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Toward Development of Novel Remote Ultrasound Robotic System Using Soft robotics Technology

Journal of engineering and Science in Medical Diagnostics and Therapy 2024年第2期7卷 021012页

作者： Papendorp, Sky Ovando, Ammy Gharaie, Saleh Mosadegh, Bobak Guerra-Zubiaga, David Alaie, Seyedhamidreza Ashuri, Turaj Moghadam, Amir Ali Amiri Department of Robotics and Mechatronics Engineering Kennesaw State University MariettaGA30060 United States School of Engineering Deakin University GeelongVIC3216 Australia Department of Radiology Dalio Institute of Cardiovascular Imaging Weill Cornell Medicine New YorkNY10021 United States Department of Mechanical and Aerospace Engineering New Mexico State University Las CrucesNM88003 United States Southern Polytechnic College of Engineering and Engineering Technology Kennesaw State University MariettaGA30060 United States

This paper reports on the development of a novel soft robotic system for remote ultrasound applications. Direct contact of the ultrasound probe with the patient’s body represents a safety risk and therefore control of the probe’s positioning and applied force is a crucial task. The proposed robot uses a passive control system that provides safe interaction between the robot and the patient by leveraging soft robotics technology. The soft robot’s structure can be considered as a nonlinear spring which can be designed to exert a safe force within the robot’s workspace to guarantee the safety of human–robot interaction. The literature suggests that effective ultrasound imaging of both the heart and abdomen requires six degrees-of-freedom. These degrees-of-freedom consist of three translational motions, which are achieved using a novel hybrid soft cable-driven parallel robot, and three wrist motions, which is based on a universal joint design. The experimental results show that the robot can achieve all these six degrees-of-freedom, and its blocking force can be engineered to generate a uniform force within the workspace. Copyright © 2024 by ASME.

关键词： Probes

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MonoRollBot: 3-DOF Spherical Robot with Underactuated Single Compliant Actuator Design

MonoRollBot: 3-DOF Spherical Robot with Underactuated Single...

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IEEE International Conference on Soft robotics (RoboSoft)

作者： Zhiwei Liu Seyed Amir Tafrishi Geometric Mechanics and Mechatronics in Robotics (gm2R) Lab the School of Engineering Cardiff University Cardiff United Kingdom

ISBN: (数字)9798331520205

ISBN: (纸本)9798331520212

Spherical rolling robots have garnered significant attention in the field of mobile robotics for applications such as inspection and space exploration. Designing underactuated rolling robots poses challenges in achieving multi-directional propulsion with high degrees of freedom while utilizing a limited number of actuators. This paper presents the MonoRollBot, a novel 3-degree-of-freedom (DOF) spherical robot that utilizes an underactuated mechanism driven by only a single springmotor system. Unlike conventional spherical robots, MonoRoll-Bot employs a minimalist actuation approach, relying on only one motor and a passive spring to control its locomotion. The robot achieves 3-DOF motion through an innovative coupling of spring dynamics and motor control. In this work, we detail the design of the MonoRollBot and evaluate its motion capabilities through design studies. We also study its locomotion behaviours based on changes in rotating mass and stiffness properties.

关键词： Actuators Dynamics 3-DOF Soft robotics Propulsion Motors Stability analysis Space exploration Springs Robots

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Control Simulation of Proportional-Integral and Sliding Mode Control for Precision Seed Planters

Control Simulation of Proportional-Integral and Sliding Mode...

