检索结果-内蒙古大学图书馆

International Conference on advanced Electrical Engineering (ICAEE)

作者： Seif Eddine Seray Ishak Bey Isma Akli Department of Control and Power University of M'hammed Bouguerra Boumerdes Algeria Robotics and Industrial Automation Division Center for Development of Advanced Technologies Algiers Algeria

ISBN: (数字)9798350349351

ISBN: (纸本)9798350349368

The quantity of domestic wastes is constantly increasing, resulting on overload of wastes. Recycling became imperative for ecologic and economical considerations in order to apply circular economy rules. In general, humans are recruited in waste sorting plants for performing the dangerous and tedious sorting tasks. The automation is, thus, necessary. This paper deals with the problem of waste sorting automation. The proposed solution consists of waste recognition and classification using YOLOv8, and human presence detection using RFID (Radio frequency Identification) tags. The proposed solution is validated in simulation. The virtual robot performs a task in order to simulate the behavior of a real robot with high fidelity, depending on the information coming from the RFID tags and a visual sensor.

关键词： Visualization Automation Software architecture Operating systems Robot vision systems Robot sensing systems Recycling RFID tags Middleware Sorting

来源：评论

学校读者我要写书评

暂无评论

Predictive Control of Vehicle Dynamics Equipped with Intelligent Tire Sensors via Gaussian Process Regression of Lateral Tire Force

Predictive Control of Vehicle Dynamics Equipped with Intelli...

引用

International Conference on Control and Automation (ICCA)

作者： Kunhee Ryu Jinsung Kim Minkyu Han Juhoon Back Vehicle Control Technology Development Team Division of Advanced Vehicle Platform Hyundai Motor Company Republic of Korea School of Robotics Kwangwoon University Seoul Republic of Korea

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

This paper investigates the estimation of lateral tire forces and predictive control for vehicles equipped with intelligent tires. Motivated by the capability of intelligent tires to estimate lateral tire forces, we propose a control scheme that includes a predictor for lateral tire forces, utilizing the Gaussian Process Regression technique. In addition, a metric for online data management is proposed, which has the characteristic of retaining more data in regions where the change of the function value is relatively large. The proposed metric can be interpreted as an extension of the existing method, allowing for the control of dataset quality within its limited size. We apply the proposed control scheme to the model predictive contouring control problem. Numerical simulations demonstrate the robustness of the proposed control scheme to tire parameter uncertainty, in comparison to a baseline controller.

关键词： Measurement Uncertain systems Gaussian processes Predictive models Numerical simulation Tires Robustness

来源：评论

学校读者我要写书评

暂无评论

MSCKF-DVIO: Multi-State Constraint Kalman Filter based RGB-D Visual-Inertial Odometry with Spline Interpolation and Nonholonomic Constraint

MSCKF-DVIO: Multi-State Constraint Kalman Filter based RGB-D...

引用

International Conference on Ubiquitous Robots (UR)

作者： Kwangyik Jung Jaebong Song Samwoo Seong Hyun Myung Department of Autonomous Driving Software Development Twinny Yuseong-gu Republic of Korea Urban Robotics Lab School of Electrical Engineering Korea Advanced Institute of Science and Technology Republic of Korea

