The Experts below are selected from a list of 198 Experts worldwide ranked by ideXlab platform
H. W. Yu - One of the best experts on this subject based on the ideXlab platform.
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A Variational Observation Model of 3D Object for Probabilistic Semantic SLAM
2019 International Conference on Robotics and Automation (ICRA), 2019Co-Authors: H. W. Yu, J. Y. MoonAbstract:We present a Bayesian object observation model for complete probabilistic semantic SLAM. Recent studies on object detection and feature extraction have become important for scene understanding and 3D mapping. However, 3D shape of the object is too complex to formulate the probabilistic observation model; therefore, performing the Bayesian inference of the object-oriented features as well as their pose is less considered. Besides, when the robot equipped with an RGB mono camera only observes the projected single view of an object, a significant amount of the 3D shape information is abandoned. Due to these limitations, semantic SLAM and viewpoint-Independent Loop closure using volumetric 3D object shape is challenging. In order to enable the complete formulation of probabilistic semantic SLAM, we approximate the observation model of a 3D object with a tractable distribution. We also estimate the variational likelihood from the 2D image of the object to exploit its observed single view. In order to evaluate the proposed method, we perform pose and feature estimation, and demonstrate that the automatic Loop closure works seamlessly without additional Loop detector in various environments.
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A Variational Feature Encoding Method of 3D Object for Probabilistic Semantic SLAM
2018 IEEE RSJ International Conference on Intelligent Robots and Systems (IROS), 2018Co-Authors: H. W. YuAbstract:This paper presents a feature encoding method of complex 3D objects for high-level semantic features. Recent approaches to object recognition methods become important for semantic simultaneous localization and mapping (SLAM). However, there is a lack of consideration of the probabilistic observation model for 3D objects, as the shape of a 3D object basically follows a complex probability distribution. Furthermore, since the mobile robot equipped with a range sensor observes only a single view, much information of the object shape is discarded. These limitations are the major obstacles to semantic SLAM and view-Independent Loop closure using 3D object shapes as features. In order to enable the numerical analysis for the Bayesian inference, we approximate the true observation model of 3D objects to tractable distributions. Since the observation likelihood can be obtained from the generative model, we formulate the true generative model for 3D object with the Bayesian networks. To capture these complex distributions, we apply a variational auto-encoder. To analyze the approximated distributions and encoded features, we perform classification with maximum likelihood estimation and shape retrieval.
J Poulton - One of the best experts on this subject based on the ideXlab platform.
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a cmos mixed signal clock and data recovery circuit for oif cei 6g backplane transceiver
IEEE Journal of Solid-state Circuits, 2006Co-Authors: M Y He, J PoultonAbstract:A CMOS low-power mixed-signal clock and data recovery circuit is presented in this paper. It is designed for OIF CEI-6G+ LR backplane transceiver, and consists of a phase detector, Loop filter, phase control logic, and phase interpolator. A unique subsampled architecture makes it possible for a low-power mixed-signal clock recovery Loop running at a rate of 6 Gb/s. The proposed architecture has data pattern Independent Loop bandwidth. Fabricated in a 0.13-/spl mu/m CMOS technology in an area of 280/spl times/100 /spl mu/m/sup 2/, the clock and data recovery Loop exhibits a frequency tracking range up to 2000 ppm. The bit error rate is less than 10/sup -12/ with a pseudorandom bit sequence of length 2/sup 31/-1. The power dissipation is 24 mW for clock and data recovery circuits from a single 1.2-V supply.
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A CMOS mixed-signal clock and data recovery circuit for OIF CEI-6G+ backplane transceiver
IEEE Journal of Solid-State Circuits, 2006Co-Authors: M Y He, J PoultonAbstract:A CMOS low-power mixed-signal clock and data recovery circuit is presented in this paper. It is designed for OIF CEI-6G+ LR backplane transceiver, and consists of a phase detector, Loop filter, phase control logic, and phase interpolator. A unique subsampled architecture makes it possible for a low-power mixed-signal clock recovery Loop running at a rate of 6 Gb/s. The proposed architecture has data pattern Independent Loop bandwidth. Fabricated in a 0.13-/spl mu/m CMOS technology in an area of 280/spl times/100 /spl mu/m/sup 2/, the clock and data recovery Loop exhibits a frequency tracking range up to 2000 ppm. The bit error rate is less than 10/sup -12/ with a pseudorandom bit sequence of length 2/sup 31/-1. The power dissipation is 24 mW for clock and data recovery circuits from a single 1.2-V supply.
