University of Oulu

Intelligent Systems Group (ISG)

Professor Juha Röning, Professor Jukka Riekki and Professor Tapio Seppänen,
Computer Engineering Laboratory, Department of Electrical and Information Engineering, University of Oulu
juha.roning(at), jukka.riekki(at), tapio.seppanen(at)

Background and Mission

The Intelligent Systems Group’s (ISG) mission is to carry out long-term research on novel technologies and applications of intelligent systems. The main objective is to develop enhanced adaptivity and context-awareness for smart environments. The research specifically focuses on the creation of dynamic models that enable monitoring, diagnostics, prediction and control of target systems (living and artificial) or operating environments. It is our aim to make the environment adapt to the users, instead of making the users adapt to an inflexible environment. We believe that, by creating these novel components for smart environments, important enabling functionality will emerge that will multiply the versatility and applicability of such living environments.

We see behaviour modelling as a major challenge in developing truly intelligent and proactive environments. Human users of smart environments often behave in such a complex manner that it is hard to predefine and preprogram all of their behavioural patterns in the software. Models of user behaviour are required that are able to grasp the user’s context at any moment and to enable adaptation of the functionality of the intelligent environment to the situation at hand. Further, it is essential to model the behaviour of the devices controlled by the intelligent environment, which enables adaptation to environmental changes without reprogramming. Systems should eventually learn and adapt automatically through these models, and thus perform their duties effectively.

Our research group combines a variety of key skills and technologies to attain this goal. We have experience of the following key technologies: system architectures and implementation of context-aware systems; modelling and recognition of contexts from sensor signals; data mining algorithms; nomadic learning robots; embedded systems technologies; software security; and smart environment implementations. The key application areas are: smart living environments of homes and institutes; industrial automation; mobile robots; context-aware mobile devices; and wellness and medical applications. Each of these domains possesses special characteristics but, from the point of view of developing algorithms for an intelligent system, they also possess remarkable similarities. They all produce a multitude of signals that represent the status of the system. The target system behaviour should be modelled and recognized based on the signals. The application service should then act accordingly. The availability of several application domains yields many advantages: a solution to a special problem in one domain may offer added-value functionality in some other domain; our solutions are deployed by many of our client industries; solutions to a wide range of real-world problems define a credible and versatile tool-box that has a major impact on our development-oriented subcontractual projects.

The group co-operates with many international and domestic partners. In applied research, the group is active in European projects, and several joint projects funded by the Finnish Funding Agency for Technology and Innovation (Tekes) and by industry.

The group and its members are active in the scientific community. For example, Prof. Juha Röning served as Co-chair on the program committee of Intelligent Robots and Computer Vision XXIV: Algorithms, Techniques, and Active Vision (1-4 October 2006, Boston, Massachusetts, USA). In the software security area The European Intensive Programme on Information Security Management and Technology 6th Winter School was arranged in Oulu 4-12 April, 2006 and The Second Crisis Management Workshop (CRM2006) in Rovaniemi. Finland, September 28, 2006. Prof. Riekki arranged a co-operative seminar in Sendai, Japan in Spring 2006. Also several members of the group were on the committees of international conferences. The group’s expertise is recognized; for example, one survey for the Finnish Ministry of Transport and Communications was prepared as well as several invited talks and lectures were given.

The third To be or Well be seminar on wellness was arranged in Oulu. Prof. Seppänen was one of the main organizers. Almost 200 visitors from all over Finland participated the seminar. Prof. Seppänen was a leading figure in establishing the WellTech Oulu institute for wellness and medical technology in the University of Oulu. The new institute coordinates the research and education in this area, as well as participates in various activities in the operating environment. Prof. Seppänen was also the leading figure in the establishment of the Oulu School of Biomedical Engineering, an umbrella organization of wellness and medical technology education at the University of Oulu and the Oulu University of Applied Sciences.

We have talented members in the team. The Master’s thesis “Exploiting Communication Patterns in Complex Information Networks” by Jani Kenttälä received two awards, the Telecom Scholarship 2005 (best telecom related thesis in Finland published in 2005) and the Finnish Association for Mathematicians, Physicists and Computer Scientists (SMFL) prize for the best pro gradu thesis in 2005.

Interest in our research has been strong. For example this year the EU Press delegation from Japan, Korea and Malaysia and the Finnish Minister of Education and Science visited our research group. During the visits, robotics research was demonstrated.

The activities of the ISG are led by professors Juha Röning (Director), Jukka Riekki and Tapio Seppänen.

