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arXiv 2023年

作者： Lee, Ung Hee Shepherd, Tor Kim, Sangbae De, Avik Su, Hao Gregg, Robert Mooney, Luke Rouse, Elliott Neurobionics Lab. University of Michigan Ann ArborMI48109 United States Department of Mechanical Engineering University of Michigan United States The Robotics Institute University of Michigan United States Department of Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA19104 United States Lab of Biomechatronics and Intelligent Robotics Department of Mechanical Engineering and Aerospace Engineering North Carolina State University RaleighNC27695 United States Department of Electrical Engineering and Computer Science University of Michigan United States Dephy Inc. MaynardMA01754 United States

A key step in the development of lightweight, high performance robotic systems is the modeling and selection of permanent magnet brushless direct current (BLDC) electric motors. Typical modeling analyses are completed a priori, and provide insight for properly sizing a motor for an application, specifying the required operating voltage and current, as well as assessing the thermal response and other design attributes e.g. transmission ratio). However, to perform these modeling analyses, proper information about the motor’s characteristics are needed, which are often obtained from manufacturer datasheets. Through our own experience and communications with manufacturers, we have noticed a lack of clarity and standardization in modeling BLDC motors, compounded by vague or inconsistent terminology used in motor datasheets. The purpose of this tutorial is to concisely describe the governing equations for BLDC motor analyses used in the design process, as well as highlight potential errors that can arise from incorrect usage. We present a power-invariant conversion from phase and line-to-line reference frames to a familiar q-axis DC motor representation, which provides a "brushed" analogue of a three phase BLDC motor that is convenient for analysis and design. We highlight potential errors including incorrect calculations of winding resistive heat loss, improper estimation of motor torque via the motor’s torque constant, and incorrect estimation of the required bus voltage or resulting angular velocity limitations. A unified and condensed set of governing equations is available for designers in Appendix A. The intent of this work is to provide a consolidated mathematical foundation for modeling BLDC motors that addresses existing confusion and fosters high performance designs of future robotic systems. © 2023, CC BY-NC-ND.

关键词： Design

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Enabling Autonomous Ultrasound-Guided Tumor Ablation During Robotic Surgery

Enabling Autonomous Ultrasound-Guided Tumor Ablation During ...

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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： Nils Marahrens Dominic Jones Jack Stevenson James McLaughlan Chandra Shekhar Biyani Margaret Lucas Pietro Valdastri Institute of Robotics Autonomous Systems and Sensing (IRASS) School of Electronic and Electrical Engineering Uni-versity of Leeds Leeds UK Centre for Medical and Industrial Ultrasonics (C-MIU) James Watt School of Engineering University of Glasgow Glasgow UK Department for Urology James's Uni-versity Hospital Leeds Teachings Hospitals NHS Trust Leeds UK

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

While technologies such as cryo- or radio-frequency ablation allow for less invasive treatment of tumors than re-section, they still require needles to reach the target location with the potential risk of spreading tumor tissue around. High Intensity Focused Ultrasound (HIFU) on the other hand allows for a completely remote and concentrated delivery of energy to a target location without the need for direct access and is particularly well suited to be robotically guided and thus used as part of an autonomous system. While robotic HIFU devices have been extensively explored for extracorporeal applications, their application into a laparoscopic setting is still widely unexplored. This paper presents a novel robotic HIFU pick-up device along with an automated workflow that includes the autonomous acquisition of the tumor geometry via Ultrasound (US) imaging, trajectory planning and autonomous execution of the HIFU ablation constraint by the tissue surface. Therefore, a novel sensorised water-filled membrane is developed and evaluated, enabling hybrid force position control that allows for minimising interaction forces with the tissue surface while maintaining sufficient acoustic coupling for ablation. Experiments on a phantom with a HIFU probe dummy demonstrate the effectiveness of the approach in targeting hidden structures.

