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检索条件"任意字段=International Conference on Pattern Analysis and Intelligence Robotics"

共 15923 条记录，以下是441-450 订阅

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Control Design Based on EKF via Pigeon-Inspired Optimization with pattern Search for UAV Close Formation Flight

Control Design Based on EKF via Pigeon-Inspired Optimization...

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2023 IEEE international conference on robotics and Biomimetics, ROBIO 2023

作者： Yuan, Guangsong Duan, Haibin Luo, Delin State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical Engineering Beijing100083 China Xiamen University School of Aerospace Engineering Xiamen361102 China

ISBN: (纸本)9798350325706

An unmanned aerial vehicle (UAV) close formation controller based on extended kalman filter (EKF) has been designed in this paper. The Newton-Raphson iterative method is designed for extremum location estimation, namely extremum seeking control (ESC). To facilitate extremum position estimation, the performance function is approximated using first and second-order Taylor expansions. The EKF is still utilized to estimate the gradient and Hessian matrix of the parameterized performance function. Compared with traditional estimation strategy, this allows a faster convergence and smooth command reference for close formation controller. The pigeon-inspired optimization (PIO) with pattern search (PS) is proposed to optimize these free parameters of the EKF. The simulation results show that the proposed PIO with pattern search has strong optimization performance. The EKF optimized by the algorithm enables the controller to converge well to the optimal relative position. © 2023 IEEE.

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Leveraging Artificial intelligence in Education: Analyzing Academic Engagement, Application, and Challenges 4th

Leveraging Artificial Intelligence in Education: Analyzing A...

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4th international conference on Intelligent Systems and pattern Recognition-ISPR

作者： Al-Hadrami, Ahmed Alyahmadi, Hamed Al-Khatib, Khalil Muhammad Boukhalkhal, Ali Al Rashidi, Said Al Habsi, Khoula Salim ASharqiyah Univ Ibra Oman AOU Oman Seeb Oman Sanaa Univ Sanaa Yemen Al Razi Univ Sanaa Yemen Univ Amar Telidji Laghouat Laghouat 03000 Algeria Islam Educ Seeb Oman

ISBN: (纸本)9783031821493;9783031821509

The objective of the study is to examine the referencing behavior of a group of academic university members in relation to the utilization of artificial intelligence in the educational process, as well as the difficulties associated with its implementation. The study employed a descriptive methodology, using interviews as a means to analyze the reference activity of a selected group of Arab university academics. The investigation produced the subsequent findings: The study sample estimated that there are numerous and different uses of artificial intelligence in the educational process at universities. The arithmetic means of these applications, as determined by the study of reference activity, fell within the range of 5.61 to 6.01, indicating relatively high levels for both. The scale levels for the use of reference activity were as follows: observance (mean = 5.72), specification (mean = 5.43), clarity (mean = 6.16), and conception (mean = 5.94).The interviews revealed a variety of difficulties and barriers (including human, technical, financial, cognitive, and social factors) encountered by university instructors when incorporating artificial intelligence into the teaching process. These challenges varied from an arithmetic mean of 5.6 to 6.17, indicating moderately high and moderately high levels, respectively. The research suggests the incorporation of artificial intelligence application technology into the higher education teaching process.

关键词： Reference Activity analysis Artificial intelligence Educational Process

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Automated Vision-based Bolt Sorting by Manipulator for Industrial Applications 20

Automated Vision-based Bolt Sorting by Manipulator for Indus...

