Robot positioning control method and system based on point cloud normal vector direction clustering servo

Abstract

The invention discloses a robot positioning control method and system based on point cloud normal vector direction clustering servo, and belongs to the technical field of visual servo, and the robot has six-degree-of-freedom motion and is fixedly connected with an RGBD depth camera; the method comprises the following steps: acquiring an ideal point cloud image of a to-be-positioned target; calculating and clustering normal vectors of all points in the ideal point cloud image, and obtaining a clustering centroid set to obtain an actual point cloud image of the to-be-positioned target; calculating and clustering normal vectors of all points in the actual point cloud image, and obtaining a clustering centroid set MC; calculating a rotation matrix and a translation transformation vector of theRGBD depth camera at the current position relative to the ideal position according to the clustering centroid set and the MC, and calculating the speed VC of the RGBD depth camera based on the calculation result; and if the VC is not converged to 0, enabling the robot to move according to the VC for a preset time, recalculating the VC and judging until the VC is converged to 0. The invention hasa stable and high-precision positioning result for a weak texture target, and has better adaptability.

Description

technical field

[0001] The invention belongs to the technical field of visual servoing, and more specifically relates to a robot positioning control method and system based on point cloud normal vector direction clustering servo. Background technique

[0002] Robot positioning and servo control have a wide range of application requirements in robotic processing and manufacturing, intelligent logistics warehousing, medical assistance and other fields. Visual servoing is a visual control technology that uses visual information to control the movement of a robot to a desired position to achieve robot positioning.

[0003] Existing visual servoing techniques are generally divided into position-based visual servoing (PBVS) and image-based visual servoing (IBVS). PBVS needs to obtain the geometric model of the target, the internal parameters of the camera and the observed image feature information, and then estimate the relative pose of the camera and the target. Reducing the pos...

Examples

Embodiment 1

[0050] A robot positioning control method based on point cloud normal vector direction clustering servo, wherein, the robot has six degrees of freedom of motion, and is fixedly connected with an RGBD depth camera, consisting of the robot and the RGBD depth camera fixedly connected with it figure 1 In the visual platform 1 shown in , the target to be positioned 2 is figure 1 the blade shown;

[0051] In order to use the RGBD depth camera to obtain the point cloud image of the target to be located, the coordinate system of the target to be located and the coordinate system of the RGBD depth camera are respectively constructed, as shown in figure 2 shown;

[0052] Such as image 3 As shown, the robot positioning control method based on point cloud normal vector direction clustering servo provided by this embodiment includes the following steps:

[0053] (S1) Calculate the three-dimensional coordinates of each point on the target to be positioned in the coordinate system of th...

Embodiment 2

[0080] A robot positioning control system based on point cloud normal vector direction clustering servo, including: a positioning control module and a vision platform;

[0081] The visual platform consists of a robot with six degrees of freedom of movement and an RGBD depth camera fixedly connected to it;

[0082] The positioning control module includes: an ideal point cloud image acquisition unit, a first cluster centroid set acquisition unit, an actual point cloud image acquisition unit, a second cluster centroid set acquisition unit, a speed acquisition unit and a movement control unit;

[0083] The ideal point cloud image acquisition unit is used to calculate the three-dimensional coordinates of each point on the target to be positioned in the coordinate system of the RGBD depth camera when the robot is in an ideal position relative to the target to be positioned, to obtain an ideal point cloud image of the target to be positioned, and then Trigger the first cluster centro...

technical field

[0001] The invention belongs to the technical field of visual servoing, and more specifically relates to a robot positioning control method and system based on point cloud normal vector direction clustering servo. Background technique

[0002] Robot positioning and servo control have a wide range of application requirements in robotic processing and manufacturing, intelligent logistics warehousing, medical assistance and other fields. Visual servoing is a visual control technology that uses visual information to control the movement of a robot to a desired position to achieve robot positioning.

[0003] Existing visual servoing techniques are generally divided into position-based visual servoing (PBVS) and image-based visual servoing (IBVS). PBVS needs to obtain the geometric model of the target, the internal parameters of the camera and the observed image feature information, and then estimate the relative pose of the camera and the target. Reducing the pos...

Examples

Embodiment 1

[0050] A robot positioning control method based on point cloud normal vector direction clustering servo, wherein, the robot has six degrees of freedom of motion, and is fixedly connected with an RGBD depth camera, consisting of the robot and the RGBD depth camera fixedly connected with it figure 1 In the visual platform 1 shown in , the target to be positioned 2 is figure 1 the blade shown;

[0051] In order to use the RGBD depth camera to obtain the point cloud image of the target to be located, the coordinate system of the target to be located and the coordinate system of the RGBD depth camera are respectively constructed, as shown in figure 2 shown;

[0052] Such as image 3 As shown, the robot positioning control method based on point cloud normal vector direction clustering servo provided by this embodiment includes the following steps:

[0053] (S1) Calculate the three-dimensional coordinates of each point on the target to be positioned in the coordinate system of th...

Embodiment 2

[0080] A robot positioning control system based on point cloud normal vector direction clustering servo, including: a positioning control module and a vision platform;

[0081] The visual platform consists of a robot with six degrees of freedom of movement and an RGBD depth camera fixedly connected to it;

[0082] The positioning control module includes: an ideal point cloud image acquisition unit, a first cluster centroid set acquisition unit, an actual point cloud image acquisition unit, a second cluster centroid set acquisition unit, a speed acquisition unit and a movement control unit;

[0083] The ideal point cloud image acquisition unit is used to calculate the three-dimensional coordinates of each point on the target to be positioned in the coordinate system of the RGBD depth camera when the robot is in an ideal position relative to the target to be positioned, to obtain an ideal point cloud image of the target to be positioned, and then Trigger the first cluster centro...

Images