Scientific Progress

In 2006 the research at ISG concentrated on prototyping smart environments, mobile and context-aware systems, data mining methods, signal analysis and secure programming. These were applied in context-aware mobile systems, intelligent service robots, steel plant and spot welding process quality control, and analysis of biomedical ECG and EEG signals.

Research on prototyping: from a smart environment towards remote distributed intelligence

Verification of the developed methods and models in prototypes will be an important part of the research. To support this activity, we will develop software and hardware architectures for smart environments. In addition to verification, prototypes speed up the commercialization of the research results. In prototyping, we have set and tackled the following objectives:

Developing software architectures for a smart environment. The aim is to create a software architecture supporting the development of context-aware applications for a smart environment. We have developed a Property Service Architecture, a modular and scalable software concept that provides the possibility to connect resources to larger systems. The distributed system consists of device services that provide features and functionalities to systems, and control services that create smart functionalities for the whole system. Different kinds of devices can be tested on the system as they communicate similarly, and even complex applications can be built rather easily using higher level control services. Dynamic capabilities of the general interface provide the possibility to expand and adapt the system to match the task and environment’s requirements.

The other main objective here is to develop an architecture that provides a software library that integrates all our research work to a rich set of tools. Therefore these methods and solutions are easily usable on forthcoming projects which speeds up and develops our research work and capabilities.

Developing hardware architecture for a smart environment. The aim is to develop a basis for devices operating in a smart environment. We have recently developed a modular electronic concept, called Atomi, and created general software components for building complex activities. Atomi electronics provides us with a possibility to modify the hardware easily; new functionalities are available immediately in a plug-n-play way. Modularity has been achieved using Atomi electronics and a modular software architecture - Property Service, which provides an interface for these resources and an opportunity to control different robots and other devices in a smart environment.

Building a testing environment. In addition to software and hardware architectures, a test environment will be needed. We are building a prototype of a smart living room in our laboratory. This living room will be a large, proactive system. The technology and computation will be hidden as far as possible; the goal is to provide the user with a natural environment that offers advanced services. The hardware for the first version of the prototype has been installed. The implementation of the basic software and the development of the computational methods will continue.

Remote Distributed Intelligence. The aim is to develop a prototype for testing and verifying Remote Distributed Intelligence. This is realized by implementing a multi-agent system composed of state-of-art miniature mobile robots equipped with sensors and communication devices which support a wide range of applications including guarding, inspection, and environment monitoring. This research will give us valuable knowledge about the possibilities of a multi-robot team in real world applications.

Miniature mobile robots form a multi-robot team to investigate Remote Distributed Intelligence.

The miniaturization of mobile robots is rapidly progressing due to developments in electronics and material technology. Multirobot systems composed of a group of miniaturized robots can have numerous applications in the future. They may be a regular sight on space expeditions or they may operate inside the human body for our well being. At present, multirobot systems are a rare sight in real world applications. However, they have already been used in surveillance applications, military demonstrations, and in distributed sensing applications.

Distributed sensing is an interesting application domain as the multirobot system is inherently spatially distributed. The spatial distribution of robots can be naturally utilized to overcome problems that the miniaturization of the robots introduces to the sensing technology in some problem domains. We have shown how a multirobot system can be used to extract 3-D information from an environment with a system of two heterogeneous robots which together form a distributed structured light based scanning device. The distributed 3-D scanning concept is useful in applications where a group of robots needs to extract geometrical information in remote locations without a requirement that a single robot must alone carry the necessary technology for performing the range measurements.

Top: a range image from a cooperative 3-D scanning experiment. Two robots have scanned a person laying on the floor. The image demonstrates how, by simple cooperation, a pair of miniature mobile robots (bottom) can obtain dense range data from objects of an environment.

An infrared based location module was developed for the miniature robots. The module provides information about the relative poses of the robots. The module can be used to create measurement formations and automatically perform measurements about lighting and the magnetic field of the environment, for example.

A measurement formation.

Measured directions of the local magnetic field.

Miniature robot with the location module on the top.

Wireless sensors. Based on our long experience in mobile robotics and sensor systems, we have developed small wearable wireless sensors for measuring the activity of humans and objects. The sensors provide information about 3-D acceleration, temperature, atmospheric pressure, sound space and lighting conditions every 10 ms. This information is used to recognize the context of a person. The sensors can also be attached to the objects the person is manipulating, which makes it possible to register the measurements from different sources (human and objects), and to recognize various human-environment interactions. Recognizing human-environment interactions has many applications, especially in sports and education.

A wireless sensor (top right) and a base station (centre). The base station receives the sensor readings and saves them into a memory card. The data can later be downloaded into a host computer for data analysis.

