CN109255837B - Construction method of efficient B-spline surface for laser radar point cloud data processing - Google Patents
Construction method of efficient B-spline surface for laser radar point cloud data processing Download PDFInfo
- Publication number
- CN109255837B CN109255837B CN201810882398.4A CN201810882398A CN109255837B CN 109255837 B CN109255837 B CN 109255837B CN 201810882398 A CN201810882398 A CN 201810882398A CN 109255837 B CN109255837 B CN 109255837B
- Authority
- CN
- China
- Prior art keywords
- point
- spline
- point cloud
- cloud data
- control points
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/30—Polynomial surface description
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Optimization (AREA)
- Mathematical Physics (AREA)
- Mathematical Analysis (AREA)
- Algebra (AREA)
- Computer Graphics (AREA)
- Geometry (AREA)
- Software Systems (AREA)
- Theoretical Computer Science (AREA)
- Optical Radar Systems And Details Thereof (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention relates to a construction method of a high-efficiency B-spline curved surface for laser radar point cloud data processing, which is characterized by firstly simplifying and correcting collected laser radar point cloud data; secondly, fitting the simplified point cloud data by adopting a plurality of B spline curves; then sampling the B-spline curve according to the required precision to obtain control points with uniformly distributed rotation angles and pitch angles; and finally, generating a uniform rational B-spline curved surface by using the obtained control points, realizing indoor environment three-dimensional modeling, and being used for navigation and obstacle avoidance of intelligent mobile robots and automatic guided vehicles.
Description
Technical Field
The invention relates to a method for three-dimensional modeling of an indoor environment, belongs to the field of mechanical automation, and particularly relates to a method for constructing a high-efficiency B-spline surface for processing laser radar point cloud data.
Background
The laser radar transmits laser beams and receives reflected signals, and position information of a target is obtained by comparing and processing the reflected signals and the transmitted signals. Laser radar is increasingly applied to outdoor unmanned driving and navigation of indoor mobile robots and automatic guided vehicles due to the advantages of high resolution, strong anti-interference capability, small size, light weight and the like. The method is characterized in that point cloud data of an indoor three-dimensional space are obtained by utilizing a laser radar, and then a model of the three-dimensional space is reconstructed, so that the problem to be solved firstly in indoor navigation is solved.
Dense point cloud data are output by the laser radar, a unified mathematical expression is not provided, the shape of an object is not described, meanwhile, the situation of mutation exists in the data, the data cannot be directly applied to navigation, and an indoor three-dimensional model needs to be restored by adopting a corresponding algorithm, so that the data can be used for subsequent positioning and path planning of an indoor mobile robot and an automatic guide trolley and obstacle avoidance.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a method for constructing a high-efficiency B-spline surface for processing laser radar point cloud data, so as to realize modeling of an indoor three-dimensional space.
In order to achieve the purpose, the basic idea of the invention is as follows:
firstly, compacting and correcting dense point cloud data acquired by a laser radar; secondly, fitting the simplified point cloud by using a B spline curve to obtain a B spline curve family of the three-dimensional space; secondly, cutting a B-spline curve by adopting a series of planes which are perpendicular to the ground and penetrate through the rotation axis of the laser radar to obtain a series of intersection points with uniformly distributed rotation angles and pitch angles; and finally, drawing a uniform rational B spline surface by taking the intersection points as control points to realize the modeling of a three-dimensional space.
According to the above concept, the technical scheme provided by the invention is as follows:
a method for constructing an efficient B-spline surface for laser radar point cloud data processing comprises the following specific steps:
1) Designing an efficient method for simplifying and correcting laser radar point cloud data, preprocessing initial dense point cloud data, and simplifying the initial dense point cloud data;
2) Fitting the simplified point cloud data by using a B spline curve to form a continuous and smooth space B spline curve family with a strict mathematical expression;
3) Designing a rapid solving method of the intersection point of a B-spline curve and a plane, constructing an efficient algorithm for dividing the B-spline curve by using the intersection point of a connecting line of two points on the B-spline curve and the plane, and rapidly solving the intersection point by using iterative computation;
4) According to the required precision, cutting the B-spline curve family and solving an intersection point by adopting a plane of the rotary axis of the series of the over-laser radar to obtain control points with uniformly distributed rotary angles and pitch angles on the space curved surface where the original laser radar point cloud is located;
5) And generating a uniform rational B spline surface by using the obtained control points, and realizing modeling of a three-dimensional space.
