Lothar Wenzel

The applicability of the visual programming language LabVIEW to large real-world applications

Graphical programming languages allow a natural, intuitive man-machine interaction. As a result, graphical programming has gained much popularity over the past several years, primarily because many scientists and engineers have experienced improvements in programming efficiency due to the natural understandability of graphical programming tools. In general, however, there is a perception that the graphical paradigm does not lend itself well to large-scale applications. The paper examines the suitability of graphical programming languages to real-world applications. The specific graphical programming language evaluated in this paper is LabVIEW, though some of the concepts discussed apply to other visual programming languages as well. A relatively large case study involving simulation as well as real-time acquisition programmed in LabVIEW is investigated. Advantages and limitations of LabVIEW for such applications are discussed.

Low-Discrepancy Curves and Efficient Coverage of Space

We introduce the notion of low-discrepancy curves and use it to solve the problem of optimally covering space. In doing so, we extend the notion of low-discrepancy sequences in such a way that sufficiently smooth curves with low discrepancy properties can be defined and generated. Based on a class of curves that cover the unit square in an efficient way, we define induced low discrepancy curves in Riemannian spaces. This allows us to efficiently cover an arbitrarily chosen abstract surface that admits a diffeomorphism to the unit square. We demonstrate the application of these ideas by presenting concrete examples of low-discrepancy curves on some surfaces that are of interest in robotics.

Control strategies and image processing

This paper presents three real-world applications that highlight the benefits of using image processing and machine vision techniques for control applications. These examples also illustrate how classical and modern control techniques can be used to solve image processing and machine vision problems. For many applications the use an appropriate combination of image processing and control theory offers advantages over alternative approaches.

Induced well-distributed sets in Riemannian spaces

The concept of Riemannian geometries is used to construct induced homogeneous point sets on manifolds that are based on well-distributed point sets in unit cubes of an appropriately chosen Euclidean space. These well-distributed point sets in unit cubes are based on standard low-discrepancy sequences. The approach is algorithmic, that is, the methods developed in this article have been implemented and tested. Applications in image processing, graph theory and measurement-based exploration are presented.

Pattern matching based on a generalized Fourier transform

In a two-dimensional pattern matching problem, a known template image has be located in another image, irrespective of the templates position, orientation and size in the image. One way to accomplish invariance to the changes in the template is by forming a set of feature vectors that encompass all the variations in the template. Matching is then performed by finding the best similarity between the feature vector extracted from the image to the feature vectors in the template set. In this paper we introduce a new concept of a generalized Fourier transform. The generalized Fourier transform offers a relatively robust and extremely fast solution to the described matching problem. The application of the generalized Fourier transform to scale invariant pattern matching is shown here.

Field programmable gate array-assigned complex-valued computation and its limits

We discuss how leveraging Field Programmable Gate Array (FPGA) technology as part of a high performance computing platform reduces latency to meet the demanding real time constraints of a quantum optics simulation. Implementations of complex-valued operations using fixed point numeric on a Virtex-5 FPGA compare favorably to more conventional solutions on a central processing unit. Our investigation explores the performance of multiple fixed point options along with a traditional 64 bits floating point version. With this information, the lowest execution times can be estimated. Relative error is examined to ensure simulation accuracy is maintained.

A versatile LabVIEW and field-programmable gate array-based scanning probe microscope for in operando electronic device characterization

Understanding the complex properties of electronic and spintronic devices at the micro- and nano-scale is a topic of intense current interest as it becomes increasingly important for scientific progress and technological applications. In operando characterization of such devices by scanning probe techniques is particularly well-suited for the microscopic study of these properties. We have developed a scanning probe microscope (SPM) which is capable of both standard force imaging (atomic, magnetic, electrostatic) and simultaneous electrical transport measurements. We utilize flexible and inexpensive FPGA (field-programmable gate array) hardware and a custom software framework developed in National Instruments LabVIEW environment to perform the various aspects of microscope operation and device measurement. The FPGA-based approach enables sensitive, real-time cantilever frequency-shift detection. Using this system, we demonstrate electrostatic force microscopy of an electrically biased graphene field-effect transistor device. The combination of SPM and electrical transport also enables imaging of the transport response to a localized perturbation provided by the scanned cantilever tip. Facilitated by the broad presence of LabVIEW in the experimental sciences and the openness of our software solution, our system permits a wide variety of combined scanning and transport measurements by providing standardized interfaces and flexible access to all aspects of a measurement (input and output signals, and processed data). Our system also enables precise control of timing (synchronization of scanning and transport operations) and implementation of sophisticated feedback protocols, and thus should be broadly interesting and useful to practitioners in the field.

A Rapid Prototyping Tool for Embedded, Real-Time Hierarchical Control Systems

Laboratory Virtual Instrumentation and Engineering Workbench (LabVIEW) is a graphical programming tool based on the dataflow language G. Recently, runtime support for a hard real-time environment has become available for LabVIEW, which makes it an option for embedded systems prototyping. Due to its characteristics, the environment presents itself as an ideal tool for both the design and implementation of embedded software. In this paper, we study the design and implementation of embedded software by using G as the specification language and the LabVIEW RT real-time platform. One of the main advantages of this approach is that the environment leads itself to a very smooth transition from design to implementation, allowing for powerful cosimulation strategies (e.g., hardware in the loop, runtime modeling). We characterize the semantics and formal model of computation of G. We compare it to other models of computation and develop design rules and algorithms to propose sound embedded design in the language. We investigate the specification and mapping of hierarchical control systems in LabVIEW and G. Finally, we describe the development of a state-of-the-art embedded motion control system using LabVIEW as the specification, simulation and implementation tool, using the proposed design principles. The solution is state-of-the-art in terms of flexibility and control performance.

Peak locations in all-pass signals - the Makhoul Conjecture Challenge

The Makhoul Conjecture Challenge (Makhoul, 2000) has been published. To answer was the question whether or not the location of the peak of a digital stable all-pass filter lies in [0,2p-1], where p is the order of the all-pass filter. We construct numerous counter-examples, prove a new theorem stating that there is at least an upper bound on the order of p/sup 3/2/ for the location of the peak, and discuss the algebraic structure of all-pass filters and their impulse responses. The paper is heavily based on an experimental approach.

A differential geometric approach to discrete-coefficient filter design

This paper is concerned with the problem of computing a discrete-coefficient approximation to a digital filter. In contrast to earlier works that have approached this problem using standard combinatorial optimization tools, we take a geometric approach. We define a Riemannian manifold, arising from the difference in frequency response between the two systems of interest, on which we design efficient algorithms for sampling and approximation. This additional structure enables us to tame the computational complexity of the native combinatorial optimization problem. We illustrate the benefits of this approach with design examples involving IIR and FIR filters.