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  • 51.
    Nilsson, Jonatan
    University of Skövde, School of Engineering Science.
    Planering och utvecklande av testplattform för tryckpulsation2019Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Autotube is a company based in Varberg that develops and produces air- and fluid solutions primarily to the automotive industry. Recently the automotive manufacturers have increased the fuel injection pressure in petrol engines which has led to the absence of proper test equipment which limits the company’s product development department as pressure test has to be bought by a third-party company. The costs and lack of insight in the pressure tests that is associated with purchasing the service from a third part company has led Autotube to invest in new equipment that will allow the company to do future tests in-house. The ambition is to perform pressure pulsation tests and burst tests for both product development and production samples. The general purpose of the thesis is to program the PLC logic, design the HMI-panel and to create and electrically transferrable report after test completion.

    During the progression of the project studies and the company’s empirical knowledge showed that the result from a test facility is characterized primarily by three key parameters; functionality, real time monitoring and data management. Each category includes several subcategories that adds value to each key parameter.

    Functionality requires reliable hardware that can stay commissioned for extended periods of times without Interruption. However, if interruptions do occur it is important that the data from the ongoing test is saved so that data is not lost. To avoid irritation and mishandling it’s important to design the user interface according to the needs of the users and to avoid excessive information that is not vital for the result.

    A proper real time monitoring solution requires that information is easily available both at the location of the test facility and at distance in order to enable to user to act no matter where the user is located. Warning signals that indicate when the test facility does not perform as expected should be used in order to reduce the workload.

    Data management should be automatic in order to store the correct data and prevent errors caused by the human factor. Several reports should be used during the test as it allows the user to compare the data in the different test stages which improves the insight and analysis capability of the performed test.

    The performed work has analysed different alternatives and used literature relevant to the key parameters combined with continuous feedback from the company’s technicians in order to create the software for the test facility. The result is a reliable facility with tailored real time monitoring and automatic data management.

  • 52.
    Nordby, Johan
    et al.
    University of Skövde, School of Engineering Science.
    Tholin, Mikael
    University of Skövde, School of Engineering Science.
    TIDSSTUDIEANALYS AV MANUELL PRODUKTHANTERING VID I- OCH URLASTNING I PRODUKTIONSUTRUSTNINGAR: Produktionssystemutveckling enligt Chaku-Chaku/Hanedashi-principen2013Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The project is located at Autoliv Sverige AB (Autoliv) in Vårgårda. Autoliv wants to improve the handle of material in the processes by increasing the availability of the machines. Material is alternately handled by man and machine. The mission is to make one or more concrete that uses the production technique Chaku-Chaku, also known as Hanedashi, as well as being a solution efficient regarding both cost and time and to make use of already existing production equipment.The project is narrowed to just include the top three production cells that demands the most production (operator) time as well as one newly created cell.To be able to calculate the time efficiency on the processes we made a time study and with the analysis of the study we could determine important values of the production for later savings calculations. Four suggestions of improvements were developed and analyzed for time efficiency. Three out of these four were handpicked to be calculated for cost and cost savings of the maximum capacity of the new production or if the yearly production stayed the same. The requirement was that the new maximized production would increase the yearly production by 7%.The first of the handpicked suggestions was to preassemble a component on a separate table instead of assemble it inside of a machine, for this was regarded as a problematic procedure. The solution also contained a new schedule of movements for the operators and a new production cell layout. The second suggestion of improvement aim that when the module has been in one of the assembly machines it will automatically be ejected and therefor made available for the next module. The first and second solutions are recommended to be combined as these can be a complement for each other, as these suggestions are on the same production cell. The third solution was to implement a grasping device that moved aside the module a bit to be processed manually. Thus would make it possible for the next module to be placed inside the machine at the same time. This solution would make two separate waiting times into one synchronized processing. The suggestions of improvements were calculated to result in saved labour if production stayed the same. If the production were maximized the calculations showed the point of break-even. The suggestions would pay-off after 700 units were manufactured on each production cell and further increase the capacity with more than 7%.

  • 53.
    Potros, Bashar
    University of Skövde, School of Engineering Science.
    Framställning av mätmetod för att upptäcka defekta luftmunstycken: Framställa en säker och tillförlitlig mätmetod för att mäta mängd vatten i 50 provrör2018Independent thesis Basic level (university diploma), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    To detect defective air nozzles, Ecco Finishing AB in Skara has developed a new test equip-ment to replace an unreliable and uncertain existing test machine. Ecco Finishing AB wants to find a reliable and safe measurement method that will measure the amount of water in 50 test tubes. The overall goal of the thesis is to find a precise and repeatable measurement method for level measurement of fluid in the test tubes. Two measurement methods were evaluated that are most suitable for level measurement, vision systems and measurement by weighing. The reason for the choice of these two measurement methods is the test tubes of the test equipment, and that there are many measuring points and because of the small test tubes. Twenty experiments for vision systems and twenty experiments for weighingmethodwere made to evaluate and describe pros and cons. The experiments of vision systems and weighing were first made in the laboratory phase and then tested on the company's existing test equipment. The results of measurements were saved in an Excel sheet used to evaluate collected data. The evaluations were compared to set goals, reliability, accuracy, repeatabil-ity, automatic reporting of results and time of measurement. Vision systems are recom-mended for continued work and implementation on the existing test equipment

