Affordance Based Approach to Automatic Program Generation for Industrial Robots in Manufacturing

Abstract

Due to the increasing demand for flexible and low-cost production, manufacturing solutions involving human robot interaction have become much sought-after. Robotic manufacturers meet the demand with a rising number of low cost robots specifically designed around safety and usability. However, the programming is still based on a tool centric teach-in. This paper discusses an affordance based approach for process programming in industrial manufacturing. Using low level feature detection and a consecutive evaluation, a fast programming method for industrial applications is presented. The paper presents the concept and a prototypic implementation for a welding process. Using the affordance detection, the system is able to identify relevant seams based on an image of the work space. The identified seams are then presented to the user for review with the means of augmented reality. Lastly, the system derives a welding program based on the detected seams. First experiments show promising results concerning programming speed and path accuracy for different work piece shapes and task definitions. Finally, based on the experience gained with the prototype, the outlook discusses the possibilities and further fields for future work.