Research projects

Project leader: Sabine Sachweh(Opens in a new tab) 

Period: July 2018 – March 2019

Funded by: Federal Ministry of Education and Research (BMBF)(Opens in a new tab) 

Funding-ID: 16SV8036

Technology is playing an increasingly important role in the domestic environment. At the same time, the use of this technology is becoming increasingly complex and can quickly overwhelm users. 
New types of interaction with technical devi-ces - such as voice control - represent alternative operating concepts, but are not sufficient to ensure comfortable operation in everyday life in all cases and for all users.

The aim of the project Plug-In is to enable the implementation of customized operating concepts. These will allow intelligent user interfaces to be created which can adapt their complexity individually to the wishes and abilities of the users.

The basis is provided by the “Plug-In” platform (Figure 1) that should be able to carry out individual adaptation for any household appliance on the basis of environment, usage and action context. 
This results in customized and personal device operation that can take into account impairments as well as preferences.

In a large-scale competition for ideas, IDiAL was able to prevail with the Plug-In idea in a multi-stage application process against a large number of competitors. The current funding allows for the refinement of the concept design, including the compilation of an appropriate consortium and the preparation of an early prototype for the evaluation of the state of the art and the implementation of a Future Workshop with potential users to validate and substantiate the project idea, among others. At the end of the current concept project is the submission of a complete application for the final round of the competition.

Technologically, the early prototype is based on the Eclipse Smart Home (ESH) framework, which enables the control of a variety of household appliances. On the basis of a simple static set of rules and existing personal descriptions, it is able to make simple adjustments to the standard ESH interface. Thus, the prototype already forms a solid basis for an iterative and successive process, to be further developed in the final funding phase of the “Plug-In” platform.

Methodically, by using a co-productive Design Thinking approach, the workshop presents the integration of potential end users already during the application phase. Paper prototypes and drafting of interaction scenarios created in this workshop should provide the basis for ongoing user engagement for the final funding phase.

Project leader: Christof Röhrig  

Period: July 2017 - June 2020

Funded by: Ministry of Culture and Science of the State of North Rhine-Westphalia (MKW NRW)(Opens in a new tab) 

Funding-ID: 005-1703-0008

The demographic change is causing an altered age structure in the working population of Germany. The proportion of older working people is rising without any reduction in physical strain at the workplace. With increasing age, physical fitness is usually reduced and this necessitates new work organization and new forms of robot usage.

The aim of this research project is to reduce the load on humans in physically demanding work processes without individual human robot cooperation. During human robot cooperation humans work directly with robots with out any safety fencing. The aim is an optimal work split between human and robot, where the human can use their experience as well as their superior sensory and sensorimotor abilities, while the robot can take on physically heavy tasks with high repetitive accuracy without tiring. Two fields of application have so far been neglected by research: in manufacturing assembly, intralogistics and especially order picking are manual and physically very challenging tasks. During order picking, a central function of intralogistics, parts from a large range with great variety of size, shape and weight need to be collected for often short notice customer orders. A second field of application is civil safety and here especially the work of the fire service. The work of the fire service is characterized by heavy physical demands. It therefore offers great potential for human robot cooperation. Jointly with four project partners specific application scenarios and specific solution concepts are being developed for both fields of application. Individual physical limitations particularly are being taken into account during the development of solution concepts. Ideally the robot will adapt to the individual limitations. For intralogistics an assistant robot as a demonstrator will additionally be developed for an example application scenario and tested in an industrial environment. 

In the design of the human robot interface not only the proficiency of the robot for the production process will be considered, but also the impact of the working conditions of the human will be taken into account.

