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arXiv 2021年

作者： Huang, Qiangqiang Pu, Can Khosoussi, Kasra Rosen, David M. Fourie, Dehann How, Jonathan P. Leonard, John J. MIT Computer Science and Artificial Intelligence Laboratory CambridgeMA02139 United States MIT Department of Nuclear Science and Engineering CambridgeMA02139 United States Robotics and Autonomous Systems Group DATA61 CSIRO BrisbaneQLD4069 Australia Northeastern University Department of Electrical and Computer Engineering BostonMA02115 United States NavAbility BostonMA02110 United States MIT Department of Aeronautical and Astronautical Engineering CambridgeMA02139 United States

This paper presents normalizing flows for incremental smoothing and mapping (NF-iSAM), a novel algorithm for inferring the full posterior distribution in SLAM problems with nonlinear measurement models and non-Gaussian factors. NF-iSAM exploits the expressive power of neural networks, and trains normalizing flows to model and sample the full posterior. By leveraging the Bayes tree, NF-iSAM enables efficient incremental updates similar to iSAM2, albeit in the more challenging non-Gaussian setting. We demonstrate the advantages of NF-iSAM over state-of-the-art point and distribution estimation algorithms using range-only SLAM problems with data association ambiguity. NF-iSAM presents superior accuracy in describing the posterior beliefs of continuous variables (e.g., position) and discrete variables (e.g., data association). Copyright © 2021, The Authors. All rights reserved.

关键词： Gaussian noise (electronic)

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Preliminary study in motion assistance of soft exoskeleton robot based on data-driven kinematics model learning

Preliminary study in motion assistance of soft exoskeleton r...

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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Li, Ning Li, Jialin Yang, Tie Yang, Yang Yu, Peng Liu, Lianqing Qin, Wanglin Xi, Ning Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing University of Chinese Academy of Sciences Beijing100049 China Shenyang Jianzhu University Institutes for Robotics and Intelligent Manufacturing Shenyang110000 China Emerging Technologies Institute Department of Industrial and Manufacturing Systems Engineering University of Hong Kong Pokfulam Hong Kong

ISBN: (纸本)9781728163215

Exoskeleton is widely used to enhance human mobility. Especially in recent years, the soft exoskeleton robots have developed rapidly, which could realize natural human-machine physiological coupling. However, the motion patterns and physiological parameters are significant various between different subjects. The parameters of the soft exoskeletons change differently during motion. In this paper, we proposed kinematics model based on data-driven model learning. The proposed model learning method not only has the fast learning ability of model-based controller, but also has the adaptability of sensor-based controller. Firstly, we use the data of the rigid model to pre-train the kinematics model network, which can make the output of the network consistent with the kinematics model. Then, we use the sensors to collect the actual motion data and send the motion data into the pre-trained neural network model. By increasing the iteration times of training, the network model outputs model parameters that are consistent with the trend of the simulation model. Through the training and learning of the bionic motion platform, the speed of learning adaptation in human body can be accelerated. © 2019 IEEE.

关键词： Physiological models

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Programmable cell aggregation by a synthetic biosilicification approach

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iScience 2025年第6期28卷

作者： Wang, Qing Sun, Jing Zang, Lei Yao, Huaxiong Wang, Lin Zhu, Runtao Li, Jie Zeng, Simin Tang, Hongting Wang, Teng Liu, Ji Wang, Bo Li, Bo Liu, Zhiyuan Dai, Zhuojun State Key Laboratory of Quantitative Synthetic Biology Shenzhen Institute of Synthetic Biology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Chemistry and Chemical Engineering Harbin Institute of Technology Harbin 150001 China Center of Neural Engineering CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen 518055 China Department of Civil Engineering University of Nottingham Ningbo China 199 Taikang East Road Ningbo 315100 China

