Updated on 2021/08/03

写真a

 
CARBALLO SEGURA Alexander
 
Organization
Institutes of Innovation for Future Society Mobility Research Course Designated associate professor
Graduate School
Graduate School of Informatics
Title
Designated associate professor
Contact information
メールアドレス
Other name(s)
CARBALLO Alexander
Profile
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.
External link

Degree 1

  1. Doctor of Philosophy in Engineering ( 2011.3   University of Tsukuba ) 

Research Interests 8

  1. Autonomous Robots

  2. Autonomous Vehicles

  3. Computer Vision

  4. Machine Learning

  5. Artificial Intelligence

  6. Computer Engineering

  7. Computer Networks

  8. LiDAR

Research Areas 3

  1. Manufacturing Technology (Mechanical Engineering, Electrical and Electronic Engineering, Chemical Engineering) / Communication and network engineering

  2. Informatics / Perceptual information processing  / LiDAR, Computer Vision

  3. Informatics / Intelligent robotics

Research History 5

  1. Tier IV Inc.   Senior Research Fellow

    2018.1

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    Country:Japan

  2. Nagoya University   Institute of Innovation for Future Society   Designated associate professor

    2017.7

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    Country:Japan

  3. Osaka City University   Graduate School of Engineering   Part time lecturer

    2016.10

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    Country:Japan

  4. Hokuyo Automatic Co. Ltd.   Research and Development

    2011.4 - 2017.6

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    Country:Japan

  5. Costa Rica Institute of Technology   Department of Computer Science   Lecturer

    1996.1 - 2006.6

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    Country:Costa Rica

Education 2

  1. University of Tsukuba   Graduate school of Systems and Information Engineering   Department of Computer Science

    2007.4 - 2011.3

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    Country: Japan

    Notes: Doctoral Program

  2. University of Tsukuba   Graduate School of Systems and Information Engineering   Department of Computer Science

    2006.4 - 2007.3

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    Country: Japan

    Notes: Research student at Intelligent Robots Lab.

Professional Memberships 4

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

    2019.10

  2. IEEE Intelligent Transportation Systems Society (ITSS)

    2018.1

  3. Robotics Society of Japan (RSJ)

    2009.4

  4. IEEE Robotics and Automation Society (RAS)

    2008.1

Awards 1

  1. Journal of Robotics and Mechatronics (JRM) Best Paper Award 2019

    2020.1   Fuji Technology Press Ltd.   End-to-End Autonomous Mobile Robot Navigation with Model-Based System Support

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

 

Papers 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)     2021.7

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

    Yafu Tian, Alexander Carballo, Ruifeng Li, Kazuya Takeda

    IEEE Intelligent Vehicles Symposium (IV)     2021.7

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

    Naren Bao, Alexander Carballo, Kazuya Takeda

    IEEE Intelligent Vehicles Symposium (IV)     2021.7

  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     2021.7

  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     2021.7

  6. Road Scene Graph: A Semantic Graph-Based Scene Representation Dataset for Intelligent Vehicles Reviewed

    Yafu Tian, Alexander Carballo, Ruifeng Li, Kazuya Takeda

        2020.11

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    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

    Other Link: http://arxiv.org/pdf/2011.13588v1

  7. LIBRE: The Multiple 3D LiDAR Dataset Reviewed

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

    2020 IEEE Intelligent Vehicles Symposium (IV)     page: 823 - 830   2020.10

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    Authorship:Lead author   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/iv47402.2020.9304681

    arXiv

  8. Point Grid Map-Based Mid-To-Mid Driving without Object Detection Reviewed

    Shunya Seiya, Alexander Carballo, Eijiro Takeuchi, Kazuya Takeda

    2020 IEEE Intelligent Vehicles Symposium (IV)     page: 2044 - 2051   2020.10

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    Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/iv47402.2020.9304809

