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Mixed reality for assembly processes programming and guiding with path optimisation
University of Skövde, School of Engineering Science.
2023 (English)Independent thesis Advanced level (degree of Master (One Year)), 12 credits / 18 HE creditsStudent thesis
Abstract [en]

BACKGROUND: The integration of robotics, and mixed reality has ushered in a substantial revolution within the realm of Industry 4.0. The incorporation of robots into the manufacturing sector plays a pivotal role in enhancing productivity, in which humans and robots collaborate with each other. However, the current robotic system operates within predefined pathways exclusively, lacking an automated mechanism for identifying obstacle free routes to facilitate the movement of robot . Also, in the Human Robot Collaboration , there exists a deficiency in visualising robot motion and status, consequently arise safety vulnerabilities for human operators.

OBJECTIVES: This thesis aims to implement a pathfinding algorithm for the robot movement using a mixed reality environment. This Mixed Reality application is used to assign targets and handle obstacles in the robot movement path. The visual guide about the robot movement path, the state of the robot and the tasks to the user that will be displayed using MR.

METHODS : In pursuit of the thesis objectives, a Mixed Reality environment was developed using Unity alongside MRTK plugins. Within this framework, an A Star pathfinding algorithm was implemented, facilitating the computation of obstacle free routes between source and destination points. This MR environment not only visualises the trajectory of the robot 's movement but also presents robot status updates and an intuitive interface for operator robot communication. The development process involved creating essential code using C# within the Visual Studio IDE. This code was subsequently deployed onto the HoloLens 2, the designated hardware device for MR applications. The positioning and alignment of virtual objects in relation to the physical world were achieved using the QR code methodology. In this context, source and destination points for the robot 's movement were symbolised as targets, while obstacles were represented by square game objects. For the control and communication of the ABB GoFa C RB 15000 robot, RAPID code was devised within Robot Studio.To guide the thesis, a constructivist philosophical paradigm was embraced, aiming to enhance efficacy. Ethical considerations were scrupulously considered for data collection, prioritising user privacy within the MR environment. Furthermore, commitment to sustainability was maintained throughout the thesis work, yielding environmental, economic, and societal advantages.

ANALYSIS: The project that was developed underwent analysis through the scenarios, including both obstacle laden and obstacle free pathfinding situations. The A Star pathfinding algorithm, effectively calculated the obstacle free routes between targets and accomplished designated robotic tasks. This implementation not only offered visual path guidance but also supplied status updates. The analysis process involved observations, video recordings, and documentation. The findings indicated that the created Mixed Reality environment indeed enhanced safety and cognitive ergonomics for the operator. This section also outlines the industrial applications of the project developed.

CONCLUSION: Successful development of a Mixed Reality environment has been achieved, aimed at enabling automated obstacle free pathfinding. This environment also offers visualisations for path and status information, with the goal of enhancing safety and cognitive ergonomics in Human Robot Collaboration. Throughout this thesis endeavour, strong attention has been paid to ethical considerations and sustainability.

Place, publisher, year, edition, pages
2023. , p. 52
Keywords [en]
Mixed reality, Hololens 2, Unity, RobotStudio, Human Robot Collaboration, Path Finding, A Star algorithm
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:his:diva-23318OAI: oai:DiVA.org:his-23318DiVA, id: diva2:1806237
Subject / course
Virtual Product Realization
Educational program
Intelligent Automation - Master's Programme, 60 ECTS
Supervisors
Examiners
Available from: 2023-10-20 Created: 2023-10-20 Last updated: 2023-12-05Bibliographically approved

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CiteExportLink to record
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Citation style
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