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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Yasir Nawaz Muhammad Usman Qadir Muhammad Awais Khan Izhar Ul Haq Kamran Shah Tahir Khan Department of Mechatronics Advanced Robotics & Automation Lab University of Engineering and Technology Peshawar Pakistan

The desired development and design of an electric control system (ECS) for a precision planter is one of the most crucial elements in evaluating the efficacy of applicators for plant production. The seeds would be sown using this approach. Years have been invested in the continuous development of a range of application methods and metering systems, each of which offers specific advantages for applying the required system with a high degree of precision. Researchers worldwide have been trying to make electric-driven seed meters (EDSM) for planters, but they haven't succeeded. This study looks into the current state of installing seed metering systems for precision planters. Proportional-integral (PI) and sliding mode control (SMC) designs of the control system have been implemented to improve the planting quality of the planters. We want to highlight the electrically driven control system (EDCS) using these designs. An overview of the noteworthy features and limitations of past research is given. We also discuss several future directions for future research, concentrating on the knowledge gaps in this area.

关键词： Meters Industries PI control Automation System performance Production Robustness

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An Efficient Inverse Kinematic Method for SSRMS-type Manipulator with Conformal Geometric Algebra

An Efficient Inverse Kinematic Method for SSRMS-type Manipul...

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

作者： Jingdong Zhao Jiayu Zhang Liangliang Zhao Zhonglai Tian Zirui Wang Wei Jiang Hong Liu School of Mechatronics Engineering State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin Heilongjiang Province China

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

SSRMS-type Manipulator is a typical type of space manipulator featuring 7-degree-of-freedom offset configuration with redundancy characteristic. It is challenging to solve inverse kinematics in high efficiency, make the upmost of redundancy characteristic, and select optimal redundant parameter. This paper proposes an analytical inverse kinematic method, named three-continuous-parallel-Link Direction Vector Parameterization (LDVP), in the theory of Conformal Geometric Algebra. This method employs the direction vector of the axis of parallel Joint 3, Joint 4, and Joint 5 as the parameter, and selects the optimal parameter according to context plan-points in a given trajectory. The process of solving inverse kinematics is divided into two steps, including solving joint positions and joint variables. The average solution time of forward and inverse kinematics is 9.79 us and 0.25 ms respectively. The continuous path tracking experiment verifies that all seven joints changing to pursue the optimal configuration, which makes full use of redundancy characteristic.

关键词： mechatronics Algebra Termination of employment Kinematics Manipulators Vectors Orbits

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Diagnosis of Localized Bearing Defects using Texture Analysis of Vibration Envelope Signals and Machine Learning

Diagnosis of Localized Bearing Defects using Texture Analysi...

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2023 International Conference on robotics and Automation in Industry, ICRAI 2023

作者： Nguyen, Cong Dai Nasir, Fazal E. Khan, Shahbaz Khan, Sheraz Ali Kim, Jong-Myon Le Quy Don Technical University Faculty of Radio-Electronic Engineering Hanoi Viet Nam Advanced Robotics and Automation Lab National Center for Robotics and Automation Peshawar Pakistan Institute of Manufacturing University of Engineering and Applied Sciences Swat Pakistan University of Engineering and Technology Department of Mechatronics Engineering Peshawar Pakistan University of Ulsan Department of IT Convergence Ulsan Korea Republic of PD Technology Ulsan Korea Republic of

ISBN: (纸本)9781665464727

Bearings are important because they play a critical role in the operation of many machines and devices by reducing friction and enabling smooth motion between two moving parts. They are commonly used in rotating machinery, such as electric motors, turbines, pumps, and gearboxes, where they support and guide the rotating shafts. The primary cause of failure in wind turbines and induction motors is bearing faults, resulting in significant downtime and economic losses. Detecting these faults accurately and promptly is crucial to preventing unexpected shutdowns. Most of the existing methods for bearing fault detection rely on envelope analysis, which involves filtering and demodulating the raw signal, and Fourier analysis of the envelope signal to identify defect frequencies. Recent research has focused on improving the visibility of these frequencies by selecting an optimal band for filtering, using sub-band analysis and spectral kurtosis, which is a complex process and can be time-consuming. This paper presents a new approach to envelope signal analysis using texture analysis of the envelope signals that are projected as 2D grayscale images where each fault generates a unique texture. These textures are encoded using the local binary pattern operator and then used for fault classification. The method is tested on a publicly available seeded fault dataset. © 2023 IEEE.

