Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology最新文献

Estimation of Maximum Friction Coefficient Using Recurrent Artificial Neural Networks 基于递归人工神经网络的最大摩擦系数估计

Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology Pub Date : 2022-07-22 DOI: 10.1145/3560453.3560459

Nicolas Lampe, Zygimantas Ziaukas, C. Westerkamp, Hans-Georg Jacob

{"title":"Estimation of Maximum Friction Coefficient Using Recurrent Artificial Neural Networks","authors":"Nicolas Lampe, Zygimantas Ziaukas, C. Westerkamp, Hans-Georg Jacob","doi":"10.1145/3560453.3560459","DOIUrl":"https://doi.org/10.1145/3560453.3560459","url":null,"abstract":"Knowledge of vehicle dynamics and in particular the maximum friction coefficient is required for the optimization of advanced driver assistance systems and the implementation of autonomous driving. Since the maximum friction coefficient cannot be measured directly, estimating this coefficient based on available sensors is a field of interest. In particular, model-based approaches based on Kalman filter derivates are used. However, their accuracy is limited by the accuracy of the physical model. Due to the real-time capability required, more detailed modeling is not possible. In addition, system identification and a robust filter design are needed. As a result, data-based approaches are gaining popularity in vehicle dynamics, which are also suitable for estimating the maximum friction coefficient. In this paper, maximum friction coefficient estimation is presented using recurrent artificial neural networks (RANN) based on vehicle sensors. In order to avoid incorrect estimations during low vehicle excitation, an excitation monitoring approach is introduced. Typical longitudinal and lateral driving maneuvers on different road surfaces simulated in IPG CarMaker with a Dacia Duster are used for training, validation and testing of the RANN. Finally, the data-based approach shows improved results compared to the model-based approach of a sensitivity-based unscented Kalman filter (sUKF) from previous works.","PeriodicalId":345436,"journal":{"name":"Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126948697","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

Abuse Torque Load Simulation and Design of Differential Mechanism in Hybrid Electric Vehicle 混合动力汽车差动机构滥用扭矩载荷仿真与设计

Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology Pub Date : 2022-07-22 DOI: 10.1145/3560453.3560458

Guogeng Zhang, Pengcheng Huang, Xiaowen Song

引用次数: 0

Development of an Underwater Cleaning Robot with Vortex Suction Mechanism 涡吸式水下清洁机器人的研制

Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology Pub Date : 2022-07-22 DOI: 10.1145/3560453.3560455

Yibing Zhao, Canjun Yang

引用次数: 0

Research on working condition transformation of Huangshan test bench based on Markov braking vibration noise 基于马尔可夫制动振动噪声的黄山试验台工况变换研究

Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology Pub Date : 2022-07-22 DOI: 10.1145/3560453.3560462

Ruijun Dou, Tianji Feng, M. Zhou, Qin Xu, Liang Kou

{"title":"Research on working condition transformation of Huangshan test bench based on Markov braking vibration noise","authors":"Ruijun Dou, Tianji Feng, M. Zhou, Qin Xu, Liang Kou","doi":"10.1145/3560453.3560462","DOIUrl":"https://doi.org/10.1145/3560453.3560462","url":null,"abstract":"In order to realize the purpose of early braking vibration and noise verification and assist in model selection, data screening and kinematic segment division of the collected vehicle brake Huangshan braking load spectrum were carried out, and the Markov working condition was used to construct the theory, and the state transition probability matrix was carried out. build, and apply the stochastic case construction method for candidate case construction.Cluster analysis is performed on the constructed candidate working conditions, the final transformation working condition is selected, and the transformation working condition is formulated as the inertia test bench working condition.Finally, the same samples were subjected to inertia bench test and vehicle road test respectively, and the test results of the two were compared and analyzed. It can be seen from the analysis results that the converted bench conditions can reproduce the problems found in the vehicle test to a certain extent.Through the conversion conditions of this study, it can realize the preliminary verification for the main engine factory in the early stage of brake system selection, find and solve most of the vibration and noise problems of the selected samples, shorten the development cycle and save the development cost.","PeriodicalId":345436,"journal":{"name":"Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126589626","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

Super Resolution DOA Based on Virtual Sparse Extension Array for FMCW Automotive Radar 基于虚拟稀疏扩展阵列的FMCW汽车雷达超分辨方位分析

Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology Pub Date : 2022-07-22 DOI: 10.1145/3560453.3560461

Wei Zhang, Shunxing Xu, Zhihang Wang, Fang Yu, Zishu He

{"title":"Super Resolution DOA Based on Virtual Sparse Extension Array for FMCW Automotive Radar","authors":"Wei Zhang, Shunxing Xu, Zhihang Wang, Fang Yu, Zishu He","doi":"10.1145/3560453.3560461","DOIUrl":"https://doi.org/10.1145/3560453.3560461","url":null,"abstract":"Automotive radar has been emerging as a key technology enabling intelligent and autonomous features in modern vehicles. However, its great weakness is the poor angular resolution compared with its competitors, such as LiDAR or camera. Thus, one of the most challenging problems automotive radars faced is how to achieve high angular resolution, especially with the restriction of limited array aperture and in high dynamic environment. In this paper, a novel approach for high angular resolution DOA is proposed to separate two targets in the same range and Doppler cell by introducing one completely new concept of virtual sparse extension array. Based on the radar returns from the physical array, an extremely large virtual sparse aperture can be formed in a unique way. The simulation results demonstrate that, for a typical time division modulation (TDM) multiple-input multiple-output (MIMO) automotive radar with 3 transmitters and 4 receivers, the angular resolution can reach 0.01°, which is far better than other algorithms. In addition, the proposed method only needs single snapshot, and this is especially valuable to deal with the practical high dynamic environment.","PeriodicalId":345436,"journal":{"name":"Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115017417","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

