This project is carried out in the field of motion planning of AGVs for the company AGVE with the aim to automate the obstacle free trajectory generation process. The process of manually generating splines in AutoCAD to achieve obstacle avoidance is replaced by the automatic generation of paths by running a python script. Artificial potential field algorithm is implemented in the python script to achieve obstacle avoidance. Clothoid curve is used to create feasible trajectories for obtaining obstacle free paths. The developed program is tested and proved suitable on three scenarios including a real-life problem encountered by the company. The output obstacle free path can be manipulated using three factors which are alpha, moving the neighbours and manipulating the scaling factor for potential fields in the APF algorithm.

This thesis introduces a novel framework for enabling intelligent machines and robots with the fifth-generation (5G) cellular network technology. Autonomous robots, such as Unmanned Aerial Vehicles (UAVs), Autonomous Guided Vehicles (AGVs), and more, can notably benefit from multi-agent collaboration, human supervision, or operation guidance, as well as from external computational units such as cloud edge servers, in all of which a framework to utilize reliable communication infrastructure is needed. Autonomous robots are often employed to alleviate humans by operating demanding missions such as inspection and data collection in harsh environments or time-critical operations in industrial environments - to name a few. For delivering data to other robots to maximize the effectiveness of the considered mission, for executing complex algorithms by offloading them into the edge cloud, or for including a human operator/supervisor into the loop, the 5G network and its advanced Quality of Service (QoS) features can be employed to facilitate the establishment of such a framework. This work focuses on establishing a baseline for integrating various time-critical robotics platforms and applications with a 5G network. These applications include offloading computationally intensive Model Predictive Control (MPC) algorithms for trajectory tracking of UAVs into the edge cloud, adapting data sharing in multi-robot systems based on network conditions, and enhancing network-aware surrounding autonomy components. We have identified a set of key performance indicators (KPIs) crucially affecting the performance of network-dependent robots and applications. We have proposed novel solutions and mechanisms to meet these requirements, which aim to combine traditional robotics techniques to enhance mission reliability with the exploitation of 5G features such as the QoS framework. Ultimately, our goal was to develop solutions that adhere to the essential paradigm of co-designing robotics with networks. We thoroughly evaluated all presented research using real-life platforms and 5G networks.

Data-Driven Control (DDC) is an active field of research in modern control theory, providing exciting new methods for both model identification and controller design that leverage data to avoid time-consuming manual methods for identification and controller tuning. This thesis presents a practical application of direct Data-Driven Control where the task was to balance an instrumented bicycle at a constant velocity by controlling the steering angle. Exploring the potential of direct DDC as a stabilisation method for bicycles could improve efficiency and effectiveness in controlling similar unstable and nonlinear systems. This approach could eliminate the need for complex modelling and parameter fine-tuning which are present in alternative methods. The approach involved modifying the hardware and software of an existing instrumented bicycle, collecting data, computing direct DDC feedback gains with different state and exploratory control signal combinations, and evaluating the performance of their associated controllers through practical experiments. The study found that 14 out of 48 controllers managed to balance the instrumented bicycle, with the careful selection of states, exploratory control signals, and sufficient size of the data collection set indicating to be the important factors for successful implementation of direct DDC. The thesis provides valuable insights into the practical implementation of direct DDC on unstable and nonlinear systems and highlights potential areas for future research

An Arduino based car resembling robot equipped with heat- and ultrasonic sensors has been developed as a prototype for a rescue robot. The robot is controlled using an Android app developed in MIT App Inventor 2. In the app the sensors' information is divided in two modes; driving mode and not driving mode. The ultrasonic sensor's information is available when in driving mode, displaying the distance in centimeters straight ahead. The heat sensor's information is displayed in not driving mode, disabling motor skills, with a 8x8 pixel, blue and red color scaled picture fully updated within 2.38 seconds. An important part of the development is the Auto mode where the robot goes off on its own and signals the app user when a heat signature matching a human is detected within 35 centimeter. If the object close by is not within this temperature range, the robot turns away in another direction. Despite it's rough appearance and slow update speed, the robot fulfills the purpose of the project being able to locate a human heat signature by itself or a app user.

