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An improved active homodyne detector

Key Engineering Materials 2008年 381-382卷 329-332页

作者： Seek, H.L. Zhang, Y. Soh, Y.C. Singapore Institute of Manufacturing Technology 71 Nanyang Avenue Singapore 638075 Singapore Center for Modeling and Control of Complex Systems School of Electrical and Electronics Engineering Nanyang Technological University Nanyang Avenue Singapore 639798 Singapore

This paper proposes an improved active homodyne detection technique to compensate for the drift in homodyne measurement. The technique is implemented on a fiber based Michelson interferometer where a computer controller is designed to drive a piezoelectric cylinder attached to one arm of the interferometer. It is shown that the proposed technique can efficiently stabilize the interferometric output.

关键词： Michelson interferometers

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Hydrodynamic modeling and Parameter Identification of a Bionic Underwater Vehicle:RobDact

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Cyborg and Bionic systems 2022年第1期2022卷 164-176页

作者： Qiyuan Cao Rui Wang Tiandong Zhang Yu Wang Shuo Wang State Key Laboratory of Management and Control for Complex Systems Institute of A utomationChinese Academy of SciencesBeijingChina School of Artific ial Itelligence University of Chinese Academy of Sciences BeijingChina Center for Excellence in Brain Science and Itelligence Technology Chinese Academy of SciencesShanghaiChina

In this paper,the hydrodynamic modeling and parameter identifcation of the RobDact,a bionic underwater vehide inspired byDactylopteridae,are carried out based on computational fluid dynamics(CFD)and force measurement ***,thePaper briely describes the RobDact,then establishes the kinematis model and rigid body dynamics model of the RobDactaccording to the hydrodynamic force and moment *** CFD simulations,the hydrodynamic force of theRobDact at diferent speeds is obtained,and then,the hydrodynamic model parameters are ***,themeasurement platform is developed to obtain the relationship between the thrust generated by the RobDact and the inputfluctuation parameters,Finally,combining the rigid body dynamics model and the fin'thrust mapping model,thehydrodynamic model of the RobDact at diferent motion states is constructed.

关键词： dynamics(CFD) equations hydrodynamic

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MixedFusion: 6D Object Pose Estimation from Decoupled RGB-Depth Features

MixedFusion: 6D Object Pose Estimation from Decoupled RGB-De...

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International Conference on Pattern Recognition

作者： Hangtao Feng Lu Zhang Xu Yang Zhiyong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences

Estimating the 6D pose of objects is an important process for intelligent systems to achieve interaction with the real-world. As the RGB-D sensors become more accessible, the fusion-based methods have prevailed, since the point clouds provide complementary geometric information with RGB values. However, due to the difference in feature space between color image and depth image, the network structures that directly perform point-to-point matching fusion do not effectively fuse the features of the two. In this paper, we propose a simple but effective approach, named MixedFusion. Different from the prior works, we argue that the spatial correspondence of color and point clouds could be decoupled and reconnected, thus enabling a more flexible fusion scheme. By performing the proposed method, more informative points can be mixed and fused with rich color features. Extensive experiments are conducted on the challenging LineMod and YCB-Video datasets, which shows that our method significantly boosts the performance without introducing extra overheads. Furthermore, when the minimum tolerance of metric narrows, the proposed approach performs better for the high-precision demands.

关键词： Measurement Three-dimensional displays Image color analysis Fuses Pose estimation Color Pattern recognition

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Development and initial experiments of an intelligent dual-arm mobile robot - Baymax-I

Development and initial experiments of an intelligent dual-a...