Swarm robotics. ROBOSWARM is an EU project that was launched on November 1st 2006. Together with eight other participants ISG has an important role in this project, which aims to develop an open knowledge environment for self-configurable, low-cost and robust robot swarms usable in everyday applications. Advances in the state-of-the art of networked robotics are proposed through the introduction of a local and global knowledge base for ad hoc communication within a low-cost swarm of autonomous robots operating in a surrounding smart IT infrastructure.

Knowledge environment for Interacting Swarms: demonstration system of ROBOSWARM.

Research on context-aware services

A growing variety of services are nowadays available for users. We are approaching a situation where the sheer number of services hinders their utilization. Our hypothesis is that this service overload can be managed by utilizing the user’s context. To develop context-aware services, we have set and tackled the following objectives:

Recognizing the user’s context. The aim is to find and develop methods for recognizing the user’s context from sensor data using signal processing, pattern recognition and machine learning methods. Context can be used to identify the services that are relevant in the situation at hand - and to adapt these services. In earlier research, our focus has been on wlan position data, data produced by our pressure-sensitive EMFI floor and heart rate measurements.

The research of user modelling on the EMFI floor has been concentrating on development of machine learning and pattern recognition methods for footstep-based person identification as well for real-time multiple object tracking. In the person identification domain, different base classifiers from the statistical machine learning field are tested. An ensemble learning method, which uses multiple base classifiers trained on different features sets, is developed. In ensemble learning, two level combinations of base classifiers’ probabilistic outputs and multiple adjacent footstep profiles are fused to make an accurate decision on a person’s identity. The best results were achieved using Support Vector Machine (SVM) base classifiers and the features based on spatial, statistical, and spectral properties of footstep patterns. A 95% success rate of ten different walkers was achieved. In addition, we have studied real-time multiple person and mobile robot tracking, based on dynamic sequential modelling of moving objects; they are individually tracked using Particle Filtering (PF). The method is able to track a small number of objects simultaneously on the floor and it gives ground for future work on higher level contextual and behavioural modelling of users and robots. The figure below shows an example of PF tracking estimates of two moving objects on the floor.

Particle Filtering tracking estimates of two moving objects on the floor.

We have also continued our work on activity recognition and sentient artefacts based on signal processing and learning methods utilizing the measurements from different sensory devices. One of our post doc researchers visited the Distributed Computing Laboratory (DCL) at Waseda University in Tokyo, Japan. Also, during 29th October - 28th December 2006, Dr. Kaori Fujinami from DCL visited ISG.

The research aims at reliable context recognition, utilizing different sensory devices and sentient artefacts. Together with DCL members, pattern recognition methods for extracting people’s context, the management of contextual information, and ways of dealing with the heterogeneity of sensing device and contextual information are studied. In our research, we have combined the environmental context and the user context (activity). In our system, the user’s activity was recognized from wearable 3D acceleration sensors (on the right wrist and thigh, triaxial acceleration signals), shown here in the figure on the right, with a neural network. This information was combined to the state-of-use of a sentient artefact (embedded with 3D acceleration sensors, pressure sensors, or other sensors) with a linkage condition (sitting activity linked to a chair, walking activity linked to a door). This way the wearer was identified as the user of the artefact. In the case of multiple users performing the same activity, the identity of the user was verified with correlation analysis between the artefact’s and user’s acceleration signals.

Modelling user behaviour. The aim is to find models that can be used to predict user behaviour. User models will enable services to be adapted automatically based on the users’ personal preferences and also enable proactiveness. Objectives will create the necessary basis for this work; the model will be created by observing the user’s context changes and actions over time. In earlier research, we have created rule-based models of user behaviour by utilizing data mining algorithms to associate different contexts in order to better serve the user. In the future, adaptive machine learning models based on neural networks, kernel methods, and sequential modelling will be applied along with the study of novel sensor measurements recorded from the different wearable and environmental sensing devices. We have continued this co-operation with Waseda University, and also the co-operation with the Tokyo University of Agriculture and Technology is planned.

Labelling personal information with context. The aim is to develop methods that could help in the management and utilization of the growing quantities of digital information related to our lives. The hypothesis is that context is an intuitive way of organizing personal information, as it allows users to relate information to their experiences. We especially aim to produce a methodology for collecting and storing an extensive set of digitally available, context-labelled data from a person’s everyday actions and activities, and to outline data mining and learning methods for accessing, visualising and utilising such data in useful ways.

