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The diploma thesis is focused on Industry 4.0, where all essential elements of Industry 4.0 are gradually being discussed. This thesis presents the collaborative robots and their specifications are described and then the market for these robots is depicted. Subsequently, the robot cell is designed with collaborative robots ABB Yumi to serve the educational purposes. This created robotic cell is displayed exemplary role. In the last part of the thesis a risk analysis is created for this robotized workplace. This entire Risk Analysis Protocol is attached.

Hospitals are crucial aspects of society, run by incredible people that dedicate their life to caring for others. However, there are several tasks that are vital to a hospitals operation that do not require an empathic competence. One such tasks is the continuous resupply of consumable items needed to maintain necessary hygiene levels.   The Pluto concept act as a helping hand to the assistant nurses, relieving them and enabling them to spend more time with the patients and emphasizes their empathic, inherently human capabilities. The chief motivation is that nurses value the interaction with the patients the most in their work, which is also their primary task. However, they are charged with so many menial tasks that they have little time to care for their patients.

<p> Vision-based robots have been utilized for pick-and-place operations for their repeatability. Various vision-based autonomous pick and place approaches using machine learning techniques have been researched for more flexible and lightweight operations with a large dataset for training. there is rare research about human intervention for dataset. This research suggests two methods for pick-and-place with minimum human intervention </p>

In recent years, the traditional manufacturing industry is challenged worldwide with the astounding growth and advancement so-called Industry 4.0. One of the multiple objectives pursued by the industry with this technological revolution is to achieve a new enhanced standard of safety. In addition, a solution against inaccurate offline robot programming needs to be tackled. The combination of a Digital Shadow (DS) of the robot with visualisation in Mixed Reality (MR) can help to increase safety and eventually, even make the design process faster. In this survey paper, a visualisation system in MR that allows the user to overlay digital tools into a UR10e Physical Robot (PR), thus permitting the PR to interact with digital work objects is proposed. To achieve the synchronisation between the digital and real assets, a DS of the robot has been developed. The integration of the Digital Models (DMs) of tools and work objects allows the user to work with the robot without load, opening the possibility of recreating and testing in real-time experimental industrial processes.

This project focuses on the integration of Computer Vision (CV) and robotics to automate object assembly tasks using a collaborative robot. By combining both disciplines, the project aims to improve productivity and safety in multiple environments by enabling safe and efficient assembly operations. To this end, an RGBD camera will be used as a vision system to capture both color and depth data from the environment. A further aspect to highlight is the importance of education and training for operators to enhance accessibility and familiarity with manipulator robots beyond the robotics industry and for the creation of adapted paths without knowledge of conventional robot path programming. The objectives cover conducting research, developing simulation environments, implementing algorithms, and their application in both real and virtual robots. This project is intended to enhance automation and efficiency while promoting the advantages of computer vision and robotics in industrial applications.

As Industry 4.0 continues to evolve, human-robot collaboration, HRC, has become more common in industries. This study aimed to explore perceived safety in HRC within manufacturing, with a focus on the assembly processes at Volvo. The goal was to promote perceived safety among operators by applying the Human-Technology-Organization, HTO, perspective, including Safety-I, -II, and -III. A framework was developed to illustrate the aim in relation to the theory and the approach taken in the study. The Volvo case RITA, a collaborative robot designed to assist with kitting, was used as a use case in the study. Numerous interviews were conducted with organizational representatives and assembly line operators with a complementary questionnaire. Since RITA was not operational, a video of the case was utilized extensively throughout the study. Operator interviews were centered on gathering their insights on perceived safety, drawing from the above safety perspectives. The formulated recommendations emphasized the importance of comprehensive operator training and early involvement in new development processes. Various traffic rules were devised for different collaboration scenarios, and the significance of clear workspaces was underscored to maintain system efficiency. These recommendations were later validated by an organizational representative from Volvo. Lastly, the study emphasizes that while technical solutions for safety are necessary, they are not sufficient without a strong safety culture that encourages openness and collaboration. By considering technical, organizational, and human aspects of safety, this study contributes to a deeper understanding of the dynamics in HRC and lays the foundation for safe and efficient manufacturing processes.

This diploma thesis deals with design of end effector for collaborative robot which manipulates with RFID labels. The first part of this thesis is theoretical and deals with collaborative robots and end effector for these collaborative robots. The second part of this thesis is practical and begins with selecting the suitable collaborative robot to tackle this issue and then there are presented several variants of end effectors where is again chosen the suitable one. In the next step there are made design calculations for the chosen variant followed by verifications consisted of practical tests of functionality and CFD simulation. According to made verifications is developed the final construction solution of the chosen end effector variant that includes a commentary about the construction documentation. The next step consists of making risk analysis used for reducing the risks leading to increase the workplace safety. In the last part is made an estimation of the cost of eventual production of one piece of the end effector protype.

