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2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)最新文献

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Asynchronous steady-state visual evoked potential brain-computer interface application: True and false positive rate comparison between with and without eye-tracking switch paradigms 非同步稳态视觉诱发电位脑机接口应用:带与不带眼动追踪切换范式的真阳性率和假阳性率比较
Pub Date : 2021-07-15 DOI: 10.1109/RCAR52367.2021.9517381
Jun Xie, Huanqing Zhang, Yi Liu, Peng Fang, Hongwei Yu, Liushi He, Guanglin Li, Song Yuan, Guanghua Xu, Min Li
Due to the bypass of muscle activity or peripheral nerve control, brain-computer interface (BCI) technique has advantages in different fields such as medical field for the rehabilitation of paralyzed patients. Steady-state visual evoked potential (SSVEP) has been widely adopted in BCI applications. SSVEP based BCIs have the advantages of high information transfer rate, less or no need of training, and strong anti-interference, which could be used in the more natural asynchronous BCI application with control of the users rather than the operant system of the synchronous mode. In order to solve the problem of high false positive rate (FPR) in common asynchronous SSVEP BCI applications, this paper proposed an eye-tracking switch based BCI paradigm to reduce the FPR and to improve the performance of the asynchronous BCI system. In the proposed paradigm, the fixation point position instead of EEG signal is used to determine whether the system is in idle state. Experimental results showed that when eye-tracking switch was applied in the asynchronous SSVEP BCI, the FPR was reduced to less than 10% and the recognition accuracy (i.e., the true positive rate, TPR) can also be improved to a certain extent, which proved the applicability of the eye-tracking switch in asynchronous BCI applications.
脑机接口(brain-computer interface, BCI)技术由于绕过了肌肉活动或周围神经的控制,在麻痹患者的康复治疗等多个领域都具有优势。稳态视觉诱发电位(SSVEP)在脑机接口中得到了广泛的应用。基于SSVEP的BCI具有信息传输率高、无需训练或较少训练、抗干扰性强等优点,可用于更自然的异步BCI应用,由用户控制而非同步模式的操作系统。为了解决常见的异步SSVEP BCI应用中存在的高误报率问题,本文提出了一种基于眼动追踪开关的BCI模式,以降低误报率,提高异步BCI系统的性能。在该范式中,使用注视点位置而不是脑电信号来判断系统是否处于空闲状态。实验结果表明,将眼动追踪开关应用于异步SSVEP脑接口时,FPR降低到10%以下,识别准确率(即真阳性率,TPR)也有一定程度的提高,证明了眼动追踪开关在异步脑接口应用中的适用性。
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引用次数: 2
UCAS-Hand: An Underactuated Powered Hand Exoskeleton for Assisting Grasping Task UCAS-Hand:辅助抓取任务的欠驱动动力手外骨骼
Pub Date : 2021-07-15 DOI: 10.1109/RCAR52367.2021.9517383
Houcheng Li, Long Cheng, Zhengwei Li, Guotao Li
This paper presents a novel underactuated coupled adaptive hand exoskeleton, called UCAS-Hand, which is designed to assist users with weak muscle strength to complete the operation of daily living items. In mechanical design, the proposed UCAS-Hand considers the human-robot kinematic compatibility, grasping adaptability for different objects, portability with motors attached to the hand, force transfer efficiency with applying normal force to the finger phalanges, and passive backdrivability with low gear reduction ratio motor. The UCAS-Hand can realize finger underactuated motions such as flexion/extension and thumb underactuated motions such as flexion/extension, abduction/adduction, and thumb opposability. To minimize the backlashes of bevel gear transmission, a spherical four-bar mechanism and a spherical seven-bar mechanism are designed for the index finger and thumb mechanisms, respectively. Finally, the experiment is implemented to reveal the characteristics of the UCAS-Hand.
