Robot-Based Machining of Unmodeled Objects via Feature Detection in Dense Point Clouds

Abstract

Machining applications using robots are still not common in industrial settings. Reasons are the unintuitive programming concepts which typically require expert knowledge and the inflexibility regarding small alterations of the workpieces. We present a prototypical solution for an intuitive and flexible robotic machining concept for unmodeled work pieces. For this we use a high resolution laser scanner to record very dense point clouds. Algorithms to detect linear edges with obtuse angled corners, linear edges with acute angled corners, linear inner edges and circular edges were developed, demonstrated and validated. To accurately execute generated trajectories in practice, an algorithm to directly calibrate the transformation between the sensor and the milling tool was developed. For the algorithms and the calibration process a repeatability tolerance of 0.2 mm is achieved.