CN112008730B - Sun position identification and avoidance method based on solid-state area array laser radar - Google Patents
Sun position identification and avoidance method based on solid-state area array laser radar Download PDFInfo
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- CN112008730B CN112008730B CN202010911783.4A CN202010911783A CN112008730B CN 112008730 B CN112008730 B CN 112008730B CN 202010911783 A CN202010911783 A CN 202010911783A CN 112008730 B CN112008730 B CN 112008730B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
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Abstract
The invention discloses a sun position identification and avoidance method based on a solid-state area array laser radar, which comprises the following steps: (1) installing a solid-state area array laser radar at the tail end of the operating arm, identifying the position of the sun by the solid-state area array laser radar according to the point cloud picture and the gray scale picture, and setting the pixel point cloud distance in the block area as a maximum value to represent an overexposure point cloud cluster; (2) traversing all point cloud data of target positions acquired by the solid-state area array laser radar in real time to extract all exposure points; (3) carrying out point cloud clustering, and extracting a clustered point cloud center of mass to obtain a sun center position under a solid-state area array laser radar coordinate system; (4) converting the coordinate system of the robot into a coordinate system of the robot; (5) and the robot calculates the angle of the solid-state area array laser radar scanning electric wire according to the difference between the sun direction vector and the electric wire trend vector and plans the movement of the operation arm. The invention does not need to wait for the sun to move out of the visual field range for operation, and is suitable for various outdoor sunlight environments.
Description
Technical Field
The invention relates to the field of laser radar detection, in particular to a sun position identification and avoidance method based on a solid-state area array laser radar.
Background
The live working robot needs to work in the air outdoors, the situation of strong light is unavoidable, the robot depends heavily on accurate data provided by the solid-state area array laser radar in local modeling in actions such as wire grabbing, wire stripping, wire hanging and the like, but under the condition that the sun exists in the field of view of the solid-state area array laser radar, as shown in fig. 1, local exposure can be caused, the point cloud precision of a target is influenced, the solid-state area array laser fails to identify the target object, the process can be continued only after the angle of the sun is changed, and therefore a set of reasonable and effective sun position identification and avoidance scheme is needed.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the defects, the invention provides a sun position identification and avoidance method based on a solid-state area array laser radar.
The technical scheme is as follows:
a sun position identification and avoidance method based on a solid-state area array laser radar comprises the following steps:
(1) installing a solid-state area array laser radar at the tail end of an operating arm of the robot, identifying the area where the sun is located by the solid-state area array laser radar according to the point cloud picture and the gray scale picture, and setting the pixel point cloud distance in the area as a maximum value to represent an overexposure point cloud cluster;
(2) the robot traverses all points of point cloud data of a target position acquired by the solid-state area array laser radar in real time, and extracts all points with the maximum pixel point cloud distance, namely exposure points;
(3) carrying out point cloud clustering, and extracting a clustered point cloud mass center reaching an exposure point number threshold value to obtain a solar central position under a coordinate system of the solid-state area array laser radar;
(4) converting the sun center position under the solid area array laser radar coordinate system to the robot coordinate system to obtain the sun center position and the pointing vector thereof under the robot coordinate system, wherein the sun pointing vector is the vector of the origin of the solid area array laser radar pointing to the sun;
(5) and (4) controlling an operation arm of the robot to calculate the angle of the solid-state area array laser radar scanning electric wire according to the sun center position and the pointing vector under the robot coordinate system obtained in the step (4) and the difference value between the sun pointing vector and the electric wire trend vector, and re-planning the motion of the operation arm of the robot.
