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2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)最新文献

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Drone detection using YOLOv3 with transfer learning on NVIDIA Jetson TX2 在NVIDIA Jetson TX2上使用带有迁移学习的YOLOv3进行无人机检测
2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP) Pub Date : 2021-01-20 DOI: 10.1109/ICA-SYMP50206.2021.9358449
Daniel Tan Wei Xun, Yoke Lin Lim, S. Srigrarom
{"title":"Drone detection using YOLOv3 with transfer learning on NVIDIA Jetson TX2","authors":"Daniel Tan Wei Xun, Yoke Lin Lim, S. Srigrarom","doi":"10.1109/ICA-SYMP50206.2021.9358449","DOIUrl":"https://doi.org/10.1109/ICA-SYMP50206.2021.9358449","url":null,"abstract":"The rise of drones in the recent years largely due to the advancements of drone technology which provide drones the ability to perform many more complex tasks autonomously with the incorporation of technologies such as computer vision, object avoidance and artificial intelligence. However, the misuse of drones such as the Gatwick Airport drone incident resulted in major disruptions which affected approximately 140,000 passengers. To deter this from happening in the future, drone surveillance are extremely crucial. With this, it will be achieved firstly by detection and followed by tracking of drones. This paper presents and investigates the use of a deep learning object detector, YOLOv3 with pretrained weights and transfer learning to train YOLOv3 to specifically detect drones. We demonstrated that the detection results from YOLOv3 after machine learning had an average accuracy of 88.9% at input image size of $416times 416$. Finally, we integrated into NVIDIA Jetson TX2 for real-time drone detection.","PeriodicalId":147047,"journal":{"name":"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121001335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 25
V2V Network Topologies for Vehicle Platoons with Cooperative State Variable Feedback Control 具有协同状态变量反馈控制的车辆队列V2V网络拓扑
2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP) Pub Date : 2021-01-20 DOI: 10.1109/ICA-SYMP50206.2021.9358435
A. Prayitno, I. Nilkhamhang
{"title":"V2V Network Topologies for Vehicle Platoons with Cooperative State Variable Feedback Control","authors":"A. Prayitno, I. Nilkhamhang","doi":"10.1109/ICA-SYMP50206.2021.9358435","DOIUrl":"https://doi.org/10.1109/ICA-SYMP50206.2021.9358435","url":null,"abstract":"This paper aims to study and compare the effect of V2V network topology on vehicle platooning applications, with the objective of maintaining inter-vehicular spacing at all times. The platoon is formulated as a cooperative state variable feedback control problem with constant spacing policy and homogenous agents. The communication topologies considered include predecessor-following (PF), bidirectional (BD), predecessor-following-leader (PFL), bidirectional-leader (BDL), two-predecessor-following (TPF), and two-predecessor-following-leader (TPFL). Simulation analysis is performed under normal operations and when a disturbance occurs in one of the follower vehicles. The effect of the coupling gain is also discussed. For large platoons under normal conditions, more complex topologies, such as TPFL, BDL, and PFL, provide better performance in terms of platoon response. The propagation of disturbance in upstream and/or downstream directions is observed for certain topologies. Increasing the coupling gain can improve the system response of the platoon but also requires more control effort.","PeriodicalId":147047,"journal":{"name":"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124891267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Development and characterization of a low-cost vibration monitoring instrument based on MEMS acceleration sensor 基于MEMS加速度传感器的低成本振动监测仪的研制与表征
2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP) Pub Date : 2021-01-20 DOI: 10.1109/ICA-SYMP50206.2021.9358445
N. Suttiwong, P. Rattanangkul
{"title":"Development and characterization of a low-cost vibration monitoring instrument based on MEMS acceleration sensor","authors":"N. Suttiwong, P. Rattanangkul","doi":"10.1109/ICA-SYMP50206.2021.9358445","DOIUrl":"https://doi.org/10.1109/ICA-SYMP50206.2021.9358445","url":null,"abstract":"This paper describes the design and the error evaluation of a low-cost vibration monitoring instrument based on the MEMS acceleration sensor, which can be applied to various applications for the building structure monitoring. The developed instrument can be utilized to monitor five measuring points simultaneously and remotely on twisted pair conductors up to 100 meters. The design focuses strongly on the instrument mobility, easy to install on the measuring site, real-time processing, and accuracy. The current-loop technique is used in the design of the signal conditioner to enhance the ability of data transmission in a longer distance without noise. The instrument is intended to use with the frequency up to 20 Hz. The sensitivity of the sensor head and monitoring station were calibrated with the standard shaker. The calibration method conforms to ISO16063-21. The accuracy of the overall instrument is at ±0.3 m/s2 at the frequency range of 1 Hz to 20 Hz.","PeriodicalId":147047,"journal":{"name":"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129414635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Study on Safety Issues of Hybrid Wireless Power Transfer in Laboratory 实验室混合无线电力传输安全问题研究
