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Magnetically Driven Soft Continuum Microrobot for Intravascular Operations in Microscale

Cyborg and Bionic systems 2022年第1期2022卷 265-272页

作者： Dan Liu Xiaoming Liu Zhuo Chen Zhaofeng Zuo Xiaoqing Tang Qiang Huang Tatsuo Arai Key Laboratory of Biomimetic Robots and Sytems Ministry of EducationState Key Laboratory of Ielligent Control and Decision.of Complex SystemBeijing Advanced Innovation Center for Itelligent Robots and Systemsand School of Mechatronical EngineeringBeijing Institute of TechnologyBejing 100081China Center for Neuroscience and Biomedical Engineering The University of Electro-CommunicationsTokyo 1828585Japan

Remotely controlled soft continuum robots with active steering capability have broad prospects in medical ***,conventional continuum robots have the miniaturization *** paper presents a microscale soft continuum microrobot with steering and locomotion capabilties based on magnetic field *** magnetically driven soft continuum microrobot is made of NdFeB particles and polyd imethylsiloxane(PDMS),and it can be as small as 200 pum in ***,a hydrogel layer is covered on the surface of the microrobot,which not only overcomes the adhesion force between the microobjects and the soft tip but also reduces the friction between the microrobot and *** performance test indicates the soft continuum microrobot featured excellent control and steering *** experimental results demonstrate that the soft continuum microrobot can travel through the microfluidic channel by its own vibration and flexibly steer in a bifurcation ***,the micromanipulation of microbeads in the microfluidic channels proves that the proposed microscale soft continuum microrobot has a great potential for intravascu lar manipu lation.

关键词： friction robot overcome

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Modeling and Simulation of an Elastic Passive Joint for Non-flipping Jumping Robot

Modeling and Simulation of an Elastic Passive Joint for Non-...

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

作者： Qi Li Liang Peng Zhiyuan Wu Pengda Ye Weitao Zhang Yi Xu Qing Shi Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

To enhance the environmental adaptability of small-sized robots, jumping is commonly employed to achieve high mobility and obstacle-clearing capabilities. However, the prevalent problem of flipping in jumping robots limits their practical applications. Instead of adding extra control mechanisms and actuators, we propose an elastic passive joint (EPJ) to mitigate flipping. By incorporating a revolute joint, a switch, and a spring at the base of the hindleg, the leg can rotate around the body during the take-off phase, with the spring absorbing angular kinetic energy to reduce excessive angular velocity. We conducted dynamic modeling and a series of simulations to optimize the EPJ’s position and stiffness. The simulation results indicate that with the EPJ in operation, adjusting the axis position slightly results in a zero-point for angular velocity. Additionally, the optimal spring stiffness of 1566 N/m ensures a non-flipping jump, which decreases the jumping height but improves the jumping distance.

关键词： Legged locomotion Analytical models Simulation Prototypes Switches Angular velocity Real-time systems

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A Fault Diagnosis Method for High-Speed Train Wheelset Bearings Based on Deep Learning 5

A Fault Diagnosis Method for High-Speed Train Wheelset Beari...

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5th World Conference on Mechanical Engineering and Intelligent Manufacturing, WCMEIM 2022

作者： Zheng, Hu Tan, Libin Yu, Xiaoliu Anhui University of Technology AnHui Province Key Laboratory of Special Heavy Load Robot Ma'anshan China Beijing Advanced Innovation Center for Intelligent China Robots and Systems Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665473699

Aiming at the problem that the traditional fault diagnosis method is difficult to effectively extract the fault features of the high-speed train wheelset bearing signal, this paper proposes a fault diagnosis method based on the two-dimensional image method. First, the one-dimensional vibration signal is converted into a Two-dimensional grayscale image, eliminating the influence of expert experience on the feature extraction process. Then an improved network model is proposed, which can automate the process of feature extraction and fault diagnosis. Finally, this paper simulates the complex driving environment of high-speed trains by adding noise with different SNRs to the vibration signal and analyzes the influence of noise on the diagnostic ability of the method. The results show that the method is effective. © 2022 IEEE.

关键词： Failure analysis

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Collision-free Motion Generation Based on Stochastic Optimization and Composite Signed Distance Field Networks of Articulated Robot

arXiv

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arXiv 2023年

作者： Liu, Baolin Jiang, Gedong Zhao, Fei Mei, Xuesong The State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong University Shaanxi Key Laboratory of Intelligent Robots School of Mechanical Engineering Xi’an Jiaotong University Shaanxi Xi’an710049 China

