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An IoT Peripheral Sensor Integration to Assist Elderly Drivers 物联网外围传感器集成助力老年司机
Pub Date : 2018-11-01 DOI: 10.1109/CACS.2018.8606778
Tung-Lin Hsieh, Bo-Chien Zheng, Fudi Lin, Chan-Yun Yang
Due to gradually aging lifespan of elders in human society, a lot of new demands have been brought to facilitate their daily life. The elder driving assistive technology is one of the demands. The elder driving assistive technology is not only beneficial in increasing safety of the driver and the people around his vehicle, but also advantageous in decreasing the public cost of society safety. Thus, the study set a goal to pursue a driving assistive apparatus which can respond immediately to the elder a helpful warning or arrestment during a potential accident crisis. The apparatus dynamically monitors the vehicle movement and it corresponding diver operation mode, and detects the irregularity between the driver and his vehicle. Sensory devices for detecting the behaviors were installed in the vehicle, including imaging camera, inertial measurement unit, Lidar scanner, steering wheel angle sensor, depression sensors on accelerator pedal and brake pedal to form a sensory network for collecting the signals for irregularity identification. Together with an array of ultrasonic sensors installed surrounding the vehicle to scout the suspicious objects around, a sensor harness was integrated and formed to evaluate the irregularity level of the danger. Once the risk level is significant enough, the danger classification will be delivered to the processing center to activate a corresponding ensemble of sensory feedbacks to remind adaptively the driver. The signal interface which has been designed attempts to resist automatically or even stops immediately an inaccurate operation of the driver which might cease an accident disaster.
随着人类社会老年人寿命的逐渐老龄化,为老年人的日常生活带来了许多新的需求。老年人驾驶辅助技术是需求之一。老年驾驶辅助技术不仅有利于提高驾驶员和车辆周围人员的安全,而且有利于降低社会安全的公共成本。因此,本研究的目标是开发一种驾驶辅助装置,在潜在的事故危机中,它可以立即对老年人发出有益的警告或逮捕。该装置动态监测车辆运动及其对应的潜水员操作模式,并检测驾驶员与车辆之间的不正常状态。在车内安装成像摄像头、惯性测量单元、激光雷达扫描仪、方向盘角度传感器、加速踏板和刹车踏板上的俯角传感器等感知装置,形成一个感知网络,收集信号进行违规识别。与安装在车辆周围的超声波传感器阵列一起,用于侦察周围的可疑物体,集成并形成传感器线束,以评估危险的不规则程度。一旦危险级别足够显著,危险分类将被传递到处理中心,以激活相应的感官反馈集合,自适应地提醒驾驶员。所设计的信号接口试图自动抵制甚至立即停止可能停止事故灾难的驾驶员的不准确操作。
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引用次数: 1
An eight degree-of-freedom robotic endoscope holder 一个八自由度的机器人内窥镜支架
Pub Date : 2018-11-01 DOI: 10.1109/CACS.2018.8606736
Sung-Chi Chiang, Yang-Cheng Huang, Kuan Shen, J. Yen
Laparoscopic minimally invasive surgery has been extensively used in the medical field recently years, due to the small wounds, shorter recovery time and less suffering of patients. Combined with robotic technology, laparoscopic minimally invasive surgical robots can obtain higher surgical accuracy. The main purpose of this paper is to design a force controller to achieve the angle control of an 8-DOF laparoscopic minimally invasive surgical robot.First, we introduce the design of a motor driven endoscope mechanism and deduces the kinematics and dynamic model of the manipulator arm and endoscope. Under the constraint of the celiac incision, a null-space matrix relative to the task space would be derived. Perspective space of the endoscope camera would be analyzed and a null-space impedance control architecture would be constructed so that the endoscope-holding manipulator can provide images with different perspectives in the situation where the target object does move in the picture and does not generate lateral force on the incision.
