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2024 IEEE International Conference on Real-Time Computing and robotics, RCAR 2024

作者： Wang, Zhiyang Wang, Qifeng Du, Liang Wang, Mingyuan Hu, Zhengtao Bao, Sheng Yuan, Jianjun Shanghai University Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai China Shanghai University Shanghai Robotics Institute Shanghai China Changshu New & Hi-Tech Industrial Development Zone China

ISBN: (纸本)9798350372601

With the expanding of pipeline applications and development in related technologies, there is a growing requirement for inside anti-corrosion of pipelines. Currently, there is relatively limited application of robots for large-diameter pipeline inside anti-corrosion, and the design of such robots often facing coupling issues between the locomotion capability and operation requirements. In this study, an axiomatic design method is employed to analyze the design of a pipeline inside anti-corrosion robot, and a decoupling method is proposed to separate the locomotion and the anti-corrosion mechanism. The robot design is implemented with the axiomatic method. Preliminary analysis using dynamic simulation demonstrates that the robot equipped with independently adjustable steering functions works more stably and effectively during anti-corrosion operations pipelines inside. © 2024 IEEE.

关键词： Machine design

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Spatio-Temporal Communication Compression in Distributed Prime-Dual Flows 63

Spatio-Temporal Communication Compression in Distributed Pri...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Ren, Zihao Wang, Lei Yuan, Deming Su, Hongye Shi, Guodong Zhejiang University College of Control Science and Engineering China Nanjing University of Science and Technology School of Automation China University of Sydney Australia Centre for Field Robotics Australia

ISBN: (纸本)9798350316339

In this paper, we study distributed prime-dual flows for multi-agent optimization with spatio-temporal compressions. The central aim of multi-agent optimization is for a network of agents to collaboratively solve a system-level optimization problem with local objective functions and node-to-node communication by distributed algorithms. The scalability of such algorithms crucially depends on the complexity of the communication messages, and a number of communication compressors for distributed optimization have recently been proposed in the literature. First of all, we introduce a general spatio-temporal compressor characterized by the stability of the resulting dynamical system along the vector field of the compressor. We show that several important distributed optimization compressors such as the greedy sparsifier, the uniform quantizer, and the scalarizer all fall into the category of this spatio-temporal compressor. Next, we propose two distributed prime-dual flows with the spatio-temporal compressors being applied to local node states and local error states, respectively, and prove (exponential) convergence of the node trajectories to the global optimizer for (strongly) convex cost functions. Finally, a few numerical examples are present to illustrate our theoretical results. © 2024 IEEE.

关键词： Cost functions

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Evaluation of Muscle Activation Reaction on Vertical Climbing 9

Evaluation of Muscle Activation Reaction on Vertical Climbin...

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9th International Conference on Electrical engineering, Control and robotics, EECR 2023

作者： Wang, Li Pang, Muye Xiang, Kui Luo, Jing Tang, Biwei Lu, Baizhong Wuhan University of Technology School of Automation Wuhan China Wuhan Guozhi Robotics System Engineering Co. Ltd. China

ISBN: (纸本)9781665491204

Vertical climbing is a common movement in industrial field, which requires coordination of entire body joints and is a high-risk task for workers. Exoskeletons have the ability to assist wear to perform vertical climbing and reduce the risk of failed motion. However, raw studies have paid attention on exoskeleton-assisted vertical climbing. In order to develop vertical climbing assistance strategy for exoskeleton system, it is essential to obtain the inherent control strategy of human subject for this movement. Muscle activations, which can be observed by surface Electromyography (sEMG) signals, are able to present muscle activity or human potential control intent. Therefore, we adopt muscle synergy technology to analyze human vertical climbing movement. Firstly, the whole process is divided into four phases according to the movement data and sEMG data collected in experiment. Then, the preprocessed signals were decomposed using a non-negative matrix factorization (NNMF) algorithm. Finally, four muscle synergistic responses are extracted by variance accounted for (VAF) approach. The results of the experiments showed that the subjects' muscle synergy between the different phases was not highly correlated. The final finding may indicate that during vertical climbing, human beings change muscle activation patterns to adapt to the impacts from body stability and to realize vertical climbing. © 2023 IEEE.

关键词： Non-negative matrix factorization

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Disturbance Observation and Control of Operational Unmanned Aerial Vehicles

Disturbance Observation and Control of Operational Unmanned ...