2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP) Pub Date : 2021-01-20 DOI: 10.1109/ICA-SYMP50206.2021.9358440
Jarurote Tippayachai, S. Kiattisin, T. Samanchuen, K. Jirasereeamornkul, C. Ekkaravarodome, T. Singhavilai
{"title":"A Study on Safety Issues of Hybrid Wireless Power Transfer in Laboratory","authors":"Jarurote Tippayachai, S. Kiattisin, T. Samanchuen, K. Jirasereeamornkul, C. Ekkaravarodome, T. Singhavilai","doi":"10.1109/ICA-SYMP50206.2021.9358440","DOIUrl":"https://doi.org/10.1109/ICA-SYMP50206.2021.9358440","url":null,"abstract":"Hybrid wireless power transfer (HPT) employs both magnetic and electric fields to transmit the power across air-gap distance at the resonant frequency, enhancing the potential for charging battery in electric vehicles. While the HPT technology is still under research study, the safety concerns for HPT have not yet been reported during the experiment. This study aims to re-investigate the safety issues of HPT in experiment by creating and testing the HPT prototype. The HPT proposed by Luo is used in our study, consisting of two coupling coils, four aluminium plates, and two compensation capacitors. This HPT prototype is tested in the frequency range of 600 to 700 kHz. To reveal the effects of thermal and EMF leakages, a thermal scan and EMF detector are used in the experiment. The results demonstrated that the prototype of HPT operates at high frequency, high power, and high efficiency. Moreover, the safety issues in experiment are summarized.","PeriodicalId":147047,"journal":{"name":"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116817312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Multi-camera Multi-drone Detection, Tracking and Localization with Trajectory-based Re-identification 基于轨迹再识别的多摄像头多无人机检测、跟踪与定位
2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP) Pub Date : 2021-01-20 DOI: 10.1109/ICA-SYMP50206.2021.9358454
S. Srigrarom, Niven Jun Liang Sie, Huimin Cheng, Kim Hoe Chew, Mengda Lee, P. Ratsamee
{"title":"Multi-camera Multi-drone Detection, Tracking and Localization with Trajectory-based Re-identification","authors":"S. Srigrarom, Niven Jun Liang Sie, Huimin Cheng, Kim Hoe Chew, Mengda Lee, P. Ratsamee","doi":"10.1109/ICA-SYMP50206.2021.9358454","DOIUrl":"https://doi.org/10.1109/ICA-SYMP50206.2021.9358454","url":null,"abstract":"This paper presents a real-time multiple camera system for detecting, tracking and localizing multiple moving drones simultaneously in a 3 dimension space. The distinct feature of the system is in its target re-identification process, which provides for information fusion among cameras based on the targets' trajectories and relative locations. Drones are detected by the multiple camera system based on motion-based blob detection, and the 2D locations of each drone in individual camera frames are tracked by A geometry- and camera-based model. From the paths of the tracked drones, their trajectories are examined using drone track feature variable. Cross-correlated among cameras for object re-identifications will allow the individual 2D position information to be integrated into overall global 3D positions of all the tracked drones from all cameras. Preliminary outdoor flight demonstrations with 2 drones flying in formation and using 3 cameras show optimal results. The system is able to detect, track, localize and re-identifying individual drone with average positional error of 8%.","PeriodicalId":147047,"journal":{"name":"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129157733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Development of a Vision Based Ball Catching Robot 基于视觉的接球机器人的研制
2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP) Pub Date : 2021-01-20 DOI: 10.1109/ICA-SYMP50206.2021.9358432
Kasun Gayashan Hettihewa, M. Parnichkun
{"title":"Development of a Vision Based Ball Catching Robot","authors":"Kasun Gayashan Hettihewa, M. Parnichkun","doi":"10.1109/ICA-SYMP50206.2021.9358432","DOIUrl":"https://doi.org/10.1109/ICA-SYMP50206.2021.9358432","url":null,"abstract":"This paper investigates an automated solution for ball catching task using a static camera and an automatically controlled mechanical system. The robot system is able to catch a ball which comes towards the ball catching plane. The robot accomplishes the ball-catching task with different success rates according to the trajectory type and speed of the ball. The thrown ball is visually tracked through a ball detection image processing algorithm. 2D synchronized motion of the ball catcher is coordinated by PID algorithm. Experimental results are conducted to evaluate the robot performance.","PeriodicalId":147047,"journal":{"name":"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132821583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Anomaly Detection of a Reciprocating Compressor using Autoencoders 基于自编码器的往复式压缩机异常检测
2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP) Pub Date : 2021-01-20 DOI: 10.1109/ICA-SYMP50206.2021.9358453
