CN-121389731-B - Pose calculation method and device for six-degree-of-freedom parallel mechanism in underground scene

CN121389731BCN 121389731 BCN121389731 BCN 121389731BCN-121389731-B

Abstract

The invention discloses a pose calculation method and a pose calculation device of a six-degree-of-freedom parallel mechanism in an underground scene, wherein the method comprises the steps of obtaining a training sample set; dividing each training sample into corresponding geometric areas based on training joint variables in a training sample set, training each geometric area, updating dictionary atoms, determining area weights of each geometric area, wherein the dictionary atoms are a list of elements of a dictionary and comprise basic features of a jacobian matrix, determining a target area in each geometric area based on the area weights, searching in the target area to obtain the closest training joint variable closest to the current joint variable, taking training pose corresponding to the closest training joint variable as a coarse sample, determining a coarse sample approximation jacobian matrix corresponding to the coarse sample based on the dictionary atoms, and performing iterative optimization on the coarse sample approximation jacobian matrix to obtain the current pose. The pose of the parallel mechanism can be accurately determined in real time in an underground scene.

Inventors

Sun Jiedi
ZHANG XIAOLONG
ZHANG ZHONGYUAN
SUN DONGSHENG

Assignees

燕山大学
中国地质科学院地质力学研究所

Dates

Publication Date: 20260508
Application Date: 20251013

Claims (8)

1. The pose calculation method of the six-degree-of-freedom parallel mechanism in the underground scene is characterized by comprising the following steps of: Acquiring a training sample set based on a kinematic model of the six-degree-of-freedom parallel mechanism, wherein training samples in the training sample set specifically comprise corresponding training joint variables and training poses; Dividing each training sample into corresponding geometric areas based on training joint variables in the training sample set, wherein the geometric areas are specifically a plurality of working areas which are divided according to the movable range of a center point of a movable platform and the maximum angle which can be achieved by the movable platform in space; Training each geometric region and updating dictionary atoms, and determining the region weight of each geometric region, wherein the dictionary atoms are specifically a list of elements of a dictionary and comprise basic features of a jacobian matrix; Determining a target area in each geometric area based on the area weight, searching in the target area to obtain a closest training joint variable which is closest to the current joint variable, and taking a training pose corresponding to the closest training joint variable as a rough sample; Determining a coarse sample approximation jacobian matrix corresponding to the coarse sample based on the dictionary atoms; and carrying out iterative optimization on the rough sample approximate jacobian matrix to obtain the current pose.
2. The method for calculating the pose of a six-degree-of-freedom parallel mechanism in an underground scene according to claim 1, wherein the kinematic model Is specifically shown as , wherein, For the position of the moving platform center point in the stationary coordinate system, For the rotation angle of the moving platform relative to the static coordinate system, the kinematic model based on the six-degree-of-freedom parallel mechanism acquires a training sample, and particularly generates the training sample through an inverse kinematic model and uniform grid sampling.
3. The method for calculating the pose of a six-degree-of-freedom parallel mechanism in an underground scene according to claim 1, wherein the division of the geometric region is specifically implemented by the following formula: , in the formula, As a region of the geometry, For the kth geometric region, Is the center of the i-th region, To train joint variables.
4. The method for calculating the pose of a six-degree-of-freedom parallel mechanism in an underground scene according to claim 1, wherein the updating dictionary atoms specifically comprises: Randomly selecting jacobian matrixes corresponding to limited training samples in the geometric area so as to obtain a plurality of initial dictionary atoms; and updating the plurality of initial dictionary atoms to obtain final dictionary atoms.
5. The method for pose calculation of six-degree-of-freedom parallel mechanism in underground scene according to claim 4, wherein the initial dictionary atoms are updated by the following formula: ; in the formula, To train the reorganized form of the jacobian matrix corresponding to the sample, To train the dictionary in the work area where the sample is located, For a sparse coded representation of the training samples correspondence, Is the Frobenius norm, For a sparse representation vector of the i-th signal, The maximum number of non-zero elements allowed in each sparse coding vector.
6. The method for calculating the pose of a six-degree-of-freedom parallel mechanism in an underground scene according to claim 1, wherein the regional weight is determined specifically by the following formula: ; in the formula, For the region weight of the i-th geometrical region, For the number of individuals in the i-th region, For the number of individuals in the j-th region, Is the total number of divided regions.
7. The method for calculating the pose of a six-degree-of-freedom parallel mechanism in an underground scene according to claim 1, wherein the coarse sample approximation jacobian matrix is iteratively optimized by the following formula: ; in the formula, For the direction and value of the data update, The jacobian matrix is approximated for the coarse samples, As a residual between the stem length of the coarse sample and the target stem length that corresponds to the current joint variable, In order to update the pose of the person, In order to be a damping coefficient, The pose is not updated.
8. A pose computing device of a six-degree-of-freedom parallel mechanism in an underground scene, the device comprising: the acquisition module is used for acquiring a training sample set based on a kinematic model of the six-degree-of-freedom parallel mechanism, wherein training samples in the training sample set are specifically corresponding training joint variables and training poses; The dividing module is used for dividing each training sample into corresponding geometric areas based on training joint variables in the training sample set, wherein the geometric areas are specifically a plurality of working areas which are divided according to the movable range of the center point of the movable platform and the maximum angle which can be achieved by the movable platform in space; The weight module is used for training each geometric region and updating dictionary atoms, and determining the region weight of each geometric region, wherein the dictionary atoms are specifically a column of elements of a dictionary and comprise basic features of a jacobian matrix; The searching module is used for determining a target area in each geometric area based on the area weight, searching in the target area to obtain a closest training joint variable which is closest to the current joint variable, and taking a training pose corresponding to the closest training joint variable as a rough sample; The determining module is used for determining a coarse sample approximation jacobian matrix corresponding to the coarse sample based on the dictionary atoms; and the updating module is used for carrying out iterative optimization on the rough sample approximate jacobian matrix to obtain the current pose.