The research project is being carried out with inter- and transdisciplinary partners from science and the professional world:

Fraunhofer Institute for Material Flow and Logistics (IML): Identification of application scenarios and definition of requirements for human robot cooperation in the area intralogistics and order picking

Institute for Fire and Rescue Technology of the City of Dortmund (IFR): Identification of application scenarios and definition of requirements for human robot cooperation in the area fire service and civil safety

Research Institute for Technology and Disability (FTB) of the evangelical foundation Volmarstein: Development of requirements from the human perspective, expertise in development and evaluation of technical support systems for people with physical limitations

J.D. Theile GmbH and Co KG (JDT) Schwerte: Both as developer of robot systems (JDT robotics) and as potential user of the devised human robot cooperation in the intralogistics of chain production.

Project leader: Robert Höttger 

Period: September 2017 - December 2019

Funded by: Federal Ministry of Education and Research (BMBF)(Opens in a new tab) 

Funding-ID: 01IS16047D

The complexity of software intensive embedded automobile systems has reached a new dimension with the implementation of connected car scenarios and the associated networking of vehicles. To ensure the system safety of a vehicle it will no longer be sufficient to just consider and appropriately respond to errors that stem from components in the individual vehicle, like defective sensors. When developing a connected car, the data exchange with external sources will also need to be considered. This does not only result in further possibilities for service offerings for vehicle occupants but also the danger of gaps in security. As a result there are new demands with respect to data protection as well as the trustworthiness of external data. Already during the system development of the vehicle well defined interfaces for the exchange with the IoT platform are needed on the one hand, but also adherence to standards of the automobile industry like AUTOSAR must be taken care of.

APPSTACLE persues the aim to generate an open de-facto standard and an open source implementation of a complete technology stack for connected car scenarios, as well as an associated ecosystem of libraries, tools and also business models, services and service offerings. The development of networked vehicles is to be supported by the provision of suitable components in order to, for example, administer vehicle data decentrally or to enable innovative development features (OTA(Over the air) ECU upgrades). By means of open access software libraries, APIs, the development of a standardised automobile gateway (with standardized communication technologies) as well as a development and administration platform, an overarching basis is created that enables innovative and at the same time efficient applications in the areas Internet of Things (IoT), cloud computing and automotive. Additionally, interfaces for the individual extension for new features and adaptation of existing ones are provided.

APPSTACLE is working within the European consortium on three key elements: the automobile platform (In-Car components), the Car2Cloud communication solution, and the (automotive) Cloud respectively IoT platform. The German consortium is concentrating on the automobile and automotive IoT platform, as well as on the provision of a demonstrator. Suitable communication solutions therein represent results of other part consortia. The developed platform will be published as open source under the Eclipse Public Licence. Because of the open availability of the source code and the documented interfaces, open source as well as commercial services will arise which will, over time, yield an ecosystem for connected car scenarios.

Project leader: Andreas Püsche 

Period: January 2017 - August 2019

Funded by: Federal Ministry of Education and Research (BMBF)(Opens in a new tab) 

Funding-ID: 03FH0I11IA

Successful thermal energy transition requires the refinement of regenerative energy systems, the integration of the systems into the (existing) decentralized and centralized infrastructures, as well as the making available of user specific information and control options. This demands a stronger coupling across systems and energy carriers of energy systems, like optimally matched system components, whose interaction via control and regulating systems and centralised software platforms are enhanced for efficient data processing. While the virtualization of intelligent power networks is by now in the standardization phase, many thermal energy users, stores and generators are either not electronically controlled or not equipped with relevant components (M2M). The integration of intelligent IoT middleware and platform solutions are required.

The aim is the flexible, decentralized feed in of solar and geothermal heat into thermal energy networks utilizing existing supply and network structures. Seasonal excess heat is to be stored in former coal mine workings. For the decentralized part, bidirectional thermal consumer/producer systems are planned, for example buildings with district heating connection and solar thermal. This thermal energy network requires a distributed system architecture where both consumers and producers can be connected by intelligent IoT midd-leware and cost effective control devices via hardware solutions and a cloud-based software platform.

