Friedrich M. Wahl

Technische Universität Braunschweig, Brunswyck, Lower Saxony, Germany

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Publications (178)44.24 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: For the further development of robot-assisted endoscope guidance in functional endoscopic sinus surgery (FESS), ground data about the workspaces and endoscope movements in conventional FESS are needed.
    International Journal of Medical Robotics and Computer Assisted Surgery 06/2014; · 1.49 Impact Factor
  • Yosef Dalbah, Nicolas Dingeldey, Friedrich M. Wahl
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    ABSTRACT: We present a method that estimates the ego motion of a vehicle based on camera data of high resolution (207x204 pixels) Time-of-Flight cameras using visual odometry techniques. Translation and rotation of camera motion in six degrees of freedom are calculated. Point correspondences in consecutive amplitude image pairs are built. By consideration of the depth image of the camera 3D point correspondences are derived from the two dimensional point correspondences. Camera motion between the two images is then computed by registration of the two resulting point clouds. The process is optimized by incorporation of outlier removal and a multi sensor setup. The presented optimizations raise the precision and robustness of the method and enable visual odometry by Time-of-Flight camera data as an alternative to common odometry systems in low speed scenarios.
    11/2013;
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    Carsten Last, Simon Winkelbach, Friedrich M Wahl
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    ABSTRACT: Statistical shape models provide an important means in many applications in computer vision and computer graphics. However, the major problems are that the majority of these shape models require dense point-correspondences along all training shapes and that a large number of training shapes is needed in order to capture the full amount of intra-class shape variation. In this contribution, we focus on a statistical shape model that can be constructed from a set of training shapes without defining any point-correspondences. Additionally, we show how a local statistical shape model can make better use of the available shape information, greatly reducing the number of required training shapes. Finally, we present a new framework to fit this local statistical shape model without correspondences to range scans that represent incomplete parts of the trained shape class. The fitted model is then used to reproduce a natural-looking approximation of the complete shape.
    VMV 2013: Vision, Modeling & Visualization; 09/2013
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    ABSTRACT: The problem of object localization is a well-known problem in industrial robotics. Manufactured parts arrive at factories as bulk goods in boxes. Single parts need to be picked out of the boxes and have to be fed to a machine. The task of automatically isolating single objects is known as the bin-picking problem. Even in modern factories the task of bin-picking is not automated widely yet. The automatization of this task is expensive since state-of-the-art solutions require object-class specific algorithms. In this paper we present an applicable solution for the bin-picking problem which is based on a standard 3d-sensor and is able to handle arbitrary objects. Furthermore, it is robust against noise and object occlusions. Additionally, we propose an approach for optimal grasp pose estimation with collision avoidance that effectively reduces system cycle times.
    Robotics and Automation (ICRA), 2013 IEEE International Conference on; 01/2013
  • Dennis Rosebrock, Friedrich M. Wahl
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    ABSTRACT: The generic camera model considered in this work can be regarded as a mapping between image pixels and viewing rays. These rays are independent of each other which prohibits a standard parametric approach for calibration and modeling of these cameras. Spline surfaces are used here to calibrate and model generic imaging devices. This allows the utilization of sparse planar calibration boards and facilitates general forward projection as well as subpixel back projection. In contrast to other works the complete image area is to be calibrated, not only a part of it. This is done by adding further views of calibration patterns after an initial calibration step, which expands the calibrated region of the camera image. Results with two different imaging devices prove the general applicability of the proposed method and the comparison to an established parametric calibration procedure shows its superiority.
    Asian Conference on Computer Vision (ACCV); 11/2012
  • Ulrike Thomas, Friedrich Wahl
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    ABSTRACT: In this paper, it is shown how robust execution of assembly skills can be planned by using sensor state space graphs. The here proposed method is evaluated by some assembly skills in which force feedback is applied. Assembly skills are implemented by manipulation primitive nets which constitute an interface between planning and execution of robotic systems. The sensor state space graph is introduced, which is an extension of the contact formation graph in a more general way, when various sensors might be used simultaneously for assembly execution. It is shown, how contact formation graphs can be generated by simulation of rigid body motions. The known contact formation graphs are enhanced by the definition of contact types between higher order surfaces. Additionally, a more general view is given by introducing sensor state space graphs. It is shown how contact formation graphs can be mapped to manipulation primitive nets, which allow the robust execution of assembly skills, despite the appearance of uncertainties. The approach is demonstrated successfully on some assembly tasks. Here the task of plugging a power socket on a top hat rail is illustrated due to its complex sequence. The shown assembly task is characterized by small fitting tolerances, where the application of force feedback is indispensable.