Numerical study of the axial mechanical properties of braided corrugated hose with different braiding angles 不同编织角度编织波纹软管轴向力学性能的数值研究

Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology Pub Date : 2022-07-22 DOI: 10.1145/3560453.3560464

Dacheng Huang, Jianrun Zhang

引用次数: 0

Machinery Fault Diagnosis using Continuous Wavelet Transform and Artificial Intelligence based classification 基于连续小波变换和人工智能分类的机械故障诊断

Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology Pub Date : 2022-07-22 DOI: 10.1145/3560453.3560463

Maamar Al Tobi, Ramachandran K p, Saleh Al-Araimi, Rene Pacturan, Amuthakkannan Rajakannu, Geetha Achuthan

{"title":"Machinery Fault Diagnosis using Continuous Wavelet Transform and Artificial Intelligence based classification","authors":"Maamar Al Tobi, Ramachandran K p, Saleh Al-Araimi, Rene Pacturan, Amuthakkannan Rajakannu, Geetha Achuthan","doi":"10.1145/3560453.3560463","DOIUrl":"https://doi.org/10.1145/3560453.3560463","url":null,"abstract":"This work presents an investigation for a number of mechanical conditions (healthy, imbalance, misalignment, gear fault, bearing fault). The vibration conditions are simulated and based on real-time vibration data that are acquired from a Machinery Fault Simulator (MFS). The diagnosis process passes through two main stages after the data acquisition, where then the Continuous Wavelet Transform (CWT) method is applied to preprocess the obtained datasets (signals), and extract the features based on five statistical parameters namely: RMS, Kurtosis, Peak, Impulse Factor and Shape Factor. Then Artificial Intelligence (AI) based classification is applied using the Multilayer Feed-Forward Perceptron Neural Network (MLP) using different cases, where different number of neurons for the hidden layer and two different datasets of the input features with 250 features for each condition and also 2000 features for each condition once with normalized and also with non-normalized features to investigate the best cases for the performance classification in terms of neurons and features number, and also the impact of features normalization. The obtained results based on the classification performance using MLP-NN with the different cases are comparable, where the normalized features with less number of features and moderate neurons have shown better classification performance. Moreover, the results have shown the advantage of integrating CWT with the MLP-NN by providing significant classification rates for the different mechanical conditions.","PeriodicalId":345436,"journal":{"name":"Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132588133","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

Swarm Ornithopter Robirds: An Architecture to Protect Aerospace for Aerial Defense 蜂群扑翼机Robirds:一种用于空中防御的保护航空航天的架构

Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology Pub Date : 2022-07-22 DOI: 10.1145/3560453.3560456

Yash Patel, Parag Rughani

引用次数: 1

Research on Reliability Evaluation of the Substation Anti-misoperation Locking System 变电站防误操作锁定系统可靠性评估研究

Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology Pub Date : 2022-07-22 DOI: 10.1145/3560453.3560466

Junjie Zhang, Li Zhang, Xin-zhu Li

引用次数: 0

Analyzing the Influence of Driver, Route and Vehicle-Related Factors in Electric Vehicle Energy Consumption, Based on Real Life Data 基于真实生活数据的驾驶员、路线和车辆相关因素对电动汽车能耗的影响分析

Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology Pub Date : 2022-07-22 DOI: 10.1145/3560453.3560467

Iker Arandia, Iñaki Cejudo, E. Irigoyen, Itziar Urbieta, Harbil Arregui, E. Loyo

{"title":"Analyzing the Influence of Driver, Route and Vehicle-Related Factors in Electric Vehicle Energy Consumption, Based on Real Life Data","authors":"Iker Arandia, Iñaki Cejudo, E. Irigoyen, Itziar Urbieta, Harbil Arregui, E. Loyo","doi":"10.1145/3560453.3560467","DOIUrl":"https://doi.org/10.1145/3560453.3560467","url":null,"abstract":"In electric vehicles context, battery consumption and \"range anxiety\" are the biggest worries. Different studies have shown that electric vehicle battery consumption depends on many factors and parameters that can be related with the vehicle, the driver or the route. In this paper we will show the impact of those parameters in the energy consumption based on a real life dataset. This dataset contains information about different real life routes completed by an electric vehicle (Volkswagen e-Golf). To see if a parameter affects the energy consumption, we will use different graphics and the statistical ANOVA-test and Welch's test. When parameters are categorical variables, we will see how the energy consumption changes between categories, showing that different values of that parameter imply different value of energy consumption. Continuous variables are going to be analyzed using the pairplot. The results show that using auxiliaries, an aggressive driving style and winter tires increase the consumption. Also, it is an important conclusion how in long routes the energy consumption is more stable than in shorter routes.","PeriodicalId":345436,"journal":{"name":"Proceedings of the 2022 3rd International Conference on Robotics Systems and Vehicle Technology","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128173097","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