Three universities are researching an integrated solution in the base project GeoSmaGriR together with com2m GmbH and Geomecon GmbH. The solution concept in the illustration integrates various hardware and software components. Smart Device Controllers (SDCs) represent the decentralized low cost hardware modules that tie in the sensors and actuators in the mine workings and small generators. They capture energy data and send switching commands to local control systems. Data is initially aggregated and prefiltered locally before being transmitted to the cloud platform. Several SDCs will be locally clustered to improve the control and stability of the whole network, especially in case of limited outages. The thus structured components together form a so-called Smart Grid.

In the project context IDiAL signs as responsible for the prototype provision of the cloud platform as a distributed software architecture along the microservice paradigm. The platform stores transmitted energy data with regard to data protection and data security and makes a flexible framework available that allows external developers to generate applications on the basis of data explicitly made available by potential users.

In the course of protecting the systems, a secure update procedure with runtime integrity checking and with a secured life cycle for the SDC has been developed in cooperation with the university partners. Both are intended to ensure that no unauthorized changes can be made or unknown devices are put into operation. The life cycle takes into account the GDPR when decommissioning, in the sense of data destruction on the terminals, to ensure no data remains and to prevent it falling into the hands of third parties.

Project leader: Uwe Großmann  

Period: October 2016 - September 2019

Funded by: NRW-Landesregierung (EFRE.NRW)(Opens in a new tab) 

Funding ID: EFRE-0800466

Demographic change is leading to a nursing crisis, not only in Germany: there is a lack of staff and costs are continuously rising. Smart Service Power would like to develop a solution and enable age appropriate, technology supported living in the community by intelligent digitalization and 'smartification'. The sick, people in need of nursing or care, people with impairments and the elderly should be able to live as long as possible, socially integrated in their own community, according to their wishes, thereby aiding the reduction of costs in care and follow on costs for health insurances, church and council providers, through prevention, close to home provision, and networked value creation chains.

The project initially wants to integrate existing features in the areas of e-health, smart home, AAL, distress call systems, care and home help services, and interlink their data silos. The bringing together of the various data of the occupant, in combination with intelligent analysis and evaluation, not only collects more distress signals, but demand conditions will be derived and forwarded. Processes, connections and changes become visible and can be proactively reacted to.

In this project intelligent algorithms will be developed that detect home emergencies and can capture the needs of the occupant. These algorithms will work on the basis of probabilistic models, to be developed in the project, and utilize both vital data of the occupant and activity data from the smart home. Commercially available systems and sensors for vital data capture and smart home will be integrated for this.

Safety modules will be generated to ensure end-to-end safety. In collaboration with the application partners, a legal data usage concept with flexible and context based access rights will be also developed. Cost-effectiveness analysis will also be part of this project and based on that, suggestions for business models. On top of that, a system to support the decision making will be devised, to suggest a fair allocation of savings and returns for the collaborative business models.

Project leader: Martin Hirsch  

Period: June 2016 - May 2019

Funded by: Federal Ministry of Education and Research (BMBF)(Opens in a new tab) 

Funding-ID: 01|S15055 F

To develop production micro planning and micro controlling at machine level, the enabling of the production machines and cells as autonomous planning instances is required. This opens up far reaching potential. The intelligent production machine is in a position to evaluate its own locally captured sensor and operational data and to recognize critical system states, like defects or neccessary maintenance tasks. Depending on the degree of planning priority and equipment, it is capable to solve a problem locally, for example by shifting the timing of orders, or replanning orders to other production machines. This replanning is not trivial, but can be achieved within an interlinked machine park by negotiation with appropriate planning priorities. Where whole orders, or for example finishing steps, are subcontracted across companies, finding globally optimized solutions has equal relevance for SMEs.

Here the utilization of the Internet of Things (IoT) will allow quick establishment of value adding networks and fast data exchange across company boundaries. Prerequisite are open source interfaces and standards, as currently defined and being defined within the machine to machine and IoT domains. IoT middleware systems enable the linking of production facilities at any location, any time needing minimal time and resources. This way a local intelligent machine can make its information available to the established collaborating production process across locations. The vision of InMachine is to interconnect the real and virtual world more closely at a technical level with such systems and to develop an integration concept into the existing systems and production landscape. The system will be validated and demonstrated in two typical medium sized production scenarios, continuous serial production and discrete workshop production.