The efficient laser radar point cloud data compaction and correction method in the step 1) comprises the following specific steps:
1-1) arranging the point clouds acquired by the lasers of each line according to the line pair on the original point cloud data acquired by the multi-line laser radar, calculating the distance between each point and calculating the total chord length;
1-2) compact the dense point cloud collected by each line of laser into a finite number of control points, and the distances between the control points are uniform, and the specific method comprises the following steps: dividing the total chord length by the number of the required control points to obtain the distance between the simplified control points;
1-3) traversing dense point clouds acquired by each line of laser, and summing and averaging the positions of all points at the same interval to obtain a simplified control point.
The method for fitting the simplified point cloud data by adopting the B-spline curve in the step 2) to form a continuous and smooth spatial B-spline curve family with a strict mathematical expression comprises the following specific steps:
2-1) arranging control points obtained by simplifying and correcting each line, and calculating the total chord length;
2-2) calculating the sum of the distances from the initial control point to the current control point, and then dividing the sum by the total chord length to obtain a node vector;
2-3) constructing a B spline curve aiming at each line control point and each node vector, and finally forming a continuous and smooth B spline curve family in the space with a strict mathematical expression.
The fast solving method for the intersection point of the B-spline curve and the plane in the step 3) comprises the following specific steps:
3-1) calculating the distance from each control point of the B spline curve to the plane, and finding out two adjacent control points positioned on different sides of the plane according to the positive and negative of the distance;
3-2) constructing a straight line passing through the two control points, and solving an intersection point of the straight line and the plane by an analytic method;
3-3) respectively calculating the distances from the two control points to the intersection point, and dividing to obtain a ratio;
3-4) dividing a nodal value corresponding to the B spline curve section between the two control points according to the ratio value, and substituting the new nodal value into a B spline curve equation to obtain a new point on the B spline curve;
3-5) solving the distance from the new point to the plane, and if the distance is smaller than a given threshold value, solving a point on the B spline curve close enough to the plane, namely an intersection point; otherwise, according to the positive and negative of the distance value, judging which side of the plane the new point is positioned on, and then replacing the control point on the same side with the new point;
3-6) repeating the steps 3-2), 3-3), 3-4) and 3-5) until the intersection point is obtained.
In the step 4), according to the required precision, a plane of a series of laser radar revolution axes is adopted to cut the B spline curve family and calculate the intersection point, so as to obtain control points with evenly distributed revolution angles and pitch angles on the space curved surface, and the method specifically comprises the following steps:
4-1) setting the size of the rotation angle interval according to the required precision to obtain a series of rotation shafts of the over-laser radar, which are vertical to the ground, and adjacent planes have planes with equal rotation angle intervals;
4-2) setting a rotating shaft of the laser radar as a coordinate axis z, establishing a three-dimensional space coordinate system, and calculating four coefficients of a space plane equation of each plane;
4-3) adopting the fast solving method of the intersection point of the B-spline curve and the plane given in the step 3) to solve the intersection point of the B-spline curve family and the series plane to obtain control points with uniformly distributed rotation angles and pitch angles on the space curved surface where the original laser radar point cloud is located.
The obtained control points are used in the step 5) to generate a uniform rational B-spline surface, so that the modeling of the three-dimensional space is realized, and the method specifically comprises the following steps:
5-1) constructing node vectors in the rotation direction and the pitching direction based on the control points obtained in the step 4);
5-2) calculating various bar basis functions;
5-3) generating a uniform rational B-spline surface, thereby utilizing a reduced number of control points to realize accurate modeling of a three-dimensional space.
