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检索条件"任意字段=5th International Conference on Robotics and Automation Systems, Robotics 2010"

共 1354 条记录，以下是61-70 订阅

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Design and Operation Requirements for a Foot and Ankle Prosthesis 5

Design and Operation Requirements for a Foot and Ankle Prost...

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5th IEEE international conference on Communications, Information, Electronic and Energy systems, CIEES 2024

作者： Uzbekbayev, Arman Zhetenbayev, Nursultan Sultan, Aidos Ozhikenov, Kassymbek Iliev, Teodor Sergazin, Gani Satbayev University Institute of Automation and Information Technologies Department of Robotics and Technical Means of Automation Almaty Kazakhstan University of Ruse Dept. of Telecommunications Ruse Bulgaria

ISBN: (纸本)9798350352863

the loss of mobility due to amputation or severe damage to the ankle joint can significantly reduce a person's quality of life. the ankle joint and foot play a key role in maintaining balance, movement, and weight support, making the development of prostheses that restore these functions a critical task in biomedical engineering. this article examines the main design and operational requirements for ankle joint prostheses. It begins by analyzing the anatomical and biomechanical characteristics of the joint, followed by a discussion of conditions that necessitate prosthetic replacement, including traumatic injuries, vascular diseases, and degenerative joint changes. An overview of existing solutions, their limitations, and an analysis of current technological innovations are provided. the article justifies the need for the development of prostheses with optimized weight and mechanical parameters, capable of energy transmission and reproducing natural movements to enhance mobility and user independence. © 2024 IEEE.

关键词： Knee prostheses

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An Improved YOLOv7 Model for Obstacle Recognition in Autonomous Driving 5

An Improved YOLOv7 Model for Obstacle Recognition in Autonom...

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5th international conference on robotics, Intelligent Control and Artificial Intelligence, RICAI 2023

作者： Zhu, Zhaomin Liu, Qi Lin, Lu School of Electronic Information and Automation Guilin University of Aerospace Technology Guangxi Guilin541004 China School of Machinery and Shipbuilding Beibu Gulf University Guangxi Qinzhou535011 China School of Computer and Electronic Information Guangxi University Guangxi Nanning530004 China

ISBN: (纸本)9798350357950

this paper focuses on the problem of obstacle recognition in autonomous driving. On the basis of the original YOLOv7 algorithm, we add the simAM attention mechanism and replac the original CIOU loss function with the EIOU loss function. Meanwhile our model minimizes the difference in height and width between the predicted box and the real box and accelerats the model convergence speed. the results show that on the produced dataset, when using the improved YOLOv7 algorithm for object detection, its mAP reached 82.3%, an increase of 3% compared to the original YOLOv7 algorithm. © 2023 IEEE.

关键词： attention mechanism autonomous driving loss function obstacle recognition YOLOv7

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iWMS: A Warehouse Management System for a Goods-to-Person Warehouse automation 5th

iWMS: A Warehouse Management System for a Goods-to-Person Wa...

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5th 5th Olympus - international conference on Supply Chain

作者： Zotou, Dimitra Papadam, Stefanos Kargakos, Andreas Kostavelis, Ioannis Bliantidou, Maria Giakoumis, Dimitrios Ioannidis, Dimosthenis Tzovaras, Dimitrios Informat Technol Inst CERTH ITI Ctr Res & Technol Hellas 6 Km Charilaou Thermi Thessaloniki Greece Int Hellen Univ P Kanellopoulou 2 Katerini Greece TETTIX NMORENOS SINGLE MEMBER PC Zone COt 48A Thessaloniki 57400 Greece

ISBN: (纸本)9783031693434;9783031693441

Recently, there has been a surge in the development of advanced warehouse management systems that seamlessly incorporate robotized technologies. these robots have the capability to operate independently or collaborate with human staff to enhance the efficiency of items picking and storage. the paper at hand, introduces an intelligent Warehouse Management System, denoted as iWMS, designed for a goods-to-person warehouse environment. the system is configured to retrieve data of standard format compatible with commercial WMS through an application programming interface (API), while maintaining control over the robotic processes. this work aims to address the development of a software that will analyze incoming and outgoing orders and allocate the task of collecting and distributing bins with an Autonomous Mobile Robot (AMR). the proposed software performs a systematic analysis of incoming orders, linking them with the respective fiducial markers that contain detailed information about the precise location of the relevant bin within the warehouse. Subsequently, the system assigns the task of orders collection to one or more AMRs, taking into account their availability and current positions within the warehouse. this is achieved using an algorithm that maximizes efficiency by optimizing both execution time and travel distances. Additionally, the application consistently updates the stock in the database based on the products identified within the bins, ensuring accurate and real-time stock counting in the warehouse database. the ultimate goal of the iWMS is to provide an easy-to-use tool, allowing the seamless co-existence between the workers and the robotic platforms in a common workplace. this iWMS is part of a robotic warehouse solution currently undergoing testing in simulation.

关键词： Warehouse Management System Order picking robotics goods-to-person

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ECA-TabTransformer for the Growth Periods Classification and Disease Detection of Barley Grass through Multispectral imaging 5

ECA-TabTransformer for the Growth Periods Classification and...

