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

作者： Dong, Huijie Zhao, Chunyang Qiao, Tiezhu Wang, Jian Chen, Di Meng, Yan Yu, Junzhi Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Chinese Academy of Sciences Laboratory of Cognitive and Decision Intelligence for Complex System Institute of Automation Beijing100190 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China Guangdong Ocean University College of Electronics and Information Engineering Zhanjiang524088 China

ISBN: (纸本)9798350327182

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. © 2023 IEEE.

关键词： Fish

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RINGO: Real-time Navigation with a Guiding Trajectory for Aerial Manipulators in Unknown Environments

arXiv

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arXiv 2025年

作者： Zhang, Zhaopeng Wu, Shizhen Guo, Chenfeng Fang, Yongchun Han, Jianda Liang, Xiao Institute of Robotics and Automatic Information System College of Artificial Intelligence Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China

Motion planning for aerial manipulators in constrained environments has typically been limited to known environments or simplified to that of multi-rotors, which leads to poor adaptability and overly conservative trajectories. This paper presents RINGO: Real-time Navigation with a Guiding Trajectory, a novel planning framework that enables aerial manipulators to navigate unknown environments in real time. The proposed method simultaneously considers the positions of both the multi-rotor and the end-effector. A pre-obtained multi-rotor trajectory serves as a guiding reference, allowing the end-effector to generate a smooth, collision-free, and workspace-compatible trajectory. Leveraging the convex hull property of B-spline curves, we theoretically guarantee that the trajectory remains within the reachable workspace. To the best of our knowledge, this is the first work that enables real-time navigation of aerial manipulators in unknown environments. The simulation and experimental results show the effectiveness of the proposed method. The proposed method generates less conservative trajectories than approaches that consider only the multi-rotor. © 2025, CC BY.

关键词： Manipulators

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A Magnetically Steerable and Automatically Propulsion Guidewire Robot system for Vascular Interventional Surgery

A Magnetically Steerable and Automatically Propulsion Guidew...

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2022 IEEE International Conference on Real-Time Computing and robotics, RCAR 2022

作者： Fu, Shixiong Zhang, Shanxiu Yin, Meng Wang, Shu Li, Dong Wu, Xinyu Du, Shiwei Xu, Tiantian Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518055 China SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China Shenzhen Key Laboratory of Minimally Invasive Surgical Robotics and System Shenzhen Institute of Advanced Technology CAS Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China South China Hospital of Shenzhen University Department of Neurosurgery Shenzhen518111 China

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

Magnetically soft continuum robot with automatic navigation capability has great potential to improve the treatment conventional vascular interventional surgery, which exists many problems such as long procedure time and high radiation for doctors to manipulate the passive guidewire. This paper proposes a novel guidewire robot system with magnetically steering and automatically propulsion ability. Actuated by an external magnetic field, the system is able to greatly increase the autonomy of conventional guidewires through the efficient coordination of steering and propulsion. We model the kinematics of autonomous propulsion and magnetically actuation steering separately. Then, the steering performance of the guidewire robot is validated under different magnetic field magnitudes and directions. Finally, two scenario application experiments are implemented to demonstrate the automatic navigation capability of the proposed guidewire robot in a simulated clinical environment. The proposed guidewire robot system provides an effective solution for advancing the automation of vascular interventional surgery. © 2022 IEEE.

关键词： Propulsion

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Initialization is Critical to Whether Transformers Fit Composite Functions by Reasoning or Memorizing 38

Initialization is Critical to Whether Transformers Fit Compo...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Zhang, Zhongwang Lin, Pengxiao Wang, Zhiwei Zhang, Yaoyu Xu, Zhi-Qin John Institute of Natural Sciences MOE-LSC Shanghai Jiao Tong University China School of Mathematical Sciences Shanghai Jiao Tong University China Key Laboratory of Marine Intelligent Equipment and System Ministry of Education China Shanghai Seres Information Technology Co. Ltd. Shanghai China Center for LLM Institute for Advanced Algorithms Research Shanghai China

Transformers have shown impressive capabilities across various tasks, but their performance on compositional problems remains a topic of debate. In this work, we investigate the mechanisms of how transformers behave on unseen compositional tasks. We discover that the parameter initialization scale plays a critical role in determining whether the model learns inferential (reasoning-based) solutions, which capture the underlying compositional primitives, or symmetric (memory-based) solutions, which simply memorize mappings without understanding the compositional structure. By analyzing the information flow and vector representations within the model, we reveal the distinct mechanisms underlying these solution types. We further find that inferential (reasoning-based) solutions exhibit low complexity bias, which we hypothesize is a key factor enabling them to learn individual mappings for single anchors. We validate our conclusions on various real-world datasets. Our findings provide valuable insights into the role of initialization scale in tuning the reasoning and memorizing ability and we propose the initialization rate γ to be a convenient tunable hyper-parameter in common deep learning frameworks, where 1/dγin is the standard deviation of parameters of the layer with din input neurons. © 2024 Neural information processing systems foundation. All rights reserved.