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2023 IEEE International Conference on Unmanned Systems, ICUS 2023

作者： Yao, Guanyu Yang, Liying Chang, Yanchun He, Yuqing School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China Shenyang Institute of Automation State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350316308

UAVs are used widely in all works and life, and their operation forms and application scenarios are more complex than ever before. In order to deal with various disturbances faced by operational UAVs in application scenarios and achieve stable control, a disturbance observation and compensation structure combining linear extended state observer and sliding mode controller is proposed to achieve stable control of operational UAVs. Firstly, the typical operational UAV is taken as the research object, and the kinematics and dynamics models are established. Then, a linear extended state observer is designed to estimate the environment and body disturbances, and the sliding mode control method is combined to control the system. Finally, the effectiveness of the designed control method is verified through simulation. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Geometric design of a kirigami gripper with form-enclosing grasping mode

Geometric design of a kirigami gripper with form-enclosing g...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Hu, Bingyan Du, Liang Wang, Mingyuan Bao, Sheng Yuan, Jianjun Ma, Shugen Shanghai University Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai200444 China Shanghai University Shanghai Robotics Institute Shanghai China Ritsumeikan University Department of Robotics Shiga Japan

ISBN: (纸本)9798350325706

Although various grasp strategies have been proposed in soft gripper area, form-enclosing grasping mode always plays a marginal role because of the challenges to calculate the deformations of soft materials. In this study, we propose a easy-to-make kirigami gripper and a geometric optimization method to obtain the fingers boundary shape that achieves a complete form-enclosing grasping after bending. We used a FEM model to represent the finger shape and calculated the finger boundary, and then used a iterative method to find the best finger shape that generates the form-enclosing grasping result. The optimization method is based on the minimum energy rule, and has the advantages of being computationally efficient and being universal for optimizing the boundary of gripper with form-enclosing grasping mode. The effectiveness of the proposed method was validated by ANSYS simulation and practical experimental results. Moreover, an objective functions and multiple geometric constraints were derived to quantitatively evaluate the gripper designs. © 2023 IEEE.

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Traffic Police Gesture Command Recognition Based on Convolutional Neural Network AlexNet 2

Traffic Police Gesture Command Recognition Based on Convolut...

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2nd International Conference on Signal Processing and Intelligent Computing, SPIC 2024

作者： Qin, Lijuan Wang, Shiyi Shenyang Ligong University School of Information Science and Engineering Shenyang China Chinese Academy of Science State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang China

ISBN: (纸本)9798350368888

Traffic police gesture signal recognition is of great significance in traffic management and urban intelligent transportation system, this paper researches the automatic recognition technology of traffic police command gesture signal based on the deep learning method, in the process of model training, the training set is used to train AlexNet, and the model is evaluated by the test set. The experimental results show that the model achieves high accuracy in the recognition of traffic police gesture signals. Finally, based on the trained model, a traffic police gesture signal recognition system is designed in MATLAB platform to realize the gesture signal recognition function on local images. The system can be used as a practical application tool for gesture signal recognition in traffic management, providing support for improving the efficiency and safety of urban traffic command. © 2024 IEEE.

关键词： Deep learning

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Research on Pear Detection Algorithm Based on Improved YOLOv7 24

Research on Pear Detection Algorithm Based on Improved YOLOv...

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4th International Joint Conference on robotics and Artificial Intelligence, JCRAI 2024

作者： Hu, Xiaomei Zhao, Longjie Tong, Shanggao Chen, Yi The Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai China Shanghai Triowin Intelligent Machinery Co. Ltd. Shanghai China

ISBN: (纸本)9798400710100

In pear-picking, the method of pear detection directly affects the accuracy and efficiency of the picking process. To address the issue of low detection accuracy in orchards, this paper proposes the ViT-YOLOv7 pear detection model. First, a backbone network based on the Vision Transformer is designed to extract features of the fruits in complex environments using convolution and self-attention mechanisms. Next, a lightweight feature fusion network is constructed by introducing partial convolution to replace traditional convolution operations. Finally, to address the issues of misidentification and missed detection caused by fruit occlusion, a decoupled detection head is designed, and a no-anchor strategy is adopted for fruit detection. Experimental results show that compared to YOLOv7-Tiny, the ViT-YOLOv7 model can accurately identify and locate pears with high efficiency, ensuring that picking operations are performed quickly and precisely, thereby improving overall picking efficiency. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Pear Detection

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Quadruped Reinforcement Learning without Explicit State Estimation

Quadruped Reinforcement Learning without Explicit State Esti...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Li, Qikai Dong, Guiyu Qin, Ripeng Chen, Jiawei Xu, Kun Ding, Xilun Robotics Institute Beihang University School of Mechanical Engineering and Automation Beijing100191 China