Description

Pose calculation method and device for six-degree-of-freedom parallel mechanism in underground scene Technical Field The invention belongs to the technical field of parallel mechanisms, and particularly relates to a pose calculation method and device of a six-degree-of-freedom parallel mechanism in an underground scene. Background The parallel mechanism is also called a parallel robot (PARALLEL MECHANISM), called PM for short, and is a closed-loop mechanism which is formed by connecting a movable platform and a fixed platform through at least two independent motion chains, has two or more degrees of freedom and is driven in a parallel mode. In the prior art, the pose solving method for the parallel mechanism comprises a jacobian solving method based on kinematic analysis, a numerical differentiation method, a solving method based on a group intelligent algorithm and a jacobian predicting model based on a neural network, but the method is better in a conventional scene, but in an underground scene such as precise monitoring of an in-situ induced seismic signal through underground fault activity, the terrain is complex, and the precision of the existing scheme is reduced due to fault breaking zones with heterogeneous characteristics, vibration noise around faults and the like possibly existing in the underground scene, for example, the jacobian solving method based on the kinematic analysis is caused, a micro-slip effect which is difficult to model is caused on the contact surface of a mechanism branch and surrounding rock due to the heterogeneous characteristics of the fault breaking zones, when the fault dip angle exceeds a certain angle, the method is increased to twice the theoretical value due to unconsolidated rock mass-mechanism coupling dynamics, the displacement settlement error is seriously influenced by the inversion precision of fault momentum, and the mechanism is easy to enter the singular position shape during the peristaltic stage, and the jacobian solving method based on the kinematic analysis is directly invalid. Therefore, how to determine the pose of the parallel mechanism in real time and accurately in the underground scene is a technical problem to be solved by the person skilled in the art. Disclosure of Invention The invention aims to solve the technical problem that the pose of a parallel mechanism cannot be rapidly and accurately determined in an underground application scene in the prior art. In order to achieve the technical purpose, in one aspect, the invention provides a pose calculation method of a six-degree-of-freedom parallel mechanism in an underground scene, which comprises the following steps: Acquiring a training sample set based on a kinematic model of the six-degree-of-freedom parallel mechanism, wherein training samples in the training sample set specifically comprise corresponding training joint variables and training poses; Dividing each training sample into corresponding geometric areas based on training joint variables in the training sample set, wherein the geometric areas are specifically a plurality of working areas which are divided according to the movable range of a center point of a movable platform and the maximum angle which can be achieved by the movable platform in space; Training each geometric region and updating dictionary atoms, and determining the region weight of each geometric region, wherein the dictionary atoms are specifically a list of elements of a dictionary and comprise basic features of a jacobian matrix; Determining a target area in each geometric area based on the area weight, searching in the target area to obtain a closest training joint variable which is closest to the current joint variable, and taking a training pose corresponding to the closest training joint variable as a rough sample; Determining a coarse sample approximation jacobian matrix corresponding to the coarse sample based on the dictionary atoms; and carrying out iterative optimization on the rough sample approximate jacobian matrix to obtain the current pose. Further, the kinematic modelIs specifically shown as, wherein,For the position of the moving platform center point in the stationary coordinate system,For the rotation angle of the moving platform relative to the static coordinate system, the kinematic model based on the six-degree-of-freedom parallel mechanism acquires a training sample, and particularly generates the training sample through an inverse kinematic model and uniform grid sampling. Further, the division of the geometric region is specifically implemented by the following formula: , in the formula, As a region of the geometry,For the kth geometric region,Is the center of the i-th region,To train joint variables. Further, the updating dictionary atom specifically includes: Randomly selecting jacobian matrixes corresponding to limited training samples in the geometric area so as to obtain a plurality of initial dictionary atoms; and updating the plurali