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WRC Symposium on advanced robotics and Automation (WRC SARA)

作者： Peng Ba Pengyi Wang Hongde Wu Qian Yang Yongqiang Feng Junchen Wang Yida David Hu Changsheng Li Wenyong Liu Shaolong Kuang Bai-Quan Su Medical Robotics Laboratory School of Intelligent Engineering and Automation Beijing University of Posts and Telecommunications Beijing China Plastic Surgery Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China School of Mechanical Engineering and Automation Beihang University Beijing China Brigham and Women’s Hospital Harvard Medical School Boston MA USA School of Mechatronical Engineering Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry Beijing Advanced Innovation Centre for Biomedical Engineering School of Biological Science and Medical Engineering Beihang University Beijing China School of Health Science and Environmental Engineering Shenzhen University of Technology Shenzhen China

ISBN: (数字)9798331506100

ISBN: (纸本)9798331506117

Hair direction is an important external feature of hair, and recognising hair direction is a prerequisite for processing hair. In this paper, a new algorithm is proposed and systematically verified experimentally for the problem of recognising hair direction. The main goal of this paper is to develop an algorithm that can identify hair direction in a complex image environment. A curve segment analysis method based on image skeletonisation is adopted, which is based on skeleton extraction, intersection identification, curve segmentation and direction prediction. In addition, this paper combines the technique of non-maximal value suppression and PCA analysis to improve the accuracy and stability of the estimation. In the experimental design, this paper chooses a representative image dataset to verify the effectiveness of this paper's algorithm. The experimental process includes the steps of image preprocessing, skeletonisation processing, intersection detection and merging, and direction prediction. The experimental results show that the method in this paper can accurately and effectively identify the hair direction. The main contribution of this paper is to propose a new hair direction recognition method and experimentally verify its effectiveness and accuracy in complex backgrounds.

关键词： Hair Image segmentation Accuracy Three-dimensional displays Merging Prediction algorithms Stability analysis

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A smart wearable device for capturing biomechanical energy from human knee motion

A smart wearable device for capturing biomechanical energy f...

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IEEE/ASME (AIM) International Conference on advanced intelligent Mechatronics

作者： Hugo Hung-Tin Chan Haisu Liao Xuan Zhao Junrui Liang Wei-Hsin Liao Xinyu Wu Fei Gao Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin Hong Kong China School of Information Science and Technology ShanghaiTech University Shanghai China

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

Sustainable power supply is a challenge for portable and wearable electronic devices such as cell phones and headsets. To address this, researchers proposed capturing biomechanical energy from human motion to generate electricity. This paper proposed and developed a lightweight wearable device to capture the biomechanical energy from the human knee motion. To reduce the effect of inertial force on human gait, we developed a lightweight and compact transmission chain to convert the bidirectional rotation of the knee to a unidirectional rotation of the generator. Two input bevel gears with opposite one-way bearings on the same shaft are engaged with a single output bevel gear of the generator thereby only one input bevel gear is engaged for each input direction, achieving unidirectional output. In addition, to reduce velocity fluctuation and further minimize the effect of inertial force, a flywheel was fixed to the motor shaft via a gearbox. A prototype of the wearable device was developed and tested on a subject walking on a treadmill. Experimental results shows the flywheel enabled the harvester to achieve a continuous output while halving voltage fluctuations compared to a conventional harvester. The harvesters average power output can reach 0.11 W with minimal effects on the subject’s walking gait.

关键词： Knee Legged locomotion Biomechanics Shafts Fluctuations Voltage fluctuations Torque

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A Tendon-Driven Actuator with Cantilever Initiated Variable Stiffness Used for Robotic Fingers

SSRN

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SSRN 2024年

作者： Li, Chenning Yang, Shangkui Branson, David T. Song, Zhibin Sun, Tao Dai, Jiansheng Kang, Rongjie Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education School of Mechanical Engineering Tianjin University Tianjin300072 China Advanced Manufacturing Technology Research Group Faculty of Engineering University of Nottingham NottinghamNG7 2RD United Kingdom Beijing Institute of Technology China Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Southern University of Science and Technology Shenzhen518055 China

Variable stiffness actuators (VSAs) have emerged as a key actuation technology known for their bionic performance and task adaptability. However, current VSAs often exhibit relatively large sizes, making them possible for use in robotic arms and legs but less convenient for integrations into robotic hands. This paper introduces a compact design of a tendon-driven variable stiffness actuator (TVSA) based on an adjustable cantilever mechanism, which can be embedded into a robotic finger. This implementation endows the robotic finger with the decoupled regulation of joint position and stiffness. A concise and computationally efficient stiffness mapping model from the TVSA to the finger joints is then established, providing a theoretical foundation for the stiffness regulation of the tendon-driven fingers. A prototype of a robotic hand equipped with the presented TVSA demonstrates safe interactions with various objects with diverse shapes, weights and stiffness. © 2024, The Authors. All rights reserved.

