检索结果-内蒙古大学图书馆

International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Ramsha Shahid Anam Baloch Humayun Tahir Anayat Ullah Control Automotive and Robotics Lab National Centre of Robotics and Automation Rawalpindi Pakistan Department of Electronic Engineering Balochistan University of IT Engineering and Management Sciences Quetta Pakistan

Terrain adaptability gives snake robots an edge over wheeled mobile robots. Snake robot's applications expansion to disaster management is due to its limbless and modular design. Replicating the navigation and locomotion of a biological snake have been in the spotlight for many researchers. In this study, a robust localization algorithm of a snake robot is developed. A sensor fusion-based algorithm using probabilistic approaches: UKF (Unscented Kalman Filter) and EKF (Extended Kalman Filter) has been proposed. Odometry is fused with one and two IMUs (Inertial Measurement Units) with both probabilistic approaches. Evaluation of results in a simulation environment showed that the fusion of two IMUs and odometry using EKF outer performs in terms of accuracy when odometry is fused with one IMU using EKF. Furthermore, the fusion of two IMUs and odometry with UKF is computationally expensive resulting in a large convergence time which is not the best suitable approach that can be utilized for the snake robot.

关键词： Location awareness Industries Measurement units Snake robots Inertial navigation Disaster management Robot sensing systems

来源：评论

学校读者我要写书评

暂无评论

Doppler-only Single-scan 3D Vehicle Odometry

Doppler-only Single-scan 3D Vehicle Odometry

引用

IEEE International Conference on robotics and automation (ICRA)

作者： Andres Galeote-Luque Vladimír Kubelka Martin Magnusson Jose-Raul Ruiz-Sarmiento Javier Gonzalez-Jimenez System Engineering and Automation Department Machine Perception and Intelligent Robotics (MAPIR) Group University of Malaga Spain Mobile Robotics & Olfaction (MRO) AASS Research Centre Örebro University Sweden

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

We present a novel 3D odometry method that recovers the full motion of a vehicle only from a Doppler-capable range sensor. It leverages the radial velocities measured from the scene, estimating the sensor’s velocity from a single scan. The vehicle’s 3D motion, defined by its linear and angular velocities, is calculated taking into consideration its kinematic model which provides a constraint between the velocity measured at the sensor frame and the vehicle *** carried out prove the viability of our single-sensor method compared to mounting an additional IMU. Our method provides a more reliable translation of the sensor, compared to the errors linked to IMUs due to noise and biases. Its short-term accuracy and fast operation (∼5ms) make it a proper candidate to supply the initialization to more complex localization algorithms or mapping pipelines. Not only does it reduce the error of the mapper, but it does so at a comparable level of accuracy as an IMU would. All without the need to mount and calibrate an extra sensor on the vehicle.

关键词： Accuracy Three-dimensional displays Roads Heuristic algorithms Pipelines Kinematics Odometry

来源：评论

学校读者我要写书评

暂无评论

Towards mechatronics Approach of System Design, Verification and Validation for Autonomous Vehicles

Towards Mechatronics Approach of System Design, Verification...

引用

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

作者： Chinmay Samak Tanmay Samak Venkat Krovi Department of Automotive Engineering Automation Robotics and Mechatronics Laboratory (ARMLab) Clemson University International Center for Automotive Research (CU-ICAR) Greenville USA

Modern-day autonomous vehicles are increasingly becoming complex multidisciplinary systems composed of mechanical, electrical, electronic, computing and information subsystems. Furthermore, the individual constituent technologies employed for developing autonomous vehicles have started maturing up to a point, where it seems beneficial to start looking at the synergistic integration of these components into sub-systems, systems, and potentially, system-of-systems. Hence, this work applies the principles of mechatronics approach of system design, verification and validation for the development of autonomous vehicles. Particularly, we discuss leveraging multidisciplinary co-design practices along with virtual, hybrid and physical prototyping and testing within a concurrent engineering framework to develop and validate a scaled autonomous vehicle using the AutoDRIVE Ecosystem. We also describe a case-study of autonomous parking application using a modular probabilistic framework to illustrate the benefits of the proposed approach.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Exploiting Scale-Variant Attention for Segmenting Small Medical Objects

arXiv

引用

arXiv 2024年

作者： Dai, Wei Liu, Rui Wu, Zixuan Wu, Tianyi Wang, Min Zhou, Junxian Yuan, Yixuan Liu, Jun The Centre for Robotics and Automation City University of Hong Kong Hong Kong The Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong

Early detection and accurate diagnosis can predict the risk of malignant disease transformation, thereby increasing the probability of effective treatment. Identifying mild syndrome with small pathological regions serves as an ominous warning and is fundamental in the early diagnosis of diseases. While deep learning algorithms, particularly convolutional neural networks (CNNs), have shown promise in segmenting medical objects, analyzing small areas in medical images remains challenging. This difficulty arises due to information losses and compression defects from convolution and pooling operations in CNNs, which become more pronounced as the network deepens, especially for small medical objects. To address these challenges, we propose a novel scale-variant attention-based network (SvANet) for accurately segmenting small-scale objects in medical images. The SvANet consists of scale-variant attention, cross-scale guidance, Monte Carlo attention, and vision transformer, which incorporates cross-scale features and alleviates compression artifacts for enhancing the discrimination of small medical objects. Quantitative experimental results demonstrate the superior performance of SvANet, achieving 96.12%, 96.11%, 89.79%, 84.15%, 80.25%, 73.05%, and 72.58% in mean Dice coefficient for segmenting kidney tumors, skin lesions, hepatic tumors, polyps, surgical excision cells, retinal vasculatures, and sperms, which occupy less than 1% of the image areas in KiTS23, ISIC 2018, ATLAS, PolypGen, TissueNet, FIVES, and SpermHealth datasets, respectively. © 2024, CC BY.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Exploration of Unknown Environment using Deep Reinforcement Learning

Exploration of Unknown Environment using Deep Reinforcement ...

引用

International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Asad Ali Sarah Gul Tallat Mahmood Anayat Ullah Control Automotive and Robotics Lab National Centre of Robotics and Automation (NCRA) Rawalpindi Pakistan Department of Electrical Engineering Balochistan University of IT Engineering and Management Sciences Quetta Pakistan

Exploring the unknown environment is a very crucial task where human life is at risks like search and rescue operations, abandoned nuclear plants, covert operations and more. Autonomous robots could serve this task efficiently. The existing methods use uncertainty models for localization and map building to explore the unknown areas requiring high onboard computation and time. We propose to use Deep Reinforcement Learning (DRL) for the autonomous exploration of unknown environments. In DRL, the agent interacts with the environment and learns based on experiences (feedback/reward). We propose extrinsic and curiosity-driven reward functions to explore the environment. The curiosity-based reward function motivates the agent to explore unseen areas by predicting future states, while the extrinsic reward function avoids collisions. We train the differential drive robot in one environment and evaluate its performance in another unknown environment. We observe curiosity-driven reward function outperformed the extrinsic reward by exploring more areas in the unknown environment. The test results show the generalization capability to explore unknown environments with the proposed methods.

关键词： Deep learning Location awareness Industries Uncertainty Service robots Computational modeling Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Robot-Assisted Navigation for Visually Impaired through Adaptive Impedance and Path Planning

Robot-Assisted Navigation for Visually Impaired through Adap...

引用

IEEE International Conference on robotics and automation (ICRA)

作者： Pietro Balatti Idil Ozdamar Doganay Sirintuna Luca Fortini Mattia Leonori Juan M. Gandarias Arash Ajoudani HRI2 Lab Istituto Italiano di Tecnologia Genoa Italy Dept. of Informatics Bioengineering Robotics and System Engineering University of Genoa Genoa Italy Systems Engineering and Automation Department Robotics and Mechatronics Lab University of Malaga Malaga Spain

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper presents a framework to navigate visually impaired people through unfamiliar environments by means of a mobile manipulator. The Human-Robot system consists of three key components: a mobile base, a robotic arm, and the human subject who gets guided by the robotic arm via physically coupling their hand with the cobot’s end-effector. These components, receiving a goal from the user, traverse a collision-free set of waypoints in a coordinated manner, while avoiding static and dynamic obstacles through an obstacle avoidance unit and a novel human guidance planner. With this aim, we also present a legs tracking algorithm that utilizes 2D LiDAR sensors integrated into the mobile base to monitor the human pose. Additionally, we introduce an adaptive pulling planner responsible for guiding the individual back to the intended path if they veer off course. This is achieved by establishing a target arm end-effector position and dynamically adjusting the impedance parameters in real-time through a impedance tuning unit. To validate the framework we present a set of experiments both in laboratory settings with 12 healthy blindfolded subjects and a proof-of-concept demonstration in a real-world scenario.

关键词： Target tracking Navigation Robot kinematics End effectors Real-time systems Path planning Sensors

来源：评论

学校读者我要写书评

暂无评论

Task Space Outer-Loop Integrated DOB-Based Admittance Control of An Industrial Robot

TechRxiv

引用

TechRxiv 2023年

作者： Samuel, Kangwagye Haninger, Kevin Oboe, Roberto Oh, Sehoon The Department of Robotics and Mechatronics Engineering DGIST Daegu42988 Korea Republic of The Department of Automation Fraunhofer IPK Berlin10589 Germany The Department of Management and Engineering University of Padova Vicenza35122 Italy

Admittance control can improve robot performance and robustness in interactive tasks, but is still limited by stability when implemented on low-admittance hardware, such as position-controlled industrial robots. This limits applications which require the payload, reach, or positioning accuracy. While the idealized reference admittance behavior would be stable with any passive environment (provided positive damping), real robots can be unstable, especially with high-stiffness environments. Thus, instability comes from deviation from the ideal reference model, due to either inner-loop bandwidth, time-delay, or other model error. To improve accuracy of rendered dynamics and reduce contact forces, a novel integrated disturbance observer-based admittance control method which is implemented on a position/velocity-controlled industrial robot in task space is proposed. The multisensor information, i.e., the velocity command, measured output velocity, inverse model of the velocity controlled system, and the force/torque (F/T) sensor measurement are integrated to estimate and cancel the disturbances, outside the position/velocity control loop, all in task space. Theoretical analyses and experiments on the actual robot show that the proposed method is able to improve accuracy and reduce contact forces even at higher admittance. © 2023, CC BY.