Project leader:: Marius Khan

Periodt: May 2016 - June 2018

Funded by: Federal Ministry for Economic Affairs and Energy (BMWi)(Opens in a new tab) 

Funding-ID: ZF4038203SA5

The aim of the project is to develop an infrastructure for the permanent monitoring and, based on this, the reduction of the harmful gas and and dust pollution in intensive farming fattening barns. On the one hand, this is related to the demands of agriculture to achieve maximum economy and competitiveness in livestock production. On the other hand, a reduction, by up to 50%, of ammonia pollution in the the barns will greatly benefit the health of both staff and animals and in turn reduce the need for medication. The increased cleanliness of the exhaust from the barns, with the relevant verification, will also lead to increased acceptance by the local communities of any new construction or extension of animal barns near residential areas. Within this project the focus initially is on the harmful gas pollution and ammonia reduction in piggeries. The approach will be designed to be relatively easy to transfer to the housing of other animals, like cattle.

Application of the to be developed technology will, for the first time, enable the sustainable reduction of harmful gas pollution. This will include associated documentation and therefore be verifiable. Perpetual documentation of this pollution is also required by the new European Union legislation on the continuous monitoring of harmful gases in animal housing.

In summary there are three technical focal points:

Development of sensors for harmful gases, especially ammonia, based on a new infrared measurement technique that is suitable for application in animal housing. The sensor will be applicable in single gas measurement systems, as well as integrated in stationary or mobile measuring systems for stable atmospheres.

Development of a sensor circuit board that allows, not only the capture of ammonia data, but also the addition of further sensor types at run time. The board will contain interfaces suitable for the connection of hardware/software controllers for the control of stable climate improvements components, such as filters and gas scrubbing. Cooperation partner Barntec UG will take on the development of the sensors, the sensor circuit board and the hardware/software control. They are a business partner with experience in agricultural sensor development.

Development of a software engineering Smart-Data-Infrastructure which will take a barn's captured sensor data from the Hardware/Software controller, and derive control rules for optimal barn climate, based on statistical models and machine learning techniques. It will also enable long term documentation of harmful gas pollution. Based on the continuous transmission of measured harmful gas concentration data, as well as additional climate affecting data, the Smart-Data-Infrastructure will continually adapt the control rules and transmit these to the hardware/software controller. Within consideration of the existing infrastructure, optimal barn climate will be generated by best possible reduction of harmful gas pollution.

Figure 1 illustrates an overview of the envisaged system. The development of the Smart-Data-Infrastructure will be taken on by the research group Smart Environments Engineering Laboratory (SEELAB).

Project leader: Fabian Wackermann

Period: August 2015 - December 2017

Funded by: Federal Ministry for Economic Affairs and Energy (BMWi)(Opens in a new tab) 

Funding-ID: ZF4038201DB5

Economic requirements regarding logistics, for example, include a more efficient utilization of traffic routes by vehicles that act both intelligently and autonomously. However, smart cars and trucks are only one step towards a modern traffic system. A digitized transportation infrastructure, the Digital Road, is also needed to satisfy future road traffic requirements.

Within the project “High-performance Sensing and Cloud-based Real-time Data Processing for a Digital Road in Urban and Longdistance Traffic”, Fachhochschule Dortmund - University of Applied Sciences and Arts, TU  Dortmund University and the industrial partner Wilhelm Schröder GmbH are working together on tasks related to the implementation of the Digital Road. The project partners focus on comprehensive capturing of traffic data in real-time. This results in various application scenarios that include the immediate detection and notification of vehicles moving in the wrong direction, demand driven traffic flow control in urban areas and statistical analysis of traffic and parking data. The prototype developed by the project partners integrates the necessary sensor technology in delineator posts on the roadside, which supercedes the costly installation of induction loops for vehicle detection and classification.