  • 54.
    Potros, Bashar
    University of Skövde, School of Engineering Science.
    Framställning av mätmetod för att upptäcka defekta luftmunstycken: Framställa en säker och tillförlitlig mätmetod för att mäta mängd vatten i 50 provrör2018Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    To detect defective air nozzles, Ecco Finishing AB in Skara has developed a new test equip-ment to replace an unreliable and uncertain existing test machine. Ecco Finishing AB wants to find a reliable and safe measurement method that will measure the amount of water in 50 test tubes. The overall goal of the thesis is to find a precise and repeatable measurement method for level measurement of fluid in the test tubes. Two measurement methods were evaluated that are most suitable for level measurement, vision systems and measurement by weighing. The reason for the choice of these two measurement methods is the test tubes of the test equipment, and that there are many measuring points and because of the small test tubes. Twenty experiments for vision systems and twenty experiments for weighing method were made to evaluate and describe pros and cons. The experiments of vision systems and weighing were first made in the laboratory phase and then tested on the company's existing test equipment. The results of measurements were saved in an Excel sheet used to evaluate collected data. The evaluations were compared to set goals, reliability, accuracy, repeatabil-ity, automatic reporting of results and time of measurement. Vision systems are recom-mended for continued work and implementation on the existing test equipment.

  • 55.
    Racca, Mattia
    et al.
    School of Electrical Engineering, Aalto University, Finland.
    Pajarinen, Joni
    Intelligent Autonomous Systems (IAS) and Computational Learning for Autonomous Systems (CLAS) labs at TU Darmstadt.
    Montebelli, Alberto
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Kyrki, Ville
    School of Electrical Engineering, Aalto University, Finland.
    Learning in-contact control strategies from demonstration2016In: IROS 2016: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, 2016, p. 688-695Conference paper (Refereed)
    Abstract [en]

    Learning to perform tasks like pulling a door handle or pushing a button, inherently easy for a human, can be surprisingly difficult for a robot. A crucial problem in these kinds of in-contact tasks is the context specificity of pose and force requirements. In this paper, a robot learns in-contact tasks from human kinesthetic demonstrations. To address the need to balance between the position and force constraints, we propose a model based on the hidden semi-Markov model (HSMM) and Cartesian impedance control. The model captures uncertainty over time and space and allows the robot to smoothly satisfy a task's position and force constraints by online modulation of impedance controller stiffness according to the HSMM state belief. In experiments, a KUKA LWR 4+ robotic arm equipped with a force/torque sensor at the wrist successfully learns from human demonstrations how to pull a door handle and push a button.

  • 56.
    Raupach, Staffan
    et al.
    University of Skövde, School of Engineering Science.
    Lindelöw, Fredrik
    University of Skövde, School of Engineering Science.
    Virtual Value Stream Mapping: Evaluation of simulation based value stream mapping using Plant Simulation2015Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    VSM, Value stream mapping, V2SM, virtual value stream mapping, lean, lean manufacturing, DES, discrete event simulation, Tecnomatix Plant Simulation

  • 57.
    Richardson, Kathleen
    et al.
    De Montfort University, Leicester, United Kingdom.
    Coeckelbergh, Mark
    De Montfort University, Leicester, United Kingdom.
    Wakunuma, Kutoma
    De Montfort University, Leicester, United Kingdom.
    Billing, Erik
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ziemke, Tom
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Gómez, Pablo
    Vrije Universiteit, Brussel, Belgium.
    Vanderborght, Bram
    Vrije Universiteit, Brussel, Belgium.
    Belpaeme, Tony
    University of Plymouth, Plymouth, United Kingdom.
    Robot Enhanced Therapy for Children with Autism (DREAM): A Social Model of Autism2018In: IEEE technology & society magazine, ISSN 0278-0097, E-ISSN 1937-416X, Vol. 37, no 1, p. 30-39Article in journal (Refereed)
    Abstract [en]

    The development of social robots for children with autism has been a growth field for the past 15 years. This article reviews studies in robots and autism as a neurodevelopmental disorder that impacts socialcommunication development, and the ways social robots could help children with autism develop social skills. Drawing on ethics research from the EU-funded Development of Robot-Enhanced Therapy for Children with Autism (DREAM) project (framework 7), this paper explores how ethics evolves and developed in this European project.

  • 58.
    Rosén, Julia
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Richardson, Kathleen
    De Montfort University, Leicester, United Kingdom.
    Lindblom, Jessica
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Billing, Erik
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    The Robot Illusion: Facts and Fiction2018In: Proceedings of Workshop in Explainable Robotics System (HRI), 2018Conference paper (Refereed)
    Abstract [en]

    "To researchers and technicians working with robots on a daily basis, it is most often obvious what is part of the staging and not, and thus it may be easy to forget that illusions like these are not explicit and the that the general public may actually be deceived. Should the disclosure of the illusion be the responsibility of roboticists? Or should the assumption be that human beings, on the basis of their experiences as an audience in film, theatre, music or video gaming, assume the audience is able to enjoy the experience without needing to know everything in advance about how the illusion is created? Therefore, we believe that a discussion of whether or not researchers should be more transparent in what kinds of machines they are presenting is necessary. How can researchers present interactive robots in an engaging way, without misleading the audience?"

