检索结果-内蒙古大学图书馆

HighTech and Innovation Journal 2023年第4期4卷 829-837页

作者： De Guzman, C.J.P. Chua, A.Y. Chu, T.S. Secco, E.L. Department of Mechanical Engineering De La Salle University 2401 Taft Ave. Malate Manila Philippines Robotics Laboratory School of Mathematics Computer Science & Engineering Liverpool Hope University United Kingdom

Quadrotors have been vital for automating warehouse processes. However, a significant gap in recent studies is that they use a single quadrotor with limited battery life, considering that their objective involves navigation in a large-scale environment such as a warehouse. Using an energy consumption model to enable more efficient navigation can be explored. Conventional data-driven energy models and path planning algorithms are insufficient for describing the various motions that a quadrotor can perform in warehouse operations, such as changes in yaw. This study aims to design a novel exhaustive data-driven energy consumption model and evolutionary algorithm-based path planning algorithm to consider various quadrotor movements involved in warehouse operations. The quadrotor is tasked with performing a set of movements to each be represented as a power equation in terms of their velocity. The obtained equations were subsequently used as the primary optimization objective for the path planning algorithm, which included yaw angle objectives and constraints. A set of experiments was performed with Crazyflie quadrotors to verify the model and the algorithm. The results showcased the accuracy of the energy consumption model, which was kept at a maximum difference of 0.6%. The designed path planning algorithm obtained greater energy efficiency in the generated paths compared to other state-of-the-art evolutionary algorithms with similar objectives and constraints. © Authors retain all.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

RT-Swap: Addressing GPU Memory Bottlenecks for Real-Time Multi-DNN Inference 30

RT-Swap: Addressing GPU Memory Bottlenecks for Real-Time Mul...

引用

30th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2024

作者： Kang, Woosung Lee, Jinkyu Lee, Youngmoon Oh, Sangeun Lee, Kilho Chwa, Hoon Sung DGIST Dept. of Electrical Engineering and Computer Science Korea Republic of Dept. of Computer Science and Engineering Korea Republic of Hanyang University Dept. of Robotics Korea Republic of Ajou University Department of Software and Computer Engineering Korea Republic of School of AI Convergence Soongsil University Korea Republic of

ISBN: (纸本)9798350358414

The increasing complexity and memory demands of Deep Neural Networks (DNNs) for real-Time systems pose new significant challenges, one of which is the GPU memory capacity bottleneck, where the limited physical memory inside GPUs impedes the deployment of sophisticated DNN models. This paper presents, to the best of our knowledge, the first study of addressing the GPU memory bottleneck issues, while simultaneously ensuring the timely inference of multiple DNN tasks. We propose RT-Swap, a real-Time memory management framework, that enables transparent and efficient swap scheduling of memory objects, employing the relatively larger CPU memory to extend the available GPU memory capacity, without compromising timing guarantees. We have implemented RT-Swap on top of representative machine-learning frameworks, demonstrating its effectiveness in making significantly more DNN task sets schedulable at least 72% over existing approaches even when the task sets demand up to 96.2% more memory than the GPU's physical capacity. © 2024 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

RoboCup@Home 2024 OPL Winner NimbRo: Anthropomorphic Service Robots Using Foundation Models for Perception and Planning

RoboCup@Home 2024 OPL Winner NimbRo: Anthropomorphic Service...

引用

27th RoboCup International Symposium, 2024

作者： Memmesheimer, Raphael Nogga, Jan Pätzold, Bastian Kruzhkov, Evgenii Bultmann, Simon Schreiber, Michael Bode, Jonas Karacora, Bertan Park, Juhui Savinykh, Alena Behnke, Sven Autonomous Intelligent Systems Computer Science Institute VI Lamarr Institute for Machine Learning and Artificial Intelligence and Center for Robotics University of Bonn Bonn Germany

ISBN: (纸本)9783031858581

We present the approaches and contributions of the winning team NimbRo@Home at the RoboCup@Home 2024 competition in the Open Platform League held in Eindhoven, NL. Further, we describe our hardware setup and give an overview of the results for the task stages and the final demonstration. For this year’s competition, we put a special emphasis on open-vocabulary object segmentation and grasping approaches that overcome the labeling overhead of supervised vision approaches, commonly used in RoboCup@Home. We successfully demonstrated that we can segment and grasp non-labeled objects by text descriptions. Further, we extensively employed Large Language Model (LLMs) for natural language understanding and task planning. Throughout the competition, our approaches showed robustness and generalization capabilities. A video of our performance can be found online (https://***/videos/RoboCup_2024). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Robot programming

来源：评论

学校读者我要写书评

暂无评论

Energy Efficient Hardware Acceleration of Neural Networks with Power-of-Two Quantisation

Energy Efficient Hardware Acceleration of Neural Networks wi...

