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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Song, Bochao Ge, Weizong Wang, Chang Wang, Yanan He, Mingyuan Han, Meng Chen, Jiawei Xu, Kun Ding, Xilun Robotics Institute School of Mechanical Engineering and Automation Beihang University Beijing100191 China

ISBN: (纸本)9781665481090

This paper presents a novel real-time 6-DoF object pose estimation framework leveraging template iteration combined with RGB information. By integrating object detection, template matching, and pose refinement techniques, the proposed approach constructs a pose estimation network characterized by strong generalization capabilities, real-time performance, and high accuracy. Traditional RGB-based 6-DoF pose estimation methods typically rely on computing the residual between rendered images of coarsely estimated poses and the input query images. However, due to the lack of sufficient 3D structural information, these methods often exhibit poor generalization to unseen objects. In this paper, we propose a 3D feature set-based pose iterative network that eliminates the need for rendering images on the input pose, thus enabling pose estimation without CAD models. Initially, object detection algorithms are employed to identify objects within the scene, followed by template matching to determine the initial pose. Subsequently, the pose iterative network is designed to refine the initial pose, achieving higher estimation accuracy. To ensure real-time performance, model pruning techniques are utilized to compress the pose iterative network, significantly reducing computational complexity while maintaining estimation accuracy. Experimental results demonstrate that our method exhibits robust generalization capability, real-time performance, and high accuracy across various scenarios, providing an efficient and reliable pose estimation solution for robotic vision and automation. © 2024 IEEE.

关键词： Template matching

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Dynamic Analysis and Parametric Optimization of Telescopic Tubular Mast Applied on Solar Sail

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Chinese Journal of Mechanical engineering 2023年第2期36卷 279-290页

作者： Chenyang Ji Jinguo Liu Chenchen Wu Pengyuan Zhao Keli Chen State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of ScienceShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China School of Mechanical Engineering and Automation Northeastern UniversityShenyang 110819China University of Chinese Academy of Sciences Beijing 100049China

Large-scale solar sails can provide power to spacecraft for deep space exploration.A new type of telescopic tubular mast(TTM)driven by a bistable carbon fiber-reinforced polymer tube was designed in this study to solve the problem of contact between the sail membrane and the spacecraft under light *** with the traditional TTM,it has a small size,light weight,high extension ratio,and simple *** anti-blossoming and self-unlocking structure of the proposed TTM was *** aimed to simplify the TTM with a complex structure into a beam model with equal linear mass density,and the simulation results showed good *** dynamic equation was derived based on the equivalent model,and the effects of different factors on the vibration characteristics of the TTM were *** performance parameters were optimized based on a multiobjective genetic algorithm,and prototype production and load experiments were *** results show that the advantages of the new TTM can complete the deployment of large-scale solar sails,which is valuable for future deep space exploration.

关键词： Telescopic tubular mast Solar sail Genetic algorithm Modal analysis Optimization

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Examining the Impact of Metallurgical and Optimised Machining Parameters on Inconel 713C Superalloy Using the Taguchi Technique

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Journal of The Institution of Engineers (India): Series D 2024年 1-11页

作者： Suryawanshi, Vinayak P. Deshmukh, Prashant D. Chapke, Yashwant Department of Mechanical Engineering Datta Meghe College of Engineering Airoli Navi Mumbai400708 India Department of Automation & amp Robotics JSPM’S Rajarshi Shahu College of Engineering Maharashtra Pune India

This study examined the metallurgical properties of Inconel 713C superalloy and the impact of utilising the Taguchi technique to optimise machining settings. The cutting tool was a strong carbide substance coated with WC-TiAlN. The impact of cutting force parameters and surface roughness was observed on the Inconel 713C superalloy. The goal of using Taguchi was to maximise the limitations for spinning Inconel 713C alloy at high speeds. An orthogonal array of L27 was used. In order to assess the microstructural and compositional changes, metallurgical tests were conducted. Compared to tool inserts that have not been treated, the EDS scans showed that there is less material deposition on the workpiece. As a result, there was reduced cutting force, friction, and a homogeneous distribution of temperature, which produced a superior surface finish. The workpiece's higher amount of iron, aluminium, and other components, along with the untreated tool, caused localised heating and increased friction. This, in turn, increased cutting force and impacted surface roughness. According to the numerical analysis, the feed rate accounted for up to 95% of the total influence and had the greatest impact on machining performance. © The Institution of Engineers (India) 2024.