  • 59.
    Schmidt, Bernard
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Active collision avoidance for human-robot collaborative manufacturing2012In: Proceedings of the SPS12 conference 2012, The Swedish Production Academy , 2012, p. 81-86Conference paper (Refereed)
    Abstract [en]

    In the human-robot collaborative manufacturing environment where humans and robots coexist, safety protection of human operators in real time is of paramount importance. This paper presents an approach for real-time active collision avoidance in augmented environment, where virtual 3D models of robots and real camera images of operators are used for monitoring and collision detection. A cost-effective depth camera is chosen for surveillance of any mobile foreign objects, including operators, which are not presented in the virtual 3D models. Two redundant Kinect sensors using structured light are used as the depth cameras for better area coverage and for eliminating possible blind spots in the surveillance area. Collision detection is performed by minumum distance. Processing applied on depth images includes background removal, filtering, labeling and points cloud generation. A prototype system is developed and linked to robot controllers for real-time robot control, with zero robot programming. According to the result of collision detection, it can alert an operator, stop a robot, or even move a robot away from an approaching operator. The results of a case study show that this approach can be applied to real-world applications such as human-robot collaborative assembly to safeguard human operators.

  • 60.
    Siegmund, Florian
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Dynamic Resampling for Preference-based Evolutionary Multi-objective Optimization of Stochastic Systems: Improving the efficiency of time-constrained optimization2016Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    In preference-based Evolutionary Multi-objective Optimization (EMO), the decision maker is looking for a diverse, but locally focused non-dominated front in a preferred area of the objective space, as close as possible to the true Pareto-front. Since solutions found outside the area of interest are considered less important or even irrelevant, the optimization can focus its efforts on the preferred area and find the solutions that the decision maker is looking for more quickly, i.e., with fewer simulation runs. This is particularly important if the available time for optimization is limited, as is the case in many real-world applications. Although previous studies in using this kind of guided-search with preference information, for example, withthe R-NSGA-II algorithm, have shown positive results, only very few of them considered the stochastic outputs of simulated systems.

    In the literature, this phenomenon of stochastic evaluation functions is sometimes called noisy optimization. If an EMO algorithm is run without any countermeasure to noisy evaluation functions, the performance will deteriorate, compared to the case if the true mean objective values are known. While, in general, static resampling of solutions to reduce the uncertainty of all evaluated design solutions can allow EMO algorithms to avoid this problem, it will significantly increase the required simulation time/budget, as many samples will be wasted on candidate solutions which are inferior. In comparison, a Dynamic Resampling (DR) strategy can allow the exploration and exploitation trade-off to be optimized, since the required accuracy about objective values varies between solutions. In a dense, converged population, itis important to know the accurate objective values, whereas noisy objective values are less harmful when an algorithm is exploring the objective space, especially early in the optimization process. Therefore, a well-designed Dynamic Resampling strategy which resamples the solution carefully, according to the resampling need, can help an EMO algorithm achieve better results than a static resampling allocation.

    While there are abundant studies in Simulation-based Optimization that considered Dynamic Resampling, the survey done in this study has found that there is no related work that considered how combinations of Dynamic Resampling and preference-based guided search can further enhance the performance of EMO algorithms, especially if the problems under study involve computationally expensive evaluations, like production systems simulation. The aim of this thesis is therefore to study, design and then to compare new combinations of preference-based EMO algorithms with various DR strategies, in order to improve the solution quality found by simulation-based multi-objective optimization with stochastic outputs, under a limited function evaluation or simulation budget. Specifically, based on the advantages and flexibility offered by interactive, reference point-based approaches, studies of the performance enhancements of R-NSGA-II when augmented with various DR strategies, with increasing degrees of statistical sophistication, as well as several adaptive features in terms of optimization parameters, have been made. The research results have clearly shown that optimization results can be improved, if a hybrid DR strategy is used and adaptive algorithm parameters are chosen according to the noise level and problem complexity. In the case of a limited simulation budget, the results allow the conclusions that both decision maker preferences and DR should be used at the same time to achieve the best results in simulation-based multi-objective optimization.

  • 61.
    Siegmund, Florian
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Deb, Kalyanmoy
    Department of Electrical and Computer Engineering, Michigan State University, USA.
    Karlsson, Alexander
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Dynamic Resampling for Guided Evolutionary Multi-Objective Optimization of Stochastic Systems2013Conference paper (Refereed)
    Abstract [en]

