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2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA)最新文献

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All-Attitude Motion Tracking Estimation Based on Euler Angles Using MARG Sensors 基于欧拉角的MARG传感器全姿态运动跟踪估计
2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA) Pub Date : 2019-08-01 DOI: 10.1109/WRC-SARA.2019.8931925
Xiaolong Xu, Xincheng Tian, Lelai Zhou
{"title":"All-Attitude Motion Tracking Estimation Based on Euler Angles Using MARG Sensors","authors":"Xiaolong Xu, Xincheng Tian, Lelai Zhou","doi":"10.1109/WRC-SARA.2019.8931925","DOIUrl":"https://doi.org/10.1109/WRC-SARA.2019.8931925","url":null,"abstract":"An all-attitude motion tracking algorithm based on Euler angles is proposed in this paper. In addition to the procedure of sensor bias compensation, a gating mechanism is established to guard against the effects that body motion and temporary magnetic disturbance may have on the reliability of sensors’ measurements. The proposed method resolves the attitude distortion and oscillation caused by the gimbal lock problem. Thus, it can be applied to all-attitude analysis. The varied gravitational acceleration has no influence on solving Euler angles. An improved Kalman filter is designed to remove the dynamic drift of gyroscopes and fuse measurements of MARG sensors to obtain accurate attitude angles. The static and dynamic performance of this method have been verified and evaluated by a wearable AHRS and a gesture capture system. Results show that the proposed algorithm is immune to the motion acceleration and temporary magnetic disturbances. It can achieve <1.5° static error and <3° dynamic error.","PeriodicalId":236286,"journal":{"name":"2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123996999","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
Collision Detection Technology in Virtual Interventional Surgery 虚拟介入手术中的碰撞检测技术
2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA) Pub Date : 2019-08-01 DOI: 10.1109/WRC-SARA.2019.8931949
Jinlong Qi, Zhi Hu, Junfeng Zhang, G. Cui
{"title":"Collision Detection Technology in Virtual Interventional Surgery","authors":"Jinlong Qi, Zhi Hu, Junfeng Zhang, G. Cui","doi":"10.1109/WRC-SARA.2019.8931949","DOIUrl":"https://doi.org/10.1109/WRC-SARA.2019.8931949","url":null,"abstract":"Collision detection of the devices and virtual organs is the key to haptic rendering in virtual interventional surgery. Based on the collision characteristics of interventional surgery system, the virtual guide wire is established by using elastic rod model, and then the guide wire dynamics algorithm based on the physical model was given. The difficulty of collision detection between guide wire and blood vessel is analyzed, and a fast collision detection algorithm based on AABB tree was proposed. The experimental results show that the guide wire model can meet the deformation behavior of the guide wire, and the collision detection algorithm is suitable for collision detection of the complex vascular models, which can ensure the real-time and fidelity of the virtual vascular interventional surgery system, thus enabling doctors' perception and interaction with virtual environment more accurate and real.","PeriodicalId":236286,"journal":{"name":"2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123189926","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
Automatic Kidney CT Segmentation and Optimization Based on Self-Learning 基于自学习的肾脏CT自动分割与优化
2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA) Pub Date : 2019-08-01 DOI: 10.1109/WRC-SARA.2019.8931799
Yi Lv, Yingdong Xu, Xiaohui Zhang, Zhen Sun, Junchen Wang
{"title":"Automatic Kidney CT Segmentation and Optimization Based on Self-Learning","authors":"Yi Lv, Yingdong Xu, Xiaohui Zhang, Zhen Sun, Junchen Wang","doi":"10.1109/WRC-SARA.2019.8931799","DOIUrl":"https://doi.org/10.1109/WRC-SARA.2019.8931799","url":null,"abstract":"Medical image processing plays an increasingly important role in clinical diagnosis and treatment. Using the results of kidney CT image segmentation for three-dimensional reconstruction is an intuitive and accurate method for diagnosis. However, the performance of traditional image segmentation algorithms is unsatisfactory due to the large difference between the kidneys of patients and the noise of CT images, and the surface of the model reconstructed will be rough and deformed when the results are