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2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

作者： Liu, Wei Wang, Haitao Wang, Rui Wen, Dayong Lu, Tao Wang, Shuo Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai200031 China

ISBN: (纸本)9781665436786

This paper addresses the design and control of an intelligent dual-arm mobile robot named Baymax-I. The mechanism design of Baymax-I is based on modular concepts, which is mainly composed of three parts, including main body, dual-arms and a mobile chassis. The main body is designed as human-like structure, carrying multiple sensors. UR3 manipulators are adopted as two arms. Each manipulator has six degrees of freedom. A two-finger grip pawl is mounted on the end of each manipulator. A MIR mobile chassis drives the Baymax-I motion with high maneuverability. As for software systems, the robot is designed based on hierarchical structure. The bottom driving layer is used to perform specific movements. The middle layer is responsible for processing sensor data. The top layer is algorithm execution layer. In the end, three experiments including SLAM, pressing the elevator and opening the fridge are presented to verify the feasibility and effectiveness of the proposed system design and control methods of the Baymax-I robot. © 2021 IEEE.

关键词： Mobile robots

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Bounded Extremum Seeking for Single-Variable Static Map with Large Measurement Delay via Time-Delay Approach to Averaging

Bounded Extremum Seeking for Single-Variable Static Map with...

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IEEE Conference on Decision and control

作者： Xuefei Yang Emilia Fridman Bowen Zhao Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin China National Key Laboratory of Modeling and Simulation for Complex Systems School of Electrical Engineering Tel-Aviv University Israel

In this paper, we present a time-delay approach to gradient-based bounded extremum seeking (ES) with large measurement constant delay, for an unknown single-input static quadratic map. We assume that the extremum point and the Hessian $H$ belong to known intervals, whereas the sign of $H$ is known. We apply a time-delay approach to the bounded ES system and arrive at the neutral type system with a nominal linear delayed system. We present the latter system as a retarded one and employ variation of constants formula for practical stability analysis. Explicit conditions in terms of simple scalar inequalities depending on tuning parameters and delay are established to guarantee the practical stability of the bounded ES control systems. Given any delay and neighborhood of the extremum point and through the solution of the constructed inequalities, we find lower bounds on the dither period that ensures the practical stability.

关键词：

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A Robust Time-Delay Approach to Continuous-Time Extremum Seeking for Multi-Variable Static Map

A Robust Time-Delay Approach to Continuous-Time Extremum See...

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IEEE Conference on Decision and control

作者： Xuefei Yang Emilia Fridman Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin China National Key Laboratory of Modeling and Simulation for Complex Systems School of Electrical Engineering Tel-Aviv University Israel

In this article, we introduce a time-delay approach to gradient-based extremum seeking (ES) in the continuous domain for n-dimensional (nD) static quadratic maps. As in the recently introduced (for 2D maps in the continuous domain), we transform the system to the time-delay one (neutral type system). This system is $\mathbf{O}(\varepsilon)$ . ‘perturbation of the averaged linear ODE system. We further explicitly present the neutral system as the linear ODE, where $\mathrm{O}(\varepsilon)$ -terms are considered as disturbances with distributed delays of the length of the small parameter $\varepsilon$ . Quantitative (for uncertain map) and qualitative (for unknown map) practical stability analyses are provided by employing a variation of constants formula that greatly simplifies the results compared to the previously used Lyapunov-Krasovskii (L-K) method. The new approach also simplifies the conditions and improves the results. Examples from the literature illustrate the efficiency of the new approach, allowing essentially large uncertainty of the Hessian matrix with bounds on $\varepsilon$ that are not too small.

关键词：

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Learning to Manipulate Tools Using Deep Reinforcement Learning and Anchor Information

Learning to Manipulate Tools Using Deep Reinforcement Learni...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Wei, Junhang Cui, Shaowei Hao, Peng Wang, Shuo The School of Future Technology University of Chinese Academy of Sciences Beijing100049 China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The University of Chinese Academy of Sciences Beijing100049 China The Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

ISBN: (纸本)9781665481090

Endowing robots with tool manipulation skills helps them accomplish challenging tasks. While robots manipulate tools to achieve goals, the alignment of tools and targets is a noise-sensitive and contact-rich task. However, it is difficult to access the accurate pose of the tool and the target. When there is unknown noise in the observations, reinforcement learning can't be sure to perform well. In this paper, we define the easier-to-obtain accurate task-related information as anchor information and introduce a tool manipulation method based on reinforcement learning and anchor information, which can perform well when the observations include unknown noise. To evaluate the method, we build a simulated environment ToolGym, which includes four different kinds of tools and different noise sampling functions for each tool. Finally, we compare our method with baseline methods to show the effectiveness of the proposed method. © 2022 IEEE.

