2021 IEEE/SICE International Symposium on System Integration (SII)最新文献_第4页

2D Position Control of a UAV Using Fuzzy Logic Control 基于模糊逻辑控制的无人机二维位置控制

2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382784

M. Say, E. Sybingco, A. Bandala, R. R. Vicerra, A. Chua

引用次数: 0

Multi-channel Environmental Sound Segmentation utilizing Sound Source Localization and Separation U-Net 基于声源定位和分离U-Net的多通道环境声分割

2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382730

Yui Sudo, Katsutoshi Itoyama, Kenji Nishida, K. Nakadai

{"title":"Multi-channel Environmental Sound Segmentation utilizing Sound Source Localization and Separation U-Net","authors":"Yui Sudo, Katsutoshi Itoyama, Kenji Nishida, K. Nakadai","doi":"10.1109/IEEECONF49454.2021.9382730","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382730","url":null,"abstract":"This paper proposes a multi-channel environmental sound segmentation method. Environmental sound segmentation is an integrated method that deals with sound source localization, sound source separation and class identification. When multiple microphones are available, spatial features can be used to improve the separation accuracy of signals from different directions; however, conventional methods have two drawbacks: (a) Since sound source localization and sound source separation using spatial features and class identification using spectral features are trained in the same neural network, it overfits to the relationship between the direction of arrival and the class. (b) Although the permutation invariant training used in speech recognition could be extended, it is not practical for environmental sounds due to the maximum number of speakers limitation. This paper proposes multi-channel environmental sound segmentation method that combines U-Net which simultaneously performs sound source localization and sound source separation, and convolutional neural network which classifies the separated sounds. This method prevents overfitting to the relationship between the direction of arrival and the class. Simulation experiments using the created datasets including 75-class environmental sounds showed that the root mean squared error of the proposed method was lower than that of the conventional method.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"54 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":"122713079","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: 5

Design of Class in Unknown Object Segmentation Focusing on 3D Object Detection in Depth Image 基于深度图像三维目标检测的未知目标分割类设计

2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382606

Tatsuya Amemiya, T. Tasaki

引用次数: 1

A Ground-Stair Walking Strategy of the Assistive Device Based on the RGB-D Camera 基于RGB-D摄像机的辅助装置地楼梯行走策略

2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382668

Shuai-Hong Yu, Bo-Rong Yang, Hee-Hyol Lee, Eiichirou Tanaka

{"title":"A Ground-Stair Walking Strategy of the Assistive Device Based on the RGB-D Camera","authors":"Shuai-Hong Yu, Bo-Rong Yang, Hee-Hyol Lee, Eiichirou Tanaka","doi":"10.1109/IEEECONF49454.2021.9382668","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382668","url":null,"abstract":"To ensure the safety of elderly people with a walking assistive device during the ground-stair transition, a system which could automatically transfer the walking mode between level walking and stair climbing was proposed. A road condition detection system with a RGB-D Camera and ultrasonic sensors was utilized in this system. The walking mode transformation is triggered by the detection of environment change. When far approach the stairs, the RGB-D Camera is responsible for the stair detection. The ultrasonic sensors are used in the near-approach of stairs and stair traversal. The ultrasonic sensors were mounted on the toe and heel to find the upwards and downwards stairs respectively. During stair traversal, if the ultrasonic sensors find the foot of the device is too closed to the edge of stairs, the target trajectory will be higher and the stride will be adjusted to prevent collisions. The Impedance control was introduced to let the device trace the predefined walking trajectories. In experiments, the device changed walking modes successfully when getting close the stairs. The results engaged in three subjects showed that the foot height was increased compared without assistance. Thus a huge potential can be expected that this system can solve the adaptability of walking assistive devices to different surroundings.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"73 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":"127572682","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

Error Identification and Recovery in Robotic Snap Assembly 机器人扣片装配中的错误识别与恢复

2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382694

Yusuke Hayami, Weiwei Wan, Keisuke Koyama, Peihao Shi, J. Rojas, K. Harada

{"title":"Error Identification and Recovery in Robotic Snap Assembly","authors":"Yusuke Hayami, Weiwei Wan, Keisuke Koyama, Peihao Shi, J. Rojas, K. Harada","doi":"10.1109/IEEECONF49454.2021.9382694","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382694","url":null,"abstract":"Existing methods for predicting robotic snap joint assembly cannot predict failures before their occurrence. To address this limitation, this paper proposes a method for predicting error states before the occurence of error, thereby enabling timely recovery. Robotic snap joint assembly requires precise positioning; therefore, even a slight offset between parts can lead to assembly failure. To correctly predict error states, we apply functional principal component analysis (fPCA) to 6Dforce/torque profiles that are terminated before the occurence of an error. The error state is identified by applying a feature vector to a decision tree, wherein the support vector machine (SVM) is employed at each node. If the estimation accuracy is low, we perform additional probing to more correctly identify the error state. Finally, after identifying the error state, a robot performs the error recovery motion based on the identified error state. Through the experimental results of assembling plastic parts with four snap joints, we show that the error states can be correctly estimated and a robot can recover from the identified error state.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"27 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":"133630812","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

