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2019 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2019

作者： Ma, Ruichen Wang, Yu Wang, Rui Wang, Shuo State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China CAS Center for Excellence in Brain Science and Intelligence Technology

ISBN: (纸本)9781728137261

This paper addresses some experiments about measurements of thrust and heave force generated by a modular designed biomimetic underwater propeller. The propeller has a ribbon fin that consists of twelve rays linked by a latex membrane. Different forms of waves can be generated by the propeller. A measurement platform is constructed to obtain the thrust and heave force generated by the waves along with the input power of the propeller. Three types of waves are performed on the platform, including sinusoidal waves, fusiform sinusoidal waves and inward counter-propagating sinusoidal waves. By changing the parameters of undulating waves, a total of three hundred series of experiments are implemented. The measurement results of three types of waves are analyzed and the differences among three types of waves are compared. © 2019 IEEE.

关键词： Fins (heat exchange)

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Generalized Visual-Tactile Transformer Network for Slip Detection

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IFAC-PapersOnLine 2020年第2期53卷 9529-9534页

作者： Shaowei Cui Junhang Wei Xiaocan Li Rui Wang Yu Wang Shuo Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Future Technology University of Chinese Academy of Sciences Beijing 100049 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai 200031 China

Slip detection plays a vital role in robotic dexterous grasping and manipulation, and it has long been a challenging problem in the robotic community. Different from traditional tactile perception-based methods, we propose a Generalized Visual-Tactile Transformer (GVT-Transformer) network to detect slip based on visual and tactile spatiotemporal sequences. The main novelty of GVT-Transformer is its ability to address unaligned vision and tactile data in various formats captured by various tactile sensors. Furthermore, we train and test our proposed network on a public and our visual-tactile grasping datasets. The experimental results show that our method is more suitable for sliding detection tasks than previous visual-tactile learning methods and more versatile.

关键词： Information sensor fusion Perception sensing Intelligent robotics Deep neural networks Visual-tactile fusion perception

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Output Feedback control for MIMO systems with Disturbances Compensation

Output Feedback Control for MIMO systems with Disturbances C...

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European control Conference (ECC)

作者： D.E. Konovalov S.A. Vrazhevsky I.B. Furtat A.S. Kremlev Martin Cech Faculty of Control Systems and Robotics ITMO University St. Petersburg Russia The Laboratory ”Control of Complex System” Institute for Problems in Mechanical Engineering of the Russian Academy of Sciences (IPME RAS) St. Petersburg Russia Pilsen — NTIS - European Center of Excellence University of West Bohemia

ISBN: (数字)9783907144022

ISBN: (纸本)9781728188133

The paper deals with the novel feedback output control law for multiple-input multiple-output (MIMO) plant with mismatched bounded disturbances. The plant model is described by linear and Lipshitz nonlinear terms. The control law is based on the auxiliary loop method for disturbance estimation and modified backstepping method for control under mismatched disturbances. Differently from existing results based on backstepping method the proposed algorithm allows to reduce the accuracy in steady state, while the existing auxiliary loop based algorithm are feasible under matched disturbances. The results in the England Power System Benchmark illustrate the efficiency of the proposed scheme.

关键词： Backstepping Steady-state control systems Mathematical model Attenuation MIMO communication Estimation

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A simulator with an elastic guidewire and vascular system for minimally invasive vascular surgery

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Science China(Information Sciences) 2018年第10期61卷 250-252页

作者： Xiaoran CHENG Xiaoliang XIE Guibin BIAN Zengguang HOU Shiqi LIU Zhanjie GAO State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences University of Chinese Academy of Sciences CAS Center for Excellence in Brain Science and Intelligence Technology

Simulators play an important role in minimally invasive vascular surgery training. A challenging task for the simulator is to model an elastic guidewire and an elastic vascular system, both of which are important aspects for vascular ***, many simulators treat the virtual vascular system as a rigid object, which reduces the immersion of operators. In this study, a virtual guidewire is first modeled based on Cosserat rod

