2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)最新文献_第7页

An Improved RRT Robot Autonomous Exploration and SLAM Construction Method 一种改进的RRT机器人自主探索与SLAM构建方法

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230216

Zeyu Tian, Chen Guo, Yi Liu, Jiting Chen

{"title":"An Improved RRT Robot Autonomous Exploration and SLAM Construction Method","authors":"Zeyu Tian, Chen Guo, Yi Liu, Jiting Chen","doi":"10.1109/CACRE50138.2020.9230216","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230216","url":null,"abstract":"When the indoor environment is unknown, how to make robots carry out effective autonomous exploration and construct related maps is one of the key issues in the field of mobile robots. In view of the fact that the real-world environment is usually partially observable and uncertain, an improved method of autonomous exploration and SLAM construction based on Rapid-exploration Random Tree (RRT) is proposed. In the local RRT exploration part, the autonomous exploration problem is regarded as a partially observable Markov decision process (POMDP) problem. Boundary points are extracted in the boundary area of known space and unknown space, and the robot is directed to the unexplored area. At the same time, during the exploration process, the global RRT tree with adaptive step values is established to explore the boundary points at the far end of the robot. The two methods are merged to speed up the search for boundary points. After the best advantage is obtained, the robot is continuously moved to the best advantage through closed-loop control. Based on the original construction of a 2D grid map, a “parallel construction” idea was proposed to construct a 3D octree map at the same time. The effectiveness of the proposed method is verified by simulation experiments and actual scenarios in a robot operating system (ROS).","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"40 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131956937","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: 7

Intelligent state evaluation method of marine engine room system 船舶机舱系统状态智能评估方法

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230286

Hui Cao, Yifan Liu, Yiru Wang, Ran Li

{"title":"Intelligent state evaluation method of marine engine room system","authors":"Hui Cao, Yifan Liu, Yiru Wang, Ran Li","doi":"10.1109/CACRE50138.2020.9230286","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230286","url":null,"abstract":"Based on system state classification and recognition, an intelligent state evaluation method was proposed for the intelligent maintenance and management in marine engine room. The method can be adopted to realize the condition-based maintenance and improve the efficiency and safety of ship operation. First, the radial basis function neural network was used to establish the state identification model of the marine engine room system to realize the state classification and identification of the system; Second, the recognized state was evaluated comprehensively by using the fuzzy analytical hierarchy process method; Finally, the validity of the results of the state identification and the fuzzy comprehensive evaluation was verified based on an actual ship system data. With the support of the system state data, the evaluation result shows a good match with the actual system state and has a high degree of credibility. On the premise of convenient data collection, the proposed method can further conduct a large-scale system state evaluation for multiple marine engine room systems. The process of the method proposed provides a new idea for the application of intelligent technology in the field of ships.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126803681","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 five-way directional soft valve with a case study: a starfish like soft robot 一种五通定向软阀用案例研究:海星状软机器人

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230177

Jiakang Zou, Mengke Yang, Guoqing Jin

引用次数: 3

Cooperative Level Curve Tracking in Advection-Diffusion Fields 平流-扩散场的协同水平曲线跟踪

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230059

Sachin Guruswamy, Wencen Wu

引用次数: 2

Spatial Pooling Network For Lane Line Segmentation 车道线分割的空间池化网络

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230089

Yanteng Ge, Yangyang Chen, Faxiang Zhang

引用次数: 0

ArUco Marker Detection under Occlusion Using Convolutional Neural Network 基于卷积神经网络的遮挡下ArUco标记检测

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230250

Boxuan Li, Jiezhang Wu, X. Tan, Benfei Wang

{"title":"ArUco Marker Detection under Occlusion Using Convolutional Neural Network","authors":"Boxuan Li, Jiezhang Wu, X. Tan, Benfei Wang","doi":"10.1109/CACRE50138.2020.9230250","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230250","url":null,"abstract":"Camera pose estimation is a significant warranty during Unmanned Aerial Vehicle (UAV) autonomous landing process. Fiducial marker system is a popular method to offer relatively precise pose information. However, square-based markers are unreliable under occlusion condition, especially when their corners are covered by unexpected disturbances. This study proposes a novel method to detect fiducial markers using neural network. The method is developed based on Convolutional Neural Network (CNN) and achieves outstanding results under various occlusion conditions, including different cover shapes and ratios. YOLOv3, along with its improved version YOLOv3-spp and its lightweight version YOLOv3-tiny, are applied as the marker detector. Compared to the traditional ArUco fiducial marker system, CNN architectures are more robust and stable in extreme environment. Performance of three different CNN models is quantified as marker detection rate. This work validates the feasibility of square-based fiducial marker localization employing CNN architecture, and reveals the potential of deep learning method in the field of fiducial marker detection and recognition.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114632316","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: 11

Remote Human-robot Collaborative Impedance Control Strategy of Pharyngeal Swab Sampling Robot 咽拭子采样机器人的远程人机协同阻抗控制策略

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230152

Yinglong Chen, Fu-Jun Song, Yongjun Gong

{"title":"Remote Human-robot Collaborative Impedance Control Strategy of Pharyngeal Swab Sampling Robot","authors":"Yinglong Chen, Fu-Jun Song, Yongjun Gong","doi":"10.1109/CACRE50138.2020.9230152","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230152","url":null,"abstract":"Pharyngeal swab sampling, as an essential link in the detection of COVID-19, is characterized by the large task volume and susceptibility to infection. Therefore, it is necessary to use medical robots for remote sampling instead of in-situ sampling. However, on one hand, due to the influence of network delay, it is difficult to guarantee the closed-loop performance manipulated remotely by medical practitioners. On the other hand, the sampling process controlled by the robot independently is not always successful due to the inaccuracy of the planned trajectory caused by the sensors or the moment of the patients. To solve the problems discussed above, this paper proposed a remote human-robot collaborative strategy based on impedance control method, which can integrate the experience of medical practitioners into the automatic sampling process. During the sampling process, when the inaccurate scanning trajectory is detected, the medical practitioners can correct the planned trajectory on line according to the sensor information and the reaction of the patients. Then, the cooperative robot tracks the adjusted planned-trajectory based on the impedance control method and ensure that the contact force of sampling is maintained within a reasonable range. The simulation results show that the proposed human-robot collaborative strategy is effective taking the advantages of both medical practitioners and robots which can deal with the trajectory tracking problem caused by the inaccurate sampling of patients.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"346 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116658983","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: 6

Reducing Caregiver’s Physical Strain in Manual Patient Transfer with Robot Support 在机器人支持下减少人工病人转移中护理人员的身体压力

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230324

Conrad Fifelski-von Böhlen, Anna Brinkmann, C. Kowalski, Ole Meyer, S. Hellmers, A. Hein

引用次数: 4

A Study of Workpiece Targeting Based on Improved Blob Analysis 基于改进斑点分析的工件定位研究

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230129

Wei Chen, Zechen Li, Jing Zhang, BaiCheng Yi

引用次数: 1

Quantized Control of Networked Control Systems with Multiplicative Noises via Event-Triggered Scheme 基于事件触发机制的乘性噪声网络控制系统的量化控制

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230046

Hong‐Du Wang, Yan Liu, M. Karkoub, Lin Yuan

引用次数: 2