本文提出了一种新型的欠驱动耦合自适应手外骨骼UCAS-Hand,旨在帮助肌肉力量较弱的用户完成日常生活物品的操作。在机械设计方面,UCAS-Hand考虑了人-机器人的运动学兼容性、对不同物体的抓取适应性、附着在手上的电机的便携性、向指骨施加法向力的力传递效率以及低齿轮减速比电机的被动反驱动性。UCAS-Hand可以实现手指屈伸等欠驱动运动和拇指屈伸、外展、内收、拇指对生等欠驱动运动。为减小锥齿轮传动的齿隙,对食指机构和拇指机构分别设计了球面四杆机构和球面七杆机构。最后进行了实验,揭示了UCAS-Hand的特点。
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引用次数: 4
Deep Convolutional Neural Network Transfer Learning Optimization Based on Visual Interpretation 基于视觉解释的深度卷积神经网络迁移学习优化
Pub Date : 2021-07-15 DOI: 10.1109/RCAR52367.2021.9517519
Yibo Xu, Jiongming Su, Fengtao Xiang, Ce Guo, Haoran Ren, Huimin Lu
In image classification tasks, the training of deep convolutional neural networks generally requires a large amount of data, and due to the constraints of environment, resources and time, it is of great practical importance to use fewer training samples to obtain a higher recognition rate in the shortest possible time. A deep convolutional neural network transfer learning optimization method based on visual interpretation is proposed for a specific image classification task. Firstly, we use class activation mapping visualization as a visual interpretation, output the class activation heat map of the validation set images, and analyze the reasons for misrecognition of the images. Secondly, we introduce “feedback” by pre-recognizing and visualizing the optimized dataset with the model trained on the original dataset, selecting the images that have a greater impact on improving the recognition rate, and maximizing the impact of the optimized images on the original model. Finally, the model is retrained on the optimized training set. The experimental results show that this method can effectively improve the recognition rate of the transfer learning model for image classification.
在图像分类任务中,深度卷积神经网络的训练通常需要大量的数据,由于环境、资源和时间的限制,使用更少的训练样本以在尽可能短的时间内获得更高的识别率具有重要的现实意义。针对特定的图像分类任务,提出了一种基于视觉解译的深度卷积神经网络迁移学习优化方法。首先,我们使用类激活映射可视化作为视觉解释,输出验证集图像的类激活热图,并分析图像误认的原因。其次,我们引入“反馈”,利用在原始数据集上训练的模型对优化后的数据集进行预识别和可视化,选择对提高识别率影响较大的图像,使优化后的图像对原始模型的影响最大化。最后,在优化后的训练集上对模型进行再训练。实验结果表明,该方法可以有效提高图像分类迁移学习模型的识别率。
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引用次数: 0
Lower Limb Exoskeleton Design Based on Knee Joint Assistance 基于膝关节辅助的下肢外骨骼设计
Pub Date : 2021-07-15 DOI: 10.1109/RCAR52367.2021.9517623
Peng Jiang, Ye Wang, Tianqi Shao, Changsoo Han, Lin Wang, Guanglin Li
Human mobility is vital to daily activities and can be directly linked to the living quality. This is an especially severe problem for the patients with walking dysfunction. There is a great need to develop viable mobility solutions to assist individuals and improve their living quality. Wearable gait-assisted exoskeletons are an effective solution to this growing problem. This paper presents a passive lower limb exoskeleton which can work on hip and knee joints for gait assistance. The hip exoskeleton is designed based on specially shaped torsion springs that work with cams for gravity compensation of the human thigh, converting the torque of the built-in torsion springs into a balanced torque of the hip and knee joints in the later stages of the gait stance phase to overcome the effects of gravity. The knee exoskeleton is designed with reference to a new spring-loaded gravity balanced structure used to carry single-degree-of-freedom rotational loads. When worn, it can help the lower leg to push out during gait swing state to compensate for falls due to the lack of lower leg swing. After the exoskeleton prototype was completed, 3D motion capture experiments were performed to obtain gait parameters. Finally, the effectiveness of the exoskeleton in assisting patients with walking dysfunction was verified using OpenSim simulation software.
