2021 IEEE/SICE International Symposium on System Integration (SII)最新文献

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EMC: Earthquake Magnitudes Classification on Seismic Signals via Convolutional Recurrent Networks 基于卷积递归网络的地震信号震级分类
2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382696
Muhammad Shakeel, Katsutoshi Itoyama, Kenji Nishida, K. Nakadai
{"title":"EMC: Earthquake Magnitudes Classification on Seismic Signals via Convolutional Recurrent Networks","authors":"Muhammad Shakeel, Katsutoshi Itoyama, Kenji Nishida, K. Nakadai","doi":"10.1109/IEEECONF49454.2021.9382696","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382696","url":null,"abstract":"We propose a novel framework for reliable automatic classification of earthquake magnitudes. Using deep learning methods, we aim to classify the earthquake magnitudes into different categories. The method is based on a convolutional recurrent neural network in which a new approach for feature extraction using Log-Mel spectrogram representations is applied for seismic signals. The neural network is able to classify earthquake magnitudes from minor to major. Stanford Earthquake Dataset (STEAD) is used to train and validate the proposed method. The evaluation results demonstrate the efficacy of the proposed method in a rigorous event independent scenario, which can reach a F-score of 67% depending upon the earthquake magnitude.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129060919","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: 4
A Novel Lenticular Angle Gauge for High-Accuracy Fiducial Markers 一种用于高精度基准标记的新型透镜角度计
2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382707
Hideyuki Tanaka
{"title":"A Novel Lenticular Angle Gauge for High-Accuracy Fiducial Markers","authors":"Hideyuki Tanaka","doi":"10.1109/IEEECONF49454.2021.9382707","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382707","url":null,"abstract":"Lenticular angle gauge (LEAG) is a planar pattern that visualizes relative orientation by the position of the black line, which moves according to the viewing angle. LEAG has the potential to turn arbitrary planar patterns into high-accuracy markers. The author has developed a new LEAG in which the direction of movement of the black line is 90◦ different from that of the previous LEAG. With this, it is no longer necessary to place two LEAGs orthogonally to create a high-accuracy fiducial marker. This paper describes the principle and behavior of the new LEAG, and the results of its functional test. A new design of high-accuracy marker under development is also presented.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122352070","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
Demonstration of expert knowledge injection in Fuzzy Rule Interpolation based Q-learning 基于模糊规则插值的q学习中的专家知识注入论证
2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382734
T. Tompa, S. Kovács, D. Vincze, M. Niitsuma
{"title":"Demonstration of expert knowledge injection in Fuzzy Rule Interpolation based Q-learning","authors":"T. Tompa, S. Kovács, D. Vincze, M. Niitsuma","doi":"10.1109/IEEECONF49454.2021.9382734","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382734","url":null,"abstract":"The learning phase of the traditional reinforcement learning methods can be started without any preliminary knowledge about the problem needed to be solved. The problem related knowledge-base is built based on the reinforcement signals of the environment during the trial and error style learning phase. If a portion of the a priori knowledge about the problem solution is available and if it could be injected into the initial knowledge of the reinforcement learning system, then the learning performance (and the learning ability of an agent) could be significantly improved. The goal of this paper is to highlight the effect of the external expert knowledge inclusion into the Fuzzy Rule Interpolation based Q-learning (FRIQ-learning) method, by briefly introducing a way for expert knowledge injection into FRIQ-learning and a discussion based on simulated runs of a practical benchmark example. The investigations presented here can aid in the designing of behaviour-based robot control systems, in such cases where the available expert knowledge is not enough by itself to construct a sufficiently working system.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129377674","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: 3
Design, Implementation and In-orbit Demonstration of Attitude and Orbit Control System for Micro-satellite ALE-2 ALE-2微卫星姿态轨道控制系统的设计、实现及在轨验证
2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382731
Yuji Sato, S. Fujita, T. Kuwahara, Y. Shibuya, K. Kamachi
