The industrial robot's principal advantage over traditional automation is programmability. Robots can perform arbitrary sequences of pre-stored motions or of motions computed as functions of sensory input. This paper reviews requirements for and developments in robot programming systems. The key requirements for robot programming systems examined in the paper are in the areas of sensing, world modeling, motion specification, flow of control, and programming support. Existing and proposed robot programming systems fall into three broad categories: guiding systems in which the user leads a robot through the motions to be performed, robot-level programming systems in which the user writes a computer program specifying motion and sensing, and task-level programming systems in which the user specifies operations by their desired effect on objects. A representative sample of systems in each of these categories is surveyed in the paper.

No description available.

In this paper we propose an architecture for a new task-level system, which we call TWAIN. Task-level programming attempts to simplify the robot programming process but requiring that the user specify only goals for the physical relationships among objects, rather than the motions needed to achieve those goals. A task-level specification is meant to be completely robot independent; no positions or paths that depend on the robot geometry or kinematics are specified by the user. We have two goals for this paper. Th is first is to present a more unified t reatment of some individual pieces of r esearch in task planning, whose r elationship has not previously been d escribed. The second is to provide a new framework for further research in task-planning. This is a slightly modified version of a paper that appeared in Proceedings of Soli d Modeling by Computers: from Theory to A pplications, Research laboratories Sympo sium Series, sponsored by General Motors, Warren, Michigan, September 1983.

The increased demands for customization in manufacturing industries require new automation methods. This thesis presents the development of such a method for a cutting procedure of customized mesh trays at WIBE Group. The work aimed to automatically generate robot targets from data extracted from Autodesk AutoCAD and demonstrate the concept in ABB RobotStudio. A literature review was conducted to find an appropriate method for data extraction and conversion into robot targets. This resulted in an approach where data for the cut positions was collected by scripts created with AutoCAD’s inbuilt programming language AutoLISP. The data was then exported to a text file that could be read by the robot in the RobotStudio simulation model. By offsetting a pre-set robot target with the imported data, new robot targets for each cut were created. The developed method was tested for different types of mesh trays and cut positions. The conclusion is that the method is fully working and that the concept is user-friendly, but some improvements are needed before the concept is ready to be put into operation. For example, further measures are needed to ensure that the correct data is collected from AutoCAD and that the concept gets easier to troubleshoot. Furthermore, development work is also needed for aspects outside the purpose of this thesis, such as the robot cell layout and design of the robot tool.

This thesis outlines the evolution of computer hardware and software architectures which are suitable for the programming and control of modular robots and distributed manipulators. Fundamental aspects of automating manufacturing functions are considered and the use of flexible machines, constructed from components of a family of mechanical modules and associated control system elements, are proposed. Many of the features of these flexible machines can be identified with those of conventional industrial robots. However a broader class of manufacturing machine is represented in as much as the industrial user defines the kinematics and dynamics of the manipulator. Such flexible machines can be referred to as "modular robots" or, where the mechanical modules are arranged in concurrently operating but mechanically decoupled groups, as "distributed manipulators". The main body of the work reported centred on the design of a family of computer control system elements which can serve a range of distributed manipulator and modular robot forms. These control system elements, whose cost is commensurate with the size and complexity of the manipulator's mechanical configuration, necessarily have many of the features found in robot controllers but also require properties of reconfigurability, programmability, and control system performance for the considerable array of manipulator configurations which can be constructed.

In order to fulfill increasing production rates, new automated production technologies are required for manufacturing carbon fiber reinforced plastic components for the aerospace industry. Currently, large, double curved composite components have to be manufactured manually, which leads to high process times and poor scalability. As a consequence, a team of cooperating robots with passively adjustable end-effectors was developed, that is capable of handling dry carbon textiles and can be used for layups in double curved molds. This thesis deals with the implementation of a robot program, that performs an automated adjustment of each end-effector to the surface geometry of the manufactured part. The functional principle and the accuracy of the process are evaluated. Further, the automatically adjusted end-effectors are utilized to cooperatively layup carbon plies. The results show, that the accuracy of the automated adjusting process is sufficient to drape carbon fabrics during pick-up and automated layup is possible with this approach. In conclusion, the developed process can be integrated into a fully automated process for future experiments, but hardware inaccuracies should be improved, in order to further enhance the accuracy of the system.

Due to their programmability, robots have been used instead of traditional automation for a longtime within the industrial sector. However, programming robots is complex and time-consuming,where for example small errors can have major consequences both materially and for the peopleworking next to the robot. Trying to find simpler ways of programming industrial robots is thus ofhigh relevance. The latest technique for simplifying programming is to use either augmented realityor mixed reality, and today, several studies show that these techniques are possible. However, moreresearch on usability and limitations such tools have is necessary. This study investigates how ageneric holographic tool, which utilizes mixed reality, needs to be improved to be usable for robotprogramming in realistic industrial settings. In this study this is done by investigating limitationsof using a holographic tool and then discuss how these limitations can be reduced or eliminated.To find limitations, a prototype has been designed and developed. The prototype can visualize adigital copy of a physical robot, that can be moved into different positions which in turn createsprogram instructions. The prototype was tested at ABB Robotics with the collaborative single armYuMi robot, and with users that had different amount of experience with similar programmingtools. The results showed several possible limitations, mainly linked to potential safety risks andtechnical limitations. Additionally, some perceived physical impact was found. The most importantimprovement stated were the importance of an easy access to an emergency stop. Finally, theprototype developed during this study does not support all functionality that are included in theprogramming tools used today. Therefore, more studies need to be made to see if the result staysthe same.

