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Preliminary Study on 3D CAD Model Retrieval 1

12th International Workshop of Advanced Manufacturing and automation, IWAMA 2022

作者： Zhou, Chuanhong Chen, Xi Liu, Haifeng School of Automation and Mechanical Engineering Shanghai University Shanghai200072 China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai200072 China

ISBN: (数字)9789811993381

ISBN: (纸本)9789811993374

With the development of manufacturing industry and the popularity of 3D CAD software, 3D CAD model data is exploding. An effective model retrieval method can help practitioners in the mechanical industry to find the parts they need from the parts library more quickly and accurately. In this paper, a new retrieval method of 3D CAD models based on 2D views is proposed. In order to improve the 2D projection effect, we improve a frame line extraction algorithm for 3D CAD models based on the existing projection methods. CaffeNet convolutional neural network is used to implement the classification of views. Through the local multi-scale GALIF feature extraction algorithm and the feature bag algorithm, the feature vector extraction of the 2D projected view is *** retrieving the model through the 2D view, the feature vector of that view is extracted and the distance is calculated with the feature vectors of all 2D projected views in the database. Finally, the model belonging to the 2D projected view with the smallest distance is returned to the user and the retrieval is completed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Extraction

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Steering Through Waters: Exploring Turning Control Techniques for Soft Underwater Snake Robots

Steering Through Waters: Exploring Turning Control Technique...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Shi, Hang Cui, Wenlong Meng, Yali Wang, Shuting Xie, Yangmin Shanghai University Department of Automation Shanghai200444 China Shanghai University Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai200444 China

ISBN: (纸本)9798350325706

Taking inspiration from the two turning mechanisms exhibited by biological snakes, this paper presents two turning methods for soft underwater snake robots: head steering and unbalanced gait steering. The structural design, driving principles, and turning motion model of the proposed snake are introduced. Through experimental validations under the same conditions, the results demonstrate the turning feasibility of two steering methods in underwater snake robots, revealing superior turning capabilities of head steering compared to unbalanced gait steering utilized by conventional ground-based snake robots. This paper pioneers head-turning investigation in underwater snake robots and offers insights for future applications involving the agile maneuvering of underwater robots in aquatic environments. © 2023 IEEE.

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Assistive robots for Beijing Winter Paralympic torch relay: Accessible technologies to restore human functionality

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The Innovation 2024年第1期5卷 19-20页

作者： Bi Zhang Mei Shuai Bicheng Han Shuo Li Lianqing Liu Xingang Zhao State Key Laboratory of Robotics Shenyang Institute of AutomationCASShenyang 110016China Institutes for Robotics and Intelligent Manufacturing CASShenyang 110169China Department of Biomedical Engineering Beihang UniversityBeijing 100191China Beijing AI-Robotics Technology Co. Ltd.Beijing 100176China Zhejiang BrainCo Technology Co. Ltd.Hangzhou 311121China

The success of the Beijing Winter Olympics and Paralympics epitomized the vision of a community with a shared future for *** robots and artificial intelligence technologies were used in various games and events,such as assisting in parades,logistics,and security *** integration of unmanned robotic systems into torch relays was one of the highlights of the Winter Olympics.

关键词： Winter Access artificial

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Industrial Wireless Control Networks:From WIA to the Future

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Engineering 2022年第1期8卷 18-24页

作者： Haibin Yu Peng Zeng Chi Xu State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China

*** Industrial automation is undergoing a significant innovation as information,communication,and operation technologies are deeply integrating with each *** this trend,industrial wireless control networks(IWCNs)are becoming increasingly attractive to industrial automation since they can help speed up production efficiency,reduce cost,enhance safety,and finally realize intelligent manufacturing[1].

