Denna rapport beskriver framtagningen av en automatiserad pulsationsrigg som är utvecklad för test av skivbromsar. Utvecklingen av den automatiserade pulsationsriggen riktar sig mot att designa och konstruera ett automatiserat system. Målet med projektet är att utveckla en systemlösning med möjligheten att övervaka och logga mätdata från varje körd testcykel för att uppnå bättre spårbarhet. Metoderna som har undersökts, utvärderats och tillämpats är befintliga lösningar inom givare som mäter kraft och slag, test-och mätsystem för dataloggning samt mjukvara för styrning av testprogram.  Arbetet resulterade i utveckling av två delsystem där hårdvaran för testriggen utgör det första delsystemet. Hårdvaran består av en magnetisk lägesgivare som mäter slag, trådtöjningsgivare och lastcell som mäter kraft. Test- och mätsystemet som är länken mellan givarna och mjukvaran består av en CompaqDAQ med tillhörande moduler utvecklat av National Instrument. Mjukvaran utgör det andra delsystemet där LabVIEW har använts för uppbyggnaden av det automatiserade testprogrammet och användargränssnitt för användaren. / This report describes the development of an automated pulsation testrig developed for testing air disc brakes. The aim of the project is to develop a system solution with the ability to monitor and log measurement data from each test cycle to achieve better traceability of each test. The methods that have been investigated, evaluated and applied are existing solutions in sensors that measure force and stroke, test and measurement systems for data acquisition, and software for control test programs. The work resulted in development of two subsystems where the hardware for the test rig is the first subsystem. The hardware consists of a magnetic displacement sensor for stroke measurements, strain gauges and load cells for force measurement. The test and measurement system that is the link between the sensors and the software consists of a CompaqDAQ and associated modules developed by National Instrument. The development of software is the second subsystem where LabVIEW has been used to build the automated test program and user interface.

For social robots to move and behave appropriately in dynamic and complex social contexts they need to be flexible in their movement behaviors. The natural complexity of social interaction makes this a difficult property to encode programmatically. Instead of programming these algorithms by hand it could be preferable to have the system learn these behaviors. In this project a framework is created in which an agent, through deep reinforcement learning, can learn how to mimic poses, here defined as the most basic case of social movements. The framework aimed to be as agent agnostic as possible and suitable for both real life robots and virtual agents through an approach called "dancer in the mirror". The framework utilized a learning algorithm called PPO and trained agents, as a proof of concept, on both a virtual environment for the humanoid robot Pepper and for virtual agents in a physics simulation environment. The framework was meant to be a simple starting point that could be extended to incorporate more and more complex tasks. This project shows that this framework was functional for agents to learn to mimic poses on a simplified environment.

Unmanned Aerial Vehicles (UAV) have been heavily studied in the past decade, where autonomous flights have been a popular subject. More complex applications have led to higher requirements on the autonomous flight algorithms and the absence of performance data complicates the selection of what algorithm to use for various applications. Therefore, this thesis focused in analyzing the performance difference between two methods, Simultaneous Localization AndMapping (SLAM) and Artificial Potential Field Approach (APFA), which are planning and reactive algorithms, respectively. Fundamental dynamics were applied, Feedback Linear Controllers (FBLC)s for stabilization and an odometry position model combined with an inverse dynamics technique that linearizes the non-linear odometry model. The SLAM approach was set up in four steps: landmark extraction which uses a point distance based method for segment separation, combined with a Split-And-Merge algorithm for extracting linear landmarks, data association that validates the landmarks, Extended Kalman Filter (EKF) that uses the landmarks together with the odometry model for estimating the position of the UAV, and a modified TangentBug as the reactive algorithm. The APFA was constructed of two functions, an attractive and a repulsive function. The two methods were implemented on the robotics simulation platform Virtual Robot Experimentation Platform (V-REP), where a quadcopter was used as the model for the UAV. All theory was implemented onto the quadcopter model and embedded scripts were used for communication within V-REP, mainly through internal Application Programming Interface (API)-functions. Furthermore, a script was written that randomly generates three different types of simulation environments. The implementation of both methods was analyzed in reaching an arbitrary goal position in terms of: the most successful, the most time efficient and the safest navigation path. Another thing analyzed was the time- and space-complexity of both implemented methods. The results stated that the implemented APFA and the SLAM approach had approximately equal success rate, SLAM had the safest navigation, was the most time efficient, and had the highest time- and space-complexity for a worst case scenario. One of the conclusions were that improvements could be done in the implementations. Future work includes adding a proper damping method, improving the flaws in the implemented methods as well as to use V-REP as a Robot Operating System (ROS)-node for creating a Software In The Loop (SITL)-simulation, in order to achieve more realistic simulations.