Compared with the prior art, the invention has the following advantages:
1. the invention designs an efficient point cloud data simplifying and correcting method, which avoids high calculation workload caused by directly or conventionally processing point cloud data, reduces the influence of mutation position points, realizes the correction of the point cloud mutation data, and can ensure the precision of the point cloud data;
2. the method adopts series B spline curve to fit the point cloud data, and compared with other fitting methods, the method has the advantages of simple structure and high precision, and the fitted curve is smooth and continuous and has a strict mathematical expression;
3. the invention designs a rapid solving method of intersection points of B-spline curves and planes, and solves the problems of complex algorithm and low efficiency in the existing solving of the intersection points of the planes and the B-spline curves;
4. the invention can construct control points corresponding to sparse density and with uniformly distributed rotation angles and pitch angles in space according to required precision and is used for generating a B-spline surface with complete mathematical expression. The uniformly distributed control points are more beneficial to the analysis of the spatial layout and the identification of subsequent spatial objects.
Drawings
Fig. 1 is a general flow chart of the implementation of the present invention.
Fig. 2 is an example of a 16-line lidar spot cloud diagram to be processed by an embodiment of the invention.
Fig. 3 is a control point obtained after a single line is simplified after the processing by the method in step 1).
FIG. 4 shows 16B-spline curves obtained after the treatment by the method described in step 2).
FIG. 5 is a B-spline surface graph with controllable precision obtained after the processing of the methods in steps 3), 4) and 5).
Detailed Description
The technical solution of the present invention is further described below by way of examples with reference to the accompanying drawings.
The laser radar adopted by the embodiment is a currently relatively mature 16-line laser radar which has the most potential application to indoor navigation, the radar comprises 16 laser transceiving components, the measurement distance is more than 150 meters, the measurement precision is within +/-2cm, the number of outgoing points is as high as 320000 points/second, the horizontal angle measurement is 360 degrees, and the vertical angle measurement is 30 degrees.
The output of the laser radar is the horizontal rotation angle and the detected distance of each reflection point, and in order to present the effect of a three-dimensional point cloud picture, the angle and distance information under a polar coordinate can be further converted into the information under a rectangular coordinate system:
wherein r is the actual measurement distance, omega is the pitch angle of the laser,
the horizontal rotation angle of the laser is shown, and X, Y and Z are coordinates of projection of polar coordinates to X, Y and Z axes of a rectangular coordinate system.
As shown in fig. 1, a method for constructing an efficient B-spline surface for laser radar point cloud data processing includes the following steps:
the method comprises the following steps: an efficient method for simplifying and correcting laser radar point cloud data is designed, initial dense point cloud data is preprocessed and simplified, and as shown in fig. 2, the method comprises the following specific steps:
1.1, processing the original point cloud data collected by the laser radar according to the line pair from 1 line to 16 lines in sequence. Arranging the point cloud data of each line and calculating the distance l between each point i And calculating the total chord length
Wherein m is the number of points in the original dense point cloud of each line;
1.2 according to the required precision, the dense point cloud collected by each line of laser is reduced into a limited number of control points M, anddividing the total chord length by the number M of the control points to obtain the spacing between the control points after simplification
1.3, traversing the original dense point cloud of each line, and summing and averaging the positions of each point on the same interval to obtain a simplified control point, as shown in fig. 3. Because summation and averaging are adopted, the influence of mutation position points is reduced, and the correction of point cloud mutation data is realized.
Step two: fitting the simplified point cloud data by adopting a B spline curve to obtain a continuous and smooth space B spline curve family with a strict mathematical expression, and the specific steps are as follows:
2.1 control Point P obtained by simplification and correction for each line j Traversing and calculating the total chord length
Wherein M is the number of control points obtained after the reduction in the step one, l j Is a control point P j Distance to the next control point.