The Fachhochschule Dortmund project team implements the Smart Data Platform, i.e. the software responsible for acquiring, processing and analyzing the captured sensor data. Fig. 1 depicts the process to be implemented by the project partners. It comprises the following steps:

• Step 1: Capturing of Raw Data
Leveraging radio tomography techniques the sensors in the delineator posts measure temporal data of passing vehicles.

• Step 2: Detection of Vehicle Characteristics
The utilization of a variety of pattern recognition methods allows the identification of lane, direction, speed and type (truck, car etc.) of a vehicle. Based on the captured data the detection algorithms are iteratively improved.

• Step 3: Sensor Communication
The sensor data set enriched with the detected vehicle attributes is transmitted to the Smart Data Platform either wirelessly or wire-based.

• Step 4: Interface Declaration
The platform offers the possibility for flexible provisioning of input and output data interfaces. The project team employs the Model-Driven Software Engineering paradigm to develop domain-specific languages, which enable the integration of new communication channels at runtime. Requirements of the data format and communication protocol of the respective interface are considered, with the result that new sensor types or adapted transmission formats may be incorporated in the platform without downtime.

• Step 5: Data Processing
Prioritized Queueing enables the platform to analyze critical data prior to those of lower importance. Hence, the communication of time sensitive traffic events like wrong-way driver detection is transmitted before processing information that does not require immediate action, e.g. statistical data. As with the interfaces, the computation processes for data aggregation are runtime adaptable. Thus, methods for calculating the number of passing vehicles or the number of vehicles in a certain parking zone at any given time, can be flexibly integrated in the platform and supplied via the defined interfaces.

Project leader: Carsten Wolff(Opens in a new tab)  

Period: September 2014 - August 2017

Funded by: Federal Ministry of Education and Research (BMBF)(Opens in a new tab) 

Funding-ID: 01IS14029K

The context of the AMALTHEA4public project is software engineering for embedded multi-core systems – predominantly for, but not limited to, automotive systems. The core scope is to aid efficient and effective model based software engineering for embedded multi-core systems.

The goal of AMALTHEA4public is to integrate results of various publicly funded projects and new developments into the methods and Ecplise-based tool platform that resulted from the AMALTHEA project. Hopefully, this will strengthen the community and drive the implementation of this tool chain in industry and research institutions in order to widely establish the tool chain platform as a de-facto standard. 

The outcomes of the earlier AMALTHEA project represent an Eclipse-based, open source tool chain infrastructure, containing several basic tools. AMALTHEA4public will offer additional new and simple interfaces to enable comprehensive adaptation and expansion of the platform. Planned features include test applications, verification and validation, safety (ISO-26262 and ISO-61508), systems engineering, product line engineering and many-core development processes, as well as domain extensions towards ICT and automation technology.

Embedded software projects, especially automotive software projects, are driven by various players, like automotive system suppliers and OEMs, tool vendors, software component or IP vendors and various engineering and consulting companies. Additionally, the complexity of automotive software projects requires dedicated tool chains tailored to the needs of the specific project. These tool chains have to combine the best in class tools, either commercially available or propriatory, as well as open source tools. AMALTHEA4public is providing a base infrastructure that facilitates the combination of these complex tools and design flows, and enables consistent data management. It allows inter-company research and development (R&D) and helps to manage software design flows for heterogeneous, cross-company, multi site, and cross-discipline projects. This enables automotive suppliers and OEMs to develop complex products more efficiently and it helps tool vendors and engineering companies to integrate their products and know-how into projects. It also improves re-use and sharing of development artefacts.

The innovative aspects of AMALTHEA4public are the integrative concept of the open source tool chain platform and the definition and integration of all necessary tools for handling the complexity of large software systems targeting multi-core ECUs. Interfaces, models and DSLs have to be designed and developed or investigated and adopted from other public funded projects for this integrative tool chain. AMALTHEA4public can incorporate innovative concepts for the early design phase to allow front loaded design, early behavior analysis and cross-domain systems engineering. Verification and test support through all stages are further innovations.

