A laser radar calibration device and calibration method based on space-time transformation

Abstract

The invention provides a laser radar calibration device based on space-time transformation, which is used for calibration of an all-solid-state three-dimensional planar array laser radar. The laser radar calibration device comprises a to-be-calibrated three-dimensional planar array laser radar installation portion, a cooperative calibration target installation part, an ambient light shielding boxbody, a directional reception active light source conduit and a time delay module, wherein the to-be-calibrated three-dimensional planar array laser radar installation portion, the cooperative calibration target installation part, the ambient light shielding box body, the directional reception active light source conduit and the time delay module are fixed by means of fixing screws and positioningholes, so as to form an integrated three-dimensional planar array laser radar calibration device. The invention further discloses a corresponding calibration method. the simple, convenient and rapidcalibration device and calibration method can perform rapid and precise calibration on the three-dimensional planar array laser radar, is high in calibration precision and wide in calibration distancerange, and does not require a special calibration environment and a special cooperative calibration target.

Description

Technical field [0001] The invention relates to a laser radar calibration technology, and particularly relates to a three-dimensional area array laser radar calibration device and a calibration method based on time-space transformation. Background technique [0002] All-solid-state 3D area array lidar is a new type of 3D ranging imaging equipment. As the "eye" of intelligent equipment, it has been used more and more widely in the fields of industrial production, transportation and logistics, and security monitoring. Applications such as sorting, robotic grabbing, AGV unmanned vehicle obstacle avoidance, auto unmanned driving, three-dimensional face recognition and behavior prediction provide real-time high-resolution distance information. [0003] Based on ToF (Time of Flight) all solid-state three-dimensional area array lidar, the distance of the target is obtained by detecting the flight (round trip) time of the light pulse by continuously sending light pulses to the target, and ...

AI Technical Summary

Problems solved by technology

[0006] 1) It is impossible to eliminate the individual differences of each pixel of the ToF sensor

The traditional calibration method, through the overall calibration method, does not consider the individual differences of the pixels, and generates the same error correction value after calibration of all the pixels, which cannot eliminate the individual measurement errors of different pixels

[0007] 2) Calibration accuracy is heavily dependent on the cooperation target used for calibration

[0008] 3) Strict requirements on the calibration environment

When calibrating the 3D area-array LiDAR ToF sensor in the traditional method, it is necessary to install a calibration cooperation target parallel to the image plane at different calibration distances and able to completely cover the image plane at this line-of-sight distance, without occlusion within the field of view. The required site and cooperative calibration target installation conditions are very harsh

At the same time, in order to obtain accurate calibration results, it is required to filter the ambient light in the same band during calibration. In practical applications, it is difficult to meet this calibration condition.

[0009] 4) The calibration operation is complicated, the process is cumbersome, and the efficiency is low

From the description of the above three points, it can be found that the calibration operation of the traditional calibration method is complicated and cumbersome, the calibration efficiency is low, and it is difficult to meet the requirements of productization

[0010] 5) Poor calibration accuracy

The calibration of the traditional calibration method is affected by uncertain factors such as individual differences in pixels, cooperative calibration goals, calibration environment, calibration process and steps, etc. The calibration results are highly random and inaccurate

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