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2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)最新文献

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ERCM: Bionic Event-based Registration Method Based on Contrast Minimum for Intelligent Unmanned Systems 基于对比度最小的智能无人系统仿生事件配准方法
2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023860
Shijie Zhang, Fan Sang, Jiaxin Li, T. Tang, Jianglong Zhang, Taogang Hou
{"title":"ERCM: Bionic Event-based Registration Method Based on Contrast Minimum for Intelligent Unmanned Systems","authors":"Shijie Zhang, Fan Sang, Jiaxin Li, T. Tang, Jianglong Zhang, Taogang Hou","doi":"10.1109/YAC57282.2022.10023860","DOIUrl":"https://doi.org/10.1109/YAC57282.2022.10023860","url":null,"abstract":"Event cameras have the advantages of high time resolution and high dynamic range, and the fusion of its image and RGB image can bring great benefits to intelligent unmanned systems. However, the two modal images are not fully registered, which may affect the performance of tasks in intelligent systems, such as semantic segmentation. In this paper, we propose a registration method of event and RGB cameras based on contrast minimum. Our experimental data consists of 8 sequences, each consisting of 20 consecutive frames from the DSEC dataset, an event-RGB image dataset. As a result, the overlaid image of event images and RGB images show better consistency in visualization. Compared with the baseline, the declining value of contrast is from 26 to 161, the proportion of overlapping pixels in edge and event image has increased by 2.00% and 0.91%, respectively. The study in this paper demonstrates promising applications of the fusion of event and RGB cameras in intelligent unmanned systems.","PeriodicalId":272227,"journal":{"name":"2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123874438","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
Towards Pose Estimation for Large UAV in Close Range 大型无人机近距离姿态估计研究
2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023647
N. Ou, Junzheng Wang, Shangfei Liu, Jiehao Li
{"title":"Towards Pose Estimation for Large UAV in Close Range","authors":"N. Ou, Junzheng Wang, Shangfei Liu, Jiehao Li","doi":"10.1109/YAC57282.2022.10023647","DOIUrl":"https://doi.org/10.1109/YAC57282.2022.10023647","url":null,"abstract":"This paper deals with the problem of 4D pose estimation for large unmanned aerial vehicles (UAVs) in close range. A sensor system consisting of one single point laser range-finder and two cameras is designed and a novel pose estimation method based on vision fusion and point cloud registration is proposed. Our approach works on one-shot mode and only requires 10 samples with real poses for template construction. Through V-rep simulation environment, we generate two 200-sample datasets of different difficulty for evaluation. Error quantiles, 5cm5deg and 10cml0deg are three evaluation metrics used in our ablation experiments. It is illustrated that our method outperforms in robustness and precision due to proposed dimension extension modification and fusion of vision sensors.","PeriodicalId":272227,"journal":{"name":"2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125277025","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
Path planning of mobile robot based on deep reinforcement learning with transfer learning strategy 基于迁移学习策略的深度强化学习移动机器人路径规划
2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023708
Jie Zhu, Chuanhai Yang, Zhaodong Liu, Chengdong Yang
{"title":"Path planning of mobile robot based on deep reinforcement learning with transfer learning strategy","authors":"Jie Zhu, Chuanhai Yang, Zhaodong Liu, Chengdong Yang","doi":"10.1109/YAC57282.2022.10023708","DOIUrl":"https://doi.org/10.1109/YAC57282.2022.10023708","url":null,"abstract":"Under complex environments, mobile robots can decision-making, autonomous learning, intelligent obstacle avoidance, and complete the task from start point to endpoint. This paper designed the mobile robot, excluding planners and unknown maps, which can successfully reach the target by autonomously learning and navigating in the unknown environment. By applying deep reinforcement learning to the path planning of mobile robots, the robot can collect data and conduct training on its own, and improve it autonomously without manual supervision. Consequently, it can complete the path planning task. The application of transfer learning improves the adaptive efficiency of the mobile robot to the environment. Finally, the results are verified by comparative experiments in three simulation environments.","PeriodicalId":272227,"journal":{"name":"2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127552454","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
Impedance and Trajectory Adaptation for Contact Robots Using Integral Reinforcement Learning 基于积分强化学习的接触式机器人阻抗和轨迹自适应
2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023727
Guangzhu Peng, Chenguang Yang, Yanan Li, C. L. Philip Chen
