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SSRN 2024年

作者： Seong, Jihun Han, Yeji Seo, Suyeon Han, Min-Woo Department of Mechanical Engineering Dongguk University Seoul04620 Korea Republic of Department of Mechanical Robotics and Energy Engineering Dongguk University Seoul04620 Korea Republic of

This study presents composite resistive soft tactile sensors combining conductive fabric and polydimethylsiloxane. The sensors utilize the changes in resistance of the conductive fabric when stretched to sense the pressure, while reducing the volatility of resistance of the conductive fabric by embedding the fabric within the elastomer matrix. The sensors have a compact design, a simple fabrication process using cost-effective materials, and a compliant structure. The performance evaluation of 12 samples was conducted to assess their linearity, sensitivity, time responses, and reliability, considering variations in electrode shape and width, and sensor thickness. A particular sample was chosen for its universal applicability, characterized by a rise time of ~0.38 seconds, a decay time of ~2.71 seconds, a settling time of ~851.8 seconds, and a sensitivity of 0.9333 kPa/%. Finally, the potential applications were proposed using the selected sensor, including LED control and joint detection, showcasing its capability to support closed-loop systems. © 2024, The Authors. All rights reserved.

关键词： Silicones

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On Relation Between Leakage-Free Condition and Differential Filtering Order in ETFE-Based Frequency Responce Function Estimation*

On Relation Between Leakage-Free Condition and Differential ...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Yoshihiro Maeda Taishi Yazawa Shimpei Sato Wataru Hara Department of Engineering Electrical and Mechanical Engineering Program Nagoya Institute of Technology Nagoya Japan

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

Estimation of an accurate frequency response function (FRF) of a target system is crucial to design fine servo controllers that realize fast and precise positioning control. The empirical transfer function estimation (ETFE) is the most representative and simplest FRF estimation method in terms of industrial utility. However, its applicability is limited to input and output signals of a target system measured during periodic or reciprocating operations, due to leakage errors induced by the discrete Fourier transform. Recently, an FRF estimation method combining ETFE with differential filtering has been proposed, which enables accurate FRF estimation in point-to-point motion. This paper theoretically clarifies the relationship between leakage-free condition and the differential filtering order in the ETFE-based FRF estimation framework. Furthermore, it is demonstrated through simulations that increasing the differential filtering order can broaden the input and output signals acquisition conditions that enables accurate FRF estimation.

关键词： Accuracy Mechatronics Filtering Noise Measurement uncertainty Estimation Transfer functions

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Model-Based Position Control of Energy-Efficient Electro-Hydraulic Linear Drives

Model-Based Position Control of Energy-Efficient Electro-Hyd...

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Intelligent robotics and Automatic Control (IRAC), International Conference on

作者： Xieli Zhang Damiano Padovani Department of Mechanical Engineering (Robotics) Guangdong Technion-Israel Institute of Technology Shantou China

ISBN: (数字)9798350389807

ISBN: (纸本)9798350389814

The rising interest in energy efficiency for hydraulic systems directs the research towards electro-hydraulic drives, namely linear actuators (i.e., hydraulic cylinders) directly coupled to pumps driven by electric motors. This approach removes functional power dissipations, enables energy recovery, and facilitates system commissioning. However, these drives are characterized by inherently low damping that causes unwanted payload oscillations and deteriorates the position control’s accuracy of the actuator. Adding active damping via proper control techniques is essential. Hence, this paper develops a model-based design for closed-loop position control with the addition of high-pass-filtered pressure feedback. The model supports identifying crucial control parameters, such as the proportional and integral gains of the position feedback and the gain and time constant of the pressure feedback. This method is experimentally tested on a heavy-duty robotic manipulator. The results show that the payload oscillations are reduced dramatically, and the position tracking is accurate and robust for different load cases.