Nowadays, robots have become of high importance within the manufacturing industry, as well as programming methods have evolved to adapt to the current necessities. Due to the great number of complex concepts in Robotics, the learning curve of actual robotic software can be steep for inexperienced programmers, and previous training is required. However, training that requires the use of real robots is not always available for common users because of the difficult access to the machines. In parallel, new and more powerful Mixed Reality (MR) devices have been developed, expanding the possibilities of path planning. In this project, a MR application to support robot programming for welding purposes is developed, where the targets are placed according to a work object and a welding piece. Within this application, the user can interact with several menus and objects to program the path, which can be configured and simulated in the virtual environment with reachability checking. Paths can also be exported to the real robot, where they are conducted with accurate performance. Considering the learning process, a guide can be activated to show recommended steps, and it is possible to jog the virtual robot to comprehend robot motions. In addition, two experiments are conducted to test the spatial mapping and marker detection capabilities. Finally, the benefits, limitations, and flexibility of the application are discussed considering its impact on humans, while the user experience is evaluated with a survey for further analysis. The resulting application allows the user to generate, configure and export paths through the MR environment and test them in a real robot.

The rapid advancements in Robotics and Mixed Reality (MR) have opened new avenues for intuitive human-robot interaction. In this thesis, an intuitive and accessible robot grasping application is developed using MR to enable programming using the operator’s hand movements, reducing the technical complexity associated with traditional programming. The developed application leverages the strengths of MR to provide users with an immersive and intuitive environment. It includes powerful tools such as QR code recognition for quick deployment of virtual objects or the utilization of a Virtual Station that can be placed at any desired location, allowing remote and safe control of the robot. Three modes have been implemented, including manual target placing and thorough editing of its properties, path recording of the user's hand trajectory, and real-time replication of the operator's hand movements by the robot.  To assess the effectiveness and intuitiveness of the developed application, a series of user tests are presented. These evaluations include user feedback and task completion time compared to traditional programming methods, which provide valuable insights into the application's usability, efficiency, and user satisfaction. The intuitiveness of the developed application democratizes robot programming, expanding accessibility to a wider range of users, including inexperienced operators and students. / <p>Det finns övrigt digitalt material (t.ex. film-, bild- eller ljudfiler) eller modeller/artefakter tillhörande examensarbetet som ska skickas till arkivet.</p><p>There are other digital material (eg film, image or audio files) or models/artifacts that belongs to the thesis and need to be archived.</p><p>Utbytesstudenter</p>

Le sujet de recherche est dans la continuité des travaux réalisés au cours de mon M2R sur la programmation par démonstration appliqué à la cobotique en milieu industriel. Ce sujet est à la croisée de plusieurs domaines (interaction Humain-Robot, planification automatique, apprentissage artificiel). Il s'agit maintenant d'aller au delà de ces premiers résultats obtenus au cours de mon M2R et de trouver un cadre générique pour la programmation de « cobots » (robots collaboratifs) en milieu industriel. L'approche cobotique consiste à ce qu'un opérateur humain, en tant qu'expert métier directement impliqué dans la réalisation des tâches en ligne, apprenne au robot à effectuer de nouvelles tâches et à utiliser le robot comme assistant « agile ». Dans ce contexte la thèse propose un mode d'apprentissage de type « end-user programming », c'est-à-dire simple et ne nécessitant pas d'être expert en robotique pour programmer le robot industriel Baxter. / The increasing presence of robots in industries has not gone unnoticed.Cobots (collaborative robots) are revolutionising industries by allowing robots to work in close collaboration with humans.Large industrial players have incorporated them into their production lines, but smaller companies hesitate due to high initial costs and the lack of programming expertise.In this thesis we introduce a framework that combines two disciplines, Programming by Demonstration and Automated Planning, to allow users without programming knowledge to program a robot.The user constructs the robot's knowledge base by teaching it new actions by demonstration, and associates their semantic meaning to enable the robot to reason about them.The robot adopts a goal-oriented behaviour by using automated planning techniques, where users teach action models expressed in a symbolic planning language.In this thesis we present preliminary work on user experiments using a Baxter Research Robot to evaluate our approach.We conducted qualitative user experiments to evaluate the user's understanding of the symbolic planning language and the usability of the framework's programming process.We showed that users with little to no programming experience can adopt the symbolic planning language, and use the framework.We further present our work on a Programming by Demonstration system used for organisation tasks.The system includes a goal inference model to accelerate the programming process by predicting the user's intended product configuration.