The step (3) is specifically as follows:
(31) finding n points nearest to the certain point in all the exposure points extracted in the step (2) by using kdTere, judging the distance between the n points and the certain point, and placing the point with the distance smaller than a threshold value r in a class Q;
(32) finding a point in class Q, finding n points closest to the point by using kdTere in all exposure points, judging the distance from the n points to the point, and placing the point with the distance less than a threshold value r in class Q until no new point is added in class Q;
(33) judging whether the number of point clouds in the class Q is between the set exposure point number thresholds, if so, finishing the search, and turning to the step (34); if not, returning to the step (31);
(34) calculating the coordinate mean (Q) of all pixel points in class QAverage_x、qAverage_y、qAverage_z) Namely the centroid of the clustered point cloud, namely the position (Sun) of the Sun under the camera coordinate systemCamera_x、SunCamera_y、SunCamera_z)。
The step (4) is specifically as follows: the coordinate relation of the solid-state area array laser radar coordinate system relative to the robot operating arm is RTCamera_FlangeThe identified Sun center position is SunCameraThe coordinate relation from the robot operating arm to the robot coordinate origin is RTFlange_RobotThen the coordinates Sun of the Sun center position under the robot coordinate system can be calculatedRobot＝RTFlange_Robot*RTCamera_Flangee*SunCamera。
Has the advantages that: by adopting the sun position identification and avoidance method, an outdoor robot is not required to wait for the sun to move out of the visual field range for operation, and the method can adapt to various outdoor sunlight environments at any time without blocking the whole operation flow.
Drawings
Fig. 1 is a schematic diagram of a solid-state area array lidar in the presence of the sun in the field of view.
Detailed Description
The invention is further elucidated with reference to the drawings and the embodiments.
The invention relates to a sun position identification and planning method based on a solid-state area array laser radar, which comprises the following steps:
(1) the method comprises the following steps that a solid-state area array laser radar is mounted at the tail end of an operation arm of the robot, and the depth distance of a target object can be fed back by the solid-state area array laser radar according to the identified object; when the sun enters the field range of 85 degrees to 48 degrees of the solid-state area array laser radar, the solid-state area array laser radar identifies the position of the sun according to the point cloud picture and the gray scale picture, and the pixel point cloud distance in the block area is set as the maximum value to represent the cloud cluster of the overexposure point;
(2) the robot traverses all points of point cloud data of target positions acquired by the solid-state area array laser radar in real time, and extractsThe obtained point with the maximum point cloud distance of all the pixels is the exposure point, and the method specifically comprises the following steps: the Distance between the pixel points is obtained by screeningPoint_i＝DistanceMaxTo get P (Point _ i, Point _ j, …);
(3) carrying out point cloud clustering, and extracting a clustered point cloud mass center reaching an exposure point number threshold value to obtain a sun central position coordinate under a coordinate system of the solid-state area array laser radar; the method specifically comprises the following steps:
(31) finding a certain Point P10 in P (Point _ i, Point _ j, …), finding n points nearest to the certain Point in P (Point _ i, Point _ j, …) by using kdTere, judging the distance from the n points to P10, and placing the points with the distance smaller than a threshold value r in a class Q; wherein, the threshold value r represents the maximum distance from the point p10 in the space and is set according to the clustering range;
(32) finding a point in class Q, finding n points closest to the point by using kdTere in all exposure points, judging the distance from the n points to the point, and placing the point with the distance less than a threshold value r in class Q until no new point is added in class Q;
(33) judging whether the number of point clouds in the class Q is between the set exposure point number thresholds, if so, finishing the search, and turning to the step (34); if not, returning to the step (31); wherein the exposure point number threshold is 100 pixel points;
(34) calculating the coordinate mean (Q) of all pixel points in class QAverage_x、qAverage_y、qAverage_z) Namely the centroid of the clustered point cloud, namely the position (Sun) of the Sun center under the camera coordinate systemCamera_x、SunCamera_y、SunCamera_z)。
(4) Coordinate conversion is carried out through a tf tree carried by ros, the central position of the sun under a coordinate system of the solid-state area array laser radar is converted into a coordinate system of the robot, and the central position coordinate of the sun and a pointing vector thereof under the coordinate system of the robot are obtained, namely the vector of the origin of the solid-state area array laser radar pointing to the sun;
wherein, the conversion of the position coordinates of the sun:
the coordinate relation of the solid-state area array laser radar coordinate system relative to the robot operating arm is RTCamera_FlangeThe identified Sun center position is SunCameraThe coordinate relation from the robot operating arm to the robot coordinate origin is RTFlange_RobotThen the coordinates Sun of the Sun center position under the robot coordinate system can be calculatedRobot＝RTFlange_Robot*RTCamera_Flangee*SunCamera。
(5) And (4) controlling an operating arm of the robot to calculate the angle of the solid-state area array laser radar scanning electric wire according to the sun center position and the pointing vector under the robot coordinate system obtained in the step (4) and the difference value between the sun pointing vector and the electric wire trend vector, and re-planning the motion of the operating arm of the robot, namely controlling the operating arm to rotate by taking a cable main line as an axis according to the sun center position until the cable is in the field of view of the solid-state area array laser radar, so that the sun exits the field of view of the solid-state area array laser radar, and the accuracy of cloud identification of the target object point is ensured.
