Coaxial cable-driven robotic arm configuration detection method and apparatus based on binocular vision

Abstract

The present invention relates to a coaxial cable-driven robotic arm configuration detection method and apparatus based on binocular vision. A coaxial cable-driven robotic arm comprises a plurality of joints. The method comprises: acquiring a first image and a second image of a coaxial cable-driven robotic arm which are captured by a binocular camera; on the basis of the first image and the second image, calculating center coordinates of each joint; and on the basis of the center coordinates of the joints, determining the configuration of the coaxial cable-driven robotic arm. The present invention realizes the accurate detection of the configuration of a coaxial cable-driven robotic arm, thereby providing strong support for the operation of the robotic arm in a narrow space; moreover, the detection process is simplified and the dependency on a sensor and a complex model is reduced, thereby reducing the costs and maintenance difficulty, and being applicable to different types of coaxial cable-driven robotic arms and different application scenarios.

Description

Coaxial rope-driven robot arm configuration detection method and device based on binocular vision TECHNICAL FIELD

[0001] The present application relates to the technical field of computer vision, in particular to a coaxial rope-driven robot arm configuration detection method and device based on binocular vision. BACKGROUND

[0002] With the development of minimally invasive surgery and oral detection medical technologies, higher requirements are put forward for robot systems operating in narrow spaces. Coaxial rope-driven robot arms show great application potential in these fields due to their unique flexibility and redundancy. However, due to the structural characteristics of coaxial rope-driven robot arms, configuration detection in narrow spaces becomes a technical problem.

[0003] Currently, configuration detection of coaxial rope-driven robot arms mainly relies on traditional measurement methods, such as sensor arrays, mechanical models of robot arms, etc. However, these methods have many limitations in practical applications, such as the complexity of sensor arrangement, the inaccuracy of mechanical models, etc., resulting in difficulty in meeting the requirements of detection accuracy and robustness.

[0004] SUMMARY

[0005] The main purpose of the present application is to provide a coaxial rope-driven robot arm configuration detection method and device based on binocular vision to solve the problem of low configuration detection accuracy of coaxial rope-driven robot arms in the prior art.

[0006] To achieve the above-mentioned purpose, the first aspect of the present application provides a coaxial rope-driven robot arm configuration detection method based on binocular vision, the coaxial rope-driven robot arm comprising a plurality of joints, the method comprising:

[0007] obtaining a first image and a second image of the coaxial rope-driven robot arm taken by a binocular camera;

[0008] calculating the center coordinates of each joint according to the first image and the second image, respectively;

[0009] determining the configuration of the coaxial rope-driven robot arm according to the center coordinates of each joint.

[0010] Further, the joint comprises a first connecting part and a second connecting part connected to each other, the second connecting part comprises opposite top and bottom surfaces, the top surface is adjacent to the first connecting part of the same joint, and the bottom surface is adjacent to another joint;

[0011] Two adjacent joints are connected by inserting the first connecting part of one joint into the second connecting part of the other joint; a plurality of joints are sequentially connected to form the coaxial rope-driven robot arm;

[0012] The second connecting part is cylindrical, and a preset marking graphic is provided on the outer side of the second connecting part;

[0013] The binocular camera is positioned at a predetermined distance on the side of the coaxial cable-driven robotic arm, and the side of the coaxial cable-driven robotic arm is the side from which the binocular camera can capture the predetermined marking pattern.

[0014] Furthermore, the preset identifier graphic is circular, and the step of calculating the center coordinates of each joint based on the first image and the second image includes:

[0015] Based on the first image and the second image, it is determined whether the center line of each preset mark graphic and the center line of the second connecting part of the joint corresponding to each preset mark graphic coincide, and whether the center line of the second connecting part of the joint corresponding to each preset mark graphic coincides with the axis of the binocular camera.

[0016] Based on the judgment result, calculate the center coordinates of the joints corresponding to each of the preset identifier graphics.