关键词： Signal analysis

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Real-Time Plant Disease Detection Using YOLOv5 and Autonomous Robotic Platforms for Scalable Crop Monitoring 9

Real-Time Plant Disease Detection Using YOLOv5 and Autonomou...

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9th International Conference on Control, robotics and Cybernetics, CRC 2024

作者： Hassan Tanveer, M. Fatima, Zainab Khan, Muzammil Ali Voicu, Razvan Cristian Farrukh Shahid, M. Kennesaw State University Department of Robotics and Mechatronics Engineering Marietta 30060 United States NED University of Engineering and Technology Department of Software Engineering Karachi Pakistan FAST University of computing and Emerging Science Department of AI and Data Science Karachi Pakistan

ISBN: (纸本)9798331517489

Plant diseases pose a significant threat to global food security, with annual losses amounting to billions of dollars. Early detection and intervention are critical for mitigating these losses. Traditional methods of disease detection, such as visual inspection, are time-consuming, labor-intensive, and often inefficient. This paper presents an advanced approach using the YOLOv5 (You Only Look Once) model, a state-of-the-art object detection algorithm, to identify and classify plant diseases in real-time. The YOLOv5 model offers high accuracy and efficiency, particularly for tasks requiring simultaneous detection of multiple objects, making it ideal for agricultural applications. This paper explores using novel data collection methods, such as mounting cameras on Husky UGV (Unmanned Ground Vehicle), to capture diverse images of crops from various angles in the field. These autonomous systems enhance dataset variety, contributing to more accurate detection results. Our methodology focuses on training the YOLOv5 model using annotated datasets, which enables the model to identify diseases such as apple rust leaf, bell pepper leaf spot, and others. The experimental results demonstrate a detection accuracy of 92 %, showcasing the potential of YOLOv5 for realtime crop disease monitoring. Integrating robotics for field analysis is further discussed as a future direction, providing a scalable solution for continuous crop monitoring and disease management. © 2024 IEEE.

关键词： Agricultural sustainability Autonomous systems Crop health Deep learning Machine learning Object detection Real-time monitoring robotics YOLOv5

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MPPT Algorithms for Wind Turbines: Review and Comparison 29

MPPT Algorithms for Wind Turbines: Review and Comparison

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29th International Workshop on Electric Drives: Advances in Power Electronics for Electric Drives, IWED 2022

作者： Aleksandr, Lukin Demidova, Galina Alassaf, Omar Lukichev, Dmitry Rassolkin, Anton Vaimann, Toomas ITMO University Faculty of Control System and Robotics Saint-Petersburg Russia Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia

ISBN: (纸本)9781665467865

Wind turbines play an important role in energy generation using renewable sources. The wind is very changeable, and such turbines require techniques for finding and tracking maximum power density. The presented work includes an overview of maximum power point tracking techniques applicable to small-size wind turbines based on the Magnus effect. An overview of existing algorithms is presented. Overviewed algorithms are assessed using a simulation in MATLAB with a model of the experimental Magnus effect wind turbine. © 2022 IEEE.

关键词： Wind power

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Low level position control for 4-DOF arm robot using fuzzy logic controller and 2-DOF PID controller

Low level position control for 4-DOF arm robot using fuzzy l...

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2021 International Mobile, Intelligent, and Ubiquitous Computing Conference, MIUCC 2021

作者： El-Khatib, Mohamed Fawzy Maged, Shady A. Faculty of Engineering Mechatronics and Robotics Engineering Department Badr City Cairo Egypt Ain Shams University Faculty of Engineering Mechanical and Mechatronics Engineering Department Cairo Egypt

ISBN: (纸本)9781665412438

The various types of applications for arm robots have made it one of the most important topics within the field. An important step to be considered is the application of a suitable control algorithm that takes into account the complex nonlinear dynamics. However, nonlinear control methods can still face difficulties due to the complexity of implementation. In this paper, four degrees of freedom (4-DOF) robot arm model is considered. Simple linear control methods are proposed to be used in the control of the angle of robotjoints. For this purpose, the fuzzy logic controller (FLC) and the two degree of freedom PID (2-DOF PID) controller are applied to control the joint angles of robot arm and in order to improve the response speed and reduce overshoot. The system simulation was performed using the MATLAB/Simulink software package. Simulation results show that the FLC has a faster response with a better rise time compared to the 2-DOF PID controller. © 2021 IEEE.

