2021/08/03 更新

写真a

カルバヨ セグラ アレックサンダー
CARBALLO SEGURA Alexander
CARBALLO SEGURA Alexander
所属
未来社会創造機構 モビリティ社会研究所 モビリティサービス研究部門 特任准教授
大学院情報学研究科
職名
特任准教授
連絡先
メールアドレス
通称等の別名
カルバヨ アレックサンダー
プロフィール
Alexander Carballo received his Bachelor degree in Computer Engineering from Costa Rica Institute of Technology in 1996. He worked as lecturer for the undergraduate program of the Department of Computer Science at Costa Rica Institute of Technology from 1996 to 2006. In 2006 he joined the Intelligent Robot Laboratory at University of Tsukuba as research student, where he obtained the Doctor of Engineering degree in Computer Science in 2011. He worked at the Research and Development department of Hokuyo Automatic Co. Ltd. from 2011 until 2017. He is currently appointed as designated Associate Professor at Nagoya University. His research interests include machine learning, autonomous vehicles, robot navigation, machine perception and sensor fusion.
外部リンク

学位 1

  1. 博士(工学) ( 2011年3月   筑波大学 ) 

研究キーワード 8

  1. 自律移動ロボット

  2. 自動運転

  3. 画像処理

  4. 機械学習

  5. 人工知能

  6. コンピュータ工学

  7. コンピュータネットワーク

  8. LiDAR

研究分野 3

  1. ものづくり技術(機械・電気電子・化学工学) / 通信工学

  2. 情報通信 / 知覚情報処理  / LiDAR, 画像処理

  3. 情報通信 / 知能ロボティクス

経歴 5

  1. 株式会社 ティアフォー   シニアリサーチ フェロー

    2018年1月 - 現在

      詳細を見る

    国名:日本国

  2. 名古屋大学   未来社会創造機構   特任准教授

    2017年7月 - 現在

      詳細を見る

    国名:日本国

  3. 大阪市立大学   大学院工学研究科   非常勤講師

    2016年10月 - 現在

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    国名:日本国

  4. 北陽電機株式会社   研究開発

    2011年4月 - 2017年6月

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    国名:日本国

  5. コスタリカ工科大学   講師

    1996年1月 - 2006年6月

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    国名:コスタリカ共和国

学歴 2

  1. 筑波大学   システム情報工学研究科   コンピュータサイエンス専攻

    2007年4月 - 2011年3月

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    国名: 日本国

    備考: 博士後期課程

  2. 筑波大学   システム情報工学研究科   コンピュータサイエンス専攻

    2006年4月 - 2007年3月

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    国名: 日本国

    備考: 知能ロボット研究室 研究生

所属学協会 4

  1. Asia-Pacific Signal and Information Processing Association (APSIPA)

    2019年10月 - 現在

  2. IEEE Intelligent Transportation Systems Society (ITSS)

    2018年1月 - 現在

  3. 日本ロボット学会

    2009年4月 - 現在

  4. IEEE Robotics and Automation Society (RAS)

    2008年1月 - 現在

受賞 1

  1. 2019年度 Journal of Robotics and Mechatronics (JRM) 優秀論文賞

    2020年1月   富士技術出版株式会社  

 

論文 45

  1. A comparison of methods for sharing recognition information interventions to assist recognition in autonomous driving system

    Atsushi Kuribayashi, Eijiro Takeuchi, Alexander Carballo, Kazuya Takeda

    IEEE Intelligent Vehicles Symposium (IV)     2021年7月

  2. RSG-Net: Towards Rich Semantic Relationship Prediction for Intelligent Vehicle in Complex Environment 査読有り

    Yafu Tian, Alexander Carballo, Ruifeng Li, Kazuya Takeda

    IEEE Intelligent Vehicles Symposium (IV)     2021年7月

  3. Learning Personalized Driver Models via Probabilistic Sequence-to-Sequence Approaches

    Naren Bao, Alexander Carballo, Kazuya Takeda

    IEEE Intelligent Vehicles Symposium (IV)     2021年7月

  4. Eagleye: A Lane-Level Localization Using Low-Cost GNSS/IMU

    Aoki Takanose, Yuki Kitsukawa, Junichi Meguro, Eijiro Takeuchi, Alexander Carballo, Kazuya Takeda