Although the preferred embodiments of the present invention have been described in detail, the present invention is not limited to the details of the foregoing embodiments, and various equivalent changes (such as number, shape, position, etc.) may be made to the technical solution of the present invention within the technical spirit of the present invention, and these equivalent changes are all within the protection scope of the present invention.
Claims (3)
1. A sun position identification and avoidance method based on a solid-state area array laser radar is characterized in that: the method comprises the following steps:
(1) installing a solid-state area array laser radar at the tail end of an operating arm of the robot, identifying the area where the sun is located by the solid-state area array laser radar according to the point cloud picture and the gray scale picture, and setting the pixel point cloud distance in the area as a maximum value to represent an overexposure point cloud cluster;
(2) the robot traverses all points of point cloud data of a target position acquired by the solid-state area array laser radar in real time, and extracts all points with the maximum pixel point cloud distance, namely exposure points;
(3) carrying out point cloud clustering, and extracting a clustered point cloud mass center reaching an exposure point number threshold value to obtain a solar central position under a coordinate system of the solid-state area array laser radar;
(4) converting the sun center position under the solid area array laser radar coordinate system to the robot coordinate system to obtain the sun center position and the pointing vector thereof under the robot coordinate system, wherein the sun pointing vector is the vector of the origin of the solid area array laser radar pointing to the sun;
(5) and (4) controlling an operation arm of the robot to calculate the angle of the solid-state area array laser radar scanning electric wire according to the sun center position and the sun direction vector of the robot coordinate system obtained in the step (4) and the difference value between the sun direction vector and the electric wire trend vector, and re-planning the motion of the operation arm of the robot.
2. The sun position identifying and avoiding method according to claim 1, wherein: the step (3) is specifically as follows:
(31) finding n points nearest to the certain point in all the exposure points extracted in the step (2) by using kdTere, judging the distance between the n points and the certain point, and placing the point with the distance smaller than a threshold value r in a class Q;
(32) finding a point in class Q, using kdTere to find n points nearest to the point in all the exposure points, judging the distance from the n points to the point, and placing the points with the distance less than a threshold value r in class Q until no new point is added in class Q;
(33) judging whether the number of point clouds in the class Q is between the set exposure point number thresholds, if so, finishing the search, and turning to the step (34); if not, returning to the step (31);
(34) calculating the coordinate mean (Q) of all pixel points in class QAverage_x、qAverage_y、qAverage_z)Namely the centroid of the clustered point cloud, namely the position (Sun) of the Sun under the camera coordinate systemCamera_x、SunCamera_y、SunCamera_z)。
3. The sun position identifying and avoiding method according to claim 1, wherein: the step (4) is specifically as follows: the coordinate relation of the solid-state area array laser radar coordinate system relative to the robot operating arm is RTCamera_FlangeThe identified Sun center position is SunCameraThe coordinate relation from the robot operating arm to the robot coordinate origin is RTFlange_RobotThen the coordinates Sun of the Sun center position under the robot coordinate system can be calculatedRobot＝RTFlange_Robot*RTCamera_Flangee*SunCamera。
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| CA2792156A1 (en) * | 2012-10-10 | 2014-04-10 | Mammoet Canada Holdings Inc. | Cable catcher |
| CN110120074A (en) * | 2019-05-10 | 2019-08-13 | 清研同创机器人（天津）有限公司 | A kind of hot line robot cable localization method under complex environment |
| CN110802608A (en) * | 2019-10-29 | 2020-02-18 | 许昌许继软件技术有限公司 | Live working robot and positioning method of high-voltage cable |
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