关键词： Damping Actuators Accuracy Position control Hydraulic systems Manipulators Energy efficiency Oscillators Payloads Load modeling

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Framework for Robust Localization of UUVs and Mapping of Net Pens

arXiv

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arXiv 2024年

作者： Botta, David Ebner, Luca Studer, Andrej Reijgwart, Victor Siegwart, Roland Kelasidi, Eleni The Department of Mechanical and Process Engineering ETH Switzerland Tethys Robotics Switzerland The Aquaculture Robotics and Automation Group SINTEF Ocean

This paper presents a general framework integrating vision and acoustic sensor data to enhance localization and mapping in highly dynamic and complex underwater environments, with a particular focus on fish farming. The proposed pipeline is suited to obtain both the net-relative pose estimates of an Unmanned Underwater Vehicle (UUV) and the depth map of the net pen purely based on vision data. Furthermore, this paper presents a method to estimate the global pose of an UUV fusing the net-relative pose estimates with acoustic data. The pipeline proposed in this paper showcases results on datasets obtained from industrial-scale fish farms and successfully demonstrates that the vision-based TRU-Depth model, when provided with sparse depth priors from the FFT method and combined with the Wavemap method, can estimate both net-relative and global position of the UUV in real time and generate detailed 3D maps suitable for autonomous navigation and inspection purposes. © 2024, CC BY.

关键词： Fish

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Optically-generated focused ultrasound for noninvasive brain stimulation with ultrahigh precision

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Light(Science & Applications) 2022年第11期11卷 2817-2831页

作者： Yueming Li Ying Jiang Lu Lan Xiaowei Ge Ran Cheng Yuewei Zhan Guo Chen Linli Shi Runyu Wang Nan Zheng Chen Yang Ji-Xin Cheng Department of Mechanical Engineering Boston UniversityBostonMA 02215USA Graduate Program for Neuroscience Boston UniversityBostonMA 02215USA Department of Electrical and Computer Engineering Boston UniversityBostonMA 02215USA Department of Chemistry Boston UniversitBostonMA 02215USA Department of Biomedical Engineering Boston UniversityBostonMA 02215USA Division of Materials Science and Engineering Boston UniversityBostonMA 02215USA Department of Biological Engineering Massachusetts Institute of TechnologyCambridgeMA 02142USA

High precision neuromodulation is a powerful tool to decipher neurocircuits and treat neurological *** non-invasive neuromodulation methods offer limited precision at the milimeter ***,we report opticallygenerated focused ultrasound(OFUS)for non-invasive brain stimulation with ultrahigh *** is generated by a soft optoacoustic pad(SOAP)fabricated through embedding candle soot nanoparticles in a curved polydimethylsiloxane *** generates a transcranial ultrasound focus at 15 MHz with an ultrahigh lateral resolution of 83μm,which is two orders of magnitude smaller than that of conventional transcranial-focused ultrasound(tFUS).Here,we show effective OFUS neurostimulation in vitro with a single ultrasound *** demonstrate submillimeter transcranial stimulation of the mouse motor cortex in *** acoustic energy of 0.6 mJ/cm?,four orders of magnitude less than that of tFUS,is suffcient for successful OFUS *** offers new capabilities for neuroscience studies and disease treatments by delivering a focus with ultrahigh precision noninvasively.

关键词： SOAP stimulation precision

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Phase-Based Quantification of Sports Performance Metrics Using a Smart IoT Sensor

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IEEE Internet of Things Journal 2023年第18期10卷 15900-15911页

作者： Chen, Meng Szu, Hui Fang Lin, Hsin Yen Liu, Yifan Chan, Ho-Yin Wang, Yufan Zhao, Yuliang Zhang, Guanglie Yao, Jeffrey Da-Jeng Li, Wen Jung National Tsing Hua University Physical Education Office Hsinchu City300 Taiwan Kla Corporation Tainan City744 Taiwan Michigan State University Department of Electronic and Computer Engineering East LansingMI48824 United States Shanghai Jiao Tong University School of Mechanical Engineering Department of Industrial Engineering and Management Shanghai200240 China Northeastern University at Qinhuangdao Hebei Key Lab. of Micro-Nano Prec. Optical Sensing and Msrmt. Technol. Sch. of Control Engineering Qinhuangdao066004 China City University of Hong Kong Department of Mechanical Engineering Kowloon Tong Hong Kong City University of Hong Kong Shenzhen Research Institute CASŰCityU Joint Laboratory for Robotics Shenzhen518057 China National Tsing Hua University Department of Power Mechanical Engineering Hsinchu City300 Taiwan

