Flexible and Precision Assembly

Abstract

Recently a major trend in flexible and precision assembly automation, and in automation in general, has been in robots that can safely work next to people. Increasingly, as part of collaborative automation, such robots are also designed to collaborate as teams with other robots. These intelligent machines are called cobots, or collaborative robots, and are reducing the cost and time to install robots in many applications. Flexible and precision assembly refers to an assembly system that can build multiple similar products with little or no reconfiguration of the assembly system. It can serve as a model for some of the emerging applications in flexible and precision automation. Precision assembly implies assembly with precise motions and operations. Recently, machine learning interacting with the robots’ sensors enables robots to assemble parts and components with precision that exceeds their own motion precision. A truly flexible assembly system would enable precision assembly, include flexible part feeding, grasping, and fixturing, as well as a variety of mating and fastening processes that can be quickly added or deleted without costly engineering. There is a limited science base for how to design flexible assembly systems in a manner that will yield predictable and reliable throughputs. The emergence of geometric modeling systems (as part of CAD) has enabled work in geometric reasoning in the past few years. Geometric models have been applied in areas such as machine vision for object recognition, design, and throughput analysis of flexible part feeders, dynamic simulation of assembly stations and assembly lines. Still lacking are useful techniques for automatic model generation, planning, error representation, error prevention (avoidance), and error recovery. Future software architectures for flexible and precision automation should include geometric modeling and reasoning capabilities to support autonomous, sensor-driven systems.