Kollaborativa robotar är ny teknik som erbjuder flexibilitet och precision för manuella arbetsuppgifter som tidigare har varit svåra att automatisera. Volvo Group Trucks Operations motorfabrik i Skövde är en pilotfabrik där nya tekniska lösningar testas innan de förs vidare i koncernen. Företaget ser att kollaborativa robotar kan ge fördelar som förbättringar i ergonomin för operatörerna samt förbättrad process- och produktkvalitet i slutmonteringen för 13L lastbilsmotorer. Projektets syfte är att undersöka möjligheter med kollaborativa robotar i slutmonteringen samt ge en djupare förståelse för robotarnas användningsområde. Projektet har avgränsats till Universal Robots, kitt, förarbete och slutmontering för 13L lastbilsmotorer. Målen är att ta fram utmärkande egenskaper för en coaktiv implementation, ta fram urvalsprinciper och samlokalisera möjliga arbetsmoment till en coaktiv station och om samlokalisering inte är möjligt, ge rekommendation om minimala egenskaper som bör finnas hos den kollaborativa roboten.  För att nå målen har en systematisk metod framställts för att säkerställa att projektet förhåller sig till problemet och målen. Kunskap har samlats in genom litteraturstudie och referensram för att ligga som grund till det praktiska arbetet. Alla arbetsmoment i område 1–4 på produktionslinjen har identifierats och analyserats för att urskilja coaktiva egenskaper som sedan har varit grunden till att ta fram urvalsprinciper. Flera av de egenskaper som har tagits fram från produktionslinjen stämmer överens med vad en Universal Robot kan utföra. Att dessa egenskaper stämmer överens visar att en kollaborativ robot är möjlig att implementera i slutmonteringen. Urvalsprinciperna har sedan använts för att samlokalisera två coaktiva stationer i produktionslinjen. Urvalsprinciperna kommer att kunna användas som beslutsunderlag för företaget vid en implementation av kollaborativa robotar. I takt med att tekniken kring kollaborativa robotar utvecklas behöver också egenskaperna och urvalsprinciperna uppdateras. / Collaborative robots are a new technology that offers flexibility and precision for manual tasks that previously have been difficult to automate. Volvo Group Trucks Operations engine plant in Skövde is a pilot plant where new technical solutions are tested before it is implemented in the rest of the company. The company sees that collaborative robots can provide benefits for the operator’s ergonomics and improved process and product quality in the final assembly of 13L truck engines. The purpose of the project is to investigate the possibilities of collaborative robots in the final assembly as well as to give a deeper understanding of the robot's field of application. The project has been defined to Universal Robots, preparation, preassembly and final assembly for 13L truck engines. The objectives are to develop distinctive features for a coactive implementation, to develop a basic analysis and to co-locate possible tasks into a coactive station and if co-location is not possible provide recommendations on minimal features that should be included in the collaborative robot. To achieve the goals, a systematic method has been prepared to ensure that the project addresses to the problem and the objectives. Knowledge has been gathered through literature studies and reference frameworks to form the basis for the practical work. All operations in areas 1-4 on the production line have been identified and analyzed to find coactive features, which has been the basis for developing a basic analysis. Several of the features that have been identified from the production line are consistent with what a Universal Robot can perform. That these features match, shows that a collaborative robot is possible to implement in the final assembly. The basic analysis has then been used to co-locate two coactive stations in the production line. The basic analysis could be used as a basis for the company in the implementation of collaborative robots. As technology of collaborative robots develops, the features and basic analysis needs to be updated.

Industrial robot programs are usually created with the programming language that the manufacturer provides. These languages are often limited to cover the common usages within the industry. However, when a more advanced program is needed, then third-party programs are often used to, e.g., locating objects using vision systems, applying correct force with force torque sensors, etc. Instead of using both the language of the robot and third-party programs to create more advanced programs, it is preferable to have one system that can fully control the robot. Such systems exist, e.g., Robot Operating System (ROS), Yet Another Robot Language (YARP), etc. These systems require more time to fully set up, but once they are set up supposedly they can be used for a lot of different applications and can be used on several industrial robots from different manufacturers. Currently, University of Skövde have robots from Universal Robots (UR) with several peripheral equipment which has limited control because the built-in language does not support it. Therefore, they need help with both investigating which robot system could be used and implementing that robot system. This thesis will prove the suitability of using ROS to control aforesaid hardware, fulfilling all the requirements. It will be also demonstrated the feasibility of ROS in the long-term, according to the future plans for this equipment in University of Skövde.

To optimize production at Tyco Electronics Czech s.r.o. I designed and implemented an automated classification cell with a collaborative manipulator Universal Robots UR5e and a Cognex camera system. The classification cell is supposed to pick up the loose parts and then optically test them, sorting the parts into output binders following the inspection results. First of all, I had to learn programming language for Universal Robots manipulators and Cognex vision system. Next step was to design and draw an electrical diagram. According to the diagram, I connected the cabinet and other peripherals. I also programmed an algorithm controlling the manipulator arm and inspecting of both cameras. Finally, I successfully tested the functionality of the entire classification cell.

The automation revolution already helps in many tasks that are now performed by robots.  Increases in the complexity of problems regarding robot manipulators require new approaches or alternatives in order to solve them. This project comprises a research in different available software for implementing easy and fast visual servoing tasks controlling a robot manipulator. It focuses on out-of-the-box solutions. Then, the tools found are applied to implement a solution for controlling an arm from Universal Robots. The task is to follow a moving object on a plane with the robot manipulator. The research compares the most popular software, the state-of-the-art alternatives, especially in computer vision and also robot control. The implementation aims to be a proof of concept of a system divided by each functionality (computer vision, path generation and robot control) in order to allow software modularity and exchangeability. The results show various options for each system to take into consideration. The implementation is successfully completed, showing the efficiency of the alternatives examined. The chosen software is MATLAB and Simulink for computer vision and trajectory calculation interfacing with Robotic Operating System (ROS). ROS is used for controlling a UR3 arm using ros_control and ur_modern_driver packages.  Both the research and the implementation present a first approach for further applications and understanding over the current technologies for visual servoing tasks. These alternatives offer different easy, fast, and flexible methods to confront complex computer vision and robot control problems.

Nowadays, the use of robots in industrial tasks is growing constantly. However, manual assembly is one area that is hard to make fully automated since manual assembly operations work with different shapes and products that require human finesse to do some operations. Humans, on the other hand, have a lot of limitations since this kind of task can be unergonomic and repetitive for operators, which can cause them stress, fatigue, repetitive stress injuries(RSI), and repetitive motion injuries. This project involved designing an insert for the gripper 2F-85 (version 3) that would allow the collaborative robot (UR5) to carry out more assembly tasks in order to relieve human workers of repetitive tasks. The insert has to handle cylindrical shapes in addition to bigger parts that the actual insert cannot handle due to its parallel stroke. For that, a detailed market analysis and insert research were conducted in the initial study. The new insert was then developed using a double-diamond design process. The needs were ranked using the Moscow prioritization method, and ideas were then generated using the brainstorming technique. The final concept was chosen using the weighted decision matrix method. After the final concept selection, computer-aided design (CAD) technology was employed to create the new insert's 3D model and its technical specifications. The mechanical behaviour of the new insert was analysed to reflect its range of workability, expressing the maximum force that it can withstand on each of its grip work surfaces without presenting plastic deformation. For this study, finite element analyses were conducted following the general method for linear structural analysis using Abaqus. Achieving an insert that can reach, transport, and assemble different shapes will help integrate collaborative robots into manual assembly processes, avoiding the cost of a new gripper.