Programmable cell aggregation offers valuable insights into the natural development of synthetic multicellular systems and enables precise control over spatial organization and material structuring. Previous efforts have focused on modifying cells with designed organic-based adhesive modules and assembling cells into defined patterns. Here, we present a different approach to guide cell assembly by tuning the organic-inorganic interactions. Our method involves engineering cells to express a silicifying peptide on their surfaces, which promotes silica deposition on the cell walls. This peptide simultaneously binds to the silica synthesized on adjacent cells, triggering cell clustering. The engineered cells exhibit rapid aggregation, with approximately 95% of cells assembling within 15 min. We further show that this capability can facilitate materials assembly and chemical production. Our biosilicification-based approach offers novel insights into natural multicellularity mechanisms and holds potential for applications in biomanufacturing and materials engineering. © 2025 The Author(s)

关键词： Bioengineering Biomaterials Synthetic biology

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Autonomous docking and energy sharing between two types of robotic agents

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IFAC-PapersOnLine 2018年第29期51卷 406-411页

作者： Babi, Anja Mandi, Filip Vasiljevi, Goran Mikovi, Nikola Faculty of Electrical Engineering and Computing LABUST Laboratory for Underwater Systems and Technologies University of Zagreb Unska 3 Zagreb Croatia Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems University of Zagreb Unska 3 Zagreb Croatia

In order to achieve long-term autonomy after deployment, a method of energy sharing within a heterogeneous swarm of marine robots was devised and implemented. This paper describes hardware and software solutions as well as guidance and control algorithms developed with the goal of allowing powerful energy-rich overactuated surface platforms to approach, dock, and wirelessly recharge less mobile sensor-rich agents upon request using visual servoing. The basic image processing algorithm uses data acquired by the Microsoft Kinect sensor alternating between RGB and infra-red camera modes, depending on lighting conditions. The full search and docking procedure developed for long-term operation is described. The results of a series of experiments done both in an indoor testbed and in realistic outdoor conditions are discussed and some goals for future work are given. © 2018

关键词： Autonomous agents

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Kalman filtering technique for attitude estimation on SO(3) using single inertial vector observations

Kalman filtering technique for attitude estimation on SO(3) ...

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OCEANS

作者： Joel Reis Pedro Batista Paulo Oliveira Carlos Silvestre Faculty of Science and Technology University of Macau Taipa Macao China Institute for Systems and Robotics LARSyS Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal LAETA - Associated Laboratory for Energy Transports and Aeronautics IDMEC - Institute of Mechanical Engineering Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal Instituto Superior Técnico Universidade de Lisboa Portugal

ISBN: (纸本)9781665427883

This paper presents an attitude estimation methodology for robotic platforms equipped with a set of rate gyros that can implicitly measure the Earth’s rotation rate. As is well known, standard strategies for attitude determination rely on explicit body-fixed measurements of at least two inertial reference vectors. In this work, the Earth’s spin is regarded as one of two constant inertial reference vectors. However, because that spin is only implicitly measured, we first implement a Kalman filter to obtain an estimate of it. This filter also yields: unbiased estimates of the second inertial reference vector, which is explicitly measured in the body-fixed frame; and estimates of two biases related to the sensor measurements. The platform’s rotation matrix is then computed using a Kalman-based observer evolving on the manifold $SO(3)$ that is driven by the output of the first filter. Realistic simulation results are presented to showcase the performance of the proposed technique in two different scenarios.