关键词： Superalloys

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SGT-Net: A Transformer-Based Stratified Graph Convolutional Network for 3D Point Cloud Semantic Segmentation

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Computers, Materials & Continua 2024年第6期79卷 4471-4489页

作者： Suyi Liu Jianning Chi Chengdong Wu Fang Xu Xiaosheng Yu Faculty of Robot Science and Engineering Northeastern UniversityShenyang110167China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang110169China SIASUN Robot&Automation Co. Ltd.Shenyang110169China

In recent years,semantic segmentation on 3D point cloud data has attracted much *** 2D images where pixels distribute regularly in the image domain,3D point clouds in non-Euclidean space are irregular and inherently ***,it is very difficult to extract long-range contexts and effectively aggregate local features for semantic segmentation in 3D point cloud *** current methods either focus on local feature aggregation or long-range context dependency,but fail to directly establish a global-local feature extractor to complete the point cloud semantic segmentation *** this paper,we propose a Transformer-based stratified graph convolutional network(SGT-Net),which enlarges the effective receptive field and builds direct long-range ***,we first propose a novel dense-sparse sampling strategy that provides dense local vertices and sparse long-distance vertices for subsequent graph convolutional network(GCN).Secondly,we propose a multi-key self-attention mechanism based on the Transformer to further weight augmentation for crucial neighboring relationships and enlarge the effective receptive *** addition,to further improve the efficiency of the network,we propose a similarity measurement module to determine whether the neighborhood near the center point is *** demonstrate the validity and superiority of our method on the S3DIS and ShapeNet *** ablation experiments and segmentation visualization,we verify that the SGT model can improve the performance of the point cloud semantic segmentation.

关键词： 3D point cloud semantic segmentation long-range contexts global-local feature graph convolutional network dense-sparse sampling strategy

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Development of a cable-driven redundant space manipulator with large bending angle by combining quaternion joints and segmented coupled linkages mechanism

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Chinese Journal of Aeronautics 2023年第11期36卷 483-499页

作者： Taiwei YANG Jian HUANG Wenfu XU Ke SHAO Bin LIANG School of Mechanical Engineering and Automation Harbin Institute of TechnologyShenzhen 518055China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China Department of Automation Tsinghua UniversityBeijing 100854China

A cable-driven redundant manipulator has significant potential in confined space applications, such as environmental exploration, equipment monitoring, or maintenance. A traditional design requires 3N driving motors/cables to supply 2N degrees of freedom(DOF) movement *** number of motors is 1.5 times that of the joints’ DOF, increasing the hardware cost and the complexity of the kinematics, dynamics, and control. This study develops a novel redundant space manipulator with decoupled cable-driven joints and segmented linkages. It is a 1680 mm continuum manipulator with eight DOF, consisting of four segmented linkages driven by eight motors/pairs of cables. Each segment has two equivalent DOF, which are realized by four quaternion joints synchronously driven by two linkage cables. The linkage cables of adjacent joints are symmetrically decoupled and offset at 180°. This design allows equal-angle movement of all the joints of each segment. Moreover, each decoupling driving mechanism is designed based on a pulley block composed of two fixed and movable pulleys. The two movable pulleys realize the opposite but equidistant motions of the two driving cables, i.e., pulling and loosening, assuring symmetrical movements of the two driving cables of each segment. Consequently, the equivalent 2N-DOF joints are driven only by 2N motors, significantly reducing the hardware cost and simplifying the mapping relationship between the motor angle/cable length and the joint angle. Furthermore, the bending range of each segment could reach 360°, which is three times that of a traditional design. Finally, a prototype has been developed and experimented with to verify the performance of the proposed mechanism and the corresponding algorithms.