引用

International Conference on computer Vision and Graphics, ICCVG 2022

作者： Przewlocka-Rus, Dominika Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland

ISBN: (纸本)9783031220241

Deep neural networks virtually dominate the domain of most modern vision systems, providing high performance at a cost of increased computational complexity. Since for those systems it is often required to operate both in real-time and with minimal energy consumption (e.g., for wearable devices or autonomous vehicles, edge Internet of Things (IoT), sensor networks), various network optimisation techniques are used, e.g., quantisation, pruning, or dedicated lightweight architectures. Due to the logarithmic distribution of weights in neural network layers, a method providing high performance with significant reduction in computational precision (for 4-bit weights and less) is the Power-of-Two (PoT) quantisation (and therefore also with a logarithmic distribution). This method introduces additional possibilities of replacing the typical for neural networks Multiply and ACcumulate (MAC—performing, e.g., convolution operations) units, with more energy-efficient Bitshift and ACcumulate (BAC). In this paper, we show that a hardware neural network accelerator with PoT weights implemented on the Zynq UltraScale + MPSoC ZCU104 SoC FPGA can be at least 1.4x more energy efficient than the uniform quantisation version. To further reduce the actual power requirement by omitting part of the computation for zero weights, we also propose a new pruning method adapted to logarithmic quantisation. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： System-on-chip

来源：评论

学校读者我要写书评

暂无评论

Quality Estimation of Electronic Educational Resources 2

Quality Estimation of Electronic Educational Resources

引用

2nd International Conference on Technology Enhanced Learning in Higher Education, TELE 2022

作者： Karamzina, Anastasia Silnova, Svetlana Ufa State Aviation Technical University Department of Computer Science and Robotics Ufa Russia

ISBN: (纸本)9781665470070

The transition of modern higher education to online learning is analyzed, the relevance of estimation the quality of electronic educational resources is substantiated. Using the Ishikawa diagram, problems were identified in estimation the quality of electronic educational resources. Criteria and procedure for estimation the quality of electronic educational resources were proposed, modeling of the process of estimation the quality of electronic educational resources was carried out. The requirements for conducting an expert estimation of the quality of electronic educational resources, for a user estimation of the quality of electronic educational resources have been determined. Quality estimation of electronic educational resources in the area of training 'Quality Management' was carried out. © 2022 IEEE.

关键词： E-learning

来源：评论

学校读者我要写书评

暂无评论

Maximum Stability Controller Synthesis for a System with an Interval Characteristic Polynomial Using Critical Root Diagrams

Maximum Stability Controller Synthesis for a System with an ...

引用

2022 International Russian Automation Conference, RusAutoCon 2022

作者： Sobol, Alexander Gayvoronskiy, Sergey Ezangina, Tatiana National Research Tomsk Polytechnic University School of Computer Science & Robotics Tomsk Russia

ISBN: (数字)9781665466554

ISBN: (纸本)9781665466554

This article considers the application of critical root diagrams for the synthesis of a maximum stability robust controller. These diagrams describe the root arrangement variants where the maximum stability degree is achieved in stationary systems. The article solves the problem of providing the maximum stability degree for the one-parameter controller. This regulator is used in the system with interval-indefinite coefficients of the characteristic polynomial. For this, algebraic conditions are obtained. Under these conditions, the stability degree will be maximum. Also, the algorithm of regulator synthesis is given. Based on these conditions and algorithms, the limiting stability degree of the third-order interval system is found. © 2022 IEEE.

关键词： Graphic methods

来源：评论

学校读者我要写书评

暂无评论

Traffic Sign Classification Using Deep and Quantum Neural Networks

Traffic Sign Classification Using Deep and Quantum Neural Ne...

引用

International Conference on computer Vision and Graphics, ICCVG 2022

作者： Kuros, Sylwia Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland

ISBN: (纸本)9783031220241

Quantum Neural Networks (QNNs) are an emerging technology that can be used in many applications including computer vision. In this paper, we presented a traffic sign classification system implemented using a hybrid quantum-classical convolutional neural network. Experiments on the German Traffic Sign Recognition Benchmark dataset indicate that currently QNN do not outperform classical DCNN (Deep Convolutuional Neural Networks), yet still provide an accuracy of over 90% and are a definitely promising solution for advanced computer vision. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Traffic signs

来源：评论

学校读者我要写书评

暂无评论

Optimization-Method-Inspired Update Scheme for Neural Network Assisted Control Tuning of PMSMs 26

Optimization-Method-Inspired Update Scheme for Neural Networ...