Providing easy access to services through tangible interfaces. The aim is to develop an intuitive tangible interface for requesting services with a single touch. We utilize RFID tags mounted in the environment and RFID readers integrated in mobile phones. The tags connect the physical and digital environments. Visual symbols communicate to users the objects that can be touched and the services that can be activated. When a user touches such a symbol with a mobile phone, the data stored in the tag and other contextual information related to the situation trigger the requested service. This work is related to the first objective, recognizing the user’s context, as touching an RFID tag produces accurate information about that context. We have designed sets of visual symbols in co-operation with the Department of Industrial Design at the University of Lapland. In the CAPNET project, we implemented together a tourist information board that is equipped with RFID tags and visual symbols, see the figure below. Touching a symbol brings a list of services into the mobile phone’s screen. From this list, the user can, for example, request a map to be shown on the phone’s screen. The map shows a path from the user’s current location to the target that she touched with the phone. The usability and user experience studies indicate that touching visual symbols with a mobile device is an easy way to activate services. Based on our findings, we list security, controllability and social acceptance as the main challenges in deploying this interaction method in everyday use.

Services can be activated by touching a tourist information board with a mobile phone that is equipped with an RFID reader.

Research on data mining
Biosignal processing

Sudden cardiac arrest is the most common cause of death in western countries. It accounts for approximately 50% of cardiovascular deaths and apparently has a highly variable pathophysiological etiology. The risk of sudden cardiac arrest is high in certain subgroups of patients with a history of myocardial infarction and depressed left ventricular function. The key question in research is why do some subjects develop ventricular fibrillation during acute coronary occlusion, while others survive this episode without fatal arrhythmia. The challenge for research is to develop approaches or techniques that will allow the screening of the specific risk for fatal ventricular arrhythmias as a predictor of the first event in patient populations that have a low cumulative risk, but generate a large number of victims. In addition, the predictive value of many known risk factors of sudden cardiac arrest among patients with known heart disease has not been definitively established.

Our approach to studying the heart is based on the analysis of a 12-lead ECG (electrocardiogram). ECG contains information on cardiac function that is highly relevant to diagnosis and treatment. This information includes signals of atrial electrical activity (P-wave of ECG and the corresponding atrial repolarization signal mixed with the QRS complex) and also of ventricular repolarization (T-wave). We have set and tackled the following objectives:

Computation of risk markers from ECG characteristics. The aim is to develop new methods and algorithms for the analysis and interpretation of electrophysiological signals and the autonomic regulation of the cardiovascular system. The digital 12-lead ECG was decomposed into multi-dimensional dipolar and non-dipolar components in the depolarization and repolarization phases in order to derive new risk markers of heart diseases. 12-dimensional principal component analysis was performed to extract dipolar (vector cardiographic) and non-dipolar components from the measurement signal. The depolarization and repolarization phases were analysed separately, and various parameters (e.g., VCG loop descriptors and singular value-based descriptors) were developed that describe the electrical functioning of the heart during one beat or in continuous ECG.

VCG-based simulation of cardiac electrophysiologic functioning.

Real-time measurement and interpretation of ECG includes challenging signal processing problems that are related to false alarms caused by motion artefacts of the patient. New adaptive signal processing solutions were developed that filter motion artefacts effectively through VCG-based modelling of heart behaviour, and produce significantly enhanced ECG signals. Novel solutions for automatically detecting ECG morphology changes were derived from a theory of invariant pattern recognition. Techniques were developed that can correct multichannel ECG for motion artefacts of moving patients. Algorithms were implemented that can classify the motion-artefact corrected ECG in various classes depending on patient symptoms.

An ELD-based (Equivalent Double Layer) simulation environment was utilized to model myocyte-level action potential changes of infarcted heart ventricle tissue. The infarct location, size and severity were varied and it was shown that these parameters affect significantly some commonly used ECG indexes.

Modelling of the functioning of the autonomic nervous system. The relationships between ECG, blood pressure, breathing and sympathetic nervous activity signals were modelled and identified from actual signals in order to develop new models for the autonomic control of the cardiovascular system. A novel method was developed for adaptively filtering respiration artefacts from ECG and blood-pressure signals. This method produces a significantly improved of BSR estimate than earlier reported in the literature. Measurement equipment was used that only a few research groups possess in the world.

Analysis of an autonomic nervous system from multiple biosignals.

Modelling of physical fitness. A new model was developed for estimating the endurance fitness level of a runner from the physiologic signals and contextual information related to the runner. The new method can estimate the endurance fitness within 5% inaccuracy as compared to a running ergometer.

