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A Reverse Path Planning Approach for Enhanced Performance of Multi-Degree-of-Freedom Industrial Manipulators

Computer Modeling in Engineering & Sciences 2024年第5期139卷 1357-1379页

作者： Zhiwei Lin Hui Wang Tianding Chen yingtao jiang Jianmei jiang Yingpin Chen Key Laboratory of Light Field Manipulation and System Integration Applications in Fujian Province School of Physics and Information EngineeringMinnan Normal UniversityZhangzhou363000China Department of Electrical and Computer Engineering University of NevadaLas Vegas89154USA College of Material Engineering Fujian Agriculture and Forestry UniversityFuzhou350000China

In the domain of autonomous industrial manipulators,precise positioning and appropriate posture selection in path planning are pivotal for tasks involving obstacle avoidance,such as handling,heat sealing,and *** Multi-Degree-of-Freedom(MDOF)manipulators offer kinematic redundancy,aiding in the derivation of optimal inverse kinematic solutions to meet position and posture requisites,their path planning entails intricate multiobjective optimization,encompassing path,posture,and joint motion *** satisfactory results in practical scenarios remains *** response,this study introduces a novel Reverse Path Planning(RPP)methodology tailored for industrial *** approach commences by conceptualizing the manipulator’s end-effector as an agent within a reinforcement learning(RL)framework,wherein the state space,action set,and reward function are precisely defined to expedite the search for an initial collision-free *** enhance convergence speed,the Q-learning algorithm in RL is augmented with ***,we formulate the cylindrical bounding box of the manipulator based on its Denavit-Hartenberg(DH)parameters and propose a swift collision detection ***,the motion performance of the end-effector is refined through a bidirectional search,and joint weighting coefficients are introduced to mitigate motion in high-power *** efficacy of the proposed RPP methodology is rigorously examined through extensive simulations conducted on a six-degree-of-freedom(6-DOF)manipulator encountering two distinct obstacle configurations and target *** results substantiate that the RPP method adeptly orchestrates the computation of the shortest collision-free path while adhering to specific posture constraints at the target ***,itminimizes both posture angle deviations and joint motion,showcasing its prowess in enhancing the operational performance of MDOF industrial manipulators.

关键词： Reverse path planning Dyna-Q bidirectional search posture angle joint motion

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B-Spline-Based Curve Fitting to Cam Pitch Curve Using Reinforcement Learning

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Intelligent Automation & Soft Computing 2023年第5期36卷 2145-2164页

作者： Zhiwei Lin Tianding Chen yingtao jiang Hui Wang Shuqin Lin Ming Zhu School of Physics and Information Engineering Minnan Normal UniversityZhang ZhouFujian363000China Department of Electrical and Computer Engineering University of NevadaLas VegasNV89154USA

Directly applying the B-spline interpolation function to process plate cams in a computer numerical control(CNC)system may produce verbose tool-path codes and unsmooth *** paper is devoted to addressing the problem of B-splineﬁtting for cam pitch *** that the B-spline curve needs to meet the motion law of the follower to approximate the pitch curve,we use the radial error to quantify the effects of theﬁtting B-spline curve and the pitch *** problem thus boils down to solving a difﬁcult global optimization problem toﬁnd the numbers and positions of the control points or data points of the B-spline curve such that the cumulative radial error between theﬁtting curve and the original curve is minimized,and this problem is attempted in this paper with a double deep Q-network(DDQN)reinforcement learning(RL)algorithm with data points ***ﬁcally,the RL envir-onment,actions set and current states set are designed to facilitate the search of the data points,along with the design of the reward function and the initialization of the neural *** experimental results show that when the angle division value of the actions set isﬁxed,the proposed algorithm can maximize the number of data points of the B-spline curve,and accurately place these data points to the right positions,with the minimum average of radial *** work establishes the theoretical foundation for studying splineﬁtting using the RL method.

