检索结果-内蒙古大学图书馆

Corrections to “A Piecewise Monotonic Smooth Phase Variable for Speed-Adaption Control of Powered Knee-Ankle Prostheses”

引用

IEEE robotics and Automation Letters 2022年第4期7卷 11475-11475页

作者： Teng Ma Yuxuan Wang Xinxing Chen Chuheng Chen Zhimin Hou Haoyong Yu Chenglong Fu Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems and Guangdong Provincial Key Laboratory of Human Augmentation and Rehabilitation Robotics in Universities Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen China Department of Biomedical Engineering National University of Singapore Singapore

Firstly, in the letter [1], there is a missing citation in Section II, part B, the first sentence. It should be “In a manner similar to [2], [3], speed estimation was achieved by a double-pendulum model.” In our previous version [1], speed estimation was based on the principles in [3]. We also referred to the interpretation and expression form of 6 and 7 in [2], but did not cite this reference in [1]. It should be noted that the 9 in [1] is not the same as 5 in [2]. Because our prosthesis can measure the kinematic information of the hip, knee, and ankle, we considered using the kinematics of the three joints to estimate the velocity, instead of only using the angle hip and knee as in [2], therefore we additionally introduced the ankle angle in 9 of [1]. This led to changes in the lower extremity model used in our calculations and changes in the formula for calculating the stride length.

关键词： Prosthetics Robot sensing systems Phase measurement Biomedical measurement Thigh Noise measurement Legged locomotion

来源：评论

学校读者我要写书评

暂无评论

Position control of XY precision planar motion table based on input shaping filter

Position control of XY precision planar motion table based o...

引用

作者： HuaLiang Zhang Xu Lu DanPing Jia BingJie Zhao Tao Zhang Yang Liu HongYu Yan Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Artificial Intelligence Shenyang University of Technology School of Information Science and Engineering Shenyang University of Technology

In order to solve the vibration problem of mining equipment,a Simulink simulation model of current loop,speed loop and position loop of permanent magnet synchronous motor was established to track the input position signal of the motor system.[1] At the same time,the input shaper is introduced into the motor three loop control model to study the vibration suppression effect of the input shaper.[2] The essence of the input shaper is to filter the input ***,the parameters of the input shaper need to be accurately identified and the detailed parameters of the system need to be ***,the problem that the identification accuracy of the system is not enough often makes the parameters of the shaper *** view of the problem that the system identification is not accurate,a method of adjusting and setting input shaper parameters is designed,which is not very dependent on the *** results show that the optimal parameters of the shaper can be selected by the *** with the parameters of the shaper selected according to the identification model,the vibration suppression effect is better.

关键词： system identification input shaping oscillation suppression

来源：评论

学校读者我要写书评

暂无评论

EFaR 2023: Efficient Face Recognition Competition

EFaR 2023: Efficient Face Recognition Competition

引用

IEEE International Joint Conference on Biometrics (IJCB)

作者： Jan Niklas Kolf Fadi Boutros Jurek Elliesen Markus Theuerkauf Naser Damer Mohamad Alansari Oussama Abdul Hay Sara Alansari Sajid Javed Naoufel Werghi Klemen Grm Vitomir Štruc Fernando Alonso-Fernandez Kevin Hernandez Diaz Josef Bigun Anjith George Christophe Ecabert Hatef Otroshi Shahreza Ketan Kotwal Sébastien Marcel Iurii Medvedev Bo Jin Diogo Nunes Ahmad Hassanpour Pankaj Khatiwada Aafan Ahmad Toor Bian Yang Fraunhofer Institute for Computer Graphics Research IGD Germany TU Darmstadt Germany Department of Electrical and Computer Engineering Khalifa University Abu Dhabi United Arab Emirates Laboratory for Machine Intelligence Faculty of Electrical Engineering University of Ljubljana Slovenia Halmstad University Sweden Idiap Research Institute Martigny Switzerland École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Université de Lausanne (UNIL) Lausanne Switzerland Institute of Systems and Robotics University of Coimbra Coimbra Portugal Department of Information Security and Communication Technology eHealth and Welfare Security Group Norwegian University of Science and Technology Norway