M Y He - One of the best experts on this subject based on the ideXlab platform.
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a cmos mixed signal clock and data recovery circuit for oif cei 6g backplane transceiver
IEEE Journal of Solid-state Circuits, 2006Co-Authors: M Y He, J PoultonAbstract:A CMOS low-power mixed-signal clock and data recovery circuit is presented in this paper. It is designed for OIF CEI-6G+ LR backplane transceiver, and consists of a phase detector, Loop filter, phase control logic, and phase interpolator. A unique subsampled architecture makes it possible for a low-power mixed-signal clock recovery Loop running at a rate of 6 Gb/s. The proposed architecture has data pattern Independent Loop bandwidth. Fabricated in a 0.13-/spl mu/m CMOS technology in an area of 280/spl times/100 /spl mu/m/sup 2/, the clock and data recovery Loop exhibits a frequency tracking range up to 2000 ppm. The bit error rate is less than 10/sup -12/ with a pseudorandom bit sequence of length 2/sup 31/-1. The power dissipation is 24 mW for clock and data recovery circuits from a single 1.2-V supply.
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A CMOS mixed-signal clock and data recovery circuit for OIF CEI-6G+ backplane transceiver
IEEE Journal of Solid-State Circuits, 2006Co-Authors: M Y He, J PoultonAbstract:A CMOS low-power mixed-signal clock and data recovery circuit is presented in this paper. It is designed for OIF CEI-6G+ LR backplane transceiver, and consists of a phase detector, Loop filter, phase control logic, and phase interpolator. A unique subsampled architecture makes it possible for a low-power mixed-signal clock recovery Loop running at a rate of 6 Gb/s. The proposed architecture has data pattern Independent Loop bandwidth. Fabricated in a 0.13-/spl mu/m CMOS technology in an area of 280/spl times/100 /spl mu/m/sup 2/, the clock and data recovery Loop exhibits a frequency tracking range up to 2000 ppm. The bit error rate is less than 10/sup -12/ with a pseudorandom bit sequence of length 2/sup 31/-1. The power dissipation is 24 mW for clock and data recovery circuits from a single 1.2-V supply.
J. Y. Moon - One of the best experts on this subject based on the ideXlab platform.
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A Variational Observation Model of 3D Object for Probabilistic Semantic SLAM
2019 International Conference on Robotics and Automation (ICRA), 2019Co-Authors: H. W. Yu, J. Y. MoonAbstract:We present a Bayesian object observation model for complete probabilistic semantic SLAM. Recent studies on object detection and feature extraction have become important for scene understanding and 3D mapping. However, 3D shape of the object is too complex to formulate the probabilistic observation model; therefore, performing the Bayesian inference of the object-oriented features as well as their pose is less considered. Besides, when the robot equipped with an RGB mono camera only observes the projected single view of an object, a significant amount of the 3D shape information is abandoned. Due to these limitations, semantic SLAM and viewpoint-Independent Loop closure using volumetric 3D object shape is challenging. In order to enable the complete formulation of probabilistic semantic SLAM, we approximate the observation model of a 3D object with a tractable distribution. We also estimate the variational likelihood from the 2D image of the object to exploit its observed single view. In order to evaluate the proposed method, we perform pose and feature estimation, and demonstrate that the automatic Loop closure works seamlessly without additional Loop detector in various environments.
Huafeng Ding - One of the best experts on this subject based on the ideXlab platform.