关键词： Point cloud compression Accuracy Ultrasonic imaging Transducers Trajectory planning Phantoms Kinematics Acoustics Trajectory Tumors

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Hybrid Disassembly Line Balancing for Human-robot Collaborative Remanufacturing

Hybrid Disassembly Line Balancing for Human-robot Collaborat...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Feng Guo XiWang Guo MengChu Zhou Weitian Wang ShuJin Qin Qi Kang College of Information and Control Engineering Liaoning Petrochemical University Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA Collaborative Robotics and Smart Systems Laboratory (CRoSS Lab) Montclair State University Montclair NJ USA College of Economics and Management Shangqiu Normal University Shangqiu P R. China

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

As technologies advance rapidly, the urgency of remanufacturing is escalating. Efficient disassembly processes are crucial at the outset of remanufacturing. This work proposes an innovative disassembly scheme aimed at amplifying efficiency through the utilization of parallelization and human-robot collaboration in the context of a hybrid disassembly line. A single-objective mixed-integer programming model is developed to optimize disassembly profit. A discrete salp swarm algorithm is proposed to solve it since it is NP-hard. We have proposed and integrated uniform variation and two-point crossover operators in this algorithm. After comparing its results with those of the exact solver and other intelligent optimization methods, we conclude its competitive performance in both solution quality and efficiency.

关键词： Computer aided software engineering Automation Optimization methods Human-robot interaction Collaboration Programming

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Creating Own AI Datasets from Different Language Sources Efficiently: Advantages, Disadvantages and Best Pracitces to Make Own Datasets 6

Creating Own AI Datasets from Different Language Sources Eff...

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6th IEEE International Conference and Workshop Obuda on electrical and Power engineering, CANDO-EPE 2023

作者： Molnar, Gyorgy Cserko, Jazsef Nagy, Eniko Balogh, Zoltan Óbuda University Kandó Kálmán Faculty of Electrical Engineering Budapest Hungary Széchenyi University János Csere Apáczai Faculty Győr Hungary John von Neumann University Gamf Faculty of Engineering and Computer Science Kecskemét Hungary Győr Hungary Institute of Cyberphysical Systems Óbuda University Antal Bejczy Center for Intelligent Robotics John von Neumann Faculty Budapest Hungary Constantine the Philosopher University in Nitra Faculty of Natural Sciences and Informatics Department of Informatics Nitra94901 Slovakia

ISBN: (纸本)9798350328752

Artificial Intelligence (AI) has become a ubiquitous technology that has the potential to revolutionize many industries. However, AI requires access to vast amounts of data to achieve its full potential. By understanding these data sources and the best practices for working with them, we can unlock the full potential of AI and create groundbreaking solutions that benefit society as a whole. Data sources can be utilized to train AI algorithms, including structured and unstructured data, but finding relevant datasets is challenging. The main problem is the international sources. Most of the datasets are available only in English or other common languages. However these are good sources, but translating them is expensive and time-consuming. This paper shows how to generate own datasets from open-source data with translation. © 2023 IEEE.

关键词： Artificial intelligence

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Deep Learning-Based Prediction of Subsurface Oil Reservoir Pressure Using Spatio-Temporal Data

Deep Learning-Based Prediction of Subsurface Oil Reservoir P...

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Annual Conference of Industrial Electronics Society

作者： Haibo Cheng Yunpeng He Peng Zeng Shichao Li Valeriy Vyatkin State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden Department of Electrical Engineering and Automation Aalto University Helsinki Finland

Prediction of subsurface oil reservoir pressure are critical to hydrocarbon production. However, the accurate pressure estimation faces great challenges due to the complexity and uncertainty of reservoir. The underground seepage flow and petrophysical parameters (permeability and porosity) are important but difficult to measure in oilfield. Deep learning methods have been successfully used in reservoir engineering and oil & gas production process. In this study, the effective but inaccessible subsurface seepage fields are not used, only the spatial coordinates and temporal information are selected as model input to predict reservoir pressure. A stacked GRU-based deep learning model is proposed to map the relationship between spatio-temporal data and reservoir pressure. The proposed deep learning method is verified by using a three-dimensional reservoir model, and compared with commonly-used methods. The results show that the stacked GRU model has a better performance and higher accuracy than other deep learning or machine learning methods in pressure prediction.

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Hardware-in-the-Loop Simulation of Vehicle-Manipulator systems for Physical Interaction Tasks

Hardware-in-the-Loop Simulation of Vehicle-Manipulator Syste...

