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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Chen, Yunwang Kang, Yaozhong Zhao, Ziqi Hong, Yue Meng, Lingxiao Meng, Max Q.-H. Southern University of Science and Technology Shenzhen Key Laboratory of Robotics Perception and Intelligence Shenzhen518055 China SUSTech Department of Electrical and Electronic Engineering Shenzhen China School of System Design and Intelligent Manufacturing SUSTech Shenzhen China

ISBN: (纸本)9781665481090

This paper presents a collaborative fall detection and response system integrating Wi-Fi sensing with robotic assistance. The proposed system leverages channel state information (CSI) disruptions caused by movements to detect falls in non-line-of-sight (NLOS) scenarios, offering non-intrusive monitoring. Besides, a companion robot is utilized to provide assistance capabilities to navigate and respond to incidents autonomously, improving efficiency in providing assistance in various environments. The experimental results demonstrate the effectiveness of the proposed system in detecting falls and responding effectively. © 2024 IEEE.

关键词： Fall detection

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Domain-Invariant Similarity Activation Map Contrastive Learning for Retrieval-Based Long-Term Visual Localization

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IEEE/CAA Journal of Automatica Sinica 2022年第2期9卷 313-328页

作者： Hanjiang Hu Hesheng Wang Zhe Liu Weidong Chen Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China IEEE Department of Automation Institute of Medical RoboticsKey Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China Department of Computer Science and Technology University of CambridgeCambridge CB30FDUnited Kingdom

Visual localization is a crucial component in the application of mobile robot and autonomous *** retrieval is an efficient and effective technique in image-based localization *** to the drastic variability of environmental conditions,e.g.,illumination changes,retrievalbased visual localization is severely affected and becomes a challenging *** this work,a general architecture is first formulated probabilistically to extract domain-invariant features through multi-domain image ***,a novel gradientweighted similarity activation mapping loss(Grad-SAM)is incorporated for finer localization with high *** also propose a new adaptive triplet loss to boost the contrastive learning of the embedding in a self-supervised *** final coarse-to-fine image retrieval pipeline is implemented as the sequential combination of models with and without Grad-SAM *** experiments have been conducted to validate the effectiveness of the proposed approach on the CMU-Seasons *** strong generalization ability of our approach is verified with the RobotCar dataset using models pre-trained on urban parts of the CMU-Seasons *** performance is on par with or even outperforms the state-of-the-art image-based localization baselines in medium or high precision,especially under challenging environments with illumination variance,vegetation,and night-time ***,real-site experiments have been conducted to validate the efficiency and effectiveness of the coarse-to-fine strategy for localization.

关键词： Deep representation learning place recognition visual localization

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SEMG-Based Gesture Recognition in Multiple Scenarios Using a Phase Locked Value-Based Deep Learning Method

SEMG-Based Gesture Recognition in Multiple Scenarios Using a...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Zhang, Xueze Wang, Minjie Chen, Zihua Wang, Lu Wang, Hongbo Kang, Xiaoyang Laboratory for Neural Interface and Brain Computer Interface Engineering Research Center of Ai & Robotics Ministry of Education Shanghai Engineering Research Center of Ai & Robotics Moe Frontiers Center for Brain Science State Key Laboratory of Medical Neurobiology Institute of Ai & Robotics Institude of Meta-Medical Academy for Engineering & Technology Fudan University Shanghai China

ISBN: (纸本)9798350386226

Surface electromyography (sEMG) signals-based gesture recognition method is widely employed in human-computer interaction task. In this paper, we proposed a phase locked value (PLV)-based feature extraction method for sEMG-based gesture recognition. We conducted validation experiments on public datasets by integrating the previous proposed gesture recognition algorithms, STCN-GR and ConSSL. PLV-STCN-GR and PLV-ConSSL were utilized to test the performance of proposed feature extraction method in intra-session, inter-session and inter-subject scenarios. In general, the proposed PLV-based sEMG decoding framework has achieved good recognition results on public datasets and demonstrated the possibility of its application in practical scenarios. © 2024 IEEE.

