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8th IEEE International Conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Qi, Peng Wu, Yunfeng Yao, Tianliang Lu, Bo Sun, Yi Dai, Jian S. College of Electronics and Information Engineering Tongji University Department of Control Science and Engineering Shanghai China Robotics and Microsystems Center School of Mechanical and Electric Engineering Soochow University Jiangsu Suzhou China Ecole Polytechnique Federale de Lausanne Laboratory of Intelligent Systems Lausanne1015 Switzerland College of Engineering Southern University of Science and Technology Department of Mechanical and Energy Engineering Shenzhen518055 China School of Natural Mathematical and Engineering Sciences King's College London United Kingdom

ISBN: (纸本)9798350300178

To effectively interact with the physical world, an intelligent robot is required to have the ability to obtain the detailed features of an unknown object. Visual devices are commonly used to detect the global geometry of an object;however, detailed information such as surface properties cannot be identified using these devices. The current study proposes an efficient haptic exploration method to recognize the physical properties of surfaces using an intelligent fingertip. Our surface-following algorithm utilizes the normal force vector and the tangential force vector at the contact point between the fingertip and the target object to predict the moving direction and implement the surface exploration. And a correction index K is introduced to adjust the sliding velocity. The algorithm is proved to be robust and high performance both in simulation and lab experiments. Finally, we propose and explore a haptic prediction neural network, which enables our robot to have an accurate feel through physical interaction. In the classification experiment of four types of objects with different surface properties, the average accuracy of the proposed model is 90.2%. © 2023 IEEE.

关键词： Surface properties

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Rehabilitation Training of Spinal Cord Injured Individuals by a Self-Balancing Exoskeleton Robot

Rehabilitation Training of Spinal Cord Injured Individuals b...

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

作者： Li, Wentao Li, Jinke He, Yong Tian, Dingkui Li, Feng Sun, Jianquan Wu, Xinyu Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518055 China Siat Cuhk Joint Laboratory of Robotics and Intelligent Systems China University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Shenzhen518055 China China Construction Third Bureau First Engineering Mep Co. Ltd. Shenzhen518109 China

ISBN: (纸本)9798350327182

Physical therapy plays an important role in the rehabilitation for spinal cord injured individuals, and exoskeleton can assist with this process. In this paper, a self-balancing exoskeleton robot is introduced, which can provide assist not only in gait training, but also in balance training. In addition, it allows individuals walk with it without other assistive devices. This exoskeleton is designed to have a high degree of compatibility with humans. The structure and control system of the exoskeleton is introduced and the forward and inverse kinematic are solved, which enables the robot to perform various rehabilitation training actions as required. Experiments with a male subject have shown that this exoskeleton achieves the predicted results in gait training and balance training. © 2023 IEEE.

关键词： Inverse kinematics

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CPL-CLIP: Compound Prompt Learning for Flexible-Modal Face Anti-Spoofing 18

CPL-CLIP: Compound Prompt Learning for Flexible-Modal Face A...

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18th IEEE International Joint Conference on Biometrics, IJCB 2024

作者： Zhang, Ying Zhu, Xiangyu Liu, Ajian Lin, Xun Wan, Jun Zhang, Jing Lei, Zhen Beihang University School of Computer Science and Engineering China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation China University of Chinese Academy of Sciences School of Artificial Intelligence China Macau University of Science and Technology School of Computer Science and Engineering China Chinese Academy of Sciences Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation China

ISBN: (纸本)9798350364132

Face anti-spoofing (FAS) is pivotal in safeguarding the integrity of face recognition systems. Flexible-modal FAS utilizes multi-modal data and trains a unified model adaptable to any single-modal testing scenario. This innovation addresses the shortcomings of conventional multi-modal FAS approaches, which typically demand separate model training and deployment for each modality. However, existing flexible-modal FAS approaches activate specific network branches based on the modality of the tested sample. This not only increases the model's parameters but also necessitates the provision of the image's modality for testing, thereby constraining deployment flexibility. To address the issue, we present Compound Prompt Learning CLIP (CPL-CLIP), a novel method for flexible-modal FAS. This approach capitalizes on a learned textual prompt that is nearly independent of modality, thus bolstering class-based classification across arbitrary modalities. Specifically, our CPL-CLIP introduces a Dual-Branch Prompt (DBP), consisting of class and modal prompts that describe and guide classification, where each prompt is composed of learnable vectors and fixed templates. To further render the class prompt as modality-agnostic as possible, a Cosine Similarity Loss (CSL) is proposed to facilitate the maximal separation of the class prompt from the modality prompt. With only the class prompt utilized during testing, CPL-CLIP enables deployment in diverse modal testing scenarios without the necessity of the test image's modality to be known. Extensive experiments demonstrate CPL-CLIP's superiority over existing methods on several flexible-modal FAS benchmarks. © 2024 IEEE.

关键词： Face recognition

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Design and Implementation of OpenWSN Hardware Platform 2

Design and Implementation of OpenWSN Hardware Platform

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2nd International Conference on Algorithms, High Performance Computing and Artificial Intelligence, AHPCAI 2022

作者： Zhang, Shusheng Xie, Chuang Liu, Jun Zhao, Chun Yang, Zhijia Mao, Jizhi College of Automation and Electrical Engineering Shenyang Ligong University Shenyang110159 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798350334784

This paper proposes a new wireless sensor network hardware platform based on OpenWSN project launched by the University of California, Berkeley. The hardware platform's processor uses a 32-bit microcontroller (STM32F103RCT6) produced by STMicroelectronics (ST), and the wireless module uses the WISA470 chip. The final experimental results show that this platform can support the Open WSN project very well. © 2022 IEEE.

关键词： Wireless sensor networks

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Active Camera View Planning Based on Deep Reinforcement Learning in Indoor Exploration

Active Camera View Planning Based on Deep Reinforcement Lear...

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第42届中国控制会议

作者： Hao-Yu Wang Qing-Hao Meng Xu-Yang Dai Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and SystemSchool of Electrical and Information Engineering Tianjin University

In the last decades, significant progress has been made in the field of active vSLAM（visual simultaneous localization and mapping）. However, the majority of active vSLAM methods suffer from the problem of coupling the camera's viewpoint to the robot's motion, which limits the initiative during the exploration of unknown environments. To address this issue, this study proposes a camera view planning method based on deep reinforcement learning（DRL）, which makes the camera rotate independently. First, feature encoding is performed on the reconstructed navigation map using a multi-layer convolutional neural network（CNN）. Second, the DRL-based camera view planning method is trained through the proximal policy optimization（PPO）algorithm. Last, a significant number of tests is performed on a public dataset of indoor environments. The simulation results show that the proposed camera view planning method improves the exploration coverage by an average of 4%（33.86 m for traditional vs. 35.21 m for the suggested method）. Meanwhile, the kind of semantic information newly observed in each step increases by 21%（2.9 for traditional vs. 3.5 for the proposed method） on average, indicating the improvement in the efficiency of information acquisition.

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A Framework Leveraging robotics and Machine Learning Technologies for Early Disease and Pest Detection in Greenhouse Tomato Crops

A Framework Leveraging Robotics and Machine Learning Technol...

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International Conference on Control, Artificial Intelligence, robotics & Optimization (ICCAIRO)

作者： Nikolaos Kounalakis Emmanouil Kalykakis Dimitrios Kosmopoulos John Fasoulas Michael Sfakiotakis Control Systems and Robotics Laboratory (CSRL) School of Engineering Hellenic Mediterranean University Heraklion Greece Dept. of Computer Engineering and Informatics University of Patras Patras Greece

We present an integrated framework for intelligent automated plant monitoring, towards early disease and pest detection in greenhouse tomato crops. The framework combines the use of a robotic mobile platform to autonomously collect multi-spectral images of the plants, with a tool that utilizes Faster R-CNN to detect regions that signify the presence of a disease or pest. The robot is based on a modified mobile vertical mast lift platform, and integrates a 6-dof robotic arm that is used to position the plant imaging multi-spectral camera. The robot can navigate autonomously inside the greenhouse via a magnetic guidance sensor. Results from a series of experiments demonstrate the validity and effectiveness of the implemented framework.

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Bio-Integrated Microrobots:Fabrication,Actuation and Biomedical Applications

SmartBot

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SmartBot 2025年第1期1卷 3-26页

作者： Huaping Wang Jiaxin Liu Ruhao Nie Qing Shi Qiang Huang Toshio Fukuda School of Mechatronical Engineering The Intelligent Robotics InstituteBeijing Institute of TechnologyBeijingChina The Key Laboratory of Biomimetic Robots and Systems Beijing Institute of TechnologyMinistry of EducationBeijingChina Institutes of Innovation for Future Society Nagoya UniversityNagoyaJapan

Bio-integrated microrobots(BIMs),which are fabricated with biofriendly materials,biological units(*** or biomolecules),or cell-material hybrids have emerged as a promising technology for minimally invasive *** diminutive size and flexible structures enable BIMs to navigate within narrow,deep,and challenging-to-reach in vivo regions,performing biopsy,diagnostic,drug delivery,and therapeutic functions with minimal ***,the clinical deployment of BIMs is a highly orchestrated task that requires consideration of material properties,structural design,locomotion,observation,therapeutic outcomes,and side effects on cells and tissues,*** this review,we review and discuss the latest advances in the biointegrated microrobot domain,evaluating various methods associated with materials,fabrication,actuation,and the implementation of biomedical functions in *** comparing the advantages and shortcomings of these techniques,this review highlights the challenges and future trends in highly intelligent bio-integrated microrobots,which have huge potential in minimally invasive biomedicine.

关键词： actuation biofabrication biomedical application microrobots

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SWhegPro3: A Three-Impeller Wheel-Leg Transformable Robot with Variable Robust Adaptability to Stair Dimensions

SWhegPro3: A Three-Impeller Wheel-Leg Transformable Robot wi...

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IEEE International Conference on robotics and Biomimetics

作者： Haoran Wang Siyuan Wang Cunxi Dai Zhenzhong Jia Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology (SUSTech) Shenzhen China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities SUSTech Shenzhen China

This paper reports the design innovation and implementation of a novel wheel-leg transformable robot named SWhegPro3. The robot uses a three-impeller design to significantly improve the overall stair-climbing performance. Unlike other impeller-based designs that use gear sets to unfold the impellers, this robot uses self-locking electric push rods for mode switching, thereby greatly improving its load capacity. We also analyze the stair climbing operation and derive a model to calculate the optimal configuration of the wheel-leg module and the corresponding displacement of the push rod, in order to better adapt to different sized stairs. We conduct both simulation and field experiments to validate our proposed design and control strategy.

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Atomic force microscopy for revealing micro/nanoscale mechanics in tumor metastasis:from single cells to microenvironmental cues

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中国药理学报（英文版） 2021年第3期42卷 323-339页

作者： Mi Li Ning Xi Yue-chao Wang Lian-qing Liu State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China University of Chinese Academy of Sciences Beijing 100049China Department of Industrial and Manufacturing Systems Engineering The University of Hong KongHong KongChina

Mechanics are intrinsic properties which appears throughout the formation,development,and aging processes of biological *** have been shown to play important roles in regulating the development and metastasis of tumors,and understanding tumor mechanics has emerged as a promising way to reveal the underlying mechanisms guiding tumor *** particular,tumors are highly complex diseases associated with multifaceted factors,including alterations in cancerous cells,tissues,and organs as well as microenvironmental cues,indicating that investigating tumor mechanics on multiple levels is significantly helpful for comprehensively understanding the effects of mechanics on tumor ***,diverse techniques have been developed for probing the mechanics of tumors,among which atomic force microscopy(AFM)has appeared as an excellent platform enabling simultaneously characterizing the structures and mechanical properties of living biological systems ranging from individual molecules and cells to tissue samples with unprecedented spatiotemporal resolution,offering novel possibilities for understanding tumor physics and contributing much to the studies of *** this review,we survey the recent progress that has been achieved with the use of AFM for revealing micro/nanoscale mechanics in tumor development and *** and future progress are also discussed.

关键词： atomic force microscopy tumor mechanics cancerous cell tumor microenvironment exosome extracellular matrix

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Motion Capture and Gait Analysis of Ants with Leg Injuries

Motion Capture and Gait Analysis of Ants with Leg Injuries

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第42届中国控制会议

作者： Ming Zeng Yuanhao Li Chang Meng Shutong Zhong Zhijing Wang Feng Zhao Institute of Robotics and Automation Systems Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin University

Many insects in nature, such as ants, recover quickly after sustaining leg injuries. If this capability could be imparted to multi-legged robots, it would drastically enhance their ability to resist destruction and adapt to the environment. In this paper, the Camponotus Japonicus is used as the research object, and its locomotive patterns are studied under different leg-loss *** facilitate this, a high-speed acquisition system, with a dual-view(bottom view and side view) setup, is designed to analyze the ant's linear gaits. Subsequently, the pivotal gait characteristics of the injured ants are extracted by keyframe annotation technology, including the gait phase diagram, duty factor, angle before support, angle before swing, and leg swing range. Lastly,according to the obtained gait characteristics, the general and specific laws of gait adjustment in the absence of one or two legs are systematically analyzed, which provides the basis for parametric settings and strategy optimization of robotic injured gait self-adjustment.

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