Sports performance is often judged based on the results of a series of motions rather than observing and analyzing the detailed sequential motions that lead to the results. Hence, subjective feedback from the coaches is often ineffective in improving player performance. In this work, we custom-built a smart Internet of Things wristband motion sensor to implement data-based sports performance evaluation. A phase-based feature selection method is also proposed to assess the athletes' sequential detailed motion for selected sport activities. To demonstrate the merits of this technology, we quantified the quality of the sequential motions of a specific type of volleyball serve by analyzing 183 samples of motion data obtained from a total of 18 players. The general skill levels (i.e., elite, subelite, and amateur) of the players were identified by machine learning algorithms, with accuracies of up to 95%. Moreover, we adopted biomechanical principles to extract 11 motion-related performance metrics from various phases of the players' serve motion. We identified the distributions of these metrics across different skill levels and found eight key metrics that were highly correlated to the skill level of a players. We suggest that these metric distributions can be used as a reference for providing feedback to the coaches and players, to improve a player's skill in the future. This phased-based analysis method can potentially be applied across many sports to increase the effectiveness of athletes' training. © 2014 IEEE.

关键词： Internet of things

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Constrained Control for Autonomous Spacecraft Rendezvous: Learning-Based Time Shift Governor

Constrained Control for Autonomous Spacecraft Rendezvous: Le...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Kim, Taehyeun Kee, Robin Inho Kolmanovsky, Ilya Girard, Anouck Department of Aerospace Engineering University of Michigan 1320 Beal Ave Ann ArborMI48109 United States Department of Mechanical Engineering University of Michigan Ann ArborMI48109 United States Department of Aerospace Engineering University of Michigan 3038 FXB 1320 Beal Ave Ann ArborMI48109 United States Robotics and Aerospace Engineering University of Michigan 3264 FMCRB 2505 Hayward Street Ann ArborMI48109 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This paper develops a Time Shift Governor (TSG)-based control scheme to enforce constraints during rendezvous and docking (RD) missions in the setting of the Two-Body problem. As an add-on scheme to the nominal closed-loop system, the TSG generates a time-shifted Chief spacecraft trajectory as a target reference for the Deputy spacecraft. This modification of the commanded reference trajectory ensures that constraints are enforced while the time shift is reduced to zero to effect the rendezvous. Our approach to TSG implementation integrates an LSTM neural network which approximates the time shift parameter as a function of a sequence of past Deputy and Chief spacecraft states. This LSTM neural network is trained offline from simulation data. We report simulation results for RD missions in the Low Earth Orbit (LEO) and on the Molniya orbit to demonstrate the effectiveness of the proposed control scheme. The proposed scheme reduces the time to compute the time shift parameter in most of the scenarios and successfully completes rendezvous missions. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Orbits

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Frequency Measurement Using Frequency Control to Improve Distance Resolution of FMCW LiDAR

Frequency Measurement Using Frequency Control to Improve Dis...

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IEEE SENSORS

作者： Jubong Lee Youngjoon Cho Kyihwan Park Department of mechanical and robotics engineering Gwangju institute of science and technology Gwangju Repulic of Korea

ISBN: (数字)9798350363517

ISBN: (纸本)9798350363524

Frequency modulation continuous wave (FMCW) LiDAR is valued for its robustness in harsh environments like rain, snow, and fog. It measures distance by detecting interference frequencies between transmitted and received beams, typically using Fast Fourier Transform(FFT). However, FFT is slow in achieving high-resolution frequency measurements. This study proposes using a frequency-to-voltage converter (FVC) for faster measurement through one-shot conversion. Despite its speed, FVC introduces ripple noise, reducing resolution. To mitigate this noise, a frequency control technique shifts the frequency to minimize ripple noise, indirectly measuring the interference frequency. The paper provides mathematical analysis and experimental validation of this method.

