{"title":"An Interval Shrinking Trust Region Algorithm for GNSS/eLoran Pseudorange Fusion Positioning Initialization","authors":"Kai Liu, Wenhe Yan, Jiangbin Yuan, Zaihui Xiao, Chaozhong Yang, Yu Hua","doi":"10.1109/ICARCE55724.2022.10046591","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046591","url":null,"abstract":"Fusion of Global Navigation Satellite System (GNSS) with eLoran can greatly improve the coverage and availability of Positioning Navigation and Timing (PNT) services. However, due to the strong nonlinearity in the eLoran pseudorange equations, traditional methods may fail to converge or converge incorrectly when solving the fused pseudorange equation system. In this paper, an interval shrinking trust region algorithm (ISTR) is proposed to solve the pseudorange-based eLoran/GNSS fusion positioning problem, especially when no reliable initial values are available. Simulation and measured data verify that the ISTR algorithm can help the receiver to complete reliable positioning initialization without reliable initial values, and the initialization success rate is 100%.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125881675","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}
{"title":"Human-Robot Collaboration using Monte Carlo Tree Search","authors":"Feng Yao, Huailin Zhao, Huaping Liu","doi":"10.1109/ICARCE55724.2022.10046470","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046470","url":null,"abstract":"Human-Robot collaboration as a challenging task has received great attention in the academic research field. Many existing search models are aimed at single agent or multi-agent, but there are some defects in the search efficiency of their task targets. Therefore, we propose a human-computer cooperative search algorithm in the indoor scene, where people and agents cooperate to complete the search of related objects. We have developed a platform for human-robot collaboration, and designed a set of algorithms for agent to integrate scene prior knowledge, target recognition, and path planning. The experimental results that the H-R cooperative search model proposed by us shows good efficiency in target search tasks.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124804426","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}
{"title":"Sliding Muscle Surface Control of the Muscle-Driven Musculoskeletal System","authors":"Yerui Fan, Jianbo Yuan, Yaxiong Wu, Shuai Gan","doi":"10.1109/ICARCE55724.2022.10046635","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046635","url":null,"abstract":"In this study, a sliding muscle surface controller (SMSC) is designed to suppress disturbances and to reduce uncertainty in the muscle-driven musculoskeletal system (MDMS). When performing manipulation tasks in unstructured environments, bio-inspired robots are able to exhibit more flexibility and safety. Although the model of MDMS can be solved by combining the muscle model and the joint-link dynamics, the influence of unknown external disturbances and dynamic uncertainties makes it difficult to describe the system perfectly in practice. In order to solve the problems, a sliding muscle surface controller with an integral power reaching law is designed to suppress the chattering problem in the control and improve the anti-interference ability of the system and reduce the integrates error between expected and simulation. Subsequently, the stability of musculoskeletal system was ensured using the principle of Lyapunov synthesis. Finally, the simulation results showed that the proposed design techniques could effectively improve the robustness of muscle model.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128888529","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}
Jiamei Jiang, Xuhan Li, Xingyu Hao, Tao Liu, R. Qiu, Qunfeng Miao
{"title":"A Study on the Classification of Subclasses of Glass Artifacts Based on Feature Selection","authors":"Jiamei Jiang, Xuhan Li, Xingyu Hao, Tao Liu, R. Qiu, Qunfeng Miao","doi":"10.1109/ICARCE55724.2022.10046593","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046593","url":null,"abstract":"To explore the subclass types of ancient glass artifacts, first we combined the features provided in the dataset with the data on whether the artifacts were weathered or not, constructed a random forest model, and calculated the relative importance of each chemical component by the VIM (Variable Importance Measures) to give the important factors influencing the classification of major classes. Subsequently, we innovatively extracted the important components by improving the coefficient of variation to give the important factors influencing the classification of subclasses. Then, we construct a K-means clustering model for subclassification and give specific criteria for subclassification. Finally, we conducted the rationality analysis from two perspectives of chemical composition and heritage characteristics; we repeated the experiment to test the sensitivity of the large class division model for the random forest model normally distributed white noise sequence; we introduced Dunn index and contour coefficient for sensitivity analysis of the clustering model.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125458757","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}
{"title":"Maximum Temperature Prediction Based on GPS and Meteorological Data by Using Neural Network","authors":"Shenzheng Zuo, Renjie Cai, Yan Wang, Enrui Hu, Lingzhi Liu, Yibo Guo","doi":"10.1109/ICARCE55724.2022.10046621","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046621","url":null,"abstract":"Temperature prediction is a task involving agriculture, military, industry and other aspects, and it is related to daily life and production tasks. Therefore, accurate temperature prediction is an important research topic at present. In this paper, a neural network-based maximum temperature prediction method is proposed. Combined with the Precipitable Water Vapor (PWV) data calculated from GPS satellite data, it achieves high precision, high time granularity prediction under the condition of low computing power requirements.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120949202","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}