The most important expected outcomes are an Eclipse-based tool chain environment, the integration of tools for all major design steps, and the demonstration of the capabilities within a real world case showing the extended AMALTHEA design flow and methodology. On top of that a community is being built around the open source tools to disseminate the results and to ensure continuous development of the tool chain platform.

Project leader: Jan Oelker

Period: June 2016 – May 2017

Funded by: Ministry of Culture and Science of the State of North Rhine-Westphalia (MKW NRW)(Opens in a new tab) 

Funding-ID: EFRE-0400075

The shortage of care and nursing staff is a global problem. By the end of 2030, there will be a world wide shortage of 40 million nursing staff. Reasons are the weak wage development and rising demand due to the demographic changes. This trend makes senior citizens the main demand group, causing significant pressure on the health care system. This prospect is worrying for health care services, the people concerned and their families. Nevertheless, many people do not want to leave their familiar environment, even when in need of care, and would like more control, independence and active participation in health care. This results in greater demand for technical support. Current support systems, however, require the collaboration of the user, are specific to each manufacturer and have no regard for the user‘s privacy.

covibo is a technical allround-carefree system, which allows elderly people longer independent living in their own homes. It improves care, safety and comfort without disruption to their usual day to day living. 
At the same time it eases the load on the relatives and the care system. High benefit and ease of use are of high importance.

covibo combines three basic functions, automatic vital data capture, activity tracking and therapy plan. For the automatic vital data capture, the system takes the data immediately after the measurement, like weight and blood pressure, then stores and documents it. So there is no added effort besides the normal measuring. A resident‘s activity level will be passively tracked by movement detectors, door contact sensors and the operation of the system. Exceptional inactivity triggers the sending of an alarm. All taking of medication and measurements will be entered into the therapy plan, so that reminders are sounded and measures are not forgotten. Sensitive data is stored locally in the home. Residents may give access to specific data to relatives, care services or doctors. The system consists of a compact base station, a mobile app and a web service. The base station contains all functions and interfaces for environment devices, and also acts as a digital data store. The app allows visual inspection of the data. In case the resident rejects the mobile app, they have the option for a system without user interaction. The web service, not visible to the end user, can access the data externally.

The area of application is private dwellings in cooperation with the family or private home helps. This approach is a reaction to the growing demand for flexible services in the domestic sphere. The potential cooperation with care providers widens the aerea of application. The most appropriate form of care depends on the care requirements and needs of the client. Bluetooth Low Energy is the market favourite close range communication technology and so is used in covibo. The number of measuring devices and sensors using this technology is constantly rising. 
The choice of add-on devices is independent of manufacturers, making for an open, easy to integrate system. covibo is currently being used and tested under real life conditions in cooperation with a care service provider.

Project leader: Andrea Kienle

Period: April 2015 – March 2017

Funded by: DFG - Deutsche Forschungsgemeinschaft(Opens in a new tab)  

Funding-ID: GZ KI 864/3-1

The DFG project, eye tracking based interaction management of synchronous written communication (ebiss), designs and tests 
eye tracking as the basis of an innovative interaction management and for the attraction of attention in synchronous written communication.

Starting point for this project is the observation that communication systems that facilitate synchronous written communication are well established and widely utilized despite several alternatives, like video conferencing. Problems frequently arise in the sequence of the interaction, as participants can type at any time including in parallel. Conventions known from verbal communication, as well as the many implicit signals exchanged by the participants, are only partially applied in synchronous written communication. In synchronous written communication these hints are missing and situations arise where new rules of interaction need to be established.

One possibility to establish verbal interaction management in synchronous written communication, is the extension of the technical setup with the aim to supply missing information and to offer more comprehensive avenues of interaction.

Eye tracking, the capture, analysis and mirroring back of eye movements of the communication partners, when applied to synchronous written communication, represents an additional channel for the transmission 
of human actions in order to support interaction management.