{"title":"Impedance and Trajectory Adaptation for Contact Robots Using Integral Reinforcement Learning","authors":"Guangzhu Peng, Chenguang Yang, Yanan Li, C. L. Philip Chen","doi":"10.1109/YAC57282.2022.10023727","DOIUrl":"https://doi.org/10.1109/YAC57282.2022.10023727","url":null,"abstract":"In this paper, we develop a learning controller that adapts and tracks the impedance and trajectory for robots interacting with unknown environments. Impedance adaptation is used to compensate for contacting with the environment, while the reference trajectory learning is to maintain a prescribed interaction force. The tracking performance is ensured by an adaptive learning controller with Integral Reinforcement learning (IRL) for partially unknown system dynamics. The contact dynamics are analysed via Lyapunov theory and the effectiveness of the proposed control method is verified through simulations.","PeriodicalId":272227,"journal":{"name":"2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122902301","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
Adaptive neural network control for active suspension systems with asymmetric time-varying output constraints 非对称时变输出约束下主动悬架系统的自适应神经网络控制
2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023813
Jiawei Peng, Yinlong Hu, Qiyu Zhang, Hui Zhou, Tian Hua, Changjun Cheng
{"title":"Adaptive neural network control for active suspension systems with asymmetric time-varying output constraints","authors":"Jiawei Peng, Yinlong Hu, Qiyu Zhang, Hui Zhou, Tian Hua, Changjun Cheng","doi":"10.1109/YAC57282.2022.10023813","DOIUrl":"https://doi.org/10.1109/YAC57282.2022.10023813","url":null,"abstract":"In this paper, the influence of asymmetric vertical motion of the car on suspension dynamic performance is studied. An adaptive neural network control scheme with asymmetric time-varying displacement and speed constraints in the vertical direction is proposed, which is aimed to insulate the car from the impact of the road. Firstly, the asymmetric time-varying Barrier Lyapunov functions (ATBLFs) are constructed to prevent the car from surpassing the constraints. Moreover, taking the variance of the car-body mass into account, the radical basis function (RBF) neural networks are adopted to approximate the part related to the uncertain car-body mass. The stability of the closed-loop system is then demonstrated. Finally, to verify whether the proposed control scheme is effective, numerical simulations of the quarter-car Active suspension systems (ASSs) are provided.","PeriodicalId":272227,"journal":{"name":"2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123021761","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
Gait recognition for exoskeleton robots based on improved KNN-DAGSVM fusion algorithm 基于改进KNN-DAGSVM融合算法的外骨骼机器人步态识别
2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023588
Hao Xing, Rui Zhang
{"title":"Gait recognition for exoskeleton robots based on improved KNN-DAGSVM fusion algorithm","authors":"Hao Xing, Rui Zhang","doi":"10.1109/YAC57282.2022.10023588","DOIUrl":"https://doi.org/10.1109/YAC57282.2022.10023588","url":null,"abstract":"Currently exoskeleton robots have a wide range of applications in medical bionics, and care projects for the elderly and disabled. The recognition accuracy of human gait and the real-time performance of the system remain to be improved with urgent need. The conventional KNN method and the DAGSVM algorithm for gait detection are used in this research to divide a whole gait cycle of a human walking on level ground into five stages. It proposes a joint fusion algorithm (im-proved KNN-DAGSVM algorithm) on the basis of KNN algorithm and DAGSVM algorithm. The results reveal that the im-proved KNN-DAGSVM algorithm can successfully improve the recognition rate while shortening identification time.","PeriodicalId":272227,"journal":{"name":"2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131357910","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
ESN-Based Multi-Condition Model Predictive Control Method for Chemical Processes 基于esn的化工过程多条件模型预测控制方法
2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023880
Yu Miao, Hongguang Li, Yang Bo
{"title":"ESN-Based Multi-Condition Model Predictive Control Method for Chemical Processes","authors":"Yu Miao, Hongguang Li, Yang Bo","doi":"10.1109/YAC57282.2022.10023880","DOIUrl":"https://doi.org/10.1109/YAC57282.2022.10023880","url":null,"abstract":"In both academia and industry, it is shown that model predictive control is very effective for handling complex chemical processes with nonlinearities and large time lags. However, the establishment of predictive models usually requires online test experiments and affects normal production. In addition, chemical processes can be affected by feedstock conditions and scheduling strategies to generate multiple operating conditions, which can cause large deviations in a single predictive model. In the face of these problems, this paper proposes a data-driven deep learning-based predictive control method for chemical process models with multiple operating conditions. Multi-parallel ESN are trained with historical data of different operating conditions to integrate a data-driven prediction model. Based on the LM algorithm, the objective function is solved by rolling optimization of the working conditions for the future response of the controlled object, and the optimal control strategy is obtained. A distillation tower simulation model is used as the object. Simulation experiments are conducted for the proposed method, and satisfactory control effects are obtained to verify the effectiveness of the method.","PeriodicalId":272227,"journal":{"name":"2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121269702","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
