2022 7th International Conference on Control, Robotics and Cybernetics (CRC)最新文献

Design and Implementation of SysML Activity Diagram Simulation Function Based on fUML Specification 基于uml规范的SysML活动图仿真功能的设计与实现

2022 7th International Conference on Control, Robotics and Cybernetics (CRC) Pub Date : 2022-12-15 DOI: 10.1109/CRC55853.2022.10041232

Bo Huang, Yubiao Liu, Xinfeng Wu, Jiyuan Lv, Yusheng Liu

引用次数: 0

Finite-Time Resilient Formation Tracking Control of Multiple Nonholonomic Mobile Robots with Communication Link Attacks 具有通信链路攻击的多非完整移动机器人有限时间弹性编队跟踪控制

2022 7th International Conference on Control, Robotics and Cybernetics (CRC) Pub Date : 2022-12-15 DOI: 10.1109/CRC55853.2022.10041233

Yani Wang, Minyin Lu, Xinran Yu, An‐Min Zou

引用次数: 1

Realization of High-speed Serial Data to Parallel Data in Digital Camera 数字相机中高速串行数据到并行数据的实现

2022 7th International Conference on Control, Robotics and Cybernetics (CRC) Pub Date : 2022-12-15 DOI: 10.1109/CRC55853.2022.10041236

Guangkuo Zhang, Hailong Huo, Xiangzhong Zeng, F. Zhao

引用次数: 0

Path Planning for Collaborative Robot under Complex Biomedical Lab Environment 复杂生物医学实验室环境下协同机器人路径规划

2022 7th International Conference on Control, Robotics and Cybernetics (CRC) Pub Date : 2022-12-15 DOI: 10.1109/CRC55853.2022.10041198

Zhijie Pan, Mengtang Li

引用次数: 0

Event Tubelet Compressor: Generating Compact Representations for Event-Based Action Recognition 事件管状压缩器:为基于事件的动作识别生成紧凑的表示

2022 7th International Conference on Control, Robotics and Cybernetics (CRC) Pub Date : 2022-12-15 DOI: 10.1109/CRC55853.2022.10041200

Bochen Xie, Yongjian Deng, Z. Shao, Hai Liu, Qingsong Xu, Youfu Li

{"title":"Event Tubelet Compressor: Generating Compact Representations for Event-Based Action Recognition","authors":"Bochen Xie, Yongjian Deng, Z. Shao, Hai Liu, Qingsong Xu, Youfu Li","doi":"10.1109/CRC55853.2022.10041200","DOIUrl":"https://doi.org/10.1109/CRC55853.2022.10041200","url":null,"abstract":"Event cameras asynchronously capture pixel-level intensity changes in scenes and output a stream of events. Compared with traditional frame-based cameras, they can offer competitive imaging characteristics: low latency, high dynamic range, and low power consumption. It means that event cameras are ideal for vision tasks in dynamic scenarios, such as human action recognition. The best-performing event-based algorithms convert events into frame-based representations and feed them into existing learning models. However, generating informative frames for long-duration event streams is still a challenge since event cameras work asynchronously without a fixed frame rate. In this work, we propose a novel frame-based representation named Compact Event Image (CEI) for action recognition. This representation is generated by a self-attention based module named Event Tubelet Compressor (EVTC) in a learnable way. The EVTC module adaptively summarizes the long-term dynamics and temporal patterns of events into a CEI frame set. We can combine EVTC with conventional video backbones for end-to-end event-based action recognition. We evaluate our approach on three benchmark datasets, and experimental results show it outperforms state-of-the-art methods by a large margin.","PeriodicalId":275933,"journal":{"name":"2022 7th International Conference on Control, Robotics and Cybernetics (CRC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125791024","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

Supervised Latent Variable Model with Gaussian Inner Structure for Dynamic PROCESS 动态过程的高斯内结构监督潜变量模型

2022 7th International Conference on Control, Robotics and Cybernetics (CRC) Pub Date : 2022-12-15 DOI: 10.1109/CRC55853.2022.10041235

