2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR)最新文献_第2页

Autonomous Mobile Robot Navigation using Adaptive Neuro Fuzzy Inference System 基于自适应神经模糊推理系统的自主移动机器人导航

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796495

Muhammad Husnain Haider, Hub Ali, A. Khan, Hao Zheng, M. Usman Maqbool Bhutta, Shaban Usman, Pengpeng Zhi, Zhonglai Wang

{"title":"Autonomous Mobile Robot Navigation using Adaptive Neuro Fuzzy Inference System","authors":"Muhammad Husnain Haider, Hub Ali, A. Khan, Hao Zheng, M. Usman Maqbool Bhutta, Shaban Usman, Pengpeng Zhi, Zhonglai Wang","doi":"10.1109/IDITR54676.2022.9796495","DOIUrl":"https://doi.org/10.1109/IDITR54676.2022.9796495","url":null,"abstract":"Navigation of autonomous robots in unknown and cluttered environments lies among the marked trends in robotics. Unlike animals and humans, the collision-free movement of a robot is challenging and requires processing complex information. An autonomous robot needs to cope with a large amount of uncertainty while navigating. The previous methods have limitations, such as lacking obstacle avoidance behaviour, having a large number of governing rules, designing a separate controller for each navigation and obstacle avoidance, not considering the robot's dynamics, computationally expensive training, and poor performance in a cluttered environment. This paper proposes a method that comprises a single adaptive neuro fuzzy inference system (ANFIS) based controller with 16 rules compared to hundred of rules used by previous methods to address such problems. Our method takes heading angle along with distance sensors data as input. AU the inputs are fuzzified into linguistic variables such as near-far and left-right. Additionally, a fuzzy inference system (FIS) is designed and trained using the generated dataset for optimum performance of ANFIS. The proposed method efficiently provides collision-free navigation of the mobile robot in densely cluttered environments. Comprehensive experiments are performed to prove the robustness and potency of the proposed ANFIS controller. Moreover, the performance of the proposed method is compared with various previous methods. The results of these comparisons indicate our proposed method's superiority in finding a near-optimal path.","PeriodicalId":111403,"journal":{"name":"2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR)","volume":"46 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130798202","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

Identification of Single-phase Grounding Fault Type in Distribution Network Based on VMD and SVM 基于VMD和SVM的配电网单相接地故障类型识别

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796492

Bo Feng, Jia Yang, Y. Jia, Yan Chen, Hongwei Zhao, Guimei Cao

{"title":"Identification of Single-phase Grounding Fault Type in Distribution Network Based on VMD and SVM","authors":"Bo Feng, Jia Yang, Y. Jia, Yan Chen, Hongwei Zhao, Guimei Cao","doi":"10.1109/IDITR54676.2022.9796492","DOIUrl":"https://doi.org/10.1109/IDITR54676.2022.9796492","url":null,"abstract":"This paper put forward a method for the identification in single-phase grounding faults to effectively classify and identify resistance grounding faults and arc grounding faults in distribution networks, which is consist of Variational Mode Decomposition (VMD) and Support Vector Machine (SVM). Firstly, a simulation model describing the 10kV distribution network is established by PSCAD/EMTDC, and four types of single-phase grounding faults are constructed. Secondly, the different eigenmode functions are obtained through VMD decomposition of the collected fault signals of the zero-sequence current, and the permutation entropy that contributes the most is found by extract the typical characteristic of the fault signal. Thereafter, the eigenvector is constructed and imported into the SVM for identifying the single-phase grounding fault type. Finally, the simulation results in MATLAB indicate that the proposed method has more satisfactory practicability and can achieve nice accuracy compared with traditional intelligent algorithms.","PeriodicalId":111403,"journal":{"name":"2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116725777","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

Optimal Design Method for the Partitioning of OLTC-Inverter Control Parameters in Distribution Stations with High-proportion Residential Photovoltaics 高比例住宅光伏配电站oltc -逆变器控制参数分配的优化设计方法

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796497

Z. Song, Yuanting Hu, Huaiyu Guo, Jiancheng Ma, Baiyue Song, Mingyu Xu, Zhiyang Liu

引用次数: 0

Trajectory tracking method with short time step and long trajectory prediction 短时间步长轨迹预测的轨迹跟踪方法