2.2 calculating the sum L of the distances between the control points from the initial control point to the current control point, and dividing by the total chord length L 2 To obtain the node vector U, and then,
2.3 based on the above-mentioned control points P j Calculating the value N of the spline basis function j,p (u), constructing a B-spline curve, as shown in FIG. 4, wherein the concrete formula is as follows:
0≤u≤1。
step three: designing a fast solving method of a B-spline curve and a plane intersection point, constructing an efficient algorithm for dividing the B-spline curve by using the intersection point of a connecting line of two points on the B-spline curve and the plane, and fast solving the intersection point by using iterative computation, wherein the fast solving method comprises the following specific steps of:
3.1 calculating the distance from each control point of the B-spline curve to the plane, and finding two adjacent control points P on different sides of the plane according to the positive and negative of the distance i 、P i+1 Corresponding to the coordinate (x) i ,y i ,z i ) And (x) i+1 ,y i+1 ,z i+1 ) Then the distance l between the two control points is calculated i,i+1 。
3.2 constructing a straight line through the two control points
Solving to obtain the straight line and the plane A (x-x) 0 )+B(y-y 0 )+C(z-z 0 ) Intersection point P of + D =0 j ：
3.3 calculating the control Point P i And point of intersection P j A distance l of i,j And the intersection point P j To a control point P i+1 A distance l of j,i+1 To obtain a ratio
3.4 at the two control points P i 、P i+1 Corresponding node variation range u i ,u i+1 ]Dividing the node variation range according to the proportion t to obtain a new node u j I.e. u j Satisfies the following conditions: (u) i -u j )/(u j -u i+1 )＝t。
3.5 New node u j Substituting B-spline curve equationObtaining a new point P 'on the B-spline curve' j Calculating the distance of the point to the plane:
if d' j If the value is less than the predetermined threshold value, the intersection point P 'of the B-spline curve and the plane is determined' j (ii) a Otherwise by d' j P 'is judged' j On which side of the plane, then with P' j And replacing the control point on the same side, so that the next iterative calculation is performed in a smaller node interval.
3.6 repeating the above steps 3.2 to 3.5 until the intersection point of the B-spline curve and the plane is obtained.
Step four: according to the required precision, a plane of a series of over-laser radar rotation axes is adopted, a B-spline curve family is cut, an intersection point is obtained, so that control points of rotation angles and pitch angles distributed on a space curved surface in an evenly distributed mode are obtained, and the method specifically comprises the following steps:
4.1 construct a series of planes of the over-laser radar pivot axis and ensure the same pivot angle spacing between adjacent planes, the number of planes being determined by the required accuracy.
And 4.2, establishing a rectangular coordinate system by taking the laser radar rotating shaft as a Z axis, and determining the coefficient of each plane equation.
Assuming that m planes are used, the coefficients of the corresponding plane equations are:
and 4.3, solving the intersection points of the m planes and the 16 spatial B-spline curves by using the rapid solving method of the intersection points of the B-spline curves and the planes given in the step three to obtain control points with uniformly distributed rotation angles and pitch angles on the spatial curved surface where the original laser radar point cloud is located.
Step five: constructing a uniform rational B spline surface by using the obtained control points to realize modeling of a three-dimensional space, and specifically comprising the following steps:
5.1 control Point P based on the fourth step i,j And constructing node vectors U and V in the rotation direction and the pitching direction.
5.2 computing the spline basis functions N in these two directions i,p (u) and N j,q (v) The value of (c).
5.3A uniform rational B-spline surface is then constructed:
as shown in fig. 5, thereby enabling accurate modeling of a three-dimensional space with a reduced number of control points.
Claims (6)
1. A method for constructing a high-efficiency B-spline surface for laser radar point cloud data processing is characterized by comprising the following specific steps of:
1) Designing an efficient method for simplifying and correcting the point cloud data of the laser radar, preprocessing the initial dense point cloud data, and simplifying the initial dense point cloud data;
2) Fitting the simplified point cloud data by using a B-spline curve to form a continuous and smooth space B-spline curve family with a strict mathematical expression;
3) Designing a rapid solving method of the intersection point of a B-spline curve and a plane, constructing an efficient algorithm for dividing the B-spline curve by using the intersection point of a connecting line of two points on the B-spline curve and the plane, and rapidly solving the intersection point by using iterative computation;
4) According to the required precision, cutting a B-spline curve family by adopting a plane of a series of over-laser radar rotation axes and solving an intersection point to obtain control points with uniformly distributed rotation angles and pitch angles on a space curved surface where the original laser radar point cloud is located;
5) And generating a uniform rational B spline surface by using the obtained control points, and realizing modeling of a three-dimensional space.