引用

IEEE 20th international conference on Automation Science and Engineering (CASE)

作者： Prakash, Surya S. K. Shukla, Amit Pandya, Naisarg Jha, Shirish Shekhar IIT Mandi Sch Mech & Mat Engn Suran Himachal Prades India IIT Mandi Chairperson Ctr Artificial Intelligence & Robot Suran Himachal Prades India IIT Mandi Ctr Artificial Intelligence & Robot Suran Himachal Prades India

ISBN: (纸本)9798350358513;9798350358520

In industrial automation, nuts and bolts are key components that facilitate assembly processes. Estimating their sizes and sorting them accordingly would be a significant advancement for automation in industrial settings. This paper introduces a distinct approach by amalgamating deep learning based segmentation with classical vision for automated bolt sorting in unstructured industrial environment. We evaluated advanced deep learning algorithms PPLiteSeg(STDC I&II), OCRNet, and DeepLabV3+ on our custom bolt dataset. DeepLabV3+ achieved the best performance over the other models in accurate bolt segmentation, with a remarkable mean Intersection over Union (mIoU) of 0.95. Custom bolt dataset is prepared considering various environmental conditions and included both new and aged bolts. We present a comparative analysis of the segmentation results for each learning model mentioned. To estimate bolt size, we integrated the segmented binary image with depth information from Intel RealSense D415 camera. Through a series of experiments, we successfully localized bolts (both position and orientation) relative to robot's base and sorted them according to their size by using Kinova Gen3 Lite robotic arm. The proposed approach has the potential to significantly advance the automation for assembly lines and warehouse management within industries, particularly when dealing with small objects.

关键词： Robotic arms

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A Passivity-based Approach on Relocating High-Frequency Robot Controller to the Edge Cloud

A Passivity-based Approach on Relocating High-Frequency Robo...

引用

IEEE international conference on robotics and Automation (ICRA)

作者： Chen, Xiao Sadeghian, Harnid Chen, Lingyun Troebinger, Mario Swirkir, Abadalla Naceri, Abdeldjallil Haddadin, Sami Tech Univ Munich Munich Inst Robot & Machine Intelligence Munich Germany Univ Isfahan Fac Engn Esfahan *** Iran Omar Al Mukhtar Univ OMU Ctr Tactile Internet Human Loop CeTI Albaida Libya Omar Al Mukhtar Univ OMU Dept Elect & Elect Engn Albaida Libya

ISBN: (纸本)9798350323658

As robots become more and more intelligent, the complexity of the algorithms behind them is increasing. Since these algorithms require high computation power from the onboard robot controller, the weight of the robot and energy consumption increases. A promising solution to tackle this issue is to relocate the expensive computation to the cloud. In this pioneering work, the possibility of relocating a state-of-the-art nonlinear control is investigated. To this end, the Unified Force-Impedance Controller (UFIC) is relocated to a remote location and high frequency feedback loop is established by including the remote controller in the loop. Passivity analysis is used to ensure the stability of the whole system, comprising the robot in interaction with the environment, the communication channel, as well as the remote controller. The instability associated with the communication channel is resolved by Time Domain Passivity Approach (TDPA). The performance of the proposed framework is experimentally evaluated on a robot arm in interaction with the environment. The results illustrate the stability of the system to a time-varying delay of up to 50 +/- 10ms.

关键词： Energy utilization

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analysis of the application of AI Intelligent System in Land Use Control 24

Analysis of the application of AI Intelligent System in Land...

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3rd international Symposium on robotics, Artificial intelligence and Information Engineering, RAIIE 2024

作者： Yang, Xianhong Wu, Yue Yang, Kun Lei, Jianming The Natural Resources Technology Information Center of Guizhou Province Guiyang550004 China School of Geography and Environment School of Karst Science Guizhou Normal University Guiyang550001 China

ISBN: (纸本)9798400718311

With the acceleration of urbanization and the continuous growth of population, land resources are increasingly tight, and land use control has become an important means to ensure the sustainable development of cities and the rational utilization of land resources. Traditional land use control methods often rely on manual judgment and decision-making, and have problems such as low efficiency and strong subjectivity. The emergence of AI intelligent systems provides a new solution for land use control. AI technology, with its strong data processing capabilities and predictive analysis capabilities, shows great potential in the field of land use control. This paper introduces the technical support system of land use control, analyzes the current situation and necessity of land use control system in China, and then discusses the application of AI intelligent system in land use control. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Artificial intelligence

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robotics And Automation in Healthcare 1

Robotics And Automation in Healthcare

引用

1st international conference on Healthcare Innovations, Software and Engineering Technologies, HISET 2024

