Laser Welding: Techniques of Real Time Sensing and Control Development

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The AEROARMS Project: Aerial Robots with Advanced Manipulation Capabilities for Inspection and Maintenance

This article summarizes new aerial robotic manipulation technologies and methods—aerial robotic manipulators with dual arms and multidirectional thrusters—developed in the AEROARMS project for outdoor industrial inspection and maintenance (I&M). Our report deals with the control systems, including the control of the interaction forces and the compliance the teleoperation, which uses passivity to tackle the tradeoff between stability and performance the perception methods for localization, mapping, and inspection the planning methods, including a new control-aware approach for aerial manipulation. Finally, we describe a novel industrial platform with multidirectional thrusters and a new arm design to increase the robustness in industrial contact inspections. In addition, the lessons learned in applying the platform to outdoor aerial manipulation for I&M are pointed out

Vision-based Monitoring System for High Quality TIG Welding

The current study evaluates an automatic system for real-time arc welding quality assessment and defect detection. The system research focuses on the identification of defects that may arise during the welding process by analysing the occurrence of any changes in the visible spectrum of the weld pool and the surrounding area. Currently, the state-of-the-art is very simplistic, involving an operator observing the process continuously. The operator assessment is subjective, and the criteria of acceptance based solely on operator observations can change over time due to the fatigue leading to incorrect classification. Variations in the weld pool are the initial result of the chosen welding parameters and torch position and at the same time the very first indication of the resulting weld quality. The system investigated in this research study consists of a camera used to record the welding process and a processing unit which analyse the frames giving an indication of the quality expected. The categorisation is achieved by employing artificial neural networks and correlating the weld pool appearance with the resulting quality. Six categories denote the resulting quality of a weld for stainless steel and aluminium. The models use images to learn the correlation between the aspect of the weld pool and the surrounding area and the state of the weld as denoted by the six categories, similar to a welder categorisation. Therefore the models learn the probability distribution of images’ aspect over the categories considered

Real-Time Stereo Visual Servoing of a 6-DOF Robot for Tracking and Grasping Moving Objects

Robotic systems have been increasingly employed in various industrial, urban, mili-tary and exploratory applications during last decades. To enhance the robot control per-formance, vision data are integrated into the robot control systems. Using visual feedback has a great potential for increasing the flexibility of conventional robotic and mechatronic systems to deal with changing and less-structured environments. How to use visual in-formation in control systems has always been a major research area in robotics and mechatronics. Visual servoing methods which utilize direct feedback from image features to motion control have been proposed to handle many stability and reliability issues in vision-based control systems. This thesis introduces a stereo Image-based Visual Servoing (IBVS) (to the contrary Position-based Visual Servoing (PBVS)) with eye‐in‐hand configuration that is able to track and grasp a moving object in real time. The robustness of the control system is in-creased by the means of accurate 3-D information extracted from binocular images. At first, an image-based visual servoing (IBVS) approach based on stereo vision is proposed for 6 DOF robots. A classical proportional control strategy has been designed and the ste-reo image interaction matrix which relates the image feature velocity to the cameras’ ve-locity screw has been developed for two cases of parallel and non-parallel cameras in-stalled on the end-effector of the robot. Then, the properties of tracking a moving target and corresponding variant feature points on visual servoing system has been investigated. Second, a method for position prediction and trajectory estimation of the moving tar-get in order to use in the proposed image-based stereo visual servoing for a real-time grasping task has been proposed and developed through the linear and nonlinear model-ing of the system dynamics. Three trajectory estimation algorithms, “Kalman Filter”, “Recursive Least Square (RLS)” and “Extended Kalman Filter (EKF)” have been applied to predict the position of moving object in image planes. Finally, computer simulations and real implementation have been carried out to verify the effectiveness of the proposed method for the task of tracking and grasping a moving object using a 6-DOF manipulator

Open-Source TIG-Based Metal 3D-Printing

Metal 3-D printing has been relegated to high-cost proprietary high-resolution systems and low-resolution low-cost metal inert gas (MIG) systems. In order to provide a path to high-resolution, low-cost, metal 3-D printing, this manuscript proposes a new open source metal 3-D printer design based around a low-cost tungsten inert gas (TIG) welder coupled to a commercial open source self replicating rapid prototyper. Optimal printing parameters for the machine are acquired using a novel computational intelligence software. TIG has many advantages over MIG, such as having a low heat input, clean beads, and the potential for both high-resolution prints as well as insitu alloying of complex geometries. The design can be adapted to most RepRap-class systems and has a basic yet powerful free and open source software (FOSS) package for the characterization of the 3-D printer. This system can be used for fabricating custom metal scientific components and tools, near net-shape structural metal component rapid prototyping, adapting and depositing on existing metal structures, and is deployable for in-field prototyping for appropriate technology applications

Selective Darkening Filter and Welding Arc Observation for the Manual Welding Process

An optical see-through LCD (GLCD) with a resolution of n x m pixels gives the ability to selectively control the darkening in the welders view. The setup of such a Selective Auto Darkening Filter is developed and its applicability tested. The setup is done by integrating a camera into the welding operation for extracting the welding arc position properly. A prototype of a GLCD taylored for welding is mounted in the welder's view. The extraction of the welding arc position requires an enhanced video acquisition during welding. The observation of scenes with high dynamic contrast is an outstanding problem which occurs if very high differences between the darkest and the brightest spot in a scene occur. The application to welding with its harsh conditions needs the development of supporting hardware. The synchronization of the camera with the flickering light conditions of pulsed welding processes in Gas Metal Arc Welding (GMAW) stabilizes the acquisition process and allows the scene to be flashed precisely if required by compact high power LEDs. The image acquisition is enhanced by merging two different exposed images for the resulting image. These source images cover a wider histogram range than it is possible by using only a single shot image with optimal camera parameters. After testing different standard contrast enhancement algorithm a novel content based algorithm is developed. It segments the image into areas with similar content and enhances these independently