    IEEE Intelligent Vehicles Symposium (IV) Autoware – ROS-based OSS for Autonomous Driving Workshop     2021年7月

  5. Characterization of Multiple 3D LiDARs for Localization and Mapping Performance using the NDT Algorithm

    Alexander Carballo, Abraham Israel Monrroy Cano, David Robert Wong, Patiphon Narksri, Jacob Lambert, Yuki Kitsukawa, Eijiro Takeuchi, Shinpei Kato, Kazuya Takeda

    IEEE Intelligent Vehicles Symposium (IV) Autoware – ROS-based OSS for Autonomous Driving Workshop     2021年7月

  6. Road Scene Graph: A Semantic Graph-Based Scene Representation Dataset for Intelligent Vehicles 査読有り

    Yafu Tian, Alexander Carballo, Ruifeng Li, Kazuya Takeda

        2020年11月

     詳細を見る

    Rich semantic information extraction plays a vital role on next-generation
    intelligent vehicles. Currently there is great amount of research focusing on
    fundamental applications such as 6D pose detection, road scene semantic
    segmentation, etc. And this provides us a great opportunity to think about how
    shall these data be organized and exploited.
    In this paper we propose road scene graph,a special scene-graph for
    intelligent vehicles. Different to classical data representation, this graph
    provides not only object proposals but also their pair-wise relationships. By
    organizing them in a topological graph, these data are explainable,
    fully-connected, and could be easily processed by GCNs (Graph Convolutional
    Networks). Here we apply scene graph on roads using our Road Scene Graph
    dataset, including the basic graph prediction model. This work also includes
    experimental evaluations using the proposed model.

    arXiv

    その他リンク: http://arxiv.org/pdf/2011.13588v1

  7. LIBRE: The Multiple 3D LiDAR Dataset 査読有り

    Alexander Carballo, Jacob Lambert, Abraham Monrroy, David Wong, Patiphon Narksri, Yuki Kitsukawa, Eijiro Takeuchi, Shinpei Kato, Kazuya Takeda

    2020 IEEE Intelligent Vehicles Symposium (IV)     頁: 823 - 830   2020年10月

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    担当区分:筆頭著者   掲載種別:研究論文(国際会議プロシーディングス)   出版者・発行元:IEEE  

    DOI: 10.1109/iv47402.2020.9304681

    arXiv

  8. Point Grid Map-Based Mid-To-Mid Driving without Object Detection 査読有り

    Shunya Seiya, Alexander Carballo, Eijiro Takeuchi, Kazuya Takeda

    2020 IEEE Intelligent Vehicles Symposium (IV)     頁: 2044 - 2051   2020年10月

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    掲載種別:研究論文(国際会議プロシーディングス)   出版者・発行元:IEEE  

    DOI: 10.1109/iv47402.2020.9304809

    Scopus

  9. Extracting Human-Like Driving Behaviors From Expert Driver Data Using Deep Learning 査読有り

    Kyle Sama, Yoichi Morales, Hailong Liu, Naoki Akai, Alexander Carballo, Eijiro Takeuchi, Kazuya Takeda

    IEEE Transactions on Vehicular Technology   69 巻 ( 9 ) 頁: 9315 - 9329   2020年9月

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    掲載種別:研究論文(学術雑誌)   出版者・発行元:Institute of Electrical and Electronics Engineers (IEEE)  

    DOI: 10.1109/tvt.2020.2980197

    Web of Science

    Scopus

  10. Person-Following Algorithm Based on Laser Range Finder and Monocular Camera Data Fusion for a Wheeled Autonomous Mobile Robot 査読有り 国際共著

    Elvira Chebotareva, Ramil Safin, Kuo-Hsien Hsia, Alexander Carballo, Evgeni Magid

    Lecture Notes in Computer Science   12336 巻   頁: 21 - 33   2020年9月

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    掲載種別:論文集(書籍)内論文   出版者・発行元:Springer International Publishing  