关键词： B-splineﬁtting radial error DDQN RL algorithm global optimal policy

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Bifurcation-Based Stability Analysis of Electrostatically Actuated Micromirror as a Two Degrees of Freedom System

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Computer Modeling in Engineering & Sciences 2018年第3期114卷 261-276页

作者： Kuntao Ye Yan Luo yingtao jiang jiangxi University of Science and Technology School of ScienceGanzhouJiangxiChina 341000 University of Nevada Las Vegas Department of Electrical and Computer EngineeringLas VegasNVUSA 89154

Torsional micromirror devices have been widely used in micro displays,RF switches,optical communications,and optical coherence tomography *** order to study the stability of electrostatically driven torsional micromirror system with double bottom plates and two voltage sources,a dimensionless,two degrees of freedom(2-DoF)dynamic model was *** by the dimensionless phase space model equation,the pull-in and bifurcation phenomena were analyzed using the Hamiltonian method and numerical *** particular,the influence of the damping coefficient and the torsion-bending coupling effect on the phase trajectory was ***,the conditions that can lead to pull-in were numerically determined for saddle-node,pitchfork and Hopf bifurcations in the framework of 2-DoF *** showed that the dynamic pull-in voltage as predicted by the proposed 2-DoF system model is considerably lower than that by the one degree of freedom(1-DoF)system *** was also confirmed that the pull-in voltage varies with the damping coefficient and/or the ratio of the two voltages applied to the bottom plates of the *** modelling method and stability analysis presented in this paper shall provide valuable insight to the design and control of electrostatically actuated micromirror systems.

关键词： MEMS micromirror bifurcation pull-in stability phase trajectories DoF

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Wind Power Forecasting Methods Based on Deep Learning:A Survey

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Computer Modeling in Engineering & Sciences 2020年第1期122卷 273-301页

作者： Xing Deng Haijian Shao Chunlong Hu Dengbiao jiang yingtao jiang School of Computer Science Jiangsu University of Science and TechnologyZhenjiangChina School of Automation Key Laboratory of Measurement and Control for CSEMinistry of EducationSoutheast UniversityNanjingChina Department of Electrical and Computer Engineering University of NevadaLas VegasUSA

Accurate wind power forecasting in wind farm can effectively reduce the enormous impact on grid operation safety when high permeability intermittent power supply is connected to the power *** to provide reference strategies for relevant researchers as well as practical applications,this paper attempts to provide the literature investigation and methods analysis of deep learning,enforcement learning and transfer learning in wind speed and wind power forecasting ***,wind speed and wind power forecasting around a wind farm requires the calculation of the next moment of the definite state,which is usually achieved based on the state of the atmosphere that encompasses nearby atmospheric pressure,temperature,roughness,and *** an effective method of high-dimensional feature extraction,deep neural network can theoretically deal with arbitrary nonlinear transformation through proper structural design,such as adding noise to outputs,evolutionary learning used to optimize hidden layer weights,optimize the objective function so as to save information that can improve the output accuracy while filter out the irrelevant or less affected information for *** establishment of high-precision wind speed and wind power forecasting models is always a challenge due to the randomness,instantaneity and seasonal characteristics.

关键词： Deep learning reinforcement learning transfer learning wind power forecasting

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A Graph-Based Reinforcement Learning Method with Converged State Exploration and Exploitation

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Computer Modeling in Engineering & Sciences 2019年第2期118卷 253-274页

作者： Han Li Tianding Chen Hualiang Teng yingtao jiang College of Mathematics Physics and Electronic Information EngineeringWenzhou UniversityWenzhouZhejiang325035China School of Physics and Information Engineering Minnan Normal UniversityZhangzhouFujian363000China Department of Civil and Environmental Engineering Howard R.Hughes College of EngineeringUniversity of NevadaLas VegasNV454015USA Department of Electrical and Computer Engineering Howard R.Hughes College of EngineeringUniversity of NevadaLas VegasNV454015USA.

In any classical value-based reinforcement learning method,an agent,despite of its continuous interactions with the environment,is yet unable to quickly generate a complete and independent description of the entire environment,leaving the learning method to struggle with a difficult dilemma of choosing between the two tasks,namely exploration and *** problem becomes more pronounced when the agent has to deal with a dynamic environment,of which the configuration and/or parameters are constantly *** this paper,this problem is approached by first mapping a reinforcement learning scheme to a directed graph,and the set that contains all the states already explored shall continue to be exploited in the context of such a *** have proved that the two tasks of exploration and exploitation eventually converge in the decision-making process,and thus,there is no need to face the exploration *** tradeoff as all the existing reinforcement learning methods *** this observation indicates that a reinforcement learning scheme is essentially the same as searching for the shortest path in a dynamic environment,which is readily tackled by a modified Floyd-Warshall algorithm as proposed in the *** experimental results have confirmed that the proposed graph-based reinforcement learning algorithm has significantly higher performance than both standard Q-learning algorithm and improved Q-learning algorithm in solving mazes,rendering it an algorithm of choice in applications involving dynamic environments.