This paper presents the summary of the Efficient Face Recognition Competition (EFaR) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition received 17 submissions from 6 different teams. To drive further development of efficient face recognition models, the submitted solutions are ranked based on a weighted score of the achieved verification accuracies on a diverse set of benchmarks, as well as the deployability given by the number of floating-point operations and model size. The evaluation of submissions is extended to bias, cross-quality, and large-scale recognition benchmarks. Overall, the paper gives an overview of the achieved performance values of the submitted solutions as well as a diverse set of baselines. The submitted solutions use small, efficient network architectures to reduce the computational cost, some solutions apply model quantization. An outlook on possible techniques that are underrepresented in current solutions is given as well.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Accurate grid keypoint learning for efficient video prediction

arXiv

引用

arXiv 2021年

作者： Gao, Xiaojie Jin, Yueming Dou, Qi Fu, Chi-Wing Heng, Pheng-Ann The Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong The CUHK T Stone Robotics Institute Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China

Video prediction methods generally consume substantial computing resources in training and deployment, among which keypoint-based approaches show promising improvement in efficiency by simplifying dense image prediction to light keypoint prediction. However, keypoint locations are often modeled only as continuous coordinates, so noise from semantically insignificant deviations in videos easily disrupt learning stability, leading to inaccurate keypoint modeling. In this paper, we design a new grid keypoint learning framework, aiming at a robust and explainable intermediate keypoint representation for long-term efficient video prediction. We have two major technical contributions. First, we detect keypoints by jumping among candidate locations in our raised grid space and formulate a condensation loss to encourage meaningful keypoints with strong representative capability. Second, we introduce a 2D binary map to represent the detected grid keypoints and then suggest propagating keypoint locations with stochasticity by selecting entries in the discrete grid space, thus preserving the spatial structure of keypoints in the long-term horizon for better future frame generation. Extensive experiments verify that our method outperforms the state-of-the-art stochastic video prediction methods while saves more than 98% of computing resources. We also demonstrate our method on a robotic-assisted surgery dataset with promising results. Our code is available at https://***/ xjgaocs/Grid-Keypoint-Learning. Copyright © 2021, The Authors. All rights reserved.

关键词： Location

来源：评论

学校读者我要写书评

暂无评论

Enhanced cooperative single-range underwater navigation based on optimal trajectories

引用

IFAC-PapersOnLine 2020年第2期53卷 14668-14673页

作者： Santiago Rúa Naveen Crasta Rafael E. Vásquez Antonio M. Pascoal Universidad Pontificia Bolivariana Circular 1 # 70-01 School of Engineering 050031 Medellín Colombia Universidad Nacional Abierta y a Distancia Carrera 45 # 55-19 Escuela de ciencias básicas e ingeniería Medellín Colombia Laboratory of Robotics and Systems in Engineering and Science (LARSyS) IST/University of Lisbon Av. Rovisco Pais 1 1049-001 Lisbon Portugal

This work addresses the observability analysis for a cooperative range-based navigation system based on the optimization of an index. A nonlinear model is first defined in order to describe the motion of the vehicle and a mobile beacon. Then, the Fisher Information Matrix is introduced to explain how it is related with the observability problem. A unconstrained optimization problem is formulated in order to find the best sequence of actions for the beacon to ensure observability in the system; the unconstrained problem does not take into account physical limitation of the vehicle and beacon. Then, four different scenarios are solved using different constraints; we show that, when the beacon is rotating with variable angular velocity we get a better strategy than rotating with constant velocity, despite that in both scenarios the system is observable. Finally, we show that increasing the energy provided to rotate the beacon does not improve further the observability of the system. These results are important from a theoretical and practical point of view, since they represent a strategy to plan the motion of the beacon to guarantee observability in the system.

