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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Zixiang Ding Yaran Chen Nannan Li Dongbin Zhao State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

In this paper, we propose Simplified Space based Neural Architecture Search (SSNAS), an efficient approach for automatic architecture search. Inspired by the popular convolutional neural networks which have strong capability for feature extraction with small convolutional kernels, we design a simplified search space of convolutional operations with small kernel and construct a large model based on it. Furthermore, we use an Long Short-Term Memory (LSTM) to sample child model from the large model in a way of selective activation. The probability distribution of selective activation is obtained by training the LSTM with reinforcement learning for maximizing the expected reward of selected child model on the validation set. Moreover, the trained weights are saved in a large model which concludes all child models. Each weight of new sampled child model will be restored when being selected by another one again instead of training from scratch so that SSNAS can greatly reduce the expensive computation than traditional approaches for automatic model design. Extensive experiments on CIFAR-10, ImageNet and VOC show that the proposed approach excels in discovering transferable architectures with high performance.

关键词： Computer architecture Microprocessors Computational modeling Search problems Estimation Training Kernel

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A Building Evacuation Model Integrated with Multiple Algorithms

A Building Evacuation Model Integrated with Multiple Algorit...

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Chinese automation Congress (CAC)

作者： Xiaoyu Zhao Xiwei Liu Xiaoyan Gong Sifeng Jing Jian He The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing University of Technology BeiJing China

Due to the increasing frequency of terrorist attacks all over the world, we designed an emergency evacuation model under the situation of the terrorist attacks. This model uses the Ant Colony Optimization (ACO) as a macro solution, the Cellular Automata (CA) as a micro-control method, and the Queuing Theory Model (QTM) to solve the queuing problem of escape exits. Based on the model we built, the optimized evacuation plan under different conditions were obtained.

关键词： Automata Queueing analysis Terrorism Ant colony optimization Analytical models Standards Buildings

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Design and Validation of an Asymmetric Bowden-Cable-Driven Series Elastic Actuator

Design and Validation of an Asymmetric Bowden-Cable-Driven S...

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IEEE International Conference on Robotics and Biomimetics

作者： Ning Sun Long Cheng Lin Tian Zeng-Guang Hou Min Tan State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Weight, size and torque control for hand exoskeleton robots are challenging due to lack of small and compact bidirectional torque actuators. In this paper, an asymmetric Bowden-cable-driven series elastic actuator (ABLE-SEA) for hand exoskeleton robots was proposed based on the fact that the required torques for finger movements are asymmetric. Compared to series elastic actuator and transmission system that were designed separately, the elastic elements of ABLESEA were placed in transmission parts to connect series elastic actuator with transmission system, which makes system compact. ABLE-SEA is 71 mm × 19.5mm × 20mm in dimension and weighs 30g except motor which is placed remotely. The dynamic model of ABLE-SEA was established, and feedback proportional-derivative (PD) control plus a feed-forward term was used to track the reference torque for the ABLE-SEA. The reference torque tracking test at different frequencies was performed at the developed prototype. Meanwhile, the peak torque of ABLE-SEA was tested. The experimental results verified that the torque bandwidth of the proposed series elastic actuator could reach 4Hz, and the peak torque of ABLE-SEA could reach 0.3Nm, which meet the design requirement.

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A graph-based semi-supervised fraud detection framework 4

A graph-based semi-supervised fraud detection framework

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4th IEEE International Conference on Cybernetics, Cybconf 2019

作者： Jing, Rongrong Zheng, Xiaolong Tian, Hu Zhang, Xingwei Chen, Weiyun Wu, Dash Desheng Zeng, Daniel Dajun The 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 Shenzhen518129 China School of Management Huazhong University of Science Technology Wuhan430074 China

