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International Conference on Cybernetics, robotics and Control (CRC)

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

ISBN: (数字)9798331517489

ISBN: (纸本)9798331517496

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.

关键词： YOLO Plant diseases Visualization Accuracy Autonomous systems Crops Food security Real-time systems Robots Monitoring

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Dynamic model of a tendon-actuated snake robot using the Newton-Euler formulation

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IFAC-PapersOnLine 2023年第2期56卷 11639-11644页

作者： Gianluca D'Antuono Kristin Y. Pettersen Luca R. Buonocore Jan Tommy Gravdahl Mario Di Castro Department of Engineering Cybernetics Norwegian University of Science and Technology (NTNU) Trondheim Norway Mechatronics Robotics & Operation Section European Organization for Nuclear Research (CERN) Meyrin Switzerland

Dynamic models are necessary when dealing with robotic applications where requirements of dexterity, manipulability, payload and compliance have to be satisfied at the same time. This work considers a particular design of tendon-actuated snake-like robots in which links are not coupled through mechanical joints but are free to roll between each other under the effect of cable tension forces. The state of the art in modeling these tendon-actuated rolling-joints systems is limited to kinematic and quasi-static models. In order to simultaneously guarantee modeling accuracy and suitability for model-based control, the Newton-Euler (NE) formulation has been adopted, by taking into account the forces and moments generated by cable tensions, links interactions, inertias, and friction between the rolling surfaces.

关键词： Modeling dynamic model tendon-actuated robots snake robots rolling-joints

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Potholes Detection Using Yolo Algorithms and Their Integration Into Gazebo Simulation

Potholes Detection Using Yolo Algorithms and Their Integrati...

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International Conference on Cybernetics, robotics and Control (CRC)

作者： M. Hassan Tanveer Zainab Fatima Tanazzah Rehman Moaaz Siddique Arbaz Shah Razvan Cristian Voicu M. Farrukh Shahid Department of Robotics and Mechatronics Engineering Kennesaw State University Marietta USA Department of Software Engineering NED University of Engineering and Technology Karachi Pakistan Department of AI and Data Science FAST University of computing and Emerging Science Karachi Pakistan

ISBN: (数字)9798331517489

ISBN: (纸本)9798331517496

Road cavities, often called potholes, pose a major problem for our transportation infrastructure, causing accidents, costly repairs, and traffic jamming. This study shows using a computer vision technique called You Only Look Once (YOLO) to find potholes on roads. YOLO is proficient and efficient for realtime object detection. The researchers want to see which version of YOLO is more effective in object analysis in pictures and videos. We'll be comparing YOLOv5, YOLOv7, and YOLOv8, thereby also setting up the system in Gazebo simulated environment. By carefully analyzing the results, we aim to understand the advantages and disadvantages of each YOLO version. This will help us see the most useful ones for finding potholes when managing and maintaining roads.

关键词： YOLO Location awareness Roads Transportation Maintenance engineering Prediction algorithms Classification algorithms Object recognition Jamming Videos

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On the Existence of Static Equilibria of a Cable-Suspended Load with Non-stopping Flying Carriers

On the Existence of Static Equilibria of a Cable-Suspended L...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Chiara Gabellieri Antonio Franchi Robotics and Mechatronics Department Electrical Engineering Mathematics and Computer Science (EEMCS) Faculty University of Twente Enschede AE The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

This work answers positively the question whether non-stop flights are possible for maintaining constant the pose of cable-suspended objects. Such a counterintuitive answer paves the way for a paradigm shift where energetically efficient fixed-wing flying carriers can replace the inefficient multirotor carriers that have been used so far in precise cooperative cable-suspended aerial manipulation. First, we show that one or two flying carriers alone cannot perform non-stop flights while maintaining a constant pose of the suspended object. Instead, we prove that three flying carriers can achieve this task provided that the orientation of the load at the equilibrium is such that the components of the cable forces that balance the external force (typically gravity) do not belong to the plane of the cable anchoring points on the load. Numerical tests are presented in support of the analytical results.

关键词： Task analysis Aircraft Gravity

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Deep Learning-based Prior toward Normalized Metal Artifact Reduction in Computed Tomography 7

Deep Learning-based Prior toward Normalized Metal Artifact R...

