Nio Technology (anhui) Co., Ltd.

Zhenxiang Jian

Xu Chen

Tong Lin

Hiu Hong Yu

Zhongkui Wang

Waylon Y Chen

Antonio Antonellis Rufo

A calibration system for multi-sensor extrinsic calibration in a vehicle includes one or more calibration targets provided around an external environment within a threshold distance of the vehicle. Each of the one or more calibration targets includes a combination of sensor targets configured to be measured by and used for calibrating a pair of sensors selected from the group consisting of a first sensor, a second sensor or a third sensor. The system also includes a vehicle placement section configured to accommodate the vehicle on the vehicle placement section for detection of the one or more calibration targets.

High precision multi-sensor extrinsic calibration via production line and mobile station

Embodiments of the present disclosure are directed to providing scene perception display requiring reduced processing capabilities. Sensor data indicative of one or more targets from an imaging and ranging subsystem, location data from a positioning subsystem defining a geographical location of the imaging and ranging subsystem and orientation data from an orientation subsystem defining an orientation of the imaging and ranging subsystem are received. Doppler point cloud data is generated based on Doppler information and point cloud data from the sensor data, the location data and the orientation data. The targets are classified as either a static or dynamic target. Afterwards, the Doppler point cloud data is filtered by removing either the dynamic or the static targets from the Doppler point cloud data. The Doppler point cloud data of either the dynamic or the static targets are further processed and the further processed Doppler point cloud data is rendered.

Scene perception using coherent doppler LiDAR

Embodiments of the present disclosure are directed to calibrating an imaging and ranging subsystem. Sensor data indicative of one or more targets from the imaging and ranging subsystem, location data defining a geographical location of the imaging and ranging subsystem, orientation data defining an orientation of the imaging and ranging subsystem and stored translation and rotation values of the imaging and ranging subsystem are received. Estimated Doppler values for the target are provided by the sensor data and theoretical Doppler values for the targets are also calculated. The estimated Doppler values are compared to the theoretical Doppler values to determine if calibration of the imaging and ranging subsystem is required. If calibration is necessary, correction translation and correction rotation values are calculated in order to calculate updated translation and rotation values used to calibrate the imaging and ranging subsystem.

Real-time online calibration of coherent doppler lidar systems on vehicles

Extrinsic calibration of a Light Detection and Ranging (LiDAR) sensor and a camera can comprise constructing a first plurality of reconstructed calibration targets in a three-dimensional space based on physical calibration targets detected from input from the LiDAR and a second plurality of reconstructed calibration targets in the three-dimensional space based on physical calibration targets detected from input from the camera. Reconstructed calibration targets in the first and second plurality of reconstructed calibration targets can be matched and a six-degree of freedom rigid body transformation of the LiDAR and camera can be computed based on the matched reconstructed calibration targets. A projection of the LiDAR to the camera can be computed based on the computed six-degree of freedom rigid body transformation.

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Zhenxiang Jian