检索结果-内蒙古大学图书馆

IEEE International Conference on robotics and Automation (ICRA)

作者： Ana Elvira H. Martin Ashok M. Sundaram Werner Friedl Virginia Ruiz Garate Máximo A. Roa DLR the Institute of Robotics and Mechatronics German Aerospace Center Wessling Germany Mondragon Unibertsitatea Faculty of Engineering Bilbao Spain Bristol Robotics Laboratory University of the West of England Bristol United Kingdom

The integration of variable stiffness actuators (VSA) in robotic systems endows them with intrinsic flexibility and therefore robustness to unknown disturbances. However, this characteristic presents a challenge: choosing the best intrinsic stiffness setting guaranteeing the required force ap-plication capability while keeping the system as adaptable to uncertainties as possible. This paper proposes a method to set the optimal stiffness for a multi-finger VSA hand to perform a desired manipulation task. The task is generically represented as a force (with unknown magnitude) applied along a reference direction. According to the force application's direction and the hand's kinematic state, the fingers assume a certain role to split the collective force application. We employ the endpoint stiffness ellipsoid to analyze the required finger stiffness to fulfill the task. We evaluate the optimized stiffness settings in a door opening application with an iterative adaption of the stiffness behavior to handle the unknown force requirement. The results show a successful collective behavior of the fingers, where the stiffness setting considers a task-oriented force-adaptability trade-off and effective use of independent VSA fingers.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Analysis and Implementation of Motion Planning Algorithms for Real-Time Navigation of Aerial Robots in Dynamic Environments

Analysis and Implementation of Motion Planning Algorithms fo...

引用

Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Yunes Alqudsi Aerospace Engineering Department Faculty of Aeronautics and Astronautics Kocaeli University Kocaeli Türkey Mechanical Engineering Department Faculty of Engineering Kocaeli University Kocaeli Türkey Department of Mechatronics and Robotics Engineering Taiz University Taiz Yemen

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

Efficient path planning is critical for the safe and effective navigation of Autonomous Aerial Robots (AARs) in complex 3D environments. This paper presents a comprehensive exploration of path planning techniques designed for AAR operations, with a focus on the application of the D* algorithm and its variants. Beginning with an overview of traditional methods such as Dijkstra's and A* algorithms, this work delves into the advanced capabilities of the D* algorithm family, including dynamic replanning and adaptive optimization for changing environmental conditions. A key contribution of this work is the implementation of these algorithms in a manner that significantly accelerates the search phase, particularly when dealing with multiple robots and goals, enhancing computational efficiency. Through detailed analysis and simulation, this study investigates the practical implementation of these algorithms in 3D space, addressing challenges such as obstacle avoidance, computational efficiency, dynamic feasibility, and real-time adaptability. Our simulated case results demonstrate the efficacy and versatility of these techniques in various AAR missions, providing valuable insights for researchers and practitioners in the field of autonomous aerial navigation. This work not only highlights the strengths and limitations of existing methods but also offers novel solutions to improve the performance of path planning algorithms in dynamic environments.

关键词： Three-dimensional displays Navigation Heuristic algorithms Dynamics Autonomous aerial vehicles Path planning Real-time systems

来源：评论

学校读者我要写书评

暂无评论

IPMC as EMG Sensor to Diagnose Human Arm Activity 1

引用

International Conference on Industrial Instrumentation and Control,ICI2C 2021

作者： Das, Suman Ghosh, Somobrata Guin, Rohan Das, Abhirup Das, Bijoy Saha, Sampurna Bhattacharya, Srijan Bepari, Bikash Bhaumik, Subhasis Department of Electrical Engineering MCKV Institute of Engineering Howrah India Department of Applied Electronics and Instrumentation Engineering RCC Institute of Information Technology Kolkata India Department of Production Engineering Haldia Institute of Technology Haldia India School of Mechatronics and Robotics Indian Institute of Engineering Science and Technology Shibpur Howrah India

