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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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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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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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Bio-inspired Modeling and Position control for Pneumatic Artificial Muscle

Bio-inspired Modeling and Position Control for Pneumatic Art...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Hang Fu Yang Liu Jiahao Chen School of Mechanical Engineering University of Science and Technology Beijing Beijing P. R. China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing P. R. China

ISBN: (数字)9781728176840

ISBN: (纸本)9781728176857

In this paper, the modeling and position control problem of a class of pneumatic artificial muscle (PAM) is investigated for the bio-inspired robotic manipulator. The system model of PAM is firstly developed based on experiment data identification. Then, the improved particle swarm optimization (PSO) control parameter tuning method is established for the effective position control of PAM. In particular, the concept of information entropy is used during the optimal procedure. In the end, the simulation results are given for demonstrating the effectiveness of the proposed design and control approach.

关键词： Simulation Position control Muscles Particle swarm optimization Information entropy Tuning Optimization

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Distributed Formation of Autonomous Underwater Vehicles with Unreliable Switching Topologies and Transmission Delays

Distributed Formation of Autonomous Underwater Vehicles with...

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Chinese control Conference (CCC)

作者： Chao Ma Wei Wu Yidao Ji Hang Fu School of Mechanical Engineering University of Science and Technology Beijing Beijing China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

This paper investigates the formation problem of autonomous underwater vehicles with unreliable switching communication topologies and time-varying transmission delays. More precisely, the switching topologies contains achievable and unachievable sub-topologies, which can better describe the practical underwater communication environment. By performing model transformation and constructing appropriate multiple Lyapunov-function method, sufficient conditions are established based on admissible edge-dependent average dwell time, such that the desired formation configuration can be achieved with transmission delays. Finally, an illustrative example is given at last to verify the effectiveness of the main results.

关键词： Topology Switches Delays Network topology Underwater autonomous vehicles Switched systems

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Heuristic rank selection with progressively searching tensor ring network

arXiv

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arXiv 2020年

作者： Li, Nannan Pan, Yu Chen, Yaran Ding, Zixiang Zhao, Dongbin Xu, Zenglin State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing101408 China Shenzhen China Pengcheng Lab Shenzhen China

Recently, Tensor Ring Networks (TRNs) have been applied in deep networks, achieving remarkable successes in compression ratio and accuracy. Although highly related to the performance of TRNs, rank selection is seldom studied in previous works and usually set to equal in experiments. Meanwhile, there is not any heuristic method to choose the rank, and an enumerating way to find appropriate rank is extremely time-consuming. Interestingly, we discover that part of the rank elements is sensitive and usually aggregate in a narrow region, namely an interest region. Therefore, based on the above phenomenon, we propose a novel progressive genetic algorithm named Progressively Searching Tensor Ring Network Search (PSTRN), which has the ability to find optimal rank precisely and efficiently. Through the evolutionary phase and progressive phase, PSTRN can converge to the interest region quickly and harvest good performance. Experimental results show that PSTRN can significantly reduce the complexity of seeking rank, compared with the enumerating method. Furthermore, our method is validated on public benchmarks like MNIST, CIFAR10/100, UCF11 and HMDB51, achieving the state-of-the-art performance. Copyright © 2020, The Authors. All rights reserved.

关键词： Image classification

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Position control of an Underwater Biomimetic Vehicle-Manipulator System via Reinforcement Learning

Position Control of an Underwater Biomimetic Vehicle-Manipul...

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Data Driven control and Learning systems (DDCLS)

作者： Ruichen Ma Yu Wang Zisen Gao Tianzi Zhao Rui Wang Shuo Wang Chao Zhou 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 Beijing Institute of Petrochemical Technology Beijing China Naval Research Academy Beijing China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

This paper addresses a position control method of an underwater biomimetic vehicle-manipulator system (UBVMS) through reinforcement learning. The system description of the UBVMS with undulating fins is given. Considering the force/torqu generated by undulating fins and hydrodynamic force/torqu, the dynamic model of this UBVMS is established. The position control problem is modeled into a continuous-state, continuous-action Markov decision process (MDP) with a deterministic state transition algorithm based on the dynamic model. To solve this MDP, a reinforcement learning method is presented, which is based on the deep deterministic policy gradient (DDPG) theorem. The simulations of the position control in 5 cases are shown in the end.

