Apollo Intelligent Driving Technology (beijing) Co., Ltd.

Baidu Online Network Technology (beijing) Co., Ltd.

Beijing Baidu Netcom Science Technology Co., Ltd

Shirui Li

Xun Zhou

Yuanfan Xie

Liang Wang

Tong Wu

Gaifan Li

The present application discloses a method, an apparatus, a system, and a storage medium for calibrating an exterior parameter of an on-board camera, relating to the field of autonomous driving technologies. A specific implementation scheme of the method in the application is: preprocessing two frames of images of a former frame and a latter frame collected by the on-board camera; performing feature point matching on the two preprocessed frames of images to obtain matched feature points; determining a moving posture of the on-board camera according to the matched feature points; determining a conversion relationship between a vehicle coordinate system and an on-board camera coordinate system according to the moving posture, and obtaining the external parameter of the on-board camera relative to a vehicle body.

Method, apparatus, system, and storage medium for calibrating exterior parameter of on-board camera

Embodiments of the present disclosure provide a method and a device for detecting a precision of an internal parameter of a laser radar, a related apparatus and a medium. The method may include the following steps. Point cloud data collected by the laser radar arranged on an autonomous mobile carrier travelling on a flat road is obtained. A three-dimensional scene reconstruction is performed based on the point cloud data collected to obtain a point cloud model of a three-dimensional scene. The point cloud model of the three-dimensional scene is divided to obtain the road. A thickness of the road is determined based on the point cloud data of the road. It is determined whether the internal parameter of the laser radar is precise based on the thickness of the road.

Method and device for detecting precision of internal parameter of laser radar

Embodiments of the present disclosure disclose a method for calibrating a relative pose, a device, and a medium. The method includes: obtaining first point cloud data of a scene collected by the laser radar in an automatic driving mobile carrier and first pose data collected by the navigation positioning system in the automatic driving mobile carrier; and determining the relative pose between the laser radar and the navigation positioning system based on the first point cloud data, the first pose data, second point cloud data pre-collected by a laser scanner in the scene and second pose data pre-collected by a positioning device in the scene.

Method for calibrating relative pose, device and medium

Embodiments of the present disclosure disclose a method and an apparatus for determining a relative pose, a device, and a medium. The method comprises: obtaining millimeter-wave data for obstacles in a scene collected by a millimeter-wave radar sensor in a vehicle and first data for the obstacles in the scene collected by a first sensor in the vehicle, wherein, at least one millimeter-wave radar signal booster is disposed in the scene as a target obstacle and the obstacles comprise the target obstacle; determining first obstacle data for the target obstacle in a millimeter-wave radar coordinate system and second obstacle data for the target obstacle in a first sensor coordinate system according to the millimeter-wave data and the first data for the obstacles in the scene; and determining the relative pose between the millimeter-wave radar sensor and the first sensor according to the first obstacle data and the second obstacle data.

Method and apparatus for determining relative pose, device and medium

Embodiments of the present disclosure provide a method, an apparatus, a device, and a medium for determining an angle of yaw, relating to a field of automatic driving. The method includes: obtaining, during a vehicle being driving straightly on a straight road, data of each obstacle in an environment located by the vehicle, the data of each obstacle being detected by a millimeter wave radar sensor located in the vehicle, at least one metal obstacle being provided on the straight road; recognizing the metal obstacle based on the data of each obstacle, and obtaining a metal obstacle line by fitting positions of the metal obstacle at different time points; and determining an angle between the metal obstacle line and a direction of a vehicle body as an angle of yaw between the millimeter wave radar sensor and the vehicle body.

Method, apparatus, device, and medium for determining angle of yaw

Embodiments of the present disclosure provide a method and an apparatus for clock synchronization, a device, a storage medium and a vehicle. The method includes: determining a first pose change of an image acquirer with respect to a reference coordinate system at different image acquisition time points; determining a second pose change of a calibration acquirer with respect to the reference coordinate system at different corrected image acquisition time points, in which, the different corrected image acquisition correction time points are determined according to the different image acquisition time points and each predetermined correction time variable; and performing a clock synchronization on the image acquirer and the calibration acquirer according to the first pose change of the image acquirer and the second pose change of the calibration acquirer corresponding to the each correction time variable.

Method, and apparatus for clock synchronization, device, storage medium and vehicle

Embodiments of the present disclosure provide a method and an apparatus for camera calibration processing, a device for vehicle control and a storage medium. In the method according to the embodiments of the present disclosure, at least one pair of images collected by a camera and a vehicle position at a collection time of each of the images are acquired during a process of a vehicle travelling along a straight line, where each pair of images includes images taken by the camera at two different positions, and two images in each pair of images include a common static feature point. A current installation angle of the camera is calculated according to the at least one pair of images and the vehicle position at the collection time of each of the images.

Method and apparatus for camera calibration processing, device for vehicle control and storage medium

Embodiments of the present disclosure provide a sensor calibration method, a sensor calibration device, a computer device, a storage medium, and a vehicle. The method includes: detecting surrounding objects in a travelling process of a vehicle; recognizing a static object from the surrounding objects; performing feature extraction on the static object by a camera and a lidar, respectively; and calibrating an extrinsic parameter of the camera and the lidar based on the extracted feature.

Sensor calibration method and device, computer device, medium, and vehicle

Embodiments of the present disclosure provide a multi-sensor calibration method, a multi-sensor calibration device, a computer device, a medium and a vehicle. The method includes: acquiring data acquired by each of at least three sensors in a same time period in a traveling process of a vehicle; determining a trajectory of each of the at least three sensors according to the data acquired by each of at least three sensors; and performing a joint calibration on the at least three sensors by performing trajectory alignment on the trajectories of the at least three sensors.

Multi-sensor calibration method, multi-sensor calibration device, computer device, medium and vehicle

The present disclosure provides a method for calibrating relative parameters of a collector, an apparatus for calibrating relative parameters of a collector, a device and a storage medium. The technical solution of the present disclosure may determine target position and attitude information of a target image collector in a calibration coordinate system when each target image is collected, determine the first position information of a spatial point in a three-dimensional scene point cloud in the calibration coordinate system and the second position information a projection point of the spatial point in each target image, and determine a relative position and attitude value between the target image collector and the reference collector based on the target position and attitude information corresponding to each target image, the first position information and the second position information.

Growing community of inventors

Beijing, China

Shirui Li