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Particle Motion trajectory tracking based on fiber optic tweezers

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Optoelectronics Letters 2023年第8期19卷 462-467页

作者： ZHAO Cun DONG Taiji GAO Bingkun LIU Xu ZHANG Zihua Department of Electrical Information Engineering Northeast Petroleum University Qinhuangdao CampusQinhuangdao 066004China College of Electrical and Information Engineering Northeast Petroleum UniversityDaqing 163318China Faculty of Materials and Manufacturing Beijing University of TechnologyBeijing 100124China

A biosensor based on single-fiber optical tweezers is proposed,which can detect the Motion trajectory of cells based on the stable capture and transmission of silica microspheres as well as biological yeast cells by using a tapered optical fiber as a sensing element.The interference cavity is formed by using the fiber tip and the target particle,the detected interference signal is demodulated using Hilbert transform,and the displacement curve of the particle is plotted to realize the particle Motion trajectory tracking.This method provides potential technical support for process monitoring of targeted drug delivery in biomedicine.

关键词： fiber Motion particle

Autonomous live working robot navigation with real-time detection and Motion planning system on distribution line

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High Voltage 2022年第6期7卷 1204-1216页

作者： Haoning Zhao Chaoqun Wang Rui Guo Xuewen Rong Jiamin Guo Qixun Yang Lecheng Yang Yuliang Zhao Yibin Li School of Control Science and Engineering Shandong UniversityJinanChina State Grid Shandong Electric Power Company JinanChina State Grid Intelligence Technology Co. Ltd.JinanChina

In this study,an autonomous robot navigation system is designed for live working on distribution line.The developed system features a real-time detection and Motion planning system,incorporating a manipulator capable of grasping power components.In order to accurately identify targets,the authors propose an object detection method based on the Larger Scale‘You Only Look Once’Version 4(LS-YOLOv4)algorithm for detecting the insulators and drop fuses.The LS-YOLOv4 extracts features of power components by Convolutional Neural Network(CNN),and then performs feature fusion.Then the authors develop a Motion planning method based on the Node Control Optimal Rapidly Exploring Random Trees(NC-RRT*),which can drive the robot to realise the autonomous robot Motion planning and obstacle avoidance.On the grasping function,the authors present a reliable Lightweight-based Convolutional Neural Network(L-CNN)grasping point detection method.Finally,the authors evaluate fully autonomous robotic system in both simulated and real-world experiments.The experimental results demonstrate that the proposed system can effectively identify the target and complete the grasping task in an efficient way.Notably,the proposed Motion planning method can take into account both planning efficiency and accuracy to manipulation tasks.

关键词： robot system Motion

Design of freeform geometries in a MEMS accelerometer with a mechanical Motion preamplifier based on a genetic algorithm

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Microsystems & Nanoengineering 2020年第1期6卷 122-135页

作者： Chen Wang Xiaoxiao Song Weidong Fang Fang Chen Ioannis Zeimpekis Yuan Wang Aojie Quan Jian Bai Huafeng Liu Gerold Schropfer Chris Welham Michael Kraft College of Optical Science and Engineering Zhejiang UniversityHangzhou 310027P.R.China Department of Electrical Engineering and Computer Science University of LiegeLiege B-4000Belgium ESAT-MICAS University of LeuvenLeuven 3001Belgium PGMF and School of Physics Huazhong University of Science and TechnologyWuhan 430074P.R.China Shanghai Institute of Microsystem and Information Technology Chinese Academy of SciencesShanghai 200050P.R.China ORC University of SouthamptonSouthampton SO171BJUK Coventor—A Lam Research Company Villebon sur Yvette 91140France

This paper describes a novel,semiautomated design methodology based on a genetic algorithm(GA)using freeform geometries for microelectromechanical systems(MEMS)devices.The proposed method can design MEMS devices comprising freeform geometries and optimize such MEMS devices to provide high sensitivity,large bandwidth,and large fabrication tolerances.The proposed method does not require much computation time or memory.The use of freeform geometries allows more degrees of freedom in the design process,improving the diversity and performance of MEMS devices.A MEMS accelerometer comprising a mechanical Motion amplifier is presented to demonstrate the effectiveness of the design approach.Experimental results show an improvement in the product of sensitivity and bandwidth by 100%and a sensitivity improvement by 141%compared to the case of a device designed with conventional orthogonal shapes.Furthermore,excellent immunities to fabrication tolerance and parameter mismatch are achieved.