    In Multi-objective Optimization many solutions have to be evaluated in order to provide the decision maker with a diverse Pareto-front. In Simulation-based Optimization the number of optimization function evaluations is very limited. If preference information is available however, the available function evaluations can be used more effectively by guiding the optimization towards interesting, preferred regions. One such algorithm for guided search is the R-NSGA-II algorithm. It takes reference points provided by the decision maker and guides the optimization towards areas of the Pareto-front close to the reference points.In Simulation-based Optimization the modeled systems are often stochastic and a reliable quality assessment of system configurations by resampling requires many simulation runs. Therefore optimization practitioners make use of dynamic resampling algorithms that distribute the available function evaluations intelligently on the solutions to be evaluated. Criteria for sampling allocation can be a.o. objective value variability, closeness to the Pareto-front indicated by elapsed time, or the dominance relations between different solutions based on distances between objective vectors and their variability.In our work we combine R-NSGA-II with several resampling algorithms based on the above mentioned criteria. Due to the preference information R-NSGA-II has fitness information based on distance to reference points at its disposal. We propose a resampling strategy that allocates more samples to solutions close to a reference point.Previously, we proposed extensions of R-NSGA-II that adapt algorithm parameters like population size, population diversity, or the strength of the Pareto-dominance relation continuously to optimization problem characteristics. We show how resampling algorithms can be integrated with those extensions.The applicability of the proposed algorithms is shown in a case study of an industrial production line for car manufacturing.

  • 62.
    Siegmund, Florian
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Deb, Kalyanmoy
    Department of Electrical and Computer Engineering, Michigan State University, USA.
    Ng, Amos H. C.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Adaptive Guided Evolutionary Multi-Objective Optimization2013Conference paper (Refereed)
    Abstract [en]

    In Multi-objective Optimization many solutions have to be evaluated in order to provide the decision maker with a diverse Pareto-front. In Simulation-based Optimization the number of optimization function evaluations is very limited. If preference information is available however, the available function evaluations can be used more effectively by guiding the optimization towards interesting, preferred regions. One such algorithm for guided search is the Reference-point guided NSGA-II. It takes reference points provided by the decision maker and guides the optimization towards areas of the Pareto-front close to the reference points.We propose several extensions of R-NSGA-II. In the beginning of the optimization runtime the population is spread-out in the objective space while towards the end of the runtime most solutions are close to reference points. The purpose of a large population is to avoid local optima and to explore the search space which is less important when the algorithm has converged to the reference points. Therefore, we reduce the population size towards the end of the runtime. R-NSGA-II controls the objective space diversity through the epsilon parameter. We reduce the diversity in the population as it approaches the reference points. In a previous study we showed that R-NSGA-II keeps a high diversity until late in the optimization run which is caused by the Pareto-fitness. This slows down the progress towards the reference points. We constrain the Pareto-fitness to force a faster convergence. For the same reason an approach is presented that delays the use of the Pareto-fitness: Initially, the fitness is based only on reference point distance and diversity. Later, when the population has converged towards the Pareto-front, Pareto-fitness is considered as primary-, and distance as secondary fitness.

  • 63.
    Siegmund, Florian
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Deb, Kalyanmoy
    Department of Electrical and Computer Engineering, Michigan State University, USA.
    A Ranking and Selection Strategy for Preference-based Evolutionary Multi-objective Optimization of Variable-Noise Problems2016In: 2016 IEEE Congress on Evolutionary Computation (CEC), IEEE conference proceedings, 2016, p. 3035-3044Conference paper (Refereed)
    Abstract [en]

    In simulation-based Evolutionary Multi-objective Optimization the number of simulation runs is very limited, since the complex simulation models require long execution times. With the help of preference information, the optimization result can be improved by guiding the optimization towards relevant areas in the objective space, for example with the R-NSGA-II algorithm [9], which uses a reference point specified by the decision maker. When stochastic systems are simulated, the uncertainty of the objective values might degrade the optimization performance. By sampling the solutions multiple times this uncertainty can be reduced. However, resampling methods reduce the overall number of evaluated solutions which potentially worsens the optimization result. In this article, a Dynamic Resampling strategy is proposed which identifies the solutions closest to the reference point which guides the population of the Evolutionary Algorithm. We apply a single-objective Ranking and Selection resampling algorithm in the selection step of R-NSGA-II, which considers the stochastic reference point distance and its variance to identify the best solutions. We propose and evaluate different ways to integrate the sampling allocation method into the Evolutionary Algorithm. On the one hand, the Dynamic Resampling algorithm is made adaptive to support the EA selection step, and it is customized to be used in the time-constrained optimization scenario. Furthermore, it is controlled by other resampling criteria, in the same way as other hybrid DR algorithms. On the other hand, R-NSGA-II is modified to rely more on the scalar reference point distance as fitness function. The results are evaluated on a benchmark problem with variable noise landscape.

  • 64.
    Siegmund, Florian
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Deb, Kalyanmoy
    Department of Electrical and Computer Engineering, Michigan State University, USA.
    Dynamic Resampling for Preference-based Evolutionary Multi-Objective Optimization of Stochastic Systems2015Conference paper (Refereed)
    Abstract [en]

    In Multi-objective Optimization many solutions have to be evaluated in order to provide the decision maker with a diverse choice of solutions along the Pareto-front. In Simulation-based Optimization the number of optimization function evaluations is usually very limited due to the long execution times of the simulation models. If preference information is available however, the available number of function evaluations can be used more effectively. The optimization can be performed as a guided, focused search which returns solutions close to interesting, preferred regions of the Pareto-front. One such algorithm for guided search is the Reference-point guided Non-dominated Sorting Genetic Algorithm II, R-NSGA-II. It is a population-based Evolutionary Algorithm that finds a set of non-dominated solutions in a single optimization run. R-NSGA-II takes reference points in the objective space provided by the decision maker and guides the optimization towards areas of the Pareto-front close the reference points.