ISBN: (数字)9789811670114

ISBN: (纸本)9789811670107

The Ionic Polymer-Metal Composite (IPMC) is a sandwiched polymer with metal electrode. It is used as sensors and actuators in different bio-engineering applications, for this property of Electro Active Polymer (EAP) researcher across the globe using IPMCs in robotics, sensors, actuators and biomedical application, in this article, a comparative study between standard Electromyography (EMG) electrode and IPMC electrode is revealed for extracting EMG signal from human forearm. The stretching/bending of IPMC which results an output response are observed, the difference in response yields, while grasping different object can be mapped for diagnose the activity of different posture of gripping. In this experimental report, it is also revealed that using IPMC sensors/electrodes are capable of identifying the activity of a human arm. Thus, it is reported in this article that IPMC can be used for sensing EMG signals, and it can be used for identification of human gripping activity. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electrodes

来源：评论

学校读者我要写书评

暂无评论

CNN-based Methods for Object Recognition with High-Resolution Tactile Sensors

arXiv

引用

arXiv 2023年

作者： Gandarias, Juan M. García-Cerezo, Alfonso J. Gómez-De-Gabriel, Jesús M. Robotics and Mechatronics Group Systems Engineering and Automation Department University of Málaga Escuela de Ingenierías Industriales Málaga Spain

Novel high-resolution pressure-sensor arrays allow treating pressure readings as standard images. Computer vision algorithms and methods such as Convolutional Neural Networks (CNN) can be used to identify contact objects. In this paper, a high-resolution tactile sensor has been attached to a robotic end-effector to identify contacted objects. Two CNN-based approaches have been employed to classify pressure images. These methods include a transfer learning approach using a pre-trained CNN on an RGB-images dataset and a custom-made CNN (TactNet) trained from scratch with tactile information. The transfer learning approach can be carried out by retraining the classification layers of the network or replacing these layers with an SVM. Overall, 11 configurations based on these methods have been tested: 8 transfer learning-based, and 3 TactNet-based. Moreover, a study of the performance of the methods and a comparative discussion with the current state-of-the-art on tactile object recognition is presented. Copyright © 2023, The Authors. All rights reserved.

关键词： Object recognition

来源：评论

学校读者我要写书评

暂无评论

Optimal-Tolling Using Reinforcement Learning

Optimal-Tolling Using Reinforcement Learning

引用

IEEE Southeastcon

作者： Sumit Chakravarty M. Hassan Tanveer Razvan C. Voicu Madhushri Banerjee Department of Electrical Engineering Kennesaw State University Marietta Georgia USA Department of Robotics & Mechatronics Engineering Kennesaw State University Marietta Georgia USA Department of IT Georgia Gwinett College Atlanta USA

This article explores traffic management's intricacies through the lens of optimal tolling, employing advanced reinforcement learning techniques. The research delves into the dual perspectives of drivers and traffic operators, addressing the critical decision-making processes involved in lane choice and toll pricing. By modeling traffic flows based on historical data from the Georgia Department of Transportation, the study employs neural networks to simulate traffic dynamics and density-speed relationships accurately. Deep Q-Network (DQN) agents are central to the investigation, representing drivers and traffic controllers rigorously trained within a simulated environment to optimize lane choices and toll prices. This innovative approach not only maximizes revenue for traffic controllers but also ensures efficient traffic flow, striking a balance between speed and cost for drivers. The study's findings demonstrate a significant advancement in traffic management strategies, offering a scalable and data-driven solution to urban congestion and toll lane utilization challenges. This work presents a novel framework that has the potential to revolutionize traffic control systems and provide insights into the practical applications of reinforcement learning in complex real-world scenarios.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Swing-Up of a Weakly Actuated Double Pendulum via Nonlinear Normal Modes

arXiv

引用

arXiv 2024年

作者： Sachtler, Arne Calzolari, Davide Raff, Maximilian Schmidt, Annika Wotte, Yannik P. Della Santina, Cosimo Remy, C. David Albu-Schäffer, Alin Institute of Robotics and Mechatronics Münchener Straße 20 Oberpfaffenhofen82234 Germany Department of Computer Engineering Boltzmannstraße 3 Garching85748 Germany University of Stuttgart Institute for Nonlinear Mechanics Pfaffenwaldring 9 Stuttgart70569 Germany University of Twente Robotics & Mechatronics Group Drienerlolaan 5 Enschede7522 NB Netherlands Department of Cognitive Robotics Mekelweg 2 Delft2628 CD Netherlands

