Halmstad University or Halmstad University College is a University college in Halmstad, Sweden. It was established in 1983. Halmstad University is a public higher education institution offering bachelor's and master's programs in various fields of studies. In addition, it conducts Ph.D. programs in three fields of research, namely, Information Technology, Innovation Science and Health Science. Wikipedia.
News Article | May 16, 2017
Art has always been fundamentally intertwined with technology. New techniques and materials have constantly allowed artists to innovate and create new types of works. In this series we look at the impact of digital technologies on art and how artists are creating entirely novel forms of art using these modern tools. We've previously examined the fields of "datamoshing", ASCII art, BioArt, Minecraft Art and Internet Art. In this instalment we examine a fascinating world where scientists are teaching robots how to paint works of art. Artificial intelligence systems are currently excelling at producing elaborate digitally generated works of art. Every other week we seem to see a new neural network developed to mimic a famous artists' aesthetic or convert a photograph into a painterly image. But what about machines actually mimicking the process a human artist uses to paint on a canvas? That particularly human skill seems to be a lot harder for machines to replicate. In 2016, the RobotArt competition was founded by Stanford educated mechanical engineer Andrew Conru. The competition was designed to stimulate robotic engineers to create new mechanical painting devices. In setting up the competition Conru noted that many of the initial entries were expected to be variations of a simple mechanism where a robotic arm mimics the movements of a human artist, but many teams took the challenge a step further. The competition saw a variety of different entries, from a team using an eye-tracking system to control a robot's movement, to a system that had users remotely control a robot via internet-directed brush stroke commands. All the weird and wonderful results reinforced the question of how truly creative a robotically generated work of art could really be. Below are the recently announced winners of the 2017 RobotArt competition. Be sure to click through to our gallery to get a broader look at each winner's work. From a mechanical engineering team at Colombia University we get the winner of RobotArt 2017, a bot by the name of PIX18. Apparently this is the third generation of a system developed with the goal of creating a robot capable of creating original artwork using the classic medium of oil on canvas. Judging comments applauded this robot's ability to produce "some lovely paintings from sources or scratch" and noted that the work had "brush strokes evocative of Van Gogh". The ReART system uses a haptic recording system to record artists painting a work. The system tracks the position of the brush, the force being exerted and a variety of other data points. A robot then "plays back" the recording, creating a perfectly mimicked ink brush drawing. The project is from the Department of Electrical Engineering at Kasetsart University in Thailand and looks to develop motion control robotics for a variety of industrial and creative uses. CloudPainter is one of the most technically sophisticated projects in the RobotArt competition. Utilizing AI and deep learning systems, the project aims to get the machine to make as many individual creative decisions as possible. According to the creators, currently "the only decision made by a human is the decision to start a painting." More info on their process can be found on their website. One of the judges said of the machine's work, "Spontaneous paint, "mosaicing" of adjacent tones, layering effects and the graphical interplay between paint strokes of varying textures, are all hand/eye, deeply neurally sophisticated aspects of oil painting..." e-David is an evolving robotic painting system that uses a visual feedback loop to constantly record and re-process how the machine is interpreting its recreation of an input image. Using an ordinary industrial welding robot combined with cameras, sensors and a control computer, the system can correct errors as it paints, while also understanding what the makers call "human optimization processes". This is one of our favorite works from the competition. From a student at New York University Shanghai, this project is inspired by the aesthetic of American artist Chuck Close. The system starts with an input image that is converted to a low resolution and painted pixel by pixel using a mobile robot with omni wheels. Each oversized, low-res pixel that is cribbled by the robot is roughly the size of a human hand and each entire artwork is 176 X 176 cm (5.7 x 5.7 ft), or just about as tall as a human being. HEARTalion is a project from Halmstad University in Sweden that attempts to develop a system that can recognize and subsequently depict a person's emotional state. The system captures emotional signals using a Brain-Machine Interface (BCI) and a robot then attempts to convey the emotions visually based on a model that was developed with advice from two local painters in Halmstead, Peter Wahlbeck and Dan Koon. One of the impressed RobotArt judges remarked in reference to HEARTalion, "If this body of work was exhibited at a gallery and I was told that the artist aimed to capture emotion through color, composition, and textures — I would buy." This independent entry from an electronic engineer who put in most of the work after his wife and kids had gone to bed uses a simple XYZ axis painter bot guided by two basic behavioral rules. All of this project's work is from reinterpretations of input images, but because the robot receives no feedback from sensors or cameras, the mixing of colors isn't faithful to the source. However, the novel strength of this project comes from its gorgeous use of watercolor paint. Using the precision of a robotic artist to its advantage, this project created a system that minutely controls the pressure and movement of single brush strokes to create stunning images that a human would struggle to accurately produce. The members of the team describe their process in greater detail here and have also publicly offered up their source code in the hope others will build upon their work. CARP, or Custom Autonomous Robotic Painter, comes from a team at the Worcester Polytechnic Institute in Massachusetts. The system uses image decomposition techniques to dissemble input images, which are then reconstructed by a robot. Visual feedback systems are also incorporated into the process allowing for dynamic corrections to be applied to the work as it is being created. An experimental project from a team at MIT. This is an evolving robot arm that was saved from an existence as a decorative coat rack and has slowly been given more peripherals, such as an auto-brush cleaner and wireless control via a video game controller. Equipped with machine learning abilities, the robot can grow its skill set from project to project. Take a closer look through some more of the amazing and varied robot painted artworks in our gallery.