    Scopus

  9. Extracting Human-Like Driving Behaviors From Expert Driver Data Using Deep Learning Reviewed

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

    IEEE Transactions on Vehicular Technology   Vol. 69 ( 9 ) page: 9315 - 9329   2020.9

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    Publishing type:Research paper (scientific journal)   Publisher: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 Reviewed International coauthorship

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

    Lecture Notes in Computer Science   Vol. 12336   page: 21 - 33   2020.9

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    Publishing type:Part of collection (book)   Publisher: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 Reviewed

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

    IEEE Access   Vol. 8   page: 131699 - 131722   2020.7

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    Publishing type:Research paper (scientific journal)   Publisher: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 Reviewed

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

    Journal of Robotics and Mechatronics   Vol. 32 ( 3 ) page: 503 - 519   2020.6

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    Publishing type:Research paper (scientific journal)   Publisher: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 Reviewed

    Vehicles, Drivers, and Safety     page: 233 - 250   2020.5

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    Publishing type:Part of collection (book)   Publisher: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

        2020.4

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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

    Other Link: http://arxiv.org/pdf/2004.01374v1

  15. A Survey of Autonomous Driving: Common Practices and Emerging Technologies Reviewed

    Ekim Yurtsever, Jacob Lambert, Alexander Carballo, Kazuya Takeda

    IEEE Access   Vol. 8   page: 58443 - 58469   2020.3

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    Publishing type:Research paper (scientific journal)   Publisher: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 Reviewed

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

    IEEE Transactions on Intelligent Transportation Systems     page: 243 - 256   2019.12

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    Publishing type:Research paper (scientific journal)   Publisher: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 Reviewed International coauthorship

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

    2019 IEEE Intelligent Transportation Systems Conference (ITSC)     page: 4404 - 4411   2019.10

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    Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/itsc.2019.8917130

    Web of Science

    Scopus

  18. Training Engineers in Autonomous Driving Technologies using Autoware Reviewed

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

    2019 IEEE Intelligent Transportation Systems Conference (ITSC)     page: 3347 - 3354   2019.10

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    Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/itsc.2019.8917152

    Web of Science

    Scopus

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

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

    2019 IEEE Intelligent Transportation Systems Conference (ITSC)     page: 2675 - 2680   2019.10

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    Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/itsc.2019.8917386

    Web of Science

    Scopus

  20. Personalized Safety-focused Control by Minimizing Subjective Risk Reviewed

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

    2019 IEEE Intelligent Transportation Systems Conference (ITSC)     page: 3853 - 3858   2019.10

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    Publishing type:Research paper (international conference proceedings)   Publisher: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 Reviewed

    Chenxi Tu, Eijiro Takeuchi, Alexander Carballo, Kazuya Takeda

    IEEE Access   Vol. 7   page: 113616 - 113625   2019.8

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    Publishing type:Research paper (scientific journal)   Publisher: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 Reviewed

    Shunya Seiya, Alexander Carballo, Eijiro Takeuchi, Kazuya Takeda

    5th International Symposium on Future Active Safety Technology toward Zero Accidents (FAST-Zero'19)     2019.6

  23. Recognition Assistance Interface for Autonomous Vehicles Reviewed

    Atsushi Kuribayashi, Eijiro Takeuchi, Alexander Carballo, Kazuya Takeda

    5th International Symposium on Future Active Safety Technology toward Zero Accidents (FAST-Zero'19)     2019.6

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    Publishing type:Research paper (international conference proceedings)  

  24. Predicting pedestrian crossing intention using temporal contexts Reviewed

    Tajinder Singh, Alexander Carballo, Eijiro Takeuchi, Kazuya Takeda

    5th International Symposium on Future Active Safety Technology toward Zero Accidents (FAST-Zero'19)     2019.6

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

    Chenxi Tu, Eijiro Takeuchi, Alexander Carballo, Kazuya Takeda

    2019 International Conference on Robotics and Automation (ICRA)     page: 3274 - 3280   2019.5

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    Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/icra.2019.8794264