关键词： Manifolds Simulation Sea measurements Estimation Observers Robot sensing systems Gyroscopes

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Author Correction: Super-resolution multicolor fluorescence microscopy enabled by an apochromatic super-oscillatory lens with extended depth-of-focus

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Nature communications 2024年第1期15卷 1510页

作者： Wenli Li Pei He Dangyuan Lei Yulong Fan Yangtao Du Bo Gao Zhiqin Chu Longqiu Li Kaipeng Liu Chengxu An Weizheng Yuan Yiting Yu Ningbo Institute of Northwestern Polytechnical University College of Mechanical Engineering Northwestern Polytechnical University Xi'an 710072 China. Key Laboratory of Micro/Nano Systems for Aerospace (Ministry of Education) Northwestern Polytechnical University Xi'an 710072 China. Shaanxi Province Key Laboratory of Micro and Nano Electro-Mechanical Systems Northwestern Polytechnical University Xi'an 710072 China. Department of Materials Science and Engineering City University of Hong Kong Hong Kong 999077 China. dangylei@cityu.edu.hk. Department of Materials Science and Engineering City University of Hong Kong Hong Kong 999077 China. The Institute of AI and Robotics Fudan University Shanghai 200433 China. Key Laboratory of Spectral Imaging Technology of Chinese Academy of Sciences Xi'an Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xi'an 710119 China. Department of Electrical and Electronic Engineering Joint Appointment with School of Biomedical Sciences The University of Hong Kong Hong Kong 999077 China. State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Heilongjiang 150001 China. Ningbo Institute of Northwestern Polytechnical University College of Mechanical Engineering Northwestern Polytechnical University Xi'an 710072 China. yyt@***. Key Laboratory of Micro/Nano Systems for Aerospace (Ministry of Education) Northwestern Polytechnical University Xi'an 710072 China. yyt@***. Shaanxi Province Key Laboratory of Micro and Nano Electro-Mechanical Systems Northwestern Polytechnical University Xi'an 710072 China. yyt@***.

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Sensorless Control of Permanent Magnet Synchronous Motors based on Finite-Time Robust Flux Observer ⁎

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IFAC-PapersOnLine 2020年第2期53卷 9270-9275页

作者： Anton Pyrkin Alexey Bobtsov Romeo Ortega Alexey Vedyakov Dmitry Cherginets Dmitry Bazylev Petranevsky Igor ITMO University Faculty of Control Systems and Robotics49 Kronverksky Pr. St. Petersburg 197101 Russia Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Laboratory “Control of Complex Systems” Institute of Problems of Mechanical Engineering V.O. Bolshoj pr. 61 St. Petersburg 199178 Russia Laboratoire des Signaux et Systèmes CNRS-SUPELEC Plateau du Moulon 91192 Gif-sur-Yvette France

A sensorless control algorithm is developed based on novel finite-time robust flux observer for the non-salient permanent magnet synchronous motor (PMSM). Total flux equality and motor model are used to find the linear regression-like model with respect to the flux. Applying dynamic regressor extension and mixing method, we obtain two independent scalar equations and construct a finite-time flux observer. The flux estimate is used to reconstruct the rotor position and velocity with well-known trigonometric relation and phase-locked loop observer, respectively. To complete a sensorless control design, we pass these estimates to standard field orient control. The efficiency and robustness of the proposed approach are demonstrated through the set of numerical simulations.

关键词： Sensorless nonlinear observer flux observer nonlinear control systems synchronous motor

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Acoustic vector sensor underwater communications in the Makai Experiment

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Proceedings of Meetings on Acoustics 2021年第1期44卷

作者： Fabricio de Abreu Bozzi Sérgio Manuel Machado Jesus 1Laboratory for Robotics and Engineering Systems (LARSys) University of Algarve Faro Algarve 8005-139 PORTUGAL fabriciobozzi@*** sjesus@ualg.pt

The performance of a vector sensor array (VSA) receiving communication signals in the Makai experiment is quantified. The VSA composed of 4 vector sensors (VS) was tied to a drifting research vessel in shallow water. A bottom-moored source was used to transmit signals from 8k to 14kHz. In the present study, pressure and particle velocity channels are weighted-combined leading to a directional gain (VS beam steering). The communication chain for coherent modulation is composed of noise normalization, VS beam steering, synchronization, Doppler tracking, and a single Decision Feedback *** noise normalization step (denoising) is used since the noise power is not uniformly distributed among the pressure and velocity channels. This normalization emphasizes the vertical particle velocity, which benefit communication performance. Bit error rate(BER) performance is estimated for the pressure-only array, a single VS, and the VSA. It is shown that a single VS may provide similar communication performance to four pressure sensors. The BER for the shorter range (230m) varies from 0 to 5%, depending on the number of sensors used. It is noticed that in a multipath environment, steering to the Direction of Arrival (DoA) elevation may not lead to the lowest error for communications.