    In Simulation-based Optimization the modeled and simulated systems are often stochastic and a common method to handle objective noise is Resampling. Reliable quality assessment of system configurations by resampling requires many simulation runs. Therefore, the optimization process can benefit from Dynamic Resampling algorithms that distribute the available function evaluations among the solutions in the best possible way. Solutions can vary in their sampling need. For example, solutions with highly variable objective values have to be sampled more times to reduce their objective value standard error. Dynamic resampling algorithms assign as much samples to them as is needed to reduce the uncertainty about their objective values below a certain threshold. Another criterion the number of samples can be based on is a solution's closeness to the Pareto-front. For solutions that are close to the Pareto-front it is likely that they are member of the final result set. It is therefore important to have accurate knowledge of their objective values available, in order to be able to to tell which solutions are better than others. Usually, the distance to the Pareto-front is not known, but another criterion can be used as an indication for it instead: The elapsed optimization time. A third example of a resampling criterion can be the dominance relations between different solutions. The optimization algorithm has to determine for pairs of solutions which is the better one. Here both distances between objective vectors and the variance of the objective values have to be considered which requires a more advanced resampling technique. This is a Ranking and Selection problem.

    If R-NSGA-II is applied in a scenario with a stochastic fitness function resampling algorithms have to be used to support it in the best way and avoid a performance degradation due to uncertain knowledge about the objective values of solutions. In our work we combine R-NSGA-II with several resampling algorithms that are based on the above mentioned resampling criteria or combinations thereof and evaluate which are the best criteria the sampling allocation can be based on, in which situations.

    Due to the preference information R-NSGA-II has an important fitness information about the solutions at its disposal: The distance to reference points. We propose a resampling strategy that allocates more samples to solutions close to a reference point. This idea is then extended with a resampling technique that compares solutions based on their distance to the reference point. We base this algorithm on a classical Ranking and Selection algorithm, Optimal Computing Budget Allocation, and show how OCBA can be applied to support R-NSGA-II. We show the applicability of the proposed algorithms in a case study of an industrial production line for car manufacturing.

  • 65.
    Siegmund, Florian
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Deb, Kalyanmoy
    Department of Electrical and Computer Engineering, Michigan State University, East Lansing, USA.
    Hybrid Dynamic Resampling Algorithms for Evolutionary Multi-objective Optimization of Invariant-Noise Problems2016In: Applications of Evolutionary Computation: 19th European Conference, EvoApplications 2016, Porto, Portugal, March 30 – April 1, 2016, Proceedings, Part II / [ed] Giovanni Squillero, Paolo Burelli, 2016, Vol. 9598, p. 311-326Conference paper (Refereed)
    Abstract [en]

    In Simulation-based Evolutionary Multi-objective Optimization (EMO) the available time for optimization usually is limited. Since many real-world optimization problems are stochastic models, the optimization algorithm has to employ a noise compensation technique for the objective values. This article analyzes Dynamic Resampling algorithms for handling the objective noise. Dynamic Resampling improves the objective value accuracy by spending more time to evaluate the solutions multiple times, which tightens the optimization time limit even more. This circumstance can be used to design Dynamic Resampling algorithms with a better sampling allocation strategy that uses the time limit. In our previous work, we investigated Time-based Hybrid Resampling algorithms for Preference-based EMO. In this article, we extend our studies to general EMO which aims to find a converged and diverse set of alternative solutions along the whole Pareto-front of the problem. We focus on problems with an invariant noise level, i.e. a flat noise landscape.

  • 66.
    Siegmund, Florian
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Deb, Kalyanmoy
    Department of Electrical and Computer Engineering, Michigan State University, USA.
    Hybrid Dynamic Resampling for Guided Evolutionary Multi-Objective Optimization2015In: Evolutionary Multi-Criterion Optimization: 8th International Conference, EMO 2015, Guimarães, Portugal, March 29 --April 1, 2015. Proceedings, Part I / [ed] António Gaspar-Cunha, Carlos Henggeler Antunes, Carlos Coello Coello, Springer, 2015, p. 366-380Conference paper (Refereed)
    Abstract [en]

    In Guided Evolutionary Multi-objective Optimization the goal is to find a diverse, but locally focused non-dominated front in a decision maker’s area of interest, as close as possible to the true Pareto-front. The optimization can focus its efforts towards the preferred area and achieve a better result [9, 17, 7, 13]. The modeled and simulated systems are often stochastic and a common method to handle the objective noise is Resampling. The given preference information allows to define better resampling strategies which further improve the optimization result. In this paper, resampling strategies are proposed that base the sampling allocation on multiple factors, and thereby combine multiple resampling strategies proposed by the authors in [15]. These factors are, for example, the Pareto-rank of a solution and its distance to the decision maker’s area of interest. The proposed hybrid Dynamic Resampling Strategy DR2 is evaluated on the Reference point-guided NSGA-II optimization algorithm (R-NSGA-II) [9].