关键词： Fuzzy logic

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FaceEngine: A Tracking-Based Framework for Real-Time Face Recognition in Video Surveillance System

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SN Computer Science 2024年第5期5卷 609页

作者： Imran, Ahsan Ahmed, Riad Hasan, Md Mehedi Ahmed, M. Helal Uddin Azad, A.K.M. Alyami, Salem A. Department of Robotics and Mechatronics Engineering University of Dhaka Dhaka 1000 Bangladesh Department of Computer Science and Engineering BRAC University Dhaka 1212 Bangladesh Department of Management Information Systems University of Dhaka Dhaka 1000 Bangladesh Department of Mathematics and Statistics College of Science Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh 11432 Saudi Arabia

The escalating concern over worldwide security and criminal activities has led to the emergence and significance of closed-circuit television video surveillance systems as an essential tool for diverse security purposes. These systems are extensively implemented and serve a crucial function in the surveillance and upkeep of security. The predominant purpose of video surveillance systems is to gather data primarily for evidentiary purposes subsequent to the occurrence of a criminal incident. The demand for video surveillance systems capable of autonomously monitoring and promptly identifying criminals or intruders in real-time is steadily increasing. Nevertheless, the existing facial recognition methods pose difficulties in reliably identifying individuals who are in motion within a video frame. Moreover, conventional approaches necessitate a substantial quantity of photographs in order to achieve precise recognition following the acquisition of an individual’s facial pattern. In order to tackle these concerns, we developed the implementation of input optimisation algorithms alongside a novel framework for real-time face recognition in the context of video surveillance. The input optimization algorithms, integrated with adaptive thresholding techniques, effectively reduce the need for manual outlier removal by actively identifying outliers for each specific case. The application of this optimisation strategy has demonstrated a substantial enhancement in both the efficiency and precision of our system in comparison to alternative baseline methodologies. Through the use of a reduced set of input image, our system is capable of attaining a heightened degree of improvements. Specifically, employing tracking and temporal voting techniques enables our system to accomplish a real-time face recognition accuracy of 90.91%. The findings of this study suggest that our approach has the potential to be a valuable tool in various applications that necessitate rapid and precise fac

关键词： Computer vision Deep learning Face recognition Image processing Tracking Video surveillance

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Establish a Dynamic Detection System for Metal Bicycle Frame Defects Based on YOLO Object Detection

Establish a Dynamic Detection System for Metal Bicycle Frame...

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2022 IET International Conference on engineering Technologies and Applications, IET-ICETA 2022

作者： Kuan-Ying, Su Ming-Fei, Chen Po-Cheng, Tsai Cheng-Han, Tsai University of Education Department of Mechatronics Engineering National Changhua Changhua Taiwan Intelligent Robotics Technology Division Industrial Technology Research Institute Hsinchu Taiwan

ISBN: (数字)9781665491389

ISBN: (纸本)9781665491389

The purpose of this research is to develop a real-time bicycle frame's defect detection system using YOLO (You Only Look Once) and machine vision. Firstly, the defect locations are manually selected and a database is established. Next, a Darknet method is used to train the YOLO model. Its static detection accuracy rate is 92.6%, and then the static training model is combined with a robotic arm and an industrial camera to perform dynamic detection verification. The result shows that its detection rate reaches 87%. Finally, the above-mentioned defect detection technology is used with the detection machine to complete the development of the online defect detection system. © 2022 IEEE.

关键词： Object detection

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