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7th International Conference on Image Formation in X-Ray Computed Tomography

作者： Nam, Jeonghyeon Ye, Dong Hye Lee, Okkyun Department of Robotics and Mechatronics Engineering DGIST 333 Techno jungang-daero Hyeonpung-eup Dalseong-gun Daegu Korea Republic of Department of Electrical and Computer Engineering Marquette University 1250 W. Wisconsin Ave MilwaukeeWI United States

ISBN: (纸本)9781510656697

X-ray computed tomography (CT) often suffers from scatter and beam-hardening artifacts in the presence of metal. These metal artifacts are problematic as severe distortions in the CT images deteriorate the diagnostic quality in clinical applications such as orthopedic arthroplasty. The normalized metal artifact reduction (NMAR) method effectively reduces the artifacts by normalizing the sinogram with the metal traces through the forward projection of the prior image. Because the prior image is the thresholded CT image with the values of the air and soft tissues replaced, the image is noticeably different from the ideal CT thereby making normalized sinogram not completely flat. In this paper, we propose the novel NMAR method with the deep learning-enhanced prior image which is denoised by learning the relationship between NMAR and clean image without metal artifact. The denoised prior image is then forward projected to correct the sinogram with the metal trace. The experimental results on simulated rat phantom dataset demonstrate that our proposed deep prior NMAR achieves higher structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR) than the original NMAR. © 2022 SPIE.

关键词： Signal to noise ratio

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A Comparative Study on the Morphology and In Vitro Behaviour of Biopolymers/Ceramic-based Scaffolds Obtained by Drying and Lyophilization Techniques 10

A Comparative Study on the Morphology and In Vitro Behaviour...

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10th E-Health and Bioengineering Conference, EHB 2022

作者： Cojocaru, Florina Daniela Balan, Vera Istrate, Bogdan Butnaru, Maria Verestiuc, Liliana Department of Biomedical Sciences Faculty of Medical Bioengineering Grigore T. Popa University of Medicine Pharmacy of Iasi Iasi Romania Mechanical Engineering Mechatronics and Robotics Department Mechanical Engineering Faculty Gheorghe Asachi Technical University of Iasi Iasi Romania

ISBN: (纸本)9781665485579

Tissue engineering, with its crucial components (cells, scaffold and signaling molecules), is still a challenging field, and choosing the suitable manufacturing technique for bone scaffolds is a crucial issue, as such materials should possess particular characteristics: biocompatibility, biodegradability, specific mechanical features and distinguishing porous structure. Lyophilization and thermal drying are frequently used by many researchers, being affordable, efficient in terms of time and easy to perform. In this study, scaffolds based on biopolymers, calcium phosphate and magnetite nanoparticles were prepared using separately, these two processing techniques, and evaluated, in terms of physico-chemical features and in vitro behaviour. © 2022 IEEE.

关键词： Biocompatibility

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Obstacle-Aware Navigation of Soft Growing Robots via Deep Reinforcement Learning

arXiv

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arXiv 2024年

作者： El-Hussieny, Haitham Hameed, Ibrahim Department of Mechatronics and Robotics Engineering Egypt-Japan University of Science and Technology Alexandria Egypt Department of ICT and Natural Sciences Norwegian University of Science and Technology Trondheim7034 Norway

Soft growing robots, are a type of robots that are designed to move and adapt to their environment in a similar way to how plants grow and move with potential applications where they could be used to navigate through tight spaces, dangerous terrain, and hard-to-reach areas. This research explores the application of deep reinforcement Q-learning algorithm for facilitating the navigation of the soft growing robots in cluttered environments. The proposed algorithm utilizes the flexibility of the soft robot to adapt and incorporate the interaction between the robot and the environment into the decision-making process. Results from simulations show that the proposed algorithm improves the soft robot’s ability to navigate effectively and efficiently in confined spaces. This study presents a promising approach to addressing the challenges faced by growing robots in particular and soft robots general in planning obstacle-aware paths in real-world scenarios. © 2024, CC BY.

关键词： Navigation

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A Study of Stabilization and Swing-up Linear Control for a Single Link Rotary Pendulum

A Study of Stabilization and Swing-up Linear Control for a S...

