2022 22nd International Conference on Control, Automation and Systems (ICCAS)最新文献_第9页

Practical finite-time stability of homogeneous positive nonlinear systems 齐次正非线性系统的实用有限时间稳定性

2022 22nd International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2022-11-27 DOI: 10.23919/ICCAS55662.2022.10003800

Mengqian Liang, Yazhou Tian

引用次数: 0

Comparing the Effects of Admittance and Error-based Control of a Trunk Rehabilitation Robot on the User’s Balance 比较躯干康复机器人导纳与误差控制对使用者平衡的影响

2022 22nd International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2022-11-27 DOI: 10.23919/ICCAS55662.2022.10003759

Hosu Lee, Amre Eizad, Junyeong Lee, Yunho Choi, Won-Kyung Song, Kyung-Joong Kim, Jungwon Yoon

{"title":"Comparing the Effects of Admittance and Error-based Control of a Trunk Rehabilitation Robot on the User’s Balance","authors":"Hosu Lee, Amre Eizad, Junyeong Lee, Yunho Choi, Won-Kyung Song, Kyung-Joong Kim, Jungwon Yoon","doi":"10.23919/ICCAS55662.2022.10003759","DOIUrl":"https://doi.org/10.23919/ICCAS55662.2022.10003759","url":null,"abstract":"Trunk training is an important part of the rehabilitation of people suffering from the physical effects of brain lesions caused by diseases such as stroke, as it can help improve their static and dynamic balance, while also helping to improve gait performance. In order to facilitate trunk rehabilitation and reduce therapist workload, we have developed a trunk rehabilitation robot (TRR) that can provide tunable quantitative training with the option to include sensory augmentation through various bio-feedback, in order to implement a large variety of trunk training protocols. In this paper, we have developed an error-based controller to generate the unstable seat condition using the TRR. In order to verify the feasibility of this controller, we have carried out tests with 20 young healthy subjects and compared its performance with the existing admittance controller in terms of seat movement parameters and center of pressure and trunk movement based balance parameters. The results show that although there is no statistically significant difference between the controllers in terms of the balance measures, use of the error-based controller results in lesser amount of seat movement, which may make it more comfortable for the user. However, the participants had a difference of opinion about which controller they felt to be more comfortable and easier to use.","PeriodicalId":129856,"journal":{"name":"2022 22nd International Conference on Control, Automation and Systems (ICCAS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125388875","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

Visual-Inertial Odometry Priors for Bundle-Adjusting Neural Radiance Fields 束调节神经辐射场的视觉惯性测程先验

2022 22nd International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2022-11-27 DOI: 10.23919/ICCAS55662.2022.10003959

H. Kim, Minkyeong Song, Daekyeong Lee, Pyojin Kim

引用次数: 2

A Novel Technique For Indoor Object Distance Measurement By Using 3D Point Cloud and LiDAR 基于三维点云和激光雷达的室内目标距离测量新技术

2022 22nd International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2022-11-27 DOI: 10.23919/ICCAS55662.2022.10003884

Jisoo Kim, Dongik Lee

引用次数: 1

Three-dimensional Multi-missile Cooperative Guidance Law with Time and Space Constraints 具有时空约束的三维多弹协同制导律

2022 22nd International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2022-11-27 DOI: 10.23919/ICCAS55662.2022.10003825

Jian Meng, Zhen Yang, Jichuan Huang, Haiyin Piao, Yiyang Zhao, Deyun Zhou

{"title":"Three-dimensional Multi-missile Cooperative Guidance Law with Time and Space Constraints","authors":"Jian Meng, Zhen Yang, Jichuan Huang, Haiyin Piao, Yiyang Zhao, Deyun Zhou","doi":"10.23919/ICCAS55662.2022.10003825","DOIUrl":"https://doi.org/10.23919/ICCAS55662.2022.10003825","url":null,"abstract":"This study focuses on the problem of multiple air-to-air missiles coordinated intercepting maneuvering targets in three-dimensional (3-D) space. A fixed time cooperative interception law with attack time and line-of-sight (LOS) angle limitations is proposed. Firstly, we extended the commonly used two-dimensional (2-D) space guidance model to 3-D space, and constructs a 3-D missile-target relative motion model. Secondly, the missile guidance model is decoupled to along and perpendicular to the LOS, and in the LOS direction, a cooperative guiding law based on fixed-time consistency theory is intended to guarantee that all missiles strikes the target at the same moment. Moreover, in the LOS normal direction, an adaptive approach rule is created, and the LOS angle of each missile is regulated to reaching to a given value in a defined time. According to the proposed fixed time fast non-singular terminal sliding mode surface, and spatial coordination is accomplished. In addition, based on Lyapunov stability theory, a detailed fixed time stability analysis is given. In the end, simulation is used to verify the feasibility and efficacy of the guideline law.","PeriodicalId":129856,"journal":{"name":"2022 22nd International Conference on Control, Automation and Systems (ICCAS)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126005318","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

Development of Self-Training Algorithm for Predicting Mango Maturity 芒果成熟度预测自训练算法的发展

2022 22nd International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2022-11-27 DOI: 10.23919/ICCAS55662.2022.10003751

Nguyen Minh Trieu, Nguyen Truong Thinh

引用次数: 0

Combination of Deep Learner Network and Transformer for 3D Human Pose Estimation 结合深度学习网络和变压器的三维人体姿态估计