关键词： Laser radar Frequency modulation Rain Snow Noise Interference Frequency measurement Frequency control Autonomous vehicles Meteorology

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A ground robotic system for crops and soil monitoring and data collection in New Mexico chile pepper farms

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Discover Agriculture 2024年第1期2卷 1-26页

作者： Linford, Jordan Haghshenas-Jaryani, Mahdi Department of Mechanical and Aerospace Engineering New Mexico State University Las Cruces USA Bioinspired and Biomimetic Robotics (Bio²Robotics) Laboratory NMSU Las Cruces USA

This work presents the development and system integration of a ground agricultural mobile manipulator robot that is capable of traversing a field in order to monitor the health of the field and crops. The robotic platform consists of a 4-wheeled drive base rover that has a 6 degrees of freedom (DOF) robotic manipulator attached to it, which is equipped with a multitude of sensors that are used for navigation, crop inspection, and soil monitoring. To accurately measure the moisture of the soil using the moisture probe, the insertion process is very important, as the probe has to be inserted to the correct depth and be flush with the soil. It is for this reason, that the insertion process is difficult, as the field can be rough and uneven terrain. Utilizing a camera attached to the wrist of the robotic manipulator, the soil insertion process can be adjusted to more accurately insert the soil probe into the terrain with a varying degree of slopes. Along with detecting the slope of the soil to perform an accurate soil insertion, the robotic system is capable of detecting plants in various stages of development, and capture images to visually determine the crops health. The successful operation of the robot for in-situ soil measurements, crops image capturing, plant’s physical characteristics detection, and an autonomous soil slope alignment for sensor insertion have been demonstrated.

关键词：

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VibNet: Vibration-Boosted Needle Detection in Ultrasound Images

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IEEE Transactions on Medical Imaging 2025年第6期44卷 2696-2708页

作者： Huang, Dianye Li, Chenyang Karlas, Angelos Chu, Xiangyu Samuel Au, K.W. Navab, Nassir Jiang, Zhongliang Munich80333 Germany Munich80333 Germany Technical University of Munich CAMP Munich80333 Germany Technical University of Munich School of Medicine Munich80333 Germany The Chinese University of Hong Kong Department of Mechanical and Automation Engineering New Territories Hong Kong Multi-Scale Medical Robotics Centre Hong Kong

Precise percutaneous needle detection is crucial for ultrasound (US)-guided interventions. However, inherent limitations such as speckles, needle-like artifacts, and low resolution make it challenging to robustly detect needles, especially when their visibility is reduced or imperceptible. To address this challenge, we propose VibNet, a learning-based framework designed to enhance the robustness and accuracy of needle detection in US images by leveraging periodic vibration applied externally to the needle shafts. VibNet integrates neural Short-Time Fourier Transform and Hough Transform modules to achieve successive sub-goals, including motion feature extraction in the spatiotemporal space, frequency feature aggregation, and needle detection in the Hough space. Due to the periodic subtle vibration, the features are more robust in the frequency domain than in the image intensity domain, making VibNet more effective than traditional intensity-based methods. To demonstrate the effectiveness of VibNet, we conducted experiments on distinct ex vivo porcine and bovine tissue samples. The results obtained on porcine samples demonstrate that VibNet effectively detects needles even when their visibility is severely reduced, with a tip error of 1.61 ± 1.56 mm compared to 8.15 ± 9.98 mm for UNet and 6.63 ± 7.58 mm for WNet, and a needle direction error of 1.64 ± 1.86° compared to 9.29 ± 15.30° for UNet and 8.54 ± 17.92° for WNet. © 1982-2012 IEEE.

关键词： Needles

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