关键词： Marine system navigation guidance control Acoustic-Based Networked Control Navigation Cooperative control

来源：评论

学校读者我要写书评

暂无评论

Development and Evaluation of a Robotic System for Safe Cardiac Sheath Delivery

引用

IEEE Transactions on Biomedical engineering 2025年 PP卷 PP页

作者： Wang, Weizhao Saija, Carlo Xu, Zhouyang Zeidan, Aya Wilcox, Joshua Patterson, Tiffany Redwood, Simon Wang, Shuangyi Rhode, Kawal Housden, Richard King's College London School of Biomedical Engineering and Imaging Sciences LondonWC2R 2LS United Kingdom Guy's and St Thomas' NHS Foundation Trust Cardiovascular Department LondonSE1 7EH United Kingdom King's College London School of Cardiovascular Medicine and Sciences LondonSE1 7EH United Kingdom Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing101408 China Chinese Academy of Sciences Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation Hong Kong

Objective: This study aimed to develop and evaluate a 3-degree-of-freedom (DoF) robotic system for the safe delivery of cardiac sheaths through challenging anatomical structures, including the fossa ovalis and pathways with tight curves. Methods: The robot and its kinematic model were built on a previously proposed single-DoF actuation module and bending model. A sheath delivery strategy (SDS) was developed, combining two control methods: tip position control to approach an optimal entry point and point-constrained control to maintain consistent navigation through this point, minimizing tissue contact. Technical performance was evaluated through trajectory-following and point-crossing tests, followed by feasibility experiments in a simulated scenario. Trials were conducted by three cardiologists using a validated phantom model under fluoroscopic guidance, comparing SDS with joint control (JC) and manual control (MC). Results: Average root mean square errors were 2.10 mm for tip position control and 1.86 mm for point-constrained control. SDS outperformed MC with significantly shorter trajectory lengths and lower root mean square jerk. Compared to JC, SDS reduced sheath-induced movements (an indirect measure of force) and increased retraction success rates at the fossa ovalis. Conclusion: The proposed robotic system reduced tissue wall contact compared to JC and provided smoother, more controlled operations than MC, ensuring safer and more effective delivery through confined pathways. Significance: This work contributes to advancing robotic-assisted cardiac sheath delivery, providing a reliable and safer method for navigating challenging anatomical structures. © 2025 IEEE Computer Society. All rights reserved.

关键词： Medical robotics

来源：评论

学校读者我要写书评

暂无评论

Bayesian deep multi-instance learning for student performance prediction based on campus big data

引用

Neurocomputing 2025年 647卷

作者： Huang, Jiayang Yang, Keyi Wang, Quan Yang, Pengfei Ruan, Ziling Wang, Jiaxi Zhang, Zhi-Qiang School of Computer Science and Technology Xidian University Xi'an710126 China The Key Laboratory of Smart Human-Computer Interaction and Wearable Technology of Shaanxi Province Xi'an710126 China School of Electronic and Electrical Engineering Institute of Robotics Autonomous Systems and Sensing University of Leeds Leeds United Kingdom

Problem: Predicting student performance using campus big data and deep learning methods has emerged as a promising alternative to traditional psychological assessments, which are often delayed and subjective. However, existing deep learning approaches face significant challenges, including the sparsity of campus big data and susceptibility to overfitting. Objective: To address these issues, this study aims to develop a robust and effective framework for predicting student performance by overcoming data sparsity and overfitting problems. Method: We propose a novel Bayesian Deep Multi-Instance Learning (Bay-DeepMIL) framework. The method integrates multi-instance learning (MIL) to handle data sparsity and incorporates a Bayesian framework to treat network parameters as probabilistic distributions, enhancing robustness and mitigating overfitting. Additionally, a Bayesian multi-head attention mechanism is introduced to dynamically assign importance to different instances, improving the extraction of key information from multi-instance data. Results: Extensive experiments demonstrate that Bay-DeepMIL outperforms state-of-the-art methods in prediction accuracy. The framework also provides uncertainty estimates for each prediction, offering valuable confidence measures and decision support for educational stakeholders. Conclusion: The proposed Bay-DeepMIL framework not only advances the technical capabilities of predictive models but also provides practical tools for enhancing educational decision-making. This study underscores the effectiveness of integrating Bayesian inference with multi-instance learning to address core challenges such as data sparsity and model overfitting in student performance prediction. © 2025 Elsevier B.V.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

An Accelerated Iterative Learning Control Approach for X-Y precision plane motion stage

An Accelerated Iterative Learning Control Approach for X-Y p...

