The Experts below are selected from a list of 88149 Experts worldwide ranked by ideXlab platform

Michinori Hatayama - One of the best experts on this subject based on the ideXlab platform.

  • creating spatial temporal database by autonomous mobile surveillance system a study of mobile robot surveillance system using spatial temporal gis part 1
    International Symposium on Safety Security and Rescue Robotics, 2005
    Co-Authors: Junichi Meguro, K Ishikawa, Yoshiharu Amano, Takumi Hashizume, Junichi Takiguchi, Ryujiro Kurosaki, Michinori Hatayama
    Abstract:

    This study describes mobile robot surveillance system using spatial temporal GIS. This paper specially describes the method of collecting spatial temporal data by an autonomous mobile robot system used in a factory premises with some high-rise buildings. This system consists of a wireless LAN network, a base station and an autonomous vehicle. The vehicle is equipped with a GPS/INS navigation system using the network-based real-time kinematic GPS (RTK-GPS) with positioning augmentation services (PAS/spl trade/ Mitsubishi Electric Corporation 2003), an area laser radar (ALR), a slaved camera, and an omni-directional vision (ODV) sensor for surveillance and reconnaissance. The vehicle switches control modes according to the vehicle navigation error. It has three modes, "normal", "road tracking", and "crossing recognition". A Field Test Result shows that the vehicle can track the planned-path within 0.10[m] accuracy at straight paths and within 0.25[m] for curved paths even if RTK fixed solutions are not available. Field experiments and analyses have proved that the proposed navigation method can provide sufficient navigation and guidance accuracy under poor satellite geometry and visibility. Omni-directional image and ALR'S scan data, which is synchronized with both position and GPS time, is memorized as spatial temporal. This spatial temporal data enables the operator to search everywhere in the factory premises efficiently by way of arbitrary position or measured time. The Field Test reveals that the spatial temporal database is confirmed to be useful for remote surveillance.

Junichi Meguro - One of the best experts on this subject based on the ideXlab platform.

  • creating spatial temporal database by autonomous mobile surveillance system a study of mobile robot surveillance system using spatial temporal gis part 1
    International Symposium on Safety Security and Rescue Robotics, 2005
    Co-Authors: Junichi Meguro, K Ishikawa, Yoshiharu Amano, Takumi Hashizume, Junichi Takiguchi, Ryujiro Kurosaki, Michinori Hatayama
    Abstract:

    This study describes mobile robot surveillance system using spatial temporal GIS. This paper specially describes the method of collecting spatial temporal data by an autonomous mobile robot system used in a factory premises with some high-rise buildings. This system consists of a wireless LAN network, a base station and an autonomous vehicle. The vehicle is equipped with a GPS/INS navigation system using the network-based real-time kinematic GPS (RTK-GPS) with positioning augmentation services (PAS/spl trade/ Mitsubishi Electric Corporation 2003), an area laser radar (ALR), a slaved camera, and an omni-directional vision (ODV) sensor for surveillance and reconnaissance. The vehicle switches control modes according to the vehicle navigation error. It has three modes, "normal", "road tracking", and "crossing recognition". A Field Test Result shows that the vehicle can track the planned-path within 0.10[m] accuracy at straight paths and within 0.25[m] for curved paths even if RTK fixed solutions are not available. Field experiments and analyses have proved that the proposed navigation method can provide sufficient navigation and guidance accuracy under poor satellite geometry and visibility. Omni-directional image and ALR'S scan data, which is synchronized with both position and GPS time, is memorized as spatial temporal. This spatial temporal data enables the operator to search everywhere in the factory premises efficiently by way of arbitrary position or measured time. The Field Test reveals that the spatial temporal database is confirmed to be useful for remote surveillance.

Taku Noda - One of the best experts on this subject based on the ideXlab platform.

  • Application of Frequency-Partitioning Fitting to the Phase-Domain Frequency-Dependent Modeling of Overhead Transmission Lines
    IEEE Transactions on Power Delivery, 2015
    Co-Authors: Taku Noda
    Abstract:

    This paper shows that a previously proposed linear-system identification method based on frequency partitioning and adaptive weighting can be successfully applied to the phase-domain frequency-dependent modeling of overhead transmission lines for electromagnetic transient simulations. As the framework of the phase-domain modeling, the universal line model is used, and the frequency responses of the characteristic admittance and propagation function matrices are realized by linear equivalents obtained by the identification method mentioned before, instead of the well-known Vector Fitting method. In this paper, numerical techniques to enhance the identification method for this phase-domain line modeling application are also presented. For validation, the proposed approach is applied to modeling an existing 500-kV double-circuit transmission line. The effectiveness of the numerical techniques for enhancements are shown through the modeling process, and transient waveforms obtained by the proposed approach are compared with those by the rigorous Laplace transform method and with a Field-Test Result.