The analysis and mirroring back of eye tracking data incorporates communication patterns developed in linguistics. Communication patterns describe a structured sequence of communication processes. The aims of this undertaking are the analysis of the special features of the interaction management of synchronous written communication on the one hand, and based on that, the development of validated design recommendations for eye tracking based communication tools. This basic research is of great interest against the backdrop of the current wide spread adoption of eye tracking hardware.

Project leader: Christof Röhrig  

Period: June 2014 – November 2016

Funded by: Federal Ministry for Economic Affairs and Energy (BMWi)(Opens in a new tab) 

Funding-ID: KF2795209RR3

Driverless transport vehicles (FTF) and mobile robots serve the auomated transport of goods and must navigate automatically without human intervention. Traditionally FTF were track-based using either and optical guiding beam or induction guide wire. This approach is very inflexible, so today FTF use mostly virtual guidepaths. Mobile robots usually have a greater degree of autonomy than FTF and navigate freely, without physical or virtual guidepaths. For this navigation FTF and mobile robots require knowledge of their own position and orientation with reference to a two dimensional coordinate system within the deployment environment.
Locating of mobile systems outdoors can be realised via satellite positioning systems, like GPS. In environments with insufficient GPS information, like indoors or areas shaded by buildings, determining the position with GPS is not possible. Different locating technologies need to be found for such environments.

One possible approach for determining position, using Auto-ID technology, is grid navigation. Passive RFID transponders are attached to or embedded in the floor. Future-Shape GmbH has developed NaviFloor®, a floor covering with embedded FRID transponders. By embedding the RFIF underlay in a synthetic resin floor it becomes suitable for high loadings, such as that caused by heavy FTF. RFID readers in the FTF or mobile robot can read the ID of any RFID transponder within reach. By knowing all RFID transponder positions in the deployment environment the FTF or mobile robot can determine its own position. Direct detection of orientation is not possible with this technology. Only after reading two transponders can the orientation be roughly determined.

For FTF navigation using RFID transponders up to now, the orientation at start needs to be determined manually and entered into the FTF controller. Reconciliation of the orientation during travel using RFID transponders, requires additional sensors (wheel sensors, gyroscope), as well as precise knowledge of the kinematics of the FTF in combination with the geometry and positioning of the RFID aerials. Customization needs to be done for each FTF type and implemented in the vehicle controller. This customization effort currently prevents greater spread of the NaviFloor®.
Aim of the project is the development of a modular localization device, that can determine the exact position and orientation of mobile floor bound systems like driverless transport vehicles or mobile robots, outdoors using GPS and indoors using NaviFloor®. The device should work independently of the FTF‘s or mobile robot‘s sensors. Key is the separation of the FTF localization hardware and controller hardware, to minimize the integration efforts for the FTF manufacturer.

A device was developed, together with Future-Shape GmbH, that contains integrated GPS and RFID reader, as well as further sensors for determining orientation and precise position interpolation. Suitable fusion of the sensor data with the RFID reader data will enable precise determination of orientation and position.

The localization system is primarily meant for use with FTF or mobile robots. However, any other mobile object that can have a reader attached near the floor will be supported. This could be forklift trucks, shopping trolleys, electrical wheelchairs, hospital beds or other valuable devices or objects whose location needs to be captured automatically.

Project leader: Christof Röhrig  

Period: June 2014 – November 2016

Funded by: Federal Ministry for Economic Affairs and Energy (BMWi)(Opens in a new tab) 

Funding-ID: KF2795208ED3

Locating of objects outdoors can be realized with satellite positioning systems, like GPS. In environments with no or insufficient GPS information, like indoors, or areas shaded by buildings, determining the position with satellite positioning is not possible. Different locating technologies need to be found for such environments. One possibility is locating using radio. So far localization via radio has required the setup of localization infrastructure. Localization is achieved through propagation time measurements between fixed point radio stations (reference nodes) and the to be located mobile node. From the measured propagation times to at least three fixed nodes, trilateration, for instance, allows the determination of the position of the mobile node.