人类的流动性对日常活动至关重要,可以直接关系到生活质量。对于行走功能障碍的患者来说,这是一个特别严重的问题。我们非常需要开发可行的移动解决方案来帮助个人并提高他们的生活质量。可穿戴步态辅助外骨骼是解决这一日益严重的问题的有效方法。本文介绍了一种能在髋关节和膝关节上辅助行走的被动式下肢外骨骼。髋关节外骨骼的设计基于特殊形状的扭转弹簧,配合凸轮对人体大腿进行重力补偿,将内置扭转弹簧的扭矩在步态站立阶段后期转化为髋关节和膝关节的平衡扭矩,以克服重力的影响。膝关节外骨骼的设计参考了一种新的弹簧负载重力平衡结构,用于承载单自由度旋转载荷。当佩戴时,它可以帮助在步态摇摆状态下的小腿推出,以补偿由于下肢摆动不足而导致的跌倒。外骨骼原型完成后,进行三维运动捕捉实验,获取步态参数。最后,使用OpenSim仿真软件验证外骨骼辅助行走功能障碍患者的有效性。
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引用次数: 2
Automatic Venous Segmentation in Venipuncture Robot Using Deep Learning 基于深度学习的静脉穿刺机器人自动静脉分割
Pub Date : 2021-07-15 DOI: 10.1109/RCAR52367.2021.9517605
Tianbao He, Chuangqiang Guo, Li-Gen Jiang, Hansong Liu
Vein identification plays a pivotal role in realizing automatic venipuncture, and it has become a difficulty to segment the veins efficiently as well as accurately in the research of full-automatic venipuncture robots. Most studies in the field of vein segmentation have only focused on traditional image processing methods, the segmentation accuracy and generalization performance of which are poor. Therefore, we propose an automatic image segmentation algorithm using the U-Net model with the attention mechanism (Attention-UNet) which can suppress unnecessary features. Besides, the encoder-decoder and the skip-connection structure are applied for multi-scale feature recognition so that the segmentation accuracy can be improved. Meanwhile, on digital arm images for the vein segmentation data set (DAIVS data set), the newly-built human forearm veins data set, the effectiveness of the proposed method in vein segmentation is verified. Finally, we conduct experiments to acquire and process venous images with the Attention-UNet in real-time on the venipuncture robot. These results indicate that machine vision has better performance in complex visual tasks and can be translated into clinical application.
静脉识别是实现全自动静脉穿刺的关键,如何高效、准确地分割静脉已成为全自动静脉穿刺机器人研究中的难点。静脉分割领域的研究大多集中在传统的图像处理方法上,其分割精度和泛化性能较差。因此,我们提出了一种利用U-Net模型和注意机制(attention - unet)的自动图像分割算法,该算法可以抑制不必要的特征。此外,采用编解码器和跳接结构进行多尺度特征识别,提高了分割精度。同时,在基于数字臂图像的静脉分割数据集(DAIVS数据集),即新建立的人体前臂静脉数据集上,验证了所提方法在静脉分割方面的有效性。最后,我们在静脉穿刺机器人上进行了利用Attention-UNet实时获取和处理静脉图像的实验。这些结果表明,机器视觉在复杂的视觉任务中有更好的表现,可以转化为临床应用。
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引用次数: 5
Research on Graph-Based SLAM for UVC Disinfection Robot UVC消毒机器人基于图的SLAM研究
Pub Date : 2021-07-15 DOI: 10.1109/RCAR52367.2021.9517506
Xuan Tan, Hui Zhang, Xidong Zhou, Hang Zhong, Li Liu
With the emergence of the COVID-19 pandemic, more and more non-contact mobile disinfection robots have appeared in the medical field, which have made great contributions to the fight against the epidemic. Aiming at the problems of single disinfection method, single application scenario, low degree of intelligence and lack of autonomous mobile disinfection in existing disinfection robots, this paper proposes and designs a disinfection and epidemic prevention intelligent robot called Aimi-Robot UVC, which is based on graph-optimized slam algorithm to complete the localization and map creation functions of the robot in the unknown environment. After testing in the isolated single ward of the hospital, the realtime localization accuracy reaches 0.04m, which provides high-precision and high-reliability localization for the disinfection robot in the hospital scene and has great practical significance for the application of intelligent disinfection robots in epidemic prevention and control.