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5th international conference on Artificial Intelligence and Electromechanical automation, AIEA 2024

作者： Jing, Zhifeng Cai, Hongxia Shanghai University Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai China

ISBN: (纸本)9798350366174

the industrialized production of barley grass requires precise control of each growth period and effective detection of the disease state. Compared with visual detection, multispectral detection could achieve precise classification of barley grass growth periods and diseases early detection benefits from physiological information of plants. this study aims to achieve the barley grass growth periods classification and disease detection through multispectral imaging taken by low-cost instrument. We proposed ECA-TabTransformer model which introduced Efficient Channel Attention block to enhance original TabTransformer and achieved a higher accuracy of 97.99% compared to algorithms such as CNN+DT, and the performance of multispectral detection also exceeded visual detection. Multispectral detection has better performance than visual detection for barley grass growth periods classification and disease detection. Proposed method has superiority performance, but there is no linear relationship between the performance and the dimensional changes of input. © 2024 IEEE.

关键词： Plant diseases

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FDNet: Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Fourier Series and DenseNet 5

FDNet: Remaining Useful Life Prediction for Lithium-Ion Batt...

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5th international conference on Machine Learning and Computer Application, ICMLCA 2024

作者： Chen, Siwen Zheng, Xiujuan Shanghai United Imaging Healthcare Co. Ltd. Shanghai China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Engineering Research Center for Metallurgical Automation and Measurement Technology Ministry of Education Wuhan China

ISBN: (纸本)9798331530334

To enhance the prediction accuracy of the remaining useful life (RUL) of lithium-ion batteries, this study proposes a novel RUL prediction model, termed FDNet, which integrates Discrete Fourier Series (DFS) and Densely Connected Convolutional Networks (DenseNet). In contrast to traditional methods that rely on one-dimensional (1D) numerical representations of time-series data, this model utilizes a two-dimensional (2D) visual representation for direct RUL prediction. First, the DFS is employed to convert 1D time-series signals into a 2D time-frequency domain, enabling the extraction of high-dimensional features from the original data. then, these 2D images are subsequently input into DenseNet, which learns the mapping between the image features and the RUL targets. Finally, the proposed model is validated using the NASA lithium-ion battery aging dataset, and the results indicate that FDNet achieves superior prediction accuracy and exhibits notable robustness. © 2024 IEEE.

关键词： Prediction models

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A Many-to-Many UAV Pursuit and Interception Strategy Based on PERMADDPG 5

A Many-to-Many UAV Pursuit and Interception Strategy Based o...

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5th international conference on robotics and Computer Vision, ICRCV 2023

作者： Zhang, Jiacheng Qi, Guoqing Xu, Lei Li, Yinya Sheng, Andong College of Automation Nanjing University of Science and Technology Jiangsu Nanjing China

ISBN: (纸本)9798350326369

To address the problem of multiple unmanned aerial vehicles (UAVs) cooperatively pursuing and intercepting non-cooperative UAVs in complex environments, we propose a prioritized experience replay multi-agent deep deterministic policy gradient (PERMADDPG) algorithm based on deep reinforcement learning. By designing algorithm models, state spaces, action spaces, reward functions, and incorporating prioritized experience replay techniques, the UAVs are trained to learn pursuit and interception strategies within a centralized training and distributed execution framework. the algorithm expands research on scenario where the "escaping UAVs have superior speed and maneuverability compared to the pursuing UAVs" and alleviates the large amplitude and slow convergence of the MADDPG algorithm when facing complex environments. Finally, through simulation experiments, the effectiveness of the proposed algorithm in solving the many-to-many UAV pursuit and interception problem is verified. By comparing it with the traditional MADDPG algorithm, the proposed algorithm demonstrates the ability of improving pursuit success rate and reducing response time effectively, while converging faster and minimizing oscillation amplitude as well. © 2023 IEEE.

关键词： Reinforcement learning

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Modeling and Control of an Omnidirectional Micro Aerial Vehicle Equipped with a Soft Robotic Arm 5

Modeling and Control of an Omnidirectional Micro Aerial Vehi...

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5th international conference on Soft robotics (RoboSoft)

作者： Szasz, Robert Allenspach, Mike Han, Minghao Tognon, Marco Katzschmann, Robert K. Swiss Fed Inst Technol Zurich ETH Zurich Soft Robot Lab Tannenstr 3 CH-8092 Zurich Switzerland Swiss Fed Inst Technol Zurich ETH Zurich Autonomous Syst Lab Leonhardstr 21 CH-8092 Zurich Switzerland

ISBN: (纸本)9781665408288

Flying manipulators are aerial drones with attached rigid-bodied robotic arms and belong to the latest and most actively developed research areas in robotics. the rigid nature of these arms often lack compliance, flexibility, and smoothness in movement. this work proposes to use a soft-bodied robotic arm attached to an omnidirectional micro aerial vehicle (OMAV) to leverage the compliant and flexible behavior of the arm, while remaining maneuverable and dynamic thanks to the omnidirectional drone as the floating base. the unification of the arm with the drone poses challenges in the modeling and control of such a combined platform;these challenges are addressed with this work. We propose a unified model for the flying manipulator based on three modeling principles: the Piecewise Constant Curvature (PCC) and Augmented Rigid Body Model (ARBM) hypotheses for modeling soft continuum robots and a floating-base approach borrowed from the traditional rigid-body robotics literature. To demonstrate the validity and usefulness of this parametrisation, a hierarchical model-based feedback controller is implemented. the controller is verified and evaluated in simulation on various dynamical tasks, where the nullspace motions, disturbance recovery, and trajectory tracking capabilities of the platform are examined and validated. the soft flying manipulator platform could open new application fields in aerial construction, goods delivery, human assistance, maintenance, and warehouse automation.

