Spatial Visual Feedback for Robotic Arc-Welding Enforced by Inductive Machine Learning

Abstract

An intelligent system for spatial visual feedback is presented, that enables the robot's autonomy for a range of robotic assembly tasks, in particular for arc-welding, in an unstructured and ‘fixtureless’ environment. The robot's autonomy is empowered by embedded inductive inference based machine learning module which learns a welded object's structural properties in the form of geometrical properties. In particular, the system tries to recognize line segments, using a spatial (3-Dimensional) visual sensor in order to autonomously execute the objective task. The innovative result is that the recognition of the geometric primitives is done without a predefined Computer Aided Design (CAD) model, significantly improving the system's autonomy and robustness. The system is validated on real-world welding tasks.