Selective Data Collection Method for Deep Reinforcement Learning 深度强化学习的选择性数据收集方法
2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023607
Tao Wang, Haiyang Yang, Zhiyong Tan, Yao Yu
{"title":"Selective Data Collection Method for Deep Reinforcement Learning","authors":"Tao Wang, Haiyang Yang, Zhiyong Tan, Yao Yu","doi":"10.1109/YAC57282.2022.10023607","DOIUrl":"https://doi.org/10.1109/YAC57282.2022.10023607","url":null,"abstract":"In deep reinforcement learning, reinforcement learning is responsible for interacting with the environment to produce data, and artificial neural networks are responsible for value function fitting. It is observed that artificial neural networks converged differently to different inputs, which, in our analysis, is due to imbalanced data. Therefore, we propose selective data collection to boost the quality of the data by then discarding the excess data. It has been proved experimentally that our method can significantly contribute to the convergence rate of the reinforcement learning algorithm.","PeriodicalId":272227,"journal":{"name":"2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127835020","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
Requirement of Production Simulation of DC Distribution Network Containing High Renewable Energy 含高可再生能源直流配电网生产仿真的要求
2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023613
Man Li, Yi Zhang, Yan Li, Xiaoxue Li, Bo Fan, Lifeng Li, Yanmei Li, Yuan Hu
{"title":"Requirement of Production Simulation of DC Distribution Network Containing High Renewable Energy","authors":"Man Li, Yi Zhang, Yan Li, Xiaoxue Li, Bo Fan, Lifeng Li, Yanmei Li, Yuan Hu","doi":"10.1109/YAC57282.2022.10023613","DOIUrl":"https://doi.org/10.1109/YAC57282.2022.10023613","url":null,"abstract":"Renewable energy power generation connected to the DC distribution network, converter station capacity, renewable energy installed capacity and renewable energy operation mode are the primary factors that affect the maximum consumption of renewable energy. Unreasonable converter station capacity and renewable energy installed capacity planning and configuration will result in excessive renewable energy installed capacity, resulting in abandonment of wind and light, or too small installed capacity to make the converter station with full using. The renewable energy power generation operation mode strategy directly affects the DC distribution network transmission capacity and the regulation capacity of the energy storage station, which in turn affects the consumption of renewable energy power generation. The paper studies relevant time series modeling methods of wind and PV power generation, and proposes the technical requirements for optimizing the power generation operation mode considering the hybrid of multiple types of renewable energy and the DC distribution network, so as to achieve maximum consumption renewable energy, and to ensure that the power of renewable energy can be “controlled and consumed’', and ultimately ensure the stable operation and safe of renewable energy and the DC distribution network. The paper results will provide support for the future planning of the local consumption of a high proportion of renewable energy, and will effectively guide the planning and design of renewable energy and DC distribution networks.","PeriodicalId":272227,"journal":{"name":"2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"164 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133289923","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 Multi-Kernel Principal Component Analysis Method for Quality-Related Fault Detection 质量相关故障检测的多核主成分分析方法
2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023777
Lingxia Mu, Biyu Lei, Ding Liu
{"title":"A Multi-Kernel Principal Component Analysis Method for Quality-Related Fault Detection","authors":"Lingxia Mu, Biyu Lei, Ding Liu","doi":"10.1109/YAC57282.2022.10023777","DOIUrl":"https://doi.org/10.1109/YAC57282.2022.10023777","url":null,"abstract":"In this paper, a multi-kernel principal component analysis (MKPCA) method for quality-related fault detection is proposed. The initial space is firstly mapped to a new space. The correlated information between the new space and output quality is then obtained by the kernel function. Meanwhile, with consideration of the advantage of global function and local function, a weight factor which combines them together is introduced to construct a multi-kernel function. In this way, the algorithm achieves better learning ability. The new space is projected to two mutually orthogonal subspaces, i.e., quality-related part and quality-unrelated part. In each subspace, fault information is expressed by different statistical indicators. The numerical example is presented to evaluate the performance of the MKPCA. The results show better reliability and high fault detection rate through proper spatial decomposition and kernel function construction.","PeriodicalId":272227,"journal":{"name":"2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"198 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134031714","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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