Safe robot motion generation is critical for practical applications from manufacturing to homes. In this work, we proposed a stochastic optimization-based motion generation method to generate collision-free and time-optimal motion for the articulated robot represented by composite signed distance field (SDF) networks. First, we propose composite SDF networks to learn the SDF for articulated robots. The learned composite SDF networks combined with the kinematics of the robot allow for quick and accurate estimates of the minimum distance between the robot and obstacles in a batch fashion. Then, a stochastic optimization-based trajectory planning algorithm generates a spatial-optimized and collision-free trajectory offline with the learned composite SDF networks. This stochastic trajectory planner is formulated as a Bayesian Inference problem with a time-normalized Gaussian process prior and exponential likelihood function. The Gaussian process prior can enforce initial and goal position constraints in Configuration Space. Besides, it can encode the correlation of waypoints in time series. The likelihood function aims at encoding task-related cost terms, such as collision avoidance, trajectory length penalty, boundary avoidance, etc. The kernel updating strategies combined with model-predictive path integral (MPPI) is proposed to solve the maximum a posteriori inference problems. Lastly, we integrate the learned composite SDF networks into the trajectory planning algorithm and apply it to a Franka Emika Panda robot. The simulation and experiment results validate the effectiveness of the proposed method. Copyright © 2023, The Authors. All rights reserved.

关键词： Collision avoidance

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Dynamic Obstacle Avoidance for Magnetic Helical Microrobots Based on Deep Reinforcement Learning

Dynamic Obstacle Avoidance for Magnetic Helical Microrobots ...

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

作者： Yukang Qiu Yaozhen Hou Haotian Yang Yigao Gao Hen-Wei Huang Qing Shi Qiang Huang Huaping Wang Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China Laboratory for Translational Engineering Harvard Medical School Cambridge MA USA Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

Magnetic helical microrobots hold immense promise in biomedical domains owing to their compact size and efficient propulsion capabilities. However, navigating these microrobots through dynamic and unstructured environments, particularly when encountering numerous dynamic obstacles, remains a formidable challenge. In the study, a control framework based on deep reinforcement learning (DRL) with the objective of guiding a microrobot through dynamic obstacles towards specified target goals is introduced. Initially, we design and fabricate a microdrill capable of propulsion via external magnetic rotating fields produced by our magnetic actuation system. Subsequently, we construct a custom training environment, adhering to the OpenAI gym interface, to serve as the simulator for training purposes. Utilizing the proximal policy optimization algorithm, we conduct training of the navigation policy within this simulator. Simulations and experimental validations conducted in dynamic environments affirms the efficacy of the proposed method.

关键词： Training Navigation Magnetic cores Heuristic algorithms Magnetic domains Propulsion Deep reinforcement learning

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Identification of Dynamic Active Sites Among Cu Species Derived from MOFs@CuPc for Electrocatalytic Nitrate Reduction Reaction to Ammonia

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Nano-Micro Letters 2023年第8期15卷 20-34页

作者： Xue‑Yang Ji Ke Sun Zhi‑Kun Liu Xinghui Liu Weikang Dong Xintao Zuo Ruiwen Shao Jun Tao Key Laboratory of Cluster Science of Ministry of Education School of Chemistry and Chemical EngineeringLiangxiang CampusBeijing Institute of TechnologyBeijing 102488People’s Republic of China Department of Chemistry Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea Department of Materials Physics Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMTS)ThandalamChennaiTamilnadu 602105India Beijing Advanced Innovation Center for Intelligent Robots and Systems and Institute of Engineering Medicine Beijing Institute of TechnologyBeijing 100081People’s Republic of China Key Laboratory of Bio‑inspired Smart Interfacial Science and Technology of Ministry of Education School of ChemistryBeihang UniversityBeijing 100191People’s Republic of China

Direct electrochemical nitrate reduction reaction(NITRR)is a promising strategy to alleviate the unbalanced nitrogen cycle while achieving the electrosynthesis of ***,the restructuration of the high-activity Cu-based electrocatalysts in the NITRR process has hindered the identification of dynamical active sites and in-depth investigation of the catalytic ***,Cu species(single-atom,clusters,and nanoparticles)with tunable loading supported on N-doped TiO_(2)/C are successfully manufactured with MOFs@CuPc precursors via the pre-anchor and post-pyrolysis *** behavior among Cu species is co-dependent on the Cu loading and reaction potential,as evidenced by the advanced operando X-ray absorption spectroscopy,and there exists an incompletely reversible transformation of the restructured structure to the initial ***,restructured CuN_(4)&Cu_(4) deliver the high NH_(3) yield of 88.2 mmol h^(−1)g_(cata)^(−1) and FE(~94.3%)at−0.75 V,resulting from the optimal adsorption of NO_(3)^(−) as well as the rapid conversion of^(*)NH_(2)OH to^(*)NH_(2) intermediates originated from the modulation of charge distribution and d-band center for Cu *** work not only uncovers CuN_(4)&Cu_(4) have the promising NITRR but also identifies the dynamic Cu species active sites that play a critical role in the efficient electrocatalytic reduction in nitrate to ammonia.