Estimation methods of anaesthesia depth. The aim of this task is to develop new methods and algorithms for estimating the depth of anaesthesia from multi-channel EEG. A new concept of relative induction time was developed which enables a significant improvement in the depth estimation from EEG. The new method produces a time-continuous value for the depth estimate, and accurately predicts the instance of loss of consciousness. The method was extended such that it can model the depth of anaesthesia such depth that burst-suppression of EEG begins to evolve

Estimation of anaesthesia depth from ECG.


Modelling of human text writing. New techniques for predicting text production of a keyboard user were developed. The solution includes advanced statistical models of word combinations and word-class combinations, which effectively enhance text production.

Real-time data mining systems

The goal of this research track is to create on-line data mining systems with semi-independent updating properties, methods for fast and reliable implementation of the systems and installations of the new technology in real applications.

Smart Archive. The aim is to develop a framework for real-time modelling of phenomena that continuously produce new measurement data. The focus area of the technology under development is intelligent on-line data processing for the purpose of on-line modelling. The development of a software framework that enables the rapid realisation of new models as software applications is currently in progress. By using the framework, the implementation and set-up times of models can be significantly reduced, and their operational reliability improved. A specific issue to be addressed is the selective storage and effective utilisation of accumulating data that eventually comes to represent the full spectrum of the phenomenon being modelled. The technologies to be developed are collectively known as the Smart Archive. An advanced prototype version is being used to create a series of data mining solutions for diverse industrial application domains, and based on the resulting experience, the design of the framework will be further refined. The ultimate goal is a truly generic data mining meta-application with a graphical user interface that allows application instances to be constructed parametrically with the minimum quantity of application-specific code.

Joint modelling of mean and dispersion, based on large data sets is an example of a real-time industrial application. Industrial applications of data mining often focus on developing and optimizing production processes based on data gathered from production lines. The benefits include a higher level of automation, more accurate process control, better quality of goods, and improved customer satisfaction. The aim of this application was to develop new methodology for joint modelling of mean and dispersion for industrial purposes. Models for predicting the mean and variance of the mechanical properties (strength, elongation, toughness) of steel plate products have been developed. The models are utilized in a production line to optimize the process settings, based on the predicted risk of disqualification in the testing of mechanical properties. Also, methodology for the modelling of a time-varying conditional variance function has been developed.

Research on software security

Within the Intelligent Systems Group, the Oulu University Secure Programming Group (OUSPG) has continued research in the field of implementation level security issues and software security testing. Software implementation may introduce potential for unanticipated and undesired program behaviour; for example, an intruder can exploit such vulnerability to compromise the computer system.

In 2006, the research focus has been on the implications and relationships of the different technologies in complex systems. Information network environments are more complex than ever before, and this complexity will increase in the future. One important factor affecting the increase of the complexity is the convergence of information networks. One seemingly simple event may generate a number of small actions in different parts of the network. Additionally, different components may use varying protocols. Thus the development, deployment and management of complex networks are laborious and require in-depth understanding of different fields. OUSPG has approached the issue from three different directions: causal relationships, protocol genes and protocol dependence.

Causal relationships. The aim is to develop methods for inferring causal relationships in complex systems. The research applied data mining to network traffic to find data relevant to the system being analysed. Applications of the method include getting an overall view of the communication patterns of complex systems, diagnostics, and security risk assessment.

Test cases test12.arj and test13.arj causing an implementation to fail.

The results of the project were commercialized in a spin-off company, Clarified Networks Oy. The business plan was a finalist in the Venture Cup 2006 competition and was awarded a local prize. The research results were also applied in the HowNetWorks network monitoring appliance, which participated in the VMware Ultimate Virtual Appliance Challenge competition, and ultimately won the grand prize of $100,000.

In 2007, the work will be continued with a three-month research visit to Dartmouth College, where the methods will developed further for analysis of large scale wireless networks.

Identification of protocol genes. This research approaches the problem of complexity from the other direction by developing tools and techniques for reverse-engineering and identification of protocols using protocol genes - the basic building blocks of protocols. The approach is to use techniques developed for bioinformatics and artificial intelligence. Samples of protocols and file formats are used to infer structure from the data. This structural information can then be used to effectively create large numbers of test cases for this protocol.

Visualisations of file format analysis and fuzzing.

Vulnerability management of the information infrastructure contributes to protocol dependence: another angle of approaching this problem is through technology dependencies. This activity studies the impact factor of different technologies on CNI and develops a visual model for understanding dependencies related to protocols. This was accomplished by extending traditional Wikis, which are effective mass collaborative authoring services, with graphing extensions. Graphingwiki enables the deepened analysis of the Wiki data by augmenting it with semantic data in a simple, practical and easy-to-use manner. Visualisation tools are used to clarify the resulting body of knowledge so that only the data essential for a usage scenario is displayed. Logic inference rules can be applied to the data to perform automated reasoning based on the data. Perceiving dependencies among network protocols presents an example use case of the framework.

