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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Zhong, Ling Wang, Wen Zhu, Shiqiang Ji, Shanshan Zha, Changhai Wan, Minhong Gu, Jason Research Center for Intelligent Robotics Zhejiang Engineering Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Lab Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

With the wide application of service robots in people's daily life, people are not only satisfied with robots accomplishing tasks independently but also hope that robots can maintain sustainable interaction with human beings. Especially in the field of music, robots need to be equipped with intelligent cognitive skills in decision-making, so that the audience can enjoy immersive appreciation and emotional resonance in the robots performance. Visual perception and natural language understanding are essential for robots to establish human-robot friendly relationships. To enrich the interactive ability of music robots, we design a contactless interaction system based on facial expression recognition, which consists of four modules: voice wake-up, face detection, facial expression recognition, and music mapping. When people wake up the music robot with specific words, the robot will customize appropriate music to perform according to the recognition results of the FER module. As a final step, the interaction system has been successfully applied to the piano humanoid robot independently developed by our team. © 2022 IEEE.

关键词： Decision making

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Robot Embodied Dynamic Tactile Perception of Liquid in Containers 23

Robot Embodied Dynamic Tactile Perception of Liquid in Conta...

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23rd IEEE-RAS International Conference on Humanoid Robots, Humanoids 2024

作者： Xu, Yingtian Ma, Yichen Lin, Waner Sun, Zhenglong Zhang, Tianwei Wang, Ziya The Chinese Univ of Hong Kong School of Science and Engineering Shenzhen518172 China Shenzhen University Key Laboratory of Optoelectronic Devices and Systems Ministry of Education School of Physics and Optoelectronic Engineering Shenzhen518060 China Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Department of Micro-Nano Electronics Shanghai200240 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518129 China

ISBN: (纸本)9798350373578

Humans perceive objects and environments actively and dynamically using tactile sensing facilitated by the skin. However, due to the gap in sensing capabilities between electronic skin and human skin, it remains a challenge for robots to achieve intricate tactile perception. For example, the task of liquid properties estimation within containers, demands sensing and comprehension of complex dynamic tactile signals during contact. This paper introduces a novel tactile fingertip inspired by human skin enabling both static tactile sensing facilitated by a layer of porous piezoresistive elastomer and dynamic tactile sensing enabled by condenser microphones. A data-driven methodology is employed to analyze liquids through multimodal signals devoid of physical modelling. The proposed robotic system engages in shaking various bottles filled with different volumes of water, allowing the tactile fingertip to detect changes in grasping force caused by shaking and small vibrations caused by the collision of the container with liquid. Five machine learning models trained on these tactile signals are analyzed and compared. Experimental results demonstrate the proficiency of the tactile system in distinguishing liquid fill percentages across bottles of different shapes and capacities with a remarkable accuracy of 98%. This paper holds promise for advancing the embodied intelligence of robots, enhancing their ability to perceive mixed tactile signals dynamically, thereby facilitating tasks such as liquid estimation and other intricate tactile operations in environments like kitchens and hospitals. © 2024 IEEE.

关键词： Bottles

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QuerySOD: A Small Object Detection Algorithm Based on Sparse Convolutional Network and Query Mechanism

QuerySOD: A Small Object Detection Algorithm Based on Sparse...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Zhengcai Cao Junnian Li Jie Niu MengChu Zhou State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China College of Information Science and Technology Beijing University of Chemical Technology Beijing China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Although remarkable advances have been achieved in generic object detection, small object detection (SOD) remains challenging owing to small objects’ information loss and noisy representation caused by their non-uniform distribution. Their limited width and height, scale variations, and redundant computation make SOD hard. To overcome them, this work proposes a new SOD method based on sparse convolutional network (SCNet) and Query Mechanism called QuerySOD. First, an extended feature pyramid network is constructed for extracting feature maps of small objects with more regional details. Then, a Sparse Head is neatly designed by using SCNet for accelerating the interfering speed and obtaining weights of each layer. After that, a Query Mechanism is innovatively introduced for harvesting the benefit of sparse value feature maps from the Sparse Head. QuerySOD is evaluated on public benchmarks including COCO and VisDrone. Finally, we apply it on ‘Jinghai’ unmanned survey vehicles and receive excellent SOD performance from this real-world application.

关键词： Surveys Accuracy Object detection Seaports Lakes Feature extraction Prediction algorithms Convolutional neural networks Security Noise measurement

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Design, Dynamic Modeling and Control of a 2-DOF Robotic Wrist Actuated by Twisted and Coiled Actuators

arXiv

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arXiv 2025年

作者： Zhang, Yunsong Zhou, Xinyu Zhang, Feitian Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory of Turbulence and Complex Systems Peking University Beijing100871 China Department of Electrical and Computer Engineering Michigan State University East LansingMI48824 United States