关键词： Reinforcement learning

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Visuotactile Feedback Parallel Gripper for Robotic Adaptive Grasping

Visuotactile Feedback Parallel Gripper for Robotic Adaptive ...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Zhang, Boyue Cui, Shaowei Zhang, Chaofan Hu, Jingyi Wang, Shuo School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Institute of Automation Chinese Academy of Sciences Beijing100190 China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing100190 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

ISBN: (纸本)9781665481090

In robot grasp and dexterous manipulation tasks, tactile sensing is important for the control adjustment of the manipulator. In this paper, we present a novel low-cost parallel gripper with high-resolution tactile sensing, named the GelStereo Gripper. Furthermore, an adaptive grasp strategy is proposed to endow the gripper with tactile-feedback grasp stability-maintaining ability. We install the gripper on our robot platform and conduct various grasp experiments by utilizing proposed control methods. Experimental results verify the reliability of the GelStereo gripper and also prove the effectiveness of the proposed strategy for experimental objects with different features. © 2022 IEEE.

关键词： Grippers

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Hindsight generative adversarial imitation learning

arXiv

引用

arXiv 2019年

作者： Liu, Naijun Lu, Tao Cai, Yinghao Li, Boyao Wang, Shuo State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Techology Chinese Academy of Sciences

Compared to reinforcement learning, imitation learning (IL) is a powerful paradigm for training agents to learn control policies efficiently from expert demonstrations. However, in most cases, obtaining demonstration data is costly and laborious, which poses a significant challenge in some scenarios. A promising alternative is to train agent learning skills via imitation learning without expert demonstrations, which, to some extent, would extremely expand imitation learning areas. To achieve such expectation, in this paper, we propose Hindsight Generative Adversarial Imitation Learning (HGAIL) algorithm, with the aim of achieving imitation learning satisfying no need of demonstrations. Combining hindsight idea with the generative adversarial imitation learning (GAIL) framework, we realize implementing imitation learning successfully in cases of expert demonstration data are not available. Experiments show that the proposed method can train policies showing comparable performance to current imitation learning methods. Further more, HGAIL essentially endows curriculum learning mechanism which is critical for learning policies. Copyright © 2019, The Authors. All rights reserved.

关键词： Demonstrations

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Parallel Ant Colony Optimization for the Electric Vehicle Routing Problem

Parallel Ant Colony Optimization for the Electric Vehicle Ro...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Michalis Mavrovouniotis Changhe Li Georgios Ellinas Marios Polycarpou KIOS Research and Innovation Center of Excellence University of Cyprus Nicosia Cyprus School of Automation and Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

Parallelizing metaheuristics has become a common practice considering the computation power and resources available nowadays. The aim of parallelizing a metaheuristic is either to increase the quality of the generated output, given a fixed computation time, or to reduce the required time in generating an output. In this work, we parallelize one of the best-performing ant colony optimization (ACO) algorithms and apply it to the electric vehicle routing problem (EVRP). EVRP is more challenging than the conventional vehicle routing problem, as with the consideration of electric vehicles additional hard constraints arise within the EVRP due to their limited driving range (e.g., the consideration whether electric vehicles need to visit a charging station during their daily operation). The proposed parallel ACO algorithm with several colonies also uses a migration policy to allow communication between the different colonies. From the simulation studies it is shown that parallelizing ACO algorithms, both with and without a migration policy, is highly effective.

关键词： Electric vehicles Routing Batteries Technological innovation Vehicle routing Charging stations Optimization

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