    International Conference on Intelligent Robotics and Applications; 10/2012
  • Jens Spehr, Simon Winkelbach, Friedrich M Wahl
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    ABSTRACT: Articulated structures like the human body have many degrees of freedom. This makes an evaluation of the configuration's likelihood very challenging. In this work we propose new linked hierarchical graphical models which are able to efficiently evaluate likelihoods of articulated structures by sharing visual primitives. Instead of evaluating all configurations of the human body separately we take advantage of the fact that different configurations of the human body share body parts, and body parts, in turn, share visual primitives. A hierarchical Markov random field is used to integrate the sharing of visual primitives in a probabilistic framework. We propose a scalable hierarchical representation of the human body and show that this representation is especially well suited for human gait analysis from a frontal camera perspective. Furthermore, the results of the evaluation on a gait dataset show that sharing primitives substantially accelerates the evaluation and that our hierarchical probabilistic framework is a robust method for scalable detection of the human body.
    Computer methods and programs in biomedicine 02/2012; 106(2):104-13. · 1.56 Impact Factor
  • D Rosebrock, F M Wahl
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    ABSTRACT: Cameras are a commonly used sensor in advanced driver assistance systems (ADAS). They serve to get vast amounts of information about a vehicle's environment. To accurately localize the measured data in relation to the own car, exact camera calibration is a prerequisite. This includes extrinsic as well as intrinsic parameters. While many works in the area of ADAS focus on extrinsic calibration, this work covers the intrinsic calibration. We use a generic camera model which regards the viewing ray of every pixel separately and can therefore be used to describe arbitrary imaging devices even with massive lens distortions. As the calibration procedure works for any camera, only one method has to be implemented, which simplifies the sensor calibration process. Former works have shown the applicability of generic camera models but do not cover important practical aspects which are subpixel ray determination and forward projection of arbitrary 3d points to the image plane. Furthermore, the calibration processes described so far are cumbersome and prone to inaccuracies. We propose to use spline surfaces to simplify the calibration procedure and implement general back and forward projection. The applicability of our approach is proved by showing calibration results for various real cameras.
    Intelligent Vehicles Symposium (IV), 2012 IEEE; 01/2012
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    ABSTRACT: Rotary encoders and resolvers are by far the most common sensors to measure joint angles in articulated robots. Since various control approaches require angular rates as well, resolvers and encoders are also employed to derive angular rate signals. Due to the involved differentiation operation, however, quantization noise may be augmented significantly. Advanced filtering approaches can only partially overcome this drawback. Therefore, direct measurement of angular rates is desirable. Due to advancements in manufacturing technology and pushed by applications in entertainment devices, MEMS gyroscopes have become an attractive alternative for angular rate measurement. Unfortunately, they are affected by bias and other non-negligible disturbances, which may be a serious problem if consistent joint angle and angular rate measurements are required. The proposed approach fuses encoder and angular rate signals to mitigate their major drawbacks - bias and quantization errors - by exploiting their individual strong points. Bias in the angular rate signal is eliminated by analyzing the deviation between the integrated angular rate signal and the encoder signal. Quantization errors in the encoder signal are reduced by a so-called complementary filter which blends the integrated angular rate output with the encoder signal. Apart from a description of the approach and a theoretical analysis of its characteristics, experimental results demonstrating the effectiveness of the approach in closed-loop control of articulated robots are presented.
    Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on; 01/2012
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    ABSTRACT: In this paper we propose a generic 6d object localization approach based on surface normal images and CAD model data. Normal images or “normal maps” can be obtained using only one single camera shot of a simple camera-projector system. The advantages of this sensor setup are very short acquisition times and the exclusive use of consumer hardware, namely a projector and a grey value camera, making it easy and cheap to build up. All computations are analytically tractable and can be computed in the Fourier domain allowing a very effective and fast computation.
    Pattern Recognition (ICPR), 2012 21st International Conference on; 01/2012
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    ABSTRACT: Statistical shape models are one of the most powerful methods in medical image segmentation problems. However, if the task is to segment complex structures, they are often too constrained to capture the full amount of anatomical variation. This is due to the fact that the number of training samples is limited in general, because generating hand-segmented reference data is a tedious and time-consuming task. To circumvent this problem, we present a Locally Deformable Statistical Shape Model that is able to segment complex structures with only a few training samples at hand. This is achieved by allowing a unique solution in each contour point. Unlike previous approaches, trying to tackle this problem by partitioning the statistical model, we do not need predefined segments. Smoothness constraints ensure that the local solution is restricted to the space of feasible shapes. Very promising results are obtained when we compare our new approach to a global fitting approach.