关键词： Stiffness

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Generative Adversarial Learning for Trusted and Secure Clustering in Industrial Wireless Sensor Networks

arXiv

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arXiv 2022年

作者： Yang, Liu Yang, Simon X. Li, Yun Lu, Yinzhi Guo, Tan The School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China The School of Software Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China The Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph GuelphONN1G2W1 Canada

Traditional machine learning techniques have been widely used to establish the trust management systems. However, the scale of training dataset can significantly affect the security performances of the systems, while it is a great challenge to detect malicious nodes due to the absence of labeled data regarding novel attacks. To address this issue, this paper presents a generative adversarial network (GAN) based trust management mechanism for Industrial Wireless Sensor Networks (IWSNs). First, type-2 fuzzy logic is adopted to evaluate the reputation of sensor nodes while alleviating the uncertainty problem. Then, trust vectors are collected to train a GAN-based codec structure, which is used for further malicious node detection. Moreover, to avoid normal nodes being isolated from the network permanently due to error detections, a GAN-based trust redemption model is constructed to enhance the resilience of trust management. Based on the latest detection results, a trust model update method is developed to adapt to the dynamic industrial environment. The proposed trust management mechanism is finally applied to secure clustering for reliable and real-time data transmission, and simulation results show that it achieves a high detection rate up to 96%, as well as a low false positive rate below 8%. © 2022, CC BY.

关键词： Generative adversarial networks

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A differential public PUF design for lightweight authentication 16

A differential public PUF design for lightweight authenticat...

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2021 International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design, SMACD 2021 and 16th Conference on PhD Research in Microelectronics and Electronics, PRIME 2021

作者： Duan, Shengyu Sai, Gaole School of Computer Engineering and Science Shanghai University Shanghai200444 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China

ISBN: (纸本)9783800755899

Physical Unclonable Functions (PUFs) have emerged as a promising primitive to provide a hardware keyless security mechanism for integrated circuit applications. Public PUFs (PPUFs) address the crucial PUF vulnerability of requiring databases to store the secrete reference information. This paper investigates one of the PPUF families, differential PPUF (dPPUF), which exploits complexly interacted logic to create time gap between actual execution and simulation, and to prevent simulation attacks. Conventional dPPUFs have high costs. We observe the repressers have large impact on simulation time, but take a great proportion in current dPPUF structure. We thereby present a represser network with specially designed interconnection and shared logic, to maintain a high circuit complexity and to reduce the area cost. We show the proposed dPPUF has similar resilience over simulation attacks as the conventional design. Area cost can be reduced by up to 44%, and thus the proposed design can be used for lightweight authentication. © VDE VERLAG GMBH.

关键词： Authentication

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An Evolutionary Game based Secure Clustering Protocol with Fuzzy Trust Evaluation and Outlier Detection for Wireless Sensor Networks

arXiv

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arXiv 2022年

作者： Yang, Liu Lu, Yinzhi Yang, Simon X. Zhong, Yuanchang Guo, Tan Liang, Zhifang The School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China The Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph GuelphONN1G2W1 Canada The State Key Laboratory of Power Transmission Equipment & System Security and New Technology School of Electrical Engineering Chongqing University Chongqing400044 China

Trustworthy and reliable data delivery is a challenging task in Wireless Sensor Networks (WSNs) due to unique characteristics and constraints. To acquire secured data delivery and address the conflict between security and energy, in this paper we present an evolutionary game based secure clustering protocol with fuzzy trust evaluation and outlier detection for WSNs. Firstly, a fuzzy trust evaluation method is presented to transform the transmission evidences into trust values while effectively alleviating the trust uncertainty. And then, a K-Means based outlier detection scheme is proposed to further analyze plenty of trust values obtained via fuzzy trust evaluation or trust recommendation. It can discover the commonalities and differences among sensor nodes while improving the accuracy of outlier detection. Finally, we present an evolutionary game based secure clustering protocol to achieve a trade-off between security assurance and energy saving for sensor nodes when electing for the cluster heads. A sensor node which failed to be the cluster head can securely choose its own head by isolating the suspicious nodes. Simulation results verify that our secure clustering protocol can effectively defend the network against the attacks from internal selfish or compromised nodes. Correspondingly, the timely data transfer rate can be improved significantly. © 2022, CC BY.

关键词： Sensor nodes

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Crossbreeding in random forest

arXiv

引用

arXiv 2021年

作者： Nadi, Abolfazl Moradi, Hadi Taheri, Khalil Advanced Robotics and Intelligent Systems Laboratory School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran11155-4563 Iran SKKU Suwon16419 Korea Republic of

Ensemble learning methods are designed to benefit from multiple learning algorithms for better predictive performance. The tradeoff of this improved performance is slower speed and larger size of ensemble learning systems compared to single learning systems. In this paper, we present a novel approach to deal with this problem in Random Forest (RF) as one of the most powerful ensemble methods. The method is based on crossbreeding of the best tree branches to increase the performance of RF in space and speed while keeping the performance in the classification measures. The proposed approach has been tested on a group of synthetic and real datasets and compared to the standard RF approach. Several evaluations have been conducted to determine the effects of the Crossbred RF (CRF) on the accuracy and the number of trees in a forest. The results show better performance of CRF compared to RF. © 2021, CC BY-NC-ND.

