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SSRN 2022年

作者： Chehelgami, Shirin Ashtari, Erfan Basiri, Mohammad Amin Masouleh, Mehdi Tale Kalhor, Ahmad Human and Robot Interaction Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran

In this research, a global path planning method based on recurrent neural networks by means of a new loss function is presented, which regardless of the complexity of the configuration space, generates the path in a relatively constant time. The new loss function is defined in such a way that in addition to learning the input data of the network, it creates an adjustable safety margin around the obstacles and ultimately creates a safe path. Moreover, a new global path planning method is also introduced, which is used to create the dataset needed to train the proposed neural network. The convergence of this method is mathematically proven and it is shown that this method can also produce a suboptimal path in a much shorter time than the common methods of global path planning reported in the literature. In short, the main purpose of this research consists in providing a method which can create a suboptimal, fast and safe path for a mobile robot from any random starting point to any random destination in a known environment. First, the proposed methods will be implemented for different two-dimensional environments consisting of convex and non-convex obstacles, considering the robot as a pointmass, and then it will be implemented in a 3D simulation environment, *** to classical global path planning algorithms, such as RRT and A*, the proposed approach demonstrates better performance in complex and challenging environments. © 2022, The Authors. All rights reserved.

关键词： Recurrent neural networks

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Rechargeable Self-Powered Pressure Sensor Based on Zn-Ion Battery with High Sensitivity and Broad-Range Response

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SSRN 2024年

作者： Hu, Yong-Peng Liu, Kai-Yang Bai, Ruo-Ning Liu, Da-Zhuang Yu, Wei Meng, Chui-Zhou Li, Guo-Xian Guo, Shi-Jie Hebei Key Laboratory of Smart Sensing and Human-Robot Interaction Engineering Research Center The Ministry of Education for Intelligent Rehabilitation Equipment and Detection Technologies School of Mechanical Engineering Hebei University of Technology No. 5340 Xiping Road Beichen District Tianjin300401 China

Flexible pressure sensors find broad applications in electronic skin, human-computer interaction, and health monitoring. However, developing self-powered flexible sensors capable of detecting both dynamic and static pressures with high sensitivity and a wide detection range remains a significant challenge. Here, we report the design and fabrication of a new rechargeable Zn-ion battery-type flexible self-powered pressure sensor (RZIB-FPS). In the device, the anode of a flexible Zn-ion battery is designed into a sandwich configuration with a porous isolation layer in between a conductive layer decorated with polymethylmethacrylate microspheres and a flexible Zn electrode. The self-powered pressure sensing mechanism relies on the variation in output voltage resulting from the resistance change of the anode when subjected to external pressure. This RZIB-FPS exhibits an open-circuit voltage of 1.46 V, an energy density of 392 µWh cm−2, a high sensitivity (up to 42.6 mV kPa−1), a wide pressure detection range (up to 330 kPa), and excellent cycling stability (up to 12,000 cycles). Furthermore, the proposed all-in-one device design demonstrates excellent charge-discharge performance, manifesting its high integration level and potential for sensor miniaturization. This study introduces a new strategy for developing high-performance sensors for future self-powered smart wearable electronics. © 2024, The Authors. All rights reserved.

关键词： Pressure sensors

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SIVD: Dataset of Iranian Vehicles for Real-Time Multi-Camera Video Tracking and Recognition

SIVD: Dataset of Iranian Vehicles for Real-Time Multi-Camera...

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International Conference of Signal Processing and Intelligent Systems (ICSPIS)

作者： Farbod Siahkali Seyed Amirmahdi Alavi Mehdi Tale Masouleh Human and Robot Interaction Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran Human and Robot Interaction Laboratory School of Computer Science Islamic Azad University Central Tehran Branch Tehran Iran

ISBN: (纸本)9781665476249

In this paper, a new publicly available 1 web-Scraped Iranian Vehicle Dataset (SIVD) for simultaneous real-time vehicle tracking and recognition is proposed. The datasets provided for Iranian cars in the literature have two fundamental problems. First, the lack of images from different angles, and second, the small number of classes compared to the dispersion of car models in the real world. Therefore, for the purposes of this paper, Iranian vehicle images from car sales websites are collected, and the SIVD dataset is proposed which contains 29 classes and 36,705 images. This paper aims at developing a classification network for Iranian vehicle recognition and implement a real-time tracking system using the YOLOv5 network to perform real-time vehicle model recognition and tracking tasks simultaneously. The ResNet50 achieved an accuracy of 99.29%, the highest among the investigated classification networks. 1 https://***/Farbod-Siahkali/Iranian-Vehicle-Tracking-and-Recognition