[0017] Further, the step of calculating the center coordinates of the joints corresponding to each of the preset identifier graphics based on the judgment result includes:

[0018] If the centerline of the preset logo coincides with the centerline of the second connecting part of the joint corresponding to the preset logo, then the spatial coordinates a(x) of the uppermost part of the preset logo are calculated based on the first image and the second image. a ,y a ,z a The lowest spatial coordinate c(x) c ,y c ,z c The leftmost spatial coordinate b(x) b ,y b ,z b ) and the rightmost spatial coordinate d(x) d ,y d ,z d );

[0019] Through the uppermost spatial coordinates a(x) a ,y a ,z a ) and the lowest spatial coordinates c(x) c ,y c ,z c The coordinates of the center of the first marker were calculated. and the first identification center coordinate is moved along a normal vector direction of the preset identification pattern by a distance r to obtain a center coordinate of a joint corresponding to the preset identification pattern, wherein a direction of the normal vector is perpendicular from a center of the preset identification pattern to a central axis of the second connecting part, and r is an outer diameter of a cross section of the second connecting part; or

[0020] a leftmost spatial coordinate b(x b ,y b ,z b ) and a rightmost spatial coordinate d(x d ,y d ,z d ) are calculated to obtain a second identification center coordinate and the second identification center coordinate is moved along a normal vector direction of the preset identification pattern by a distance r to obtain a center coordinate of a joint corresponding to the preset identification pattern; or

[0021] a mean value of the first identification center coordinate and the second identification center coordinate is calculated to obtain a third identification center coordinate and the third identification center coordinate is moved along a normal vector direction of the preset identification pattern by a distance r to obtain a center coordinate of a joint corresponding to the preset identification pattern.

[0022] Further, the step of calculating the center coordinate of the joint corresponding to the preset identification pattern according to the judgment result comprises:

[0023] if the axis of the preset identification pattern and the second connecting part central line of the joint corresponding to the preset identification pattern do not coincide, but the second connecting part central line of the joint corresponding to the preset identification pattern coincides with the axis of the binocular camera, then a coordinate A(x A ,y A ,z A ) of an upper end point of a bottom surface circular arc segment of the second connecting part of the joint, a coordinate B(x B ,y B ,z B ) of a lower end point, and a coordinate M(x M ,y M ,z M ) of a circular arc center point of the bottom surface circular arc segment are obtained;

[0024] an intersection coordinate O(x O ,y O ,z O ) of a first median line of the line segment AM and a second median line of the line segment BM is calculated, wherein the line segment AM is composed of the upper end point and the circular arc center point, and the line segment BM is composed of the lower end point and the circular arc center point.

[0025] Move the intersection point coordinates o(x,y,z) along the central axis of the second connecting part, and from the bottom surface of the second connecting part of the same joint to the top surface of the second connecting part, by a distance h / 2, to obtain the center coordinates of the joint, where h is the generatrix length of the second connecting part.

[0026] Further, the step of calculating the center coordinates of the joints corresponding to each of the preset identifier graphics based on the judgment result includes:

[0027] If the axis of the preset identifier graphic does not coincide with the centerline of the second connecting part of the joint corresponding to the preset identifier graphic, and the centerline of the second connecting part of the joint corresponding to the preset identifier graphic does not coincide with the axis of the binocular camera, then obtain the coordinate A(x) of the upper endpoint of the bottom arc segment of the second connecting part of the joint. A ,y A ,z A The coordinates B(x) of the lower endpoint of the bottom arc segment. B ,y B ,z B ), and the coordinates M(x) of the center point of the arc of the bottom arc segment. M ,y M ,z M );

[0028] Calculate the coordinates O(x) of the intersection point of the first perpendicular bisector of line segment AM and the second perpendicular bisector of line segment BM. O ,y O ,z O The line segment AM is formed by connecting the upper endpoint and the center point of the arc, and the line segment BM is formed by connecting the lower endpoint and the center point of the arc.