  • Application of frequency-partitioning fitting to the phase-domain frequency-dependent modeling of overhead transmission lines
    2015 IEEE Power & Energy Society General Meeting, 2015
    Co-Authors: Taku Noda
    Abstract:

    This paper shows that a previously proposed linear-system identification method based on frequency partitioning and adaptive weighting can be successfully applied to the phase-domain frequency-dependent modeling of overhead transmission lines for electromagnetic transient (EMT) simulations. As the framework of the phase-domain modeling, the universal line model (ULM) is used, and the frequency responses of the characteristic-admittance and the propagation-function matrix are realized by linear equivalents obtained by the identification method mentioned above, instead of the well-known Vector Fitting (VF) method. In this paper, numerical techniques to enhance the identification method for this phase-domain line modeling application are also presented. For validation, the proposed approach is applied to the modeling of an existing 500-kV double-circuit transmission line. The effectiveness of the numerical techniques for enhancements are shown through the modeling process, and transient waveforms obtained by the proposed approach are compared with those by the rigorous Laplace transform method and also with a Field-Test Result.

Ryujiro Kurosaki - One of the best experts on this subject based on the ideXlab platform.

  • creating spatial temporal database by autonomous mobile surveillance system a study of mobile robot surveillance system using spatial temporal gis part 1
    International Symposium on Safety Security and Rescue Robotics, 2005
    Co-Authors: Junichi Meguro, K Ishikawa, Yoshiharu Amano, Takumi Hashizume, Junichi Takiguchi, Ryujiro Kurosaki, Michinori Hatayama
    Abstract:

    This study describes mobile robot surveillance system using spatial temporal GIS. This paper specially describes the method of collecting spatial temporal data by an autonomous mobile robot system used in a factory premises with some high-rise buildings. This system consists of a wireless LAN network, a base station and an autonomous vehicle. The vehicle is equipped with a GPS/INS navigation system using the network-based real-time kinematic GPS (RTK-GPS) with positioning augmentation services (PAS/spl trade/ Mitsubishi Electric Corporation 2003), an area laser radar (ALR), a slaved camera, and an omni-directional vision (ODV) sensor for surveillance and reconnaissance. The vehicle switches control modes according to the vehicle navigation error. It has three modes, "normal", "road tracking", and "crossing recognition". A Field Test Result shows that the vehicle can track the planned-path within 0.10[m] accuracy at straight paths and within 0.25[m] for curved paths even if RTK fixed solutions are not available. Field experiments and analyses have proved that the proposed navigation method can provide sufficient navigation and guidance accuracy under poor satellite geometry and visibility. Omni-directional image and ALR'S scan data, which is synchronized with both position and GPS time, is memorized as spatial temporal. This spatial temporal data enables the operator to search everywhere in the factory premises efficiently by way of arbitrary position or measured time. The Field Test reveals that the spatial temporal database is confirmed to be useful for remote surveillance.

Junichi Takiguchi - One of the best experts on this subject based on the ideXlab platform.

  • creating spatial temporal database by autonomous mobile surveillance system a study of mobile robot surveillance system using spatial temporal gis part 1
    International Symposium on Safety Security and Rescue Robotics, 2005
    Co-Authors: Junichi Meguro, K Ishikawa, Yoshiharu Amano, Takumi Hashizume, Junichi Takiguchi, Ryujiro Kurosaki, Michinori Hatayama
    Abstract:

    This study describes mobile robot surveillance system using spatial temporal GIS. This paper specially describes the method of collecting spatial temporal data by an autonomous mobile robot system used in a factory premises with some high-rise buildings. This system consists of a wireless LAN network, a base station and an autonomous vehicle. The vehicle is equipped with a GPS/INS navigation system using the network-based real-time kinematic GPS (RTK-GPS) with positioning augmentation services (PAS/spl trade/ Mitsubishi Electric Corporation 2003), an area laser radar (ALR), a slaved camera, and an omni-directional vision (ODV) sensor for surveillance and reconnaissance. The vehicle switches control modes according to the vehicle navigation error. It has three modes, "normal", "road tracking", and "crossing recognition". A Field Test Result shows that the vehicle can track the planned-path within 0.10[m] accuracy at straight paths and within 0.25[m] for curved paths even if RTK fixed solutions are not available. Field experiments and analyses have proved that the proposed navigation method can provide sufficient navigation and guidance accuracy under poor satellite geometry and visibility. Omni-directional image and ALR'S scan data, which is synchronized with both position and GPS time, is memorized as spatial temporal. This spatial temporal data enables the operator to search everywhere in the factory premises efficiently by way of arbitrary position or measured time. The Field Test reveals that the spatial temporal database is confirmed to be useful for remote surveillance.