ISBN: (纸本)9781665481090

Reinforcement learning is a promising approach to developing legged robot locomotion controllers. The gen-eral process of development is: large-scale training in the virtual simulation environment to obtain reliable control policy network, and then the policy network is deployed to real legged robot. In the training procedure, a complete robot state increases the speed of training and the stability of policy. The robot's states like body velocities are easily available in simulation training, but they are difficult to obtain in the real robot, hence specifically designed robot state estimators are needed. However, the development of state estimators requires expert knowledge related to control theory and robotics, limiting the direct application of reinforcement learning to robots. To take advantage of the end-to-end mapping of artificial neural networks, we simplified the existing reinforcement learning process for quadruped robots and propose a training method based on curriculum learning in this work. The proposed method can produce a reliable policy that does not require robot state estimator and only take raw sensors data. The feasibility of the proposed method is verified in simulations and real quadrupedal robot. Video of the quadrupedal robot is available at ***/watch?v=-iho4KIlEPw. © 2022 IEEE.

关键词： Robots

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T3SFNet: A Tuned Topological Temporal-Spatial Fusion Network for Motor Imagery with Rehabilitation Exoskeleton 7th

T3SFNet: A Tuned Topological Temporal-Spatial Fusion Network...

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7th International Conference on Cognitive Systems and Information Processing, ICCSIP 2022

作者： Shi, Kecheng Mu, Fengjun Zou, Chaobin Qin, Yizhe Peng, Zhinan Huang, Rui Cheng, Hong Center for Robotics School of Automation Engineering University of Electronic Science and Technology of China Chengdu China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9789819906161

In recent years, motor imagery-based brain computer interfaces (MI-BCI) combined with exoskeleton robot has proved to be a promising method for spinal cord injury (SCI) rehabilitation training. The core of BCI is to achieve a high accurate movement prediction based on patient’s MI. The inconsistent response frequency of MI in different trials and subjects leads to the limited performance accuracy of MI movement prediction method for the single subject. The individual differences in the activation patterns of MI brain regions bring a greater challenge to the generalization ability of the method. According to the MI mechanism, this paper proposes a graph-based tuned topological temporal-spatial fusion network (T3SFNet) for MI electroencephalography (MI-EEG) limb movement prediction. The proposed method designs a learnable EEG tuning mechanism to fuse and enhance the subject’s MI response band data, and then uses a channel node-based graph convolutional network and a temporal-spatial fusion convolutional network to extract the topological features and spatiotemporal coupling features of the fused band data respectively. We evaluate the proposed approach on two MI datasets and show that our method outperforms state-of-the-art methods in both within-subject and cross-subject situations. Furthermore, our method shows surprising results on the small-sample migration test, reaching the prediction baseline with only of the data sample size. Ablation experiments of the model demonstrate the effectiveness and necessity of the proposed framework. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electroencephalography

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Submegahertz Nucleation of Plasmonic Vapor Microbubbles near a Solid Vertical Boundary

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Physical Review Letters 2024年第6期133卷 064001-064001页

作者： Fulong Wang (王福龙) Zhibin Hu Binglin Zeng Chenliang Xia Lihua Dong Huimin Wang Lijun Yang Yuliang Wang (王玉亮) Robotics Institute School of Mechanical Engineering and Automation National Center for Materials Service Safety School of Astronautics Ningbo Institute of Technology

Laser triggered and photothermally induced vapor bubbles have emerged as promising approaches to facilitate optomechanical energy conversion for numerous applications in microfluidics and nanofluidics. Here, we report an observation of spontaneously triggered periodic nucleation of plasmonic vapor bubbles near a rigid sidewall with readily tuned nucleation frequency from 0.8 kHz to over 200 kHz. The detailed collapsing process of the vapor bubbles was experimentally and numerically investigated. We find that the lateral migration of residual bubbles toward the sidewall refreshes the laser spot area, terminates the subsequent steady bubble growth, and leads to the repeatable bubble nucleation. A mathematic model regarding the Kelvin impulses was derived. It shows that the competition between the rigid boundary induced Bjerknes force and laser irradiation caused thermal Marangoni force on collapsing bubbles governs the process. The model also leads to a criterion of γζ<0.34 for repeatable bubble nucleation, where γ is the normalized distance and ζ thermal Marangoni coefficient. This study demonstrates nucleation of violent vapor bubbles at extreme high frequencies, providing an approach to remotely realize strong localized flows in microfluidics and nanofluidics.

关键词： Bubble dynamics Drop or bubble formation Drops & bubbles Laser-induced cavitation Lasers Metals Microfluidic devices Nanofluidic devices Nanoparticles Water

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