关键词： Metal-organic frameworks Copper phthalocyanine Electrocatalytic nitrate reduction reaction

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A Novel Smart Production Line Data Perception System Based on OPC UA 5

A Novel Smart Production Line Data Perception System Based o...

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5th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021

作者： Lu, Xufeng Tao, Tao Sun, Zheng Wang, Li Yang, Hanbo Zhao, Fei Jiang, Gedong Mei, Xuesong School of Mechanical Engineering Xi'An Jiaotong University Xi'an China State Key Laboratory for Manufacturing Systems Engineering Xi'an China Shaanxi Key Laboratory of Intelligent Robots Xi'an China

ISBN: (纸本)9781665415989

With the rapid development of information and communication technology (ICT), traditional manufacturing is undergoing an upgrade and transformation to smart manufacturing. In order to achieve intelligent management and control of production process, data perception (DP) is the primary problem to be investigated during the transformation of current production line (PL). However, due to the numerous equipment types, heterogeneous communication protocols and interfaces, the cyber system and the physical world are severely separated, resulting in the phenomenon of information islands. In this paper, we propose a novel DP system architecture for smart production line (SPL) based on OPC UA, which is compatible with multiple device system protocols as well as provides a unified interaction interface for data-driven applications. Data collection and result feedback based on the protocol mapping and conversion are realized by flexibly utilizing two communication patterns of OPC UA, namely client-server (CS) and publish-subscribe (PubSub). The local and cloud case studies strongly verify the feasibility and prospect of the DP system. © 2021 IEEE.

关键词： Metadata

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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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A Modular Spiking Neural Network-Based Neuro-Robotic System for Exploring Embodied Intelligence*

A Modular Spiking Neural Network-Based Neuro-Robotic System ...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Zhe Chen Tao Sun Xie Chen Shingo Shimoda Huaping Wang Qiang Huang Qing Shi School of Medical Technology Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Ministry of Education Beijing China Graduate School of Medicine Nagoya University Nagoya Aichi Japan

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Bio-inspired construction of modular biological neural networks (BNNs) is gaining attention due to their innate stable inter-modular signal transmission ability, which is thought to underlying the emergence of biological intelligence. However, the complicated, laborious fabrication of BNNs with structural and functional connectivity of interest in vitro limits the further exploration of embodied intelligence. In this work, we propose a modular spiking neural network (SNN)-based neuro-robotic system by concurrently running SNN modeling and robot simulation. We show that the modeled mSNNs present complex calcium dynamics resembling mBNNs. In particular, spontaneous periodic network-wide bursts were observed in the mSNN, which could be further suppressed partially or completely with global chemical modulation. Moreover, we demonstrate that after complete suppression, intermodular signal transmission can still be evoked reliably via local stimulation. Therefore, the modeled mSNNs could either achieve reliable trans-modular signal transmission or add adjustable false-positive noise signals (spontaneous bursts). By interconnecting the modeled mSNNs with the simulated mobile robot, active obstacle avoidance and target tracking can be achieved. We further show that spontaneous noise impairs robot performance, which indicates the importance of suppressing spontaneous burst activities of modular networks for the reliable execution of robot tasks. The proposed neuro-robotic system embodies spiking neural networks with a mobile robot to interact with the external world, which paves the way for exploring the arising of more complex biological intelligence.

关键词： Target tracking Biological system modeling Calcium Noise Spiking neural networks Trajectory Reliability Mobile robots Collision avoidance Biological neural networks

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Design of a Miniature Flapping-Wing Robot Capable of Quick and Energy-Efficient Takeoff

Design of a Miniature Flapping-Wing Robot Capable of Quick a...

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IEEE International Conference on Robotics and Biomimetics

作者： Yi Xu Yishi Shen Liang Peng Qi Li Jin Yu Shi Zhang Qing Shi Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Micro areal vehicles are widely used in civilian and military applications, but it is still challenging for them to take off in place with both high speed and energy utilization efficiency. Inspired by locusts, one solution is to integrate the flying with the jumping motion, utilizing the speed generated by jumping to provide sufficient aerodynamic forces for the flight. In this paper, we develop a miniature locust-inspired robot capable of jumping and flying. By coupling the jumpingleg mechanism and flapping-wing mechanism, the robot has a compacted size (with a body length of 15 cm and a weight of 23 g). Furthermore, we design a cascaded jump-flying controller to achieve stable transition and maneuverable flight. A series of experimental results reveal that the robot achieves a maximum jumping height of 50 cm and a minimum flying turning radius of 0.8 m. Remarkably, the robot is capable of taking off in place through controlling the hindleg and wings coordinately.

关键词： Couplings Attitude control Robot kinematics Biomimetics Robot sensing systems Turning Control systems Energy efficiency Sensors Biosensors

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