关键词： Reinforcement learning graph exploration and exploitation maze.

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Detection of kinematics parameters of index finger movement with high-speed video camera

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仪器仪表学报 2008年第2期29卷 240-243页

作者： Hou Wensheng jiang yingtao Wu Xiaoying Zheng Xiaolin Zheng Jun Ye Yihong Department of Biomedical Engineering Chongqing University Chongqing 400044 China Department of Electrical and Computer Engineering University of Nevada Las Vegas NV 89154 USA Computer Science Department Queens College City University of New York Flushing NY 11367 USA

Synergic movement of finger's joints provides human hand tremendous dexterities,and the detection of kinematics parameters is critical to describe and evaluate the kinesiology functions of the *** present work is the attempt to investigate how the angular velocity and angular acceleration of the joints of index finger vary with respect to time during conducting a motor task.A high-speed video camera has been employed to visually record the movement of index finger,and miniaturized(5-mm diameter) reflective markers have affixed to the subject's index finger on the side close to thumb and dorsum of thumb at different joint *** images have been reviewed frame by frame to get the coordinate values of each joint,and the angular displacements,angular velocities and angular acceleration can be obtained with triangle *** experiment results show that the methods here can detect the kinematics parameters of index finger joints during moving,and can be a valid route to study the motor function of index finger.

关键词：运动学参数食指移动高速摄影机角速度协同作用

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Simulation of the fluidic features for diffuser/nozzle involved in a PZT-based valveless micropump

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仪器仪表学报 2008年第1期29卷 1-4页

作者： HouWensheng Zheng Xiaolin Biswajit Das jiang yingtao Qian Shizhi Wu Xiaoying Zheng Zhigao Department of Biomedical Engineering Chongqing University Chongqing 400044 China Nevada Nanotechnology Center University of Nevada Las Vegas NV 89154 USA Department of Electrical and Computer Engineering University of Nevada Las Vegas NV 89154 USA Department of Mechanical Engineering University of Nevada Las Vegas NV 89154 USA

PZT-based valveless micropump is a microactuator that can be used for controlling and delivering tiny amounts of fluids,and diffuser/nozzle plays an important role when this type of micropump drives the fluid flowing along a specific *** this paper,a numerical model of micropump has been proposed,and the fluidic properties of diffuser/nozzle have been simulated with *** the method of finite-element analysis,the increased pressure drop between inlet and outlet of diffuser/nozzle induces the increment of flow rate in both diffuser and nozzle simultaneously,but the increasing rate of diffuser is faster than that of *** L/R,ratio of L(length of cone pipe) and R(radius of minimal cross section of cone pipe) plays an important role in fluidic performance of diffuser and nozzle as well,and the mean flow rate will decrease with increment of L/*** mean flow rate reaches its peak value when L/R with the value of 10 regardless the divergence angle of diffuser or *** simulation results indicate that the fluidic properties of diffuser/nozzle can be defined by its geometric structure,and accordingly determine the efficiency of micropump.

关键词：流体系统模拟无阀微型泵散流器喷嘴

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Transcranial magnetic stimulation-induced finger force changes under various finger coordination patterns and target finger force phases

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Neural Regeneration Research 2010年第1期5卷 64-69页

作者： Xiaoying Wu Wensheng Hou Xiaolin Zheng Shan Shen yingtao jiang Jun Zheng Yan He Key Laboratory of Biorheological Science and Technology Ministry of Education Bioengineering College Chongqing University Chongqing 400044 China Psychology Department University of Surrey Guildford Surrey Gu2 7XFI UK Department of Computer Science New Mexico Institute of Mining and Technology Socorro NM 87801 USA Department of Electrical and Computer Engineering University of Nevada Las Vegas NV 89154 USA