关键词： Cable-driven Mechanism design Redundant manipulators Segmented linkages Kinematics

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An Untethered Miniature Soft Jumping Robot Inspired by Quadrupeds

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Journal of Bionic engineering 2023年第4期20卷 1467-1480页

作者： Tianliang Zhong Fanan Wei Zhushan Zhai Wenguang Yang School of Mechanical Engineering and Automation Fuzhou UniversityFuzhou350108China School of Electromechanical and Automotive Engineering Yantai UniversityYantai264005ShandongChina State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang110016LiaoningChina

In recent years,designing a soft robot that can jump continuously and quickly explore in a narrow space has been a hot research *** the continuous efforts of researchers,many types of actuators have been developed and successfully employed to actuate the rapid locomotion of soft *** these mechanisms have enabled soft robots with excellent movement capabilities,they largely rely on external energy supply cables,which greatly limits their ***,it is still a big challenge to realize the unconstrained movement of the soft robot and the flexible adjustment of the movement direction in a narrow ***,a wireless magnetically controlled soft jumping robot with single-leg is proposed,which can achieve continuous and rapid jumping ***'s more interesting is that by changing the frequency and waveform of the control signal,this soft robot can easily switch between forward and backward *** motion direction switching function enables the magnetically controlled soft robot to return to the initial position without adjusting the direction when it completes the operation in a narrow pipe or takes the wrong path,which greatly improves the motion efficiency of the soft jumping robot and broadens its application field.

关键词： Wireless Magnetically controlled Soft robot Jumping Bidirectional motion

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A Differential Privacy Federated Learning Scheme Based on Adaptive Gaussian Noise

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Computer Modeling in engineering & Sciences 2024年第2期138卷 1679-1694页

作者： Sanxiu Jiao Lecai Cai Xinjie Wang Kui Cheng Xiang Gao College of Automation and Information Engineering Sichuan University of Science and EngineeringYibin644000China Sanjiang Research Institute of Artificial Intelligence and Robotics Yibin UniversityYibin644000China College of Mechanical Engineering Sichuan University of Science and EngineeringYibin644000China

As a distributed machine learning method,federated learning(FL)has the advantage of naturally protecting data *** keeps data locally and trains local models through local data to protect the privacy of local *** federated learning method effectively solves the problem of artificial Smart data islands and privacy protection ***,existing research shows that attackersmay still steal user information by analyzing the parameters in the federated learning training process and the aggregation parameters on the server *** solve this problem,differential privacy(DP)techniques are widely used for privacy protection in federated ***,adding Gaussian noise perturbations to the data degrades the model learning *** address these issues,this paper proposes a differential privacy federated learning scheme based on adaptive Gaussian noise(DPFL-AGN).To protect the data privacy and security of the federated learning training process,adaptive Gaussian noise is specifically added in the training process to hide the real parameters uploaded by the *** addition,this paper proposes an adaptive noise reduction *** the convergence of the model,the Gaussian noise in the later stage of the federated learning training process is reduced *** paper conducts a series of simulation experiments on realMNIST and CIFAR-10 datasets,and the results show that the DPFL-AGN algorithmperforms better compared to the other algorithms.

关键词： Differential privacy federated learning deep learning data privacy

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Promoting Smart Industry with a Smart Monodzukuri Support Team in Thailand: A Case Study 4th

Promoting Smart Industry with a Smart Monodzukuri Support Te...