关键词： Representation learning Image recognition Video tracking Machine learning algorithms Neural networks Real-time systems Automobiles

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Kinematic analysis of an under-constrained cable-driven robot using neural networks 28

Kinematic analysis of an under-constrained cable-driven robo...

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28th Iranian Conference on Electrical engineering, ICEE 2020

作者： Zare, Soroush Haghighi, Morteza Shahamiri Hairi Yazdi, Mohammad Reza Kalhor, Ahmad Masouleh, Mehdi Tale School of Mechanical Engineering Human and Robot Interaction Laboratory University of Tehran Tehran Iran School of Electrical and Computer Engineering Human and Robot Interaction Laboratory University of Tehran Tehran Iran School of Mechanical Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781728172965

In this paper, three types of neural networks including, multilayer perceptron, radial basis function, and Local Linear Model Trees, are considered based on adaptability with the significant behavior of data to solve the forward and inverse kinematics of the under-constrained cable-driven parallel robot. The practical workspace of the robot is a rectangular cube with dimensions of 360cm × 220c× 160cm. Forward kinematics problem of the under-constrained cable-driven parallel robot is challenging to solve by reason of complexity and nonlinearity of the robot kinematic equations. The typical approach utilizes a numerical method to solve these equations, which are computationally expensive and very time-consuming. Resorting to the neural network approaches results in the feasible orientation, which confirms that all the cables are in tension. The trained neural network gives a feasible inverse kinematic problem solution and the running time of the optimal trained neural network in the control loop, obtained about 12 microseconds, pales in comparison to the sampling time of the control loop that facilitates the real-time control of the robot. Obtained results reveal that the multilayer perceptron has the mean average error order of about 2 millimeters for the position and 0.78 degrees for orientation, which makes a case for precise control in the high-speed motion of the robot. © 2020 IEEE.

关键词： Multilayer neural networks

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Configuration Design and Kinematic Performance Analysis of a Novel 4-DOF Parallel Ankle Rehabilitation Mechanism with Two Virtual Motion Centers

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Chinese Journal of mechanical engineering 2023年第6期36卷 87-104页

作者： Jingke Song Jun Wei Bin Yu Chenglei Liu Cunjin Ai Jianjun Zhang School of Mechanical Engineering Hebei University of TechnologyTianjin 300401China Hebei Provincial Key Laboratory of Robot Perception and Human-Machine Fusion Tianjin 300130China Intelligent Rehabilitation Device and Detection Technology Engineering Research Center of the Ministry of Education Tianjin 300130China

Aiming at the problem that the existing ankle rehabilitation robot is difficult to fully fit the complex motion of human ankle joint and has poor human-machine motion compatibility,an equivalent series mechanism model that is highly matched with the actual bone structure of the human ankle joint is proposed and mapped into a parallel rehabilita-tion *** parallel rehabilitation mechanism has two virtual motion centers(VMCs),which can simulate the complex motion of the ankle joint,adapt to the individual differences of various patients,and can meet the reha-bilitation needs of both left and right feet of ***,based on the motion properties and physiological structure of the human ankle joint,the mapping relationship between the rehabilitation mechanism and ankle joint is determined,and the series equivalent model of the ankle joint is *** to the kinematic and con-straint properties of the ankle equivalent model,the configuration design of the parallel ankle rehabilitation robot is carried ***,according to the intersecting motion planes theory,the full-cycle mobility of the mechanism is proved,and the continuous axis of the mechanism is judged based on the constraint power and its ***,the kinematics of the parallel ankle rehabilitation robot is ***,based on the OpenSim biomechanical soft-ware,a human-machine coupling rehabilitation simulation model is established to evaluate the rehabilitation effect,which lays the foundation for the formulation of a rehabilitation strategy for the later prototype.

