One reason Qualitative Spatial Reasoning (QSR) is becoming increasingly important to Artificial Intelligence (AI) is the need for a smooth ‘human-like’ communication between autonomous agents and people. The selected, yet general, task motivating the work presented here is the scenario of an object configuration that has to be described by an observer on the ground using only relational object positions. The description provided should enable a second agent to create a map-like picture of the described configuration in order to recognize the configuration on a representation from the survey perspective, for instance on a geographic map or in the landscape itself while observing it from an aerial vehicle. Either agent might be an autonomous system or a person. Therefore, the particular focus of this work lies on the necessity to develop description and reconstruction methods that are cognitively easy to apply for a person.

This thesis presents the representation scheme QuaDRO (Qualitative Description and Reconstruction of Object configurations). Its main contributions are a specification and qualitative classification of information available from different local viewpoints into nine qualitative equivalence classes. This classification allows the preservation of information needed for reconstruction into a global frame of reference. The reconstruction takes place in an underlying qualitative grid with adjustable granularity. A novel approach for representing objects of eight different orientations by two different frames of reference is used. A substantial contribution to alleviate the reconstruction process is that new objects can be inserted anywhere within the reconstruction without the need for backtracking or rereconstructing. In addition, an approach to reconstruct configurations from underspecified descriptions using conceptual neighbourhood-based reasoning and coarse object relations is presented.

We provide a technique to reconstruct an object configuration that has been described on site by only using intrinsic and relative frames of reference into an absolute frame of reference, as seen from the survey perspective.

We present a process for reconstructing object configurations described by a set of spatial constraints of the form (A northeast B) into a two-dimensional grid. The reconstruction process is cognitively easy for a person to fulfill and guides the user to avoid typical mistakes. For underspecified object configuration descriptions we suggest a strategy to handle coarse object relationships by representing a coarse object in a way that all disjunctive basic relationships that the coarse relationship consists of are represented within one reconstruction.

We provide a technique for describing, reconstructing and updating an object constellation of moving objects. The relations between the constituent objects, in particular axis-parallel and diagonal relations, are verbally expressed using the double cross method for qualitatively characterizing relations between pairs of objects.  The same underlying representation is used to reconstruct the constellation from the given description.

In this paper we describe a qualitative approach for natural language communication about vehicle traffic. It is an intuitive and simple model that can be used as the basis for defining more detailed position descriptions and transitions. It can also function as a framework for relating different aggregation levels. We apply a diagrammatic abstraction of traffic that mirrors the different possible interpretations of it and with this the different mental abstractions that humans might make. The abstractions are kept in parallel and according to the communicative context it will be switched to the corresponding interpretation.