关键词： attractive integrating becoming

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Real-Time Detection of Surface Floating Garbage Based on Improved YOLOv7 16th

Real-Time Detection of Surface Floating Garbage Based on Imp...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Li, Liang Li, Yiping Jiang, Zhibin Wang, Hailin State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China Key Laboratory of Marine Robotics Liaoning Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9789819964796

Cleaning up surface floating garbage is of great significance to improve the ecological environment of the waters, of which the detection of surface floating garbage is a crucial step. It is difficult to distinguish the background and garbage and solve the problem of small targets of the existing target detection methods. Therefore, an improved YOLOv7 network is proposed to achieve efficient and high-precision detection of surface floating garbage. The newly proposed DS method is applied to original YOLOv7 network for multi-scale feature fusion. Meanwhile, CBAM attention mechanism module is applied to network backbone to improve detection precision. The public data set FLOW is used to validate the method in this paper. The simulation test results show that the proposed method significantly improves the detection precision without reducing too much detection speed, which proves the effectiveness of the proposed method. Finally, the proposed method is deployed to an NVIDIA Jetson device and applied to real-time surface floating garbage detection, which proves its practicability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Deep learning

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Improved Detection of Transmission Tower Equipment Using YOLOv7 with Saliency Data Augmentation 5

Improved Detection of Transmission Tower Equipment Using YOL...

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5th International Conference on Clean Energy and Electric Power Engineering, ICCEPE 2024

作者： Xu, Yingying Song, Chunhe Sun, Yong Yu, Shimao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9798350390315

Transmission towers are critical infrastructure for power transmission, and the reliable operation of their equipment is essential to ensure electricity supply. However, the detection of transmission tower equipment faces challenges such as target overlap, large variations in size, small targets, and class imbalance due to the characteristics of the equipment. To tackle the identified issues, this study introduces a method based on YOLOv7 for the detection of transmission tower components, utilizing saliency-based data augmentation. Initially, an approach focusing on importance is employed to augment the sample size in categories with limited numbers, thereby enhancing the effectiveness of detection. Secondly, an adaptive adjustment module is introduced into the multi-head self-attention mechanism to dynamically adjust attention allocation based on the actual size of the targets and integrate contextual information, thus better handling targets with large size variations and overlaps. Finally, incorporating dynamic convolution within the backbone network significantly improves the ability to extract features from small objects. The outcomes of the experiments confirm the efficiency of the suggested approach in the smart surveillance of devices within intricate transmission settings, offering a reliable solution for maintaining power supply dependability. © 2024 IEEE.

关键词： Critical infrastructures

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Mechanical Properties Inside Origami-Inspired Structures: An Overview

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Applied Mechanics Reviews 2025年第1期77卷 011001页

作者： Yan, Peng Huang, Hailin Meloni, Marco Li, Bing Cai, Jianguo Department of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518052 China Harbin Institute of Technology Shenzhen518052 China Key Laboratory of C & PC Structures of Ministry of Education National Prestress Engineering Research Center Southeast University Nanjing211189 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Harbin Institute of Technology Shenzhen518052 China Key University Laboratory of Mechanism Machine Theory and Intelligent Unmanned Systems of Guangdong Habin Institute of Technology Shenzhen518052 China

In recent decades, origami has transitioned from a traditional art form into a systematic field of scientific inquiry, characterized by attributes such as high foldability, lightweight frameworks, diverse deformation modes, and limited degrees-of-freedom. Despite the abundant literature on smart materials, actuation methods, design principles, and manufacturing techniques, comprehensive reviews focusing on the mechanical properties of origami-inspired structures are relatively rare and unsystematic. This review aims to fill this void by analyzing and summarizing the significant studies conducted on the mechanical properties of origami-inspired structures from 2013 to 2023. We begin with an overview that includes essential definitions of origami, classical origami patterns, and their associated tessellated or stacked structures. Following this, we delve into the principal dynamic modeling method for origami and conduct an in-depth analysis of the key mechanical properties of origami-inspired structures. These properties include tunable stiffness, bistability and multistability, metamechanical properties demonstrated by origami-based metamaterials, and bio-inspired mechanical properties. Finally, we conclude with a comprehensive summary that discusses the current challenges and future directions in the field of origami-inspired structures. Our review provides a thorough synthesis of both the mechanical properties and practical applications of origami-inspired structures, aiming to serve as a reference and stimulate further research. © 2025 American Society of Mechanical Engineers (ASME). All rights reserved.

