RADIO WAVE CONTROL SYSTEM, CONTROL APPARATUS, CONTROL METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM

    公开(公告)号:US20250158649A1

    公开(公告)日:2025-05-15

    申请号:US18838279

    申请日:2022-03-08

    Abstract: The object is to provide a radio wave control system that is capable of suppressing radio wave interference. A radio wave control system according to the present disclosure includes a reflective plate (10) configured to reflect an undesired radio wave that causes interference for a communication apparatus, a control unit (21) that causes a reflected wave of the undesired radio wave to be transmitted in a direction in which the communication apparatus is present, and a communication unit (22) that receives interference information indicating an interference state in the communication apparatus, and the control unit (21) determines a phase of the reflected wave reaching the communication apparatus by using the interference information.

    Detection system, detection method, and program

    公开(公告)号:US11181923B2

    公开(公告)日:2021-11-23

    申请号:US15580810

    申请日:2016-04-28

    Inventor: Junichi Funada

    Abstract: An object of the invention is to provide a new defect detection technique using an autonomously movable apparatus. In order to accomplish the object, the invention provides a detection system (10) including a drive control unit (15) that controls a driving unit (12) causing a base unit (11) to travel in a case where a predetermined detection target is detected on the basis of information collected by a sensor unit (13) installed in the base unit (11), and a second detection unit (16) that detects a predetermined defect on the basis of the information collected by the sensor unit (13).

    RADIO COMMUNICATION TERMINAL, MOBILE AD HOC NETWORK, AND NETWORK PARTICIPATION METHOD
    9.
    发明申请
    RADIO COMMUNICATION TERMINAL, MOBILE AD HOC NETWORK, AND NETWORK PARTICIPATION METHOD 有权
    无线电通信终端,移动通信网络和网络参与方法

    公开(公告)号:US20150043381A1

    公开(公告)日:2015-02-12

    申请号:US14386939

    申请日:2013-03-18

    Inventor: Junichi Funada

    Abstract: [Problem] A mobile ad hoc network (referred to as a “network” below) including the communication terminals (referred to as a “terminal” below) for cognitive radio communication in Patent Literature 1 has a problem that it takes time for the terminal to newly participate in the network.[Solution] A radio communication terminal already participating in a mobile ad hoc network includes a pulse pilot generating unit which converts a pulse signal having a predetermined pattern into a radio signal and outputs the obtained radio signal at an unused frequency, after participating in the mobile ad hoc network. A radio communication terminal to participate in a mobile ad hoc network includes a pulse pilot checking unit which checks whether any pulse signal having a predetermined pattern exists in a radio signal for each predetermined frequency and performs a participation process for the frequency of each radio signal including the pulse signal, the participation process including inquiring whether the radio communication terminal can participate in the mobile ad hoc network.

    Abstract translation: 专利文献1中的包含认知无线电通信的通信终端(以下称为“终端”)的移动自组织网络(以下称为“网络”)存在终端需要时间的问题 新加入网络。 [解决方案]已经参与移动自组织网络的无线电通信终端包括脉冲导频生成单元,其将具有预定模式的脉冲信号转换成无线电信号,并且在参与移动终端之后以未使用的频率输出所获得的无线电信号 ad hoc网络 参与移动自组织网络的无线电通信终端包括:脉冲导频检查单元,用于检查在每个预定频率的无线电信号中是否存在具有预定模式的任何脉冲信号,并对每个无线电信号的频率进行参与处理,包括 脉冲信号,参与过程包括询问无线电通信终端是否可以参与移动自组织网络。

    Confidence determination of 3D point cloud data acquired by LIDAR sensor

    公开(公告)号:US12175699B2

    公开(公告)日:2024-12-24

    申请号:US17628750

    申请日:2020-06-19

    Abstract: Provided is an information processing device capable of determining accuracy of data acquired using an LIDAR sensor.
    An information processing device (10) according to the present disclosure includes: an image-capturing sensor (11); a learning unit (12) configured to learn, as learning data, learning image-capturing data and likelihood of a distance between points included in 3D point cloud data with correct answer in a region substantially the same region included in the learning image-capturing data, and to generate a learned model; and an estimation unit (13) configured to use the learned model to generate estimation data including likelihood of a distance between points included in estimation 3D point cloud data determined based on estimation image-capturing data, from the estimation image-capturing data acquired by the image-capturing sensor (11).

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