Transformative industrial robot programming in surface manufacturing

Programming of industrial robots is normally carried out via so-called Teach or Offline programming methodologies. Both methodologies have associated weaknesses like a high time consumption for programming on sculptured surfaces (especially Teach), and both methodologies cannot, at the same time, carry information of the real work piece and the ideal work piece (CAD-model). To be able to see both the real and ideal world is especially important when the industrial robot is used in manufacturing processes like machining, grinding, deburring etc. where the difference between the real and ideal world represents the material removal. This paper presents a new vision based programming methodology which combines information of the real and ideal world, especially adapted for robot grinding and deburring operations. Further, the presented methodology is especially developed with simplicity in mind when it comes to man-machine communication. Thus, a standard marker pen can be used by the operator to draw the robot path directly onto the work piece. This line is captured by a vision system and finally leads to the generation of the robot path. The presented methodology is a further development of the previous work of the authors as presented (Solvang et al., 2007 and Sziebig, 2007), especially concerning optimization of the robot tool positioning with respect to a work piece surface.

A Graphical User Interface for Industrial Robot Programming in Non-Repetitive Tasks

<div class="section abstract"><div class="htmlview paragraph">This paper presents a novel approach to automated robot programming and robot integration in manufacturing domain and minimizing the dependency on manual online/offline programming. Traditional industrial robots programming is typically done by online programing via teach pendants or by offline programming tools. This presents a major challenge as it requires skilled professionals and is a time-consuming process. In today’s competitive market, factories need to harness their full potential through smart and adaptive thinking to keep pace with evolving technology, customer demand, and manufacturing processes. This requires ability to manufacture multiple products on the same production line, minimum time for changeovers and implement robotic automation for efficiency enhancement. But each custom automation piece also demands significant human efforts for development and maintenance. By integrating the Robot Operating System (ROS) with vision-based 3D model generation systems, we address these challenges effectively. A ROS-based framework has been developed to automate the manual offline robot programming and enable real-time task optimization for performing manufacturing operations such as painting, welding, and torquing. The proposed framework—Capture → Connect → Compile → Create—using RGBD camera systems to record 3D point cloud data and part details. It then connects the complete points, annotate features, interprets edges and tasks to be performed and then convert into executable robotic programs. This method significantly reduces manual programming efforts and enables rapid deployment of robotic systems across diverse tasks. The paper outlines the system architecture, implementation methodology, and integration strategy within existing manufacturing lines. Through autonomous robotic programming, this approach enhances mass customization and boosts overall manufacturing efficiency. The proposed system offers a scalable solution for smart factories aiming to achieve high productivity, flexibility, and reduced operational costs.</div></div>

Intuitive robot programming through environment perception, augmented reality simulation and automated program verification

A virtual-physical collision detection interface for AR-based interactive teaching of robot

An industrial robot is an automatic multi-purpose manipulator, programmable in three or more axes. A program written in a high-level programming language controls these robots, many of these programs involve multiple tasks controlling different robots. Data races are a common problem in concurrent and multi-threaded programming and they are of big concern for the multi-task industrial robotics programmers too. We present a static analysis method for detecting data races in multi-task programs for industrial robots. We propose a technique based on a relation that models when two or more statements from a task occur in between two or more statements in another task. Our static analysis is preceded by a manual, dynamic analysis step for ensuring consistency among tasks for one of the constructs which involves a task waiting for a particular duration. We define a set of not-occurs in-between rules to detect whether two statements in different tasks may race with each other. We have developed a prototype implementation of our tool for the Rapid programming language that is used to program industrial robots of ABB. Rapid has all the features of a typical programming language for industrial robots and hence our race detection framework will generalize to any programming language for industrial robots.

Industrial robots and cobots are widely deployed in most industrial sectors. However, robotic programming still needs a lot of time and effort in small batch sizes, and it demands specific expertise and special training, especially when various robotic platforms are required. Actual low-code or no-code robotic programming solutions are exorbitant and meager. This work proposes a novel approach for no-code robotic programming for end-users with adequate or no expertise in industrial robotic. The proposed method ensures intuitive and fast robotic programming by utilizing a finite state machine with three layers of natural interactions based on hand gesture, finger gesture, and voice recognition. The implemented system combines intelligent computer vision and voice control capabilities. Using a vision system, the human could transfer spatial information of a 3D point, lines, and trajectories using hand and finger gestures. The voice recognition system will assist the user in parametrizing robot parameters and interacting with the robot’s state machine. Furthermore, the proposed method will be validated and compared with state-of-the-art “Hand-Guiding” cobot devices within real-world experiments. The results obtained are auspicious, and indicate the capability of this novel approach for real-world deployment in an industrial context.

