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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Antonio Moualeu Kevin Pluckter Jun Ueda Bio-Robotics & Human Modeling Lab School of Mechanical Engineering Georgia Institute of Technology Atlanta Georgia USA Intuitive Surgical Inc Carnegie Mellon University and formerly with the Bio-Robotics & Human Modeling Lab School of Mechanical Engineering Georgia Institute of Technology Atlanta Georgia USA

ISBN: (数字)9781728167947

ISBN: (纸本)9781728167954

The current paper addresses a central question at the basis of our research into the control of haptic assist devices: is kinetic sensor information sufficient for the intuitive control of haptic assist devices during physical human-robot interaction (pHRI) Our study proposes the addition of operator physiological data in the form of muscle cocontraction (or coactivation) information, obtained from processing surface electromyographic (sEMG) sensor data from the operator's arm muscles. Muscle coactivation has shown in previous research to correlate to the operator's endpoint stiffness, an important system variable not directly observable. Results from target tracking experiments conducted on 10 subjects using a one-degree-of-freedom (1-DoF) haptic device show a muscle cocontraction variable as the best feature to predict the motor intent of the human operator. In addition, using muscle cocontraction data in tandem with kinetic data to train a Support Vector Machine (SVM) classifier offline results in an average cross-validation accuracy of 99%, compared to an accuracy of 89% with kinetic data only. Furthermore, statistically significant trends in cocontraction levels were observed in different stability conditions (trajectory tracking experiments, 10 subjects, p

关键词： Muscles Haptic interfaces Electromyography Robot sensing systems Force Task analysis Kinematics

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Encrypted Feedback Linearization and Motion Control for Manipulator with Somewhat Homomorphic Encryption

Encrypted Feedback Linearization and Motion Control for Mani...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Kaoru Teranishi Kiminao Kogiso Jun Ueda Department of Mechanical Engineering and Intelligent Systems The University of Electro-Communications Tokyo Chofu Japan Bio-Robotics & Human Modeling Lab School of Mechanical Engineering Georgia Institute of Technology Atlanta GA USA

ISBN: (数字)9781728167947

ISBN: (纸本)9781728167954

Encrypted control is a cryptographic approach to reducing the risks of eavesdropping attacks for networked control systems. An encrypted controller determines control inputs directly from encrypted data without decryption. This study considers an implementation of an encrypted motion controller, which consists of feedback linearization and PD control, for a manipulator using somewhat homomorphic encryption. A controller reconstruction method is proposed for separating a nonlinear time-varying controller into a linear part and a nonlinear part. A plant side device supports encrypted controller operations by generating the nonlinear part in advance of encryption. Simulation results demonstrate that the proposed encrypted control system can achieve the same control performance as the one that an unencrypted control system does.

关键词： Encryption Manipulators Networked control systems Quantization (signal) Feedback linearization

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Inverse Error Function Trajectories for Image Reconstruction∗This material is based upon work supported by the National Science Foundation under Grant No. 1662029

Inverse Error Function Trajectories for Image Reconstruction...

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2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018

作者： Katoch, Rohan Fusaro, Beatriz Ueda, Jun George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Bio-Robotics and Human Modeling Lab AtlantaGA30332 United States

ISBN: (纸本)9781538680940

Capturing clear images while a camera is moving fast, is integral to the development of mobile robots that can respond quickly and effectively to visual stimuli. This paper proposes to generate camera trajectories, with position and time constraints, that result in higher reconstructed image quality. The degradation in of an image captured during motion is known as motion blur. Three main methods exist for mitigating the effects of motion blur: (i) controlling optical parameters, (ii) controlling camera motion, and (iii) image reconstruction. Given control of a camera's motion, trajectories can be generated that result in an expected blur kernel or point-spread function. This work compares the motion blur effects and reconstructed image quality of three trajectories: (i) linear, (ii) polynomial, and (iii) inverse error. Where inverse error trajectories result in Gaussian blur kernels. Residence time analysis provides a basis for characterizing the motion blur effects of the trajectories. © 2018 IEEE.

关键词： Image reconstruction

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Secure Observer-based Motion Control based on Controller Encryption

Secure Observer-based Motion Control based on Controller Enc...

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American Control Conference

作者： Kaoru Teranishi Masahiro Kusaka Naoki Shimada Jun Ueda Kiminao Kogiso Advanced Course of Electronic and Mechanical Engineering National Institute of Technology Ishikawa College Tsubata Ishikawa Japan The University of Electro-Communications Chofu Tokyo Japan National Institute of Technology Ishikawa College Tsubata Ishikawa Japan George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Bio-Robotics and Human Modeling Lab Atlanta GA 30332 USA

ISBN: (纸本)9781538679012;9781538679265

Disturbance observer-based motion control, one of effective schemes for force control and uncertainty compensation has been widely used in industrial systems such as manipulators and servo systems. Despite its effectiveness reported in the literature, security measures applicable to industrial equipment and motion control systems have not yet been established in comparison to those to information equipment. A lack of cybersecurity measures may result in critical incidents in the future. This study proposes a method to enhance the cybersecurity of an integral-type servo controller with a full-order state observer, or disturbance observer, for an industrial motion control system based on controller encryption. Feasibility of the controller encryption method was confirmed through position servo control experiments with a feed drive testbed. Influences on computational latency for real-time control were examined by varying the size of the key used for encryption. Performance degradation of the proposed encrypted control systems was millimeter order, and thus the controller encryption method can be applied as a security measure in motion control systems.