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Influence of the object stiffness on the grasp stability with compliant hand based on energetic approach

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IFAC-PapersOnLine 2020年第2期53卷 9905-9911页

作者： U. Vollhardt M. Makarov A. Caldas M. Grossard P. Rodriguez-Ayerbe Interactive Robotics Unite of CEA-LIST Gif sur Yvette France Signals and Systems Laboratory of CentraleSupélec CNRS University Paris-Sud University Paris-Saclay Gif sur Yvette Cedex France ESME Research Lab ESME Sudria Engineering schoolIvry-sur-Seine France

This article presents a stability analysis of object grasping with a compliant multi-fingered robot hand considering the influence of the flexibility of the grasped object on this stability. In this stability analysis we aimed to compute the maximum disturbance that can be withstood by a compliant hand-object system before being destabilized. Here, the case of objects with a compliant behavior that can be synthesized in a stiffness matrix is addressed. The specific example of beam objects and cylindrical grasps is investigated, a computation of the local stiffness matrix of the beam object is proposed using Euler-Bernoulli theory for beam deflection and the influence of the Young modulus of the beam on the stability is evaluated.

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IEEGview: An open-source multifunction GUI-based Matlab toolbox for localization and visualization of human intracranial electrodes

IEEGview: An open-source multifunction GUI-based Matlab tool...

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作者： Li, Guangye Jiang, Shize Chen, Chen Brunner, Peter Wu, Zehan Schalk, Gerwin Chen, Liang Zhang, Dingguo State Key Laboratory of Mechanical Systems and Vibrations Institute of Robotics Shanghai Jiao Tong University Shanghai China Department of Neurosurgery Huashan Hospital Fudan University Shanghai China Department of Neurology Albany Medical College AlbanyNY United States National Center for Adaptive Neurotechnologies Wadsworth Center New York State Department of Health AlbanyNY United States Department of Electronic and Electrical Engineering University of Bath Bath United Kingdom

Objective. The precise localization of intracranial electrodes is a fundamental step relevant to the analysis of intracranial electroencephalography (iEEG) recordings in various fields. With the increasing development of iEEG studies in human neuroscience, higher requirements have been posed on the localization process, resulting in urgent demand for more integrated, easy-operation and versatile tools for electrode localization and visualization. With the aim of addressing this need, we develop an easy-to-use and multifunction toolbox called iEEGview, which can be used for the localization and visualization of human intracranial electrodes. Approach. iEEGview is written in Matlab scripts and implemented with a GUI. From the GUI, by taking only pre-implant MRI and post-implant CT images as input, users can directly run the full localization pipeline including brain segmentation, image co-registration, electrode reconstruction, anatomical information identification, activation map generation and electrode projection from native brain space into common brain space for group analysis. Additionally, iEEGview implements methods for brain shift correction, visual location inspection on MRI slices and computation of certainty index in anatomical label assignment. Main results. All the introduced functions of iEEGview work reliably and successfully, and are tested by images from 28 human subjects implanted with depth and/or subdural electrodes. Significance. iEEGview is the first public Matlab GUI-based software for intracranial electrode localization and visualization that holds integrated capabilities together within one pipeline. iEEGview promotes convenience and efficiency for the localization process, provides rich localization information for further analysis and offers solutions for addressing raised technical challenges. Therefore, it can serve as a useful tool in facilitating iEEG studies. © 2019 IOP Publishing Ltd.

关键词： Electrodes

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