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Brillouin optical correlation domain analysis based on a phase-chaos laser

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advanced Photonics Nexus 2024年第6期3卷 106-116页

作者： Lintao Niu Yahui Wang Jing Chen Haochen Huang Lijun Qiao Mingjiang Zhang Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control SystemMinistry of EducationTaiyuanChina Taiyuan University of Technology College of Physics and OptoelectronicsTaiyuanChina Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering TaiyuanChina

The physical mechanism of gain motivation is the main theoretical bottleneck that restricts the signal-to-noise ratio(SNR)and results in a mono-merit implementation for the existing stimulated Brillouin scattering-based fiber sensors.A phase-chaos laser(PCL)is proposed and introduced in the Brillouin optical correlation domain analysis(BOCDA)scheme to promote the SNR and achieve a high-accuracy *** PCL characteristics are presented,and a theoretical model of chaos gain accumulation and extraction is ***,the simulation results reveal that the SNR is improved by 5.56 dB,and the signal-to-background noise ratio(SBR)of the Brillouin gain spectrum(BGS)is promoted by 8.28 dB with a 100-km sensing ***,the PCL is experimentally *** the proof-of-concept experiment,the accuracy of the Brillouin frequency shift is upgraded to 0.64 MHz,and the SBR of BGS is improved by 10.77 *** PCL provides a new research direction for optical chaos,and the PCL-BOCDA showcases a promising future for optimal-merit-coupling sensing and its application.

关键词： phase-chaos laser distributed fiber sensing stimulated Brillouin scattering high signal-to-noise ratio

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3D bioprinting of a dermal scaffold for full-thickness skin tissue regeneration

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Bio-Design and Manufacturing 2025年第1期8卷 68-84,I0039-I0041页

作者： Lu Han Zixian Liu Meng Li Zhizhong Shen Jianming Wang Shengbo Sang Shanxi Key Laboratory of Micro Nano Sensors&Artificial Intelligence Perception College of Electronic Information and Optical EngineeringTaiyuan University of TechnologyTaiyuan 030024China Key Laboratory of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of TechnologyTaiyuan 030024China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan 030024China Shanxi Research Institute of 6D Artificial Intelligence Biomedical Science Taiyuan 030031China General Hospital of TISCO Taiyuan 030809China

Dermal substitutes have provided a template for the regeneration and reconstruction of the ***,the healed skin tissue often exhibits abnormal morphology and functionality,including scarring and *** this study,a composite bioink composed of methacrylated gelatin(GelMA)and chitosan oligosaccharide(COS)was proposed for printing a dermal scaffold using digital light processing(DLP)*** GelMA/COS bioink exhibited suitable porosity,swelling,degradation rate,and mechanical *** inclusion of COS demonstrated antibacterial effects against both Gram positive and Gram-negative bacteria,while simultaneously fostering the proliferation of human dermal fibroblasts(HDFs).Additionally,the application of COS could effectively reduce the expression levels of fibrosis-related genes,such as collagen I,collagen III,and fibronectin *** three-dimensionally printed cell-laden dermal scaffold exhibited excellent shape fidelity and high cellular viability,facilitating the extension of HDFs along the scaffold and the simultaneous secretion of extracellular matrix ***,the HDF-laden dermal scaffold transplanted into full-thickness skin defect sites in nude mice was shown to accelerate wound closure,reduce inflammation,and improve wound ***,the DLP-printed dermal scaffold provides an appealing approach for effectively treating full-thickness skin defects in clinical settings.

关键词： 3D printing Dermal scaffold Photo-cross-linking Skin tissue regeneration

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Highly sensitive piezoresistive and thermally responsive fibrous networks from the in situ growth of PEDOT on MWCNT-decorated electrospun PU fibers for pressure and temperature sensing

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Microsystems & Nanoengineering 2023年第5期9卷 73-85页

作者： Yunyun Luo Libo Zhao Guoxi Luo Linxi Dong Yong Xia Min Li Ziping Li Kaifei Wang Ryutaro Maeda Zhuangde Jiang State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesXi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and SystemXi’an Jiaotong UniversityXi’anChina School of Mechanical Engineering Xi’an Jiaotong UniversityXi’anChina Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing YantaiChina Ministry of Education Engineering Research Center of Smart Microsensors and Microsystems College of Electronics and InformationHangzhou Dianzi UniversityHangzhouChina Department of Emergency The First Affiliated Hospital of Xi’an Jiaotong UniversityXi’anChina

