2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)最新文献_第8页

Time-Frequency Image Enhancement of Frequency Modulation Signals by Using Fully Convolutional Networks 基于全卷积网络的调频信号时频图像增强

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) Pub Date : 2018-11-01 DOI: 10.1109/ICARCV.2018.8581153

X. Xia, Fengqi Yu, Chuanqi Liu, Jiankang Zhao, Tianzhun Wu

{"title":"Time-Frequency Image Enhancement of Frequency Modulation Signals by Using Fully Convolutional Networks","authors":"X. Xia, Fengqi Yu, Chuanqi Liu, Jiankang Zhao, Tianzhun Wu","doi":"10.1109/ICARCV.2018.8581153","DOIUrl":"https://doi.org/10.1109/ICARCV.2018.8581153","url":null,"abstract":"The uncertainty principle and cross-term can lead to blur, fake signal components and energy oscillation in time-frequency distribution, deteriorate the results of signal tracking, radar/sonar imaging and parameter estimation. Hence in this paper, we propose a time-frequency image enhancement method based on convolutional neural networks for clearer instantaneous frequency curve. The training data are generated by a frequency modulation signal generator, and then an end-to-end training is performed between Wigner-Ville distributions and time-frequency images. Our networks not only extract underlying features of Wigner-Ville distribution, but also understand the semantic of instantaneous frequency curve and use the priori knowledge of the modulation mode. Therefore, it can correctly recognize and eliminate the cross-terms, and transform the Wigner-Ville distribution to an image that can accurate represent the instantaneous frequency curve. The method is tested by three kinds of frequency modulation signals randomly with Gaussian noise. The results show that it can work properly in most cases and has the generalization ability of multi-component signals.","PeriodicalId":395380,"journal":{"name":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124268857","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

Design Principle of Frequency Shaped Non-Switching Integral Sliding Mode Controller 频率型非开关积分滑模控制器的设计原理

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) Pub Date : 2018-11-01 DOI: 10.1109/ICARCV.2018.8581125

Yuki Kawai, K. Uchiyama, Kai Masuda

{"title":"Design Principle of Frequency Shaped Non-Switching Integral Sliding Mode Controller","authors":"Yuki Kawai, K. Uchiyama, Kai Masuda","doi":"10.1109/ICARCV.2018.8581125","DOIUrl":"https://doi.org/10.1109/ICARCV.2018.8581125","url":null,"abstract":"This paper proposes the frequency shaped non-switching integral sliding mode controller (FS-NS-ISMC). Non-switching integral sliding mode controller (NS-ISMC) was proposed as the first sliding mode controller guaranteeing robust stability and performance. The NS-ISMC was basically allowed to control the only matched channels like a conventional sliding mode controller. It means that NS-ISMC cannot suppress unmatched perturbation which is sensitive against control input while making the matched channel behaves as a sliding mode. However, if the robust vector gain, which is a parameter of NS-ISMC, could be designed in frequency to avoid to input in the range where the unmatched perturbation is sensitive while guaranteeing the stability of the error between the matched channel and integral sliding mode, unmatched perturbations could have been suppressed at the same time. In this paper, the design method of FS-NS-ISMC by D-K iteration $boldsymbol{mu}$-synthesis to suppress unmatched perturbation is introduced. A flexible manipulator is chosen as the system example. Design process against the manipulator is described and its effectiveness is shown in the numerical simulation.","PeriodicalId":395380,"journal":{"name":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126103887","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

Globally Stable Bearing-Only Formation Control of Multi-Agent Systems 多智能体系统全局稳定方位编队控制

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) Pub Date : 2018-11-01 DOI: 10.1109/ICARCV.2018.8581218

Xiaolei Li, M. Er, Guanghong Yang, Ning Wang

引用次数: 0

Learning Under-Specified Object Manipulations from Human Demonstrations 从人类演示中学习未指定对象的操作

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) Pub Date : 2018-11-01 DOI: 10.1109/ICARCV.2018.8581080

K. Qian, Jun Xu, Ge Gao, Fang Fang, Xudong Ma

引用次数: 2

A Hybrid Control Architecture For Autonomous Driving In Urban Environment 城市环境下自动驾驶的混合控制体系

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) Pub Date : 2018-11-01 DOI: 10.1109/ICARCV.2018.8581212

Chanyoung Jung, Seokwoo Jung, D. Shim

{"title":"A Hybrid Control Architecture For Autonomous Driving In Urban Environment","authors":"Chanyoung Jung, Seokwoo Jung, D. Shim","doi":"10.1109/ICARCV.2018.8581212","DOIUrl":"https://doi.org/10.1109/ICARCV.2018.8581212","url":null,"abstract":"Autonomous driving in an urban environment is one of the most actively studied topics. To date, many studies on autonomous driving can be classified into two main approaches: 1.local perception-based approach 2.global path tracking-based approach. However, each approach has its own limitations for fully autonomous driving. In the case of perception-based approach, it is impossible to autonomously drive to the global destination because it only runs locally within the sensor range. On the other hand, the path tracking-based approach relies heavily on accurate navigation. For accurate navigation, there are many studies using expensive equipment or extremely precise and detailed maps, but they have not been resolved yet, and they are also not practical. In this paper, we address the problem of autonomous driving in an urban environment through the proposed hybrid control architecture. Proposed control architecture is designed to be complementary of local perception-based and global path tracking-based approaches. Especially, end-to-end deep learning based autonomous driving, which mimics human driving, is applied as a local perception-based approach. In addition, path tracking-based autonomous driving is performed in an environment where directional information to the destination is required, such as intersections. At the same time, our hybrid control architecture effectively compensates for the navigation error using ICP matching between the perception-based driven trajectory and the global path to the destination without any highly detailed prior map or expensive equipment. The performance of the proposed architecture on a full-scale autonomous vehicle is verified through experiments in the urban environment.","PeriodicalId":395380,"journal":{"name":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116007912","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