    Web of Science

    Scopus

  26. End-to-End Navigation with Branch Turning Support Using Convolutional Neural Network Reviewed

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

    2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)     page: 499 - 506   2018.12

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher: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 Reviewed

    Alexander Carballo, Eijiro Takeuchi, Kazuya Takeda

    2018 21st International Conference on Intelligent Transportation Systems (ITSC)     page: 3811 - 3818   2018.11

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    Authorship:Lead author   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/itsc.2018.8569764

    Web of Science

    Scopus

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

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

    8th Biennial Workshop on DSP in Vehicles     page: O2-2   2018.10

  29. End-to-End Autonomous Mobile Robot Navigation with Model-Based System Support Reviewed

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

    Journal of Robotics and Mechatronics   Vol. 30 ( 4 ) page: 563 - 583   2018.8

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    Publishing type:Research paper (scientific journal)   Publisher: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 Reviewed

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

    Journal of Robotics and Mechatronics   Vol. 30 ( 4 ) page: 598 - 612   2018.8

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    Publishing type:Research paper (scientific journal)   Publisher: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)   Vol. 18th   2017

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

    Alexander Carballo, Akihisa Ohya, Shin’ichi Yuta

    International Journal of Social Robotics   Vol. 3 ( 2 ) page: 167 - 186   2011.4

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    Publishing type:Research paper (scientific journal)   Publisher:Springer Science and Business Media LLC  

    DOI: 10.1007/s12369-010-0086-3

    Web of Science

    Scopus

    J-GLOBAL

    Other Link: http://link.springer.com/article/10.1007/s12369-010-0086-3/fulltext.html

  33. A study on people detection using a double-layered arrangement of Laser Range Scanners for social mobile robots Reviewed

    Alexander Carballo

    Thesis (Ph. D. in Engineering)--University ofTsukuba   Vol. 甲第5686号   2011.3

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Doctoral thesis  

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

    Alexander Carballo, Akihisa Ohya, Shin'ichi Yuta

    2010 IEEE/RSJ International Conference on Intelligent Robots and Systems     page: 5849 - 5854   2010.10

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    Authorship:Lead author, Corresponding author   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/iros.2010.5649769

    Web of Science

    Scopus

  35. Laser reflection intensity and multi-layered Laser Range Finders for people detection Reviewed

    Alexander Carballo, Akihisa Ohya, Shin'ichi Yuta

    19th International Symposium in Robot and Human Interactive Communication     page: 379 - 384   2010.9

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    Authorship:Lead author   Publishing type:Research paper (international conference proceedings)   Publisher: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 Reviewed

    Alexander Carballo, Akihisa Ohya, Shin'ichi Yuta

    IEEE International Conference on Robotics and Automation (ICRA) Workshop on People Detection and Tracking     page: 94 - 100   2009.5

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    Authorship:Lead author  

  37. People Detection using Double Layered Multiple Laser Range Finders by a Companion Robot Reviewed

    Alexander Carballo, Akihisa Ohya, Shin’ichi Yuta

    Lecture Notes in Electrical Engineering     page: 315 - 331   2009.3

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    Authorship:Lead author   Publishing type:Part of collection (book)   Publisher:Springer Berlin Heidelberg  

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

    Scopus

    J-GLOBAL

  38. Autonomous Robot Navigation in Outdoor Cluttered Pedestrian Walkways

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

    Journal of Field Robotics   Vol. 26 ( 8 ) page: 609 - 635   2009

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:WILEY  

    This paper describes an implementation of a mobile robot system for autonomous navigation in outdoor concurred walkways. The task was to navigate through nonmodified pedestrian paths with people and bicycles passing by. The robot has multiple redundant sensors, which include wheel encoders, an inertial measurement unit, a differential global positioning system, and four laser scanner sensors. All the computation was done on a single laptop computer. A previously constructed map containing waypoints and landmarks for position correction is given to the robot. The robot system's perception, road extraction, and motion planning are detailed. The system was used and tested in a 1-km autonomous robot navigation challenge held in the City of Tsukuba, Japan, named "Tsukuba Challenge 2007." The proposed approach proved to be robust for outdoor navigation in cluttered and crowded walkways, first on campus paths and then running the challenge course multiple times between trials and the challenge final. The paper reports experimental results and overall performance of the system. Finally the lessons learned are discussed. The main contribution of this work is the report of a system integration approach for autonomous outdoor navigation and its evaluation. © 2009 Wiley Periodicals, Inc.