腹腔镜微创手术因其创伤小、恢复时间短、患者痛苦小等优点,近年来在医学领域得到了广泛的应用。结合机器人技术,腹腔镜微创手术机器人可以获得更高的手术精度。本文的主要目的是设计一种力控制器来实现8自由度腹腔镜微创手术机器人的角度控制。首先,介绍了电机驱动内窥镜机构的设计,推导了机械臂和内窥镜的运动学和动力学模型。在腹腔切口的约束下,导出一个相对于任务空间的零空间矩阵。对内窥镜摄像机的视角空间进行分析,构建零空间阻抗控制体系结构,使持内窥镜机械手在目标物体在画面中运动且不对切口产生侧向力的情况下,能够提供不同视角的图像。
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引用次数: 0
Object Transportation Using Networked Mobile Manipulators without Force/Torque Sensors 无力/扭矩传感器的网络化移动机械手的物体运输
Pub Date : 2018-11-01 DOI: 10.1109/CACS.2018.8606732
Van-Tam Ngo, Yen‐Chen Liu
The use of multiple mobile manipulators (MMs) to perform collaborative object transportation is a promising solution for future industry. However, most existing control laws in this field require sensors to measure interactive force-torque between the transported object and the end-effectors of the robots, which is costly and increasing the system complexity. To overcome this problem, the present study considers the interactive force/torque to be unknown nonlinear functions and estimates them using a wavelet neural network (WNN). In particular, an adaptive-wavelet neural network control law is designed to guarantee trajectory tracking for each robot. Then an output synchronization algorithm is additionally used to coordinate the movement of the network MMs. Stability of the proposed control law is proven theoretically using Lyapunov theorem. Furthermore, the effectiveness of the control law is illustrated by simulations.
使用多移动机械手(mm)进行协同物体运输是未来工业的一个很有前途的解决方案。然而,该领域现有的大多数控制律都要求传感器测量被运输物体与机器人末端执行器之间的相互作用力-扭矩,这不仅成本高,而且增加了系统的复杂性。为了克服这一问题,本研究将相互作用力/扭矩视为未知的非线性函数,并使用小波神经网络(WNN)对其进行估计。特别设计了一种自适应小波神经网络控制律,以保证每个机器人的轨迹跟踪。然后采用输出同步算法对网络mm的运动进行协调。利用李雅普诺夫定理从理论上证明了所提控制律的稳定性。通过仿真验证了控制律的有效性。
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引用次数: 4
Image-based EEG signal processing for driving fatigue prediction 基于图像的脑电信号处理在驾驶疲劳预测中的应用
Pub Date : 2018-11-01 DOI: 10.1109/CACS.2018.8606734
E. Cheng, Ku-Young Young, Chin-Teng Lin
This study proposes a EEG-based prediction system that transform the measured EEG record into an image-liked data for estimating the drowsiness level of drivers. Drowsy driving is one of the main factors to the occurrence of traffic accident. Since drivers themselves may not always immediately recognize that they are in the drowsy state, the risk of traffic accident increases while the driver is in the low vigilance state. In order to address this problem, the estimation of drowsy driving state via brain-computer interfaces (BCI) becomes a major concern in the driving safety field. This study transforms the measured EEG record into a image-liked feature maps, and then passes these feature maps to a Convolutional Neural Network (CNN) to learn the discriminative representations. The proposed drowsiness prediction system is evaluated by leave-one-subject-out cross-validation. The results indicate that our approach provides impressive and robust prediction performance on the EEG dataset without artifact removal process.