    DOI: 10.1007/978-3-030-60337-3_3

    Scopus

  11. Performance Analysis of 10 Models of 3D LiDARs for Automated Driving 査読有り

    Jacob Lambert, Alexander Carballo, Abraham Monrroy Cano, Patiphon Narksri, David Wong, Eijiro Takeuchi, Kazuya Takeda

    IEEE Access   8 巻   頁: 131699 - 131722   2020年7月

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    掲載種別:研究論文(学術雑誌)   出版者・発行元:Institute of Electrical and Electronics Engineers (IEEE)  

    DOI: 10.1109/access.2020.3009680

    Web of Science

    Scopus

  12. Personalized Subjective Driving Risk: Analysis and Prediction 査読有り

    Naren Bao, Alexander Carballo, Chiyomi Miyajima, Eijiro Takeuchi, Kazuya Takeda

    Journal of Robotics and Mechatronics   32 巻 ( 3 ) 頁: 503 - 519   2020年6月

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    掲載種別:研究論文(学術雑誌)   出版者・発行元:Fuji Technology Press Ltd.  

    Subjective risk assessment is an important technology for enhancing driving safety, because an individual adjusts his/her driving behavior according to his/her own subjective perception of risk. This study presents a novel framework for modeling personalized subjective driving risk during expressway lane changes. The objectives of this study are twofold: (i) to use ego vehicle driving signals and surrounding vehicle locations in a data-driven and explainable approach to identify the possible influential factors of subjective risk while driving and (ii) to predict the specific individual’s subjective risk level just before a lane change. We propose the personalized subjective driving risk model, a combined framework that uses a random forest-based method optimized by genetic algorithms to analyze the influential risk factors, and uses a bidirectional long short term memory to predict subjective risk. The results demonstrate that our framework can extract individual differences of subjective risk factors, and that the identification of individualized risk factors leads to better modeling of personalized subjective driving risk.

    DOI: 10.20965/jrm.2020.p0503

    Web of Science

    Scopus

  13. The PIX Moving KuaiKai: Building a Self-Driving Car in Seven Days 査読有り

    Vehicles, Drivers, and Safety     頁: 233 - 250   2020年5月

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    掲載種別:論文集(書籍)内論文   出版者・発行元:De Gruyter  

    DOI: 10.1515/9783110669787-014

  14. Characterization of Multiple 3D LiDARs for Localization and Mapping using Normal Distributions Transform

    Alexander Carballo, Abraham Monrroy, David Wong, Patiphon Narksri, Jacob Lambert, Yuki Kitsukawa, Eijiro Takeuchi, Shinpei Kato, Kazuya Takeda

        2020年4月

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    In this work, we present a detailed comparison of ten different 3D LiDAR
    sensors, covering a range of manufacturers, models, and laser configurations,
    for the tasks of mapping and vehicle localization, using as common reference
    the Normal Distributions Transform (NDT) algorithm implemented in the
    self-driving open source platform Autoware. LiDAR data used in this study is a
    subset of our LiDAR Benchmarking and Reference (LIBRE) dataset, captured
    independently from each sensor, from a vehicle driven on public urban roads
    multiple times, at different times of the day. In this study, we analyze the
    performance and characteristics of each LiDAR for the tasks of (1) 3D mapping
    including an assessment map quality based on mean map entropy, and (2) 6-DOF
    localization using a ground truth reference map.

    arXiv

    その他リンク: http://arxiv.org/pdf/2004.01374v1

  15. A Survey of Autonomous Driving: Common Practices and Emerging Technologies 査読有り

    Ekim Yurtsever, Jacob Lambert, Alexander Carballo, Kazuya Takeda

    IEEE Access   8 巻   頁: 58443 - 58469   2020年3月

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    掲載種別:研究論文(学術雑誌)   出版者・発行元:Institute of Electrical and Electronics Engineers (IEEE)  