引用

作者： Tao Zhang Hongyu Yan Danping Jia Hualiang Zhang Bingjie Zhao Xu Lu Yang Liu Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Electrical Engineering Dalian University of Technology School of Artificial Intelligence Shenyang University of Technology School of Information Science and Engineering Shenyang University of Technology

X-Y precision plane motion stage is widely used in precision motion control fields such as lithography machine workpiece stage,CNC machine tool,Laser measuring system,etc.,which requires high accuracy of the position *** X-Y precision plane motion stage uses two permanent magnet linear synchronous motors(PMLSM) as drivers to drive the motion table to perform XY two-degree-of-freedom *** open-closedloop PD-type iterative learning controller(ILC) approach based on accelerated convergence was proposed to improve trajectory tracking performance of *** interval was changed by real-time correction of the exponential gain matrix in the interval to accelerate the convergence *** to the λ norm,the monotone convergence of the proportion differentiation(PD) was developed for the *** controller consists of two terms:a PID controller which enhances robustness to disturbances and system parameter variability and an ILC which generally improves the performance in the repetitive tasks by using the information from previous *** experimental results show that tracking precision and convergence speed of PMLSM can be effectively improved by the scheme.

关键词： X-Y precision plane motion stage Iterative learning control tracking precision convergence rate

来源：评论

学校读者我要写书评

暂无评论

Low SNR communications using a double Wiener filter in an upwelling environment

引用

Proceedings of Meetings on Acoustics 2021年第1期44卷

作者： Fabio B. Louza Sergio Manuel Jesus 1Laboratory of Robotics and Engineering Systems (LarSys) University of Algarve Faro Faro 8005 139 PORTUGAL fblouza@ualg.pt sjesus@ualg.pt

This paper presents a double Wiener filter approach for low SNR communications. Low power superim-posed training bitstreams are transmitted and recorded on a four-hydrophone pyramidal array. The method uses a minimum mean square error (MSE) Wiener filter for channel equalization. To explore temporal diversity, a fast Hadamard transform estimates the channel impulse responses for synchronization of the filtered bitstreams. Coherent averaging of time-aligned signals results in an error-corrected bitstream. A second Wiener filter is then applied over the averaged sequence to eliminate residual intersymbol interference. After removing the probe interference, the original message is recovered. To prove the concept, a small subset of data collected during the experiment BioCom’19 was used. The short-range experiment was performed in an upwelling shallow-water site, in Cabo Frio Island bay (Brazil), a challenging environment for communications due to the rapid ocean temperature stratification. Despite BER fluctuation, the proposed scheme proved robust, dealing with these short time scale signal fluctuations and high noise levels that hamper efforts to recover the message. The four channels were processed independently. Compared to a previous method based on a single Wiener, the double Wiener filter approach achieved better performance, providing an average MSE gain up to 2.8 dB.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Online Collision Avoidance for Human-Robot Collaborative Interaction Concerning Safety and Efficiency

Online Collision Avoidance for Human-Robot Collaborative Int...

引用

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

作者： Guoliang Liu Haoyang He Guohui Tian Jianhua Zhang Ze Ji School of Control Science and Engineering Shandong University Jinan China School of Mechanical Engineering Hebei University of Technology Tianjin China Robotics and Autonomous Systems Laboratory School of Engineering Cardiff University Cardiff UK

ISBN: (数字)9781728167947

ISBN: (纸本)9781728167954

With the development of robot technology and the arrival of industry 4.0 era, society pays more attention to collaboration and interaction between human and robots. However, safety is still main concern in the development of human-robot collaboration. In this paper, a novel real-time collision avoidance approach for manipulator is proposed by considering the motion status of the human, which includes the relative minimum distance and velocity (both magnitude and direction) between the robot and the human. The distance and velocity of the human hand are first estimated online using a vision sensor, and then defined as danger factors in the potential function of the potential field. The novel potential function proposed in this paper considers not only the safety problem, but also the efficient problem, i.e., the manipulator can make smart control decision to avoid the collision according to the relative velocity in case of the cross over. To overcome the local minimum problem and choose a best motion direction, we propose a motion sampling mechanism for motion planning. For each sample, the robot calculates the potential function to evaluate the safety and efficiency, and chooses a direction which is best for avoidance. We finally demonstrate our idea on a real manipulator platform in a human co-existance environment.

关键词： Collision avoidance Force Manipulators Robot kinematics Safety Collaboration

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：