2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR)最新文献_第2页

EEG analysis of the Brain Language Processing oriented to Intelligent Teaching Robot 面向智能教学机器人的脑语言处理脑电分析

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535637

Madiha Khalid Syed, Hong Wang

{"title":"EEG analysis of the Brain Language Processing oriented to Intelligent Teaching Robot","authors":"Madiha Khalid Syed, Hong Wang","doi":"10.1109/IISR.2018.8535637","DOIUrl":"https://doi.org/10.1109/IISR.2018.8535637","url":null,"abstract":"Here we present a robotic language teaching assistant that also monitor the EEG band relative power to check the concentration and interest level of its students during recall phase. If the concentration level of student is lower, the word can be repeated and presented in other ways. In that way, lessons will be repeated and altered depending upon students' focus. It's an assisted learning paradigm where individuals first learn the Chinese characters with and without pinyin and then trained themselves. And for the judgment of training, there is recall phase. Neuronal oscillations with its relative frequency relate in important ways to memory processes and aid as a model for learning oscillatory activity in cognition. More imprecisely theta relativity is increased markedly during training phase while memorizing of character without pinyin at the parietal lobe. While at same instant gamma relativity dropped at the same region. It is also observed that the gamma relativity is increased with pinyin associated with the character during training and recall phase at temporal lobe. The results showed a strong association between theta and gamma relativity during learning, training and recall phase. These findings add to our understanding of how theta and gamma oscillations interact within frontal, central, parietal temporal and occipital lobes for the service of memory and how can we use these results to increase our efficiency during learning the Chinese language.","PeriodicalId":201828,"journal":{"name":"2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR)","volume":"241 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115575233","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

An Omnidirectional and Movable Palletizing Robot based on Computer Vision Positing 基于计算机视觉定位的全向移动码垛机器人

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535688

Xiong Yang, Hongbin Zhang, Tianyou Cheng, Xuebin Ni, Chenhao Wu, Huaizhi Zong, Haojian Lu, Zhiguo Lu, Yajing Shen

{"title":"An Omnidirectional and Movable Palletizing Robot based on Computer Vision Positing","authors":"Xiong Yang, Hongbin Zhang, Tianyou Cheng, Xuebin Ni, Chenhao Wu, Huaizhi Zong, Haojian Lu, Zhiguo Lu, Yajing Shen","doi":"10.1109/IISR.2018.8535688","DOIUrl":"https://doi.org/10.1109/IISR.2018.8535688","url":null,"abstract":"The palletizing robot is a type of industrial robot that performs the tasks of obtaining, transporting, stacking, and unstacking large quantities of workpieces or packages in an industrial production process. It is a high-tech mechanical and electrical product that integrates mechanical, electronics, communications, intelligent technology, computer science, and other technologies. Palletizing robotics technology has great potential in solving labor shortages, improving labor productivity, saving production costs, reducing labor intensity, and improving the production environment. Current palletizing robots are large in structure and have limited stacking heights. This paper develops a compact palletizing robot that integrates transport and stacking functions for light-weight cargo stacking. We apply an omnidirectional chassis to the palletizing robot, which allows the robot to move in any direction and expands its working range. By using the lifting mechanism, the block can be embedded from the lower end. This not only reduces the overall size of the robot but also allows for higher stacking. This paper also adds computer vision positioning for palletizing robots. On the one hand, it greatly improves the robot's own movement accuracy, on the other hand, it realizes the complete automation of robots. Finally, we verified the feasibility of the palletizing robot through experiments. In the absence of intervention, the robot successfully transported the blocks to the designated area and stacked them to four times the height of the robot itself.","PeriodicalId":201828,"journal":{"name":"2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117068087","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

Weibull Parameter Estimation Algorithm Based on Ant Colony 基于蚁群的威布尔参数估计算法

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535861

Weiguang Li, Zhen Li, Cong Ye, Jing Ye, Gong Chen, Zhuohua Lin, Wanfeng Shang, Quanquan Liu, Chunbao Wang

引用次数: 1

Path Planning Algorithm Based on an Improved Artificial Potential Field for Mobile Service Robots 基于改进人工势场的移动服务机器人路径规划算法