Volvo Cars Corporation creates robot programs off-line for all new robot implementations for virtual commissioning. These virtually created robot programs are then downloaded to the real robot, after the installation has been carried out, to be tested before they are fully operational. These tests are spanned from robot installation until full production, adjusting the robot programme according to Volvo Cars specification and correcting errors that the robot program may have. Changes of the robot programs will be saved each time it is modified, generating a series of backups for each robot until the robot is correctly adjusted along all the steps of the process. To improve the offline programming there is a necessity for visualize the modifications made during the physical robot commissioning. The objective of this thesis is to identify, categorise, quantify and visualize modifications between each different backup of a robot. A software application has been developed using Microsoft Visual Studio using C#. The application is designed in windows for different types of data. It enables the user to compare two robot programs (two different backup programs from the tests) from one robot and see the result between them graphically. The graphs are designed interactively so that the user can filter the information to see the desired data from the robot programs comparison. Key performance indicators (KPIs) has been specified for RobTargets and Procedures according to Volvo Cars Corporation requests. These KPIs are implemented and visualised in a graphical representation.

This thesis is a part of Automationsutmaningen which is a programsupported by Tillväxtverket, the program focus on helping small tomedium large manufacturing businesses in need of automatization andflexible solutions to their processing line. Via Robotdalen inVästerås a pilot study in robot automatization was conducted atEdvin Larssons Mekaniska AB (ELMAB), a manufacturer of hydrauliccylinders and industrial grapples. ELMAB want to reduce the manualhandling of materials and reduce their need for personnel, they alsowant to develop and meet future requirements. The purpose of this project is to find what process in the manufacturing chain that is most suitable to a solution in automatization and thereafter come up with suggestions and develop concepts that fulfill set requirements. The pilot study will act asbasis to an investment and show if a solution is profitable. Thepilot study focus on the manufacturing of hydraulic cylinders andthe processes lathe, grinding, washing and coating. The main parts of the report are status analysis and improvement suggestions. The status analysis was conducted through visits and thorough studies of the manufacturing process. Literature studies in production management and industrial robotics have been very important to increasing knowledge and understanding on what to look for in the status analysis and how to draw conclusions for theimprovement suggestions. The status analysis concluded that washing, coating and lathing all could use improvements but that only coating and lathing would benefit from a solution in automatization. Further analysisconcluded that lathing was most beneficial to a solution.Based on a requirements analysis, three concepts on robot cells weredeveloped. All concepts focused on keeping the robot cell flexible.The solution is focused on the difficulty on letting an operatorwork inside the robot cell at the same time as the robot handles adifferent lathe within the cell or if there is a another solutionthat solves the problem. The solution has to work within a safetyaspect. The solution is a portable robot with a built in safetysolution. The solution leads to saved personnel costs and increasesefficiency to the lathes within the cell. The investment has apayback time in less than three years.