关键词： Ankle rehabilitation robot Double-VMCs mechanism Kinematic performance human-machine rehabilitation simulation

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Accelerated prediction of Cu-based single-atom alloy catalysts for CO_(2) reduction by machine learning

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Green Energy & Environment 2023年第3期8卷 820-830页

作者： Dashuai Wang Runfeng Cao Shaogang Hao Chen Liang Guangyong Chen Pengfei Chen Yang Li Xiaolong Zou Shenzhen Geim Graphene Center Tsinghua-Berkeley Shenzhen Institute&Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen518055China Tencent Shenzhen518054China Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055China Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong Kong999077China Tsinghua-Berkeley Shenzhen Institute Tsinghua UniversityShenzhen518055China

Various strategies,including controls of morphology,oxidation state,defect,and doping,have been developed to improve the performance of Cu-based catalysts for CO_(2) reduction reaction(CO_(2)RR),generating a large amount of ***,a unified understanding of underlying mechanism for further optimization is still *** this work,combining first-principles calculations and machine learning(ML)techniques,we elucidate critical factors influencing the catalytic properties,taking Cu-based single atom alloys(SAAs)as *** method relies on high-throughput calculations of 2669 CO adsorption configurations on 43 types of Cu-based SAAs with various *** ML analyses reveal that low generalized coordination numbers and valence electron number are key features to determine catalytic *** our ML model with cross-group learning scheme,we demonstrate the model generalizes well between Cu-based SAAs with different alloying ***,electronic structure calculations suggest surface negative center could enhance CO adsorption by back donating electrons to antibonding orbitals of ***,several SAAs,including PCu,AgCu,GaCu,ZnCu,SnCu,GeCu,InCu,and SiCu,are identified as promising CO_(2)RR *** work provides a paradigm for the rational design and fast screening of SAAs for various electrocatalytic reactions.

关键词： Cu-based single-atom alloy CO adsorption Machine learning First principles CO_(2)reduction reaction

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Design and Evaluation of Adaptive and Sliding Mode Control for a 3-DOF Delta Parallel robot 28

Design and Evaluation of Adaptive and Sliding Mode Control f...

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28th Iranian Conference on Electrical engineering, ICEE 2020

作者： Azad, Faraz Abed Rahimi, Saeed Hairi Yazdi, Mohammad Reza Masouleh, Mehdi Tale Human and Robot Interaction Laboratory School of Mechanical Engineering University of Tehran Tehran Iran School of Mechanical Engineering College of Engineering University of Tehran Tehran Iran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781728172965

In this paper, simulation, kinematics analysis, and control of a 3-DOF Delta parallel robot have been investigated. Delta parallel robots are one of the most popular manipulators for industrial applications. The kinematic equations of the robot have been established by the screw theory, in which, the position and velocity analyses have been carried out. In SimScape simulation environment, the kinematic model of the robot has been verified and subsequently, an inverse kinematic model was adopted for control purposes. In order to improve the tracking ability of the robot, three important control approaches, consisting in PID, adaptive control, and a Sliding Mode Control (SMC) have been implemented. Afterwards, the effectiveness of each approach has been investigated by employing the root mean square error (RMSE) index. By comparing the obtained index values, the SMC demonstrates the best performance with the RMSE value of 0.4188 in comparison to other methods. Simulation results were illustrated to show the ability of the controllers to reject white noise disturbance added to the system's input signals. © 2020 IEEE.

关键词： Three term control systems

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Active Disturbance Rejection Control of Lower Limb Exoskeleton Based on Genetic Algorithm

Active Disturbance Rejection Control of Lower Limb Exoskelet...

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Chinese Control Conference (CCC)

作者： Jinbao Wang Lei Ni Jun Wei Jixiao Liu Jianjun Zhang Shijie Guo School of Mechanical Engineering Hebei University of Technology Tianjin Key Laboratory of Robot Perception and Human-Machine Fusion of Hebei Province Tianjin

Aiming at the problem of movement disorders in the elderly or people with lower limb muscle function degradation caused by diseases, this paper designs an exoskeleton robot that can provide assistance for human hip extension and flexion. According to the gait characteristics of the hip joint during walking, an assist strategy and an assist function are proposed to control the motor to track the desired assist curve, so that the exoskeleton robot can provide assistance to the human hip joint. In order to reduce the influence of external interference and improve the assist effect, active disturbance rejection control based on genetic algorithm is introduced. Finally, the tracking performance and anti-interference performance of the controller are verified by simulation, and the prototype of the lower limb exoskeleton robot and the corresponding experimental platform are built to evaluate the assist effect. Through the walking experiment, the change of hip joint torque under the condition of human motion is observed. It is found that the hip joint torque under the condition of power is lower than that without power. The above simulation and experiment verify that this method can improve the assist performance of the exoskeleton robot and provide effective assistance to the human body.

