公开(公告)号：US10322819B2

公开(公告)日：2019-06-18

申请号：US15657145

申请日：2017-07-22

Applicant: PARROT DRONES

Inventor： Laure Chevalley ,  Edouard Leurent

IPC: B64D47/08 ,  B64C39/02 ,  G01S17/02 ,  H04N5/225 ,  H04N5/232 ,  G05D1/00 ,  H04N17/00

Abstract: The displacements of the drone are defined by piloting commands to take moving images of a target carrying the ground station. The system comprises means for adjusting the sight angle of the camera during the displacements of the drone and of the target, so that the images are centerd to the target, and means for generating flying instructions so that the distance between drone and target fulfills determined rules, these means being based on a determination of the GPS geographical position of the target with respect to the GPS geographical position of the drone, and of the angular position of the target with respect to a main axis of the drone. These means are also based on the analysis of a non-geographical signal produced by the target and received by the drone. The system allows freeing from the uncertainty of the GPS systems equipping this type of device.

公开(公告)号：US09387927B2

公开(公告)日：2016-07-12

申请号：US14323851

申请日：2014-07-03

Applicant: PARROT

Inventor： Michael Rischmuller ,  Laure Chevalley ,  Francois Callou ,  Etienne Caldichoury

IPC: B64C39/02 ,  G05D1/10

CPC classification number: B64C39/024 ,  B64C2201/024 ,  B64C2201/141 ,  G05D1/102

Abstract: The drone comprises: a vertical-view camera (132) pointing downward to pick up images of a scene of the ground overflown by the drone; gyrometer, magnetometer and accelerometer sensors (176); and an altimeter (174). Navigation means determine position coordinates (X, Y, Z) of the drone in an absolute coordinate system linked to the ground. These means are autonomous, operating without reception of external signals. They include image analysis means, adapted to derive a position signal from an analysis of known predetermined patterns (210), present in the scene picked up by the camera, and they implement a predictive-filter estimator (172) incorporating a representation of a dynamic model of the drone, with as an input the position signal, a horizontal speed signal, linear and rotational acceleration signals, and an altitude signal.

Abstract translation: 无人机包括：向下指示的垂直摄像机（132），以拾取由无人机所溢出的地面的场景的图像; 陀螺仪，磁力计和加速度传感器（176）; 和高度计（174）。 导航意味着确定无人机在与地面相连的绝对坐标系中的位置坐标（X，Y，Z）。 这些手段是自主的，在没有接收到外部信号的情况下运行。 它们包括图像分析装置，适于从存在于摄像机拾取的场景中的已知预定模式（210）的分析中导出位置信号，并且它们实现了包含动态表示的预测滤波器估计器（172） 无人机的型号，作为输入的位置信号，水平速度信号，线性和旋转加速度信号以及高度信号。

公开(公告)号：US20150161456A1

公开(公告)日：2015-06-11

申请号：US14561063

申请日：2014-12-04

Applicant: PARROT

Inventor： Laure Chevalley

IPC: G06K9/00 ,  G06K9/46 ,  H04N7/18

CPC classification number: G06K9/00798 ,  G01B11/00 ,  G06K9/4604 ,  G06T7/80 ,  G06T2207/30256 ,  H04N5/23267 ,  H04N7/18 ,  H04N17/002

Abstract: The method consists in taking, when the vehicle is running, images of the road markings delimiting the circulation lanes of the road, and in fully estimating, through an iterative process, the orientation of the camera with respect to the vehicle, based on the position of two lanes located side-by-side on the image. The calibration essentially comprises: correcting the position of the lane edges in the image (10, 12); estimating the residual pitch and yaw (16); updating the rotation matrix (18); estimating the residual roll (20); updating the rotation matrix (24). These steps are iterated until the corrective angles estimated by each module are negligible (22).

Abstract translation: 该方法包括：当车辆行驶时，道路标记的图像限定道路的循环道路，并且通过迭代过程，基于位置来完全估计摄像机相对于车辆的取向 位于图像并排的两条车道。 校准基本上包括：校正图像（10,12）中的车道边缘的位置; 估计残余俯仰和偏航（16）; 更新旋转矩阵（18）; 估计剩余卷（20）; 更新旋转矩阵（24）。 迭代这些步骤，直到由每个模块估计的校正角度可以忽略不计（22）。

公开(公告)号：US09576207B2

公开(公告)日：2017-02-21

申请号：US14561063

申请日：2014-12-04

Applicant: PARROT

Inventor： Laure Chevalley

IPC: H04N7/18 ,  G06K9/00 ,  G06K9/46 ,  G01B11/00 ,  H04N17/00 ,  H04N5/232 ,  G06T7/00

CPC classification number: G06K9/00798 ,  G01B11/00 ,  G06K9/4604 ,  G06T7/80 ,  G06T2207/30256 ,  H04N5/23267 ,  H04N7/18 ,  H04N17/002

Abstract: The method consists in taking, when the vehicle is running, images of the road markings delimiting the circulation lanes of the road, and in fully estimating, through an iterative process, the orientation of the camera with respect to the vehicle, based on the position of two lanes located side-by-side on the image. The calibration essentially comprises: correcting the position of the lane edges in the image (10, 12); estimating the residual pitch and yaw (16); updating the rotation matrix (18); estimating the residual roll (20); updating the rotation matrix (24). These steps are iterated until the corrective angles estimated by each module are negligible (22).

Abstract translation: 该方法包括：当车辆行驶时，道路标记的图像限定道路的循环道路，并且通过迭代过程，基于位置来完全估计摄像机相对于车辆的取向 位于图像并排的两条车道。 校准基本上包括：校正图像（10,12）中的车道边缘的位置; 估计残余俯仰和偏航（16）; 更新旋转矩阵（18）; 估计剩余卷（20）; 更新旋转矩阵（24）。 迭代这些步骤，直到由每个模块估计的校正角度可以忽略不计（22）。