Topographic maps are an invaluable tool for planning routes through unfamiliar terrain. However, accurately planning routes on topographic maps is a time- consuming and error-prone task. One factor is the difficulty of interpreting the map itself, which requires prior knowledge and practice. Another factor is the difficulty of making choices between possible routes that have different trade-offs between length and the terrain they traverse. To alleviate these difficulties, this thesis presents a system to automate the process of finding routes on scanned images of topographic maps. The system allows users to select any two points on a topographic map and identify their specific preferences for their route. This system extracts terrain and contour line data from topographic map images using image processing techniques and then uses the A* Search algorithm to find a route between the specified points. This system can be used as a starting point for hand-drawn routes, as a means of considering alternative routes, or to entirely replace drawing routes by hand. This thesis also presents a user study which shows that this system produces routes in a significantly shorter time than hand-drawn routes, and with a similar level of accuracy.

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.

Commercial computer gaming is a large growing industry that already has its major contributions in the entertainment industry of the world. One of the most important among different types of computer games are Real Time Strategy (RTS) based games. RTS games are considered being the major research subject for Artificial Intelligence (AI). But still the performance of AI in these games is poor by human standards due to some fundamental AI problems those require more research to be better solved for the RTS games. There also exist some AI algorithms those can help us solve these AI problems. Anytime- Algorithms (AA) are algorithms those can optimize their memory and time resources and are considered best for the RTS games. We believe that by making AI algorithms anytime we can optimize their behavior to better solve the AI problems. Although many anytime algorithms are available to solve various kinds of AI problems, but according to our research no such study is been done to compare the performances of different anytime algorithms for an AI problem in RTS games. This study will take care of that by building our own research platform specifically design for comparing performances of our selected anytime algorithms for an AI problem. / Address: NaN Mob. +46 - 737 - 40 19 17

Commercial computer gaming is a large growing industry, that already has its major contributions in the entertainment industry of the world. One of the most important among different types of computer games are Real Time Strategy (RTS) based games. RTS games are considered being the major research subject for Artificial Intelligence (AI). But still the performance of AI in these games is poor by human standards because of some broad sets of problems. Some of these problems have been solved with the advent of an open real time research platform, named as ORTS. However there still exist some fundamental AI problems that require more research to be better solved for the RTS games. There also exist some AI algorithms that can help us solve these AI problems. Anytime- Algorithms (AA) are algorithms those can optimize their memory and time resources and are considered best for the RTS games. We believe that by making AI algorithms anytime we can optimize their behavior to better solve the AI problems for the RTS games. Although many anytime algorithms are available to solve various kinds of AI problems, but according to our research no such study is been done to compare the performances of different anytime algorithms for each AI problem in RTS games. This study will take care of that by building our own research platform specifically design for comparing performances of selected anytime algorithms for an AI problem

The aim of this thesis was to implement a software that would be able to render, simulate and record a scene with walking pedestrians in real-time, with emphasis on rendering level of realism. The output of the application could serve as an input test data for people counting systems or similar systems for video recognition. The problem was divided into three major subproblems: character animation, artificial intelligence for character movement and advanced rendering techniques. The character animation problem is solved by the skeletal animation of the model. To achieve the characters moving in a scene autonomously path finding(A* algorithm) and group behaviors(steering behaviors) were implemented. Realism in a scene is added by implemented methods such as normal-mapping, variance shadow-mapping, deffered rendering, skydome, lens flare effect and screen space ambient occlusion. Optimaliaztion of the rendering was implemented using octree data structure for space partitioning. Rendering stage of a scene can be easily parametrized through implemented GUI. Implemented application provides the user with easy way of setting a scene with walking pedestrians, setting its visualization and to record the result.