[0029] Obtain the leftmost spatial coordinates b(x) of the preset identifier graphic. b ,y b ,z b ) and the rightmost spatial coordinates d(x) d ,y d ,z d ), calculate vector The vector The first connecting part is parallel to the central axis of the two connecting parts, and is located to the left of the second connecting part;

[0030] Based on the intersection point coordinates O(x) O ,y O ,z O ) and the vector An orientation vector of the central axis of the second connecting part is obtained and converted into a central axis straight line expression;

[0031] and the uppermost spatial coordinates a(x a ,y a ,z a ), the lowermost spatial coordinates c(x c ,y c ,z c ), the leftmost spatial coordinates b(x b ,y b ,z b ) and the rightmost spatial coordinates d(x d ,y d ,z d ) of the preset identification pattern, a normal vector of a plane determined by the center of the preset identification pattern and perpendicular to and is calculated, wherein and the normal vector is converted into a normal straight line expression;

[0032] According to the central axis straight line expression and the normal straight line expression, the intersection coordinates of the central axis and the normal are calculated, and the intersection coordinates are the center coordinates of the joint corresponding to the preset identification pattern.

[0033] Further, the step of calculating the center coordinates of each joint according to the first image and the second image comprises:

[0034] The first image and the second image are preprocessed to obtain a grayscale image;

[0035] The edges of each joint are extracted from the grayscale image;

[0036] A circumscribed rectangle circumscribing the edges of the joint is drawn;

[0037] The centroid coordinates of the circumscribed rectangle are calculated, and the centroid coordinates are taken as the center coordinates of the joint.

[0038] Further, the step of determining the configuration of the coaxial rope-driven manipulator according to the center coordinates of each joint further comprises:

[0039] The spatial pose of each joint is determined according to the center coordinates of each joint and the central axis of the second connecting part of each joint.

[0040] Further, the step of determining the spatial pose of each joint according to the center coordinates of each joint and the central axis of the second connecting part of each joint further comprises:

[0041] present the configuration of the coaxial rope-driven manipulator in a three-dimensional graph according to the spatial poses of the joints.

[0042] The second aspect of the present application provides a coaxial rope-driven manipulator configuration detection device based on binocular vision, the coaxial rope-driven manipulator comprising a plurality of joints, the device comprising:

[0043] an acquisition module configured to acquire a first image and a second image of the coaxial rope-driven manipulator captured by a binocular camera;

[0044] a center coordinate calculation module configured to calculate the center coordinates of the joints according to the first image and the second image, respectively;

[0045] a configuration determination module configured to determine the configuration of the coaxial rope-driven manipulator according to the center coordinates of the joints.

[0046] The coaxial rope-driven manipulator configuration detection method and device based on binocular vision provided by the present application realize accurate detection of the configuration of the coaxial rope-driven manipulator, provide strong support for the operation of the manipulator in a narrow space, simplify the detection process, reduce the dependence on sensors and complex models, reduce costs and maintenance difficulty, and are suitable for different types of coaxial rope-driven manipulators and different application scenarios. BRIEF DESCRIPTION OF DRAWINGS

[0047] FIG. 1 is a flowchart of a coaxial rope-driven manipulator configuration detection method based on binocular vision according to an embodiment of the present application;

[0048] FIG. 2 is a side view of a coaxial rope-driven manipulator according to an embodiment of the present application;

[0049] FIG. 3 is a side view of a joint of a coaxial rope-driven manipulator according to an embodiment of the present application;

[0050] FIG. 4 is a structural diagram of the positional relationship between a preset identification pattern, a joint, and a binocular camera according to an embodiment of the present application;

[0051] FIG. 5 is a flowchart of center coordinate calculation of a joint according to an embodiment of the present application;

[0052] FIG. 6 is a diagram of the spatial relationship between the central axis of a second connecting portion spatial cylinder according to an embodiment of the present application;