Impact of several vulnerabilities.

Exploitation of Results

The results of our research were applied to real-world problems in many projects, often in collaboration with industrial and other partners. Some examples of exploitation are described below.

The Intelligent Systems Group utilizes a robotics laboratory and pressure-sensitive floor (EMFi material) installed in our laboratory as part of a smart living room. Other equipment includes a home theatre, two degree-of-freedom active cameras, four mobile robots and one manipulator, a WLAN network, and various mobile devices (PDAs, a tablet PC, Symbian mobile phones). WLAN positioning covers a large part of the campus (including the laboratory), and a home automation network is being installed. Our aim is to gradually build a versatile infrastructure that offers various generic services for pervasive applications. Naturally, this kind of environment enables realistic experiments that lead to a better understanding of such applications.

The group’s expertise in robotics was applied in developing a mobile robot for domestic help. A teleoperated robot serves as the remote eyes of the elderly and those who take care of them. During the reporting period, the main task was to develop teleoperation capabilities for the robot. A voice controlled service robot was successfully demonstrated. The purpose of the robot is to assist elderly people in their homes and provide a communication link to health care personnel. A design project was launched with the University of Lapland to further develop the appearance of the robot, and make it suitable for various applications and research studies regarding human-robot interaction.

The development in robotics has continued in the area of mechanical and miniaturization research. Qutie is an interactive mobile robot designed in co-operation with the University of Lapland. In the current year, development has focused on modular electronics, the Atomi concept, and the creation of general software components for building complex activities for the robot. As the robot has several actuators and sensors it is also a good platform for developing a method of building complex robots using modules. Modularity has been achieved using Atomi electronics and the modular software architecture Property Service.

The Atomi electronics is an implementation of our Embedded Object Concept (EOC). The EOC utilizes common object-oriented methods used in software by applying them in combined Lego-like software-hardware entities, embedded objects. This concept enables fast prototyping with target hardware, incremental device development and high-level device building for non-experts. The figure below demonstrates the idea of using the Atomi objects.

Prototyping with Atomi objects.

The development of a miniature robot is preparatory action towards swarm robotics research. Instead of using large robots, it is often desirable to have multiple small robots to save valuable work space and make the maintenance of the robots easier. Also, the implementation cost of a miniature robot is lower because of the simpler mechanical design. We have developed a novel modular miniature mobile robot designed for swarm robotics research. The sensor set of the robot includes a colour stereo camera system with two CMOS cameras and DSP, allowing each robot to perform sophisticated stereo image processing on-board. The modular design permits the addition of new modules into the system. The modules communicate using three serial buses (SPI, I2C, and UART), which enable flexible, adaptive, and fast inter-module data exchange. The robot is developed for swarm robotics research with the aim of providing a low-cost and low-power miniature mobile robot with capabilities typically found only in large robots.

During year 2006 a group of five miniature robots were fabricated, and all the necessary software components were implemented to enable the utilization of the multi-robot team in basic research.

The robot developed is a part of research which aims at understanding how a global objective can be achieved by a multi-agent system without explicit regard for cooperation with the other agents, and to investigate the relationship of spatial patterns composed of interacting entities (agents) and the resulting dynamics.

In addition, we are investigating how humans can effortlessly interact and control a multi-agent system and gain meaningful information about the environment through it, and we study what are the minimal requirements for an agent in order to produce useful behaviour at the system level.

In addition to the core research, OUSPG also maintains a test network infrastructure for research groups such as OUSPG, ISG and MediaTeam. Test networks are required for the safety of both our own research and innocent bystanders, and one was constructed for internal use in the laboratory. The network provides a fully functional infrastructure with services such as storage, backups, DNS and mail.

The infrastructure started life as an isolated test network for OUSPG use, but has expanded to provide a basic infrastructure for others with similar needs. There are three separate networks: a core network for basic services, the combined playground and the wireless access network panOULU, and an Internet-connected network with connectivity independent of the main university network.