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4th International Conference on Experimental and Computational Mechanics in engineering, ICECME 2022

作者： Sriputtha, Noppadol Robotics and Lean Automation Engineering Faculty of Engineering Thai-Nichi Institute of Technology Suanluang Bangkok10250 Thailand

ISBN: (纸本)9789819974948

This work aimed to promote improvement of manufacturing through adopting smart manufacturing in Thailand. As the manufacturing industry in Thailand moves toward Industry 4.0, many SMEs are struggling to start up and invest. To help them, the Thai and Japanese governments are collaborating to provide a Smart Monodzukuri support team to assist SMEs to have more skills and be more competitive. This team will learn techniques to implement Japan's Industrial Value Chain Initiative (IVI), an organization that uses cyber-physical manufacturing, and encourages all companies to take part in a "small start" initiative. This work provides a case study using an auto parts manufacturing company. We describe how a Smart Monodzukuri team could collaborate with this company's staff following the IVI guidelines. The results show that by using the IVI idea, the team could incorporate cyber-physical manufacturing with few difficulties and low investment. This is the first simple and feasible step toward Industry 4.0 for SMEs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Industry 4.0

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CTPU Based MetaMetarial Behaviour as a Soft Strain Sensor

CTPU Based MetaMetarial Behaviour as a Soft Strain Sensor

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2025 IEEE International Conference on Mechatronics, ICM 2025

作者： Mutlu, Rahim Asghar, Umar Odriscoll, Ciara Yildirim, Tanju Southern Cross University Faculty of Science and Engineering Lismore Australia School of Engineering University of Wollongong in Dubai Robotics and Automation Research Group United Arab Emirates School of Engineering University of Wollongong in Dubai Robotics and Automation Research Group Dubai United Arab Emirates

ISBN: (纸本)9798331533892

The surge in flexible and wearable electronics, fueled by advancements in smart technologies and growing market demand, has highlighted the importance of auxetic sensors for applications in healthcare, medical rehabilitation, soft robotics, and human-machine interfaces. For widespread adoption, these sensors must offer high sensitivity, substantial stretchability, and long-term durability. This study explores the possibilities of realizing such wearable soft sensors based on conductive thermoplastic polyurethane (cTPU) 3D printing enhanced with auxetic mechanical metamaterials. Following simultaneous empirical mechanical and electrical measurements, auxetic soft sensor designs were compared with numerical simulations. Results suggest that such soft sensors based on metamaterials are great candidates for applications in healthcare and robotics when realized with 3D printing. © 2025 IEEE.

关键词： Flexible electronics

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Gaze Betray You: Abnormal Attention Detection from Human-Robot Interaction Dynamics

Gaze Betray You: Abnormal Attention Detection from Human-Rob...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Mu, Fengjun Zhang, Jingting Zou, Chaobin Huang, Zonghai Huang, Rui Cheng, Hong School of Automation Engineering University of Electronic Science and Technology of China Center for Robotics Chengdu China

ISBN: (纸本)9781665481090

Monitoring abnormal attention has a wide range of applications in Human-Robot Interaction systems, such as autonomous driving, virtual reality, and remote operation. Due to factors like fatigue, drowsiness, and distraction, human attention can deviate from tasks that require focus, resulting in abnormal attention during interactions. Monitoring for abnormal attention is essential to ensure the safety of human-robot interactions. However, existing methods often rely on un-explainable algorithms such as neural networks, making them difficult to trust in scenarios like autonomous driving, where explicit decision-making processes and mechanisms are required. This paper presents EyeAAD, an abnormal attention detection method based on dynamic system theory. This method uses gaze signals from a serious game designed to simulate human-robot interaction. We developed several attention-related features for interpretable modeling using a deterministic learning method. By analyzing the matching relationship between the gaze signal and the predicted status from the learned dynamic models, we can detect abnormal human attention patterns. To validate our approach, we designed a serious game for eye movement data acquisition in human-robot interaction. Our analysis showed that EyeAAD enables efficient, real-time monitoring of human attention. © 2024 IEEE.

关键词： Serious games

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