Center for Life Science Automation

Rostock, Germany

Center for Life Science Automation

Rostock, Germany
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Kumar M.,Center for Life Science Automation | Stoll N.,University of Rostock | Stoll R.,University of Rostock
IEEE Transactions on Fuzzy Systems | Year: 2010

This study, under the variational Bayes (VB) framework, infers the parameters of a Takagi-Sugeno fuzzy filter having deterministic antecedents and stochastic consequents. The aim of this study is to take advantages of the VB framework to design fuzzy-filtering algorithms, which include an automated regularization, incorporation of statistical noise models, and model-comparison capability. The VB method can be easily applied to the linear-in-parameters models. This paper applies the VB method to the nonlinear fuzzy filters without using Taylor expansion for a linear approximation of some nonlinear function. It is assumed that the nonlinear parameters (i.e., antecedents) of the fuzzy filter are deterministic, while linear parameters are stochastic. The VB algorithm, by maximizing a strict lower bound on the data evidence, makes the approximate posterior of linear parameters as close to the true posterior as possible. The nonlinear deterministic parameters are tuned in a way to further increase the lower bound on data evidence. The VB paradigm can be used to design an algorithm that automatically selects the most-suitable fuzzy filter out of the considered finite set of fuzzy filters. This is done by fitting the observed data as a stochastic combination of the different Takagi-Sugeno fuzzy filters such that the individual filters compete with one another to model the data. © 2006 IEEE.


Kumar M.,Center for Life Science Automation | Weippert M.,University of Rostock | Arndt D.,Center for Life Science Automation | Kreuzfeld S.,University of Rostock | And 3 more authors.
IEEE Transactions on Fuzzy Systems | Year: 2010

This study suggests the use of fuzzy-filtering algorithms to deal with the uncertainties associated to the analysis of physiological signals. The signal characteristics, for a given situation or physiological state, vary for an individual over time and also vary among the individuals with the same state. These random variations are due to the several factors related to the physiological behavior of individuals, which cannot be taken into account in the interpretation of signal characteristics. Our approach is to reduce the effect of random variations on the analysis of signal characteristics via filtering out randomness or uncertainty from the signal using a nonlinear fuzzy filter. A fuzzy-filtering algorithm, which is based on a modification of filtering algorithm of Kumar et al. [M. Kumar, N. Stoll, and R.Stoll, IEEE Trans. Fuzzy Syst., vol. 17, no. 1, pp. 150166, Feb. 2009], is proposed for an improved performance. The method is illustrated by studying the effect of head-up tilting on the heart-rate signal of 40 healthy subjects. © 2006 IEEE.


Liu H.,University of Rostock | Stoll N.,Center for Life Science Automation | Junginger S.,University of Rostock | Thurow K.,Center for Life Science Automation
Conference Record - IEEE Instrumentation and Measurement Technology Conference | Year: 2013

In life science laboratories, mobile robots are adopted to do transportation tasks among distributed automated islands or rooms. To use those mobile robots effectively, a number of technology issues have to be considered, such as path planning of transportation and charging, localization, communication, etc. In this paper an application of charging management for mobile robot transportation is presented. In this application: (a) to localize the mobile robots accurately and fast in life science environments, a method using ceiling landmarks is adopted; (b) to measure the power status from all running robots, a power module for the server and client sides is designed; (c) to let mobile robots go charging automatically, an automated charging station is utilized; and (d) to select the best installing positions for the charging stations, an intelligent method based on the Artificial Immune Algorithm (AIA) is proposed, which considers both of the distances among the expected working positions and their distribution of transportation tasks. A real case shows that the presented application is effective for mobile robot charging management in life science environments. © 2013 IEEE.


Kumar M.,Center for Life Science Automation | Stoll N.,University of Rostock | Stoll R.,University of Rostock
IEEE Transactions on Fuzzy Systems | Year: 2011

The application of nonlinear optimization to the estimation of fuzzy model parameters is well known. To do the reverse of this, the concept of stationary fuzzy Fokker-Planck learning (SFFPL) is introduced, i.e., SFFPL applies the fuzzy modeling technique in nonlinear optimization problems. SFFPL is based on the fuzzy approximation of the stationary cumulative distribution function of a stochastic search process associated with the nonlinear optimization problem. A carefully designed algorithm is suggested for SFFPL to locate the optimum point. This paper also considers the variational Bayes (VB)-based inference of a stochastic fuzzy filter whose consequents, as well as antecedents, are random variables. The problem of VB inference of stochastic antecedents, because of the nonlinearity of the likelihood function, is analytically intractable. The SFFPL algorithm for high-dimensional nonlinear optimization that does not require the derivative of the objective function can be used to numerically solve the stochastic fuzzy filtering problem. © 2011 IEEE.


Liu H.,University of Rostock | Stoll N.,Center for Life Science Automation | Junginger S.,University of Rostock | Thurow K.,Center for Life Science Automation
International Journal of Advanced Robotic Systems | Year: 2013

The paper presents a control system for mobile robots in distributed life science laboratories. The system covers all technical aspects of laboratory mobile robotics. In this system: (a) to get an accurate and low-cost robot localization, a method using a StarGazer module with a number of ceiling landmarks is utilized; (b) to have an expansible communication network, a standard IEEE 802.11g wireless network is adopted and a XML-based command protocol is designed for the communication between the remote side and the robot board side; (c) to realize a function of dynamic obstacle measurement and collision avoidance, an artificial potential field method based on a Microsoft Kinect sensor is used; and (d) to determine the shortest paths for transportation tasks, a hybrid planning strategy based on a Floyd algorithm and a Genetic Algorithm (GA) is proposed. Additionally, to make the traditional GA method suitable for the laboratory robot's routing, a series of optimized works are also provided in detail. Two experiments show that the proposed system and its control strategy are effective for a complex life science laboratory. © 2013 Liu et al.