{"title":"Initial Alignment Method of Human Soft Strapdown Base Based on NKF-FRKF","authors":"Xiao Su Zhang, Qing Li, Zhong Su, Guodong Fu","doi":"10.1109/ICARCE55724.2022.10046500","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046500","url":null,"abstract":"Aiming at the problem of inaccurate statistical characteristics of system model noise within initial alignment of inertial pedestrian navigation, a novel heterogeneous hybrid correlation entropy Kalman filter (NHMCC-KF) alignment method is proposed considering inertial devices and human soft shortcuts. Firstly, the lever arm error is expanded as a state quantity to establish the initial alignment model of the inertial coordinate system. Then, on this basis, the covariance of the measurement noise is adjusted by combining the fast robust Kalman filter (FRKF) and the heterogenous mixture correntropy criterion, using a mixture of Laplace kernel and Gaussian kernel as the adjustment factor of the correntropy, and introducing the prior error covariance feedback adaptive Kalman filtering (NKF) to adjust the process noise. By comparing the alignment effect of NHMCC-KF and FRKF under different conditions through designed experiments, the azimuthal alignment accuracy is improved by more than 23%. The experimental findings demonstrate that the approach described in this research has superior alignment accuracy and speed.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127779266","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}
Jingjing Li, Yi Xu, Yapeng Li, Kepei Qi, Feiyong Yu, Shaohua Sun
{"title":"Research on Intelligent Recognition Solution of Tobacco Disease on Android Platform","authors":"Jingjing Li, Yi Xu, Yapeng Li, Kepei Qi, Feiyong Yu, Shaohua Sun","doi":"10.1109/ICARCE55724.2022.10046516","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046516","url":null,"abstract":"In order to improve the recognition accuracy of tobacco diseases, improve the recognition efficiency and convenience, and reduce the recognition cost, this project carried out the research on the recognition technology of tobacco diseases based on deep learning. First, the data set was established. The data set is consisted of several kinds of common tobacco diseases images which were labeled according to the experts’ diagnosis results. Second, the YOLOv7 network model was studied and pruned considering the recognition rate and accurate. Third, the pruned model was trained using the established training dataset. Then, the trained model is ported to Android system. Finally, an experimental testing was carried out, and the results show that the model can run efficiently in Android system with the detection accuracy above 90%.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133656663","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}
{"title":"The Generation Method of Simulation Scenario Sample Space Based on Sensitivity Analysis of Meta-model","authors":"Jing An, Wei Liu, Wanting Rong, Haoliang Qi","doi":"10.1109/ICARCE55724.2022.10046468","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046468","url":null,"abstract":"To ensure the feasibility and effectiveness of exploratory simulation experiments, it is necessary to take the simulation scenario sample space with acceptable scale and typical representative as input. In this paper, a method of generating simulation scenario sample space combining qualitative and quantitative analysis is proposed. This method constructs a machine learning meta-model based on simulation pre-experiment, and screens the key experimental factors based on sensitivity analysis of meta-model to determine the factor levels. Finally, the space is sampled and compressed to complete the generation of the hypothetical sample space.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130368344","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}
{"title":"An Improved Optimal Trajectory Planning Method of Six-axis Robotic Manipulators along Prescribed Path Constraints","authors":"Z. Xiong, Liping Chen, J. Ding","doi":"10.1109/ICARCE55724.2022.10046474","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046474","url":null,"abstract":"Optimal Control Problem (OCP) is a kind of classical problem with the state space equations, containing the optimal trajectory planning problem of robotic manipulators with complicated path constraints. The optimal control method (OCM) which contains direct and indirect methods is efficient to solve this kind of problems. The Pontryagin maximum principle is the core of the indirect method which includes tedious mathematical derivations, and is hard to work with the complex mechanical system. As the result, the direct methods represented by direct collocation method (DCM) are widely used in the engineering field. They transform the original optimal control problem to nonlinear programming problems (NLP), so that the general NLP solver can be used. There are mainly three different methods based on the above direct methods, including convex optimization (CO) methods, numerical integration (NI) methods and dynamic programming (DP) methods. This paper proposes a brand new idea which can streamline the problem description compared to the CO method, extend the general objective function compared to the NI method, and reduce the cost of storage compared to the DP method, and provides a feasible local optimal solution for the problem. In addition, the simulation experiment satisfies the kinodynamic constraints properly, and the validity of the proposed method is confirmed.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125611992","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}
{"title":"Kinematics Analysis of a Fully Driven Single Pendulum Spherical Mobile Robot","authors":"Minggang Li, Hanxu Sun, Long Ma, Ping Sun","doi":"10.1109/ICARCE55724.2022.10046480","DOIUrl":"https://doi.org/10.1109/ICARCE55724.2022.10046480","url":null,"abstract":"In order to further improve the reliability of the spherical robot and enrich its motion forms, a fully driven single pendulum spherical robot is proposed. An innovative way of kinematic modeling from pendulum to spherical shell is proposed. The velocity Jacobian matrix and the inverse kinematics solution of velocity level in the slope of the spherical robot are given. The simulation results verify the controllability of the spherical robot and the correctness of the kinematic model.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"227 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123159989","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}