[0053] FIG. 7 is a diagram of the geometric relationship between a point on a cylinder and the central axis according to an embodiment of the present application;

[0054] Figure 8 is a structural schematic block diagram of a coaxial rope-driven mechanical arm configuration detection device based on binocular vision in an embodiment of the present application;

[0055] The implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solutions and advantages of the present application more clear, the present application will be further described in detail below in combination with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0057] Referring to Figures 1 and 2, the embodiment of the present application discloses a coaxial rope-driven mechanical arm configuration detection method based on binocular vision, the coaxial rope-driven mechanical arm comprising a plurality of joints 1, the method comprising:

[0058] S1, acquiring a first image and a second image of the coaxial rope-driven mechanical arm taken by a binocular camera;

[0059] S2, calculating the center coordinates of each joint according to the first image and the second image, respectively;

[0060] S3, determining the configuration of the coaxial rope-driven mechanical arm according to the center coordinates of each joint.

[0061] In the above step S1 of the present embodiment, the binocular vision technology can acquire the three-dimensional coordinates of the object in real time and accurately by simulating the working principle of the human eye, providing rich visual perception information for the robot.

[0062] The installation position of the binocular camera should ensure that the binocular camera can clearly capture all or key parts of the joints of the coaxial rope-driven mechanical arm, and the field of view of the two cameras should have sufficient overlapping area for stereo matching. Generally, the cameras are installed on the side or above the mechanical arm, depending on the working environment and structural features of the mechanical arm. After installation, the binocular camera is calibrated. The purpose of calibration is to determine the relative position relationship (including rotation and translation) between the two cameras and their internal parameters (such as focal length, optical center, etc.), so as to ensure the accuracy of subsequent image processing. This is usually done by shooting a calibration board with known patterns and applying a specific algorithm. Start the binocular camera and shoot the current state of the coaxial rope-driven mechanical arm. Since the binocular camera has two lenses, they will capture two slightly different images of the mechanical arm at the same time, i.e. the first image and the second image.

[0063] In step S2, the first image and the second image are pre-processed, including denoising, contrast enhancement, grayscale processing, etc., to improve the image quality and simplify the subsequent processing steps. The features of the joints are extracted from the images through image processing techniques such as edge detection, corner detection, template matching, etc. The joint features in the first image and the second image are matched using the stereo vision principle of the binocular camera. By comparing the parallax of the corresponding points in the two images, the positions of these joint feature points in the three-dimensional space can be calculated. Then, the center coordinates of each joint are calculated based on the positions of these joint feature points.

[0064] In step S3, the method for determining the configuration of the coaxial rope-driven manipulator includes reconstructing the configuration of the coaxial rope-driven manipulator in three-dimensional space using the three-dimensional center coordinates of each joint. The configuration reconstruction step usually involves connecting the joint nodes into line segments or curves to represent the skeletal structure of the manipulator. The reconstructed configuration is analyzed to calculate the relative positions, angles, or distances between the joints to determine the current state of the manipulator (such as the bending degree, extension length, etc.). The configuration information obtained from the analysis is output in a predefined form, such as displayed on the screen, stored in a file, or sent to the control system for further processing.

[0065] The above steps achieve accurate detection of the configuration of the coaxial rope-driven manipulator, providing strong support for the operation of the manipulator in a small space. At the same time, the detection process is simplified, the dependence on sensors and complex models is reduced, the cost and maintenance difficulty are reduced, and it is suitable for different types of coaxial rope-driven manipulators and different application scenarios.