关键词： Robots Force Robot kinematics Position control Propellers Reinforcement learning Heuristic algorithms

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A comprehensive survey on image aesthetic quality assessment 18

A comprehensive survey on image aesthetic quality assessment

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18th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2019

作者： Yang, Hongtao Shi, Ping He, Saike Pan, Da Ying, Zefeng Lei, Ling College of Information Engineering Communication University of China Beijing China School of Electrical and Information Engineering Beijing Polytechnic College Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728108018

Image aesthetic quality assessment has demonstrated tremendous success in variety of application domains in recent years. This field has been growing so rapidly that various approaches have been proposed trying to solve this challenging problem. This report presents a comprehensive survey on image aesthetic quality assessment, mainly focus on the contributions and novelties of the existing approaches recently. In this work, we firstly illustrate datasets related to image aesthetics and investigate feature extractions. Then five different aesthetic tasks are reviewed, including aesthetic classification, aesthetic regression, aesthetic distribution, aesthetic factors and aesthetic description. In addition, we reviewed recent applications concerning image aesthetics. Finally, different evaluation criterions in different literatures are summarized. We hope the survey could serve as a comprehensive reference and be useful for those who are interested in exploiting image aesthetic for their research. © 2019 IEEE.

关键词： Surveys

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A grasping CNN with image segmentation for mobile manipulating robot

A grasping CNN with image segmentation for mobile manipulati...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Yu, Yingying Cao, Zhiqiang Liang, Shuang Liu, Zhicheng Yu, Junzhi Chen, Xuechao Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Intelligent Robotics Institute BIT Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing100081 China

ISBN: (纸本)9781728163215

This paper presents a grasping convolutional neural network with image segmentation for mobile manipulating robot. The proposed method is cascaded by a feature pyramid network FPN and a grasping network DrGNet. The FPN network combined with point cloud clustering is used to obtain the mask of the target object. Then, the grayscale map and the depth map corresponding to the target object are combined and sent to the DrGNet network for providing multi-scale images. On this basis, depthwise separable convolution is used for encoding. The results of encoders are refined according to the light-weight RefineNet as well as sSE, which can achieve a better grasp detection. The proposed method is verified by the experiments on mobile manipulating robot. © 2019 IEEE.

关键词： Image segmentation

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A two-level adaptive target recognition and tracking method based on vision for multi-robot system

A two-level adaptive target recognition and tracking method ...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Ren, Liang Cao, Zhiqiang Tan, Min Zhao, Peng Chen, Xuechao University of Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems CASIA Beijing China 21st Research Institute of China Electronics Technology Group Corporation Shanghai China BIT Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing China

ISBN: (纸本)9781728163215

The vision-based target recognition and tracking have received much attention in the field of robotics. Existing methods mainly focus on the vision perception of individual robot with a single view, however, the performance is susceptible to illumination and occlusion. Multi-robot collaborative perception provides a potential solution to deal with the limitation of single-view observation, however, the challenging of environmental adaptability for multi-robot collaborative decision still remains unsolved. To solve this problem, this paper proposes a two-level adaptive target recognition and tracking method based on vision for multi-robot system. The problem of multi-robot target recognition and tracking is solved under a two-level framework, which contains the features fusion level of individual robot and the cooperation level of multi-robot system. In the first level, the features measuring results that influence the visual perception of individual robot are fused, while the second level combines the voting of each robot together to determine the target for multi-robot system. Both the features measuring weights and robots voting weights are adaptively updated according to their evaluation, which lead to a beneficial result where the features and robots with higher accuracy play major roles in the first and second levels, respectively. Therefore, a good adaptability to the environments can be guaranteed. The experimental results show that the proposed approach can realize the coordination of multi-robot system in target recognition and tracking with an effective performance. © 2019 IEEE.

关键词： Multipurpose robots

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