With the ever-growing market of six-axis robots in the previous years, many different kinds of robots have been introduced into the market. A smaller group of so-called collaborative robots have during this time gotten increased popularity. One of the inconveniences with this type of smaller robot is the lack of internal pneumatic capabilities, which leads to external cables and tubing. This can cause problems with the cables attaching into unintended things and coming loose which could result in production stops, machine failure or other potential damage. Another part of this is that the external cabling hinders the robots sixth axis of rotation. The need for air pressure is to supply the common pneumatic grippers that the robots often use to gain pick-and-place capabilities. Cobotech Kalmar AB is a company based in Kalmar which specializes in robot integration with these collaborative robots. The purpose of this project is to together develop a product concept that can minimize the external cabling needed on the robot while still allow full rotation in the sixth axis. On top of this, the product should have plug-and-play capabilities to decrease the installation time of a robot unit. The method to develop the results is the participatory action research (PAR), with the five different steps that the method includes: problem approach, design/planning, acquiring data, analysis and reflection. The result of the thesis shows that it is possible to decrease the external air tubes and installation time of a collaborative robot. This can be achieved while not decreasing the robots range of motion. By developing an innovative end-effector for the robot the main problems caused by pneumatic grippers can be eliminated. The conclusion of this thesis is a concept product that has one air input and five outputs. This allows for the minimization of the external air tubes needed to only one. The product has a swivel function incorporated which allows full rotation of the robots sixth axis. This together with having the valves seated in the end-effector makes this conceptual product plug-and-play. / Med en ständigt växande marknad för sexaxliga robotar de senaste åren har många olika robotar introducerats till marknaden. Av dessa har mindre kollaborativa robotar vuxit i popularitet. Ett problem med många av dessa mindre robotar är att de inte har tryckluft inbyggt i armen som många av sina större bröder vilket leder till att tryckluftslangar måste dras externt på roboten istället. Detta kan leda tillatt kabeln fastnar och rycks loss vilket i sin tur kan leda till produktionsstopp, att maskiner skadas eller annan potentiell skada på antingen maskiner eller människor.Ett annat problem med att externt dra kabel är att den hindrar robotens sjätte rotationsaxel. Anledningen till att ha tryckluft på roboten är för att ha möjlighet att installera pneumatiska gripdon. Cobotech Kalmar AB är ett företag bosatt i Kalmar som specialiserar sig på att integrera kollaborativa robotar i olika tillverkande industrier. Syftet med detta projekt är att tillsammans utveckla ett produktkoncept som minimerar de externa kablarna på roboten och ser till att roboten får full rörlighet i sin sjätte rotationsaxel. Utöver detta ska produkten arbeta mot att ha plug-and-play kapacitet för att minska installationstiden ute hos kunden. Metoden som används för att få fram resultaten var deltagande aktionsforskning,som innehåller de följande fem stegen: problemformulering, design/planering, in-samling av data och reflektion. Resultatet av denna rapport visar att det är möjligt att minska externa luftslangar samt minska installationstid på kollaborativa robotar. Detta kan göras utan att minska robotens funktion. Genom att utveckla en innovativ end-effector till Universal robots produktutbud kan man eliminera de främsta problemen med pneumatiska gripdon. Projektet har resulterat i en nära färdig konceptuell produkt som innovativt använder magnetiska miniatyrventiler tillsammans med en svivelfunktion för att enbart ha en tryckluftkabel som input till produkten. Produktens swivelfunktion frigör robotens sjätte rotations-axel. Detta tillsammans med ventilerna som sitter i produkten gör att den får plug-and-play funktion.

Human-robot Collaboration as a new paradigm in manufacturing has already been a hot topic in both manufacturing science, production research, intelligent robotics, and computer science. Due to the boost of deep learning technologies in the nearly ten years, advanced information processing technologies bring the new possibility to human-robot Collaboration. Meanwhile, machine learning-based image processing such as convolutional neural network has become a powerful tool in dealing with problems like target recognizing and locating. This kind of technologies shows potentials on robotic manufacturing and human-robot Collaboration. A challenge is to implement well-designed deep neural networks linked to a robotic system that can conduct collaborative works with the human. Accuracy and robustness need also be concerned in the development. This thesis work will address this challenge. This thesis tries to implement a solution based in Machine Learning methods for image detection which permits us to, using a low cost image solutions (RGB single camera), detect and localize manufacturing components to pick them and finish an assembly, helping the human co-workers, using an industrial robot, simplifying also the IT tasks to run it. / Människa-robot samarbete, som ett nytt paradigm inom tillverkningsindustrin, har redan blivit ett omtalat ämne inom tillverkningsvetenskapen, produktforskningen, intelligent robotik och datavetenskapen. På grund av det senaste decenniets ökning av "deep learning" teknologier kan avancerade information-processerings teknologier bringa nya möjligheter för människarobot samarbete. Under tiden har även maskininlärnings-baserad bildklassificering med "convolutional neural network" blivit ett kraftfullt verktyg för att hantera problem så som måligenkänning och lokalisering. Dessa typer av teknologier har potential att implementeras nom robotiserad tillverkning och människa-robot samarbete. En utmaning är att implementera väldesignade "convolutional neural networks" kopplat till ett robot system som kan utföra arbete i samarbete med människan. Noggranhet och robusthet behöver också avvägas i utvecklingsarbetet. Detta examensarbete kommer att ta itu med denna utmaning. Detta examensarbete försöker att implementera en lösning baserad på maskininlärnings-metoder för bildigenkänning som tillåter oss att, med hjälp av en billig bild lösning (RGB enkel kamera), detektera och lokalisera tillverkningskomponenter att plocka upp och slutföra en montering, vilket hjälper den mänskliga medhjälparen, med en industriell robot. Detta förenklar också IT-uppgifterna för att köra den.