Parameter calibration method and apparatus of multi-line laser radar, device and readable medium

US11714174B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-11714174-B2
Application numberUS-201816117953-A
CountryUS
Kind codeB2
Filing dateAug 30, 2018
Priority dateSep 17, 2017
Publication dateAug 1, 2023
Grant dateAug 1, 2023

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Abstract

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The method comprises: creating a 3D scenario model of a calibration scenario, based on data of the calibration scenario collected by an already-calibrated 3D scanner; obtaining point cloud data collected by a to-be-calibrated multi-line laser radar at a plurality of position points in the calibration scenario respectively; aligning the point cloud data collected by the multi-line laser radar at the respective point points and point cloud data in the 3D scenario model into the same coordinate system on a principle that the respective position points are aligned with corresponding position points in the 3D scenario model; building a target function between data of points collected by the multi-line laser radar and data of matching points nearest to the points in the 3D scenario model, under the same coordinate system; calibrating the parameters of the multi-line laser radar according to the target function.

First claim

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What is claimed is: 1. A method of calibration of internal and/or external parameters of a multi-line laser radar in view of different calibration scenario, the external parameters being related to both the multi-line laser radar and a mounting machine mounted with the multi-line laser radar, wherein the method comprises: creating a 3D scenario model of a calibration scenario, based on data of the calibration scenario collected by an already-calibrated 3D scanner; obtaining point cloud data collected by a to-be-calibrated multi-line laser radar at a plurality of position points in the calibration scenario respectively, wherein a precision of the already-calibrated 3D scanner is larger than the precision of the to-be-calibrated multi-line laser radar; aligning absolutely the point cloud data collected by the multi-line laser radar at the respective point points and point cloud data in the 3D scenario model into the same coordinate system on a principle that the respective position points are aligned with corresponding position points in the 3D scenario model; building an objective function between data of points collected by the multi-line laser radar and data of matching points which are nearest to the respective points collected by the multi-line laser radar in the 3D scenario model under the same coordinate system, wherein the objective function defines a point-to-point correspondence between a point collected by the multi-line laser radar and a corresponding matching point in the 3D scenario model; calibrating the parameters of the multi-line laser radar according to the objective function. 2. The method according to claim 1 , wherein the aligning the point cloud data collected by the multi-line laser radar at the respective point points and point cloud data in the 3D scenario model into the same coordinate system on a principle that the respective position points are aligned with corresponding position points in the 3D scenario model specifically comprises: aligning respective position points to corresponding positions in the 3D scenario model; obtaining a conversion parameter at respective position points after the alignment from a coordinate system of a mounting machine mounted with the multi-line laser radar to a coordinate system of the 3D scenario model; according to the conversion parameter at respective position points from the coordinate system of the mounting machine mounted with the multi-line laser radar to the coordinate system of the 3D scenario model, and an internal parameter and an external parameter of the multi-line laser radar, converting the point cloud data collected by the multi-line laser radar at respective position points to corresponding coordinates in the 3D scenario model, so that the point cloud data collected at respective position points and the 3D scenario model belong to the same coordinate system. 3. The method according to claim 2 , wherein the step of, according to the conversion parameter at respective position points from the coordinate system of the mounting machine mounted with the multi-line laser radar to the coordinate system of the 3D scenario model, and an internal parameter and an external parameter of the multi-line laser radar, converting the point cloud data collected by the multi-line laser radar at respective position points to corresponding coordinates in the 3D scenario model specifically comprises: taking r j as raw data at any point j in the point cloud collected by the multi-line laser radar at the i th position point, and calculating coordinates of the point j in the coordinate system of the mounting machine by using the equation p b j =T b,s L(r j ; I), according to the internal parameter I of the multi-line laser radar, the