance relation and name this extension as nCDC+. For CDC, nCDC, nCDC+, we introduce an ASP-based general framework to solve consistency checking problems, address composition and inversion of qualitative spatial relations, infer unknown or missing relations between objects, and find a suitable configuration of objects which fulfills a given inquiry.