随着COVID-19大流行的出现,越来越多的非接触式移动消毒机器人出现在医疗领域,为抗击疫情做出了巨大贡献。针对现有消毒机器人消毒方式单一、应用场景单一、智能化程度低、缺乏自主移动消毒等问题,本文提出并设计了一种消毒防疫智能机器人Aimi-Robot UVC,该机器人基于图优化slam算法完成机器人在未知环境中的定位和地图创建功能。经医院隔离单病房测试,实时定位精度达到0.04m,为消毒机器人在医院场景下提供了高精度、高可靠性的定位,对于智能消毒机器人在疫情防控中的应用具有重要的现实意义。
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引用次数: 1
Design of a Battery Carrying Barge for Enhancing Autonomous Sailboat's Endurance Capacity 提高自主帆船续航能力的载电池驳船设计
Pub Date : 2021-07-15 DOI: 10.1109/RCAR52367.2021.9517585
Cheng Liang, Rong-Shyang Ou, Bairun Lin, Xiaoqiang Ji, R. Cheung, Huihuan Qian
This paper provides a new scheme to improve the sailing distance and working time of the autonomous sailboat. The main part of the article introduces a new design of sail tug which can carry more batteries that provides more power for control system, enabling sailboats to sail longer in both time and distance. The modified sail tug was tested at an advanced test site equipped with high precision infrared motion capture system. The air curtain machines in test site can produce constant wind field, to drive sailboat steadily. Comparative experiments have been conducted to show the advantages of self-supporting ability of autonomous sail tug over ordinary autonomous sailboat.
本文提出了一种提高自主帆船航行距离和工作时间的新方案。文章的主要部分介绍了一种新型的风帆拖船,它可以携带更多的电池,为控制系统提供更多的动力,使帆船可以航行更长时间和更远的距离。改进后的风帆拖船在配备高精度红外运动捕捉系统的先进试验场进行了测试。试验场的气幕机能产生恒定的风场,稳定地驱动帆船。通过对比实验,证明了自主帆拖船的自支撑能力优于普通自主帆船。
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引用次数: 1
Saturated PD with sliding mode control method for 4-DOF tower crane systems 四自由度塔吊系统饱和PD滑模控制方法
Pub Date : 2021-07-15 DOI: 10.1109/RCAR52367.2021.9517576
Weijie Huang, Menghua Zhang, Fuqiang Sun, Jin Zhang, Changhui Ma, Zaixing Zhu
A new saturated PD with sliding mode control method (or saturated PD-SMC in short) was designed by this paper for 4-DOF tower crane systems. The design was based on uncertain dynamics, external disturbances, and control input constraints. By means of jib/trolly-position/velocity and payload swing-feedback with limited control inputs, the designed control method, which is model free, can achieve accurate positioning and rapid swing suppression and elimination. Besides, by adopting the advantages of simple structure, the designed control method can be easily realized in the applications of the PD control, compared with existing control methods. This method also has strong robustness of the SMC method regarding to model uncertainties and external disturbances. As a result, this design avoids the requirements of accurate model knowledge concerned with the SMC method, as well as rapid payload swing reduction of the swing suppression control. Rigorous Lyapunov-based analysis is employed in order to ensure the stability of the controlled system. According to the information this paper has, this is by far the first model-free control method without any linearization operations for tower crane systems with uncertain dynamics, external disturbances, and control input constraints. The superior control performance and strong robustness of the designed control method was validated by a number of experimental results.
针对四自由度塔吊系统,设计了一种新的饱和PD滑模控制方法(简称饱和PD- smc)。该设计基于不确定动力学、外部干扰和控制输入约束。所设计的控制方法通过臂架/小车-位置/速度和载荷-摆动反馈,在有限的控制输入下,实现了不受模型约束的精确定位和快速的摆动抑制与消除。此外,与现有的控制方法相比,所设计的控制方法具有结构简单的优点,易于在PD控制的应用中实现。该方法对模型不确定性和外界干扰具有SMC方法较强的鲁棒性。因此,该设计避免了SMC方法对精确模型知识的要求,也避免了摆动抑制控制对快速减小载荷摆动的要求。为了保证被控系统的稳定性,采用了严格的李雅普诺夫分析方法。根据本文掌握的信息,这是迄今为止第一个针对具有不确定动力学、外部干扰和控制输入约束的塔机系统,不进行任何线性化操作的无模型控制方法。大量的实验结果验证了所设计的控制方法具有优良的控制性能和较强的鲁棒性。
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引用次数: 0
Measuring Method of Involute Profile Error Based on Machine Vision 基于机器视觉的渐开线轮廓误差测量方法
Pub Date : 2021-07-15 DOI: 10.1109/RCAR52367.2021.9517394
Zhi Shan, Meng Xin, Wu Di
To meet the requirement of fast on-line measurement of tooth profile error of medium and small modulus spur gear in automotive industry, a new algorithm for measuring involute tooth profile error based on machine vision with gear local image is proposed. The gray image of gear is acquired by gear visual measuring instrument, and the pixel information of transition zone of gear profile edge is extracted by Gauss filtering and threshold segmentation. The center of gear positioning is determined by fitting the circle based on fixed radius least square method with constraints. By extracting sub-pixel edge feature points of gear profile, a visual measurement model is constructed, and the measurement parameters, total deviation of involute profile and shape deviation of gear profile are calculated. The total tooth profile deviation of the tested gear measured by the method in this paper has reached 5-level accuracy. Compared with the result measured by M&M3525 NC Gear Measuring Center, the maximum measurement error of the total tooth profile deviation measured by the visual measuring instrument is $1mu mathrm{m}$, the maximum error of average measurement is less than $1mu mathrm{m}$. Experiments show that the measurement accuracy of the visual measurement system is equal to that of the gear measuring center, and it can meet the requirements of measuring the total tooth profile deviation of 5-level precision gear.
