CN111127640A - ROS-based offline planning method for automatic cleaning track of airplane - Google Patents
ROS-based offline planning method for automatic cleaning track of airplane Download PDFInfo
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Abstract
The invention is suitable for the technical field of off-line planning, and provides an automatic cleaning track off-line planning method of an airplane based on ROS, which comprises the following steps: s1, scanning the airplane model through a visual sensor, and establishing an airplane three-dimensional model STL through point cloud; s2, dividing the aircraft three-dimensional model STL to form a plurality of areas, and defining the cleaning positions of the areas; and S3, planning the cleaning track of each area, and cleaning the area based on the cleaning track. The automatic planning of the cleaning track of the airplane to be cleaned is carried out in different areas, so that the automatic cleaning effect of the airplane is ensured while the automatic cleaning of the airplane is realized.
Description
Technical Field
The invention belongs to the technical field of off-line planning, and provides an automatic airplane cleaning track off-line planning method based on ROS.
Background
Aircraft often come into contact with various contaminants during everyday use, which can not only affect the appearance of the aircraft, but also cause damage to the aircraft surface and affect aircraft safety. Aircraft surface cleaning has become an important component in aircraft maintenance procedures. The surface cleaning of the airplane not only enables the surface of the airplane to be clean and attractive, but also can effectively relieve and reduce corrosion. The normal movement of the aircraft is ensured, and therefore, the development of the aviation industry has higher and higher requirements on the cleanliness of the aircraft. As the number of aircraft increases, cleaning of the aircraft surfaces becomes a major problem. Most of the prior art is cleaned manually, and manual cleaning cannot contact the surface of an airplane in a short distance, so that some dead corners and key parts cannot be cleaned.
Disclosure of Invention
The embodiment of the invention provides an offline planning method for an automatic cleaning track of an airplane based on ROS, which is used for automatically generating a cleaning path and automatically cleaning based on the cleaning path.
The invention is realized in such a way that an offline planning method for an automatic cleaning track of an airplane based on ROS comprises the following steps:
s1, scanning the airplane model through a visual sensor, and establishing an airplane three-dimensional model STL through point cloud;
s2, dividing the aircraft three-dimensional model STL to form a plurality of areas, and defining the cleaning positions of the areas;
and S3, planning the cleaning track of each area, and cleaning the area based on the cleaning track.
Further, the method for dividing the cleaning tracks of the areas specifically comprises the following steps:
s31, dividing each area into a plurality of sub-areas;
s32, guiding a subregion of the region into RVIZ in an ROS system, dividing the subregion into a plurality of triangular plates, and acquiring normal vectors of the triangular plates and vertex coordinates of three vertexes;
s33, constructing a minimum bounding box of the corresponding sub-region based on the triangular plate of the sub-region;
s34, calculating vertex coordinates of eight vertexes of the minimum bounding box, and forming a projection plane by one vertex of the minimum bounding box and one axial vector;
s35, calculating the intersection points of all the triangular plates in the sub-area and the projection plane, wherein the intersection points are the target cleaning points of the sub-area;
and S36, acquiring target counting of all sub-areas in the area based on the steps S31 to S35, defining the target counting as target cleaning points of the area, and forming a cleaning track of the area based on the target cleaning points of the area.
Further, the construction method of the minimum bounding box of the sub-region specifically comprises the following steps:
s331, determining the three-axis directions of the minimum bounding box, namely the directions of an X axis, a Y axis and a Z axis based on the covariance matrix of the triangular plate in the sub-region;
s332, calculating the center coordinate of the minimum bounding box, and constructing the minimum bounding box based on the center coordinate of the minimum bounding box and the three-axis direction.
Further, the method for determining three axes of the minimum bounding box specifically includes:
s3311, acquiring a covariance matrix of a triangular plate in a subregion, and calculating three eigenvectors and corresponding eigenvalues of the covariance matrix;
s3312, taking the direction of the characteristic vector R1 as the X-axis direction of the minimum bounding box, taking R1 as the characteristic vector corresponding to the maximum characteristic value, taking the direction of the characteristic vector R2 as the Z-axis direction of the minimum bounding box, taking R2 as the characteristic vector corresponding to the minimum characteristic value, taking the direction of the characteristic vector R3 as the Y-axis direction of the minimum bounding box, and taking R3 as the characteristic vector corresponding to the middle characteristic value.