2. The method for constructing the efficient B-spline surface for the lidar point cloud data processing according to claim 1, wherein the efficient lidar point cloud data reduction and correction method in the step 1) comprises the following specific steps:
1-1) arranging the point clouds acquired by the laser of each line according to the line pair on the original point cloud data acquired by the multi-line laser radar, calculating the distance between each point and calculating the total chord length;
1-2) condensing dense point clouds acquired by each line of laser into a limited number of control points, wherein the distances between the control points are uniform, and the specific method comprises the following steps: dividing the total chord length by the number of the required control points to obtain the distance between the simplified control points;
1-3) traversing dense point clouds acquired by each line of laser, and summing and averaging the positions of all points at the same interval to obtain a simplified control point.
3. The method for constructing a high-efficiency B-spline curved surface for laser radar point cloud data processing according to claim 1, wherein the step 2) of fitting the simplified point cloud data by using a B-spline curve to form a continuous and smooth spatial B-spline curve family with a strict mathematical expression comprises the following specific steps:
2-1) arranging control points obtained by simplifying and correcting each line, and calculating the total chord length;
2-2) calculating the sum of the distances from the initial control point to the current control point, and then dividing the sum by the total chord length to obtain a node vector;
2-3) constructing a B spline curve aiming at each line control point and node vector, and finally forming a continuous and smooth B spline curve family in the space with strict mathematical expression.
4. The method for constructing the efficient B-spline surface for the lidar point cloud data processing according to claim 1, wherein the fast solving method of the intersection point of the B-spline curve and the plane in the step 3) comprises the following specific steps:
3-1) calculating the distance from each control point of the B spline curve to the plane, and finding two adjacent control points positioned on different sides of the plane according to the positive and negative of the distance;
3-2) constructing a straight line passing through the two control points, and solving an intersection point of the straight line and the plane by an analytic method;
3-3) respectively calculating the distance between the two control points and the intersection point, and dividing to obtain a ratio;
3-4) dividing a node value corresponding to a B spline curve segment between the two control points according to the ratio value, and substituting the new node value into a B spline curve equation to obtain a new point on the B spline curve;
3-5) solving the distance from the new point to the plane, and if the distance is smaller than a given threshold value, solving a point on the B spline curve close enough to the plane, namely an intersection point; otherwise, according to the positive and negative of the distance value, judging which side of the plane the new point is positioned on, and then replacing the control point on the same side with the new point;
3-6) repeating the steps 3-2), 3-3), 3-4) and 3-5) until the intersection point is obtained.
5. The method for constructing a high-efficiency B-spline curved surface for laser radar point cloud data processing according to claim 1, wherein in the step 4), according to the required precision, a series of planes passing through the rotation axis of the laser radar are adopted to cut a B-spline curve family and calculate an intersection point, so as to obtain control points with uniformly distributed rotation angles and pitch angles on the spatial curved surface, and the specific steps are as follows:
4-1) setting the size of the revolution angle interval according to the required precision to obtain a series of planes which are perpendicular to the ground and have equal revolution angle intervals and are adjacent to each other;
4-2) setting a rotating shaft of the laser radar as a coordinate axis z, establishing a three-dimensional space coordinate system, and calculating four coefficients of a space plane equation of each plane;
4-3) adopting the fast solving method of the intersection point of the B-spline curve and the plane given in the step 3) to solve the intersection point of the B-spline curve family and the series plane to obtain control points with uniformly distributed rotation angles and pitch angles on the space curved surface where the original laser radar point cloud is located.