针对汽车行业中小模数直齿轮齿形误差在线快速测量的需求,提出了一种基于齿轮局部图像的机器视觉渐开线齿形误差在线测量算法。通过齿轮视觉测量仪获取齿轮的灰度图像,并通过高斯滤波和阈值分割提取齿轮轮廓边缘过渡区域的像素信息。采用带约束的固定半径最小二乘法拟合圆确定齿轮定位中心。通过提取齿轮轮廓的亚像素边缘特征点,构建视觉测量模型,计算出齿轮渐开线轮廓的测量参数、总偏差和形状偏差。用本文方法测得的被试齿轮总齿形偏差达到5级精度。与M&M3525数控齿轮测量中心测量结果相比,视觉测量仪测量的总齿形偏差的最大测量误差为$1mu mathrm{m}$,平均测量的最大误差小于$1mu mathrm{m}$。实验表明,视觉测量系统的测量精度与齿轮测量中心的测量精度相当,能够满足5级精密齿轮总齿廓偏差的测量要求。
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引用次数: 1
Optimization Design of Configuration, Structure and Drive Train Synthesis for Serial Robotic Arms 串联机械臂构型、结构及传动系综合优化设计
Pub Date : 2021-07-15 DOI: 10.1109/RCAR52367.2021.9517620
Jingchen Li, Jia Liu, Hongyu Ding, Yisen Hu, Jianxin Pang
There have been various designs of collaborative robotic arms currently, and they have different advantages and disadvantages. Here, we propose a new method, by which one can optimally obtain a basic design of configuration, structure and drive train synthesis, based on the desired functions and performances. Specifically, we parameterize the configuration and drive train of robotic arms, simply assume the links as hollow cylinders, and parameterize the structural dimensions. These design parameters are linked to the mass, actuator selection, structural stiffness and workspace by a co-simulation model. Through using the optimization algorithm, a relatively optimal design for the desired functions and performances can be obtained. A design example demonstrates the application of the proposed approach in the optimal design of a lightweight six-degree-of-freedom robotic arm with the maximized workspace. Finally, we further analyze the workspace and illustrate the comparison between the optimal design and typical collaborative robotic arms. Our approach can be extended further for other particular design requirements.
目前,协作机械臂的设计多种多样,各有优缺点。在此,我们提出了一种新的方法,通过该方法可以根据期望的功能和性能,最优地获得配置,结构和传动系综合的基本设计。具体来说,我们对机械臂的构型和传动系进行了参数化,将连杆简单地假设为空心圆柱体,并对结构尺寸进行了参数化。通过联合仿真模型将这些设计参数与质量、驱动器选择、结构刚度和工作空间联系起来。通过使用优化算法,可以获得所需功能和性能的相对优化设计。设计实例验证了该方法在六自由度轻量化机械臂工作空间最大化优化设计中的应用。最后,对其工作空间进行了分析,并与典型的协同机械臂进行了比较。我们的方法可以进一步扩展到其他特定的设计要求。
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引用次数: 0
期刊
2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)
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