Modern programming of industrial robots is often based on the teach-repeat paradigm: a human operator places the robot in many key positions, for teaching its task. Then the robot can repeat a path defined by these key positions. This paper proposes a vision-based approach for the automation of the teach stage. The approach relies on a constant auto-calibration of the system. Therefore, the only requirement is a precise geometrical description of the part to process. The realism of the approach is demonstrated through the emulation of a glue application process with an industrial robot. Results in terms of precision are very promising.

The block-based approach to programming is an effective way to engage young learners in programming and the powerful ideas of computing. In this paper, we explore the potential of using this same approach in a very different programming context: industrial robotics. Using a customized language built with the Blockly library, we created a block-based interface for programming a one-armed industrial robot. This paper presents a block-based robot programming language called Robot Blockly, focusing on how the various affordances of block-based programming were utilized to make the challenge of robot programming more accessible. We also present results from a small-scale study showing adults with no prior programming experience successfully programming a virtual robot to accomplish a pick and place task. The contribution of this work is in showing the potential for block-based programming beyond young learners and classrooms.

This paper presents the use of a laser tracker for programming paths of industrial robots. The idea of operation, application, and the offered accuracy of the laser trackers are discussed. Then, the developed method of using a tracker for determining the path points of an industrial robot is presented. The requirements related to the developed method are indicated. The parameters of the industrial robot related to the repeatability and accuracy of the robots and the Absolute Accuracy option—increasing the accuracy—are characterized. The developed method is based on the accuracy of robots and the conversion of the position and orientation of individual coordinate systems. In the developed method, the robot is not used during programming and the programmer indicates the path points with the help of a retroreflector. The algorithm, which is the most important part of the developed method, has been implemented in the Rapid programming language to automate the programming process. This article provides an example of the use of the developed method to program the robot path during the grinding process. The advantages of the developed method are characterized and compared to existing solutions. In addition, the limitations and achieved accuracies are indicated.

On-line knowledge acquisition and enhancement in robotic assembly tasks

On the optimal process window for powder-based laser-directed energy deposition of AA7050 under different robot programs and scanning strategies

the deals with the implementation of the method of the trajectories generating for end effectors and control programs for industrial robots in an uncertain working environment. To generate correct trajectories, it is proposed to sequentially process data from vision systems, correct them in the human-machine interface, generate a control program in a generalized form using universal commands and then translate it into the form that a specific industrial robot requires. Experimental studies of the proposed method were carried out, which confirmed the operability and effectiveness of the proposed method.

Gesture-based control systems for industrial robotics benefit from a natural form of human machine interaction. Among the high costs of such systems, there are high requirements for safety, robustness of the gesture recognition and general applicability in the industrial environment. Novel consumer electronic sensors provide a robust recognition, reliability and adequate accuracies at low costs. We present our work on gesture-based control and programming with an emphasis on a natural definition of complex trajectories. Besides standard online programming methods, we introduce a programming technique, which enables the worker to define a movement by his body parts, e.g. the hand. Imitating the human movement, the robot can move its end-effector relatively from a starting point.

Additive manufacturing or 3D printing slowly and steadily replaces traditional subtractive manufacturing, where parts are manufactured by sequentially removing pieces of the workpiece material. In 3D printing, the material is added in layers, which enables producing parts of complex geometric shapes made from expensive metals with higher productivity and economic efficiency. In order to perform 3D printing on an industrial scale, it is necessary to combine robotics with 3D printing software. This article presents the results of the process design for 3D printing of a compressor impeller prototype. A detailed methodology of customization of the KUKA industrial robot for the 3D printing process is given. Once the impeller model was created in the CAD environment, it was cut into layers in the slicer program. Special software for offline programming of industrial robots was used to translate the program into the robot language and perform 3D printing using an experimental robotic complex. As a result, a prototype of a low-carbon steel compressor impeller was printed using a welding machine and steel wire. The developed technological process was successful and proved that an industrial robot combined with a welding machine can be used as an industrial 3D printer for printing real machine parts.