Online Semantic Segmentation and Manipulation of Objects in Task Intelligence for Service Robots 服务机器人任务智能中对象的在线语义分割与操作

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) Pub Date : 2018-11-01 DOI: 10.1109/ICARCV.2018.8581135

Adrian Llopart, Ole Ravn, N. Andersen, Jong-Hwan Kim

{"title":"Online Semantic Segmentation and Manipulation of Objects in Task Intelligence for Service Robots","authors":"Adrian Llopart, Ole Ravn, N. Andersen, Jong-Hwan Kim","doi":"10.1109/ICARCV.2018.8581135","DOIUrl":"https://doi.org/10.1109/ICARCV.2018.8581135","url":null,"abstract":"Task Intelligence is the capacity of a robot to learn, reason and execute specific behaviours based on its environment. In this paper, the Task Intelligence problem formulated by the Robot Intelligence and Technology Laboratory at KAIST is researched further: specifically the proposed contribution is a brand new perceptual pipeline in which the recognition, detection, segmentation and grasping of objects is achieved assuming no prior knowledge of the environments arrangement nor the objects appearance. A Convolutional Neural Net (CNN) is used to detect, recognize and semantically label those objects that need to be interacted with. 3D point clouds, corresponding to the objects model, are extracted after several segmentation procedures and registered over time. Dimensional and positional information of the object is acquired. Additional grasping pose data is calculated. All of the collected knowledge is parsed so that the Task Intelligence system is able to deal with previously unknown objects in dynamic environments. This system is formed by an Episodic Memory (Deep-ART), an action sequence generator (FF-planner) and a trajectory warping module for pre-learnt behaviours. The proposed approach has been tested using the Webots simulator.","PeriodicalId":395380,"journal":{"name":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122584658","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

Understanding Deformation Motion of Colloidal Nanosheets from CLSM Images using Deep Learning-based Approach 利用基于深度学习的方法理解CLSM图像中胶体纳米片的变形运动

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) Pub Date : 2018-11-01 DOI: 10.1109/ICARCV.2018.8581084

H. Fujioka, Jarupat Sawangphol, Shinya Anraku, N. Miyamoto, Akinori Hidaka, H. Kano

引用次数: 1

Stochastic Optimal Control of Dynamic Queue Systems: A Probabilistic Perspective 动态队列系统的随机最优控制:一个概率的视角

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) Pub Date : 2018-11-01 DOI: 10.1109/ICARCV.2018.8581152

Yulong Gao, Shuang Wu, K. Johansson, Ling Shi, Lihua Xie

引用次数: 0

CROTPN Based Collision-Free and Deadlock-Free Path Planning of AGVs in Logistic Center 基于CROTPN的物流中心agv无碰撞无死锁路径规划

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) Pub Date : 2018-11-01 DOI: 10.1109/ICARCV.2018.8581060

Sankui Sun, Chonglin Gu, Qian Wan, Hejiao Huang, X. Jia

{"title":"CROTPN Based Collision-Free and Deadlock-Free Path Planning of AGVs in Logistic Center","authors":"Sankui Sun, Chonglin Gu, Qian Wan, Hejiao Huang, X. Jia","doi":"10.1109/ICARCV.2018.8581060","DOIUrl":"https://doi.org/10.1109/ICARCV.2018.8581060","url":null,"abstract":"In recent years, automated guided vehicle (AGV) is becoming increasingly important for logistic center, which usually has tens of thousands of express packages to sort and transport every day. In order to enhance the efficiency of sorting, multiple AGVs have been used to transport as many express packages as possible in a given time. However, there may exist collisions and deadlocks when two or more AGVs are trying to pass through a shared area at the same time. In this paper, we study collision-free and deadlock-free path planning of multiple AGVs with the objective of minimizing the makespan, that is, the maximum time of the AGVs to finish a round of delivery. To solve the problem, we first propose a candidate path generation algorithm to generate several paths for each AGV, from which a combination of the paths is selected based on optimal path combination selection (OPCS) algorithm, such that the collisions and deadlocks can be minimized. Then, we construct a colored resource-oriented timed Petri net (CROTPN) model for dynamic changing AGV routes after slicing the scheduling period into timeslots. Through Slot-Control policy, the collision and deadlock can be effectively avoided. Our experiment is simulated based on CPN tools. Experiment results show that our method can achieve a high sorting throughput using the least AVGs.","PeriodicalId":395380,"journal":{"name":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","volume":"325 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122325404","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: 8

Self-Configurable Hybrid Energy Management System for Smart Buildings 智能建筑自配置混合能源管理系统

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) Pub Date : 2018-11-01 DOI: 10.1109/ICARCV.2018.8581354

Muhammad Umair, Bilal Afzal, Asad I. Khan, A. Rehman, Y. Sekercioglu, G. Shah

引用次数: 4