本研究提出了一种基于脑电图的预测系统,该系统将测量的脑电图记录转换为类似图像的数据,用于估计驾驶员的困倦程度。疲劳驾驶是导致交通事故发生的主要因素之一。由于驾驶员本身可能并不总是立即意识到自己处于困倦状态,当驾驶员处于低警觉性状态时,发生交通事故的风险就会增加。为了解决这一问题,基于脑机接口(BCI)的疲劳驾驶状态估计成为驾驶安全领域的研究热点。本研究将测量到的脑电图记录转换成类图像特征映射,然后将这些特征映射传递给卷积神经网络(CNN)学习判别表征。提出的嗜睡预测系统通过留一受试者的交叉验证进行评估。结果表明,我们的方法在没有去除伪影的情况下,对EEG数据集提供了令人印象深刻的鲁棒性预测性能。
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引用次数: 11
Traffic Lane Line Classification System by Real-time Image Processing 基于实时图像处理的交通车道线分类系统
Pub Date : 2018-11-01 DOI: 10.1109/CACS.2018.8606775
Huang Chingting, Hu Zhuqi, S. Tateno
The traffic safety has been a major concern in recent years. One of the effective approaches to prevent the traffic accident is to develop advanced driver assistance systems which can alarm driver in dangerous situation. In fact, changing lane or overtaking another vehicle is one of the most dangerous driving behaviors. Therefore, it is important for drivers to recognize current lane line types to take proper actions. However, classification systems proposed so far can only distinguish up to five types of lane lines, such as dashed and solid. Hence, the existing road classification systems are not suitable if there are more types of lane lines on the road. In this paper, an improved method is proposed to classify more lane line types by real-time image processing. In order to increase the detection accuracy of lane line types, the image stitching method is applied to reduce the misjudgment caused by blocked lane lines. A set of features about pixel distribution is utilized in the classifier to distinguish more than five lane line types. Furthermore, the results of experiments which are carried out in real road driving show high accuracy of the proposed classification method under the various situations.
近年来,交通安全一直是人们关注的主要问题。开发先进的驾驶员辅助系统是预防交通事故发生的有效途径之一。事实上,改变车道或超车是最危险的驾驶行为之一。因此,对于驾驶员来说,识别当前的车道线类型以采取适当的行动是很重要的。然而,目前提出的分类系统最多只能区分五种类型的车道线,如虚线和实线。因此,当道路上的车道线种类较多时,现有的道路分类系统就不适用了。本文提出了一种改进的方法,通过实时图像处理来分类更多的车道线类型。为了提高车道线类型的检测精度,采用图像拼接的方法减少车道线被遮挡造成的误判。在分类器中利用一组关于像素分布的特征来区分五种以上的车道线类型。此外,在实际道路驾驶中进行的实验结果表明,所提出的分类方法在各种情况下都具有较高的准确率。
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引用次数: 1
Depth Image-based Distance Measurement for Two-wheeled Robots 基于深度图像的两轮机器人距离测量
Pub Date : 2018-11-01 DOI: 10.1109/CACS.2018.8606747
Jian-Hua Jhou, Yu-Po Lin, Yih-Guang Leu
In this paper, the two-wheeled robot is combined with Kinect sensor to measure obstacle distance. When the two-wheeled robot autonomously balances or moves, the ranging value will be unstable due to the shaking of the two-wheeled robots. This paper uses a smart prediction method to correct the ranging error value in order to increase the accuracy of ranging value and the obstacle avoidance decision. Finally, in order to verify the proposed method, some experiments are performed.
本文将两轮机器人与Kinect传感器相结合来测量障碍物距离。当两轮机器人自主平衡或移动时,由于两轮机器人的晃动,测距值会不稳定。本文采用智能预测方法对测距误差值进行修正,以提高测距值和避障决策的精度。最后,为了验证所提出的方法,进行了一些实验。
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引用次数: 0
Coding optimization for the absolute optical rotary encoder 绝对光学旋转编码器的编码优化
Pub Date : 2018-11-01 DOI: 10.1109/CACS.2018.8606741
Ting-Feng Wang, Yung-Jhe Yan, H. Chiang, T. Chen, M. Ou‐Yang
Precise positioning system is assuming increasing importance. One of Implementation is an optical rotary encoder system which is composed of a fixed light source, a group of photodetectors, and a coding disc. In fact, position resolution is affected with a permutation of coding on the disc. Unstable dc voltage was found from an analog signal transmitted by photoelectric detectors. Setting up a threshold voltage for digital binarization become difficult in this case.In this paper, the limitations, characteristics and operation mode of coding on the disc operation mode arrangement rules of coding on the disc was observed. After collecting the relevant literature, the mathematical sequence named De Bruijn sequence which matches to the arrangement of the above rules and restrictions was found. The desired requirements are summarized and used to filter out the best solution in all solution sets with the designed algorithm. Finally, the characteristics of new and old solutions are compared and discussed.