    DOI: 10.1109/access.2020.2983149

    Web of Science

    Scopus

    arXiv

  16. Motion Analysis and Performance Improved Method for 3D LiDAR Sensor Data Compression 査読有り

    Chenxi Tu, Eijiro Takeuchi, Alexander Carballo, Chiyomi Miyajima, Kazuya Takeda

    IEEE Transactions on Intelligent Transportation Systems     頁: 243 - 256   2019年12月

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    掲載種別:研究論文(学術雑誌)   出版者・発行元:Institute of Electrical and Electronics Engineers (IEEE)  

    DOI: 10.1109/tits.2019.2956066

    Web of Science

    Scopus

  17. 3D Map Optimization with Fully Convolutional Neural Network and Dynamic Local NDT 査読有り 国際共著

    Zebang Shen, Yichong Xu, Muchen Sun, Alexander Carballo, Qingguo Zhou

    2019 IEEE Intelligent Transportation Systems Conference (ITSC)     頁: 4404 - 4411   2019年10月

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    掲載種別:研究論文(国際会議プロシーディングス)   出版者・発行元:IEEE  

    DOI: 10.1109/itsc.2019.8917130

    Web of Science

    Scopus

  18. Training Engineers in Autonomous Driving Technologies using Autoware 査読有り

    Alexander Carballo, David Wong, Yoshiki Ninomiya, Shinpei Kato, Kazuya Takeda

    2019 IEEE Intelligent Transportation Systems Conference (ITSC)     頁: 3347 - 3354   2019年10月

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    掲載種別:研究論文(国際会議プロシーディングス)   出版者・発行元:IEEE  

    DOI: 10.1109/itsc.2019.8917152

    Web of Science

    Scopus

  19. SECOND-DX: Single-model Multi-class Extension for Sparse 3D Object Detection 査読有り

    Yusuke Muramatsu, Yuki Tsuji, Alexander Carballo, Simon Thompson, Hiroyuki Chishiro, Shinpei Kato

    2019 IEEE Intelligent Transportation Systems Conference (ITSC)     頁: 2675 - 2680   2019年10月

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    掲載種別:研究論文(国際会議プロシーディングス)   出版者・発行元:IEEE  

    DOI: 10.1109/itsc.2019.8917386

    Web of Science

    Scopus

  20. Personalized Safety-focused Control by Minimizing Subjective Risk 査読有り

    Naren Bao, Dongfang Yang, Alexander Carballo, Umit Ozguner, Kazuya Takeda

    2019 IEEE Intelligent Transportation Systems Conference (ITSC)     頁: 3853 - 3858   2019年10月

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    掲載種別:研究論文(国際会議プロシーディングス)   出版者・発行元:IEEE  

    DOI: 10.1109/itsc.2019.8917457

    Web of Science

    Scopus

  21. Real-Time Streaming Point Cloud Compression for 3D LiDAR Sensor Using U-Net 査読有り

    Chenxi Tu, Eijiro Takeuchi, Alexander Carballo, Kazuya Takeda

    IEEE Access   7 巻   頁: 113616 - 113625   2019年8月

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    掲載種別:研究論文(学術雑誌)   出版者・発行元:Institute of Electrical and Electronics Engineers (IEEE)  

    DOI: 10.1109/access.2019.2935253

    Web of Science

    Scopus

  22. End-to-End Driving using Point Cloud Features 査読有り

    Shunya Seiya, Alexander Carballo, Eijiro Takeuchi, Kazuya Takeda

    5th International Symposium on Future Active Safety Technology toward Zero Accidents (FAST-Zero'19)     2019年6月

  23. Recognition Assistance Interface for Autonomous Vehicles 査読有り

    Atsushi Kuribayashi, Eijiro Takeuchi, Alexander Carballo, Kazuya Takeda

    5th International Symposium on Future Active Safety Technology toward Zero Accidents (FAST-Zero'19)     2019年6月

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    掲載種別:研究論文(国際会議プロシーディングス)  

  24. Predicting pedestrian crossing intention using temporal contexts 査読有り

    Tajinder Singh, Alexander Carballo, Eijiro Takeuchi, Kazuya Takeda

    5th International Symposium on Future Active Safety Technology toward Zero Accidents (FAST-Zero'19)     2019年6月