{"title":"Design, Implementation and In-orbit Demonstration of Attitude and Orbit Control System for Micro-satellite ALE-2","authors":"Yuji Sato, S. Fujita, T. Kuwahara, Y. Shibuya, K. Kamachi","doi":"10.1109/IEEECONF49454.2021.9382731","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382731","url":null,"abstract":"This paper describes procedures for the design, implementation and in-orbit verification of an advanced Attitude and Orbit Control System (AOCS) that can be applied to micro-satellites. Functional requirements imposed on AOCS are becoming severer as the mission becomes more complicated and challenging even though onboard resources are limited in micro-satellites. In addition, many verification steps must be taken for the system design, implementation, and in-orbit demonstration. In this study, an advanced AOCS design that is optimized for the mission of the artificial meteor demonstration satellite “ALE-2” is proposed. This paper presents three AOCS features that are specialized to ALE-2 but applicable to other micro-satellites: sensor calibration technique, attitude and gyroscope bias estimation using extended Kalman filter, and orbit control by small propulsion system. These functions were implemented using a hardware-in-the-loop simulator environment, allowing for quick and efficient ground evaluation. In addition, in-orbit demonstration of the proposed AOCS was performed after the launch of ALE-2. Through these verification process, it was confirmed that the AOCS functions required for the mission of ALE-2 were properly implemented and worked in orbit.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129386667","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
Online Measurement of Compact Range Image Sensor Using Image Blur of Multi-Slit Laser* 基于多狭缝激光图像模糊的紧凑距离图像传感器在线测量*
2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382644
Karin Ohashi, Kazuki Tsumura, Yonghoon Ji, K. Umeda
{"title":"Online Measurement of Compact Range Image Sensor Using Image Blur of Multi-Slit Laser*","authors":"Karin Ohashi, Kazuki Tsumura, Yonghoon Ji, K. Umeda","doi":"10.1109/IEEECONF49454.2021.9382644","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382644","url":null,"abstract":"This paper proposes a compact range image sensor with a multi-slit laser projector and a small camera. Distance is measured using image blur of the multi-slit laser lights. By determining the relationship between blur and distance per pixel in advance, 5.6 fps online measurement of range images is achieved. The effectiveness of the proposed sensor is verified by experiments of range image measurement.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117004343","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
SpheriCol: A Driving Assistance System for Power Wheelchairs Based on Spherical Vision and Range Measurements SpheriCol:基于球面视觉和距离测量的电动轮椅驾驶辅助系统
2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382766
Sarah Delmas, F. Morbidi, Guillaume Caron, Julien Albrand, Meven Jeanne-Rose, Louise Devigne, Marie Babel
{"title":"SpheriCol: A Driving Assistance System for Power Wheelchairs Based on Spherical Vision and Range Measurements","authors":"Sarah Delmas, F. Morbidi, Guillaume Caron, Julien Albrand, Meven Jeanne-Rose, Louise Devigne, Marie Babel","doi":"10.1109/IEEECONF49454.2021.9382766","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382766","url":null,"abstract":"This paper presents “SpheriCol”, a new driving assistance system for power wheelchair users. The ROS-based aid system combines spherical images from a twin-fisheye camera and range measurements from on-board exteroceptive sensors, to synthesize different augmented views of the surrounding environment. Experiments with a Quickie Salsa wheelchair show that SpheriCol improves situational awareness and supports user’s decision in challenging maneuvers, such as passing through a door or corridor centering.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114743623","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: 3
Autonomous Mobile Robot for Apple Plant Disease Detection based on CNN and Multi-Spectral Vision System 基于CNN和多光谱视觉系统的苹果植物病害自主移动机器人
2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382649
Pavel A. Karpyshev, V. Ilin, I. Kalinov, Alexander Petrovsky, D. Tsetserukou
{"title":"Autonomous Mobile Robot for Apple Plant Disease Detection based on CNN and Multi-Spectral Vision System","authors":"Pavel A. Karpyshev, V. Ilin, I. Kalinov, Alexander Petrovsky, D. Tsetserukou","doi":"10.1109/IEEECONF49454.2021.9382649","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382649","url":null,"abstract":"This paper presents an autonomous system for apple orchard inspection and early stage disease detection. Various sensors including hyperspectral, multispectral and visible range scanners are used for disease detection. For localization and obstacle detection 2D LiDARs and RTK GNSS receivers are used. The proposed system allows to minimize the use of pesticides and increase harvests. The detection approach is based on the use of neural networks for both plant segmentation and disease detection.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127313627","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: 26