关键词： accelerometer algorithm Motion

Contrast of multi-resolution analysis approach to transhumeral phantom Motion decoding

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CAAI Transactions on Intelligence Technology 2021年第3期6卷 360-375页

作者： Ejay Nsugbe Oluwarotimi William Samuel Mojisola Grace Asogbon Guanglin Li Independent Scholar Key Laboratory of Human-Machine Intelligence-Synergy Systems Chinese Academy of Sciences(CAS)Shenzhen Institutes of Advanced TechnologyShenzhenChina

In signal processing,multiresolution decomposition techniques allow for the separation of an acquired signal into sub levels,where the optimal level within the signal minimises redundancy,uncertainties,and contains the information required for the characterisation of the sensed phenomena.In the area of physiological signal processing for prosthesis control,scenarios where a signal decomposition analysis are required:the wavelet decomposition(WD)has been seen to be the favoured time-frequency approach for the decomposition of non-stationary signals.From a research perspective,the WD in certain cases has allowed for a more accurate Motion intent decoding process following feature extraction and classification.Despite this,there is yet to be a widespread adaptation of the WD in a practical setting due to perceived computational complexity.Here,for neuro-muscular(electromyography)and brainwave(electroencephalography)signals acquired from a transhumeral amputee,a computationally efficient time domain signal decom-position method based on a series of heuristics was applied to process the acquired signals before feature extraction.The results showed an improvement in Motion intent decoding prowess for the proposed time-domain-based signal decomposition across four different classifiers for both the neuromuscular and brain wave signals when compared to the WD and the raw signal.

关键词： Motion approach analysis

Parallel Planning:A New Motion Planning Framework for Autonomous Driving

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 236-246页

作者： Long Chen Xuemin Hu Wei Tian Hong Wang Dongpu Cao Fei-Yue Wang IEEE School of Data and Computer Science Sun Yat-sen University the School of Computer Science and Information Engineering Hubei University Institute of Measurement and Control Systems Karlsruhe Institute of Technology Department of Mechanical and Mechatronics Engineering University of Waterloo the State Key Laboratory of Management and Control for Complex Systems.Institute of Automation Chinese Academy of Sciences the Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology

Motion planning is one of the most significant technologies for autonomous driving. To make Motion planning models able to learn from the environment and to deal with emergency situations, a new Motion planning framework called as"parallel planning" is proposed in this paper. In order to generate sufficient and various training samples, artificial traffic scenes are firstly constructed based on the knowledge from the reality.A deep planning model which combines a convolutional neural network(CNN) with the Long Short-Term Memory module(LSTM) is developed to make planning decisions in an end-toend mode. This model can learn from both real and artificial traffic scenes and imitate the driving style of human drivers.Moreover, a parallel deep reinforcement learning approach is also presented to improve the robustness of planning model and reduce the error rate. To handle emergency situations, a hybrid generative model including a variational auto-encoder(VAE) and a generative adversarial network(GAN) is utilized to learn from virtual emergencies generated in artificial traffic scenes. While an autonomous vehicle is moving, the hybrid generative model generates multiple video clips in parallel, which correspond to different potential emergency scenarios. Simultaneously, the deep planning model makes planning decisions for both virtual and current real scenes. The final planning decision is determined by analysis of real observations. Leveraging the parallel planning approach, the planner is able to make rational decisions without heavy calculation burden when an emergency occurs.

关键词： Autonomous driving artificial traffic scene deep learning emergencies Motion planning parallel planning

All-optical Motion control of metal nanoparticles powered by propulsion forces tailored in 3D trajectories

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Photonics Research 2021年第1期9卷 1-12页

作者： OSéARODRIGO MERCEDES ANGULO TATIANA ALIEVA Universidad Complutense de Madrid Facultad de Ciencias FisicasCiudad Universitarias/nMadrid 28040Spain