Future Goals

We will continue to strengthen our long term research and researcher training. We will also continuously seek opportunities for the exploitation of our research results by collaborating with partners from industry and other research institutions in national and international research programs and projects. The group is a founding member of the European Robotic Network of Excellence (EURON). The group is a contract member of EURON II which was approved for the EU’s 6th framework as a Network of Excellence. We will strengthen our international research co-operation. One of our researchers made a 10 month post doc research visit to Professor Tatsuo Nakajima at Waseda University. We are making arrangement for another researcher visit to his laboratory. Also a three-month research visit to Dartmouth College will be made in the Spring 2007 and one of our researchers will start a one-year visit to NRC Cambridge in Autumn 2007. The group is participating two EC funded projects. A STREP project, ROBOSWARM had its kick-off meeting November 2006 and an IP project XPRESS will start in January 2007.


professors & doctors


graduate students






person years


External Funding



Academy of Finland

38 000

Ministry of Education

232 000


467 000

domestic private

257 000

EU + other international

326 000


1 138 000

Doctoral Theses

Laurinen P (2006) A top-down approach for creating and implementing data mining solutions, Acta Universitatis Ouluensis C 246.

Koskinen M (ISG) Automatic assessment of functional suppression of the central nervous system due to propofol anesthetic infusion. From EEG phenomena to a quantitative index. Acta Universitatis Ouluensis C 253.

Juutilainen I (2006) Modelling of conditional variance and uncertainty using industrial process data. Acta Universitatis Ouluensis C 258.

Kerttula M (2006) A framework for the development of personal electronic products. University of Oulu.

Selected Publications

Ahonen P, Karjalainen K, Kuusela E, Lehtonen S, Puuperä R, Röning J, Savola R, Tokola T & Uusitalo I (2006) Information security in wireless networks. LUOTI-julkaisuja 9/2006.

Elsilä U & Röning J (2006) Analysis of wedge formation in hot strip rolling after continuous casting. - Modeling of casting, welding, and advanced solidification processes. Eds. C-A Candin & M Bellet, USA. The minerals, metals & materials society, 767-774.

Eronen J & Röning J (2006) Graphingwiki - a Semantic Wiki extension for visualising and inferring protocol dependency. Proc. 1st SemWiki Workshop, June 11-14, Budva, Montenegro.

Fujinami K, Pirttikangas S, Nakajima T (2006) Who opened the door?: Towards the implicit user identification for sentient artefacts Adjunct Proceedings of Pervasive 2006, May 7-10, Dublin, Ireland, 107-111.

Haapalainen E, Laurinen P, Junno H, Tuovinen L & Röning J (2006) Feature Selection for identification of spot welding processes. The 3rd International Conference on Informatics in Control, Automation and Robotics (ICINCO 2006), August 1-5, Setubal, Portugal.

Hautala A, Kiviniemi A, Mäkikallio T, Tiinanen S, Seppänen T, Huikuri H & Tulppo M (2006) Peripheral sympathetic outflow correlates with the response to endurance training. 11th European Collage of Sport Science (ECSS), Lausanne, Switzerland, Book of Abstracts p. 304.

Juutilainen I, Röning J (2006) Adaptive modelling of conditional variance function. 17th Symposium of IASC (COMPSTAT 2006), August 28 - September 1, Rome, Italy.

Juutilainen I & Röning J (2006) Planning of strength margins using joint modelling of mean and dispersion. Materials and Manufacturing Processes 21(4): 367-373.

Kajava J, Anttila J, Varonen, R, Savola R & Röning J (2006) Information security standards and global business. Proceedings of International Conference on Industrial Technology (ICIT 2006), December 15-17, Mumbai, India, 2091-2095.

Kajava J, Anttila J, Varonen R, Savola R & Röning J (2006) Senior executives commitment to information security - from motivation to responsibility. International Conference on Computational Intelligence and Security (CIS2006), November 3-6, Guangzhou, China, 1519-1522.

Kawsar F, Fujinami K, Pirttikangas S, Nakajima T (2006) Personalization and context aware services: A middleware perspective. Proc. 2nd International Workshop on Personalized Context Modeling and Management for UbiComp Applications, in conjunction with UbiComp2005, the 7th International Conference on Ubiquitous Computing.

Kemppainen A, Haverinen J & Röning J (2006) An infrared location system for relative pose estimation of robots. Proc. 16-th CISM-IFToMM Syposium of Robot Design, Dynamics, and Control (ROMANSY 2006), June 20-24, Warsaw, Poland, 379-386.

Kiviniemi A, Hautala A, Mäkikallio T, Seppänen T, Huikuri H & Tulppo M (2006) Cardiac vagal outflow after aerobic training by analysis of high-frequency oscillation of the R-R interval. European Journal of Applied Physiology, 96(6):686-692.

Kiviniemi A, Huikuri H, Hautala A, Tiinanen S, Seppänen T, Mäkikallio T, Tulppo M (2006) Changes in fluctuation pattern of cardiovascular signals during sympathetic activation. 11th European Collage of Sport Science (ECSS) Annual Meeting, Lausanne, Switzerland 2006. Book of Abstracts, p. 301.

