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Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK
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PublicationPowerGrasp: Development Aspects for Arm Support Systems( 2022)
;Goppold, J.-P. ;Kuschan, J. ;Schmidt, H.Krüger, J.Exoskeletons can support workers on physically demanding tasks, but in industry they lack of acceptance. This contribution gives an insight into design aspects for upper body exoskeletons, especially how active exoskeletons for industrial applications differ from military and medical use-cases. To overcome typical rigid exoskeleton problems, we suggest the use of modular soft-exosuit support systems and therefore checked different types of soft actuation principles for their eligibility for the use on upper body joints. Most promising approach is using two-layered actuators sting of robust fabric with embedded rubber tubes as pressure chambers. By inflating the tubes, it is possible to vary the stiffness of the chambers, which can be effectively used to generate assisting forces and moments at human joints (shoulder, elbow, wrist, finger). -
PublicationRobust system identification for hysteresis-controlled devices using SINDy( 2020)
;Schreck, G. ;Thiele, G. ;Fey, A.Krüger, J.For advanced control of technical systems reliable system identification methods are essential. The data-driven framework Sparse Identification of Nonlinear Dynamics (SINDy) by Kutz and Brunton is extended in order to tackle hysteresis-controlled systems. In order to gain robustness, a so called proximity hysteron is introduced. This paper presents this extension and documents experiments with simulations of an academic example and an industrial chiller system. A proof of concept is followed by experiments which show that strong nonlinearities as well as inadequate sampling rates can critically impair the algorithm. -
PublicationEnergy optimal set-points for coupled systems using their topology( 2020)
;Thiele, G. ;Claus, R. ;Johanni, T.Krüger, J.Energy efficiency is an emerging topic for companies in the industrial sector. The optimization of existing machines by advanced control is increasingly approached. For interconnected systems, we present a general procedure to include topology knowledge in an automated set-point optimization routine. This paper demonstrates an exemplary algorithm, applied to a parallel connection of two chillers for test purposes. -
PublicationPoint Pair Feature Matching: Evaluating Methods to Detect Simple Shapes( 2019)
;Ziegler, M. ;Rudorfer, M. ;Kroischke, X. ;Krone, S.Krüger, J.A recent benchmark for 3D object detection and 6D pose estimation from RGB-D images shows the dominance of methods based on Point Pair Feature Matching (PPFM). Since its invention in 2010 several modifications have been proposed to cope with its weaknesses, which are computational complexity, sensitivity to noise, and difficulties in the detection of geometrically simple objects with planar surfaces and rotational symmetries. In this work we focus on the latter. We present a novel approach to automatically detect rotational symmetries by matching the object model to itself. Furthermore, we adapt methods for pose verification and use more discriminative features which incorporate global information into the Point Pair Feature. We also examine the effects of other, already existing extensions by testing them on our specialized dataset for geometrically primitive objects. Results show that particularly our handling of symmetries and the augmented features are able to boost recognition rates. -
PublicationTowards Learning 3d Object Detection and 6d Pose Estimation from Synthetic Data( 2019)
;Rudorfer, M. ;Neumann, L.Krüger, J.Deep Learning-based approaches for 3d object detection and 6d pose estimation typically require large amounts of labeled training data. Labeling image data is expensive and particularly the 6d pose information is difficult to obtain, as it requires a complex setup during image acquisition. Training with synthetic data is therefore very attractive. Large amounts of synthetic, labeled data can be generated, but it is not yet fully understood how certain aspects of data generation affect the detection and pose estimation performance. Our work therefore focuses on creating synthetic training data and investigating the effects on detection performance. We present two methods for data generation: rendering object views and pasting them on random background images, and simulating realistic scenes. The former is computationally simpler and achieved better results, but the detection performance is still very sensitive to small changes, e.g. the type of background images. -
PublicationMaximization of operational workspace of a mobile manipulator system( 2018)
;Kalidindi, V.V. ;Vick, A.Krüger, J.This paper puts forward a proposition of designing manipulator setup on a mobile platform so as to enhance the Operational Workspace range of a given Mobile-Manipulator system, by introducing the concept of Installation angle. This concept is theoretically tested on a Mobile-manipulator system built from the chosen robots, for the given operational parameters. As a part of this testing, Manipulator workspace has been expressed and approximated in terms of its enclosure volume for quantitative comparability. -
PublicationGesture based robot programming using process knowledge( 2018)
;Heimann, O. ;Hügle, J.Krüger, J.This paper is a work in progress report on a novel system for intuitive gesture based robot programming. The major contribution is the addition of an expert system into the robot programming process. The expert system uses static knowledge, such as seam types, and dynamic knowledge to reason about the intended process. The dynamic knowledge holds information about the environment and is derived from sensor data. The paper outlines the required components and the current state of development of a prototype system. An example of the inference process is given for a robot laser welding application. -
PublicationHolo Pick'n'Place( 2018)
;Rudorfer, M. ;Guhl, J. ;Hoffmann, P.Krüger, J.In this paper we contribute to the research on facilitating industrial robot programming by presenting a concept for intuitive drag and drop like programming of pick and place tasks with Augmented Reality (AR). We propose a service-oriented architecture to achieve easy exchangeability of components and scalability with respect to AR devices and robot workplaces. Our implementation uses a HoloLens and a UR5 robot, which are integrated into a framework of RESTful web services. The user can drag recognized objects and drop them at a desired position to initiate a pick and place task. Although the positioning accuracy is unsatisfactory yet, our implemented prototype achieves most of the desired advantages to proof the concept. -
PublicationBeMobil: Developing a user-friendly and motivating telerehabilitation system for motor relearning after stroke( 2017)
;Minge, M. ;Ivanova, E. ;Lorenz, K. ;Joost, G. ;Thüring, M.Krüger, J.Motor relearning after stroke is a lengthy process which should be continued after patients get discharged from the clinic. This project aims at developing a system for telerehabilitation which enables stroke patients to exercise at home autonomously or under supervision of a therapist. The system includes haptic therapy devices which are more promising and beneficial for stroke rehabilitation than non-haptic approaches. In this paper, we present the results of two initial studies investigating specific design solutions for the patient's user interface. In the first study, we developed four interactive prototypes illustrating different navigation concepts. A usability test was conducted to identify the best suitable concept. In the second study we followed a participatory design approach to create a set of design solutions for a motivating instant visual feedback for exercising with the haptic devices. The current project status and next steps are described. -
PublicationLet's do this together: Bi-Manu-Interact, a novel device for studying human haptic interactive behavior( 2017)
;Ivanova, E. ;Krause, A. ;Schälicke, M. ;Schellhardt, F. ;Jankowski, N. ;Achner, J. ;Schmidt, H. ;Joebges, M.Krüger, J.Our area of interest is robotic-based rehabilitation after stroke, and our goal is to help patients achieve optimal motor learning during high-intensity repetitive movement training through the assistance of robots. It is important, that the robotic assistance is adapted to the patients' abilities, thereby ensuring that the device is only supporting the patient as necessary ('assist-as-needed'). We hypothesize that natural and learning-effective human-machine interaction can be achieved by programming the robot's control, so that it emulates how a physiotherapist adaptively supports the patients' limb movement during stroke rehabilitation. This paper introduces the design of a novel interactive device Bi-Manu-Interact. This device is suited to be used as an experimental setup for the investigation of haptic human-human interaction and for collecting data to model therapists' haptic behavior. In this paper, we present mechanical and sensory specifications as well as task s visualizations for future investigations. Results of a pilot clinical evaluation of the Bi-Manu-Interact with nine stroke patients are also presented in this work.