关键词： Motion Control System cryptography Security measures Network security disturbance observer information equipment Controllers key length industrial equipment critical incident Servo systems Force control Real time control Manipulators Observers

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Discrete switching commands for tracking and vibration suppression using a quantized, compliant camera orientation system

Discrete switching commands for tracking and vibration suppr...

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IEEE International Conference on robotics and Automation

作者： Michael Duckjune Kim Jun Ueda Bio-Robotics and Human Modeling Lab George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta GA 30332-0405 USA.

ISBN: (纸本)9781467380270

This paper presents a method to generate discrete switching commands for a camera orientation system exhibiting quantization and flexibility to achieve smooth-pursuit like movements. Existing vibration suppression techniques and camera positioning devices have shown notable results but focused only on point-to-point movements. A desired motion profile can be generated by incorporating a classical feedback controller with PWM quantization but each unit actuator is required to produce high-frequency switching that can potentially damage the complaint mechanism. The proposed controller generates pulse-like switching commands for smooth-pursuit like motion to match the velocity of an object of interest. Then, switching commands for vibration suppression are generated to avoid high-frequency switching. The proposed method has been evaluated by using a robotic system which has a total of 32 piezoelectric actuator. The experiment results show that the camera orientation system successfully achieved dynamic vision given the proposed commands in an open-loop manner.

关键词： commands tracking vibration

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Real-time image de-blurring and image processing for a robotic vision system

Real-time image de-blurring and image processing for a robot...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Michael D. Kim Jun Ueda Bio-Robotics Human Modeling Lab Georgia Institute of Technology Atlanta GA USA

ISBN: (纸本)9781479969241

This paper proposes a method for real-time de-blurring of images captured by a robotic system. De-blurring is achieved by combining a dynamics-based approach and parallel computing. Existing methods have successfully restored a blurry image but were not suitable for real-time applications. The dynamics-based method with parallel programming in the FPGA is used to estimate the PSF during the camera exposure window. The deconvolution process, which involves iterative matrix calculations with millions of pixels, is then performed on the GPU to achieve real-time performance. The proposed method has been evaluated by using a robotic system which has a total of 32 piezoelectric actuators and one vision sensor. The frame rate of image de-blurring ranges from 20.32 to 40.68 fps and thus real-time performance is achieved. In comparison to existing methods, the proposed method produces the best image quality. The dynamics-based approach is extended to real-time image stitching which is computationally cheap and robust to motion blur. It is demonstrated from image stitching that real-time de-blurring is beneficial for image processing.

关键词： Real-time systems Cameras Robot vision systems Graphics processing units Actuators Image processing

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Real time image de-blurring and image stitching for muscle inspired camera orientation system

Real time image de-blurring and image stitching for muscle i...

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IEEE Workshop on Advanced robotics and its Social Impacts, ARSO

作者： Sean A. Kilbride Michael D. Kim Jun Ueda Bio-Robotics Human Modeling Lab Georgia Institute of Technology Atlanta GA USA

This paper proposes a method for real-time image de-blurring and panoramic image stitching. Currently there are several methods for de-blurring images and images stitching however, many take several seconds to process on a standard computer. The method proposed in this paper is to implement parallel processing techniques to an existing de-blurring method and a new dynamic-based panoramic image stitching method to achieve real-time image processing. This method has been applied to a muscle inspired camera orientation system that rapidly captures images to process these images in real time. This orientation system captures images while the camera is in motion causing a blurring effect. Using estimated position data from the system dynamics of the camera orientation system the point spread function of the image and the average image location can be estimated; hence, the image is de-blurred and stitched in real time. The proposed method makes use of parallel processing and precomputation techniques to greatly reduce the required processing time when compared to existing methods.

关键词： Cameras Real-time systems Equations Mathematical model Robot vision systems Graphics processing units

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Dynamics-based motion deblurring for a biologically-inspired camera positioning mechanism

Dynamics-based motion deblurring for a biologically-inspired...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Michael D. Kim Jun Ueda Bio-Robotics Human Modeling Lab George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta GA 30332-0405 USA

ISBN: (纸本)9781467363563

This paper presents a new dynamics-based method for image processing in coordination with rapid ocular movement. A camera positioning mechanism with piezoelectric cellular actuators will be employed to demonstrate the effectiveness of this approach. There are a number of mechanisms for automatic camera positioning, but few have much in common with the human ocular positioning system. When a rapid point-to-point motion is created in a camera positioner, like human saccadic motion, the image sensor receives blurry images. Existing image techniques rely solely on obtained images, or use external sensors to estimate a blur kernel, or point spread function (PSF), for motion deblurring. Inspired by recent oculomotor studies, this paper proposes a method for estimating PSFs directly from the system dynamics of a camera positioning mechanism without motion sensors. The proposed method has been evaluated by using a single degree-of-freedom camera orientation system. Results are compared with conventional methods in terms of speed and accuracy.

关键词： Dynamics-based biologically-inspired camera PSF

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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