ISBN: (数字)9798350361070

ISBN: (纸本)9798350361087

This study presents MSCKF-DVIO (Multi-State Constraint Kalman Filter - Depth-aided Visual Inertial Odom-etry) as an innovative approach to address the limitations of existing methods. MSCKF-DVIO leverages RGB-D images and low-cost IMU measurements to enhance the accuracy and efficiency of visual-inertial odometry systems. The proposed framework jointly optimizes RGB-D images and low-cost IMU measurements, enabling robust and precise state estimation. By reducing the number of state variables compared to the existing MSCKF-VIO, the efficiency of state augmentation and covariance computations is significantly enhanced. Notably, the prediction of the future state is achieved through the interpolation of past keyframe viewpoint poses from the image and short-time IMU integration. The proposed MSCKF-DVIO improves the accuracy of estimation by applying nonholonomic constraints (NHCs) of a differential-wheeled mobile robot and utilizing the zero velocity update (ZUPT) based on stationary state determination. The efficacy of MSCKF -DVIO is evaluated through the Absolute Pose Error (APE) using 3D LiDAR-based localization as the ground truth. The evaluation includes pose estimation outcomes and performance evaluations in comparison to other algorithms. The results demonstrate significant promise of MSCKF-DVIO for improving the performance and reliability of visual-inertial odometry systems.

关键词： Interpolation Visualization Accuracy Stationary state Filtering algorithms Information filters Real-time systems

来源：评论

学校读者我要写书评

暂无评论

A Novel Quadruple Dispensing Heads Sticking Adhesive Tape Robot System and Its Applications

A Novel Quadruple Dispensing Heads Sticking Adhesive Tape Ro...

引用

International Conference on Mechatronics (ICM)

作者： Kitti Suwanratchatamanee Hideyuki Sawada Shuji Hashimoto Robotics Research and Development Center GOLDEN ROBOT Co. Ltd. Rayong Thailand Grad. School of Advanced Science and Engineering WASEDA University Tokyo Japan WASEDA University Tokyo Japan

ISBN: (数字)9798331533892

ISBN: (纸本)9798331533908

Industrial robots are increasingly being used to assist and replace workers in factories to address the global labor shortage in various applications. The use of robots can provide many benefits to the effective production and manufacturing. Taping is one of the robots' applications. However, current tape robots can only tape one strip at a time, which can be time-consuming in practice if multiple strips of tape are required at the same time for special workpieces. This paper presents a novel sticking adhesive tape robot system. As the object to be taped are four-line hot pipes to be attached on the outer shell of refrigerator, thus four strips of tape are required at the same time before assembly process. The proposed robot system contains the novel tooling called “Quadruple Dispensing Heads”. This tooling was developed to tape four strips of tape to be applied simultaneously. This tooling can adjust the gap of tape strips from 80mm to 110mm. Moreover, the research objective is to produce a robot system that can apply tape with higher quality and faster than human workers, so that human workers can move on to more complicated tasks instead of performing repetitive, routine tasks that do not require such special skills and knowledge. As the result, our proposed system can achieve the four lines of *** length, through IS7N pushing force (when operate the air working pressure at ***) sticking taping task perfectly with 100% success rate of experiments in just 3 seconds and faster than human worker significantly. Since, human worker needs about 3 seconds per each I.5m taping line. Therefore, human needs approximately 12 seconds in total for four lines. Accordingly, our proposed robot system is faster than human worker in four times.

关键词： Strips Mechatronics Service robots Force Industrial robots Production facilities Robots Assembly

来源：评论

学校读者我要写书评

暂无评论

The A3C Algorithm With Eligibility Traces of Energy Management for Plug-In Hybrid Electric Vehicles

引用

IEEE Access 2025年 13卷 92507-92518页

作者： Dingyi Guo Guangyin Lei Huichao Zhao Fang Yang Qiang Zhang Shanghai Engineering Technology Research Center of SiC Power Device College of Intelligent Robotics and Advanced Manufacturing Fudan University Shanghai China Research Institute of Fudan University in Ningbo Ningbo China General Research and Development Institute China FAW Corporation Ltd. Changchun China