关键词： Degrees of freedom (mechanics)

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A Novel Transparent Object Detection Approach Based on Segmentation-Depth Reconstruction

A Novel Transparent Object Detection Approach Based on Segme...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Li, Zhonglin Luo, Yang Jiang, Yunxiang Zhang, Bi Song, Guoli Zhao, Xingang Zhao, Yiwen Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China Liaoning University Shenyang110036 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics China

ISBN: (纸本)9798350327182

Detecting transparent objects using visual sensors has always been a challenge in the industry. In this paper, a pipeline for depth completion of transparent objects is proposed. The first stage utilizes the input RGB image for semantic segmentation, obtaining the segmentation map of the transparent object. The second stage predicts surface normals and performs boundary detection. The third stage combines the results obtained in the first two stages to complete the depth reconstruction of the transparent object. In addition, in the first stage, a semantic segmentation method for transparent objects is proposed, and boundary optimization is performed on the segmentation results to obtain more refined segmentation results. Experiments demonstrate the effectiveness and precision of the proposed approach. © 2023 IEEE.

关键词： Semantic Segmentation

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Design of Control Method for Pointing Control Mechanism of Large Space Flexible Antenna

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Journal of Harbin Institute of Technology(New series) 2024年

作者： Fuchenglong Zhao Junlin Li Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Chinese Academy of Sciences

An innovative design method is outlined in this paper for the pointing control mechanism of large space flexible antennas. This method focuses on enhancing the accuracy and stability that are crucial for large spacecraft applications,such as space solar power stations. Utilizing potential energy function analysis,the dynamics of the antenna are modeled,treating it as an equivalent n-joint robotic arm. This approach simulates the rigid-flexible coupling effect through joint angle manipulations. The proposed HJI(Hamilton-Jacobi-Inequality)sliding mode robust control integrates HJI principle,dissipative system theory,and sliding mode control,offering improved pointing accuracy and *** results underscore the superiority of HJI sliding mode robust control over traditional PD(proportionalderivative)control in initial response,precision,and control smoothness,albeit at the cost of higher control torque requirements. This research underscores the potential of HJI sliding mode robust control in facilitating precise pointing control for future large space structures,enabling efficient space missions and reliable energy transmission.

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Multi-Agent Distributed Cooperation Decision Making Based on Incomplete Information Prediction 41

Multi-Agent Distributed Cooperation Decision Making Based on...

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第41届中国控制会议

作者： Hongda Zhang Decai Li Yuqing He State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences University of Chinese Academy of Sciences

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In order to solve the problem of difficulty in learning cooperative strategies and decision-making of multi-agent caused by the incomplete information and the inability to guarantee stable communication in the partial observable multi-agent adversarial environment,inspired by the learning and reasoning functions of the human cerebral cortex through memory,a new multi-agent distributed cooperative strategy learning method based on incomplete information prediction in a partially observable adversarial environment is *** the use of historical memory and current observation information,support vector regression(S VR) is used to predict invisible information in the environment,and the prediction information o f the unobserved part and the observed information are fused as the basis for cooperative strategy learning and ***,through the use of decentralized multi-agent reinforcement learning method for cooperative strategy learning,the decision model of each agent in the team is *** method is verified by multi-agent cooperative strategy learning and decision-making in a typical partial observable adversarial *** results show that this method can significantly improve the level of multi-agent cooperative decision-making while ensuring high prediction accuracy for unobserved parts.

关键词： Multi-agent cooperation partial observable information prediction distributed cooperative decision-making adversarial environment

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