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Generating data using radar observation model based on machine learning

机译:基于机器学习的雷达观测模型生成数据

摘要

A method includes obtaining a first track associated with a first time. A first track associated with a first time is obtained. First predicted state data associated with a second time that is later than the first time, are generated based on the first track. Radar measurement data associated with the second time are obtained from one or more radar sensors. Track data are generated by a machine learning model based on the first predicted state data and the radar measurement data. Second predicted state data associated with the second time are generated based on the first track. A second track associated with the second time is generated based on the track data and the second predicted state data. The second track associated with the second time is provided to an autonomous vehicle control system for autonomous control of a vehicle.
机译:一种方法包括获得与第一次相关联的第一轨道。获得与第一次相关联的第一轨道。基于第一轨道生成与第二时间相关联的预测状态数据。与第二时间相关联的雷达测量数据从一个或多个雷达传感器获得。跟踪数据由基于第一预测状态数据和雷达测量数据的机器学习模型生成。基于第一轨道生成与第二时间相关联的第二预测状态数据。基于跟踪数据和第二预测状态数据生成与第二时间相关联的第二轨道。与第二次相关联的第二轨道被提供给自主车辆控制系统,用于车辆的自主控制。

著录项

  • 公开/公告号US10976410B1

    专利类型

  • 公开/公告日2021-04-13

    原文格式PDF

  • 申请/专利权人 AURORA INNOVATION INC.;

    申请/专利号US202016913518

  • 发明设计人 SHAOGANG WANG;ETHAN EADE;WARREN SMITH;

    申请日2020-06-26

  • 分类号G01S7/40;G06N20;G05D1/02;G06T7/73;G01S13/86;G06T7/207;G01S13;

  • 国家 US

  • 入库时间 2022-08-24 18:11:07

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