Motion Signal Processing for a Remote Gas Metal Arc Welding Application

Abstract

This article covers the signal processing for a human–robot remote controlled welding application. For this purpose, a test and evaluation system is under development. It allows a skilled worker to weld in real time without being exposed to the associated physical stress and hazards. The torch movement of the welder in typical welding tasks is recorded by a stereoscopic sensor system. Due to a mismatch between the speed of the acquisition and the query rate for data by the robot control system, a prediction has to be developed. It should generate a suitable tool trajectory from the acquired data, which has to be a C 2 -continuous function. For this purpose, based on a frequency analysis, a Kalman-Filter in combination with a disturbance observer is applied. It reproduces the hand movement with sufficient accuracy and lag-free. The required algorithm is put under test on a real-time operating system based on Linux and Preempt_RT in connection to a KRC4 robot controller. By using this setup, the welding results in a plane are of good quality and the robot movement coincides with the manual movement sufficiently.

Trajectory Extrapolation for Manual Robot Remote Welding

“…Therefore, the quantized data from the stereoscopic system must be either filtered by a second-order linear filter or shaped into a two-times continuously differentiable trajectory by other means. In the paper [30] the authors propose and validate an interpolation algorithm consisting of a linear Kalman filter and a PT-2 error observer, which generates an appropriate trajectory with low latency. This algorithm is calculated on a dedicated real-time PC running Linux with the PREEMPT_RT [31] patch and the resulting trajectory was used as the input signal to the extrapolation algorithm covered in this paper.…”