A Knowledge Representation and Reasoning Based on Petri Nets with Spatio-Temporal Tokens

Knowledge representation of time and space, and reasoning about temporal and spatial relations, are important areas in fields such as visual object tracking, robot vision, multimedia, geographical information systems, etc. In this paper we present a formal model of knowledge representation and reasoning for spatio-temporal domains. The model is based on the high-level Petri nets called the Petri Nets with Spatio-Temporal Tokens (PNSTT), which are used as the main building block of the knowledge representation scheme called SpaTem. The SpaTem scheme integrates the theory of PNSTT and 117 spatio-temporal relations. Spatio-temporal reasoning is a spatio-temporal data-driven process based on a combination of nine spatial and thirteen temporal relations adopted for robot-vision applications, where the objects in the scene are represented by their centroids. An illustrative example of spatiotemporal reasoning for two mobile robots on a two-dimensional grid world is described.