Further, the method for calculating the center coordinate of the minimum bounding box specifically includes:
s3321, constructing a matrix E based on three eigenvectors of covariance, wherein the matrix E is expressed as follows:
wherein, [ R1, R2, R3]The feature vector corresponding to the maximum feature value, the feature vector corresponding to the intermediate feature value and the minimum feature value pairCorresponding feature vector, n represents the number of vertices in the sub-region, (X)i,Yi,Zi) Is the coordinate of the vertex of the triangle,
the mean value of the coordinates of the vertexes of the triangles in the sub-area is obtained;
s3322, calculating the coordinate (X) of the center point of the minimum bounding box based on the matrix Eo,Yo,Zo)；
Wherein (X)o,Yo,Zo) In order to coordinate the center point of the minimum bounding box, e.col (0). maxCoeff () represents the maximum value of the 1 st column in the matrix E, e.col (0). minCoeff () represents the minimum value of the 1 st column in the matrix E, e.col (1). maxCoeff () represents the maximum value of the 2 nd column in the matrix E, e.col (1). minCoeff () represents the minimum value of the 2 nd column in the matrix E, e.col (2). maxCoeff () represents the maximum value of the 3 rd column in the matrix E, and e.col (2). minCoeff () represents the minimum value of the 3 rd column in the matrix E.
Further, the method for acquiring the target inventory in the sub-area specifically comprises the following steps:
s351, detecting whether three vertexes of all the triangular plates in the sub-area are positioned on the same side of the projection plane;
and S352, if the detection result is positive, the triangular plate and the projection plane have no intersection, if the detection result is negative, the triangular plate and the projection plane have an intersection, and the intersection of the edge of the different side point of the triangular plate and the projection plane is calculated, wherein the edge of the different side point refers to a connecting line of vertexes on two sides of the projection plane.
Further, the method for determining whether the three vertexes of the triangular plate are located on the same side of the projection plane is specifically as follows:
s3511, projecting the triangular plate onto the projection plane to obtain three projection points of the triangular plate;
s3512, vectors from the three projection points to the corresponding vertexes are obtained, if the directions of the three vectors are consistent, the three vertexes of the triangular plate are located on the same side of the projection plane, and otherwise, the three vertexes of the triangular plate are not located on the same side.
The ROS-based offline planning method for the automatic cleaning track of the airplane has the following beneficial effects: the automatic planning of the cleaning track of the airplane to be cleaned is carried out in different areas, so that the automatic cleaning of the airplane is realized, and the cleaning effect of the airplane is ensured.
Drawings
Fig. 1 is a flowchart of an offline planning method for an aircraft automatic cleaning trajectory based on an ROS according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Fig. 1 is a flowchart of an offline planning method for an aircraft automatic cleaning trajectory based on an ROS according to an embodiment of the present invention, where the method specifically includes the following steps:
s1, scanning the airplane model through a visual sensor, and establishing an airplane three-dimensional model STL through point cloud;
s2, dividing the aircraft three-dimensional model STL to form a plurality of areas, and defining the cleaning positions of the areas;
the first-level division is to divide the aircraft three-dimensional model STL into four areas, namely an area A, an area B, an area C and an area D, and determine four cleaning position points of the four areas;
s3, planning a cleaning track of each area, and cleaning the area based on the cleaning track, wherein the method for dividing the cleaning track of each area specifically comprises the following steps:
s31, dividing each area into a plurality of sub-areas;
the four regions are divided into two levels, each region is divided into four subregions, namely the region A is divided into a1 subregion, a2 subregion, a3 subregion and a4 subregion, the region B is divided into B1 subregion, B2 subregion, B3 subregion and B4 subregion, the region C is divided into C1 subregion, C2 subregion, C3 subregion and C4 subregion, the region D is divided into D1 subregion, D2 subregion, D3 subregion and D4 subregion,
s32, guiding a subregion of the region into RVIZ in an ROS system, dividing the subregion into a plurality of triangular plates, and acquiring normal vectors of the triangular plates and vertex coordinates of three vertexes;
s33, constructing a minimum bounding box of the corresponding sub-region based on the triangular plate of the sub-region;
in the embodiment of the present invention, the method for constructing the minimum bounding box of the sub-region specifically includes the following steps:
s331, determining three-axis directions of the minimum bounding box, namely directions of an X axis, a Y axis and a Z axis, based on a covariance matrix of triangular plates in the sub-region, wherein the three-axis determining method specifically comprises the following steps:
s3311, acquiring a covariance matrix of a triangular plate in a subregion, and calculating three eigenvectors and corresponding eigenvalues of the covariance matrix;
if n triangle vertices exist in the current sub-region, the covariance matrix is expressed as follows:
S3312, taking the direction of the characteristic vector R1 as the X-axis direction of the minimum bounding box, taking R1 as the characteristic vector corresponding to the maximum characteristic value, taking the direction of the characteristic vector R2 as the Z-axis direction of the minimum bounding box, taking R2 as the characteristic vector corresponding to the minimum characteristic value, taking the direction of the characteristic vector R3 as the Y-axis direction of the minimum bounding box, and taking R3 as the characteristic vector corresponding to the middle characteristic value.