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796480

Chu Kaixuan, Chang Tianqing, Zhao Liyang, Zhang Jie, Yan Xiaodong

引用次数: 0

KOOPI: Keypoint-Oriented Object Positioning in Industry KOOPI:面向关键点的工业对象定位

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796493

Chonghao Zhao, Gang Wu

{"title":"KOOPI: Keypoint-Oriented Object Positioning in Industry","authors":"Chonghao Zhao, Gang Wu","doi":"10.1109/IDITR54676.2022.9796493","DOIUrl":"https://doi.org/10.1109/IDITR54676.2022.9796493","url":null,"abstract":"In manufacturing, object detection via industrial images enables many typical applications such as positioning of screw holes, electronic components, and other devices. The conventional method based on classical image processing generally consists of two steps: image feature extraction and object classification, so that it usually results in a low detection speed and poor accuracy due to its complicated procedure. In recent years, thanks to the rapid development of deep learning networks, higher classification accuracy and less computing performance requirement can be achieved in many typical applications, compared to using the conventional schemes. In this paper, by investigating object detection based on deep learning, a new idea utilizing some keypoint-oriented deep learning networks to the workpiece positioning area is proposed and verified by collecting dataset from practical workpieces. Our novel method performs competitively with existing schemes and runs in real-time. As for the simulation of screw hole positioning, the proposed network can effectively detect the screw hole in the image and accurately locate it. By comparing with commercial software such as Halcon® or VisionPro®, the feasibility of applying keypoint-oriented deep learning networks to intelligent manufacturing is validated.","PeriodicalId":111403,"journal":{"name":"2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128658679","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

Fault-Tolerant formation keeping design for Multi-AUVs in MOOS-IvP MOOS-IvP中多auv的容错队形保持设计

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796486

Peiyan Gao, Yiping Li, J. Zeng, Shuo Li

引用次数: 0

Design and Experiments of an Anthropomorphic Finger with Circular Arc Staggered Compliant Joints 具有圆弧交错柔性关节的拟人手指的设计与实验

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796484

Yin Zhang, Pengfei Chen, Xuhui Yang, Chenggang Liu, Z. Qi, Yang Li, Qinhuan Xu, Q. Zhan

{"title":"Design and Experiments of an Anthropomorphic Finger with Circular Arc Staggered Compliant Joints","authors":"Yin Zhang, Pengfei Chen, Xuhui Yang, Chenggang Liu, Z. Qi, Yang Li, Qinhuan Xu, Q. Zhan","doi":"10.1109/IDITR54676.2022.9796484","DOIUrl":"https://doi.org/10.1109/IDITR54676.2022.9796484","url":null,"abstract":"In order to reduce the axis position change during the compliant joint motion, improve its anthropomorphic appearance and fabrication convenience for the anthropomorphic finger, two kinds of circular arc staggered compliant joints were proposed in this paper, and they were analyzed through finite element simulation (FEA) and experiments, Then the compliant joint of \"C+ structure in the middle and two C- structures symmetrically distributed on both sides\" was applied to the design of an anthropomorphic finger. Finally, the finger was made using 3D printing and experiments were done. The experiments show that the proposed joint in this paper has smaller axis position change during motion. The finger with the proposed compliant joint has good anthropomorphic appearance and passive adaptability, which is helpful to enhance the grasping stability. In addition, the design and fabrication method used in this paper is helpful to realize the rapid and lightweight design and fabrication of anthropomorphic hands.","PeriodicalId":111403,"journal":{"name":"2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR)","volume":"2011 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128203972","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

Neural Network and Extreme Gradient Boosting in Near Infrared Spectroscopy 近红外光谱中的神经网络和极端梯度增强

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796490

K. Chia, Nur Aisyah Syafinaz Suarin

{"title":"Neural Network and Extreme Gradient Boosting in Near Infrared Spectroscopy","authors":"K. Chia, Nur Aisyah Syafinaz Suarin","doi":"10.1109/IDITR54676.2022.9796490","DOIUrl":"https://doi.org/10.1109/IDITR54676.2022.9796490","url":null,"abstract":"Near infrared spectroscopy is a secondary measurement approach that aims to quantitatively or qualitatively estimate the components of interest from the acquired near infrared spectrum using computation methods e.g. machine learning algorithms. After decades of investigation, neural network has been accepted as a nonlinear benchmark model in near infrared spectroscopy. Although a recent work reported that Extreme Gradient Boosting (XGBoost) outperformed neural network in groundwater level prediction, the optimization process and the learning algorithm of the neural network were not reported. This implies that the neural network might not be the optimal. Thus, this study aims to compare the performance of the optimal Bayesian regularized neural network and XGBoost in a regression application using more than one thousand of near infrared spectral data that were acquired throughout different years. The regression models were established to predict the dry matter content (DMC) of mangoes using the respective spectral data. Results show that even though XGBoost could achieve a satisfactory accuracy with RMSEV, RMSEP, R2V, and R2P of 1.16%, 1.22%, 0.73, and 0.80, respectively, the Bayesian regularized neural network achieved substantially better RMSEV, RMSEP, R2V, and R2P of 0.83%, 0.86%, 0.86, and 0.90, respectively. Thus, a Bayesian regularized neural network is recommended to be tested when more than one thousand near infrared spectral data were available.","PeriodicalId":111403,"journal":{"name":"2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114614998","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: 3

Threshold selection of wavelet denoising based on optimization algorithms 基于优化算法的小波去噪阈值选择

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796485

Han Xiao, D. Hu, Jiajun Wang

引用次数: 0

Research on Noise Filtering Method of Fire Truck Based on Digital FIR Filter 基于数字FIR滤波器的消防车噪声滤波方法研究

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796478

CanCui, ZengLi, Yuntian Bai

引用次数: 0