关键词： automation Trajectory tracking conferences Soft robotics Maintenance engineering Vehicle dynamics Task analysis

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A Fuzzy Fusion Approach for the Prediction of Position and Orientation in Robot-Assisted Cardiovascular Surgery 5

A Fuzzy Fusion Approach for the Prediction of Position and O...

引用

5th international conference on robotics and Computer Vision, ICRCV 2023

作者： Hu, Zhi Sun, Liyan Song, Aiguo School of Instrument Science and Engineering Southeast University Nanjing China Laboratory of Intelligent Control and Robotics Shanghai University of Engineering Science Shanghai China

ISBN: (纸本)9798350326369

To assist doctors in cardiovascular intervention, the use of robots in surgery can effectively separate interventionalists from X-ray radiation, prevent the spread of respiratory diseases, perform remote operations to alleviate the regional imbalance of medical resources and address some procedural challenges. However, a lack of force feedback in human computer interaction of current surgical robots affects surgical efficiency and safety. In cardiovascular surgery, the catheter bends and twists as it is the dynamic multipoint line contact with the vessel. It is difficult to accurately model and register it. In addition, time delay affects system transparency. this paper proposes a multi-information fuzzy fusion approach that is based on medical experience in order to predict position and orientation online. More specifically, Fitts law is developed with a two-motion collaborative to estimate the surgical movement time. Experimental results reveal that the proposed method can result in high system transparency in robot-assisted cardiovascular surgery. It could further improve accuracy and security in surgical procedures. © 2023 IEEE.

关键词： Forecasting

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Integration of Computer Vision and 4DOF SCARA Robot Arm for Tomato Sorting 15

Integration of Computer Vision and 4DOF SCARA Robot Arm for ...

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15th international conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Tanvashi, Shilpa Kolanur, C.B. Aakash, P. Shri Muchchandi, Tejas Dhongadi, Hrithik Hirennavar, Akarsh Aralgundagi, Sanket Shreyakar, Vaibhav Kle Technological University Department of Automation and Robotics Karnataka Hubballi India

ISBN: (纸本)9798350370249

Automating fruit recognition and classification is an important computer vision application that can improve efficiency and consistency in the fruit industry. Manual sorting methods based on visual inspection are tedious, time-consuming, and prone to inconsistencies. this work presents the design and deployment of an automated tomato sorting system that integrates computer vision and robotics. the system classifies tomatoes into three maturity stages (Green, Half-ripe, Ripe) based on color using the YOLOv5 deep learning algorithm. A SCARA robot is used for picking and placing the sorted tomatoes into respective bins. the system demonstrates a fast inference time of 22.31 milliseconds for tomato detection and can sort three tomatoes of different maturity classes in approximately 1.2 seconds on average. this consistent and efficient sorting is based on objective color criteria rather than manual visual inspection. the system can help improve product quality, reduce labor costs, and increase throughput in tomato processing facilities. the approach can be extended to sorting other fruits and vegetables based on color attributes. © 2024 IEEE.

关键词： 4 DOF SCARA Robot arm automation Deep Learning Integrated System Tomato sorting

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Multibody Dynamics Software-Based Simulation of a Game for a robotics Competition 6th

Multibody Dynamics Software-Based Simulation of a Game for a...

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6th Joint international conference on Multibody System Dynamics and 10th Asian conference on Multibody systems, IMSD-ACMD 2020

作者： Kumar, Sandeep Saha, Subir Kumar Singh, Satinder Paul Department of Mechanical Engineering Indian Institute of Technology Delhi Hauz-Khas New Delhi110016 India

ISBN: (纸本)9789819775248

Due to advancements in the area of robotics and automation, there is a need of skills for engineers. they are obtained through various workshops, seminars, conferences and participating in various competitions. Apart from the practical work skills, there is a requirement of proper software-based skills to get an idea of the performance of final tasks on the field. this paper presents the use of such a multi-body dynamics software for simulating the game of a robotics competition to check the effectiveness and completeness of the intended tasks. In this work, MSC ADAMS, a multi-body dynamics software, has been used for simulations. the tasks that have been performed are the tasks for ABU Robocon 2022. the theme was "Lagori" that is based on Indian game called as "Pithu". Two tasks of the game were considered here to demonstrate the use of a software. One is Lagori breaking and the other is hitting the Ball on Head. the simulation was performed for several speeds and angles at which the ball was thrown. the effectiveness of the tasks was checked with the real situations when the games were actually played. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： robotics

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