关键词： Pi Figure A simulator with an elastic guidewire and vascular system for minimally invasive vascular surgery

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Macroporous Ni foam-supported Co_3O_4 nanobrush and nanomace hybrid arrays for high-efficiency CO oxidation

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Journal of Environmental Sciences 2019年第1期31卷 136-144页

作者： Shengpeng Mo Hui He Quanming Ren Shuangde Li Weixia Zhang Mingli Fu Limin Chen Junliang Wu Yunfa Chen Daiqi Ye School of Environment and Energy South China University of Technology State Key Laboratory of Multi-phase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control (SCUT) Guangdong Provincial Engineering and Technology Research Centre for Environmental Risk Prevention and Emergency Disposal South China University of Technology Center for Excellence in Urban Atmospheric Environment Institute of Urban Environment Chinese Academy of Sciences

Herein, we reported the synthesis of well-defined Co_3O_4 nanoarrays(NAs) supported on a monolithic three-dimensional macroporous nickel(Ni) foam substrate for use in highefficiency CO oxidation. The monolithic Co_3O_4 NAs catalysts were obtained through a generic hydrothermal synthesis route with subsequent calcination. By controlling the reaction time,solvent polarity and deposition agent, these Co_3O_4 NAs catalysts exhibited various novel morphologies(single or hybrid arrays), whose physicochemical properties were further characterized by using several analytical techniques. Based on the catalytic and characterization analyses, it was found that the Co_3O_4 NAs-6 catalyst with nanobrush and nanomace arrays displayed enhanced catalytic activity for CO oxidation, achieving an efficient 100% CO oxidation conversion at a gas hourly space velocity(GHSV) 10,000 hr^(-1) and 150°C with longterm stability. Compared with the other Co_3O_4 NAs catalysts, it had the highest abundance of surface-adsorbed oxygen species, excellent low-temperature reducibility and was rich in surface-active sites(Co^(3+)/Co^(2+)= 1.26).

关键词： CO oxidation Nanomace Co3O4 Hybrid arrays Macroporous Ni foam

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Learning category-level implicit 3D rotation representations for 6D pose estimation from RGB Images

Learning category-level implicit 3D rotation representations...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Li, Xiaocan Cai, Yinghao Wang, Shuo Lu, Tao Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

ISBN: (纸本)9781728163215

We exploit the embedding ability of a de-noising autoencoder for an implicit 3D rotation representation learning at the category level. Contrast to the exact 3D reconstruction model of each instance-level physical object, we leverage the inexact CAD/Reconstruction models of an object as the representative model for some category. Under our assumptions that objects within the same category share resemble geometry, we train a de-noising autoencoder on synthetic 3D views of category-level objects to extract the homogenous features at the bottleneck layer. The latent representation is agnostic not only to heterogeneous textures, colors, and illuminations, but also ambiguous pose caused by object symmetry. To extend the instance-level 3D translation estimation to the category level, we considered the 3D diagonal length ratio between the source and target object. We achieved a frame rate of 17Hz. © 2019 IEEE.

关键词： Object detection

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Parameter estimation survey for multi-joint robot dynamic calibration case study

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中国科学:化学（英文版） 2019年第10期62卷 98-112页

作者： Shaolin ZHANG Shuo WANG Fengshui JING Min TAN The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai 200031 China

Accurate model parameters are the basis of robot *** linear and nonlinear models have been proposed to calibrate the inertial parameters and friction parameters of multi-joint ***,methods of choosing a model and calculating its parameters still have few *** paper reviews typical linear/nonlinear models and different calculation methods for robot dynamic *** simulations,the features of different methods are analyzed,including torque error,parameter error,model adaptability,solution time,and anti-interference ability of the calibration ***,an experiment performed on a six-degree-of-freedom industrial manipulator is used as an example to illustrate how to select the model for a specified *** comparisons and experiments provide references for the parameter calibration of multi-joint robots.