Fleischer H.,University of Rostock | Thurow K.,Center for Life Science Automation
Conference Record - IEEE Instrumentation and Measurement Technology Conference | Year: 2013

Qualitative and quantitative determination of the composition of chiral compounds is an important task in drug development, chemical and biological industries and scientific research. Usually, enantiomers are analyzed with conventional analytical techniques such as chromatography or spectroscopy. Due to their relative long run times and high material consumption these techniques are only suitable to a limited extent for using in high-throughput screenings. In contrast, mass spectrometry without previous chromatographic separation provides very short analysis times, but it requires a suitable derivatization of the chiral substrates. In this interdisciplinary study the technique of parallel kinetic resolution with mass tagged pseudo enantiomeric auxiliaries was applied for measuring the enantiomeric excess of amino acids, carboxylic acids, alcohols, amino alcohols and natural compounds. Beside the method development for sample preparation and mass spectrometric measurements a high-throughput suitable processing network was constructed. This includes automated sample preparation, sample transport, analysis and data processing. The special tasks in data evaluation such as calibration and enantiomeric excess calculation are realized by an additional software module connected to existing mass spectrometer data acquisition software. The automation system with its software solution shows great potential for its use in high-throughput screenings in various fields of industry and research. © 2013 IEEE.


Liu H.,University of Rostock | Stoll N.,Center for Life Science Automation | Junginger S.,University of Rostock | Thurow K.,Center for Life Science Automation
Conference Record - IEEE Instrumentation and Measurement Technology Conference | Year: 2013

In modern life science laboratories, more and more complicated transportation tasks are needed among distributed automatic workbenches or laboratories. There are some special requirements for the kinds of transportation: high-accuracy; robust performance; economic cost and fast integration. In this paper a fast method is proposed to manage mobile robots for effective transportation in life science environments. The architecture of this method includes three components: the PMS for transportation request the Robot Remote Center (RRC) for transportation managing, and the Robot Board Center (RBC) for transportation executing. To include any kind and size of life science laboratories, this method adopts a standard TCP/IP network for data transmission, uses a series of extensible ceiling landmarks for robot indoor localization, utilizes a flexible map-based intelligent hybrid calculation for robot path planning, and enables collision avoidance by using a group of ultrasonic sensors and artificial potential field algorithm. An experiment in a real life science laboratory (celisca, Germany) shows that the proposed method meets all requirements of life science automation and has satisfactory performance. © 2013 IEEE.


Liu H.,University of Rostock | Stoll N.,Center for Life Science Automation | Junginger S.,University of Rostock | Thurow K.,Center for Life Science Automation
2012 IEEE I2MTC - International Instrumentation and Measurement Technology Conference, Proceedings | Year: 2012

A common wireless remote control system based on standard APIs of robots is presented to enable a stable multi-robot transportation in distributed life science laboratories. This system consists of multi-robot board control centers (PCs), a remote server control center (PC), a wireless communication network and an infrared radio navigation module with ceiling passive landmarks. To let this system expand conveniently, the two-level Client/Server architecture is adopted, and a standard IEEE 802.11g wireless communication with TCP/IP protocol is utilized. An inside architecture is employed for signal sampling and controlling between robot board PCs and the robot's hardware modules. An additional outside architecture is designed for higher remote commands between robot board PCs and remote server control PC. Two experiments in this study show that the simple ceiling landmark method is suitable for the robot indoor navigation with low costs, and this kind of remote control system can work effectively in large and distributed laboratory. © 2012 IEEE.


Li Y.,Center for Life Science Automation | Junginger S.,University of Rostock | Stoll N.,University of Rostock | Thurow K.,Center for Life Science Automation
2012 IEEE I2MTC - International Instrumentation and Measurement Technology Conference, Proceedings | Year: 2012

Due to the complex and distributed nature of high-end projects in Life Science Automation, it is still not possible to simulate workflows on laboratory workbenches frequently in a real time equivalent manner. It is crucial to ensure the availability of desired assays and automated workflows in advance. This paper presents the concept of a 4D simulation system, which synthesizes technologies as Process Control Software (PCS), Data Management System (DMS), programming technology, advanced CAD technology and some 3D animation tool to realize a dynamic simulation for Laboratory Workflow Management. The system would be flexible and controllable for automation assays, improve laboratory workflows, efficiency and accuracy, which would reduce the assays cost and the risks of rushing to unreasonable plans, and also improve the laboratory management level. © 2012 IEEE.


Kumar M.,Center for Life Science Automation | Neubert S.,University of Rostock | Behrendt S.,University of Rostock | Rieger A.,University of Rostock | And 4 more authors.
IEEE Transactions on Fuzzy Systems | Year: 2012

Quantifying stress levels of an individual based on a mathematical analysis of real-time physiological data measurements is challenging. This study suggests a stochastic fuzzy analysis method to evaluate the short time series of R-R intervals (time intervals between consecutive heart beats) for a quantification of the stress level. The 5-min-long series of R-R intervals recorded under a given stress level are modeled by a stochastic fuzzy system. The stochastic model of heartbeat intervals is individual specific and corresponds to a particular stress level. Once the different heartbeat interval models are available for an individual, an analysis of the given R-R interval series generated under an unknown stress level is performed by a stochastic interpolation of the models. The stress estimation method has been implemented in a mobile telemedical application employing an e-health system for an efficient and cost-effective monitoring of patients while at home or at work. The experiments involve 50 individuals whose stress scores were assessed at different times of the day. The subjective rating scores showed a high correlation with the values predicted by the proposed analysis method. © 1993-2012 IEEE.

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