关键词： Deep learning

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NEDS-SLAM: A Neural Explicit Dense Semantic SLAM Framework using 3D Gaussian Splatting

arXiv

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arXiv 2024年

作者： Ji, Yiming Liu, Yang Xie, Guanghu Ma, Boyu Xie, Zongwu Liu, Hong State Key Laboratory of Robotics and Systems Harbin Institute of Technology China

We propose NEDS-SLAM, a dense semantic SLAM system based on 3D Gaussian representation, that enables robust 3D semantic mapping, accurate camera tracking, and high-quality rendering in real-time. In the system, we propose a Spatially Consistent Feature Fusion model to reduce the effect of erroneous estimates from pre-trained segmentation head on semantic reconstruction, achieving robust 3D semantic Gaussian mapping. Additionally, we employ a lightweight encoder-decoder to compress the high-dimensional semantic features into a compact 3D Gaussian representation, mitigating the burden of excessive memory consumption. Furthermore, we leverage the advantage of 3D Gaussian splatting, which enables efficient and differentiable novel view rendering, and propose a Virtual Camera View Pruning method to eliminate outlier gaussians, thereby effectively enhancing the quality of scene representations. Our NEDS-SLAM method demonstrates competitive performance over existing dense semantic SLAM methods in terms of mapping and tracking accuracy on Replica and ScanNet datasets, while also showing excellent capabilities in 3D dense semantic mapping. Index Terms—3D Gaussian Splatting;Dense Semantic Mapping;Neural SLAM;3D Reconstruction. Copyright © 2024, The Authors. All rights reserved.

关键词： Mapping

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Swarm-Based Dynamic Coverage of Multi-ASV systems in the Presence of Measurement Noises

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IEEE Transactions on Vehicular technology 2025年第5期74卷 7237-7250页

作者： Liu, Lu Jiao, Shijian Han, Bing Li, Tieshan Peng, Zhouhua Dalian Maritime University School of Marine Electrical Engineering Dalian116026 China Dalian Key Laboratory of Swarm Control and Electrical Technology for Intelligent Ships Dalian116026 China State Key Laboratory of Maritime Technology and Safety Dalian116026 China Shanghai Ship and Shipping Research Institute National Engineering Research Center of Ship & Shipping Control System Shanghai200135 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China

This paper is concerned with the dynamic coverage of multiple autonomous surface vehicles (ASVs) in the presence of static and dynamic obstacles, limited communication distance, and measurement noises. A modular control method including planning, guidance, and control is proposed. At the planning level, a swarm-based dynamic coverage strategy is developed to achieve the coverage of a given domain. Both the collision avoidance and connectivity preservation issues are solved by using artificial potential fields. At the kinematic level, novel adaptive line-of-sight guidance laws are presented based on cascade extended state observers (CESOs), such that accurate guidance signals are given by compensating for time-varying sideslip angle and suppressing measurement noises. At the kinetic level, two CESOs are developed to estimate the internal model uncertainties and external environmental disturbance, and antidisturbance kinetic control laws are designed subsequently. The proposed CESOs overcome the noises sensitivity problem of classical observers, and thus facilitate the practical implementation under measurement noises. The input-to-state stability of the closed-loop system is confirmed by the Lyapunov theory and cascade stability theory. Simulation and hardware-in-the-loop experiment results are provided to demonstrate the effectiveness of the proposed swarm-based dynamic coverage method. © 1967-2012 IEEE.

关键词： Velocity measurement

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Impact of net-zero emissions on atmospheric CO_(2) concentration in China: Ideal simulations based on the GEOS-Chem model

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Science China Earth Sciences 2025年第3期68卷 867-881页

作者： Jingye TAN Jun WANG Huiqin MAO Hengmao WANG Zhiqiang LIU Meirong WANG Ran YAN Xunmei WANG Fei JIANG Frontiers Science Center for Critical Earth Material Cycling International Institute for Earth System ScienceNanjing UniversityNanjing 210023China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural ResourcesSchool of Geography and Ocean ScienceNanjing UniversityNanjing 210023China Satellite Environmental Application Center Ministry of Environmental ProtectionBeijing 100094China CMA Key Open Laboratory of Transforming Climate Resources to Economy Chongqing Institute of Meteorological SciencesChongqing 401147China State Key Laboratory of Climate System Prediction and Risk Management Key Laboratory of Meteorological DisasterMinistry of EducationCollaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing 210044China Xizang Field Station for Scientific Observation and Research on Atmospheric Water Cycle in Mêdog Xigazêand Mêdog National Climate ObservatoryXizang Meteorological ServiceLhasa 850000China