Werner S.,Halmstad University
Energy | Year: 2017
The purpose with this review is to provide a presentation of the background and current position for district heating and cooling in Sweden. The review structure considers the market, technical, supply, environmental, institutional, and future contexts. The main conclusions are high utilisation of district heating in Swedish buildings, commitment to the third generation of district heating technology, high proportions of heat recycling and renewable supply, high compliance to European definition of efficient district heating, considerable reductions of fossil carbon dioxide emissions, strong national driving forces from high fossil fuel taxes, and soft district heating regulation based on transparency. District cooling systems are small compared to district heating systems. From strong legislative driving forces, the Swedish heat market became a testing ground for a market situation when fossil fuels are expensive in a heat market. The long-term market solutions have then become district heating in dense urban areas and local heat pumps in suburban and rural areas. © 2017 The Author
Agency: European Commission | Branch: FP7 | Program: MC-ITN | Phase: FP7-PEOPLE-ITN-2008 | Award Amount: 3.22M | Year: 2010
With various forms of biometric technologies becoming available, there is a growing need for scientists who are able to assess the merits of these technologies when applied to forensics. The Marie Curie ITN `Bayesian Biometrics for Forensics, or BBfor2, will provide a training infrastructure that will educate Early Stage Researchers in the core biometric technologies of speaker, face and fingerprint recognition, as well as the forensic aspects of these technologies. According to modern interpretation of evidence in court, biometric evidence must be presented as likelihood ratios. The calibration of likelihood ratios of individual behavioural and physical biometrics and of combinations of biometric modalities, including measures of the quality of the traces, is a unifying topic in all research projects in this Network. The training of ESRs will be realized as individual PhD projects at various research labs, including a forensic institute. Apart from training at their host institute and secondments with other network partners, the ESRs will receive training in dedicated Summer Schools on Biometric Signal Processing, Bayesian Techniques in Forensic Applications and Legal Issues in Forensic Applications. The Network combines 8 European Universities and a leading Forensic Institute; it is augmented by a biometric industrial and a research institute, where secondments of the ESRs will take place.
Agency: European Commission | Branch: FP7 | Program: CP-TP | Phase: NMP-2009-4.0-5 | Award Amount: 3.91M | Year: 2010
poliMATIC - Automated polishing for the European Tooling Industry For the manufacturing of tools 12 to 15 % of the manufacturing costs and 30 to 50 % of the manufacturing time are allocated to polishing. As current automated polishing techniques are almost not applicable on parts with freeform surfaces and function relevant edges like 95% of the tools, the polishing is predominantly done manually. Therefore the overall objective of poliMATIC is to strengthen the competitiveness of the European Tooling Industry by overcoming the current drawbacks of die and mould finishing by realizing automation in laser polishing and force controlled robot polishing. Both processes already achieve low roughnesss on flat surfaces. But the critical step to bring these demanding processes into production is the polishing of freeform surfaces. To achieve this, the following significant technological innovations are needed: (1) Process development to achieve a roughness of Ra=0.05 m (laser polishing) / Ra=0.005 m (robot polishing) on freeform surfaces (2) The development of a knowledge-based CAM-NC data chain to make the new technologies usable for end-users (3) The development of a new surface metrology framework for polished surfaces. Current measures are insufficient to express e.g. the visual impression of a polished surface Laser and robot polishing offer potential to strengthen the European Tooling Industry by a significant decrease of polishing costs (75%) and time (90%). In 5-7 years this will result in expected annual savings of manufacturing costs for tools of 150 Mio. Euros and in reductions of the time-to-customer by 27 to 45 %. The shorter time-to-customer will stimulate new demands. In conjunction with the decreased costs this will lead to a regain of world market shares and therefore relocation of labour back to Europe. PoliMATIC will contribute to the transformation of the resource intensive tooling industry into a knowledge-based one.