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

作者： Hemjyoti Das Bjørn Kåre Sæbø Kristin Y. Pettersen Christian Ott Faculty of Electrical Engineering and Information Technology Automation and Control Institute (ACIN) Technical University of Vienna TU Wien Vienna Austria Department of Engineering Cybernetics Centre for Autonomous Marine Operations and Systems (NTNU AMOS) NTNU Norwegian University of Science and Technology Trondheim Norway German Aerospace Center Institute of Robotics and Mechatronics Wessling Germany

Hardware-in-the-loop simulation (HILS) allows a more realistic evaluation of control approaches than what is possible with pure software simulations, but without the actual complexity of the complete system. This is important for some complex systems such as orbital robots, where testing of the system is typically not possible after its launch, and an on-ground replica is used to validate the performance of such a system. In this article, an impedance-matching approach is presented to match the end-effector dynamics of a fixed-base robot manipulator with that of a target vehicle-manipulator system (VMS), while taking into account the redundant nullspace dynamics in a connected real-time simulation framework. This approach ensures that the forces and torques exerted by the system on the environment matches with that of the simulated system. The contact wrenches used in our approach are not obtained from numerical simulations, but rather from real physical interaction, which is one of the main advantages of our approach. The effectiveness of our method is validated by demonstrating various physical interaction tasks with the environment, using a suspended aerial manipulator as the target system.

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An EMG-Based Objective Function for Human-in-the-Loop Optimization

An EMG-Based Objective Function for Human-in-the-Loop Optimi...

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IEEE International Conference on Rehabilitation robotics (ICORR)

作者： María Alejandra Díaz Sander De Bock Philipp Beckerle Jan Babič Tom Verstraten Kevin De Pauw Human Physiology and Sports Physiotherapy Research Group Brussels Human Robotic Research Center Vrije Universiteit Brussel Brussels Belgium Department of Electrical Engineering and the Department of Artificial Intelligence in Biomedical Engineering Institute of Autonomous Systems and Mechatronics Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Department of Automation Biocybernetics and Robotics Laboratory for Neuromechanics and Biorobotics Jožef Stefan Institute Ljubljana Slovenia Faculty of Electrical Engineering University of Ljubljana Ljubljana Slovenia Robotics and Multibody Mechanics Research Group Vrije Universiteit Brussel and Flanders Make Brussels Belgium

Advancements in wearable robots aim to improve the users' motion, performance, and comfort by optimizing, mainly, energetic cost (EC). However, EC is a noisy measurement with a physiological delayed response that requires long evaluation periods and wearing an uncomfortable mask. This study aims to estimate and minimize an EMG-based objective function that describes the natural energetic expenditure of individuals walking. This objective is assessed by combining multiple electromyography (EMG) variables from the EMG intensity and muscle synergies. To evaluate this objective function simply and repeatedly, we prescribed step frequency (SF) via a metronome and optimized this frequency to minimize muscle activity demands. Further, a linear mixed-effects model was fitted for EC, with the EMG variables as fixed-effects and a random intercept that varies by participant. After the model was fitted to the data, a cubic polynomial was used to identify the optimal SF that reduces the overall EMG-based objective function. Our analysis outlines that the proposed objective function is comparable to the EC during walking, the primary objective function used in human-in-the-loop optimization. Thus, this EMG-based objective function could be potentially used to optimize wearable robots and improve human-robot interaction.

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Spatio-temporal Motion Planning for Autonomous Vehicles with Trapezoidal Prism Corridors and Bézier Curves

Spatio-temporal Motion Planning for Autonomous Vehicles with...

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American Control Conference (ACC)

作者： Srujan Deolasee Qin Lin Jialun Li John M. Dolan Department of Computer Science & Information Systems Birla Institute of Technology and Science Pilani Rajasthan India Department of Electrical Engineering and Computer Science Cleveland State University Cleveland OH USA Dajiang Innovation Technology Co. Ltd Shenzhen China Robotics Institute Carnegie Mellon University Pittsburgh PA USA

Safety-guaranteed motion planning is critical for self-driving cars to generate collision-free trajectories. A layered motion planning approach with decoupled path and speed planning is widely used for this purpose. This approach is prone to be suboptimal in the presence of dynamic obstacles. Spatial-temporal approaches deal with path planning and speed planning simultaneously; however, the existing methods only support simple-shaped corridors like cuboids, which restrict the search space for optimization in complex scenarios. We propose to use trapezoidal prism-shaped corridors for optimization, which significantly enlarges the solution space compared to the existing cuboidal corridors-based method. Finally, a piecewise Bézier curve optimization is conducted in our proposed corridors. This formulation theoretically guarantees the safety of the continuous-time trajectory. We validate the efficiency and effectiveness of the proposed approach in numerical and CommonRoad simulations.