    Machine Learning in Medical Imaging - Second International Workshop, MLMI 2011, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 18, 2011. Proceedings; 09/2011
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    ABSTRACT: Electric motors clearly constitute the most common drive principle in robotics and mechatronics. Smart materials, however, offer considerably higher power-to-mass ratios than electric motors. If mechanical energy instead of electrical energy can be distributed through a system, highly dynamic and efficient torque transmission elements based on smart materials, e.g. piezoceramics, can be used to transmit torque from an input to an output element. Just like electric motors, they can thus provide position, velocity, and force-torque control of the output element. This paper introduces machine components, called adaptronic couplers, which can transmit variable torques highly dynamically from an input element to an output element employing static and/or dynamic friction. In the long run, systems (e.g. robots) based on these machine components are envisaged to compete with systems based on classic drive principles - especially electric motors - w.r.t. dynamics and power-to-mass-ratio. Apart from the concept itself, this paper addresses different control approaches and discusses their influence on energy consumption and wear. Moreover, various experimental results proving the basic concept are presented.
    Robotics and Automation (ICRA), 2011 IEEE International Conference on; 06/2011
  • D. Kubus, F.M. Wahl
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    ABSTRACT: Rotary encoders are the most common sensors to measure angles in mechatronic and robotic components, e.g., servo motors or robot joints. Especially, if encoders are not mounted on the motor shaft but on the output side of geared motors, high encoder resolutions are required. Resolution requirements may increase further if velocities are to be derived from the encoder signals, e.g., for motion control purposes. To avoid noise amplification problems when estimating angular rates from encoder signals, angular velocity sensors may be employed instead. However, a significant drawback of angular rate sensors - particularly of cheap MEMS gyroscopes - is their drift.
    Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on; 01/2011
  • Daniel Kubus, Friedrich M. Wahl
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    ABSTRACT: Rotary encoders are the most common sensors to measure angles in mechatronic and robotic components, e.g., servo motors or robot joints. Especially, if encoders are not mounted on the motor shaft but on the output side of geared motors, high encoder resolutions are required. Resolution requirements may increase further if velocities are to be derived from the encoder signals, e.g., for motion control purposes. To avoid noise amplification problems when estimating angular rates from encoder signals, angular velocity sensors may be employed instead. However, a significant drawback of angular rate sensors - particularly of cheap MEMS gyroscopes - is their drift. Both the requirements on encoder resolution and the drift of the angular rate signal can be reduced significantly by the sensor fusion approach presented in this paper. The approach utilizes the encoder to eliminate the drift of the angular rate signal and integrates the resulting signal to obtain estimates of the angle. Apart from a detailed description of the approach and a theoretical analysis of its disturbance characteristics, various simulation and experimental results are presented demonstrat- ing its effectiveness. the angle and the angular velocity. If encoders are used to provide angular velocity and angular acceleration signals, filters or estimators are generally required to reduce the noise in the velocity and acceleration signals. Regarding signals with low velocities, no encoder counts may occur during several sampling intervals. In this case, velocity estimation becomes especially delicate and sophisticated methods are required to provide meaningful estimates. Needless to say that increasing the encoder resolution is a viable solution in most cases but it comes at a non negligible cost. Therefore, direct angular rate measurement has become an attractive alternative with the advent of MEMS-based angular rate sensors. In contrast to expensive fiber optic gyroscopes (2), these sensors are affordable for most robotics applications. However, direct angular rate sensing with MEMS gyroscopes has a significant drawback: MEMS gyroscopes are not only affected by uncorrelated random noise but also by slowly time-varying disturbances denoted as drift. The characteris- tics of this random process have been analyzed in (3). The combination of low-resolution encoders with inexpen- sive (MEMS) angular rate sensors to compensate the major disadvantage of either sensor may be a viable alternative to high-resolution encoders. The angular rate sensor can be utilized to virtually increase encoder resolution while the encoder can be employed to eliminate the drift of the angular rate sensor. This approach may be implemented using model-based or model-free approaches. Considering industrial applicability, model-free approaches that can be applied with minimum setup and tuning efforts are generally more desirable than model-based approaches that require in- depth system knowledge. Therefore this paper introduces a model-free drift and offset compensator (DOC) employing FIR/IIR filtering tech- niques, which also lends itself to implementation in hardware (e.g. DSPs and FPGAs). Section II reviews related work. In Section III the concept of the DOC is presented and in Section IV its characteristics are analyzed. Section V shows the effectiveness of the approach in terms of encoder resolution enhancement and drift reduction with various simulations and experimental results. Section VI addresses further work and concludes the paper.
    2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2011, San Francisco, CA, USA, September 25-30, 2011; 01/2011
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    ABSTRACT: One of the main tasks of intelligent vehicles is the extraction of information from the vehicle's surroundings and the understanding of the extracted information. The understanding of the environment allows the vehicle to drive autonomously or to support the driver in difficult or dangerous situations. In this paper we propose a vision-based hierarchical interpretation approach. First, we consider one single physical camera as a set of virtual sensors, where each virtual sensor gathers a type of 3d information. Then, the 3d information of this set is converted to high-level information that allows further reasoning. The interpretation is based on a hierarchical scene representation, where objects are recognized using nonparametric belief propagation. To demonstrate this approach we adopted the scene understanding to a parking spot finding application and show that it is real-time applicable and reliable even for multiple camera (on-board) systems.