  25. Point Cloud Compression for 3D LiDAR Sensor using Recurrent Neural Network with Residual Blocks 査読有り

    Chenxi Tu, Eijiro Takeuchi, Alexander Carballo, Kazuya Takeda

    2019 International Conference on Robotics and Automation (ICRA)     頁: 3274 - 3280   2019年5月

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    掲載種別:研究論文(国際会議プロシーディングス)   出版者・発行元:IEEE  

    DOI: 10.1109/icra.2019.8794264

    Web of Science

    Scopus

  26. End-to-End Navigation with Branch Turning Support Using Convolutional Neural Network 査読有り

    Shunya Seiya, Alexander Carballo, Eijiro Takeuchi, Chiyomi Miyajima, Kazuya Takeda

    2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)     頁: 499 - 506   2018年12月

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    記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)   出版者・発行元:IEEE  

    © 2018 IEEE. End-to-end navigation refers to methods of generating control signals for mobile autonomous devices directly from external sensors, which is an area gaining attention within the autonomous driving research community. Previous autonomous driving research has mostly been focused on keeping moving vehicles within their lanes, but reliable navigation along other trajectories, including branching off onto other routes, has not yet been achieved. In this study we propose a deep learning system for end-to-end navigation which would allow an autonomous vehicle to turn at intersections. Our system's inputs include camera images and directions to a target, while the outputs are the steering control signals needed to direct the vehicle. We validate the system's performance by conducting experiments involving three different driving scenarios: short, indoor trajectories containing a single branching turn; long, outdoor trajectories containing many branching turns; and long, outdoor trajectories which were not included during training. Our end-to-end navigation system allowed an autonomous robot to successfully follow outdoor trajectories with right and left turns, including those which were not part of the training course.

    DOI: 10.1109/robio.2018.8665079

    Web of Science

    Scopus

  27. High Density Ground Maps using Low Boundary Height Estimation for Autonomous Vehicles 査読有り

    Alexander Carballo, Eijiro Takeuchi, Kazuya Takeda

    2018 21st International Conference on Intelligent Transportation Systems (ITSC)     頁: 3811 - 3818   2018年11月

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    担当区分:筆頭著者   掲載種別:研究論文(国際会議プロシーディングス)   出版者・発行元:IEEE  

    DOI: 10.1109/itsc.2018.8569764

    Web of Science

    Scopus

  28. The PIX Moving Kuaikai – Building a Self-Driving Car in 7 Days 査読有り

    David Robert Wong, Alexander Carballo, Rohan Rao, Oscar Rovira, Chuan Yu

    8th Biennial Workshop on DSP in Vehicles     頁: O2-2   2018年10月

  29. End-to-End Autonomous Mobile Robot Navigation with Model-Based System Support 査読有り

    Alexander Carballo, Shunya Seiya, Jacob Lambert, Hatem Darweesh, Patiphon Narksri, Luis Yoichi Morales, Naoki Akai, Eijiro Takeuchi, Kazuya Takeda

    Journal of Robotics and Mechatronics   30 巻 ( 4 ) 頁: 563 - 583   2018年8月

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    掲載種別:研究論文(学術雑誌)   出版者・発行元:Fuji Technology Press Ltd.  

    Autonomous mobile robot navigation in real unmodified outdoor areas frequented by people on their business, children playing, fast running bicycles, and even robots, remains a difficult challenge. For eleven years, the Tsukuba Challenge Real World Robot Challenge (RWRC) has brought together robots, researchers, companies, government, and ordinary citizens, under the same outdoor space to push forward the limits of autonomous mobile robots. For the Tsukuba Challenge 2017 participation, our team proposed to study the problem of sensors-to-actuators navigation (also called End-to-End), this is, having the robot to navigate towards the destination on a complex path, not only moving straight but also turning at intersections. End-to-End (E2E) navigation was implemented using a convolutional neural network (CNN): the robot learns how to go straight, turn left, and turn right, using camera images and trajectory data. E2E network training and evaluation was performed at Nagoya University, on similar outdoor conditions to that of Tsukuba Challenge 2017 (TC2017). Even thought E2E was trained on a different environment and conditions, the robot successfully followed the designated trajectory in the TC2017 course. Learning how to follow the road no matter the environment is of the key attributes of E2E based navigation. Our E2E does not perform obstacle avoidance and can be affected by illumination and seasonal changes. Therefore, to improve safety and add fault tolerance measures, we developed an E2E navigation approach with model-based system as backup. The model-based system is based on our open source autonomous vehicle software adapted to use on a mobile robot. In this work we describe our approach, implementation, experiences and main contributions.