  • 67.
    Steinmetz, Franz
    et al.
    German Aerospace Center (DLR), Institute of Robotics and Mechatronics, Oberpfaffenhofen-Weßling, Germany.
    Montebelli, Alberto
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Kyrki, Ville
    Department of Electrical Engineering and Automation, Aalto Univeristy, Aalto, Finland.
    Simultaneous kinesthetic teaching of positional and force requirements for sequential in-contact tasks2015In: Proceedings of the 2015 IEEE-RAS International Conference on Humanoid Robots (Humanoids), IEEE Computer Society, 2015, p. 202-209Conference paper (Refereed)
    Abstract [en]

    This paper demonstrates a method for simulta-neous transfer of positional and force requirements for in-contact tasks from a human instructor to a robotic arm throughkinesthetic teaching. This is achieved by a specific use of thesensory configuration, where a force/torque sensor is mountedbetween the tool and the flange of a robotic arm endowedwith integrated torque sensors at each joint. The humandemonstration is modeled using Dynamic Movement Primitives.Following human demonstration, the robot arm is provided withthe capacity to perform sequential in-contact tasks, for examplewriting on a notepad a previously demonstrated sequence ofcharacters. During the reenactment of the task, the systemis not only able to imitate and generalize from demonstratedtrajectories, but also from their associated force profiles. In fact,the implemented framework is extended to successfully recoverfrom perturbations of the trajectory during reenactment andto cope with dynamic environments.

  • 68.
    Telander, Andreas
    et al.
    University of Skövde, School of Engineering Science.
    Fahlgren, Jessica
    University of Skövde, School of Engineering Science.
    Building a new production line: Problems, pitfalls and how to gain social sustainability2015Independent thesis Basic level (university diploma), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This thesis has been performed in collaboration with Volvo Cars Engine in Skövde, Sweden and Zhangjia-kou, China in order to receive a bachelor degree in automation engineering from the University of Skövde.

    The project focuses on analyzing the capacity of a future production line by using discrete event simulation. The production line is built in two different discrete event simulation software, FACTS analyzer and Plant Simulation. The focus of the study will be to compare the output results from the two software in order to give recommendations for which software to use in similar cases. This is done in order for Volvo Cars Corporation to have as a basis for further work in similar cases. The aim of the work is to verify the planned capacity of the new production line and to perform a leadership study with Chinese engineers in order to find out how they view the Swedish leadership and how this can be adapted to China and the Chinese culture and give recommendations for future work.

    The results of the capacity analysis show that the goals of parts produced can be reached for both planned capacities but also that there are potential constraints that have been identified in the system. The results of the leadership study also show that the overall approach should be slightly adapted to be better suited for the Chinese culture. The comparison of the two simulation software suggests that FACTS Analyzer is suit-able to use when less complex logic or systems are represented, however when building more complex models consisting of more complex logic Plant Simulation is more suitable.

  • 69.
    Thabet, Mohammad
    et al.
    Department of Intelligent Hydraulics and Automation, Tampere University of Technology, Finland.
    Montebelli, Alberto
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Kyrki, Ville
    Department of Electrical Engineering and Automation, Aalto University, Finland.
    Learning Movement Synchronization in Multi-component Robotic Systems2016In: : ICRA 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 249-256Conference paper (Refereed)
  • 70.
    Thellman, Sam
    et al.
    Cognition & Interaction Lab, Department of Computer and Information Science, Linköping University, Linköping, Sweden.
    Silvervarg, Annika
    Cognition & Interaction Lab, Department of Computer and Information Science, Linköping University, Linköping, Sweden.
    Ziemke, Tom
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. Cognition & Interaction Lab, Department of Computer and Information Science, Linköping University, Linköping, Sweden.
    Folk-Psychological Interpretation of Human vs. Humanoid Robot Behavior: Exploring the Intentional Stance toward Robots2017In: Frontiers in Psychology, ISSN 1664-1078, E-ISSN 1664-1078, Vol. 8, article id 1962Article in journal (Refereed)
    Abstract [en]

    People rely on shared folk-psychological theories when judging behavior. These theories guide people's social interactions and therefore need to be taken into consideration in the design of robots and other autonomous systems expected to interact socially with people. It is, however, not yet clear to what degree the mechanisms that underlie people's judgments of robot behavior overlap or differ from the case of human or animal behavior. To explore this issue, participants (N = 90) were exposed to images and verbal descriptions of eight different behaviors exhibited either by a person or a humanoid robot. Participants were asked to rate the intentionality, controllability and desirability of the behaviors, and to judge the plausibility of seven different types of explanations derived from a recently proposed psychological model of lay causal explanation of human behavior. Results indicate: substantially similar judgments of human and robot behavior, both in terms of (1a) ascriptions of intentionality/controllability/desirability and in terms of (1b) plausibility judgments of behavior explanations; (2a) high level of agreement in judgments of robot behavior -(2b) slightly lower but still largely similar to agreement over human behaviors; (3) systematic differences in judgments concerning the plausibility of goals and dispositions as explanations of human vs. humanoid behavior. Taken together, these results suggest that people's intentional stance toward the robot was in this case very similar to their stance toward the human.

