Laser scanners are essential for many industrial applications such as inspection, metrology, assembly, and welding. Laser scanners are especially interesting in robotic welding to determine the shape and position of the welding groove. There is a wide range of commercial laser scanners available in the market, still, they exhibit some limitations when scanning reflective metals like aluminium, which poses a challenge when laser scanners are used for robotic welding of aluminium. In this paper, a novel laser scanning solution is presented based on a polarization image sensor, which minimizes unwanted reflections when scanning metallic surfaces. The hardware and software architectures are detailed in the paper. The proposed system is validated in experiments with the aluminium alloy 6082 where the system is able to detect the shape of a laser profile with higher precision than a standard image sensor-based laser scanner.

In this work, we propose a novel pipeline method for laser line extraction from images with a polarization image sensor. The proposed method is specially developed for strong laser beam reflections from metal surfaces. For the pre-processing stage, we propose a demosaicing algorithm for color polarizer filter array (CPFA) sensors. This can be implemented by using either one quarter or full resolution of the sensor. In addition, we propose two methods for optimizing the information available in a 12-channel color polarization image: The first method, is based on the minimum linearly polarized irradiance, and the second method, is based on the linear polarization intensity. These preprocessing, and optimization methods are combined with laser line extraction methods. The laser line extraction is done with either the Polarized Finite Impulse Response (FIR) Center Of Gravity (COG), where the laser line coordinates are computed from the filtered laser intensity distribution, or with the Polarized FIR-Peak, where the laser line coordinates are calculated from the first derivative of the filtered laser signal. The performance of the proposed algorithms is studied experimentally using a laser line scanner assembly, made of a polarization camera, and a laser line projector operating in the blue wavelength range.

Automation and the use of robots for welding operations is an important research topic. Being able to automate and, thus, save time for setting up and using robotic welding for complex, large-scale structures made of reflective materials, such as aluminium, will provide clear economic and competitive advantages. However, challenges coming from the ability to accurately detect and calibrate the robot for a given physical workpiece in addition to noises, such as the reflections, make it hard to develop and demonstrate a feasible automation solution. This paper proposes combining laser line scanning technology with CAD-based analysis of a workpiece geometry to support the identification of relevant elements of the workpiece in the physical world and thus support welding operations. An extendable trigger definition method is proposed to identify features of interest in a workpiece. The method can potentially support the execution of welding sequences, which in our case can be represented as a sequence of triggers that have to be observed and followed at the robot runtime to weld the workpiece together.