BACKGROUND： The detection of motor evoked potential is utilized to explore neuromuscular finger coordination. The influence of transcranial magnetic stimulation on finger force has been investigated mainly on a single finger, and only time-dependent increased target finger force has been detected in the finger force task. OBJECTIVE： To explore the neural mechanism of finger force coordination in the motor cortex by observing the influence of various finger coordination patterns and patterns of transcranial magnetic stimulation （TMS）-induced finger force changes. DESIGN, TIME AND SETTING： Neurophysiological and behavioral study was performed at the Biomedical Engineering Laboratory of Chongqing University from April to June 2008. PARTICIPANTS： A total of 10 healthy, university students, comprising 5 males and 5 females, aged 21-23 years, voluntarily participated in this study. All participants were right-handed, with normal or corrected vision. Individuals with upper limb complaints or other musculoskeletal disorders were excluded. METHODS： A target force-tracking task was conducted on the index finger, the index and middle fingers, and four fingers （index, middle, ring, and little）, respectively. Target force trace in a single trial consisted of a 6-second ramp phase, a 20-second constant phase, and a 6-second drop phase. During experimentation, an unpredictable single-pulse TMS （120% motor threshold） was applied to the primary motor cortex （M1） in each phase. MAIN OUTCOME MEASURES： Changes in peak force induced by TMS were obtained for each finger pattern during each force-tracking phase. Differences in force changes were tested between different finger pattems with regard to ramp, constant, and drop phases of target force. RESULTS： Under ramp, constant, and drop phases of target force, the increase in magnetic stimulation-induced finger forces changes positively correlated with the number of fingers involved in the force tracking task. The magnetic stimulation-ind

关键词： transcranial magnetic stimulation finger force peak force changes finger combination

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Ultrasensitive strain gauge with tunable temperature coefficient of resistivity

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Nano Research 2016年第5期9卷 1346-1357页

作者： Lizhi Yi Weihong Jiao Changming Zhu Ke Wu Chao Zhang Lihua Qian Shuai Wang yingtao jiang Songliu Yuan School of Physics Huazhong University of Science and Technology Wuhan 430074 China Flexible Electronics Research Center Huazhong University of Science and Technology Wuhan 430074 China School of Chemistry and Chemical Engineering Huazhong University of Science and Technology Wuhan 430074 China Nevada Nanotechnology Center & Department of Electrical and Computer Engineering University of Nevada Las Vegas Nevada 89154-4026 USA

We demonstrate an ultrasensitive strain gauge based on a discontinuous metal film with a record detection limit as low as 8.3 × 10^-6. Constructed by well-tunable crevices on the nanometer scale within the film, this gauge exhibits an ultrafast dynamic response to vibrations with a frequency range of 1 Hz to 10 kHz. More importantly, the temperature coefficient of resistivity （TCR） of the metal film is tunable owing to the cancellation effect caused by the possibility of tunneling across the nanoscale crevices （showing a negative temperature dependence） and the electron conduction within the metal islands （showing a positive temperature dependence）. Consequently, a nullified TCR is achievable when the crevice size can be precisely controlled. Thus, a fabrication strategy to precisely control the nanoscale crevices was developed in this study through the real-time tracking of the electrical conductivity during thermal evaporation. The ultrasensitive strain gauge with a tunable thermal drift introduces numerous opportunities for precision devices and wearable electronics with superior reliability.

关键词： strain gauge flexible gauge Au nanoparticle sound-wave detection radial-artery detection electron tunneling

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Correlation between primary motor cortex neural activity and fingertip force following transcranial magnetic stimulation

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Neural Regeneration Research 2010年第24期5卷 1905-1909页

作者： Xiaoying Wu Wensheng Hou Xiaolin Zheng yingtao jiang Jun Zheng Yan He Key Laboratory of Biorheological Science and Technology Ministry of Education Bioengineering College Chongqing University Chongqing 400044 China Department of Electrical and Computer Engineering University of Nevada Las Vegas NV 89154 USA Department of Computer Science New Mexico Institute of Mining and Technology Socorro NM 87801 USA

A better understanding of the neural mechanisms of finger-force regulation can help to explain the relationship between the central nervous system and nerve-muscle force, as well as assist in motor functional rehabilitation and the development robot hand designs. In the present study, 11 healthy volunteers performed a different target force-tracking task, which involved the index finger alone, index and middle finger together, and the combination of four fingers （i.e., index, middle, ring, and little）. The target force trace corresponded to 3 levels of 20% maximal voluntary changes （MVC）, 30% MVC, and 40% MVC in 20 seconds. In the test, an unexpected single 120% motor threshold transcranial magnetic stimulation was applied to the primary motor cortex （M1） during force tracking. Results revealed that peak force changes increased with increasing background force and the number of involved task fingers. These results demonstrate that M1 neural activities correlate with finger-force production, and M1 plays a role in finger-force control. Moreover, different neuronal networks were required for different finger patterns; a complicated task required multi-finger combinations and a complicated neuronal network comprised a large number of neurons.

关键词： transcranial magnetic stimulation finger motor control neural activities primary motor cortex background force

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