Agency: European Commission | Branch: H2020 | Program: MSCA-RISE | Phase: MSCA-RISE-2016 | Award Amount: 1.08M | Year: 2017
The aim of this Project is to create an International and Intersectoral network to facilitate the exchange of staff to progress developments in reminding technologies for persons with dementia which can be deployed in smart environments. The focus will be on developing staff and partner skills in the areas of user centered design and behavioral science coupled with improved computational techniques which in turn will offer more appropriate and efficacious reminding solutions. This will be further supported through research involving user centric studies into the use of reminding technologies and the theory of behaviour change to improve compliance of usage. A program of work has been established to maximise the transfer of knowledge between the different sectors offering a range of development and training opportunities for staff. Industrial staff will benefit from bi-lateral exchanges from the technical domains of context aware reminding technologies, soft computing, aware intelligent systems, pervasive computing and the psychological domain of behaviour change. The academic beneficiaries will benefit from gaining experience in the development of industrial standard software conforming to ISO and medical standards, engagement with stakeholders through a user centred design process and working with organisations delivering care to the elderly and persons with dementia. The consortium is comprised of an International network of beneficiaries and partners, all of which are committed to progressing the notion of reminding technologies within smart environments.
Agency: European Commission | Branch: H2020 | Program: CSA | Phase: EE-14-2015 | Award Amount: 2.11M | Year: 2016
In Europe, there is a clear long-term objective to decarbonize the energy system, but it is very unclear how this will be achieved in the heating and cooling sector. As a result, there is currently a lot of uncertainty among policymakers and investors in the heating and cooling sector, primarily due to a lack of knowledge about the long-term changes that will occur in the coming decades. This HRE proposal will enable new policies as well as prepare the ground for new investments by creating more certainty in relation to the changes that are required. The work in this proposal will build on three previous HRE studies, all of which have been successfully completed on time and all of which have already influenced high-level policymakers at EU and national level in Europe. The work from these previous studies will be significantly improved in this project. The new knowledge in this project will: - Improve at least 15 new policies at local, national, or EU level, - Specify how up to 3,000,000 GWh/year of fossil fuels can be saved in Europe, and - Quantify how the 3 trillion of investment required to implement these savings will reduce the net cost of heating and cooling in Europe. Furthermore, one of the most significant improvements compared to previous studies is the dissemination and communication strategy that has been developed as part of this proposal. These activities represent the largest work package in this proposal, which is necessary to ensure that policymakers, investors, and researchers at local, national, and EU level are all aware of the new data, tools, methodologies, and results from this project. The dissemination activities are expected to directly build the skills and capacity of at least 350 people in specific target groups identified by the consortium, while the communication activities will inform at least 50,000 people about the project activities and results.
Agency: European Commission | Branch: FP7 | Program: JTI-CP-ARTEMIS | Phase: SP1-JTI-ARTEMIS-2013-ASP3 | Award Amount: 39.61M | Year: 2014
DEWI (dependable embedded wireless infrastructure) envisions to significantly foster Europes leading position in embedded wireless systems and smart (mobile) environments such as vehicles, railway cars, airplanes and buildings. These environments comprise wireless sensor networks and wireless applications for citizens and professional users. Therefore the consortium introduces the concept of a sensor & communication bubble featuring: - locally confined wireless internal and external access - secure and dependable wireless communication and safe operation - fast, easy and stress-free access to smart environments - flexible self-organization, re-configuration, resiliency and adaptability - open solutions and standards for cross-domain reusability and interoperability DEWI identifies and implements an integrated dependable communication architecture using wireless technology capable of replacing the traditional heavy wiring between computers / devices / sensors, and therefore makes possible less expensive and more flexible maintenance and re-configuration. Citizens will gain easier, more comfortable, more transparent and safer access to information provided by the sensor &communication bubble. DEWI will provide a platform and toolset containing methods, algorithms, prototypes, and living labs solutions for cross-domain reusability, scalability and open interface standards, and will contribute to the ARTEMIS repository by connecting to other ASP and AIPP initiatives to ensure long-term sustainability and impact towards society. Key results of DEWI will be demonstrated in exemplary show cases, displaying high relevance to societal issues and cross-domain applicability. Regarding interoperability, DEWI will also contribute to establishing a standard for wireless systems engineering in a certification and security context, which entails conformity to both domain-specific standards and international domain-independent standards. TA approved by ARTEMIS-JU on 17/12/2013 Amendment 1 changes approved by ECSEL-JU on 18/03/2015 Note: SPICER OFF- HIGHWAY appears with short name DANA after its mother company DANA BELBIUM NV in anticipation of a follow-up amendment for UTRO