  • 71.
    Tykal, Martin
    et al.
    Aalto University, Finland.
    Montebelli, Alberto
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Kyrki, Ville
    Department of Electrical Engineering and Automation, Aalto University, Finland.
    Incrementally Assisted Kinesthetic Teaching for Programming by Demonstration2016In: Human-Robot Interaction (HRI), 2016 11th ACM/IEEE International Conference on: HRI 2016, IEEE Computer Society, 2016, p. 205-212Conference paper (Refereed)
  • 72.
    Vernon, David
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Artificial Cognitive Systems: A Primer2014Book (Refereed)
    Abstract [en]

    This book offers a concise and accessible introduction to the emerging field of artificial cognitive systems. Cognition, both natural and artificial, is about anticipating the need for action and developing the capacity to predict the outcome of those actions. Drawing on artificial intelligence, developmental psychology, and cognitive neuroscience, the field of artificial cognitive systems has as its ultimate goal the creation of computer-based systems that can interact with humans and serve society in a variety of ways. This primer brings together recent work in cognitive science and cognitive robotics to offer readers a solid grounding on key issues.

  • 73.
    Vernon, David
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Cognitive System2014In: Computer Vision: A Reference Guide / [ed] Katsushi Ikeuchi, Boston: Springer, 2014, p. 100-106Chapter in book (Refereed)
  • 74.
    Vernon, David
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Beetz, Michael
    Institute for Artificial Intelligence, University of Bremen, Bremen, Germany.
    Giulio, Sandini
    Department of Robotics, Brain and Cognitive Sciences, Istituto Italiano di Tecnologia, Genova, Italy.
    Prospection in cognition: The case for joint episodic-procedural memory in cognitive robotics2015In: Frontiers in Robotics and AI, ISSN 2296-9144, Vol. 2, article id 19Article in journal (Refereed)
  • 75.
    Vernon, David
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Billing, Erik
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Hemeren, Paul
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Thill, Serge
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ziemke, Tom
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. Department of Computer and Information Science, Linköping University, Sweden.
    An Architecture-oriented Approach to System Integration in Collaborative Robotics Research Projects: An Experience Report2015In: Journal of Software Engineering for Robotics, ISSN 2035-3928, E-ISSN 2035-3928, Vol. 6, no 1, p. 15-32Article in journal (Refereed)
    Abstract [en]

    Effective system integration requires strict adherence to strong software engineering standards, a practice not much favoured in many collaborative research projects. We argue that component-based software engineering (CBSE) provides a way to overcome this problem because it provides flexibility for developers while requiring the adoption of only a modest number of software engineering practices. This focus on integration complements software re-use, the more usual motivation for adopting CBSE. We illustrate our argument by showing how a large-scale system architecture for an application in the domain of robot-enhanced therapy for children with autism spectrum disorder (ASD) has been implemented. We highlight the manner in which the integration process is facilitated by the architecture implementation of a set of placeholder components that comprise stubs for all functional primitives, as well as the complete implementation of all inter-component communications. We focus on the component-port-connector meta-model and show that the YARP robot platform is a well-matched middleware framework for the implementation of this model. To facilitate the validation of port-connector communication, we configure the initial placeholder implementation of the system architecture as a discrete event simulation and control the invocation of each component’s stub primitives probabilistically. This allows the system integrator to adjust the rate of inter-component communication while respecting its asynchronous and concurrent character. Also, individual ports and connectors can be periodically selected as the simulator cycles through each primitive in each sub-system component. This ability to control the rate of connector communication considerably eases the task of validating component-port-connector behaviour in a large system. Ultimately, over and above its well-accepted benefits for software re-use in robotics, CBSE strikes a good balance between software engineering best practice and the socio-technical problem of managing effective integration in collaborative robotics research projects. 

  • 76.
    Vernon, David
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Thill, Serge
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ziemke, Tom
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    The Role of Intention in Cognitive Robotics2016In: Toward Robotic Socially Believable Behaving Systems: Volume I / [ed] Anna Esposito & Lakhmi C. Jain, Switzerland: Springer, 2016, p. 15-27Chapter in book (Refereed)
    Abstract [en]

    We argue that the development of robots that can interact effectively with people requires a special focus on building systems that can perceive and comprehend intentions in other agents. Such a capability is a prerequisite for all pro-social behaviour and in particular underpins the ability to engage in instrumental helping and mutual collaboration. We explore the prospective and intentional nature of action, highlighting the importance of joint action, shared goals, shared intentions, and joint attention in facilitating social interaction between two or more cognitive agents. We discuss the link between reading intentions and theory of mind, noting the role played by internal simulation, especially when inferring higher-level actionfocussed intentions. Finally, we highlight that pro-social behaviour in humans is the result of a developmental process and we note the implications of this for the challenge of creating cognitive robots that can read intentions.

