A spatial reasoning system must be able to represent and manipulate the location of objects in its world model. There are two general schemes for doing this’absolute symbolic schemes based on an independent coordinate system, and relative schemes which reference objects in relation to other objects of known location. This paper is concerned strictly with the latter. Given a relative scheme, there are several possible strategies for segmenting space. Two such strategies are identified and discussed. The first, called the situation-specific strategy is the one currently being explored and employed in most spatial reasoning systems. The second, here referred to as the general-purpose or cognitive strategy is the one used by the human cognitive system. It is suggested that while both strategies have outstanding strengths and weakness, the latter holds greater potential for achieving maximal coverage with minimal resources. The paper then proceeds to describe the structure of cognitive models of locative space and to specify how such models can be built from 3-D geometric models. This description is based on a cognitively motivated implementation called SEE-TELL. SEE-TELL takes as its input a 3-D geometric model and outputs a proposition of the form locative (referent, relatum). The function which maps the input to the output is a two part heuristic procedure. The first part determines the referent and relatum and the second part assigns the locative predicate. The system can assign the predicates on, right-of/left-of, and front-of/back-of. On and right-of/left-of are, respectively, illustrative of invariant and variant locatives. Front-of/back-of allows for a conflict between an ego/observer and a canonical object. These three situations are thought to cover the different classes of problems that can arise in assigning any locative. The paper concludes by summarizing the findings, identifying the shortcomings and limitations, and making suggestions for future work.
|Number of pages||15|
|Journal||Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM|
|Publication status||Published - 1988|
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Artificial Intelligence