Elevated atmospheric carbon dioxide(CO_(2)) concentrations have caused global climate change such as global warming and more frequent climate extremes. Countries worldwide have proposed carbon neutrality strategies to curb the rising CO_(2) concentrations. To investigate the impact of China's carbon neutrality goal on atmospheric CO_(2) concentrations, we conducted a series of ideal simulations from 2015 to 2019 using a global 3D chemistry transport model, Goddard Earth Observing system Chemistry(GEOS-Chem). Compared with the column-averaged dry-air mole fraction of atmospheric CO_(2) (XCO_(2) ) from Orbiting Carbon Observatory-2(OCO-2) and surface CO_(2) measurements in Obs Pack, we find that GEOS-Chem effectively reproduces the spatiotemporal variability of CO_(2) . The model exhibits a root mean square error(RMSE) of 1.51 ppm(R^(2)=0.89) for OCO-2 XCO_(2) in China and 2.65 ppm(R^(2)=0.75) for surface CO_(2) concentrations at the WLG station. Further, compared to 2.83 ppm yr^(-1)in the control experiment, we suggest that net-zero CO_(2) emissions in China decelerate the increasing trends of XCO_(2) to 1.81 ppm yr^(-1),making a decrease of approximately 35.89%. Meanwhile, the seasonal cycle amplitude(SCA) of XCO_(2) is moderately reduced from 7.39±0.81 to 6.75±0.70 ppm, representing a relative reduction of 9.91%. Spatially, net-zero CO_(2) emissions induce a more significant decrease in XCO_(2) trends over northern and southern China, while their impact on SCA is more evident in northern and northeastern China. Moreover, ideal experiments demonstrate that zero fossil CO_(2) emissions lead to a greater attenuation of the linear trends of XCO_(2) by 40.81%, while the absence of terrestrial CO_(2) sinks largely diminishes the SCA by 16.61%. Additionally,trends and SCA in surface CO_(2) concentrations exhibit almost identical decreasing responses to net-zero CO_(2) emissions but display greater sensitivities compared to XCO_(2) . Overall, our study underscores the pote

关键词： XCO_(2) GEOS-Chem Carbon neutrality Net-zero emissions Surface CO_(2)concentrations

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Time-resolved characteristics of a nanosecond pulsed multi-hollow needle plate packed bed dielectric barrier discharge

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Plasma Science and technology 2024年第7期26卷 48-57页

作者：秦亮李瑶郭浩姜楠宋颖贾锐周雄峰袁皓杨德正 Key Laboratory of Materials Modification by Laser Ionand Electron Beams(Dalian University of Technology)Ministry of EducationDalian 116024People’s Republic of China School of Electrical Engineering Dalian University of TechnologyDalian 116024People’s Republic of China State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System Luoyang 471003People’s Republic of China School of Physics and Materials Engineering Dalian Minzu UniversityDalian 116600People’s Republic of China

In this paper,self-designed multi-hollow needle electrodes are used as a high-voltage electrode in a packed bed dielectric barrier discharge reactor to facilitate fast gas flow through the active discharge area and achieve large-volume stable *** dynamic characteristics of the plasma,the generated active species,and the energy transfer mechanisms in both positive discharge(PD)and negative discharge(ND)are investigated by using fast-exposure intensified charge coupled device(ICCD)images and time-resolved optical emission *** experimental results show that the discharge intensity,number of discharge channels,and discharge volume are obviously enhanced when the multi-needle electrode is replaced by a multihollow needle *** a single voltage pulse period,PD mainly develops in a streamer mode,which results in a stronger discharge current,luminous intensity,and E/N compared with the diffuse mode observed in *** PD,as the gap between dielectric beads changes from 0 to250μm,the discharge between the dielectric bead gap changes from a partial discharge to a standing filamentary micro-discharge,which allows the plasma to leave the local area and is conducive to the propagation of surface *** ND,the discharge only appears as a diffusionlike mode between the gap of dielectric beads,regardless of whether there is a discharge ***,the generation of excited states N_(2)^(+)(B^(2)∑_(u)^(+))and N2(C^(3)Π_(u))is mainly observed in PD,which is attributed to the higher E/N in PD than that in ***,the generation of the OH(A^(2)∑^(+))radical in ND is higher than in *** is not directly dominated by E/N,but mainly by the resonant energy transfer process between metastable N_(2)(A^(3)∑_(u)^(+))and OH(X^(2)Π).Furthermore,both PD and ND demonstrate obvious energy relaxation processes of electron-to-vibration and vibration-to-vibration,and no vibration-to-rotation energy relaxation process is observed.

关键词： packed bed reactor multi-hollow needle electrodes positive and negative discharges optical emission spectra time-resolved images

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A Predictive Model for Morphogenesis of a Robot Sequence Mimicking Protein Folding 14

A Predictive Model for Morphogenesis of a Robot Sequence Mim...