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535745

Min Song, Junyou Yang, Yina Wang, Chunwei Yu, Donghui Zhao

引用次数: 4

Micro-UAV onboard vehicle detection: architecture and experiments 微型无人机机载车辆检测:架构与实验

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535835

Zhengyuan Zhou, Yong Zhou, Dengqing Tang, Kuang Zhao, Tianjiang Hu

{"title":"Micro-UAV onboard vehicle detection: architecture and experiments","authors":"Zhengyuan Zhou, Yong Zhou, Dengqing Tang, Kuang Zhao, Tianjiang Hu","doi":"10.1109/IISR.2018.8535835","DOIUrl":"https://doi.org/10.1109/IISR.2018.8535835","url":null,"abstract":"In this paper, an onboard processing architecture is proposed for micro fixed-wing unmanned aerial vehicle (UAV). The typical application scenarios include online detection of moving vehicles on the ground. The detection architecture is compatible with extremely limited computing resources provided by the micro UAVs. Eventually, the multi-vehicle detector is composed of saliency-based region proposal and neural network supported classifier. A typical convolutional neural network, connected with the Cifar10 dataset [1], is selected as the classifier, by performance comparisons driven by the annotated datasets. Furthermore, both “progress balance” and “quantity balance” strategies are developed and compared for training sample structure optimizing to reduce misclassification and leakage classification. Under such circumstances, experiments are conducted with onboard imagery of flying micro fixed-wing vehicles during surveillance on multiple moving vehicles on the ground. Experimental results validate the feasibility and effectiveness of the proposed onboard detection architecture. Typically, four-vehicle mAP is promoted from 52.50% to 57.76% by using the unified progress and quantity dataset balance strategy.","PeriodicalId":201828,"journal":{"name":"2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129425322","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

Safety Velocity Tracking Control for an Omnidirectional Rehabilitative Training Walker with Uncertainty 具有不确定性的全向康复训练步行器安全速度跟踪控制

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535948

Tong Sun, P. Sun

引用次数: 0

A Structure Design of Safety PLC with Heterogeneous Redundant Dual-Processor 异构冗余双处理器安全PLC的结构设计

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535915

Mingshi Li, Yue Ma, Zhenyu Yin, Mengjia Lian, Chunxiao Wang

引用次数: 1

Development and Safety Management of a Rubble Field in ImPACT Tough Robotics Challenge Field Evaluation 冲击机器人挑战场评估中碎石场的开发与安全管理

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535768

Yudai Hasumi, Toshiroh Houshi, Hiroki Igarashi, Tetsuya Kimura, Y. Murao, T. Takamori

引用次数: 0

When Machine Learning meets Security Issues: A survey 当机器学习遇到安全问题:一项调查

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535799

Zhenyu Guan, Liangxu Bian, Tao Shang, Jianwei Liu

引用次数: 22

Visual Tracking and Positioning for an Astronaut Assistant Robot 宇航员辅助机器人的视觉跟踪与定位

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535853

Lihong Dai, Jinguo Liu, Zhaojie Ju

{"title":"Visual Tracking and Positioning for an Astronaut Assistant Robot","authors":"Lihong Dai, Jinguo Liu, Zhaojie Ju","doi":"10.1109/IISR.2018.8535853","DOIUrl":"https://doi.org/10.1109/IISR.2018.8535853","url":null,"abstract":"Cabin robot can provide assistance for astronauts in the cabin. On the one hand, it can be used to alarm the smoke and other contingencies in the cabin to ensure personal safety. On the other hand, when astronauts are lonely, it can monitor the mental/physical health of the astronauts in the cabin. For this purpose, real-time visual tracking and positioning of the second generation Astronaut Assistant Robot (AAR-2) is carried out. Because of the limitation of the cabin space, with the movements of the robot, sometimes only the local/partial images of targets can be captured by camera. So how to carry out the tracking and pose calculation through those partial images is a challenge. The paper proposes an integration method with a target feature template and a local search algorithm to track a moving target in real time, where the position and attitude of the camera are calculated using the PnP algorithm. Camera calibration and moving target tracking are expounded in detail. Furthermore, the accuracy is verified by experimental results. It turns out that the visual positioning system meets the precision requirement in real time.","PeriodicalId":201828,"journal":{"name":"2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125218504","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