    Intelligent Vehicles Symposium (IV), 2011 IEEE; 01/2011
  • Ambient Assisted Living-AAL. 01/2011;
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    ABSTRACT: Online trajectory scaling approaches represent a possible way for handling robotic systems characterized by kinematic or dynamic saturations. Scaling methods are based on the path/velocity decomposition principle: a dynamic filter is used to modify the longitudinal velocity along a planned path in order to satisfy given system constraints. The strategy here proposed enhances the results of a previous work by enlarging the number of considered constraints. In particular, still accounting for the existence of bounds on joint velocities and torques, in this paper, the presence of constraints on joint accelerations is also considered. Furthermore, the nonlinear filter, which represents the core of the scaling system, has been revised in order to devise a new and more compact implementation. Finally, some practical issues that could occur in actual implementations are discussed and solutions are proposed to overcome possible problems.
    Robotics and Automation (ICRA), 2011 IEEE International Conference on; 01/2011
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    Dennis Rosebrock, Markus Rilk, Jens Spehr, Friedrich M. Wahl
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    ABSTRACT: In this work we propose a way to detect vehicles in monocular camera images and determine their position and orientation on the ground plane relative to the camera. The camera does not need to be stationary which allows the method to be used in mobile applications. Its results can therefore serve as an input to advanced driver assistance systems (ADAS). The single feature used is the shadow beneath the vehicles. We implemented a real-time applicable method to detect these shadows under strongly varying conditions and determine the corresponding vehicle pose. Finally we evaluate our results by comparing them to ground truth data.
    Advances in Visual Computing - 7th International Symposium, ISVC 2011, Las Vegas, NV, USA, September 26-28, 2011. Proceedings, Part I; 01/2011
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    ABSTRACT: Worldwide, ageing societies are bringing challenges for independent living and healthcare. Health-enabling technologies for pervasive healthcare and sensor-enhanced health information systems offer new opportunities for care. In order to identify, implement and assess such new information and communication technologies (ICT) the 'Lower Saxony Research Network Design of Environments for Ageing' (GAL) has been launched in 2008 as interdisciplinary research project. In this publication, we inform about the goals and structure of GAL, including first outcomes, as well as to discuss the potentials and possible barriers of such highly interdisciplinary research projects in the field of health-enabling technologies for pervasive healthcare. Although GAL's high interdisciplinarity at the beginning slowed down the speed of research progress, we can now work on problems, which can hardly be solved by one or few disciplines alone. Interdisciplinary research projects on ICT in ageing societies are needed and recommended.
    Informatics for Health and Social Care 12/2010; 35(3-4):92-103. · 1.27 Impact Factor
  • Torsten Kröger, Bernd Finkemeyer, Friedrich M. Wahl
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    ABSTRACT: This paper introduces a generic framework for sensor-based robot motion control. The key contribution is the introduction of an adaptive selection matrix for sensor-based hybrid switched-system control. The overall control system consists of multiple sensors and open- and closed-loop controllers, in-between which the adaptive selection matrix can switch discretely in order to supply command variables for low-level controllers of robotic manipulators. How control signals are chosen, is specified by Manipulation Primitives, which constitute the interface to higher-level applications. This programming paradigm is formally specified in order to establish the possibility of executing sensor-guided and sensor-guarded motion commands simultaneously and in a very open way, such that any kind and any number of sensors can be addressed. A further key feature of this generic approach is, that the control structure can be directly mapped to a corresponding software architecture. The resulting control system is freely scalable depending on the performance requirements of the desired system.
    11/2010: pages 293-313;

Publication Stats

857 Citations
44.24 Total Impact Points

Institutions

  • 1970–2014
    • Technische Universität Braunschweig
      • Institut für Robotik und Prozessinformatik
      Brunswyck, Lower Saxony, Germany
  • 2008
    • Klinikum Braunschweig
      Brunswyck, Lower Saxony, Germany
    • Deutsche Gesellschaft für Hals-Nasen-Ohren-Heilkunde, Kopf- und Hals-Chirurgie e.V.
      Bonn, North Rhine-Westphalia, Germany
  • 2007–2008
    • University of Bonn
      Bonn, North Rhine-Westphalia, Germany
  • 2006
    • Hannover Medical School
      • Trauma Department
      Hannover, Lower Saxony, Germany
    • Szczecin University of Technology
      • Institute of Control Engineering
      Stettin, West Pomeranian Voivodeship, Poland