Agency: European Commission | Branch: H2020 | Program: IA | Phase: FoF-06-2014 | Award Amount: 8.05M | Year: 2015
In nearly every sector of industrial manufacturing polishing techniques are used. But often manual polishing is the only option because the tasks are too complex to be automated. Therefore in SYMPLEXITY Symbiotic Human-Robot Solutions for Complex Surface Finishing Operations will be developed. The main SYMPLEXITY Objectives are SO 1 Accurate and cognitive industrial robot systems enabling safe human-robot collaboration for surface finishing operations SO 2 Easy to use interfaces for planning, control and re-planning of shared finishing tasks SO 3 Collaboration oriented process technology for abrasive finishing, laser and fluid jet polishing SO 4 Integrated and autonomous sensing system for objective identification of surface properties SO 5 Introduction of developed collaborative finishing solutions into manufacturing industry In SO5 the results of the first 4 objectives will be combined to 3 demonstrator human-robot collaboration cells, one for each of the investigated process technologies. The 3 demonstrator cells will be tested in operational environment at 3 end-users. SYMPLEXITY is the consistent continuation of 3 recent EU projects that achieved TRL 4-5: COMET Plug-and-produce COmponents and METhods for adaptive control of industrial robots SAPHARI Safe and Autonomous Physical Human-Aware Robot Interaction poliMATIC Polishing processes and tools development SYMPLEXITY will bring together the results and key partners of these 3 projects to achieve TRL7 and thereby support the European Industry to win the competition in the global market with higher quality, efficient manufacturing and economic production, based on human robot collaboration for polishing complex shaped metallic surfaces. Relevant branches are tool making, medical engineering, aeronautics and automotive industry. Case studies show, that for many applications todays >90% of manual work can be converted in 80 % of robotic work under human control and 20 % of manual work.
Agency: European Commission | Branch: FP7 | Program: CP-FP | Phase: GC.SST.2013-7. | Award Amount: 3.92M | Year: 2013
Cargo handling by Automated Next generation Transportation Systems for ports and terminals aims to to create smart Automated Guided Vehicles (AGVs) and Highly Automated Trucks (HATs) that can co-operate in shared workspaces for efficient and safe freight transportation in main ports and freight terminals. The project builds on an active dialog with customers, workforce and authorities to maximize acceptance and exploitation of the project results. The specific objectives are: -Increase performance and throughput of freight transportation in main ports and freight terminals and maintain a high level of safety -Develop an automated shared work yard for intelligent AGVs and highly automated trucks -Develop and demonstrate planning, decision, control and safety strategies for automated vehicles -Develop and demonstrate an environmental perception system and a grid-independent positioning system Research questions -Which combination of positioning techniques and sensors allow for reliable and accurate positioning in view of the proposed applications? -How can reliable environmental perception be achieved, i.e. moving and stationary object detection, drivable path detection, docking point detection, absolute and relative object positioning ? -How to set-up and integrate a vehicle control system, including high-level site planning, path planning, interaction planning and feedback control? -How can functional safety of automated vehicles be achieved?
Baath L.B.,Halmstad University
Renewable Energy | Year: 2013
This paper presents observations of audio noise in frequency range 20-20 000 Hz from wind turbines. The observations were performed around the theoretically calculated 40 dBA noise perimeter around the wind turbine farm at Oxhult, Sweden. This paper describes a newly designed and constructed a field qualified data acquisition system to measure spectra and total noise level of sound from wind turbines. The system has been calibrated at SP Borås. It is shown that it has a flat frequency response and is linear with amplitude and time.The total noise level (as integrated 20-20 000 Hz) is shown to be below 35 dBA (below the reference background noise at 36 dBA) at a 10 m altitude wind speed of 4-5 m/s. The measurements were made along the theoretical 40 dBA border at 8 m/s.It is concluded that the theoretical 40 dBA border seems reasonable calculated if the manufacturer specifications are used to extrapolate the sound level to correspond to 8 m/s at 10 m. Our data indicate that a simple sound propagation model is sufficient since the sound level is more affected by the nearby environment than the large scale forest structure. Also, the large scale forestry structure is bound to change with time and the error bars of measurements on total sound level are about 1 dBA, which is larger than any fine tuning with a more sophisticated model. More care should be taken to model the reflections from walls and other obstacles close to the microphones.The distribution of the spectral noise level around the turbine farm suggests that the noise originates from individual wind turbines closest to the measurement location rather than from the wind turbine farm as a whole. The spectra show narrow band spectral line features which do not contribute significantly to the total noise at this level. The narrow band features are only detectable at very long integration time and at 1 Hz spectral resolution. The spectral features are typical to originate from mechanical noise.The spectral acquisition method described in this paper can be used as a field qualified system for sound measurements in forest areas. The high spectral resolution is a viable remote diagnostic method for mechanical faults in the turbine machinery. Future work will concentrate on these two areas. © 2013 Elsevier Ltd.