An energy management system is crucial for optimizing the performance and reducing fuel consumption of Plug-in Hybrid Electric Vehicles (PHEVs), which plays an important role in sustainable transportation. This paper presents a comprehensive study of the energy management problem for a selected PHEV, outlining key vehicle parameters such as battery state-of-charge (SOC), engine power, and energy consumption patterns. A mathematical formulation of the energy management problem is proposed to optimize fuel consumption while adhering to the vehicle’s operational constraints. The core of the paper focuses on the application of the Asynchronous Advantage Actor-Critic (A3C) algorithm to address this problem. To enhance the learning process, eligibility traces are introduced to refine the advantage function by weighting historical actions. This adjustment improves the decision-making process by making the action distribution more concentrated, which is crucial for optimizing fuel consumption. The proposed Asynchronous Advantage Actor-Critic Eligibility Traces (A3CET) algorithm incorporates these modifications and shows a significant improvement in fuel efficiency. During the training phase, it achieves 93.6% of the fuel optimality of the Dynamic Programming (DP) benchmark, and maintains 91.5% of DP’s performance during the testing phase. Moreover, A3CET reduces computation time by 62.5% compared to DP, and outperforms other EMSs in terms of both efficiency and real-time applicability.

关键词： Energy management Engines Batteries Reinforcement learning Prediction algorithms Motors Mechanical power transmission Heuristic algorithms Adaptation models Energy consumption

来源：评论

学校读者我要写书评

暂无评论

A Real- Time Multi-Camera Auto-Adjustment Framework for Infrastructure Inspections

A Real- Time Multi-Camera Auto-Adjustment Framework for Infr...

引用

IEEE/SICE International Symposium on System Integration

作者： Chuong Phuoc Le Charles Ellison Steven Bunkley Hung La Anton Netchaev Department of Computer Science and Engineering Advanced Robotics and Automation (ARA) Lab University of Nevada Reno NV USA USACE Engineer Research and Development Center (ERDC) Information Technology Lab Vicksburg MS USA

In this paper, we proposed a novel multi-camera auto-adjustment framework for infrastructure inspections, specifically 3D point cloud mapping via lidar-camera fusion. Our method uses a single controller for consensus target brightness and adaptive lighting. In addition, a vignette correction filter was created to apply to images outputted from cameras to avoid dark strips on the point cloud data. This approach is designed to be a versatile, real-time friendly, and platform agnostic software stack.

关键词：

来源：评论

学校读者我要写书评

暂无评论

16-Layer 3D Stacking Based on Self-Assembly Technology for HBM Application

16-Layer 3D Stacking Based on Self-Assembly Technology for H...

引用

IEEE International Conference on 3D System Integration, 3DIC

作者： Du Zehua Hiroshi Kikuchi Hayato Hishinuma Tetsu Tanaka Takafumi Fukushima Graduate School of Engineering Tohoku University Sendai Japan Advanced Technology Development Center Yamaha Robotics Holdings Co. Ltd. Tokyo Japan Graduate School of Biomedical Engineering Tohoku University Sendai Japan

ISBN: (数字)9798331516505

ISBN: (纸本)9798331516512

We address a trade-off issue between chip assembly time and positioning accuracy in a traditional pick-and-place method using self-assembly technology driven by liquid surface tension. This method allows 16-layer stacking of 50-um-thin chips fabricated via Plasma Dicing Before Grinding (PDBG). The surface tension of liquid droplets enables sub-50 nm alignment accuracy even with manual chip placement. By identifying key parameters such as pre-alignment position and liquid volume/distribution, we optimize the self-assembly process for High Bandwidth Memory (HBM) applications. Additionally, we discuss the effects of liquid bridges and wetting contrast between the chip surface and sidewall on multi-layer stacking.