directly used for three-dimensional reconstruction. To improve this situation, we propose a segmentation, reconstruction and optimization system(SROS), which combines the auto segmentation of kidney CT sequence images and the optimization of three-dimensional reconstruction. According to the characteristics of U-Net, we improved it to be suitable for accomplishing our task. Firstly, we initialize the size and gray value range of CT image sequence. Secondly, we use sequence images and label images to train the network model. Thirdly, we use the trained network model to segment the sequence images. Finally, we use the model to optimize the reconstruction. The experimental results show that SROS has a good performance in terms of 3D reconstruction accuracy, smoothness and robustness.","PeriodicalId":236286,"journal":{"name":"2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123206762","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
Double-terminal Asynchronous Adaptive Event-Triggered Control Based on State Observer 基于状态观测器的双端异步自适应事件触发控制
2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA) Pub Date : 2019-08-01 DOI: 10.1109/WRC-SARA.2019.8931919
Mingsheng Li, Yang Yang, Xiaozhong Qi, Zhenxing Li
{"title":"Double-terminal Asynchronous Adaptive Event-Triggered Control Based on State Observer","authors":"Mingsheng Li, Yang Yang, Xiaozhong Qi, Zhenxing Li","doi":"10.1109/WRC-SARA.2019.8931919","DOIUrl":"https://doi.org/10.1109/WRC-SARA.2019.8931919","url":null,"abstract":"For a class of networked control systems(NCS) with network-induced delays, an event-triggered control method for asymptotically stable systems is proposed based on state observer and double-terminal asynchronous adaptive event-triggered mechanism when the system state cannot be measured directly. Firstly, to further reduce the triggering frequency of event-triggered mechanism and improve the utilization of network resources, adaptive event-triggered mechanism is added to sensor and controller side respectively. Secondly, a state observer is added to the controller to reconstruct the state of the system and send it to the controller. Then, the closed-loop time delay model of the system is established. Combined with linear matrix inequality and Lyapunov stability theory, the joint design method of controller and event-triggered mechanism is given. Finally, the validity of the proposed control method is verified by simulation.","PeriodicalId":236286,"journal":{"name":"2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA)","volume":"177 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121432523","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
Pose Analysis of Humanoid Robot Imitation Process Based on Improved MLP Network 基于改进MLP网络的仿人机器人仿真过程位姿分析
2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA) Pub Date : 2019-08-01 DOI: 10.1109/WRC-SARA.2019.8931970
Shuhuan Wen, Yang Liu, Leibo Zheng, F. Sun, Bin Fang
{"title":"Pose Analysis of Humanoid Robot Imitation Process Based on Improved MLP Network","authors":"Shuhuan Wen, Yang Liu, Leibo Zheng, F. Sun, Bin Fang","doi":"10.1109/WRC-SARA.2019.8931970","DOIUrl":"https://doi.org/10.1109/WRC-SARA.2019.8931970","url":null,"abstract":"This paper proposes a system, by which humanoid robots could imitate human movements to learn human behaviors. Considering the security problem during humanoid robot imitation process, a method of stability identification based on improved Multi-Layer Perception (MLP) is proposed. Firstly, the positions of the human joints are collected by a Kinect. Secondly, the human joints information is transformed into robot angles information by the inverse kinematics equation. Finally, the stability of the robot is identified by the deep neural network, which has the robot angles as its input. Simulations and experimental results demonstrate that compared with the Back Propagation neural network (BPnn), RBF neural network (RBFnn), Support Vector Machine (SVM) and Extreme Learning Machine (ELM), MLP neural network has the best identification accuracy. And the filters we used can overcome the problem of speed pulse, to some extent, and achieved an ideal imitation result.","PeriodicalId":236286,"journal":{"name":"2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133594698","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
Anchor Point based Hough Transformation for Automatic Line Detection of Engineering Drawings 基于锚点的Hough变换的工程图纸线自动检测
