Intelligent Control of Modular Robotic Welding Cell

Although robotic machines are routinely used for welding, such machines do not normally incorporate intelligent capabilities. We are studying the general problem of formulating usable levels of intelligence into welding machines. From our perspective, an intelligent machine should: incorporate knowledge of the welding process, know if the process is operating correctly, know if the weld it is making is good or bad, have the ability to learn from its experience to perform welds, and be able to optimize its own performance. To this end, we are researching machine architecture, methods of knowledge representation, decision making and conflict resolution algorithms, methods of learning and optimization, human/machine interfaces, and various sensors. This paper presents work on the machine architecture and the human/machine interface specifically for a robotic, gas metal arc welding cell. Although the machine control problem is normally approached from the perspective of having a central body of control in the machine, we present a design using distributed agents. This new design is loosely based on biological models of social insects. For example, in an ant colony each ant functions according to local rules of behavior [Hölldobler and Wilson, 1990, see chapters 8 and 9]. There is no “king” or “queen”, although the latter name has been given to the reproducing ant. Following a similar approach, we present a modular machine architecture in which each machine element has local rules of behavior but no single element understands how to make a weld. A prime goal of this work is to develop an architecture for an intelligent machine that will support a modular, plug and play standard. A secondary goal of this work is to formulate a human/machine interface that treats the human as an active agent in the modular structure.