In near future, robots are envisioned to work alongside humans in professional anddomestic environments without significant restructuring of workspace. Roboticsystems in such setups must be adept at observation, analysis and rational de-cision making. To coexist in an environment, humans and robots will need tointeract and cooperate for multiple tasks. A fundamental such task is the manip-ulation of large objects in work environments which requires cooperation betweenmultiple manipulating agents for load sharing. Collaborative manipulation hasbeen studied in the literature with the focus on multi-agent planning and controlstrategies. However, for a collaborative manipulation task, grasp planning alsoplays a pivotal role in cooperation and task completion.In this work, a novel approach is proposed for collaborative grasping and manipu-lation of large unknown objects. The manipulation task was defined as a sequenceof poses and expected external wrench acting on the target object. In a two-agentmanipulation task, the proposed approach selects a grasp for the second agentafter observing the grasp location of the first agent. The solution is computed ina way that it minimizes the grasp wrenches by load sharing between both agents.To verify the proposed methodology, an online system for human-robot manipu-lation of unknown objects was developed. The system utilized depth informationfrom a fixed Kinect sensor for perception and decision making for a human-robotcollaborative lift-up. Experiments with multiple objects substantiated that theproposed method results in an optimal load sharing despite limited informationand partial observability.

Visual Simultaneous Localisation And Mapping is a useful tool forcreating 3D environments with feature points. These visual systemscould be very valuable in autonomous vehicles to improve the localisation.Cameras being a fairly cheap sensor with the capabilityto gather a large amount of data. More efficient algorithms are stillneeded to better interpret the most valuable information. This paperanalyses how much a feature based map can be reduced without losingsignificant accuracy during localising. Semantic segmentation created by a deep neural network is used toclassify the features used to create the map, the map is reduced by removingcertain classes. The results show that feature based maps cansignificantly be reduced without losing accuracy. The use of classesresulted in promising results, large amounts of feature were removedbut the system could still localise accurately. Removing some classesgave the same results or even better in certain weather conditionscompared to localisation with a full-scale map.

A production industry with many robots working 24 hours a day, 7 days a week consumes a lot of energy. Industries aim to reduce the energy consumed per machine so as to support their financial budgets and also to be a more sustainable, energy efficient entity. Energy models can be used to predict the energy consumed by robot(s) for optimising the input parameters which determine robot motion and task execution. This work presents an ener-gy model to predict the energy consumption of 2D belt robots used for press line tending. Based on the components' specifications and the trajectory, an estimation of the energy consumption is computed. As part of this work, the proposed energy model is formulated, implemented in MATLAB and experimentally validated. The energy model is further used to investigate the effect of tool weight on energy consumption which includes predicting potential energy reductions achieved by reducing the weight of the gripper tools. Further, investigation of potential energy savings which can be achieved when mechanical brakes are used when the robot is idle is also presented. This illustrates the purpose and usefulness of the proposed energy model.

I detta projekt byggdes en fjärrstyrd robot som styrs över Wi-Fi, ochstreamar video till användaren av vad den ser. Som komplement körsäven en temperatursensor för att utöka robotens möjlighet att kännaav sin omgivning. Huvudkomponenten är en Raspberry PI 3 modell B, därall kod för styrning och hemsidekontrollerna körs. Resultatet är enrobot som kan styras utanför synhåll och kan sända tillbaka en stabilkameraström så länge den är kopplad till ett stabilt nätverk.Dessvärre sjunker resultatet i takt med nätverkskvalitén. Vid ettsvagare nätverk blir det långa laddningstider för kameraströmmenvilket leder till att roboten blir mindre responsiv. Det tillsammansmed den förlorade kameraströmmen resulterar i att roboten ärobrukbar. Vid tillräckligt svaga nätverk, eller vid nätverksproblemkommer roboten repetera sin sista order tills dess att kontakt äråterupprättad.

The industrial testing phase of graphical user interfaces and the behaviour of screens, is still involving manual tests with human interaction. This type of testing is particularly difficult and time consuming to manually perform, due to time sensitive messages and information used within these interfaces. This thesis address this issue by introducing an approach to automate this process by utilizing high grade machine vision cameras and existing algorithm implementations from OpenCV 3.2.0. By knowing the expected graphical representation in advance, a comparison between the actual outcome and this expectation can be evaluated by applying image processing algorithms. It is found that this approach presents an Equal Error Rate of 6% while still maintaining a satisfactory time performance, in relation to the timeframe requirement of these time sensitive messages. Accuracy and time performance is profoundly affected by hardware equipment, partially due to the immense amount of image processing involved.