Visual ObservationforHybrid Intelligent Previous:

Visual ObservationforHybrid Intelligent

Introduction

A previous paper has discussed a new framework and representation for the general problem of observation [9]. That paper also asserted that the system being studied can be considered a ``hybrid'' one, due to the fact that we need to report on distinct and discrete visual states that occur in the continuous, asynchronous and three-dimensional world, from two-dimensional observations that are sampled periodically. In this work we expand that discussion to elaborate on the application of the new framework to detect error states and sequences.

The problem of observing a moving agent has been addressed in the literature extensively. It was discussed in the work addressing tracking of targets and determination of the optic flow [1], recovering 3-D parameters of different kinds of surfaces [7], and also in the context of other problems [2]. However, the need to recognize, understand, and report on different visual steps within a dynamic task was not sufficiently addressed. In particular, there is a need for high-level symbolic interpretations of the agents' actions. A previous work [9] closely examined the possibilities for errors, mistakes, and uncertainties in the visual manipulation system, observer construction process and event identification mechanisms, leading to a DEDS formulation with uncertainties.