S332, calculating the center coordinate of the minimum bounding box, and constructing the minimum bounding box based on the center coordinate of the minimum bounding box and the three-axis direction, wherein the calculation method of the center coordinate of the minimum bounding box comprises the following specific steps:
s3321, constructing a matrix E based on three eigenvectors of covariance, wherein the matrix E is expressed as follows:
wherein [ R1, R2, R3] are the eigenvector corresponding to the maximum eigenvalue, the eigenvector corresponding to the intermediate eigenvalue and the eigenvector corresponding to the minimum eigenvalue, respectively;
s3322, calculating the coordinate (X) of the center point of the minimum bounding box based on the matrix Eo,Yo,Zo)；
Wherein (X)o,Yo,Zo) In order to coordinate the center point of the minimum bounding box, e.col (0). maxCoeff () represents the maximum value of the 1 st column in the matrix E, e.col (0). minCoeff () represents the minimum value of the 1 st column in the matrix E, e.col (1). maxCoeff () represents the maximum value of the 2 nd column in the matrix E, e.col (1). minCoeff () represents the minimum value of the 2 nd column in the matrix E, e.col (2). maxCoeff () represents the maximum value of the 3 rd column in the matrix E, and e.col (2). minCoeff () represents the minimum value of the 3 rd column in the matrix E.
S34, calculating vertex coordinates of eight vertexes of the minimum bounding box, and forming a projection plane by one vertex of the minimum bounding box and one axial vector;
s35, calculating the intersection points of all the triangular plates in the sub-area and the projection plane, wherein the intersection points are the target cleaning points of the sub-area, and the method for acquiring the target cleaning points in the sub-area is as follows:
s351, detecting whether three vertexes of all the triangular plates in the sub-area are positioned on the same side of the projection plane;
and S352, if the detection result is positive, the triangular plate and the projection plane have no intersection, if the detection result is negative, the triangular plate and the projection plane have an intersection, and the intersection of the edge of the different side point of the triangular plate and the projection plane is calculated, wherein the edge of the different side point refers to a connecting line of vertexes on two sides of the projection plane.
In the embodiment of the present invention, the method for determining whether the three vertices are located on the same side of the projection plane specifically includes:
s3511, projecting the triangular plate onto the projection plane to obtain three projection points of the triangular plate;
s3512, vectors from the three projection points to the corresponding vertexes are obtained, if the directions of the three vectors are consistent, the three vertexes of the triangular plate are located on the same side of the projection plane, and otherwise, the three vertexes of the triangular plate are not located on the same side.
And S36, acquiring target counting of all sub-areas in the area based on the steps S31 to S35, defining the target counting as target cleaning points of the area, and forming a cleaning track of the area based on the target cleaning points of the area.
And performing secondary division on each area, dividing each area into four sub-areas, acquiring a target cleaning point of each sub-area, and forming a cleaning track of the area on the basis of all the target cleaning points of the area.
In the embodiment of the invention, in order to ensure the stability of the tail end of the robot, firstly, Cartesian space linear planning is adopted, in order to ensure the effect of the planning result, a certain number of target points are selected each time, the planning is carried out for five times, the selection success rate is the highest one time, and for unreachable target points, deletion operation is adopted, and for deleted target points, the operation is simplified.
The ROS-based offline planning method for the automatic cleaning track of the airplane has the following beneficial effects: the automatic planning of the cleaning track of the airplane to be cleaned is carried out in different areas, so that the automatic cleaning effect of the airplane is ensured while the automatic cleaning of the airplane is realized.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (7)
1. An offline planning method for an automatic cleaning track of an aircraft based on ROS is characterized by comprising the following steps:
s1, scanning the airplane model through a visual sensor, and establishing an airplane three-dimensional model STL through point cloud;
s2, dividing the aircraft three-dimensional model STL to form a plurality of areas, and defining the cleaning positions of the areas;
and S3, planning the cleaning track of each area, and cleaning the area based on the cleaning track.