关键词： dynamic parameter calibration friction calibration robot dynamics industrial manipulator dynamic models

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Programming by visual demonstration for pick-and-place tasks using robot skills

Programming by visual demonstration for pick-and-place tasks...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Hao, Peng Lu, Tao Cai, Yinghao Wang, Shuo State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

ISBN: (纸本)9781728163215

In this paper, we present a vision-based robot programming system for pick-and-place tasks that can generate programs from human demonstrations. The system consists of a detection network and a program generation module. The detection network leverages convolutional pose machines to detect the key-points of the objects. The network is trained in a simulation environment in which the train set is collected and auto-labeled. To bridge the gap between reality and simulation, we propose a design method of transform function for mapping a real image to synthesized style. Compared with the unmapped results, the Mean Absolute Error (MAE) of the model completely trained with synthesized images is reduced by 23% and the False Negative Rate FNR (FNR) of the model fine-tuned by the real images is reduced by 42.5% after mapping. The program generation module provides a human-readable program based on the detection results to reproduce a real-world demonstration, in which a longshort memory (LSM) is designed to integrate current and historical information. The system is tested in the real world with a UR5 robot on the task of stacking colored cubes in different orders. © 2019 IEEE.

关键词： Demonstrations

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Grasp State Assessment of Deformable Objects Using Visual-Tactile Fusion Perception

arXiv

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arXiv 2020年

作者： Cui, Shaowei Wang, Rui Wei, Junhang Li, Fanrong Wang, Shuo State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Further Technology Universty of Chinese Academy of Sciences Beijing100190 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

Humans can quickly determine the force required to grasp a deformable object to prevent its sliding or excessive deformation through vision and touch, which is still a challenging task for robots. To address this issue, we propose a novel 3D convolution-based visual-tactile fusion deep neural network (C3D-VTFN) to evaluate the grasp state of various deformable objects in this paper. Specifically, we divide the grasp states of deformable objects into three categories of sliding, appropriate and excessive. Also, a dataset for training and testing the proposed network is built by extensive grasping and lifting experiments with different widths and forces on 16 various deformable objects with a robotic arm equipped with a wrist camera and a tactile sensor. As a result, a classification accuracy as high as 99.97% is achieved. Furthermore, some delicate grasp experiments based on the proposed network are implemented in this paper. The experimental results demonstrate that the C3D-VTFN is accurate and efficient enough for grasp state assessment, which can be widely applied to automatic force control, adaptive grasping, and other visual-tactile spatiotemporal sequence learning problems. Copyright © 2020, The Authors. All rights reserved.

关键词： Deformation

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Evolution and Neural Representation of Mammalian Cooperative Behavior

SSRN

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SSRN 2021年

作者： Jiang, Mengping Wang, Miaoyaoxin Shi, Qianqian Wei, Lei Lin, Yongqin Wu, Dingcheng Liu, Boyi Nie, Xiupeng Qiao, Hong Xu, Lin Yang, Tianming Wang, Zuoren Institute of Neuroscience State Key Laboratory of Neuroscience CAS Center for Excellence in Brain Science &Intelligence Technology Chinese Academy of Sciences Shanghai200031 China Key Laboratory of Animal Models and Human Disease Mechanisms and Laboratory of Learning and Memory Kunming Institute of Zoology Chinese Academy of Sciences KunmingYunnan650223 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

Cooperation is common in nature and has been pivotal to the development of human society. However, the details of how and why cooperation evolved remain poorly understood. Cross-species investigation of cooperation may help to elucidate the evolution of cooperative strategies. Thus, we designed a novel cooperative behavioral paradigm and quantitatively examined the cooperative abilities and strategies of mice, rats, and tree shrews. We found that social communication played a key role in the establishment of new cooperation, and that increased cooperative ability and a more efficient cooperative strategy emerged as a function of the evolutionary hierarchy of the tested species. We also found neural representations of distinct aspects of cooperation in the brains of rats through in vivo electrophysiological recording. Cooperation-preferential signals were identified in addition to material reward-preferential signals, each of which may represent internal drives for cooperation. © 2021, The Authors. All rights reserved.

关键词： Rats

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