Experiments with a cognitive industrial robot

Abstract

Input—expectation discrepancy reduction is a ubiquitous mechanism; it permeates the human nervous system. This mechanism thus appears to be a generic strategy underlying many aspects of intelligent behavior. We have applied this paradigm to the domain of industrial robotics. In addition, we have explored some applications of human perceptual mechanisms in the visual system of the robot; the general strategy employed yielded a trade-off between efficient, intelligent decisions and errors. The result is a cognitive industrial robot that exemplifies a novel view of the industrial robotics field and serves to cast some fundamental problems, of AI as well as of robotics, in a new light. In particular, we describe a concrete application of our ideas which can be contrasted with most AI projects, functioning as they do in purely abstract domains. The concrete application introduces subproblems such as inexact matching and uncertainty with respect to all interactions with the real world, problems that abstract applications of AI theories can, and often do, avoid.