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Dead Center Identification of Two-Degrees-of-Freedom Planar Parallel Manipulator Using Graph Theory and Transmission Angle
Journal of Mechanisms and Robotics, 2020Co-Authors: Huafeng DingAbstract:Abstract Parallel manipulators are widely applied for their advantages of high stiffness, load-bearing, operation speed, and precision positioning capabilities, which are required in many industrial applications. However, dead center identification is a challenging task and fundamental problem during design stage of parallel manipulators, and becomes more intractable for two-degrees-of-freedom (DOF) complex planar parallel manipulators (PPMs) design. This paper proposes a method to identify the dead center positions of two-DOF PPMs based on graph theory and transmission angle. First, these PPMs are denoted by a set of Independent Loops using a topological structural analysis of the kinematic chains and structural decomposition. Then, the relationship between the mobility factor and the Loop factor in the same Independent Loop is utilized to obtain the folded or stretched operation to form the new PPMs containing the corresponding instantaneous virtual Loop. Subsequently, the dead center positions can be located since the corresponding transmission angle of the new PPMs is equal to 0 deg or 180 deg. As a result, the solved dead center positions of the two-DOF three types seven-bar, nine-bar, and 11-bar PPMs will provide guidance for the proper design of these PPMs. Finally, the Jacobian method for identifying the dead center position is then used to verify the proposed method. The proposed method is systematic and programmable and can be applied to any two-DOF PPM regardless of the number of Independent Loops or types of joints.
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Dead Center Identification of Single-DOF Multi-Loop Planar Manipulator and Linkage Based on Graph Theory and Transmission Angle
IEEE Access, 2019Co-Authors: Huafeng DingAbstract:The dead center position (or singular position) is an important kinematic characteristic in mechanical design. However, its identification is a challenging task and becomes even more complex in multi-Loop planar linkages (or manipulators). According to graph theory and transmission angle, this paper proposes a method to identify the dead center positions of single-degree-of-freedom (DOF) planar linkages. The planar linkages can be denoted by a set of Independent Loops based on topological structural analysis of the kinematic chains and a structural decomposition. According to the relationship between the mobility factor wi and Loop factor fi in the same Independent Loop, the dead center positions can be located when the new planar linkages containing the corresponding instantaneous virtual Loop are formed by adjusting fi to equal to wi or (wi -1), in which the corresponding transmission angle is equal to 0° and 180°. The Jacobian method for identifying the dead center position is then used to verify the proposed method. Furthermore, the dead center positions of the single-DOF 10-bar and 12-bar planar linkages are solved. The proposed method is systematic and programmable and can be applied to any single-DOF multi-Loop linkage regardless of the number of Independent Loops or types of joints.
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The establishment of edge-based Loop algebra theory of kinematic chains and its applications
Engineering With Computers, 2009Co-Authors: Huafeng Ding, Jing Zhao, Zhen HuangAbstract:Based on the edge-based array representation of Loops in the topological graphs of kinematic chains, this paper first proposes three arithmetic operations of Loops. Then the concept of the Independent Loop set as well as its determination rules is introduced, and a new structure decomposition algorithm of kinematic chains is presented. Based on the algorithm, an automatic and efficient method for rigid sub-chain detection and driving pair selection of kinematic chains is proposed. Finally, an index is proposed to assess computation complexity of kinematic analysis with respect to different driving pair selections.
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Computer-Aided Edge Loop Theory of Kinematic Structure of Mechanisms and Its Applications
Volume 7: 33rd Mechanisms and Robotics Conference Parts A and B, 2009Co-Authors: Huafeng Ding, Jing Zhao, Qinchuan Li, Zhen HuangAbstract:Based on the edge-based array representation of Loops in the topological graphs of kinematic chains, this paper first proposes three arithmetic operations of Loops. Then the concept of the Independent Loop set as well as it determination rules is introduced, and a new structure decomposition algorithm of kinematic chains is presented. Based on the algorithm, an automatic and efficient method for rigid subchain detection and driving pair selection of kinematic chains is proposed. Finally, an index is proposed to assess computation complexity of kinematic analysis with respect to different driving pair selections.Copyright © 2009 by ASME
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A new theory for the topological structure analysis of kinematic chains and its applications
Mechanism and Machine Theory, 2007Co-Authors: Huafeng Ding, Zhen HuangAbstract:Abstract Based on the array representation of Loops in topological graphs of kinematic chains, this paper proposes two basic Loop operations, “Θ” and “⊕”, for the first time. The existent conditions and properties of “⊕” operation are researched and four laws about the operation are presented. Furthermore, after the important concepts of the Independent Loop set and its selection theorem are proposed, the Loop relationship of kinematic chains is revealed; thus an original theory of Loop analysis is established. Finally, some applications are given under the basic theory above, such as the isomorphism identification, the detection of rigid sub-chains, and the freedom type analysis of kinematic chains.