  • 77.
    Vernon, David
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    von Hofsten, Claes
    Department of Psychology, University of Uppsala, Sweden.
    Fadiga, Luciano
    Section of Human Physiology, University of Ferrara, Italy / IIT@UniFe Center for Translational Neurophysiology, Istituto Italiano di Tecnologia, Ferrara, Italy.
    Desiderata for developmental cognitive architectures2016In: Biologically Inspired Cognitive Architectures, ISSN 2212-683X, E-ISSN 2212-6848, Vol. 18, p. 116-127Article in journal (Refereed)
    Abstract [en]

    This paper complements Ron Sun’s influential Desiderata for Cognitive Architectures by focussing on the desirable attributes of a biologically-inspired cognitive architecture for an agent with a capacity for autonomous development. Ten desiderata are identified, dealing with value systems & motives, embodiment, sensorimotor contingencies, perception, attention, prospective action, memory, learning, internal simulation, and constitutive autonomy. These desiderata are motivated by studies in developmental psychology, cognitive neuroscience, and enactive cognitive science. All ten focus on the ultimate aspects of cognitive development — why a feature is necessary and what it enables — rather on than the proximate mechanisms by which it can be realized. As such, the desiderata are for the most part neutral regarding the paradigm of cognitive science — cognitivist or emergent — that is adopted when designing a cognitive architecture. Where some element of a desideratum is specific to a particular paradigm, this is noted.

  • 78.
    Wang, Lihui
    et al.
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Mohammed, Abdullah
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Wang, Xi Vincent
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Schmidt, Bernard
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Energy-efficient robot applications towards sustainable manufacturing2018In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 31, no 8, p. 692-700Article in journal (Refereed)
    Abstract [en]

    The cloud technology provides sustainable solutions to the modern industrial robotic cells. Within the context, the objective of this research is to minimise the energy consumption of robots during assembly in a cloud environment. Given a robot path and based on the inverse kinematics and dynamics of the robot from the cloud, a set of feasible configurations of the robot can be derived, followed by calculating the desirable forces and torques on the joints and links of the robot. Energy consumption is then calculated for each feasible configuration along the path. The ones with the lowest energy consumption are chosen. Since the energy-efficient robot configurations lead to reduced overall energy consumption, this approach becomes instrumental and can be applied to energy-efficient robotic assembly. This cloud-based energy-efficient approach for robotic applications can largely enhance the current practice as demonstrated by the results of three case studies, leading towards sustainable manufacturing.

  • 79.
    Wang, Lihui
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. KTH Royal Institute of Technology, Stockholm, Sweden.
    Mohammed, Abdullah
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Wang, Xi Vincent
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Schmidt, Bernard
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Recent Advancements of Smart Manufacturing: An Example of Energy-Efficient Robot2016In: Proceedings of the 26th International Conference on Flexible Automation and Intelligent Manufacturing, 2016, p. 884-892Conference paper (Refereed)
    Abstract [en]

    The cloud technology provides sustainable solutions to the modern industrial robotic cells. Within the context, the objective of this research is to minimise the energy consumption of robots during assembly in a cloud environment. Given a trajectory and based on the inverse kinematics and dynamics of a robot from the cloud, a set of feasible configurations of the robot can be derived, followed by calculating the desirable forces and torques on the joints and links of the robot. Energy consumption is then calculated for each feasible configuration along the trajectory. The ones with the lowest energy consumption are chosen. Since the energy-efficient robot configurations lead to reduced overall energy consumption, this approach becomes instrumental and can be applied to energy-efficient robotic assembly.

  • 80.
    Wolak, Peter
    et al.
    University of Skövde, School of Engineering Science.
    Johansson, Mattias
    University of Skövde, School of Engineering Science.
    Buffer optimisation of a packaging line using Volvo GTO's flow simulation methodology2019Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    With the rapid development of computers and their proven usability in manufacturing environments, simulation-based optimisation has become a recognised tool for proposing near-optimal results related to manufacturing system design and improvement. As a world-leading manufacturer within their field, Volvo GTO in Skövde, Sweden is constantly seeking internal development and has in recent years discovered the possibilities provided by flow simulation. The main aim of this thesis is to provide an optimal buffer size of a new post-assembly and packaging line (Konpack) yet to be constructed. A by-product of the flow simulation optimisation project in form of a flow simulation process evaluation was also requested.

    The simulation project started with a pre-study including the development of the frame of reference and an analysis of the literature focused on merging Lean philosophy with simulation-based optimisation. The simulation model was built based on both historical and estimated data. The optimisation results showed different buffer size alternatives depending on the throughput to be achieved, these are discussed, and near-optimal solutions presented for decision-making. Additionally, four experiments were carried out, both contributing to the model’s credibility as well as providing new and valuable insight to the stakeholders. The conclusions drawn from the optimisation and experiments indicate that Konpack will be able to meet the established throughput goals, provided that the suggested near-optimal solutions are considered. The experiments also unanimously point to the fact that Konpack has a built-in overcapacity, utilizable by optimising certain suggested input parameters.

    Additionally, an evaluation of the completeness of the standard simulation process employed by Volvo GTO is provided, concluding that no major changes are needed. Nevertheless, there is always room for improvement. Hence, future work regarding the flow simulation process at Volvo GTO is proposed.

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