Koskinen M, Mustola S & Seppänen T (2006) Forecasting the unresponsiveness to verbal command on the basis of EEG frequency progression during anesthetic induction with propofol. IEEE Transactions on Biomedical Engineering 53(10): 2008-2014.

Koskinen M, Seppänen T, Tong S, Mustola S & Thakor N (2006) Monotonicity of approximate entropy during transition from awareness to unresponsiveness due to propofol anesthetic induction. IEEE Transactions on Biomedical Engineering 53(4): 669-675.

Laurinen P, Siirtola P & Röning J (2006) Efficient algorithm for calculating similarity between trajectories containing an increasing dimension. Artificial Intelligence and Applications (AIA 2006), February 13-16, Innsbruck, Austria.

Linna E, Perkiömäki J, Karsikas M, Seppänen T, Savolainen M, Kesäniemi A & Huikuri H (2006) Functional significance of KCNH2 (HERG) K897T polymorphism on cardiac repolarization assessed by analysis of T-wave morphology. Annals of Noninvasive Electrocardiology 11: 57-62.

Perkiömäki J, Hyytinen-Oinas M, Karsikas M, Seppänen T, Hnatkova K, Malik M & Huikuri H (2006) Usefulness of T-wave loop and QRS complex loop to predict mortality after acute myocardial infarction. The American Journal of Cardiology. 97: 353-360.

Pietikäinen P & Huttunen L (2006) Behavioral study of bot obedience using causal relationship analysis. Proc. 18th Annual FIRST Conference, June 25-30, Baltimore, MD, USA.

Pirttikangas S, Fujinami K, Nakajima T (2006) Feature selection and activity recognition from wearable sensors. International Symposium on Ubiquitous Computing Systems (UCS2006), October 11-13, Seoul, Korea, 516-527.

Pirttikangas S, Riekki J & Hietajärvi J (2006) Extensions for CommonGIS to aid the development work of context-aware systems. Advances in Computer Science and Technology (ACST 2006), January 23-25, Puerto Vallarta, Mexico.

Riekki J, Salminen T & Alakärppä I (2006) Requesting pervasive services by touching RFID tags. IEEE Pervasive Computing 5(1):40-46.

Seydou F, Ramahi O, Duraiswami R & Seppänen T (2006) A numerical computation of Green’s function in two-dimensional finite-size photonic crystal of infinite length. Optics Express 14(23): 11362-11371.

Seydou F, Ramahi O & Seppänen T (2006) Analytical computation of energy levels and wave functions in chaotic cavities. Invited speech. Bellagio International Workshop on Mathematical Modeling, Simulation, Visualization and e-Learning, November 20-26, Bellagio, Italy.

Seydou F & Seppänen T (2006) A volume integral method in inverse scattering. IEEE AP-S International Symposium, USNC/URSI National Radio Science Meeting AMEREM Meeting, July 9-14, 2006, Albuquerque, New Mexico.

Tikanmäki A, Haverinen J, Kemppainen A & Röning J (2006) Remote-operated robot swarm for measuring an environment. Proc. ICMA 2006 - International Conference on Machine Automation, June 7-8, Seinäjoki, Finland.

Tulppo M, Kiviniemi A, Hautala A, Mäkikallio T, Tiinanen S, Seppänen T & Huikuri H (2006) Association between baroreflex sensitivity and aerobic fitness after dynamic exercise. ACSM Annual Meeting, Med Sci Sports Exer. Suppl. 38: 18.

Vallius T & Röning J (2006) A telepresence robot system realized by embedded object Concept. Proc. Intelligent Robots and Computer Vision XXIV: Algorithms, Techniques, and Active Vision, October 3-4, Boston, Massachusetts, USA.

Vallius T & Röning J (2006) ATOMI II - Framework for easy building of object-oriented embedded systems. Proc. 9th Euromicro Conference on Digital System Design: Architectures, Methods and Tools, August 30 - September 1, Dubrovnik, Croatia, 464-472.

Wieser C & Röning J (2006) Über die Verwundbarkeit von IP-Telefonie-Systemen. Proc. 13th Workshop Sicherheit in vernetzten Systemen, March 1-2, Hamburg, Germany 2006.

Wieser C, Röning J & Takanen A (2006) Security analysis and experiments for VoIP RTP media streams. Proc. 8th International Symposium on Systems and Information Security (SSI2006). November 8-10, Sao Jose dos Campos, Sao Paolo, Brazil.