关键词： Bridges Liquids Accuracy Self-assembly Three-dimensional displays Stacking System integration Surface tension Plasmas Surface treatment

来源：评论

学校读者我要写书评

暂无评论

Learning Terminal State of the Trajectory Planner: Application for Collision Scenarios of Autonomous Vehicles

Learning Terminal State of the Trajectory Planner: Applicati...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Joonhee Lim Kibeom Lee Jangho Shin Dongsuk Kum Robotics Program Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea Department of Mechanical Engineering Gachon University Seongnam Republic of Korea Research & Development Division Hyundai Motor Company Hwaseong Republic of Korea The Cho Chun Shik Graduate School of Mobility Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Collision Avoidance/Mitigation System (CAMS) for autonomous vehicles is a crucial technology that ensures the safety and reliability of autonomous driving systems. Conventional collision avoidance approaches struggle in complex and various scenarios by avoiding collisions based on rules for specific collision scenarios. This has led to learning-based methods using neural networks for adaptive collision avoidance. However, the approaches directly outputting control inputs through neural networks have drawbacks in interpretability and stability. To address these limitations, we propose a trajectory planning method for CAMS that combines deep reinforcement learning (DRL) and quintic polynomial (QP) trajectory planning. The proposed method determines the terminal state and confidence of the trajectory using DRL and plans a QP trajectory based on them. By utilizing the terminal state and confidence of the trajectory rather than direct control inputs as the output of the neural network, it generates a more realistic and continuous path. Moreover, this approach considers collision avoidance and mitigation in an integrated manner through the reward function of RL. Our experimental results demonstrate that the proposed method not only improves interpretability and stability compared to existing learning-based methods but also upholds performance in complex and various collision scenarios.

关键词： Learning systems Trajectory planning Neural networks Trajectory Cams Safety Reliability

来源：评论

学校读者我要写书评

暂无评论

Utilizing Artificial Intelligence (Ai) and Knowledge Based Engineering (Kbe) for Enhanced Ship Design: A Technical Feasibility

SSRN

引用

SSRN 2023年

作者： Shahzad, Tufail Peng, Wang Hoffmans, Jacques van Lith, Peter School of Marine Science and Technology Northwestern Polytechnical University China Department of Innovation MasterShip Software BV Netherlands Department of Research & Development MasterShip Software BV Netherlands Department of Advanced robotics Multimotions BV Netherlands

As the shipbuilding industry continues to evolve and embrace new technologies, artificial intelligence (AI) and knowledge-based engineering (KBE) software have emerged as promising tools for enhancing the design process. This paper examines the technical feasibility of utilizing artificial intelligence (AI) and Knowledge-Based Engineering (KBE) software for ship design, aiming to virtually incorporate practical knowledge and technical constraints of experienced workers during detailed engineering and work preparation stages. While the shipbuilding industry has made significant advancements in CAD/CAM technology, AI/KBE software could potentially simulate human problem-solving processes to make informed decisions. Additionally, the paper examines the potential economic and modernization impacts of this technology on ship design and construction. The study concludes that such a system is possible, and could enhance the decision-making process and improve the maturity of CAD/CAM applications within the shipbuilding industry. This research also highlights the potential of AI/KBE software for future ship design and calls for further research and development in this area to fully realize its benefits. © 2023, The Authors. All rights reserved.

关键词： Shipbuilding

来源：评论

学校读者我要写书评

暂无评论

AMR Navigation Based on Dynamic Control Sampling Space

AMR Navigation Based on Dynamic Control Sampling Space

引用

Advances in Electronics, Control and Communication Systems (ICAECCS), International Conference on

作者： Sara Bouraine Idriss Hasani Alla Djoudi Ahmed Gourine Boualem Kazed Division Robotics and Industrial Automation Center for Development of Advanced Technologies Baba Hassen Algeria Electronic and Automation department University BLIDA-1 Blida Algeria University of Science and Technology Houari Boumedienne Bab ezzouar Algeria

This paper addresses the problem of local navigation for autonomous mobile robots in partially observable dynamic environments. The main contribution of this work is the expansion of a sampling based approach to deal with the robot and environment dynamic constraints and integrate a safety distance to keep the robot away from collisions. The developed algorithm has been implemented on a robotic platform with a Robot Operating System based embedded architecture, where it has been tested and validated in an indoor environment.

关键词： Navigation Service robots Operating systems Heuristic algorithms Control systems Safety Planning

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：