In many applications it is not, however, possible to use or install such a known reference node infrastructure. In fires or emergency situations, for example, the fire services are not in a position to pre-install such infrastructure. In deployment inside buildings, satellite positioning is also not possible. Apart from that, the installation of a radio infrastructure is very expensive.

In partnership with Nanotron Technologies, the project swarmLOC is developing a novel infrastructre free, or low infrastructure, 
localization system, that enables the cooperative location detection of people and objects using radio propagation time measurements. The system will be based on a mobile ad hoc network and so be completely independant of any installed infrastructure. This approach makes rapid deployment of the system possible.

Each radio node will be optionally extended by further sensors. For instance GPS or proximity based sensors, like RFID, supply absolute position information, that can supplement the relative positions from the cooperative localisation system. Inertia sensors can additionally increase the accuracy of the location data. Cooperative localization algorithms, based on probabilistic filters, will be used in the fusion of all differnt sensor data. Swarm-based algorithms especially will be analyzed with respect to their efficiency and suitability in the planned system.

Figure 1 shows collision prevention in open cast mining as a possible application of swarmLOC. The person carries a radio node and communicates with the radio nodes in the vehicles. Cooperative locating provides localization of all radio nodes relative to each other and drivers are warned of any collision dangers.

Project leader: Klaus-Peter Priebe

Period: August 2014 – July 2016

Funded by: F(Opens in a new tab) ederal Ministry for Economic Affairs and Energy (BMWi)(Opens in a new tab) (Opens in a new tab) 

Funding-ID:
KF3338401ST4 FH-Dortmund
KF2795210ST4 FH-Dortmund

Climate change, the need to minimize CO2 emissions and the finite availability of fossil fuels are all driving the undisputed need for maximizing the exploitation of waste heat. Organic Rankine Cycle (ORC) turbines can efficiently generate direct mechanical work and electricity from low temperature heat. The ZIM ORC-Project for the development of a most efficient, double-staged ORC-facility for the generation of electricity from waste heat is supported by the German Federal Ministry for Economic Affairs and Energy (BMWi). A fully functioning prototype of a small power plant is being constructed. Fachhochschule Dortmund - University of Applied Sciences and Arts looks after the electrical and communication networks and the brain of the installation for optimal power and thermal control. Paderborn University is responsible for the thermodynamic design, Smart Mechatronics for the control engineering, and Lütkemüller GmbH and Heim Precision Technology for the mechanics and turbines. 

The construction contains a number of replaceable modules. Figure 1 illustrates these modules from right to left. Module 1 represents the direct evaporator followed by module 2, the high temperature system up to 300 °C, module 3, the low temperature system up to 110 °C and finally module 4, the condenser/liquefier. Due to the modular design, systems can be built with one or two ORC turbines, allowing adaptation for different waste heat profiles. The system can be configured to work with waste heat input of only 500 kWth. Currently available solutions require far greater thermal input for economic feasibility. 

Development of demand based control for the two stage installation is particularly challenging. A hierarchical management and control system, based on the Operator-Controller-Module (OCM) from Paderborn University is being developed. Control of the first level depends on Paderborn University‘s thermodynamic data for the various mass cycles, as well as on the thermodynamic behavior of the devices in the system. 
Regulation of the second level control circuits comes from a Model Predictive Controller (MPC) and is based on Matlab/Simulink modeling. Level 3 of the OCM model is the communication network and control center of the machine. It is implemented as a reflective operator for process control and error handling and can automatically correct faults, or carry out a controlled shut down if necessary. Finally, level 4 as the cognitive operator contains the self-learning optimization program, designed to optimize economic operation of the whole system under varying conditions and with due consideration for maintenance cycles and costs. 

The target markets of this technology can be found wherever there is waste heat above 300 °C with more than 300 kWth of power. These levels of available heat are common in biogas power plants and in industry, and also in solar thermal power generation. The development goal is to generate additional electricity from waste heat at "better than grid parity". This means, 1 kWh from waste heat must cost no more than 0.12 €/kWh, including all costs and without support funding, and with a pay back period of less than six years.