[0066] Specifically, referring to FIGS. 1 and 2, the joint 1 of the coaxial rope-driven manipulator includes a first connecting part 11 and a second connecting part 12 connected to each other. The second connecting part includes opposite top and bottom surfaces 121 and 122. The top surface 121 is adjacent to the first connecting part 11 of the same joint 1, and the bottom surface 122 is adjacent to another joint 1. Two adjacent joints 1 are connected by inserting the first connecting part 11 of one joint 1 into the second connecting part 12 of the other joint 1. A plurality of joints 1 are sequentially connected to form the coaxial rope-driven manipulator. The second connecting part 12 is cylindrical, and a preset identification pattern 13 is provided on the outer side surface of the second connecting part 12. In order to improve the recognition accuracy and efficiency of the joints by the binocular camera, the preset identification pattern 13 is provided on the outer side surface of the second connecting part 12. The preset identification pattern 13 can be a simple geometric shape (such as a circle, a square, etc.), or a pattern with specific coding information.

[0067] The binocular camera is arranged at a preset distance from the side of the coaxial rope-driven mechanical arm, and the side of the coaxial rope-driven mechanical arm is a side from which the binocular camera can capture the preset identification pattern. The preset distance is selected to ensure that the binocular camera can clearly capture all the joints and the corresponding preset identification patterns, and the field of view of the two cameras has sufficient overlapping area for stereo matching.

[0068] In one specific embodiment, the preset identification pattern is a circle, and the step S2 of calculating the center coordinates of each joint according to the first image and the second image comprises:

[0069] S21, judging whether the axis of each preset identification pattern and the center line of the second connecting part of the joint corresponding to each preset identification pattern coincide, and whether the center line of the second connecting part of the joint corresponding to each preset identification pattern and the axis of the binocular camera coincide according to the first image and the second image;

[0070] S22, calculating the center coordinates of the joint corresponding to each preset identification pattern according to the judgment result.

[0071] In this embodiment, a circle is preferably used as the preset identification pattern because the circle has the advantages of easy recognition and calculation. A circular identification pattern is arranged on the outer side of the second connecting part of each joint to assist the binocular camera in image processing and three-dimensional coordinate calculation. The step S21 of this embodiment calculates the axis of the preset identification pattern and the center line of the second connecting part by image processing on the first image and the second image. The axis of the preset identification pattern is a straight line passing through the center of the preset identification pattern and perpendicular to the tangent plane at the center of the preset identification pattern. The second connecting part of the joint is approximately rectangular in the first or second image captured by the binocular vision camera, and the center line is a straight line passing through the center of the rectangle and perpendicular to the second connecting part axis. The second connecting part is cylindrical, and the second connecting part axis is a straight line passing through the center of the cross section (circle) of the second connecting part and perpendicular to the cross section. The axis of the binocular camera is the main optical axis of the lens, which can be determined by the parameters of the binocular camera (such as the manually set height, lens size parameters, etc.). The center coordinates of the joint are calculated by selecting different methods based on the positional relationship of the three.

[0072] In one specific embodiment, the step S22 of calculating the center coordinates of the joint corresponding to each preset identification pattern according to the judgment result comprises:

[0073] S2211, referring to FIGS. 4(a) and 4(b), if the axis of the preset identification pattern and the second connecting part center line of the joint corresponding to the preset identification pattern coincide, the uppermost spatial coordinates a(x a ,y a ,z a ), the lowermost spatial coordinates c(x c ,y c ,z c ), the leftmost spatial coordinates b(x b ,y b ,z b ) and the rightmost spatial coordinates d(x d ,y d ,z d ) of the preset identification pattern are calculated according to the first image and the second image; the spatial coordinates of specific points (such as the uppermost, the lowermost, the leftmost and the rightmost) on the identification pattern can be calculated by using the first image and the second image taken from different angles by the two cameras through the binocular stereo vision technology, and through feature matching and triangulation.