精确定位系统的重要性日益凸显。其中一种实现方法是光学旋转编码器系统,该系统由固定光源、光电探测器组和编码盘组成。实际上,位置分辨率受光盘上编码排列的影响。从光电探测器发射的模拟信号中发现直流电压不稳定。在这种情况下,设置数字二值化的阈值电压变得困难。本文分析了光盘编码的局限性、特点及操作方式,观察了光盘编码的操作方式及排列规则。通过搜集相关文献,找到了与上述规则和限制的排列方式相匹配的数学序列De Bruijn序列。利用所设计的算法,对期望需求进行汇总,并从所有解集中筛选出最优解。最后,对新旧方案的特点进行了比较和讨论。
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引用次数: 2
Performance Evaluation for a Photovoltaic-Thermal (PVT) Module 光伏-热(PVT)模块的性能评估
Pub Date : 2018-11-01 DOI: 10.1109/CACS.2018.8606742
Jen-Yung Lin, Chia-Chung Hsu, Huan-Liang Tsai
This paper presents the model simulation and experiment measurement for performance evaluation of a novel air-type photovoltaic/thermal (PVT) module. With the encapsulation of solar cells directly on a fin-type heat sink, the direct conduction mechanism and the convective area for the thermal transportation are effectively increased. Through a two-month experiment measurement, it is found that the thermal efficiency of PVT module is obviously enhanced up to 50% in sunny days. In addition, the waste heat recovery decreases the operating temperature of solar cells and concurrently improves the PV efficiency. The results demonstrate the concurrent enhancement of the novel PVT module with air circulation in solar electricity and thermal efficiency with a reciprocal aid.
本文介绍了一种新型空气式光伏/热组件的模型仿真和性能评估实验测量。将太阳能电池直接封装在翅片式散热器上,有效地增加了太阳能电池的直接传导机制和热传递的对流面积。通过两个月的实验测量,发现PVT组件在晴天的热效率明显提高,可达50%。此外,余热回收降低了太阳能电池的工作温度,同时提高了光伏效率。结果表明,新型PVT模块与空气循环同时增强太阳能发电和热效率。
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引用次数: 0
Model Reference Adaptive Control for Atomic Force Microscope 原子力显微镜模型参考自适应控制
Pub Date : 2018-11-01 DOI: 10.1109/CACS.2018.8606763
Huang-Chih Chen, L. Fu
This paper demonstrates the approach of a direct model reference adaptive control (MRAC) to maintain the constant amplitude of the oscillating Atomic Force Microscope (AFM) cantilever. Compared with PID controllers, the MRAC strategy can improve the scan velocity without losing the image quality.
本文介绍了一种直接模型参考自适应控制(MRAC)方法来保持原子力显微镜(AFM)悬臂梁的振幅恒定。与PID控制器相比,MRAC策略在不影响图像质量的前提下提高了扫描速度。
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引用次数: 0
Mixed Performance of Switched Systems with Time-varying Random Delay 时变随机延迟交换系统的混合性能
Pub Date : 2018-11-01 DOI: 10.1109/CACS.2018.8606781
C. Lien, K. Yu, Hao‐Chin Chang
In this paper, the mixed H2/H∞ performance analysis of switched time-delay systems with time-varying random delay via a switching signal selection is considered. Some delay-dependent LMI-based criteria are proposed to achieve the design of switching signal. Our approach is proposed to guarantee the mixed performance of system under consideration by Wirtinger-based inequality. A numerical example is given to show the main contribution of this paper.
本文研究了具有时变随机延迟的切换时滞系统的混合H2/H∞性能分析。为了实现开关信号的设计,提出了一些基于时延相关lmi的准则。本文提出的方法是为了保证基于wirtinger不等式的系统的混合性能。最后给出了一个数值算例来说明本文的主要贡献。
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引用次数: 1
期刊
2018 International Automatic Control Conference (CACS)
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