作者： Ingole, Aachal Sonwane, Sandip Datta Meghe Institute of Higher Education and Research Datta Meghe College of Pharmacy Wardha India

ISBN: (纸本)9798350360707

Automation and machinery are growing more and more integrated in the healthcare sector and are going through a significant transition. This article gives a thorough analysis of the crucial part that these technical developments have played in the development of patient care. We begin with an overview of the history and follow the growth of robots in healthcare from its inception to today's state of affairs. Going more, this article discusses the roles and responsibilities of a variety of robots used in healthcare by taking a close look at them. We investigate the wide range of uses for these devices, from telemedicine robots that bridge geographical divides to surgical robots that execute complex procedures with unparalleled precision and patient care robots that enhance the lives of those in need. Technological marvels offer. Additionally, we examine the widespread use of automation and artificial intelligence in the medical sector, emphasizing their transformative impact. AI is changing healthcare in several ways, including machine learning algorithms that facilitate quick and precise diagnosis, predictive analytics that foresee disease outbreaks, and personalized medicine that alters therapies based on each patient's unique genetic makeup. Amid this revolutionary growth, we carefully weigh the advantages and disadvantages of increasing automation and machines in healthcare. On the one hand, we call for emphasis on the potential for better patient outcomes due to reduced procedures, improved precision, and reduced labor costs. Yet we also address problems concerning data security, privacy, and the prospect of job displacement, all of which demand particular care in this modern day and time of quick changes in technology. © 2024 IEEE.

关键词： artificial intelligence automation healthcare robotics

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Fabrication and analysis of Pneumatically Actuated Soft Robotic Gripper with Negative Pressure

Fabrication and Analysis of Pneumatically Actuated Soft Robo...

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2025 international conference on Advances in Design, Materials, Manufacturing and Surface Engineering for Mobility, ADMMS 2025

作者： Sreejith, Warriar J.S. Sadique, Anwar George, Boby Government Engineering College Thrissur India

Soft-bending actuators are gaining considerable attention in robotics for handling delicate objects and adapting to complex shapes, making them ideal for biomimetic robots. Soft pneumatic actuators (SPAs) are preferred in soft robotics because to their safety and compliance characteristics. Using negative pressure for actuation, it enhances stability by reducing the risk of sudden or unintended movements, crucial for delicate handling and consistent performance. Negative pressure actuation is more energy-efficient, safe and are less prone to leakage, increasing reliability and durability. This paper involves development of a new soft pneumatic actuator design by comparing various designs and to determine its performance parameters. This paper depicts on designing, and fabricating flexible soft pneumatic actuators working under negative pressure for soft robotic applications. The material used for fabrication was liquid silicone rubber and uniaxial tensile tests were conducted to characterise the properties of materials used to fabricate the soft actuator. The design process begins with conceptualizing the gripper's geometry and layout, considering factors such as material properties, actuation mechanisms etc. Finite element analysis is then employed to evaluate the performance and behavior of the gripper under different loading conditions in negative pressure. Moulds were manufactured using rapid prototyping machine for manufacturing soft pneumatic actuators. Experimental studies were conducted and compared with simulation results. © 2025 SAE international. All Rights Reserved.

关键词： Tensile testing

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DOUBLY ROBUST PROXIMAL CAUSAL LEARNING FOR CONTINUOUS TREATMENTS 12

DOUBLY ROBUST PROXIMAL CAUSAL LEARNING FOR CONTINUOUS TREATM...