ISBN: (纸本)9781728100302

Credit card payment has become one of the most commonly used consumption methods in modern society, yet risks of fraud transactions using credit cards also increased. Numerous methods have been proposed for credit card fraud detection during past decades. However, most of the existing frameworks mainly focus on directly processing structured data. While they lack inner relations between features of raw descriptions for credit owners, this could lead to information deficiency. Therefore, we proposed a graph-based semi-supervised fraud detection framework. In this work, the structured dataset is translated to graph format through the sample similarity in order to improve the effect of label propagation on the graph. We further adopt the GraphSAGE algorithm which has been demonstrated to show excellent performance on node classification tasks. Experimental results on the real-world dataset show that our graph-based model can outperform state-of-the-art baselines. We argue that our model could be extended to other classification tasks using structured data. © 2019 IEEE.

关键词： Graph neural networks

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Object Pose Estimation Based on RGB-D Sensor for Cooperative Spray Painting Robot

Object Pose Estimation Based on RGB-D Sensor for Cooperative...

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IEEE International Conference on Cyber Technology in automation, control, and Intelligent systems

作者： Zhe Wang Fengshui Jing Junfeng Fan Zhaoyang Liu Yunong Tian Zishu Gao State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728107707

ISBN: (纸本)9781728107714

For human-robot cooperative spray painting robot, offline programming based on predefined model of the unpainted object is a robust and efficient method for trajectory generation. To apply the programmed trajectory on the unpainted object, the relative pose between the object and the predefined model needs to be acquired. Nevertheless, acquiring an accurate estimation of the pose in spray painting setting remains a problem. To address this, a RGB-D pose estimation system based on deep learning and iterative closest point (ICP) alignment is proposed in this paper. The perception module of this system is RGB-D sensor. The RGB-D image of the object is segmented using Fully Convolutional Network (FCN) with RGB-D input. The resulting segmented point cloud is aligned with the model candidates using ICP algorithm to estimate the pose of the object. It is validated in the experiments that the proposed system and methods are effective and robust.

关键词： Painting Robot sensing systems Solid modeling Three-dimensional displays Pose estimation Image segmentation Iterative closest point algorithm

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Design of a Robotic Fish Based on a Passive Flexible Mechanism*

Design of a Robotic Fish Based on a Passive Flexible Mechani...

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IEEE International Conference on Robotics and Biomimetics

作者： Ben Lu Yuzhuo Fu Qianqian Zou Sai Deng Chao Zhou State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

In recent years, along with the rapid development of manufacturing, control, sensing and other technologies, biomimetic robotic fish has played an increasingly important role in marine exploration, underwater rescue, water quality monitoring and other fields. This paper designed a robotic fish based on a passive flexible mechanism to realize the fish-like propulsion function. The motion simulation of the designed transmission mechanism was carried out to get the actual curve of the structure. Through the analysis of the force of the fishtail, the preliminary selection scheme of the elastic joints based on the passive flexible mechanism was obtained. Finally, this paper built a robotic fish based on a passive flexible mechanism, which could achieve the motion frequency adjustable from 0.5 to 9 Hz, and the maximum swimming speed reaching 1.05 BL/s (BL, body length). This design scheme provided a new reference for the design of the biomimetic robotic fish and had certain practical significance.

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Self-modeling Tracking control of Crawler Fire Fighting Robot Based on Causal Network*

Self-modeling Tracking Control of Crawler Fire Fighting Robo...

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2019 IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Wenkai Chang Peng Li Caiyun Yang Tao Lu Yinghao Cai Shuo Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

In this paper, a self-modeling method based on a causal network is proposed for the tracking control of the Crawler Fire Fighting Robot (CFFR). The method mainly consists of two parts, one is a motion model, based on data driving, learning to establish the correspondence between control signal sequence and vehicle motion, estimating the motion state of the next moment from historical data, eliminating complex CFFR modeling. The other is the tracking network. Based on the simulation data of the motion model, the relationship between the target trajectory and the current control command is learned, which simplifies the design and cumbersome tuning of the complex controller. The effectiveness of the proposed method is verified in both simulated and real-world environments. Qualitative and quantitative experimental results verify the accuracy of the tracking.