Chittkasem Charoenchitt, P. Tangamchit
{"title":"Anomaly Detection of a Reciprocating Compressor using Autoencoders","authors":"Chittkasem Charoenchitt, P. Tangamchit","doi":"10.1109/ICA-SYMP50206.2021.9358453","DOIUrl":"https://doi.org/10.1109/ICA-SYMP50206.2021.9358453","url":null,"abstract":"This study introduces a novel approach for early fault detection using an autoencoder under time-varying conditions of a reciprocating compressor. The main strategy of this unprecedented method functions by combining a thermodynamic equation of compressor's discharge temperature with sensors' data to increase the prediction accuracy. This equation enables the model to identify the relationships between variables including the temperature, pressure and molecular weight of gas, thus alleviating the problem of poor data quality. Energy spectrum of vibration signals in the frequency domain was also used as additional features. The model was trained to recognize normal operations with 5-year data sampled every one minute. Two months before a machine shutdown was considered as abnormal period, of which the model wanted to identify it. The result suggested that the model can differentiate between normal and abnormal operations by a substantial margin.","PeriodicalId":147047,"journal":{"name":"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115237935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Double Loop Neural Fractional-Order Terminal Sliding Mode Control of MEMS Gyroscope MEMS陀螺仪的双回路神经分数阶末端滑模控制
2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP) Pub Date : 2021-01-20 DOI: 10.1109/ICA-SYMP50206.2021.9358437
Zhe Wang, J. Fei
{"title":"Double Loop Neural Fractional-Order Terminal Sliding Mode Control of MEMS Gyroscope","authors":"Zhe Wang, J. Fei","doi":"10.1109/ICA-SYMP50206.2021.9358437","DOIUrl":"https://doi.org/10.1109/ICA-SYMP50206.2021.9358437","url":null,"abstract":"A fractional-order nonsingular terminal sliding mode controller is proposed for a MEMS gyroscope using a double loop recurrent neural network approximator. For higher accuracy and faster convergence, the fractional-order (FO) calculus is employed into the nonsingular terminal sliding mode controller with additional degree of freedom. For the system robustness, the neural network is designed to approximate the lumped uncertainty. The inner recurrent loop and external recurrent loop is employed to provide feedback signal to obtain satisfactory approximation accuracy. Furthermore, the Lyapunov stability theorem is employed to verify the asymptotical stability and convergence of system. Simulations for a MEMS gyroscope are studied to exhibit the superiority of the proposed control strategy.","PeriodicalId":147047,"journal":{"name":"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125558081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Classification of the Resistance Spot Weld Failure Mode Using Convolutional Neural Network 基于卷积神经网络的电阻点焊失效模式分类
2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP) Pub Date : 2021-01-20 DOI: 10.1109/ICA-SYMP50206.2021.9358428
Watchanun Piriyabunjerd, Chettapong Janya-anurak
{"title":"Classification of the Resistance Spot Weld Failure Mode Using Convolutional Neural Network","authors":"Watchanun Piriyabunjerd, Chettapong Janya-anurak","doi":"10.1109/ICA-SYMP50206.2021.9358428","DOIUrl":"https://doi.org/10.1109/ICA-SYMP50206.2021.9358428","url":null,"abstract":"The resistance spot welding (RSW) is a comprehensive used process in the automotive industry. However, in the production line the quality of the weld is normally roughly assessed from its appearance by human. In this work, we propose the prediction of the quality of the resistance spot weld by using the convolutional neural network (CNN). The architecture of CNN applied in this work was MobileNetV3. The quality of the weld in this work was the failure mode of RSW determined by strength of the weld by tensile shear test. The external apparent image of welds was used as information for predicting the quality of the welds. For building the data set, the RSW was conducted with specific welding conditions and the heat trace image of welds was captured. The parameters of the CNN were trained from the apparent image of the welds and their failure mode. As a result, the CNN model was able to predict the class of the failure mode of the RSW from the welds image with satisfactory F1-score of 94.32% for unseen validation data set.","PeriodicalId":147047,"journal":{"name":"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130877905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICASYMP) 第二届仪器、控制、人工智能与机器人国际研讨会(ICASYMP)
2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP) Pub Date : 2021-01-20 DOI: 10.1109/ica-symp50206.2021.9358443
{"title":"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICASYMP)","authors":"","doi":"10.1109/ica-symp50206.2021.9358443","DOIUrl":"https://doi.org/10.1109/ica-symp50206.2021.9358443","url":null,"abstract":"","PeriodicalId":147047,"journal":{"name":"2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114437957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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