Flexible electronics have demonstrated various strategies to enhance the sensory ability for tactile perception and wearable physiological *** microstructures have attracted much interest because of their excellent mechanical properties and ***,a structurally robust fibrous mat was first fabricated by electrospinning,followed by a sequential process of functionalization utilizing ultrasonication treatment and in situ polymerization *** polyurethane(PU)microfibers were anchored with multi-walled carbon nanotubes(MWCNTs)to form conductive paths along each fiber by a scalable ultrasonic cavitation treatment in an MWCNT ***,a layer of poly(3,4-ethylene dioxythiophene)(PEDOT)was grown on the surface of PU fibers decorated with MWCNTs to enhance the conductive conjunctions of *** to the superior electromechanical behaviors and mechanical reinforcement of PEDOT,the PEDOT/MWCNT@PU mat-based device exhibits a wide working range(0–70 kPa),high sensitivity(1.6 kPa−1),and good mechanical robustness(over 18,000 cycles).The PEDOT/MWCNT@PU mat-based sensor also demonstrates a good linear response to different temperature variations because of the thermoelectricity of the PEDOT/MWCNT *** novel strategy for the fabrication of multifunctional fibrous mats provides a promising opportunity for future applications for high-performance wearable devices.

关键词： fibers PEDOT conductive

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Real-time Terrain Recognition based on Transformer and Gait Prediction based on CNN-LSTM-Attention for Exosuit

Real-time Terrain Recognition based on Transformer and Gait ...

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

作者： Yang, Fangliang Chen, Chunjie Wang, Zhuo Xu, Yinsheng Liu, Yao Wu, Xinyu University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Shenzhen518055 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China Guilin University of Technology Guilin541004 China

ISBN: (纸本)9798350327182

For wearable soft exosuits, an imprecise control strategy can easily injure the wearer, while real-time terrain recognition and accurate gait phase estimation can effectively improve the control strategy of the exosuit and make the wearer comfortable and safe. In this paper, a real-time terrain recognition algorithm based on Transformer and a gait estimation algorithm based on CNN-LSTM-Attention are implemented. The Transformer-based recognition of different terrains improves the recognition accuracy to some extent, and the CNN-LSTM-Attention based feature extraction for temporal signals such as gait phase is also extremely noticeable. Experiments show that the Transformer-based algorithm achieves 99.64 % recognition accuracy in six different terrain environments. In the gait phase estimation experiment, CNN-LSTM-CBAM achieved the best performance with an evaluation index r2 of 0.9221. The aforementioned terrain recognition algorithms and gait phase estimation algorithms may have a positive impact on soft exosuit and dynamic prosthetics research. © 2023 IEEE.

关键词： Landforms

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A Robust Multi-AGV Cooperative Path Planning Method Considering Spatiotemporal Distance 5

A Robust Multi-AGV Cooperative Path Planning Method Consider...

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5th International Conference on Computer Engineering and intelligent Control, ICCEIC 2024

作者： Chen, Maolin Chen, Songhang Lian, Mingchang School of Advanced Manufacturing Fuzhou University Quanzhou China Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences Fuzhou China Fujian Provincial Key Laboratory of Intelligent Identification and Control of Complex Dynamic System Quanzhou China Fujian College University of Chinese Academy of Sciences Fuzhou China Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou China

ISBN: (纸本)9798331507992

With the widespread application of Automated Guided Vehicles (AGVs) in warehousing and logistics systems, the optimization of multi-AGV path planning has become a critical issue. Current methods primarily focus on minimizing operating time and energy consumption but often overlook spatiotemporal distances between paths, leading to frequent path conflicts and interferences in the system. This paper proposes a neural network based time window estimation model, designed to generate time windows that better align with dynamic environments. Based on this model, we introduce a collaborative multi-AGV path planning method that optimizes spatiotemporal distances between paths. Compared to the Conflict-Based Search (CBS) method, this approach significantly improves the spatiotemporal distance between AGVs during task execution, enhancing the robustness of AGV clusters while only marginally increasing time costs. © 2024 IEEE.

关键词： Automatic guided vehicles

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Hole-Peg Assembly Strategy Based on Deep Reinforcement Learning 5th

Hole-Peg Assembly Strategy Based on Deep Reinforcement Learn...

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5th International Conference on Cognitive systems and Signal Processing, ICCSIP 2020

作者： Zhang, Xiaodong Ding, Pengchao Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Application Beijing Institute of Spacecraft System Engineering CAST Beijing100086 China Institute of Technology Harbin Heilongjiang150001 China

ISBN: (纸本)9789811623356

Hole-peg assembly using robot is widely used to validate the abilities of autonomous assembly task. Currently, the autonomous assembly is mainly depended on the high precision of position, force measurement and the compliant control method. The assembly process is complicated and the ability in unknown situations is relatively low. In this paper, a kind of assembly strategy based on deep reinforcement learning is proposed using the TD3 reinforcement learning algorithm based on DDPG and an adaptive annealing guide is added into the exploration process which greatly accelerates the convergence rate of deep reinforcement learning. The assembly task can be finished by the intelligent agent based on the measurement information of force-moment and the pose. In this paper, the training and verification of assembly verification is realized on the V-rep simulation platform and the UR5 manipulator. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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