6. The method for constructing the efficient B-spline surface for the lidar point cloud data processing according to claim 1, wherein the step 5) is to generate a uniform rational B-spline surface by using the obtained control points, so as to realize modeling of a three-dimensional space, and the specific steps are as follows:
5-1) constructing node vectors in the rotation direction and the pitching direction based on the control points obtained in the step 4);
5-2) calculating various basic functions of the sample;
5-3) generating a uniform rational B-spline surface, thereby utilizing a reduced number of control points to realize accurate modeling of a three-dimensional space.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810882398.4A CN109255837B (en) | 2018-08-06 | 2018-08-06 | Construction method of efficient B-spline surface for laser radar point cloud data processing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810882398.4A CN109255837B (en) | 2018-08-06 | 2018-08-06 | Construction method of efficient B-spline surface for laser radar point cloud data processing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109255837A CN109255837A (en) | 2019-01-22 |
| CN109255837B true CN109255837B (en) | 2022-12-23 |
Family
ID=65049147
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810882398.4A Active CN109255837B (en) | 2018-08-06 | 2018-08-06 | Construction method of efficient B-spline surface for laser radar point cloud data processing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109255837B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110375668A (en) * | 2019-07-08 | 2019-10-25 | 西北农林科技大学 | Loess Surface mima type microrelief Surface Reconstruction based on point cloud data |
| CN110908337B (en) * | 2019-12-18 | 2021-04-13 | 湘潭大学 | Method for predicting inverse control point of NURBS |
| CN113686251B (en) * | 2021-08-19 | 2022-12-13 | 山东科技大学 | Method and system for measuring upward movement and downward movement offset of fully mechanized coal mining face equipment |
| CN114217572B (en) * | 2021-12-08 | 2023-07-25 | 中国科学院数学与系统科学研究院 | CAM-based time spline surface generation method |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104392488A (en) * | 2014-12-11 | 2015-03-04 | 福州大学 | Automatic point cloud data rectification method aiming at laser scanner and three-coordinate measuring arm |
-
2018
- 2018-08-06 CN CN201810882398.4A patent/CN109255837B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104392488A (en) * | 2014-12-11 | 2015-03-04 | 福州大学 | Automatic point cloud data rectification method aiming at laser scanner and three-coordinate measuring arm |
Non-Patent Citations (3)
| Title |
|---|
| "三维点云数据拼接与精简技术的研究";徐尚;《硕士电子期刊》;20091115(第11期);第1-70页 * |
| "基于性能的复杂曲面零件面形再设计建模技术";魏伟力;《硕士电子期刊》;20110515(第5期);第1-70页 * |
| "基于逆向参数化的B样条曲面重建算法";曲道奎等;《沈阳建筑大学学报自然（科学版）》;20080331;第24卷(第2期);第340-344页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109255837A (en) | 2019-01-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109255837B (en) | Construction method of efficient B-spline surface for laser radar point cloud data processing | |
| CN107239076B (en) | AGV laser SLAM method based on virtual scanning and distance measurement matching | |
| CN105133840B (en) | A kind of construction method of hyperboloid furred ceiling | |
| CN102044088B (en) | LOD (level of detail) model quick constructing method for scanning mass scattered point cloud by ground laser in single station | |
| CN110645974A (en) | Mobile robot indoor map construction method fusing multiple sensors | |
| CN103106632B (en) | A kind of fusion method of the different accuracy three dimensional point cloud based on average drifting | |
| CN110598239B (en) | Application method based on track area point cloud big data | |
| CN102607459A (en) | Splicing method and splicing device of Lidar measurement data | |
| CN114061486A (en) | Automatic measuring device and method for large-scale skin curved surface of airplane | |
| CN115952691B (en) | Optimal station distribution method and device for multi-station passive time difference cross joint positioning system | |
| Cai et al. | Analyzing infrastructure lidar placement with realistic lidar simulation library | |
| CN106408653A (en) | Real-time robust cluster adjustment method for large-scale three-dimensional reconstruction | |
| CN114332291A (en) | Oblique photography model building outer contour rule extraction method | |
| CN115201849A (en) | Indoor map building method based on vector map | |
| CN111722202A (en) | Reflector position fitting method and system based on echo intensity | |
| CN207456381U (en) | Improve the device of laser tracker measurement accuracy | |
| CN113239580A (en) | Laser radar measuring station position planning method for large structural member profile detection | |
| CN113406658A (en) | Mobile robot positioning method based on point-line characteristic scanning matching | |
| CN116338716B (en) | Multi-target association method of air-ground unmanned system based on azimuth topological structure | |
| Liu et al. | Unmanned aerial vehicle positioning algorithm based on the secant slope characteristics of transmission lines | |
| CN116500648A (en) | Wind profile inversion method for foundation laser radar target area | |
| CN112734677B (en) | Airborne LiDAR point cloud cavity interpolation method and system | |
| CN115453549A (en) | Method for extracting environment right-angle point coordinate angle based on two-dimensional laser radar | |
| CN115713607A (en) | Method for improving modeling quality based on laser radar and oblique photography | |
| CN114912171A (en) | Building shielding-based sunlight radiation calculation method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |