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International Conference on Vision, Image and Signal Processing (ICVISP)

作者： Yingyuan Yang Guoyuan Liang Xinyu Wu Biao Liu Chao Wang Jun Liang Jianquan Sun Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology Shenzhen China The University of Chinese Academy of Sciences Beijing China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology Shenzhen China Guangzhou gosuncn robot Co. Ltd Guangzhou China China Nuclear Power Technology Research Institute Co. Ltd Shenzhen China

ISBN: (数字)9798331541460

ISBN: (纸本)9798331541477

As the increasing number of multi-camera surveillance systems, researchers have been investigating the potential of multi-view action recognition. The skeleton-based methods are favorable due to the good performance. However, relying on specialized hardware with depth sensors or the efficient estimation for human poses, makes them less suitable for real-world deployment. In this study, we concentrate on the RGB modality for multi-view action recognition and propose a novel cross-view fused network. In details, gated adaptive fusion is utilized to aggregate the global representation across different views and spatio-temporal cross-attention module is employed to facilitate the effective fusion for spatio-temporal features. Based on three well-known multi-view action datasets: NTU-60, NTU-120, and N-UCLA, a series of experiments are conducted and verifies the effectiveness and robustness of the method under multi-view scenarios.

关键词： Image recognition Aggregates Interactive systems Logic gates Streaming media Signal processing Video surveillance Robustness Real-time systems Sensors

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Locust-Inspired Timing Strategy for Wing Deployment in Jump-Fly Robots

Locust-Inspired Timing Strategy for Wing Deployment in Jump-...

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Yunhao Si Yanzhou Jin Chengcheng Jing Zhiqiang Yu Toshio Fukuda Qing Shi Beijing Advanced Innovation Center for Intelligent Robots and Systems the School of Mechatronical Engineering and Key Laboratory of Biomimetic Robots and System Ministry of Education Beijing Institute of Technology Beijing P.R. China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing P.R. China

Small-scale robots often face challenges in traversing terrains of different scales. The combination of jumping and flying motion can enhance their obstacle-surmounting ability, and the timing of wing deployment undoubtedly plays a critical role in their jump-fly performance. However, previous studies of jump-fly robots have deployed wings speculatively at the highest point of the jump trajectory, resulting in suboptimal locomotion distance. In this study, we characterized the jump-fly motion of locusts and found that wing deployment timing is regulated by both airspeed and body angle. To verify the effect of this discovery on jump-fly robot motion, we constructed a jump-fly robot model in MATLAB and found that deploying wings based on the discovered airspeed-body angle relationship results in the farthest locomotion distance. Our findings provide valuable insights for improving the locomotion ability of jump-fly robots.

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Comprehensive-Forecast Multiobjective Genetic Programming for Neural Architecture Search

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IEEE Transactions on Evolutionary Computation 2025年

作者： Cao, Bin Luo, Xiao Liu, Xin Li, Yun Hebei University of Technology State Key Laboratory of Intelligent Power Distribution Equipment and System Tianjin300401 China Hebei University of Technology School of Artificial Intelligence Tianjin300401 China Hebei University of Technology School of Economics and Management Tianjin300401 China University of Electronic Science and Technology of China Industrial Artificial Intelligence Centre Shenzhen Institute for Advanced Study Guangdong Shenzhen518110 China

Neural Architecture Search (NAS) requires global topological exploration and is hence time consuming. To address this challenge, we propose the comprehensive-forecast multiobjective genetic programming for NAS, or CFMOGP-NAS for short. By integrating the strengths of various regression models and synthesizing the forecast of multiple candidates, the accuracy and robustness of architecture predictions are enhanced. The resultant algorithm this way incorporates a strategy of a mixture of complete and partial training, which balances cost and accuracy of evaluation. To also balance the population diversity, we develop a regularized tournament scheme for genetic programming. Experimental studies show that CFMOGP-NAS achieves a 50% reduction in search time without sacrificing accuracy, and verify that it substantially improves efficacy and efficiency compared with the state-of-the-art NAS methods. © 1997-2012 IEEE.

关键词： Multiobjective optimization

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A MATLAB Multi-Body Simulation Platform Toward Multiple Flapping Wing Vehicles

A MATLAB Multi-Body Simulation Platform Toward Multiple Flap...

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Chinese Control Conference (CCC)

作者： Jifu Yan Fan Jia Chen Qian Yongchun Fang Institute of Robotics and Automatic Information System Nankai University Tianjin P. R. China Zhejiang Laboratory Interdisciplinary Innovation Research Centers Intelligent Robotic Research Center Hangzhou P. R. China Institute of Intelligence Technology and Robotics Systems Shenzhen Research Institute of Nankai University Shenzhen P. R. China

The article notices rare simulation implementations of multiple flapping wing vehicles(FWVs) with the complicate mechanisms, aerodynamics, and control systems. Moreover, we expect that one can research FWV flight by CAD model import, joint connection, and parameter setup. Therefore, we establish a general and simple simulation platform framework based on MATLAB/Simulink with Simscape Multibody Toolbox for FWV mechanism, aerodynamics, and formation control for hovering or forward flight. Inspired by Purdue Hummingbird design, we provided simplified flapping wing aerodynamics with passive rotation, virtual environment interaction, adaptive cascade control, and consensus formation algorithms in the MATLAB integration platform. This work is fundamental for the verification of research, and useful for the improvement of mechanic design, actuator selection, and control algorithms of the ontology or swarm thanks to its compatibility.

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DEdgeNet: Extrinsic Calibration of Camera and LiDAR with Depth-discontinuous Edges

DEdgeNet: Extrinsic Calibration of Camera and LiDAR with Dep...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Yiyang Hu Hui Ma Leiping Jie Hui Zhang Faculty of Science and Technology United International College BNU-HKBU Zhuhai China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences Shenzhen Institute of Advanced Technology Department of Computer Science Hong Kong Baptist University Hong Kong China

This paper addresses the problem of calibrating extrinsic parameter matrix between an RGB camera and a LiDAR. Multimodal sensing systems are essential for fully autonomous navigation platforms. A key pre-requisite for such a system is calibration between different sensors. As the two most widely equipped sensors, calibration between RGB cameras and LiDARs remains challenging. Existing methods address this problem without using explicit geometric priors. In this paper, we propose a novel real-time network that utilizes depth-discontinuous edges extracted from a single image to calibrate cameras and LiDARs. Our network consists of two key components: (1) a self-supervised edge extraction network named DEdgeNet, which detects depth-discontinuous edges from a single image and extracts corresponding features; (2) prediction of the extrinsic parameter matrix between the camera and the LiDAR by matching fixed features in RGB images and updating depth features in a coarse-to-fine frame. Specifically, considering that edges are rich and common in natural scenes, DEdgeNet simplifies RGB image encoding and extracts fixed edges for feature matching. We conducted extensive experiments on the KITTI-odometry dataset. The results show that our method achieves an average rotation error of 0.028° and an average translation error of 0.247 cm, which demonstrates the superiority of our method.

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Numerical study of nanochannel on a silicon-silver dimer gap for significantly enhanced fluorescence

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Results in Physics 2024年 62卷

作者： Wang, Qiang Chen, Zhihui Gu, Zhiyuan Li, Lingqiao Guo, Deyi Shi, Baopeng Wang, Yang Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Electronic Information and Optical Engineering Taiyuan University of Technology Taiyuan 030024 China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Physics Taiyuan University of Technology Taiyuan 030024 China Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education Institute of Biotechnology Shanxi University Taiyuan 030006 China

The metal-dielectric dimer is an ideal structure for enhancing single-molecule fluorescence. When a single-molecule interacts with the metal-dielectric dimer, the metal-dielectric plasmonic system creates strong resonance, which amplifies the electric field by several orders of magnitude. One-dimensional photonic crystals (1D PCs) provide a photonic bandgap (PBG) and nearly perfect reflection for specific wavelengths. These phenomena contribute significantly to fluorescence enhancement. Herein, we propose the structure of 1D PCs with a silicon-silver dimer to achieve remarkable fluorescence enhancement under numerical study. Specifically, our design involves a 20 nm gapped silicon-silver dimer with a 50 nm nanochannel positioned above it. Through the optimization of structural parameters, our results demonstrate that quantum dots with a high intrinsic quantum yield, such as 100 %, are capable of achieving a fluorescence directional emission enhancement of up to three orders of magnitude compared to the bare structure, with an average enhancement factor reaching 407-fold. These findings stand for the unique sensitivity of the device, making it a promising choice for applications in biological nanoparticle detection, environmental monitoring, and other fields in the future. © 2024

关键词： Localized surface plasmon resonance (LSPR) Resonant cavity Silicon-silver dimer Ultra-high fluorescence enhancement

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Auto-MatRegressor材料性能自动预测器:解放材料机器学习"调参师"

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Science Bulletin 2023年第12期68卷 1259-1270,M0004页

作者：刘悦王双燕杨正伟 Maxim Avdeev 施思齐 School of Computer Engineering and Science Shanghai UniversityShanghai 200444China Shanghai Engineering Research Center of Intelligent Computing System Shanghai 200444China State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringShanghai UniversityShanghai 200444China Materials Genome Institute Shanghai UniversityShanghai 200444China Zhejiang Laboratory Hangzhou 311100China Australian Nuclear Science and Technology Organisation Sydney 2232Australia School of Chemistry The University of SydneySydney 2006Australia

机器学习因其能够快速、精准拟合数据的潜在模式而被广泛应用于材料构效关系研究。然而,材料科学家往往需要进行繁琐的模型选择及参数寻优才能构建出高精度预测模型,为了解放材料机器学习"调参师",本文研发了基于元学习的材... 详细信息

机器学习因其能够快速、精准拟合数据的潜在模式而被广泛应用于材料构效关系研究。然而,材料科学家往往需要进行繁琐的模型选择及参数寻优才能构建出高精度预测模型,为了解放材料机器学习"调参师",本文研发了基于元学习的材料性能自动预测器,采集了60份文献公开数据集与60份标准数据集,基于此训练18种常用回归算法并获得其预测性能,定义与计算了27个刻画数据集特点的元特征,以此构建了一份蕴含建模经验的元数据集;同时,创建了表征数据集所属材料类型的类别树,将其嵌入基于距离的元学习算法,进一步耦合贝叶斯优化算法,实现领域知识和元数据协同驱动下的自动算法推荐和模型参数确定,实验结果表明,材料科学家仅需为新材料性能预测任务提供数据集,便可利用该预测器高效地构建具有与文献报道相当或更高预测精度的机器学习模型.

关键词：机器学习贝叶斯优化算法预测器材料科学家元数据参数寻优预测性能材料性能

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Exoskeleton-Based Lower Limb Rehabilitation Robot Design and Simulation for Children with Cerebral Palsy

Exoskeleton-Based Lower Limb Rehabilitation Robot Design and...

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World Rehabilitation Robot Convention (WRRC)

作者： Wujing Cao Shuo Zhang Yupeng Zou Xinqiang Guo Changyu Li Jingxin Wang Worawarit Kobsiriphat Xinyu Wu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China and SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems. SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society School of Mechanical Engineering China University of Petroleum East China Jining Zhongke Intelligent Technology Co. Ltd. Department of Rehabilitation Medicine Zhengzhou Central Hospital Affiliated Zhengzhou University Zhengzhou China National Metal and Materials Technology Center Thailand

ISBN: (数字)9798350355123

ISBN: (纸本)9798350355130

Squat gait is the most common abnormal gait in children with cerebral palsy. Gait training with lower limb rehabilitation robots can improve rehabilitation efficiency and reduce manual labor for them. A novel exoskeleton-based lower limb rehabilitation robot for children with cerebral palsy is proposed, considering the squat gait characteristics of children with cerebral palsy. The structure of the lower limb rehabilitation robot, which combines hip and knee with 4 active degrees of freedom exoskeleton and mobile walker, is designed and optimized. Static analysis of the key mechanical structure of the exoskeleton is conducted using ANSYS Workbench, and local structures are optimized to ensure the safety factor of the mechanical structure is greater than 1, guaranteeing reasonable structural strength and stiffness design. Dynamic simulation analysis based on the ADAMS model validates the reliability and dynamic walking effect of the lower limb exoskeleton rehabilitation robot, obtaining the curve relationship between joint angles and motion cycles, thus verifying the effectiveness of the mechanical system motion.

关键词： Knee Training Cerebral palsy Exoskeletons Dynamics Static analysis Assistive robots Safety Finite element analysis Hip

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

作者： Ma, Jiajun Liang, Guoyuan Liang, Yu Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9781665436786

3D facial similarity measure is a critical research direction in fields such as 3D face recognition, craniofacial reconstruction, and heritability estimation, etc. and represents a challenging and meaningful task. In this paper, we propose a novel method based on deformation field to establish the similarity relationship between 3D faces. The main idea is divided into two steps as follows: (1) The landmarks are semi-automatically marked on all faces to build correspondences between landmarks (2) According to the distance field and the dense corresponding relationship of faces, a deformation field is generated between 3D faces that deform the source model to the target model. The path of deformation is computed to measure the similarity between two 3D faces. Comprehensive experiments conducted on the BU3DFE database illustrate that the similarity measure method is consistent with the subjective evaluation and provides high discriminability for different individuals. © 2021 IEEE.

关键词： Deformation

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Design of a Novel Autonomous Docking system With a Supporting robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Huijie Dong Chunyang Zhao Tiezhu Qiao Jian Wang Di Chen Yan Meng Junzhi Yu Ministry of Education Key Laboratory of Advanced Transducers and Intelligent Control System Taiyuan University of Technology Taiyuan China Institute of Automation Laboratory of Cognitive and Decision Intelligence for Complex System Chinese Academy of Sciences Beijing China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China College of Electronics and Information Engineering Guangdong Ocean University Zhanjiang China

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named ‘CourierFish’. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks.

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