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12th international conference on Learning Representations, ICLR 2024

作者： Wu, Yong Fu, Yanwei Wang, Shouyan Sun, Xinwei Institute of Science and Technology for Brain-Inspired Intelligence Fudan University China School of Data Science Fudan University China Zhangjiang Fudan International Innovation Center China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University China MOE Frontiers Center for Brain Science Fudan University China Shanghai Engineering Research Center of AI & Robotics Fudan University China Engineering Research Center of AI & Robotics Ministry of Education Fudan University China

Proximal causal learning is a powerful framework for identifying the causal effect under the existence of unmeasured confounders. Within this framework, the doubly robust (DR) estimator was derived and has shown its effectiveness in estimation, especially when the model assumption is violated. However, the current form of the DR estimator is restricted to binary treatments, while the treatments can be continuous in many real-world applications. The primary obstacle to continuous treatments resides in the delta function present in the original DR estimator, making it infeasible in causal effect estimation and introducing a heavy computational burden in nuisance function estimation. To address these challenges, we propose a kernel-based DR estimator that can well handle continuous treatments for proximal causal learning. Equipped with its smoothness, we show that its oracle form is a consistent approximation of the influence function. Further, we propose a new approach to efficiently solve the nuisance functions. We then provide a comprehensive convergence analysis in terms of the mean square error. We demonstrate the utility of our estimator on synthetic datasets and real-world applications. © 2024 12th international conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Delta functions

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An Efficient Frequency Guided Image Enhancement Network for Shadow Removal 5

An Efficient Frequency Guided Image Enhancement Network for ...

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5th international conference on Smart Sensors and Application, ICSSA 2024

作者： Murtaza, Ali Khairuddin, Uswah Faudzi, Ahmad A.M. Hamamoto, Kazuhiko Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur Malaysia Centre for Artificial Intelligence and Robotics Universiti Teknologi Malaysia Johor Baru Malaysia School of Information Science and Technology Tokai University Tokyo Japan

ISBN: (纸本)9798350354294

Shadow removal poses a significant challenge in computer vision as it seeks to accurately restore image details obscured by shadowed areas. Existing methods for shadow removal often struggle to strike a balance between computational complexity, speed, and performance, rendering many models either too resource-intensive or inadequately effective for real-world applications. Recognizing this gap, we introduce a novel Frequency Guided Network that integrates the benefits of frequency domain processing using Discrete Wavelet Transform with the benefits of deep learning. By decomposing input signals into low and high frequencies, our approach enables the network to prioritize the recovery of crucial information from low-frequency regions while preserving essential high-frequency details, which risk getting lost in the deeper network layers. Notably, our model exhibits impressive efficiency, with a mere parameter count of less than half a million while rivaling the performance of models with significantly more parameters – up to 200 times in some cases. This architecture allows us to process a 1024x1024 image in just 0.14s, demonstrating it’s suitability for real world scenarios. © 2024 IEEE.

关键词： Frequency domain analysis

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Research on Motion Modeling and Interactive Control Technology of Lower Limb Exoskeleton Rehabilitation Robots 24

Research on Motion Modeling and Interactive Control Technolo...

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4th international conference on Control and Intelligent robotics, ICCIR 2024

作者： Xu, Fan Hefei University of Technology Anhui Province Xuancheng City242000 China

ISBN: (纸本)9798400709937

In recent years, the increasing aging population has led to a rising number of patients with lower limb functional impairments. To address these issues, the application of lower limb exoskeleton rehabilitation robots can significantly alleviate problems such as high medical pressure, insufficient allocation of medical resources, and shortage of medical personnel. Simultaneously, utilizing such robots for appropriate and suitable rehabilitation training for patients with lower limb functional impairments can effectively aid in neural reorganization and compensation, thereby greatly improving their survival rate and the likelihood of restoring motor functions. In this paper, focusing on the characteristics of lower limb exoskeleton rehabilitation robots, kinematic modeling is conducted, followed by kinematic analysis, to achieve more efficient and precise control of the robot. Based on the established model, the dynamic equations of the model are derived to analyze the interaction forces between the robot and the patient, ensuring the safety of robot usage and enhancing the rehabilitation effects for patients. To enhance the accuracy of dynamic modeling, model precision, and the adaptability of patients with the robot, this paper analyzes methods and theories of robot parameter identification. Finally, it is concluded that the future direction of interactive robot control will trend towards greater intelligence and personalization. © 2024 held by the owner/author(s).

关键词： Exoskeleton (robotics)

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