引用

26th International Conference on Electrical Machines and Systems, ICEMS 2023

作者： Yin, Zhenxiao Zhao, Hang Lu, Pei Shen, Yang Robotics and Autonomous Systems Thrust Guangzhou China The Hong Kong University of Science and Technology Department of Electronic & Computer Engineering Hong Kong

ISBN: (纸本)9798350317589

The derivative of the control increment concerning the output of the neural network (NN) stands as a pivotal factor within the NN-assisted control tuning approach for permanent magnet synchronous motors (PMSMs). However, the significance of selecting an appropriate formula lacks explanation. Through an analysis of gradient-based optimization methods, the underlying principle behind the update of control increments becomes evident. Consequently, the design of the control tuning scheme incorporates gradient descent with and without momentum, as well as accelerated momentum. These techniques are applied to formulate the update law for the backpropagation neural network (BPNN) assisted control. Subsequently, these devised methodologies are integrated into the BPNN framework for the purpose of comparison. Finally, the results are validated in experiments. © 2023 IEEE.

关键词： Optimization

来源：评论

学校读者我要写书评

暂无评论

PierGuard: A Planning Framework for Underwater Robotic Inspection of Coastal Piers

引用

IEEE Transactions on Automation science and Engineering 2025年 22卷 15941-15952页

作者： Wang, Pengyu Lin, Hin Wang Li, Jialu Wang, Jiankun Shi, Ling Meng, Max Q.-H Southern University of Science and Technology Shenzhen Key Laboratory of Robotics Perception and Intelligence Department of Electronic and Electrical Engineering Shenzhen China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Southern University of Science and Technology Jiaxing Research Institute Jiaxing China Hong Kong University of Science and Technology Department of Chemical and Biological Engineering Hong Kong The Chinese University of Hong Kong Department of Electronic Engineering Hong Kong University of Alberta Canada Department of Electrical and Computer Engineering Canada

Using underwater robots instead of humans for the inspection of coastal piers can enhance efficiency while reducing risks. A key challenge in performing these tasks lies in achieving efficient and rapid path planning within complex environments. Sampling-based path planning methods, such as Rapidly-exploring Random Tree* (RRT*), have demonstrated notable performance in high-dimensional spaces. In recent years, researchers have begun designing various geometry-inspired heuristics and neural network-driven heuristics to further enhance the effectiveness of RRT*. However, the performance of these general path planning methods still requires improvement when applied to highly cluttered underwater environments. In this paper, we propose PierGuard, which combines the strengths of bidirectional search and neural network-driven heuristic regions. We design a specialized neural network to generate high-quality heuristic regions in cluttered maps, thereby improving the performance of the path planning. Through extensive simulation and real-world ocean field experiments, we demonstrate the effectiveness and efficiency of our proposed method compared with previous research. Our method achieves approximately 2.6 times the performance of the state-of-the-art geometric-based sampling method and nearly 4.9 times that of the state-of-the-art learning-based sampling method. Our results provide valuable insights for the automation of pier inspection and the enhancement of maritime safety. (Video1). © 2004-2012 IEEE.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

Medical Recommendation System Based on Collaborative Filtering Algorithms

Medical Recommendation System Based on Collaborative Filteri...

引用

International Russian Smart Industry Conference (SmartIndustryCon)

作者： Diana Bogdanova Gyuzel Shakhmametova Albert Niiazgulov Department of Computer Science and Robotics Ufa University of Science and Technology Ufa Russia

The article deals with the issues of designing a medical recommendation system based on the collaborative filtering algorithm. The problem under consideration is a large number of medical errors, which are one of the most common causes of patient deaths. In Russia alone, more than 70 thousand people suffer severe complications every year for this reason. The aim of the research is to analyze the possibility of designing and implementing software that reduces the probability of occurrence of medical errors and allows to realize the automation of prescribing by a doctor of the optimal treatment for a particular patient. The article analyzes the subject area and problem situation, identifies the causes of a large number of medical errors in public medical institutions in Russia. The problem statement is considered, mathematical support of the recommendation system based on the algorithm of collaborative filtering is proposed. The analysis of methods for solving the problem is given. The implementation of the recommendation system in the Python programming language is considered, the results of research in the form of a computational experiment are analyzed and interpreted. According to the results of the research, it is concluded that the proposed implementation of the medical recommendation system based on the collaborative filtering algorithm can be used in the further design of a full-fledged system and then used in medical institutions as a part of the system.

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：