    DOI: 10.20965/jrm.2018.p0563

    Web of Science

    Scopus

  30. Tsukuba Challenge 2017 Dynamic Object Tracks Dataset for Pedestrian Behavior Analysis 査読有り

    Jacob Lambert, Leslie Liang, Luis Yoichi Morales, Naoki Akai, Alexander Carballo, Eijiro Takeuchi, Patiphon Narksri, Shunya Seiya, Kazuya Takeda

    Journal of Robotics and Mechatronics   30 巻 ( 4 ) 頁: 598 - 612   2018年8月

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    掲載種別:研究論文(学術雑誌)   出版者・発行元:Fuji Technology Press Ltd.  

    Navigation in social environments, in the absence of traffic rules, is the difficult task at the core of the annual Tsukuba Challenge. In this context, a better understanding of the soft rules that influence social dynamics is key to improve robot navigation. Prior research attempts to model social behavior through microscopic interactions, but the resulting emergent behavior depends heavily on the initial conditions, in particular the macroscopic setting. As such, data-driven studies of pedestrian behavior in a fixed environment may provide key insight into this macroscopic aspect, but appropriate data is scarcely available. To support this stream of research, we release an open-source dataset of dynamic object trajectories localized in a map of 2017 Tsukuba Challenge environment. A data collection platform equipped with lidar, camera, IMU, and odometry repeatedly navigated the challenge’s course, recording observations of passersby. Using a background map, we localized ourselves in the environment, removed the static background from the point cloud data, clustered the remaining points into dynamic objects and tracked their movements over time. In this work, we present the Tsukuba Challenge Dynamic Object Tracks dataset, which features nearly 10,000 trajectories of pedestrians, cyclists, and other dynamic agents, in particular autonomous robots. We provide a 3D map of the environment used as global frame for all trajectories. For each trajectory, we provide at regular time intervals an estimated position, velocity, heading, and rotational velocity, as well as bounding boxes for the objects and segmented lidar point clouds. As additional contribution, we provide a discussion which focuses on some discernible macroscopic patterns in the data.

    DOI: 10.20965/jrm.2018.p0598

    Web of Science

    Scopus

  31. CNNを用いたEnd-to-Endナビゲーションシステムによるつくばチャレンジへの取り組み

    清谷竣也, CARBALLO Alexander, 竹内栄二朗, 宮島千代美, 宮島千代美, 武田一哉, 武田一哉

    計測自動制御学会システムインテグレーション部門講演会(CD-ROM)   18th 巻   2017年

     詳細を見る

  32. Reliable People Detection Using Range and Intensity Data from Multiple Layers of Laser Range Finders on a Mobile Robot 査読有り

    Alexander Carballo, Akihisa Ohya, Shin’ichi Yuta

    International Journal of Social Robotics   3 巻 ( 2 ) 頁: 167 - 186   2011年4月

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    掲載種別:研究論文(学術雑誌)   出版者・発行元:Springer Science and Business Media LLC  

    DOI: 10.1007/s12369-010-0086-3

    Web of Science

    Scopus

    J-GLOBAL

    その他リンク: http://link.springer.com/article/10.1007/s12369-010-0086-3/fulltext.html

  33. 二層配置レーザ距離センサを用いた移動ロボットのための人間検出に関する研究 査読有り

    カルバヨ アレックサンダー

    筑波大学博士 (工学)博士論文   甲第5686号 巻   2011年3月

     詳細を見る

    担当区分:筆頭著者, 責任著者   記述言語:英語   掲載種別:学位論文(博士)  