2. The ROS-based offline planning method for the automatic cleaning track of the airplane as claimed in claim 1, wherein the method for dividing the cleaning track of each area specifically comprises the following steps:
s31, dividing each area into a plurality of sub-areas;
s32, guiding a subregion of the region into RVIZ in an ROS system, dividing the subregion into a plurality of triangular plates, and acquiring normal vectors of the triangular plates and vertex coordinates of three vertexes;
s33, constructing a minimum bounding box of the corresponding sub-region based on the triangular plate of the sub-region;
s34, calculating vertex coordinates of eight vertexes of the minimum bounding box, and forming a projection plane by one vertex of the minimum bounding box and one axial vector;
s35, calculating the intersection points of all the triangular plates in the sub-area and the projection plane, wherein the intersection points are the target cleaning points of the sub-area;
and S36, acquiring target counting of all sub-areas in the area based on the steps S31 to S35, defining the target counting as target cleaning points of the area, and forming a cleaning track of the area based on the target cleaning points of the area.
3. The ROS-based offline planning method for the automatic cleaning trajectory of the airplane as claimed in claim 2, wherein the construction method for the minimum bounding box of the sub-area is specifically as follows:
s331, determining the three-axis directions of the minimum bounding box, namely the directions of an X axis, a Y axis and a Z axis based on the covariance matrix of the triangular plate in the sub-region;
s332, calculating the center coordinate of the minimum bounding box, and constructing the minimum bounding box based on the center coordinate of the minimum bounding box and the three-axis direction.
4. The ROS-based offline planning method for the automatic cleaning trajectory of an aircraft according to claim 3, wherein the determination method of the three axes of the minimum bounding box is as follows:
s3311, acquiring a covariance matrix of a triangular plate in a subregion, and calculating three eigenvectors and corresponding eigenvalues of the covariance matrix;
s3312, taking the direction of the characteristic vector R1 as the X-axis direction of the minimum bounding box, taking R1 as the characteristic vector corresponding to the maximum characteristic value, taking the direction of the characteristic vector R2 as the Z-axis direction of the minimum bounding box, taking R2 as the characteristic vector corresponding to the minimum characteristic value, taking the direction of the characteristic vector R3 as the Y-axis direction of the minimum bounding box, and taking R3 as the characteristic vector corresponding to the middle characteristic value.
5. The ROS-based offline planning method for automatic cleaning trajectory of aircraft according to claim 3, wherein the calculation method for the center coordinates of the minimum bounding box is specifically as follows:
s3321, constructing a matrix E based on three eigenvectors of covariance, wherein the matrix E is expressed as follows:
wherein, [ R1, R2, R3]Respectively, the eigenvector corresponding to the maximum eigenvalue, the eigenvector corresponding to the intermediate eigenvalue and the eigenvector corresponding to the minimum eigenvalue, n represents the number of vertices in the subregion, (X)i,Yi,Zi) Is the coordinate of the vertex of the triangle,
the mean value of the coordinates of the vertexes of the triangles in the sub-area is obtained;
s3322, calculating the coordinate (X) of the center point of the minimum bounding box based on the matrix Eo,Yo,Zo)；
Wherein (X)o,Yo,Zo) Col (0), minCoeff () represents the maximum value of the 1 st column in matrix E, col (0), minCoeff () represents the minimum value of the 1 st column in matrix E, and e.col (1), maxCoeff () represents the center point coordinate of the minimum bounding boxCol (1) minCoeff () represents the minimum value of column 2 in matrix E, col (2) maxCoeff () represents the maximum value of column 3 in matrix E, and col (2) minCoeff () represents the minimum value of column 3 in matrix E.
6. The ROS-based offline planning method for the automatic cleaning trajectory of the aircraft as claimed in claim 2, wherein the method for acquiring the target inventory in the sub-area is specifically as follows:
s351, detecting whether three vertexes of all the triangular plates in the sub-area are positioned on the same side of the projection plane;
and S352, if the detection result is positive, the triangular plate and the projection plane have no intersection, if the detection result is negative, the triangular plate and the projection plane have an intersection, and the intersection of the edge of the different side point of the triangular plate and the projection plane is calculated, wherein the edge of the different side point refers to a connecting line of vertexes on two sides of the projection plane.
7. The ROS-based offline planning method for automatic cleaning trajectory of aircraft according to claim 6, wherein the method for determining whether three vertexes of the triangular plate are located on the same side of the projection plane is specifically as follows:
s3511, projecting the triangular plate onto the projection plane to obtain three projection points of the triangular plate;
s3512, vectors from the three projection points to the corresponding vertexes are obtained, if the directions of the three vectors are consistent, the three vertexes of the triangular plate are located on the same side of the projection plane, and otherwise, the three vertexes of the triangular plate are not located on the same side.
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