2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA) Pub Date : 2019-08-01 DOI: 10.1109/WRC-SARA.2019.8931934
Tianbo Liu, Quanbin Hua, S. Yuan, Lixue Yin, Gong Cheng
{"title":"Anchor Point based Hough Transformation for Automatic Line Detection of Engineering Drawings","authors":"Tianbo Liu, Quanbin Hua, S. Yuan, Lixue Yin, Gong Cheng","doi":"10.1109/WRC-SARA.2019.8931934","DOIUrl":"https://doi.org/10.1109/WRC-SARA.2019.8931934","url":null,"abstract":"We propose an algorithm that connects the edge graph by anchor points in advance and then performs line detection. The algorithm can generate valid edge segments, each of which is a valid pixel chain. Unlike some traditional edge detection algorithms, which works on threshold gradient amplitude clustering to determine edge elements. Our algorithm firstly obtains the anchor points according to the edge boundary direction of the image and the gradient values, and then connects the anchor points through the intelligent routing algorithm to obtain the edge images, and generates effective edge segments, which are valid pixel chains, then, according to the half-sampled Hough transform line detection, so as to realize the detection of graphics in a straight line, The edge map generated by the previous stage always contains a clean, perfectly continuous, well-positioned single-pixel wide edge. In addition, the quality of the edge pixel chain is also very good, and then the line is fitted by the least squares method again, and the final detected line effect is significant.","PeriodicalId":236286,"journal":{"name":"2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131321996","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
Experimental Evaluation of Direct Monocular Visual Odometry Based on Nonlinear Optimization 基于非线性优化的直接单目视觉里程测量的实验评价
2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA) Pub Date : 2019-08-01 DOI: 10.1109/WRC-SARA.2019.8931911
Jian Liang, Xin Cheng, Yezhou He, Xiaoli Li, Huashan Liu
{"title":"Experimental Evaluation of Direct Monocular Visual Odometry Based on Nonlinear Optimization","authors":"Jian Liang, Xin Cheng, Yezhou He, Xiaoli Li, Huashan Liu","doi":"10.1109/WRC-SARA.2019.8931911","DOIUrl":"https://doi.org/10.1109/WRC-SARA.2019.8931911","url":null,"abstract":"Since the feature-based monocular simultaneous localization and mapping (SLAM) system consumes a lot of computing resources on extracting features and associating descriptors, it still discards potentially valuable photometric information. To solve this problem, a direct monocular visual odometry (DMVO) approach is investigated to model the SLAM system by photometric error optimization, where a photometric error model is established, residual pattern defined in direct sparse odometry (DSO) is modified, and the Gauss-Newton algorithm is adopted to implement the DMVO. The DMVO approach in this paper uses more image information and totally avoids consuming computing resources on features and descriptors. The comparative tests on the TUM monocular visual odometry dataset are presented and the results showed that the alignment error of DMVO approach is smaller than that of DSO and ORB-SLAM with loop-closure and re-localization disabled.","PeriodicalId":236286,"journal":{"name":"2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117298045","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
Surface Defect Classification of Steels Based on Ensemble of Extreme Learning Machines 基于极限学习机集成的钢材表面缺陷分类
2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA) Pub Date : 2019-08-01 DOI: 10.1109/WRC-SARA.2019.8931807
Yanan Liu, Ying Jin, Hongbin Ma
{"title":"Surface Defect Classification of Steels Based on Ensemble of Extreme Learning Machines","authors":"Yanan Liu, Ying Jin, Hongbin Ma","doi":"10.1109/WRC-SARA.2019.8931807","DOIUrl":"https://doi.org/10.1109/WRC-SARA.2019.8931807","url":null,"abstract":"In recent years, iron and steel industry of China has developed rapidly, and steel surface defects recognition has attracted wide attention in the field of industrial inspection. Aiming at the problems of poor precision and low speed of traditional surface defect detection methods, we propose to use a fully learnable ensemble of Extreme Learning Machines (ELMs), which is ELM-IN-ELM, for defect classification. The Local Binary Pattern is adopted as the basic feature extraction method. The ELM-IN-ELM determines the final classification decision