    DOI: 10.1002/rob.20301

    Web of Science

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    J-GLOBAL

  39. Tsukuba University Intelligent Robot Laboratory "Okugai-gumi" Initiatives at Tsukuba Challenge 2008 Reviewed

    Takashi TSUBOUCHI, Yoichi MORALES, Alexander CARBALLO, Yoshitaka HARA, Atsushi ABURADANI, Hiroyasu KUNIYOSHI, Atsushi HIROSAWA, Yusuke SUZUKI, Kristou MEHREZ, Tomoya YAMAGUCHI, Yukiko Sawada, Naoki MORIKAWA

        2008.12

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

    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     page: 22 - 26   2008.9

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    Publishing type:Research paper (international conference proceedings)   Publisher: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 Reviewed

    Alexander Carballo, Akihisa Ohya, Shin'ichi Yuta

    2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems     page: 677 - 682   2008.8

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    Authorship:Lead author   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/mfi.2008.4648023

    Web of Science

    Scopus

  42. Time synchronization between SOKUIKI sensor and host computer using timestamps Reviewed

    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     page: 261 - 266   2008.8

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    Authorship:Lead author   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/mfi.2008.4648075

    J-GLOBAL

  43. System integration approach for outdoor traveling robots of the "Okugai-gumi" of the Intelligent Robot Laboratory at University of Tsukuba Reviewed

    Takashi Tsubouchi, Y. Morales, Wataru Tokunaga, Eijiro Takeuchi, A. Carballo, Hiroyasu Kuniyoshi, Yusuke Suzuki, Atsushi Aburadani, Atsushi Hirosawa

        2007.12

  44. Time Synchronization between SOKUIKI Sensor and Host Computer using Timestamps Reviewed

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

    2007 JSME Annual Conference on Robotics and Mechatronics (Robomec)   Vol. 1P1-K05   2007.11

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    Authorship:Lead author   Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    Time is crucial in applications such as sensor data fusion, autonomous mobility and SLAM. However clocks at end systems are rarely synchronized and often running at different speeds. Lack of synchronization therefore reduces the accuracy of sensor readings. The SOKUIKI scanning laser range finder allows acquiring time values by timestamping range readings. Our work consists in a method for time synchronization, with clock skew estimation, between a laser range finder sensor and a host computer. ©2008 IEEE.

    DOI: 10.1109/MFI.2008.4648075

    Web of Science

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  45. Developing a Web Caching architecture with configurable consistency: A proposal Reviewed

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

    WEBIST 2005 - 1st International Conference on Web Information Systems and Technologies, Proceedings     page: 110 - 116   2005.1

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    Authorship:Lead author, Corresponding author   Publishing type:Research paper (international conference proceedings)  

    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.

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Presentations 4

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

    2020.12.3 

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    Event date: 2020.12

    Presentation type:Oral presentation (general)  

  2. Education in Autonomous Driving Technologies using Autoware

    Alexander Carballo

    IEEE Intelligent Vehicles Symposium (IV) Autoware – ROS-based OSS for Autonomous Driving Workshop  2020.10.23 

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    Event date: 2020.10

    Presentation type:Oral presentation (general)  

  3. LIBRE: The 3D LiDAR Dataset – leveraging access to LiDARs Invited

    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  2020.9.24 

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    Event date: 2020.9

    Presentation type:Oral presentation (general)  

  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 

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    Event date: 2017