2022 22nd International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2022-11-27 DOI: 10.23919/ICCAS55662.2022.10003954

T. Tran, Xuan-Thuy Vo, Duy-Linh Nguyen, K. Jo

{"title":"Combination of Deep Learner Network and Transformer for 3D Human Pose Estimation","authors":"T. Tran, Xuan-Thuy Vo, Duy-Linh Nguyen, K. Jo","doi":"10.23919/ICCAS55662.2022.10003954","DOIUrl":"https://doi.org/10.23919/ICCAS55662.2022.10003954","url":null,"abstract":"Deep neural networks (DNNs) have attained the maximum performance today not just for human pose estimation but also for other machine vision applications (e.g., semantic segmentation, object detection, image classification). Besides, the Transformer shows its good performance for extracting the information in temporal information for video challenges. As a result, the combination of deep learner and transformer gains a better performance than only the utility one, especially for 3D human pose estimation. At the start point, input the 2D key point into the deep learner layer and transformer and then use the additional function to combine the extracted information. Finally, the network collects more data in terms of using the fully connected layer to generate the 3D human pose which makes the result increased precision efficiency. Our research would also reveal the relationship between the use of the deep learner and transformer. When compared to the baseline-DNNs, the suggested architecture outperforms the baseline-DNNs average error under Protocol 1 and Protocol 2 in the Human3.6M dataset, which is now available as a popular dataset for 3D human pose estimation.","PeriodicalId":129856,"journal":{"name":"2022 22nd International Conference on Control, Automation and Systems (ICCAS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124325200","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: 1

Image classification using DETR based object-level feature 基于对象级特征的DETR图像分类

2022 22nd International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2022-11-27 DOI: 10.23919/ICCAS55662.2022.10003912

Chung-Gi Ban, Dayoung Park, Youngbae Hwang

引用次数: 0

Adapting Masking Network for Bloom Identification Number Recognition to Different Domains 基于掩模网络的多域布隆识别码识别

2022 22nd International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2022-11-27 DOI: 10.23919/ICCAS55662.2022.10003768

Wonseok Jeong, Hyeyeon Choi, Bum Jun Kim, Hyeonah Jang, Dong Gu Lee, Donggeon Lee, Sang Woo Kim

{"title":"Adapting Masking Network for Bloom Identification Number Recognition to Different Domains","authors":"Wonseok Jeong, Hyeyeon Choi, Bum Jun Kim, Hyeonah Jang, Dong Gu Lee, Donggeon Lee, Sang Woo Kim","doi":"10.23919/ICCAS55662.2022.10003768","DOIUrl":"https://doi.org/10.23919/ICCAS55662.2022.10003768","url":null,"abstract":"These days, there are lots of smart factories with automatic systems that improve the factory’s manufacturing efficiency. One of the systems is product identification number recognition. In this study, we handled Bloom Identification Number (BIN) which is common in steel industries. For our BIN recognition algorithm, we adopted deep learning because it outperforms conventional algorithms in many computer vision tasks. Furthermore, applying a trained deep learning model to another factory is a big issue because data from different factories can look alike to us, but the trained models might confuse them because of the difference in background, light condition, and camera position. For this reason, new label annotations are required to train the model once again. However, label annotations will always be a big burden whenever applying a trained model to different factories. In this paper, we introduce a new method of BIN recognition that does not require data labeling of new data when training. This gives us the advantage of eliminating the time of labeling new collected data when applying the deep learning network to other factories.","PeriodicalId":129856,"journal":{"name":"2022 22nd International Conference on Control, Automation and Systems (ICCAS)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123414913","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: 1

Group Estimation for Social Robot Navigation in Crowded Environments 拥挤环境下社交机器人导航的群体估计

2022 22nd International Conference on Control, Automation and Systems (ICCAS) Pub Date : 2022-11-27 DOI: 10.23919/ICCAS55662.2022.10003761

Mincheul Kim, Youngsun Kwon, Sung-eui Yoon

{"title":"Group Estimation for Social Robot Navigation in Crowded Environments","authors":"Mincheul Kim, Youngsun Kwon, Sung-eui Yoon","doi":"10.23919/ICCAS55662.2022.10003761","DOIUrl":"https://doi.org/10.23919/ICCAS55662.2022.10003761","url":null,"abstract":"Socially acceptable navigation in a crowded environment is a challenging problem in robotics due to diverse and unknown human intent. Previous studies have dealt with the social navigation problem in dense crowds via multi-robot collision avoidance. However, it is intractable to follow social compliant trajectory since human-robot interaction differs from the multi-robot collision avoidance problem. To approach our goal, this work exploits a human behavior model and focuses on social group actions such as walking together. We observed that human recognizes the other human groups and avoids them during navigation while maintaining social distances. Based on this observation, this paper proposes a social robot navigation method under group space estimation of crowds on a deep reinforcement learning framework. The proposed method estimates the social groups of crowds based on the behavioral similarities in sensory information. Our reinforcement learning framework learns a socially compliant and effective navigation policy through the proposed human group-aware reward. Our experiment in a crowd simulation demonstrates that the proposed approach generates a human-friendly trajectory with improved navigation performance.","PeriodicalId":129856,"journal":{"name":"2022 22nd International Conference on Control, Automation and Systems (ICCAS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131936407","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