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Theoretical and Applied Computer Science and engineering (ICTASCE), International Conference on

作者： Zied Ben Hazem Zafer Bingül Department of Mechatronics Engineering Istanbul Gedik University Istanbul Turkey Department of Mechatronics Engineering Automation and Robotics Laboratory Kocaeli University Kocaeli Turkey

Single link rotary inverted pendulum (SLRIP) is a highly nonlinear control system that has complex dynamic behavior. This type of system requires a high-performance controller for its control. The rotary pendulum system is present as a control problem challenge because the system often moves to an uncontrolled state. The problem consists to balance one or more attached pendulums vertically in the upward position on a rotational arm which has a single degree of freedom and turns horizontally on only one axis. The aim is to find a control strategy that provides accurate performance with respect to the angles of the pendulums and the horizontal arm. This paper proposes a study of a PID, Linear Quadratic Regulator (LQR) stabilization control, and swing-up linear control based on LQR. The gains of the PID and LQR controllers are optimized by using the particle swarm optimization (PSO) algorithm to provide more robust controllers. A dynamic mechanical simulation study was conducted on MATLAB/SimMechanics obtained by the designed 3D-CAD models of the SLRIP. According to experimental results, the systems demonstrate the efficiency and robustness of all controllers.

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Design and Development of an Anthropomorphic Robotic Hand Using TPU Material 2

Design and Development of an Anthropomorphic Robotic Hand Us...

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2nd International Conference on Innovation in engineering and Technology, ICIET 2019

作者： Nihal, Ragib Amin Broti, Nawara Mahmood Deowan, Shamim Ahmed Rahman, Sejuti University of Dhaka Department of Robotics and Mechatronics Engineering Dhaka Bangladesh University of Dhaka Department of Robotics and Mechatronics Engineering Dhaka Bangladesh University of Dhaka Department of Robotics and Mechatronics Engineering Dhaka Bangladesh University of Dhaka Department of Robotics and Mechatronics Engineering Dhaka Bangladesh

ISBN: (纸本)9781728163093

The paper presented here approaches to solve the complexity of an anthropomorphic robotic hand. robotics is now the most advancing field and there has always been an intention of mimicking human-like actuation and behavior. An anthropomorphic hand is one of the approaches to imitate human-like operations. In this paper, the idea of developing an anthropomorphic hand with 15 degrees of freedom and 5 actuators has been elaborated as well as the mechanical design, control system, composition, and peculiarities of the robotic hand have been discussed. The hand has an anthropomorphic appearance and also can perform human-like functionalities, for example, gripping and hand gestures representation. The results reveal that the hand is designed as one part and does not need any kind of assembly and it exhibits an excellent weight lifting capacity, since it is made of flexible thermoplastic polyurethane (TPU) material, and its elasticity also ensures that the hand is safe for interacting with humans as well. This hand may be used in a humanoid robot as well as a prosthetic hand. The limited number of actuators makes the control simpler and the hand lighter. © 2019 IEEE.

关键词： 3D printers

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Automated COVID-19 Detection from Chest X-Ray Images: A High-Resolution Network (HRNet) Approach

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SN Computer Science 2021年第4期2卷 294页

作者： Ahmed, Sifat Hossain, Tonmoy Hoque, Oishee Bintey Sarker, Sujan Rahman, Sejuti Shah, Faisal Muhammad Hiperdyne Corporation Tokyo Japan Department of Computer Science and Engineering Ahsanullah University of Science and Technology Dhaka Bangladesh Department of Robotics and Mechatronics Engineering University of Dhaka Dhaka Bangladesh

The pandemic, originated by novel coronavirus 2019 (COVID-19), continuing its devastating effect on the health, well-being, and economy of the global population. A critical step to restrain this pandemic is the early detection of COVID-19 in the human body to constraint the exposure and control the spread of the virus. Chest X-Rays are one of the non-invasive tools to detect this disease as the manual PCR diagnosis process is quite tedious and time-consuming. Our intensive background studies show that, the works till now are not efficient to produce an unbiased detection result. In this work, we proposed an automated COVID-19 classification method, utilizing available COVID and non-COVID X-Ray datasets, along with High-Resolution Network (HRNet) for feature extraction embedding with the UNet for segmentation purposes. To evaluate the proposed method, several baseline experiments have been performed employing numerous deep learning architectures. With extensive experiment, we got a significant result of 99.26% accuracy, 98.53% sensitivity, and 98.82% specificity with HRNet which surpasses the performances of the existing models. Finally, we conclude that our proposed methodology ensures unbiased high accuracy, which increases the probability of incorporating X-Ray images into the diagnosis of the disease. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： COVID-19 Healthcare HRNet Pandemic UNet X-Ray

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