  34. People detection using range and intensity data from multi-layered Laser Range Finders 査読有り

    Alexander Carballo, Akihisa Ohya, Shin'ichi Yuta

    2010 IEEE/RSJ International Conference on Intelligent Robots and Systems     頁: 5849 - 5854   2010年10月

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    担当区分:筆頭著者, 責任著者   掲載種別:研究論文(国際会議プロシーディングス)   出版者・発行元:IEEE  

    DOI: 10.1109/iros.2010.5649769

    Web of Science

    Scopus

  35. Laser reflection intensity and multi-layered Laser Range Finders for people detection 査読有り

    Alexander Carballo, Akihisa Ohya, Shin'ichi Yuta

    19th International Symposium in Robot and Human Interactive Communication     頁: 379 - 384   2010年9月

     詳細を見る

    担当区分:筆頭著者   掲載種別:研究論文(国際会議プロシーディングス)   出版者・発行元:IEEE  

    DOI: 10.1109/roman.2010.5598657

    Web of Science

    Scopus

    J-GLOBAL

  36. Multiple people detection from a mobile robot using double layered laser range finders 査読有り

    Alexander Carballo, Akihisa Ohya, Shin'ichi Yuta

    IEEE International Conference on Robotics and Automation (ICRA) Workshop on People Detection and Tracking     頁: 94 - 100   2009年5月

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    担当区分:筆頭著者  

  37. People Detection using Double Layered Multiple Laser Range Finders by a Companion Robot 査読有り

    Alexander Carballo, Akihisa Ohya, Shin’ichi Yuta

    Lecture Notes in Electrical Engineering     頁: 315 - 331   2009年3月

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    担当区分:筆頭著者   掲載種別:論文集(書籍)内論文   出版者・発行元:Springer Berlin Heidelberg  

    DOI: 10.1007/978-3-540-89859-7_22

    Scopus

    J-GLOBAL

  38. 屋外の雑然とした歩道での自律ロボットナビゲーション

    MORALES Yoichi, CARBALLO Alexander, TAKEUCHI Eijiro, ABURADANI Atsushi, TSUBOUCHI Takashi

    Journal of Field Robotics   26 巻 ( 8 ) 頁: 609 - 635   2009年

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    記述言語:英語   掲載種別:研究論文(学術雑誌)  

    DOI: 10.1002/rob.20301

    Web of Science

    Scopus

    J-GLOBAL

  39. つくばチャレンジ 2008 における筑波大学知能ロボット研究室 「屋外組」 の取組み 査読有り

    坪内, Y. Morales, A. Carballo, 原, 油谷, 城吉, 廣澤, 鈴木, K. Mehrez, 山口, 澤田, 森川

    第 9 回 SICE システムインテグレーション部門講演会 (SI2008)     2008年12月

  40. 1Km autonomous robot navigation on outdoor pedestrian paths "Running the Tsukuba challenge 2007" 査読有り

    Yoichi MORALES, Eijiro TAKEUCHI, Alexander CARBALLO, Wataru TOKUNAGA, Hiroyasu KUNIYOSHI, Atsushi ABURADANI, Atsushi HIROSAWA, Yoshisada NAGASAKA, Yusuke SUZUKI, Takashi TSUBOUCHI

    2008 IEEE/RSJ International Conference on Intelligent Robots and Systems     頁: 22 - 26   2008年9月

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    掲載種別:研究論文(国際会議プロシーディングス)   出版者・発行元:IEEE  

    DOI: 10.1109/iros.2008.4650584

    Web of Science

    Scopus

  41. Fusion of double layered multiple laser range finders for people detection from a mobile robot 査読有り

    Alexander Carballo, Akihisa Ohya, Shin'ichi Yuta

    2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems     頁: 677 - 682   2008年8月

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    担当区分:筆頭著者   掲載種別:研究論文(国際会議プロシーディングス)   出版者・発行元:IEEE  

    DOI: 10.1109/mfi.2008.4648023

    Web of Science

    Scopus

  42. Time synchronization between SOKUIKI sensor and host computer using timestamps 査読有り

    Alexander Carballo, Yoshitaka Hara, Hirohiko Kawata, Tomoaki Yoshida, Akihisa Ohya, Shin'ichi Yuta