We identify the nonlinear normal modes spawning from the stable equilibrium of a double pendulum under gravity, and we establish their connection to homoclinic orbits through the unstable upright position as energy increases. This result is exploited to devise an efficient swing-up strategy for a double pendulum with weak, saturating actuators. Our approach involves stabilizing the system onto periodic orbits associated with the nonlinear modes while gradually injecting energy. Since these modes are autonomous system evolutions, the required control effort for stabilization is minimal. Even with actuator limitations of less than 1% of the maximum gravitational torque, the proposed method accomplishes the swing-up of the double pendulum by allowing sufficient time. Copyright © 2024, The Authors. All rights reserved.

关键词： Dynamical systems

来源：评论

学校读者我要写书评

暂无评论

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...

引用

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

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of Model Predictive Control (MPC) Based Pressure Regulation System for a Precision Agricultural Sprayer

Design and Implementation of Model Predictive Control (MPC) ...

引用

International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Adrees Khan Fazal Nasir Muhammad Tufail Muhammad Haris Muhammad Tahir Khan Zhang Dong Department of Mechatronics Engineering University of Engineering and Technology Peshawar Pakistan Advanced Robotics and Automation Lab National Center of Robotics and Automation Peshawar Pakistan Institute of Automation Qilu University of Technology (Shandong Academy of Sciences) Jinan China

Model Predictive Control (MPC) is a control scheme that involves predicting the future behavior of a system and optimizing control actions to accomplish the desired objective. In this study, we develop an intelligent control algorithm, based on MPC to regulate the target pressure in variable-rate agriculture sprayer robots. Modeling and simulation steps of the spraying system are developed using MATLAB/Simulink environment, before passing to the description of the MPC algorithm. Real-time implementation of the MPC algorithm was conducted on an Arduino Mega 2560 controller board by using Simulink Support Package for Arduino Hardware in MATLAB/Simulink to experimentally validate the preliminary results of simulations. The work evaluates MPC to regulate the pressure in the system and compares the results with a traditional PID control system. Moreover, MPC is a novel method for nonlinear system control that achieves zero steady-state error, low transient response, and reduces peak overshoot compared to the results obtained with a PID controller, thereby reducing the waste of chemicals, and minimizing the toxicology and environmental risk.

关键词： Transient response Toxicology Software packages Spraying Agriculture Regulation Real-time systems

来源：评论

学校读者我要写书评

暂无评论

State Estimation of Continuum Robots: A Nonlinear Constrained Moving Horizon Approach

arXiv

引用

arXiv 2023年

作者： Abdelaziz, Hend Nada, Ayman Ishii, Hiroyuki El-Hussieny, Haitham Department of Mechatronics and Robotics Engineering Egypt-Japan University of Science and Technology Alexandria Egypt Faculty of Science and Engineering Waseda University Tokyo169-8050 Japan

Continuum robots, made from flexible materials with continuous backbones, have several advantages over traditional rigid robots. Some of them are the ability to navigate through narrow or confined spaces, adapt to irregular or changing environments, and perform tasks in proximity to humans. However, one of the challenges in using continuum robots is the difficulty in accurately estimating their state, such as their tip position and curvature. This is due to the complexity of their kinematics and the inherent uncertainty in their measurement and control. This paper proposes a moving horizon estimation (MHE) approach for estimating the robot's state, including its tip position and shape parameters. Our approach involves minimizing the error between measurement samples from an IMU attached to the robot's tip and the estimated state along the estimation horizon using an inline optimization problem. We demonstrate the effectiveness of our approach through simulation and experimental results. Our approach can potentially improve the accuracy and robustness of state estimation and control for continuum robots. It can be applied to various applications such as surgery, manufacturing, and inspection. © 2023, CC BY.

关键词： State estimation

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：