Robotic wrists play a pivotal role in the functionality of industrial manipulators and humanoid robots, facilitating manipulation and grasping tasks. In recent years, there has been a growing interest in integrating artificial muscle-driven actuators for robotic wrists, driven by advancements in technology offering high energy density, lightweight construction, and compact designs. However, in the study of robotic wrists driven by artificial muscles, dynamic model-based controllers are often overlooked, despite their critical importance for motion analysis and dynamic control of robots. This paper presents a novel design of a two-degree-of-freedom (2-DOF) robotic wrist driven by twisted and coiled actuators (TCA) utilizing a parallel mechanism with a 3RRRR configuration. The proposed robotic wrist is expected to feature lightweight structures and superior motion performance while mitigating friction issues. The Lagrangian dynamic model of the wrist is established, along with a nonlinear model predictive controller (NMPC) designed for trajectory tracking tasks. A prototype of the robotic wrist is developed, and extensive experiments are conducted to validate its superior motion performance and the proposed dynamic model. Subsequently, extensive comparative experiments between NMPC and PID controller were conducted under various operating conditions. The experimental results demonstrate the effectiveness and robustness of the dynamic model-based controller in the motion control of TCA-driven robotic wrists. Copyright © 2025, The Authors. All rights reserved.

关键词： Industrial manipulators

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Customizing Textile and Tactile Skins for Interactive Industrial Robots

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ASME Letters in Dynamic systems and Control 2023年第3期3卷 031007页

作者： Su, Bo Ying Wei, Zhongqi McCann, James Yuan, Wenzhen Liu, Changliu Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA 15213 Department of Mechanical Engineering Carnegie Mellon University Pittsburgh PA 15213 Robotics Institute Carnegie Mellon University Pittsburgh PA 15213

Tactile skins made from textiles enhance the robot–human interaction by localizing contact points and measuring contact forces. This paper presents a solution for rapidly fabricating, calibrating, and deploying these skins on industrial robot arms. The novel automated skin calibration procedure maps skin locations to robot geometry and calibrates contact force. Through experiments on a FANUC LR Mate 200id/7L industrial robot, we demonstrate that tactile skins made from textiles can be effectively used for human–robot interaction in industrial environments, and can provide unique opportunities in robot control and learning, making them a promising technology for enhancing robot perception and interaction.

关键词： Robots sensors and sensor networks Calibration textile and tactile skin Textiles Skin interactive industrial robots skin calibration human-in-the-loop control robotics

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Keynote Talk: Qualitative model based diagnosis of complex systems using decomposition 22

Keynote Talk: Qualitative model based diagnosis of complex s...

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Proceedings of the 7th International Conference on Sustainable Information engineering and Technology

作者： Katalin M. Hangos Systems and Control Laboratory Institute for Computer Science and Control Hungary and Department of Electrical Engineering and Information Systems University of Pannonia Hungary

ISBN: (纸本)9781450397117

Decomposition offers the potential to reduce the complexity of model-based optimization, prediction, control and diagnosis by accounting for the structure and sparsity of the describing model. Motivated by this fact, a rich and powerful collection of decomposition methods are available for model based diagnosis of large-scale complex dynamic systems, too. At the same time, one usually does not have enough information about a large-scale complex dynamic system to construct its precise enough model, so a kind of qualitative dynamic model is often used for the diagnosis [1]. Two structural decomposition based qualitative diagnostic methods are presented in this lecture, together with their component-driven system decomposition ***, a model-based diagnostic method is described that is able to detect and isolate non-technical losses (illegal loads) in low voltage electrical grids of one transformer area [2]. As a preliminary off-line step of the diagnosis, a powerful electrical decomposition method is proposed, which breaks down the overall network to subsystems with one feeder layout enabling to make the necessary computations efficient. The diagnostic method is based on analyzing the differences between the measured and model-predicted voltages. The uncertainty in the model parameters together with the measurement uncertainties are also taken into account to make the approach applicable in real-world cases. The proposed method is able to detect and localize multiple illegal loads, and the amount of the illegal consumption can also be *** a second case study, a high level decomposition approach for process system fault diagnosis using event traces is given [3], [4]. Using a simple component graph model behind the process system and the measured trace applied for the diagnosis, the method can find the root cause(s) of propagating failures between separate components. The method can connect individually operating lower-level component-specific diag

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Efficient Drinking Water Quality Analysis using Machine Learning Model with Hyper-Parameter Tuning 7

Efficient Drinking Water Quality Analysis using Machine Lear...

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7th International Conference on Intelligent Computing and Control systems, ICICCS 2023

作者： Maheswari, M Uma Sudharsanan, R. Arthy, M. Jenefer, Anne Oormila, L. Samuthira Pandi, V. RMD Engineering College Department of Electrical and Electronics Engineering Tamil Nadu India SRM Institute of Science and Technology Department of Information Technology Tamil Nadu Ramapuram India SRM Institute of Science and Technology Department of Data Science and Business Systems Tamil Nadu Kattankulathur India Panimalar Engineering College Department of Electronics and Communication Engineering Tamil Nadu India Agni College of Technology Department of Computer Science Engineering Tamil Nadu India SRM Institute of Science and Technology Department of Electronics Ad Communication Engineering Tamilnadu Ramapuram India

