Combining Force and Position Measurements for the Monitoring of Robotic Assembly

Abstract

A method for combining dynamic force and static position measurements for the monitoring of assembly is presented. A multilayer perceptron (MLP) network is used as a classifier where the individual network outputs correspond to contact state transitions occuring during the assembly process. When a contact state transition occurs, the MLP output with the largest value is chosen. The recognised contact state is sent to a discrete event controller which guides the workpiece through a series of contact states to the final desired configuration. The MLP has been successfully implemented on a Motorola 68040 based VxWorks board with successful recognition rates of 94.4% and 92.0% on a training set and an independent test set, respectively. 1 Introduction Reliable monitoring of robotic assembly allows for error detection and recovery from unwanted and unexpected situations. In this paper we present a method for combining data from two common information sources; dynamic force and static pos..