关键词： Learning systems

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NeRF in robotics: A Survey

arXiv

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arXiv 2024年

作者： Wang, Guangming Pan, Lei Peng, Songyou Liu, Shaohui Xu, Chenfeng Miao, Yanzi Zhan, Wei Tomizuka, Masayoshi Pollefeys, Marc Wang, Hesheng The University of Cambridge ETH Zurich Switzerland The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of System Control and Information Processing Ministry of Education of China China Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China ETH Zurich Zurich Switzerland Mechanical Systems Control Laboratory University of California Berkeley United States

Meticulous 3D environment representations have been a longstanding goal in computer vision and robotics fields. The recent emergence of neural implicit representations has introduced radical innovation to this field as implicit representations enable numerous capabilities. Among these, the Neural Radiance Field (NeRF) has sparked a trend because of the huge representational advantages, such as simplified mathematical models, compact environment storage, and continuous scene representations. Apart from computer vision, NeRF has also shown tremendous potential in the field of robotics. Thus, we create this survey to provide a comprehensive understanding of NeRF in the field of robotics. By exploring the advantages and limitations of NeRF, as well as its current applications and future potential, we hope to shed light on this promising area of research. Our survey is divided into two main sections: The Application of NeRF in robotics and The Advance of NeRF in robotics, from the perspective of how NeRF enters the field of robotics. In the first section, we introduce and analyze some works that have been or could be used in the field of robotics from the perception and interaction perspectives. In the second section, we show some works related to improving NeRF's own properties, which are essential for deploying NeRF in the field of robotics. In the discussion section of the review, we summarize the existing challenges and provide some valuable future research directions for reference. © 2024, CC BY-NC-ND.

关键词： robotics

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Pulsed Microfluid Force-Based On-Chip Modular Fabrication for Liver Lobule-Like 3D Cellular Models

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Cyborg and Bionic systems 2021年第1期2021卷 222-233页

作者： J.Cui H.P.Wang Q.Shi T.Sun Science and Technology on Electronic Test and Measurement Laboratory North University of ChinaTaiyuan 030051China Intelligent Robotics Institute School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China Key Laboratory of Biomimetic Robots and Systems(Beijing Institute of Technology) Ministry of EducationBeijing 100081China

In vitro three-dimensional(3D)cellular models with native tissue-like architectures and functions have potential as alternatives to human tissues in regenerative medicine and drug ***,it is difficult to replicate liver constructs that mimic in vivo microenvironments using current approaches in tissue engineering because of the vessel-embedded 3D structure and complex cell distribution of the *** paper reports a pulsed microflow-based on-chip 3D assembly method to construct 3D liver lobule-like models that replicate the spatial structure and functions of the liver *** heterogeneous cell-laden assembly units with hierarchical cell distribution are fabricated through multistep photopatterning of different cell-laden *** fluid force interaction by pulsed microflow,the hierarchical assembly units are driven to a stack,layer by layer,and thus spatially assemble into 3D cellular models in the closed liquid chamber of the assembly *** 3D models with liver lobule-like hexagonal morphology and radial cell distribution allow the dynamic perfusion culture to maintain high cell viability and functional expression during long-term culture in *** results demonstrate that the fabricated 3D liver lobule-like models are promising for drug testing and the study of individual diagnoses and treatments.

关键词： culture maintain spatially

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A moving target detection and localization strategy based on optical flow and pin-hole imaging methods using monocular vision

A moving target detection and localization strategy based on...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Wang, Shun Guo, Qingqiang Xu, Sheng Su, Dan School of Control Science and Engineering Shandong University Shandong Jinan250061 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China Shandong Institute of Advanced Technology Chinese Academy of Sciences Shandong Jinan250102 China Orbbec Inc. Shenzhen518057 China

ISBN: (纸本)9781665436786

This paper proposes a new strategy for moving target detection and localization based on monocular vision. Firstly, to detect a moving target with large displacement and high speed accurately, two consecutive video images captured by a monocular camera are preprocessed using the enhancement and denoising methods. Then, the optical flow representing motion information is calculated iteratively by the modified Lucas-Kanade optical flow method. Secondly, a new interest region extraction method is developed to overcome the negative impacts caused by the noises in the background. Specifically, this proposed method combines a two-level image segmentation strategy from coarse to fine, including median filtering, two-direction dynamic threshold segmentation, the Otsu method, and morphological processing. Thirdly, a low computational cost target localization algorithm is proposed based on pin-hole imaging theory. Besides, it only uses two-dimensional image and camera parameters to obtain the moving target's position in the three-dimensional space. Finally, experimental results show that the proposed strategy can effectively eliminate noise interferences and realize moving target detection, extraction, and localization. © 2021 IEEE.

关键词： Image segmentation

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