关键词： Industrial robots

来源：评论

学校读者我要写书评

暂无评论

Laser Erasing and Rewriting of Flexible Copper Circuits

引用

Nano-Micro Letters 2021年第11期13卷 409-420页

作者： Xingwen Zhou Wei Guo Peng Peng School of Mechanical Engineering and Automation Beihang UniversityBeijing 100191People’s Republic of China Department of Mechanical and Mechatronics Engineering Centre for Advanced Materials JoiningUniversity of WaterlooWaterlooON N2L 3G1Canada

Integrating construction and reconstruction of highly conductive structures into one process is of great interest in developing and manufacturing of electronics,but it is quite challenging because these two involve contradictive additive and subtractive *** this work,we report an all-laser mask-less processing technology that integrates manufacturing,modifying,and restoring of highly conductive Cu *** traveling a focused laser,the Cu patterns can be fabricated on the flexible substrate,while these as-written patterns can be selectively erased by changing the laser to a defocused ***,the fresh patterns with identical conductivity and stability can be rewritten by repeating the writing ***,this erasing–rewriting process is also capable of repairing failure patterns,such as oxidation and *** to the high controllability of this writing–erasing–rewriting process and its excellent reproducibility for conductive structures,it opens a new avenue for rapid healing and prototyping of electronics.

关键词： Laser writing Laser erasing Copper electrodes Electronic repairing Flexible electronics

来源：评论

学校读者我要写书评

暂无评论

Smart Shopping and Cart Billing System Using Deep Learning

Smart Shopping and Cart Billing System Using Deep Learning

引用

Intelligent Cyber Physical Systems and Internet of Things (ICoICI), International Conference on

作者： Ramkumar S Saravanan R Kanagaraj Venusamy Rani Jabbar N. Jeevitha Department of Robotics and Automation Rajalakshmi Engineering College Thandalam Chennai India Department of Mechatronics Engineering Rajalakshmi Engineering College Chennai India EDICT Department Electrical Engineering Program Bahrain polytechnic Isa town Kingdom of Bahrain Department of Electrical and Electronics Engineering Roever Engineering College Perambalur India

ISBN: (数字)9798331540661

ISBN: (纸本)9798331540678

There are many problems faced by people who stand for hours at billing counter after shopping, even though crowds are avoided everywhere, shopping mall billing queue isn't reducing since ages. Since the world relies on automation today, everyone has to automate processes which consumes time, money and efforts wherever possible. The technique related with the use of Raspberry Pi, LCD display and Webcam helps the people to bill the groceries within the shopping cart. It reduces consumption of time and their energy can be conserved which can't happen when they stand in a queue for billing process. User have to scan the object in front of webcam and LCD display allows them to add purchased items along with their price and quantity. They can also remove the product fromthe cart and it will be automatically removed. At the end of process, payment can be made online using a QR code or UPI. The Bill will be generated to their respective mail or it will be sent as SMS. User have to register or Log in when they start shopping. Automatic detection is possible without any inspection behind. The model is much portable and does not face any problem in its operation. When compared with the existing methods the processor, display along with its webcam accuracy is much better, it does not require complete continuous guidance and maintenance upon its usage. The need to push the cart has been eliminated as the cart can move along/follow the user autonomously.

关键词： Deep learning Webcams QR codes Inspection Liquid crystal displays Registers Maintenance Internet of Things Faces Postal services

来源：评论

学校读者我要写书评

暂无评论

Multi-class machine learning based approach for sleep disorder identification using EEG signals

Multi-class machine learning based approach for sleep disord...

引用

7th IET Smart Cities Symposium (SCS 2023)

作者： Rajalakshmi Murugesan Karthik Chandran P. K. Dutta Department of Mechatronics Thiagarajar College of Engineering Madurai Tamilnadu India Department of Robotics & Automation Jyothi Engineering College Kerala India Department of Electronics and Communication School of Engineering and Technology Amity University Kolkata India

Accurately identifying sleep stages is crucial for the analysis and management of sleep disorders. Electroencephalogram (EEG) signals have shown promise in sleep stage identification. This research presents a novel method for classifying different sleep stages using EEG data based on a multi-class support vector machine (SVM) approach. The proposed method involves preprocessing the EEG signals to remove noise and artifacts, followed by feature extraction using wavelet transform and statistical methods. A multi-class SVM classifier is then trained to identify four sleep stages: waking, non-rapid eye movement (NREM) stage 1, non-rapid eye movement (NREM) stage 2, and rapid eye movement (REM) stage. The method is evaluated on a dataset comprising EEG signals collected from 20 healthy individuals during a full-night sleep study. The results demonstrate that the proposed technique outperforms existing EEG-based approaches, achieving anaverage classification accuracy of 86.2 for sleep stage identification. The suggested method has potential applications in clinical settings for sleep disorder evaluation and management. Additionally, it can be extended to other applications requiring the identification of various classes from EEG data.

关键词：

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：