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Experimental Study on Reducing the Oscillations of a Cable-Suspended Parallel robot for Video Capturing Purposes using Simulated Annealing and Path Planning

Experimental Study on Reducing the Oscillations of a Cable-S...

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International Conference of Signal Processing and Intelligent Systems (ICSPIS)

作者： Mohammad Ghanatian Mohammad Reza Hairi Yazdi Mehdi Tale Masouleh Human and Robot Interaction Laboratory School of Mechanical Engineering University of Tehran Tehran Iran School of Mechanical Engineering University of Tehran Tehran Iran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781665409391

This paper aims to smoothen the movements of an under-constrained cable-suspended parallel robot which carries a camera for video capturing purposes, especially for video capturing of football games. This goal is achieved by means of an accurate while simple PID controller optimized by the Simulated Annealing algorithm and implemented on the joint space. Moreover, a planning strategy is considered for the joint space trajectory of the robot which guarantees the zero jerk, acceleration, and velocity at the start and the end of motions. On this regard, a septic function for each joint of the robot is considered and the corresponding boundary conditions are applied to the function to make the end-effector movements less oscillatory. This method is implemented and tested on an experimental setup while the end-effector oscillation data is recorded using an IMU sensor attached to the end-effector of the robot. Applying frequency analysis on the oscillatory data of the end-effector reveals that this simple method, on average, resulted in a 33.8% reduction in the average amplitude of the end-effector oscillations. Moreover, the maximum joint space error was decreased by 76.68% when using septic joint profile compared to the ordinary linear Cartesian trajectory planning approach. Upon applying the proposed strategy, the error of the controller has been reduced by 92.26% with respect to the previous research performed on this experimental setup. Without requiring any knowledge on the dynamic model of the robot or the natural frequencies of the end-effector or using any complex controller, this method significantly increased the smoothness and accuracy of the robot movements. The proposed method can be regarded as a definitive asset when this robot is used for video capturing purposes.

关键词： Vibrations Parallel robots Trajectory planning Simulated annealing Games Aerospace electronics End effectors

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All-Printed 3d Solid-State Rechargeable Zinc-Air Micro-Batteries

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SSRN 2022年

作者： Liu, Gengsheng Ma, Zhaolei Li, Guoxian Yu, Wei Wang, Peng Meng, Chuizhou Guo, Shijie State Key Laboratory for Reliability and Intelligence of Electrical Equipment Hebei Key Laboratory of Smart Sensing and Human-Robot Interaction School of Mechanical Engineering Hebei University of Technology Tianjin300401 China

Lightweight, compact, integrated and miniaturized energy devices are under high pursuit for portable and wearable electronics. However, improving the energy density per area still remains a long-standing challenge. Herein, we report the design and fabrication of a solid-state zinc-air micro-battery (ZAmB) by a facile 3D direct printing technique. The interdigital electrodes, gel electrolyte and encapsulation frame are all printed with customized design, with composition of the printing inks optimized to obtain the best battery performance. Multiple layers of interdigital electrodes are sequentially printed with a fine overlapping to achieve an ultrahigh thickness of 2.5 mm for a remarkably increased specific areal energy of up to 45.6 mWh cm−2. To meet different powering requirement for output voltage and current, battery modules consisting of individual ZAmBs connected in series or parallel or combination of the two are printed with a facile integration to external loads. Powering of LEDs, digital watch, mini rotary motor and even charging of a smartphone by the printed ZAmB modules are successfully demonstrated. The versatile 3D direct printing technique enables the fabricated ZAmBs with adjustable form factor and integration capability with other electronics, paving the way of exploring new energy systems with diverse structures and extended functionalities. © 2022, The Authors. All rights reserved.

关键词： 3D printers

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