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Machine Learning-Enabled Power Scheduling in IoT-Based Smart Cities

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Computers, Materials & Continua 2021年第5期67卷 2449-2462页

作者： Nabeela Awan Salman Khan Mohammad Khalid Imam Rahmani Muhammad Tahir Nur Alam MD Ryan Alturki Ihsan Ullah Department of Computer Science Government Girls Degree College MardanKPK23200Pakistan Department of Electrical Energy System UETPeshawar25000Pakistan Department of Computer Science College of Computing and InformaticsSaudi Electronic UniversityKSA Department of Smart Computing Kyungdong UniversityGlobal CampusGosung24764South Korea Department of Information Sciences College of Computer and Information SystemsUmm Al-Qura UniversityMakkahSaudi Arabia Robotics Engineering Daegu Gyeongbuk Institute of Science and TechnologySouth Korea

Recent advancements in hardware and communication technologies have enabled worldwide interconnection using the internet of things(IoT).The IoT is the backbone of smart city applications such as smart grids and green energy *** smart cities,the IoT devices are used for linking power,price,energy,and demand information for smart homes and home energy management(HEM)in the smart *** complex smart gridconnected systems,power scheduling and secure dispatch of information are the main research *** challenges can be resolved through various machine learning techniques and data *** this paper,we have proposed a particle swarm optimization based machine learning algorithm known as a collaborative execute-before-after dependency-based requirement,for the smart *** proposed collaborative execute-before-after dependencybased requirement algorithm works in two phases,analysis and assessment of the requirements of end-users and power distribution *** the rst phases,a xed load is adjusted over a period of 24 h,and in the second phase,a randomly produced population load for 90 days is evaluated using particle swarm *** simulation results demonstrate that the proposed algorithm performed better in terms of percentage cost reduction,peak to average ratio,and power variance mean ratio than particle swarm optimization and inclined block rate.

关键词： PSO IBR machine learning IoT smart cities CDBR

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Dynamic Behavior of Levitated Flexible Steel Plate in Bending Electromagnetic Levitation System During Disturbance Input

Dynamic Behavior of Levitated Flexible Steel Plate in Bendin...

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International Conference on electrical Machines and systems (ICEMS)

作者： Yamato Uchida Kazuki Ogawa Ikkei Kobayashi Jumpei Kuroda Daigo Uchino Keigo Ikeda Taro Kato Ayato Endo Takayoshi Narita Hideaki Kato Course of Mechanical Engineering Tokai University Hiratsuka Kanagawa Japan Department of Electronics and Robotics Aichi University of Technology Gamagori Aichi Japan Course of Science and National Institute of Standards and Technology Tokai University Hiratsuka Kanagawa Japan Research of Institute of Science and Technology Tokai University Hiratsuka Kanagawa Japan Department of Mechanical Engineering Numazu National College of Technology Numazu Shizuoka Japan Department of Mechanical Engineering Hokkaido University of Science Sapporo Hokkaido Japan Department of Mechanical Engineering Tokyo University of Technology Hachioji Tokyo Japan Department of Electrical Engineering Fukuoka Institute of Technology Fukuoka Fukuoka Japan Department of Mechanical Systems Engineering Tokai University Hiratsuka Kanagawa Japan

ISBN: (数字)9784886864406

ISBN: (纸本)9798350379105

In thin steel plate production lines, contact conveying by rollers is used, which sometimes results in scratches and plating defects on the steel plate surface. To solve this problem, non-contact conveyance by magnetic levitation is expected. When thin steel plates are magnetically levitated, magnetic levitation control becomes difficult due to deflection caused by the flexibility of the plate. Therefore, we have proposed a curved magnetic levitation system that improves the levitation stability by curving the steel plate for magnetic levitation. However, the dynamic behavior of thin steel plates during bending magnetic levitation have not been clarified. In this report, we performed a levitation experiments of bending steel plate, and input disturbance to the bending levitation device. From the measured response of levitated and oscillated steel plate, it was confirmed that the bending thin steel plate was in rigid body motion due to the disturbance.

关键词： Vibrations Production Bending Sensor phenomena and characterization Plating Market research Sensor systems Steel Frequency control Magnetic levitation

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