Increasing interest has been drawn to optical manipulation of metal(plasmonic)nanoparticles due to their unique response on electromagnetic radiation,prompting numerous applications in nanofabrication,photonics,sensing,etc.The familiar point-like laser tweezers rely on the exclusive use of optical confinement forces that allow stable trapping of a single metal nanoparticle in 3 D.Simultaneous all-optical(contactless)confinement and Motion control of single and multiple metal nanoparticles is one of the major challenges to be overcome.This article reports and provides guidance on mastering a sophisticated manipulation technique harnessing confinement and propulsion forces,enabling simultaneous all-optical confinement and Motion control of nanoparticles along 3 D trajectories.As an example,for the first time to our knowledge,programmable transport of gold and silver nanospheres with a radius of 50 and 30 nm,respectively,along 3 D trajectories tailored on demand,is experimentally demonstrated.It has been achieved by an independent design of both types of optical forces in a single-beam laser trap in the form of a reconfigurable 3 D curve.The controlled Motion of multiple nanoparticles,far away from chamber walls,allows studying induced electrodynamic interactions between them,such as plasmonic coupling,observed in the presented experiments.The independent control of optical confinement and propulsion forces provides enhanced flexibility to manipulate matter with light,paving the way to new applications involving the formation,sorting,delivery,and assembling of nanostructures.

关键词： Motion walls silver

A Real Time Self-Tuning Motion Controller for Mobile Robot Systems

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 84-96页

作者： Mohamed Boukens Abdelkrim Boukabou Mohammed Chadli the Department of Electronics University of Laghouat IEEE the Department of Electronics University of MSB Jijel University of Picardie Jules Verne

This paper proposes an intelligent controller for Motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method.In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.

关键词： Learning and adaptive systems Motion control metaheuristic robust control real-time tuning self-tuning wheeled mobile robot

Periodic Motion Planning and Control for Double Rotary Pendulum via Virtual Holonomic Constraints

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 291-298页

作者： Zeguo Wang Leonid B.Freidovich Honghua Zhang Beijing Institute of Control Engineering IEEE the Robotics and Control Laboratory (www.control.tfe.umu.se) Department of Applied Physics and ElectronicsUmea University

Periodic Motion planning for an under-actuated system is rather difficult due to differential dynamic constraints imposed by passive dynamics, and it becomes more difficult for a system with higher underactuation degree, that is with a higher difference between the number of degrees of freedom and the number of independent control inputs. However, from another point of view, these constraints also mean some relation between state variables and could be used in the Motion planning.We consider a double rotary pendulum, which has an underactuation degree 2. A novel periodic Motion planning is presented based on an optimization search. A necessary condition for existence of the whole periodic trajectory is given because of the higher underactuation degree of the system. Moreover this condition is given to make virtual holonomic constraint(VHC) based control design feasible. Therefore, an initial guess for the optimization of planning a feasible periodic Motion is based on this necessary condition. Then, VHCs are used for the system transformation and transverse linearization is used to design a static state feedback controller with periodic matrix function gain. The controller gain is found through another optimization procedure. The effectiveness of initial guess and performance of the closed-loop system are illustrated through numerical simulations.

关键词： Double rotary pendulum periodic Motion planning under-actuated mechanical systems virtual holonomic constraint (VHC)

Synthetic Jet Control on the Propulsion Behavior of a Foil in Plunge-pitch Motion

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Journal of Bionic Engineering 2020年第2期17卷 303-314页

作者： Yadong Li Guoqing Zhou Jie Wu Liaoning General Aviation Academy Shenyang Aerospace UniversityShenyang 110136China College of Aerospace Engineering Shenyang Aerospace UniversityShenyang 110136China State Key Laboratory of Mechanics and Control of Mechanical Structures Nanjing University of Aeronautics and AstronauticsNanjing 210016China

The Synthetic Jet(S J)control on the propulsion behavior of a foil in plunge-pitch Motion is examined in this work by numerical simulations.An elliptic foil with ratio of 8 performs the plunge and pitch Motions synchronously.A pair of SJs with the same frequency and strength is integrated into the upper and lower surfaces of the foil.As a result,the local flow field around the foil could be obviously modified by the SJs.At the Reynolds number of 200,the effects of the inclined angle between the jet direction and the chord line,the phase angle between the SJs and the flapping Motion as well as the location of SJ on the propulsion performance are systematically investigated.Compared with the pure plunging and pitching foil,it is indicated that the enhancement of mean thrust and propulsive efficiency can be obtained by the SJs with suitable working parameters.Based on the numerical analysis,it is found that the jet flow on the foil surfaces,which changes the local pressure distribution to increase the pressure difference between upper and lower surfaces,can benefit the propulsion behavior of the flapping foil.

关键词： propulsion behavior plunge-pitch Motion elliptic foil synthetic jet