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14th IEEE International Conference on Cyber technology in Automation, Control, and Intelligent systems, CYBER 2024

作者： Ni, Zihao Han, Zhi Wang, Shixian Gu, Yuping Yang, Yongliang School of Artificial Intelligence Shenyang University of Technology Liaoning Shenyang110023 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China

ISBN: (纸本)9798331506056

The swarm phenomena observed in nature have inspired many control algorithms for diverse robot swarm systems. However, most of these endeavors are qualitative simulations aimed at understanding the mechanisms underlying biological swarm behavior. Reliably predicting morphologies of robot swarms from their features remains a formidable challenge. In molecular biology, the 3D structure of a protein molecule, which is a main factor of its functions, is mainly determined by its sequence of amino acids. Inspired by this, our lab developed RoboFold, a robot swarm platform for developing protein-folding-inspired methods controlling the morphologies of robot swarms. Using the data collected from this platform, we proposed a deep learning approach to predict the morphologies of swarm robotics based on their initial sequences. The goal of this research is predicting the initial sequence of robots forming the desired morphology. Preliminary results presented here demonstrated the efficacy of this method and underscore the feasibility of applying protein-folding-inspired methods to program robot swarms. © 2024 IEEE.

关键词： Microrobots

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A geometric method based on space arc for pose-configuration simultaneous planning of segmented hyper-redundant manipulators

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Science China(Technological Sciences) 2021年第11期64卷 2389-2407页

作者： HU ZhongHua YUAN Han XU WenFu YANG TaiWei LIU TianLiang LIANG Bin 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 100084China

A segmented hyper-redundant manipulator can perform complicated operation tasks in a confined space due to its high flexibility and dexterity. However, the trajectory planning in a narrow space and obstacles environment is very challenging for the manipulator. In this paper, we propose a geometry method to simultaneously plan the end-effector pose and manipulator’s configuration. Firstly, the geometries of each segment are described by an inscribed arc(IA) and a circumscribed arc(CA). Then,the whole kinematics chain is considered as an inscribed curve(IC) or a circumscribed curve(CC) which are composed of multiple IAs or CAs. Furthermore, the IC and CC of the manipulator are divided into multiple spatial single-arc and double-arc groups according to requirements. The pose-configuration simultaneous planning is realized by the spatial single-arc/double-arc modeling and joints angles solving. By numerical iteration, the spatial arcs’ parameters are determined according to desired pose and boundary condition of obstacle avoidance. The angles of joints are analytically solved when the above parameters are known. Finally, a narrow space detection task is simulated and experimented respectively. The results verify the proposed method.

关键词： segmented hyper-redundant manipulator pose-configuration simultaneous planning spatial arc modeling obstacle avoidance geometric planning

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Synthesized colonoscopy dataset from high-fidelity virtual colon with abnormal simulation

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Computers in Biology and Medicine 2025年 186卷 109672-109672页

作者： He, Dongdong Liu, Ziteng Yin, Xunhai Liu, Hao Gao, Wenpeng Fu, Yili School of Life Science and Technology Harbin Institute of Technology Harbin150080 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150080 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Department of Gastroenterology The First Affiliated Hospital of Harbin Medical University Harbin150001 China

With the advent of the deep learning-based colonoscopy system, the need for a vast amount of high-quality colonoscopy image datasets for training is crucial. However, the generalization ability of deep learning models is challenged by the limited availability of colonoscopy images due to regulatory restrictions and privacy concerns. In this paper, we propose a method for rendering high-fidelity 3D colon models and synthesizing diversified colonoscopy images with abnormalities such as polyps, bleeding, and ulcers, which can be used to train deep learning models. The geometric model of the colon is derived from CT images. We employed dedicated surface mesh deformation to mimic the shapes of polyps and ulcers and applied texture mapping techniques to generate realistic, lifelike appearances. The generated polyp models were then attached to the inner surface of the colon model, while the ulcers were created directly on the inner surface of the colon model. To realistically model blood behavior, we developed a simulation of the blood diffusion process on the colon's inner surface and colored vertices in the traversed region to reflect blood flow. Ultimately, we generated a comprehensive dataset comprising high-fidelity rendered colonoscopy images with the abnormalities. To validate the effectiveness of the synthesized colonoscopy dataset, we trained state-of-the-art deep learning models on it and other publicly available datasets and assessed the performance of these models in abnormal classification, detection, and segmentation. Notably, the models trained on the synthesized dataset exhibit an enhanced performance in the aforementioned tasks, as evident from the results. © 2025 Elsevier Ltd

关键词： Digital elevation model

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