Xiaoyu Sun, Jianchang Liu, Xia Yu, Honghai Wang, Shubin Tan

{"title":"Supervised Latent Variable Model with Gaussian Inner Structure for Dynamic PROCESS","authors":"Xiaoyu Sun, Jianchang Liu, Xia Yu, Honghai Wang, Shubin Tan","doi":"10.1109/CRC55853.2022.10041235","DOIUrl":"https://doi.org/10.1109/CRC55853.2022.10041235","url":null,"abstract":"Supervised multivariate statistical techniques are important tools for modeling the relationship between variables in dynamic processes. To building the dynamic relationship between variables, a supervised dynamic latent variable (LV) model with Gaussian inner structure is proposed to extract explicit LVs from the process and quality data with high collinearity. The outer dynamic latent structure gains stronger prediction ability by paying attention to both the variance and covariance of data while extracting LVs from the process and quality data. As a Gaussian process, the inner model is directly estimated as a function that is searched for within an infinite-dimensional space, such that an inner model with appropriate model order is obtained. Besides, the properties of the inner structure, such as exponential stability and smoothness, are integrated into the process of identifying the Gaussian model. As a result, the prediction capability of the proposed supervised LV model is enhanced. What's more, it is easy to interpret the results obtained by the proposed model as the dynamic LVs are directly extracted from the original process and quality data matrices rather than the augmented data matrices. The efficiency of the proposed model is demonstrated by modeling the glycemic dynamics of people with type 1 diabetes.","PeriodicalId":275933,"journal":{"name":"2022 7th International Conference on Control, Robotics and Cybernetics (CRC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129208534","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

Distributed Fixed-time Bipartite Containment Control of Multi-agent Systems with Unknown Disturbances 具有未知干扰的多智能体系统的分布式固定时间二部约束控制

2022 7th International Conference on Control, Robotics and Cybernetics (CRC) Pub Date : 2022-12-15 DOI: 10.1109/CRC55853.2022.10041227

Shuguang Xin, Mengji Shi, Weihao Li, Jiangfeng Yue, Boxian Lin, Kaiyu Qin

引用次数: 0

Command Pattern-based MOF Design and Testing 基于命令模式的MOF设计与测试

2022 7th International Conference on Control, Robotics and Cybernetics (CRC) Pub Date : 2022-12-15 DOI: 10.1109/CRC55853.2022.10041228

Minghui Liu, Chenchuan Zhou, Xin Wu, Jiyuan Lv, Yusheng Liu

引用次数: 0

Study of Deck Motion Prediction Based on Adaptive Forgetting Least Squares Algorithm 基于自适应遗忘最小二乘算法的甲板运动预测研究

2022 7th International Conference on Control, Robotics and Cybernetics (CRC) Pub Date : 2022-12-15 DOI: 10.1109/CRC55853.2022.10041237

X. Wang, Qidan Zhu

引用次数: 0

Backstepping Terminal Sliding Mode Control of FOG Inertial Platform Stability Loop Based on Extended State Observer 基于扩展状态观测器的光纤陀螺惯性平台稳定环反步末端滑模控制

2022 7th International Conference on Control, Robotics and Cybernetics (CRC) Pub Date : 2022-12-15 DOI: 10.1109/CRC55853.2022.10041229

Hongwu Liu, Shuling Hu, Qingzhong Cai, Yongfeng Zhang, Kun Zhang

{"title":"Backstepping Terminal Sliding Mode Control of FOG Inertial Platform Stability Loop Based on Extended State Observer","authors":"Hongwu Liu, Shuling Hu, Qingzhong Cai, Yongfeng Zhang, Kun Zhang","doi":"10.1109/CRC55853.2022.10041229","DOIUrl":"https://doi.org/10.1109/CRC55853.2022.10041229","url":null,"abstract":"To realize the high-precision control of the inertial platform of fiber optic gyroscope (FOG) under the influence of multi-source nonlinear disturbance torques, a backstepping terminal sliding mode control method for the FOG inertial platform stability loop based on the extended state observer was proposed. Firstly, the mathematical model of velocity loop control and position loop control of the inertial platform stability loop was established by using FOG as the sensitive element. Secondly, the backstepping terminal sliding mode control law was designed, and the extended state observer was used to estimate the disturbances and unknown states of the velocity loop and position loop respectively. The chattering caused by the sliding mode control law was reduced. This method is compared with the traditional PID single-loop control method. Under the same disturbance, the results show that the maximum rotation angle of the platform body axis caused by step disturbance is reduced 12.6” and the amplitude of the rotation angle of the platform axis caused by sinusoidal disturbance is reduced 11.34”. The stability loop using the backstepping terminal sliding mode control law based on the extended state observer has high stability accuracy and strong anti-interference ability.","PeriodicalId":275933,"journal":{"name":"2022 7th International Conference on Control, Robotics and Cybernetics (CRC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116601719","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