The application of a dynamic error framework to robotic assembly

Abstract

The dynamic error recovery vector framework developed by P.M. Taylor and G.E. Taylor (IEEE Proc. Int. Conf. Robotics and Automation, p.1096-100, 1985) is summarized and extended. Various operators are defined for upper-bound, lower-bound, and best-guess estimates for sensor signals given a priori estimates of error causes or effects. The Bayes theorem is then used for the backwards calculation to estimate the causes of error in a robotic workcell from the sensory information. A practical illustrative example is given to demonstrate the use of the operators.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>