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Line-of-Sight Strategy-Based Path-Following System for a Multi-Joint Robotic Fish

Line-of-Sight Strategy-Based Path-Following System for a Mul...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Shijie Dai Chao Zhou Zhengxing Wu Min Tan Junzhi Yu School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Naval Research Academy Beijing China State Key Laboratory for Turbulence and Complex System BIC-ESAT College of Engineering Peking University Beijing China

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

This paper proposes a real-time path-following control system for a multi-joint robotic fish. The mechanical structure and dynamic model of the robotic fish for pathfollowing are first described. Then, the framework of the path-following control algorithm is established based on the built dynamic model, including a modified line-of-sight (LOS) guidance law, an active disturbance rejection control (ADRC)based heading controller and a proportional-integral-derivative (PID)-based speed controller. Specially, the modified LOS strategy is designed to select the tracking points and also provide the desired heading angle. Afterwards, to overcome systematic uncertainties and environmental disturbances, the ADRC method is adopted to design the heading controller. Meanwhile, the PID controller is also developed to maintain an appropriate swimming speed. Finally, simulations in both linear-and circular-path following are presented to validate the effectiveness of the proposed method.

关键词： Robots Robot kinematics Task analysis Real-time systems Oscillators Mathematical model Force

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An Image-based Automatic Calculation Algorithm for Bridge Crack Size

An Image-based Automatic Calculation Algorithm for Bridge Cr...

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Chinese automation Congress (CAC)

作者： Qi Wang Xisong Dong Zhen Shen Gang Xiong Jun Yan Lulu Niu The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

The crack is a serious disease of bridges and one of the important topics in the bridge detecting. Compared with the traditional manual methods for measuring crack size directly or indirectly, this paper proposes a new method based on Matlab toolbox for digital calculation of crack images. After preprocessing and detecting the original image, some morphological operation like corrosion and expansion have been used in this paper to improve the calculation accuracy. Relying on the connected region calculation, the stepped line is introduced to approach the real crack and obtain the number of pixels in length and width. Then through some calculations, the true size of the crack can be converted from pixel values, which provides a good basis for determining its hazard level. At the end of this paper, experiment results verify the accuracy and practicability of the method, and this method can be used as a subsequent part of crack identification to obtain crack size information.

关键词： Bridges Matlab Matrices Ultrasonic variables measurement Image edge detection Size measurement Feature extraction

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Impacts of export restrictions on the global personal protective equipment trade network during COVID-19

arXiv

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arXiv 2021年

作者： Ye, Yang Zhang, Qingpeng Cao, Zhidong Chen, Frank Youhua Yan, Houmin Stanley, H. Eugene Zeng, Daniel Dajun School of Data Science City University of Hong Kong Hong Kong Hong Kong The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Shenzhen China Department of Management Sciences College of Business City University of Hong Kong Hong Kong Hong Kong Department of Physics Boston University BostonMA02215 United States

The COVID-19 pandemic has caused a dramatic surge in demand for personal protective equipment (PPE) worldwide. Many countries have imposed export restrictions on PPE to ensure the sufficient domestic supply. The surging demand and export restrictions cause shortage contagions on the global PPE trade network. Here, we develop an integrated network model, which integrates a metapopulation model and a threshold model, to investigate the shortage contagion patterns. The metapopulation model captures disease contagion across countries. The threshold model captures the shortage contagion on the global PPE trade network. Results show that, the shortage contagion patterns are mainly decided by top exporters. Export restrictions exacerbate the shortages of PPE and cause the shortage contagion to transmit even faster than the disease contagion. Besides, export restrictions lead to ineffective and inefficient allocation of PPE around the world, which has no benefits for the world to fight against the pandemic. Copyright © 2021, The Authors. All rights reserved.

关键词： Protective clothing

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