A large amount of people suffer from mental illnesses such as depression and autism. Receiving the care they need can be a very difficult process, with long queues and expensive bills. Automating part of the therapeutic process might be a solution to this. More patients could be treated at the same time, and the cost could be decreased. This project explores the possibilities of using a robot that paints together with patients. Such a robot would encourage the patient to be creative, which is thought to be an efficient way of improving their well-being. The painting will be done in a turn-based fashion, each taking turns adding details to the same painting. Software is developed for the robot Baxter, made by Rethink Robo\-tics. Computer vision concepts and algorithms is applied to interpret what the user has painted and construct a plan of what Baxter will paint. Painting is then done by tracing the target shape through a set of pre-defined points on a canvas. The constructed system performs fairly well - although the user is limited to painting lines, squares, rectangles and circles. Further work can be done to increase the amount of options available to the user. This system serves as a model of how a similar system could be used in reality. / En stor mängd folk lider av mentala sjukdomar som depression och autism. Att få den hjälp som dem behöver kan vara en jobbig process, med långa köer och dyra kostnader. Detta innebär att många människor lider längre tid än vad de vad de ska behöva göra, eller att de inte har råd att skaffa den hjälp som dem behöver. Att automatisera en del av den terapeutiska processen skulle kunna vara en lösning till detta. Flera patienter skulle kunna bli behandlade samtidigt och kostnaderna skulle minska. Detta projekt utforskar möojligheterna kring användning av en robot som målar tillsammans med patienter. Detta skulle uppmuntra patienterna att vara kreativa, vilket tros vara ett effektiv sätt att förbättra deras välmående. Roboten kommer måla tillsammans med patienter på ett tur-baserat vis, där var och en lägger till detaljer i samma målning. Mjukvara utvecklas till roboten Baxter, gjord av Rethink Robo\-tics. Koncept och algoritmer för datorseende appliceras för att tolka vad som använ\-daren har målat och bygga upp en plan av vad Baxter ska måla. Målandet utförs genom att spåra den slutgiltiga formen genom ett par för-definierade punkter på tavlan. Det tillverkade systemet presterar hyfsat bra - även om användaren är begr\-änsad till att rita linjer, kvadrater, rektanglar och cirklar. Fortsatt utveckling kan utöka antal valmöjligheter för användaren. Systemet agerar som en modell för hur ett liknande system skulle kunna användas i verkligheten.

Automatisering av arbetsprocesser har varit ett aktuellt tema för många verksamheter i många år. Ofta är dessa automatiseringar relaterade till fysisk automation som exempelvis robotar vid produktionslinjer. Men med dagens teknik finns det potential för att automatisera arbetsprocesser i verksamheters back-office processer. Robotic process automation, eller förkortat som RPA, är en teknik som har förmågan att imitera användarens steg i en arbetsprocess och återskapa arbetsprocessen utan den mänskliga resursen.   Denna studie har som syfte att fastställa utmaningar och möjligheter som är relaterade vid införande av RPA i verksamheter. Genom intervjuer och tidigare publicerat material om RPA, skall denna studie erbjuda en djupare förståelse kring utmaningar och möjligheter för den stigande trenden robotic process automation. / Automation has been a hot topic for many businesses for a number of years now. The term is usually related to automation of physical machinery like robots to speed up production and assembling of cars.  But with currently technology, the automation has taken a step further. Automation is now capable of automating back-office processes. Robotic Process Automation, also known as RPA, is a technology that is capable of imitating the users step in a business process and replicate it automatically, without human intervention.   The purpose of this study is to determine the challenges and opportunities related to the implementation of RPA in businesses. By performing interviews and examining existing material about RPA, this study aims to deliver a deeper and wider understanding of the rising technology that is Robotic Process Automation.

