External parameter calibration method and device of vehicle sensor and computer readable storage medium

Abstract

The invention discloses an external parameter calibration method and device for a vehicle sensor and a computer readable storage medium, and the method comprises the steps: obtaining the first road identification data of a corresponding high-precision map according to the current position of a vehicle; obtaining first sensor data collected by a first sensor of the vehicle and processing the first sensor data to obtain second road sign data; second sensor data collected by a second sensor of the vehicle are obtained and processed, and third road sign data are obtained; constructing a nonlinear optimization model according to the first road identification data, the second road identification data and the third road identification data; and according to the nonlinear optimization model, determining the external parameter of the calibrated first sensor and the external parameter of the calibrated second sensor. According to the method, the external parameters of the sensors can be calibrated in real time according to the road identification data provided by the high-precision map and the road identification data of different sensors, and the robustness and precision of the external parameters of the sensors are improved through mutual constraint among the road identification data of different sources.

Description

technical field [0001] The present application relates to the technical field of automatic driving, and in particular, to an external parameter calibration method, device and computer-readable storage medium for vehicle sensors. Background technique [0002] In recent years, with the development of Advanced Driver Assistance System (ADAS) and Automated Driving (AD) technologies, research based on multi-sensor perception such as cameras and lidars has been widely used. [0003] Among them, the calibration accuracy of the sensor relative to the external parameter of the center of the vehicle body affects the measurement of the sensor, which in turn affects the practical application. For example, the road marking information such as lane lines, stop lines, arrows, etc. detected from the road images collected by the camera is registered with the high-precision data in the high-precision map, and the position of the vehicle during driving can be judged; lidar can perceive The th...

AI Technical Summary

Problems solved by technology

Since all detection results need to be converted to the vehicle body coordinate system through its external parameters for application, the quality of the sensor external parameters will affect the application of subsequent modules

[0004] Many existing sensor calibration methods usually use off-line calibration. Due to the inevitable vibration of the vehicle during driving, the position and angle of the sensor installation are inconsistent with the initial position, resulting in errors in the initially calibrated external parameters.

In this regard, some real-time calibration methods for sensors are provided in the prior art. However, these calibration methods usually only use the data of one sensor for calibration, resulting in low robustness and low accuracy of the calibration results.

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