conversion function for converting the raw data into the multi-line laser radar coordinate system, and the conversion parameter from the coordinate system of the multi-line laser radar to the coordinate system of the mounting machine mounted with the multi-line laser radar, wherein r j ∈R i , R i is a set of raw data collected by the multi-line laser radar at the i th position; L(r j ; I) is the conversion function from the raw data to the multi-line laser radar coordinate system; T b,s is a set of conversion parameters from the coordinate system of the multi-line laser radar to the coordinate system of the mounting machine mounted with the multi-line laser radar, T b,s ={T b,s i }, wherein T b,s i is the conversion parameter from the coordinate system of the i th multi-line laser radar to the coordinate system of the mounting machine mounted with the multi-line laser radar; p b j is the coordinates of the point j in the coordinate system of the mounting machine; calculating coordinates of the point j in the coordinate system of the 3D scenario model by using equation p m j =T m,b i p b j according to a conversion parameter T m,b i at the i th position point from the coordinate system of the mounting machine to the coordinate system of the 3D scenario model, and coordinates p b j of the point j in the coordinate system of the mounting machine; wherein p m j is coordinates of the point j in the coordinate system of the 3D scenario model. 4. The method according to claim 3 , wherein the building an objective function between data of points collected by the multi-line laser radar and data of matching points nearest to the points in the 3D scenario model, under the same coordinate system specifically comprises: setting a weight w(p)=f(c(p)) and a normal direction n(p) of points p in the 3D scenario model; wherein c(p) is a scalar function, which measures a curve degree of a model surface adjacent to point p; function f( ) is a monotone function to map c(p) to between 0 and 1; a value of w(p) is closer to 1 in a flatter region of the surface adjacent to the point p measured by c(p), otherwise the value of w(p) is closer to 0 in a more curved region of the surface adjacent to the point p measured by c(p); n(p) is the normal direction of the point p; obtaining coordinates m j of a matching point nearest to coordinates p m j of the point j in the 3D scenario model collected at the i th position point, and obtaining a weight w(m j ) and a normal direction n(m j ) of the matching point m j ; building an objective function using the following formula according to the coordinates p m j of the point j in the coordinate system of the 3D scenario model, the coordinates m j of the matching point, and the weight w(m j ) and the normal direction n(m j ) of the matching point m j : E ( T m,b ,T b,s ,I )=Σ i Σ j ρ( w ( m j ) n T ( m j )( m j −p m j )), m j ∈M where E(T m,b , T b,s , I) is an objective function; ρ(·) is a loss function; n T (m j ) is transposition of the normal direction n(m j ) of the matching point m j ; M is a set of points in the 3D scenario model; T m,b ={T m,b i } and is a set of conversion parameters T m,b i of all i position points from the coordinate system of the mounting machine to the coordinate system of the 3D scenario model. 5. The method according to claim 4 , wherein the calibrating the parameters of the multi-line laser radar according to the objective function specifically comprises: optimizing a conversion parameter T b,s in the objective function from the coordinate system of the multi-line laser radar to the coordinate system of the mounting machine mounted with the multi-line laser radar, to make the objective function converge; jointly optimizing the T b,s and internal parameter I in the objective function to enable the objective function to take a minimal value; obtaining a value of the corresponding T b,s and internal parameter I when the objective function takes the minimal value, respectively as the external parameter and int

Assignees

Inventors

Classifications

  • G01S7/497Primary

    Means for monitoring or calibrating · CPC title

  • Simultaneous measurement of distance and other co-ordinates (indirect measurement G01S17/46) · CPC title

  • G01S7/40Primary

    Means for monitoring or calibrating · CPC title

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What does patent US11714174B2 cover?
The method comprises: creating a 3D scenario model of a calibration scenario, based on data of the calibration scenario collected by an already-calibrated 3D scanner; obtaining point cloud data collected by a to-be-calibrated multi-line laser radar at a plurality of position points in the calibration scenario respectively; aligning the point cloud data collected by the multi-line laser radar at…
Who is the assignee on this patent?
Apollo Intelligent Driving Tech Beijing Co Ltd
What technology area does this patent fall under?
Primary CPC classification G01S7/497. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Aug 01 2023 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 2 related publications on this page (citations in our corpus or others sharing the same primary CPC).