Development of a Tower-type Cooking Robot 塔式烹饪机器人的研制

2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382622

Masahiro Inagawa, T. Takei, Etsujiro Imanishi

引用次数: 4

The application of virtual reality in programming of a manufacturing cell 虚拟现实技术在制造单元编程中的应用

2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382657

H. Arnarson, B. Solvang, Beibei Shu

引用次数: 2

Feasibility Evaluation of Mixed Reality Obstacles on Treadmill using HoloLens to Elicit Real Obstacle Negotiation 利用HoloLens对跑步机上混合现实障碍进行可行性评估，以引发真实障碍协商

2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382780

Tamon Miyake, Mohammed Al-Sada, Tingting Zhong, Wen Wang, S. Sugano

{"title":"Feasibility Evaluation of Mixed Reality Obstacles on Treadmill using HoloLens to Elicit Real Obstacle Negotiation","authors":"Tamon Miyake, Mohammed Al-Sada, Tingting Zhong, Wen Wang, S. Sugano","doi":"10.1109/IEEECONF49454.2021.9382780","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382780","url":null,"abstract":"An ability of visually-guided and anticipatory adjustments of locomotion corresponding to upcoming obstacles is important to avoid trip-induced fall. For establishing gait training based on visually-guided and anticipatory adjustments, techniques reproducing realistic training environment are essential. Although some previous works proposed virtual obstacles using mixed reality, the feasibility of virtual obstacles encouraging people to perform realistic obstacle negotiation on a treadmill, where gait training is usually conducted, is still unclear. In this study, we investigated toe heights when stepping over the obstacle in both cases of virtual and real obstacles during walking on the treadmill. Five participants stepped over two types of mixed reality boxes and real boxes, with box placements close and distant from them. The results generally indicate that the toe heights of the leading foot tended to be similar between mixed reality and real obstacles in cases where the obstacle was located distant from participants, a condition that enabled participants to predict when obstacles approached. However, the toe heights of the trailing foot tended to be lower when stepping over the MR obstacles than the real obstacles. We discuss the feasibility and shortcomings of the future use of MR HMDs as replacement for traditional gait training setup.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"20 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":"132561042","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

An unsupervised auditory scene analysis system using incremental low-dimensional embedding 基于增量低维嵌入的无监督听觉场景分析系统

2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382632

K. Shinzato, Ryosuke Kojima

{"title":"An unsupervised auditory scene analysis system using incremental low-dimensional embedding","authors":"K. Shinzato, Ryosuke Kojima","doi":"10.1109/IEEECONF49454.2021.9382632","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382632","url":null,"abstract":"This paper addresses the low-dimensional embedding of sounds towards unsupervised auditory scene analysis. Summarizing long-time recordings by mapping them into lowdimensional space is an essential task in long-time environmental monitoring. In this paper, we propose a novel low-dimensional embedding system using an incremental embedding algorithm. To analyze long-time recordings, we design an incremental system consisting of recording, feature extraction, low-dimensional embedding, and visualization. Recently, many low-dimensional embedding methods for acoustic scenes have been studied; however, applicability of these methods to the long-time recording is not adequately evaluated. Thus, this paper describes the construction of the scene analysis system and evaluates the performance of this system. In this paper, we especially focus on two important viewpoints in long-time monitoring: incremental methods and effects of noisy data. To realize an incremental system, we use Self-Organizing Nebulous Growths (SONG), which can incrementally construct a low-dimensional embedding space. Also, in our experiments, we apply our system to bird song analysis under noise conditions. By the preliminary experiments using benchmark datasets, we discover noise sensitivity of our system and applicability to environmental monitoring.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"35 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":"121928454","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

Transporting a heavy object on a frictional floor by a mobile manipulator based on adaptive MPC framework 基于自适应MPC框架的移动机械手在摩擦地板上搬运重物

2021 IEEE/SICE International Symposium on System Integration (SII) Pub Date : 2021-01-11 DOI: 10.1109/IEEECONF49454.2021.9382761

Yunzhuo Wang, Hitoshi Kusano, T. Sugihara

{"title":"Transporting a heavy object on a frictional floor by a mobile manipulator based on adaptive MPC framework","authors":"Yunzhuo Wang, Hitoshi Kusano, T. Sugihara","doi":"10.1109/IEEECONF49454.2021.9382761","DOIUrl":"https://doi.org/10.1109/IEEECONF49454.2021.9382761","url":null,"abstract":"This work tackles a task to transport an object by a mobile manipulator to the designated location. Heavy objects that the robot cannot lift up and needs to push or drag are targeted. It is assumed that the mass property of the object and the frictional characteristics between the object and the floor are unknown. In addition, a caging strategy of loosely holding the object is employed in order to reduce the required motor torques. Thus, a challenge is how to deal with uncertainties accompanied with interactions between the robot, the object and the ground. A control system that stands on a combination of an instantaneous equilibration model of a planar frictional movement and the adaptive model predictive control (MPC) to modify the model parameters during the operation is proposed and implemented on a mobile manipulator. Efficacy of the proposed method was verified through experiments, in which even objects that are equipped with casters and thus have largely different characteristics from the supposed friction model were successfully moved to the desired destination.","PeriodicalId":395378,"journal":{"name":"2021 IEEE/SICE International Symposium on System Integration (SII)","volume":"29 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":"116737336","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