ISBN: (纸本)9798350397253

The conventional approaches to determining the quality of water include costly and lengthy statistical and laboratory testing;hence, the concept of real-time monitoring is no longer applicable in the modern day. The disastrous implications of poor water quality demand that there be a remedy that is both more expedient and more realistic. This research study examines a variety of supervised machine learning algorithms in order to identify the quality of the water. A variety of variables, such as the pH value, the hardness, the solids, the chloramines, the sulfates, the conductivity, the organic carbon, the trihalomethanes, the turbidity, and the potability of the water, are essential for determining the quality of the water. Random Forest (RF) and Decision Tree (DT) are used in order to ascertain the caliber of the water that is suitable for human consumption. The standard laboratory approach for testing the quality of water is one that takes a lot of time and may be somewhat expensive at times. In a very short length of time, the algorithms that are proposed in this study are able to provide an estimation of the quality of drinking water. DT has a height accuracy F1 score of 99%, whereas RF has a score of 87.86% and a precision of 82.36%. The difference in these two scores is due to the fact that DT's precision is lower. The suggested method demonstrates its potential for usage in real-time water quality monitoring systems by achieving appropriate accuracy with a minimal set of parameters. To prove the usefulness of this program, this is essential. © 2023 IEEE.

关键词： Water quality

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Analysis of Parasitic Stored Energy Loss and PCB Layout Optimization for 48V-to-1V Series-Capacitor Buck

Analysis of Parasitic Stored Energy Loss and PCB Layout Opti...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Xinmiao Xu Qiang Li Department of Electrical and Computer Engineering Center for Power Electronics Systems Virginia Polytechnic Institute and State University Blacksburg VA United States

As power conversion architectures based on 48-V bus rails become more widely adopted, there are a growing number of single-stage solutions that directly convert 48 V to core voltages of microprocessors. This paper presents series-capacitor buck (SCB) solutions that feature minimal high-frequency loop inductance. With the interaction between transistor output capacitance and current commutation loop inductance included, the effect of parasitic stored energy on converter efficiency is analyzed for SCB in point-of-load applications. Different layouts of printed circuit boards are compared to minimize the commutation loop inductance, which helps realize high switching frequency, low filter inductance and high efficiency simultaneously. A 48V-to-1.8V MOSFET-based prototype switching at 700 kHz is constructed, which achieves 94.18% peak efficiency, 91.14% full-load efficiency (including gating loss) and 402 W/in 3 power density with 30-A current per phase. The same hardware operating at 500 kHz achieves 92.55% peak efficiency and 88.74% full-load efficiency at 1.0-V output voltage. Experimental designs based on gallium nitride transistors are also included for comparison.

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Hybrid Modulation Method for Single Phase Full Bridge CRM Inverter to Improve Reactive Power Capability

Hybrid Modulation Method for Single Phase Full Bridge CRM In...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Xingyu Chen Qiang Li The Bradley Department of Electrical and Computer Engineering Center for Power Electronics Systems Virginia Polytechnic Institute and State University Blacksburg VA USA

This paper presents a hybrid modulation method for single phase full bridge critical conduction mode (CRM) inverter aimed at improving the reactive power capability. The conventional unipolar modulation method causes a current distortion issue under non-unity power factor operation and faces an extremely high switching frequency problem at line current i αc zero-crossing point. The proposed approach combines the benefits of unipolar modulation and bipolar modulation and resolves the current distortion problem. The discontinuous current mode (DCM) modulation is applied during i ac zero-crossing area to eliminate the high switching frequency problem. The efficacy of the proposed modulation method is validated through both simulation and hardware experimentation.

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Symmetric Series-Capacitor Buck in 48V-to-12V Regulated Conversion for High-Performance Server Boards

Symmetric Series-Capacitor Buck in 48V-to-12V Regulated Conv...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Xinmiao Xu Qiang Li Department of Electrical and Computer Engineering Center for Power Electronics Systems Virginia Polytechnic Institute and State University Blacksburg VA United States

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

This paper presents an extended-conversion-ratio modulation for a two-phase symmetric series-capacitor buck (SSCB) converter. With the proposed scheme, highly efficient and regulated 48V-to-12V conversion can be realized with the SSCB topology. A versatile regulated first stage streamlines power delivery architectures for server boards in data centers, because regulated 12-V buses not only serve loads requiring well-controlled 12-V input but also simplify design and optimization of a 12V-to-1V second stage for processors. Based on this idea, a highly efficient and regulated power architecture is proposed for 48-V server boards. A prototype is built with gallium nitride (GaN) transistors and minimal high-frequency loop inductance, operating with a relatively wide input voltage range from 40 V to 60 V and generating a regulated 12-V output. In 48V-to-12V regulated conversion, the GaN-based prototype achieves 98.88% peak efficiency, 98.11% full-load efficiency (including gating loss) and 787 W/inch 2 power density with 80-A output current, which is beyond the performance of state-of-the-art commercially available solutions.

关键词： Power system measurements Density measurement Switching frequency Prototypes Topology Servers Transistors Voltage control Gallium nitride Switching circuits

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