by automatically learning the output of M independent ELM sub-models. To further illustrate the superiority of the ELM-IN-ELM algorithm for classification, the Northeastern University (NEU) surface defect database is used to evaluate its classification effect. The experimental results demonstrate that this method works remarkably well for surface defects classification. Compared with other methods, the proposed method can identify the types of defects more accurately, which is of practical significance to steel surface defect detection.","PeriodicalId":236286,"journal":{"name":"2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129778867","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
Developing Robot Reaching Skill via Look-ahead Planning 通过前瞻计划发展机器人到达技能
2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA) Pub Date : 2019-08-01 DOI: 10.1109/WRC-SARA.2019.8931964
Tianlin Liu, Mengxi Nie, Xihong Wu, D. Luo
{"title":"Developing Robot Reaching Skill via Look-ahead Planning","authors":"Tianlin Liu, Mengxi Nie, Xihong Wu, D. Luo","doi":"10.1109/WRC-SARA.2019.8931964","DOIUrl":"https://doi.org/10.1109/WRC-SARA.2019.8931964","url":null,"abstract":"Reaching is a basic ability of robots and the basis for many complex manipulation tasks. It is an indispensable ability for robots to enter the human family. Previous methods mostly rely on an accurate model such as inverse kinematics model to solve this problem. However, in practice, the model is often inaccurate due to errors caused by measurements and calculations. In this paper, we present a multi-stage approach to develop robot reaching skill based on an internal model and look-ahead planning. We do not assume that the internal model is absolutely accurate. In fact, the inadequacy caused by the inaccuracy of the model can be compensated by the iterative planning in the fine tuning process. In the first stage, the robot collects training data through self-exploration. In the second stage, the robot uses the training data to build an internal model that establishes the relationship between proprioception and spatial position. In the final stage, the robot will reach the goal through coarse tuning and fine tuning. It first gets a rough action (joint movement) through the internal model and then performs the action. Then it will use a planning method to continually fine-tune the action until it finally reaches the goal. The effectiveness and the efficiency of the proposed method have been verified in experiments with the humanoid robot platform Baxter.","PeriodicalId":236286,"journal":{"name":"2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129537011","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: 2
Progress and Challenges of Hand-eye-foot Coordination for Mobile Manipulator 移动机械手手眼脚协调的进展与挑战
2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA) Pub Date : 2019-08-01 DOI: 10.1109/WRC-SARA.2019.8931956
Fuwen Hu, Yunchang Bao
{"title":"Progress and Challenges of Hand-eye-foot Coordination for Mobile Manipulator","authors":"Fuwen Hu, Yunchang Bao","doi":"10.1109/WRC-SARA.2019.8931956","DOIUrl":"https://doi.org/10.1109/WRC-SARA.2019.8931956","url":null,"abstract":"The goal of mobile manipulators is to perform complex operational tasks autonomously in a structured and unstructured environment and to work or closely interact with humans. Mobile manipulators brings more complicated engineering problems and deeper scientific problems. It is not easy to simply combine the research results of mobile platforms and robot arms to solve the unique and complex problems: hand-eye-foot coordination for mobile manipulator. Firstly, this paper mainly presented a survey of mobile manipulator from three aspects: autonomous grasping strategy, mobile platform and path planning. Especially, we discussed the basic principle of space trajectory planning for mobile manipulators and its practical application combined with vision, and further divided them into six categories according to different modeling principles. In conclusion, we suggest that mobile manipulators still face three major challenges: uncertainty in high-dimensional space, highly coupled dynamic nonlinearity, real-time performance of dynamic task planning.","PeriodicalId":236286,"journal":{"name":"2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127406898","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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