Observing Nocturnal Birds Using Localization Techniques 利用定位技术观察夜行鸟类
2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382665
Shiho Matsubayashi, Fumiyuki Saito, Reiji Suzuki, K. Nakadai, H. Okuno
{"title":"Observing Nocturnal Birds Using Localization Techniques","authors":"Shiho Matsubayashi, Fumiyuki Saito, Reiji Suzuki, K. Nakadai, H. Okuno","doi":"10.1109/IEEECONF49454.2021.9382665","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382665","url":null,"abstract":"Although nocturnal birds in Japan are rare, they often play critical roles in the ecosystem. Because they are elusive, however, the accurate and efficient monitoring of such birds, has been a challenge for field researchers. Furthermore, difficulties multiply when the population size of the target species is decreasing. This paper introduces recording examples conducted in the field to secretively monitor nocturnal birds in different environments, using localization techniques. We observed two different species, the ruddy-breasted crake (Porzana Fusca) in wetland and the Ural owls (Strix uralensis) in a forest, both of which are rare and their conservation is of environmental concern. We localized the territorial calls of crakes, and the feeding and fledgling scenes of owls, derived from one or multiple microphone arrays. The localized sounds successfully captured the fine-scale movements of these species in space and time, which cannot be easily obtained from any other monitoring method. Our results provide the first cases of monitoring such rare species using microphone arrays in the field.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127499855","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
Dynamic 3D-Obstacles Detection by a Monocular Camera and a 3D Map 基于单目摄像机和三维地图的动态三维障碍物检测
2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382660
Junya Shikishima, T. Tasaki
{"title":"Dynamic 3D-Obstacles Detection by a Monocular Camera and a 3D Map","authors":"Junya Shikishima, T. Tasaki","doi":"10.1109/IEEECONF49454.2021.9382660","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382660","url":null,"abstract":"We developed a new method for 3D-obstacles de-tection using a 3D map. Three-dimensional-obstacles detection is a key function of autonomous driving. It is easy to detect static obstacles because they exist in the 3D map. However, the 3D detection of dynamic obstacles that are not in the 3D map is difficult for a typical in-vehicle camera that cannot measure the distance. We aim to detect dynamic obstacles three-dimensionally, using an in-vehicle camera. And we deal with the new problem of accurate 3D reconstruction by using a monocular camera and a 3D map. To solve this problem, we focused on semantic segmentation for detection and depth completion to complement the depth map. We propose a multitask neural network (NN) that shares the encoder of semantic segmentation NN and depth completion NN, whose inputs are an image and a 3D map. The proposed multi-task NN detects dynamic obstacles 1.4 times more accurately than the singletask state-of-the-art method.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"264 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123264290","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 Simulator-based System for Testing Skill to Maneuver Robot Remotely* : -Implementations of Data Collection and Presentation Functions Related to Robot Maneuver- 基于模拟器的机器人远程机动技能测试系统* -机器人机动相关数据采集与呈现功能的实现
2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382608
Fumiaki Abe, K. Kawabata, Kenta Suzuki, Hiroshi Yashiro
{"title":"A Simulator-based System for Testing Skill to Maneuver Robot Remotely* : -Implementations of Data Collection and Presentation Functions Related to Robot Maneuver-","authors":"Fumiaki Abe, K. Kawabata, Kenta Suzuki, Hiroshi Yashiro","doi":"10.1109/IEEECONF49454.2021.9382608","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382608","url":null,"abstract":"This paper describes a simulator-based system for testing skill to maneuver the robot remotely. Our motivation is to apply the robot simulator to the skill verification process of the remote operation of robots. As a first step in achieving this, we developed the functions which work in conjunction with Choreonoid for collecting the data during operation and displaying collected data after the trial on-demand. In this paper, we described concrete implementation for considering the task of passing through the narrow passage in the dark and the result of a test run by using the developed prototype system.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123818490","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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