    2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems     頁: 261 - 266   2008年8月

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    担当区分:筆頭著者   掲載種別:研究論文(国際会議プロシーディングス)   出版者・発行元:IEEE  

    DOI: 10.1109/mfi.2008.4648075

    J-GLOBAL

  43. 筑波大学知能ロボット研究室 『屋外組』 における屋外走行ロボットのシステムインテグレーション 査読有り

    坪内, Y. Morales, 徳永, 竹内, A. Carballo, 城吉, 鈴木, 油谷, 廣澤

    第 8 回 SICE システムインテグレーション部門講演会 (SI2007)     2007年12月

  44. 時刻印によるSOKUIKIセンサとホストコンピュータの間の同期化 査読有り

    Alexander CARBALLO, Yoshitaka HARA, Hirohiko KAWATA, Tomoaki YOSHIDA, Akihisa OHYA, Shin'ichi YUTA

    日本機械学会ロボティクス・メカトロニクス講演会講演論文集(CD-ROM)   1P1-K05 巻   2007年11月

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    担当区分:筆頭著者   記述言語:英語   掲載種別:研究論文(国際会議プロシーディングス)  

    DOI: 10.1109/MFI.2008.4648075

    Web of Science

    Scopus

    J-GLOBAL

  45. Developing a Web Caching architecture with configurable consistency: A proposal 査読有り

    Francisco J. Torres-Rojas, Esteban Meneses, Alexander Carballo

    WEBIST 2005 - 1st International Conference on Web Information Systems and Technologies, Proceedings     頁: 110 - 116   2005年1月

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    担当区分:筆頭著者, 責任著者   掲載種別:研究論文(国際会議プロシーディングス)  

    In recent years, Web Caching has been considered one of the key areas to improve web usage efficiency. However, caching web objects proposes many considerations about the validity of the cache. Ideally, it would be valuable to have a consistent cache, where no invalid relationships among objects are held. Several alternatives have been offered to keep consistency in the web cache, each one being better in different situations and for diverse requirements. Usually, web cachers implement just one strategy for maintaining consistency, sometimes giving bad results if circumstances are not appropriate for such strategy. Given that, a web cacher where this policy can be adapted to different situations, will offer good results in an execution with changing conditions. A web caching architecture is proposed as a testbed for consistency models, allowing both timing and ordering issues to be considered.

    Scopus

▼全件表示

講演・口頭発表等 4

  1. LIBRE Dataset: A Study of Multiple 3D LiDARs Performance for Autonomous Driving 招待有り

    第2回自律移動体シームレス化研究会, 愛知県公益財団法人 科学技術交流財団  2020年12月3日 

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    開催年月日: 2020年12月

    会議種別:口頭発表(一般)  

  2. Education in Autonomous Driving Technologies using Autoware

    Alexander Carballo

    IEEE Intelligent Vehicles Symposium (IV) Autoware – ROS-based OSS for Autonomous Driving Workshop  2020年10月23日 

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    開催年月日: 2020年10月

    会議種別:口頭発表(一般)  

  3. LIBRE: The 3D LiDAR Dataset – leveraging access to LiDARs 招待有り

    Alexander Carballo, Jacob Lambert, Abraham Israel Monrroy Cano, David Robert Wong, Patiphon Narksri, Yuki Kitsukawa, Eijiro Takeuchi, Shinpei Kato, Kazuya Takeda

    Automotive LiDAR 2020, 3rd Annual Conference and Exhibition, Michigan, USA  2020年9月24日 

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    開催年月日: 2020年9月

    会議種別:口頭発表(一般)  

  4. CNNを用いたEnd-to-Endナビゲーションシステムによるつくばチャレンジへの取り組み

    清谷竣也, CARBALLO Alexander, 竹内栄二朗, 宮島千代美, 宮島千代美, 武田一哉, 武田一哉

    計測自動制御学会システムインテグレーション部門講演会(CD-ROM)  2017年 

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    開催年月日: 2017年