Planning and controlling traffic for multiple drones in a system without intercommunication betweenthe drones is a daunting proposition. This paper presents a thesis work developing a multi-dronecontrol system capable of planning and executing missions in a 3-D aerial space. Generic 2-D pathplanning algorithms are extended into the 3-D space to handle multiple parts of the path planning,creating highways through a gridded area which is used as obstacles for other drones.Three path planning algorithm are compared with other each other wavefront, Astar and po-tential fields, scheduling is also documented to find the optimal drone amount that the system canhandle given an area of interest, this is done to see how often and for how long drones stand idle.Simulations and equations have been implemented to verify and compare results.

Intelligent and autonomous robotic applications often require robots to have more information about their environment than provided by traditional occupancy maps. An example are semantic maps, which provide qualitative descriptions of the environment. While research in the area of semantic mapping has been performed, most robotic frameworks still offer only occupancy maps. In this thesis, a framework is developed to handle multi-layered 2D maps in ROS. The framework offers occupancy and semantic layers, but can be extended with new layer types in the future. Furthermore, an algorithm to automatically generate semantic maps from RGB-D images is presented. Software tests were performed to check if the framework fulfills all set requirements. It was shown that the requirements are accomplished. Furthermore, the semantic mapping algorithm was evaluated with different configurations in two test environments, a laboratory and a floor. While the object shapes of the generated semantic maps were not always accurate and some false detections occurred, most objects were successfully detected and placed on the semantic map. Possible ways to improve the accuracy of the mapping in the future are discussed.

Bakgrund: Exoskeletten uppfanns för användning inom militären, men forskning och utveckling av den här robottekniken har öppnat en möjlighet även till användning i rehabiliteringssyfte. Syfte: Att beskriva exoskelett för övre extremitet, ändamålet till vilket dessa används inom rehabilitering för personer med fysiska funktionsnedsättningar, samt värdet av att använda dem. Metod: Systematisk litteraturstudie. De databaser som användes var Amed, Cinahl och Medline. Genom en kombination av olika sökord resulterade sökningen i 11 artiklar som inkluderades i studien. Resultat: Åtta olika exoskelett togs med i uppsatsen. Ändamålet med de flesta exoskeletten var i huvudsak att assistera terapeuten i träning av hand och arm medan ett exoskelett användes i studier som handlade om att underlätta för användaren vid dennes ADL-utförande. Användningen av exoskeletten visade en övergripande förbättrad förmåga i bland annat motorik, rörelseomfång, muskelstyrka, reducering av tremor och i utförandet av dagliga aktiviteter. De flesta studier som handlar om exoskelett är förstudier inför större, kliniska studier. Slutsats: Att använda sig av exoskelett är en potentiell och effektiv rehabiliteringsmetod som ger möjlighet till större självständighet hos individerna. Viss utveckling krävs för ökad bekvämlighet och alla exoskelett är under vidareutveckling. Kvaliteten på materialet är medelmåttligt, varvid resultatet bör läsas med viss förbehållsamhet.

Drones or UAVs are quickly becoming a bigger part of today's society. Delivery servicesand transportation are elds were big development is being done. For the UAVs to beable to perform its given tasks safely more and more sensors are implemented.This report covers the development and implementation of a sensor system to helpan UAV to keep a xed altitude and provide proximity measurements of the environ-ment to avoid obstacles. The system is build around the ATmega328P microprocessorand uses I2C to communicate with the sensors. Measurements are ltered and pub-lished into ROS where the autopilot can reach the measurements and make decisionsbased on the readings. Additionally, simple algorithms to avoid obstacles have beenimplemented and simulated in the simulation software Gazebo. The altitude controlsystem which has been the main focus of the project has been implemented with goodresults in both simulation and real ight tests. The system will be used in a competi-tion held in Arizona, USA where the project team together with two other project willcompete in the prestigious CPS-challenge.