[0074] S2212, the first identification center coordinates are calculated by the uppermost spatial coordinates a(x a ,y a ,z a ) and the lowermost spatial coordinates c(x c ,y c ,z c ), and the center coordinates of the joint corresponding to the preset identification pattern are obtained by moving the first identification center coordinates along the normal vector direction of the preset identification pattern by a distance r, wherein the direction of the normal vector is perpendicular to the second connecting part center line from the center of the preset identification pattern, and r is the outer diameter of the cross section of the second connecting part; wherein the cross section of the second connecting part is a circular cross section. Or,

[0075] S2213, the second identification center coordinates are calculated by the leftmost spatial coordinates b(x b ,y b ,z b ) and the rightmost spatial coordinates d(x d ,y d ,z d ), and the center coordinates of the joint corresponding to the preset identification pattern are obtained by moving the second identification center coordinates along the normal vector direction of the preset identification pattern by a distance r, wherein the direction of the normal vector and the definition of r are the same as those in S2203. Or,

[0076] S2214, averaging the first and second identification center coordinates to obtain a third identification center coordinate and moving the third identification center coordinate along the normal vector direction of the preset identification pattern by a distance r to obtain the center coordinate of the joint corresponding to the preset identification pattern, wherein the direction of the normal vector and the definition of r are the same as in S2203. Step S2204 can further improve the calculation accuracy of the center coordinate.

[0077] In one embodiment, the step S22 of calculating the center coordinate of the joint corresponding to the preset identification pattern according to the judgment result comprises:

[0078] If the axis line of the preset identification pattern coincides with the center line of the second connecting part of the joint corresponding to the preset identification pattern, but the center line of the second connecting part of the joint corresponding to the preset identification pattern does not coincide with the axis line of the binocular camera, referring to FIG. 4(b), then,

[0079] According to the uppermost spatial coordinate a(x a ,y a ,z a ), the lowermost spatial coordinate c(x c ,y c ,z c ), the leftmost spatial coordinate b(x b ,y b ,z b ) and the rightmost spatial coordinate d(x d ,y d ,z d ) of the preset identification pattern, the direction vector of the uppermost direction of the preset identification pattern pointing to the lowermost direction of the preset identification pattern is calculated as and the direction vector of the leftmost direction of the preset identification pattern pointing to the rightmost direction of the preset identification pattern is calculated as

[0080] The normal vector of the preset identification pattern is calculated as wherein the direction of the normal vector is perpendicular to the central axis of the cylinder from the center of the preset identification pattern; wherein and represent the lengths of the corresponding vectors, and θ is the included angle between the two vectors, represents a unit normal vector perpendicular to the plane determined by and .

[0081] Given the center spatial coordinate of the marker point and the normal vector The axis line of the marker point is expressed in a straight line point formula.

[0082] Since the axis of the preset identification pattern coincides with the second connecting part center line, only the center point space coordinate of the mark point is moved along the axis of the preset identification pattern by a distance of a radius of a second connecting part cross section (circular surface). The coordinate of a point on the axis of the preset identification pattern is P(x1, y1, z1), and the new coordinate of the point after moving a distance r on the straight line is Q(x2, y2, z2), which is the center coordinate of the joint. The normal vector of the axis of the preset identification pattern is The equation of the straight line after simplification of the direction vector is ax+by+cz+d=0.

[0083] Wherein a, b, and c are the direction vector of the straight line, and d is the intercept.

[0084] Suppose the coordinate of a general point on the axis of the preset identification pattern is (x, y, z), and the relationship between the point P and the general point can be expressed as (x, y, z)=(x1+a r r, y1+br, z1+cr).

[0085] Substitute the coordinate of this point into the general expression of the axis, and the relationship is obtained after arrangement: a 2 r+b 2 r+c 2 r=-(ax1+by1+cz1+d).

[0086] According to the above equation, the coordinates of the new coordinate point Q(x2, y2, z2) after moving can be obtained as:

[0087] In one specific embodiment, the step S22 of calculating the center coordinates of the joints corresponding to each of the preset identification patterns according to the judgment result comprises:

[0088] S2231, referring to FIG. 4(c), if the axis of the preset identification pattern does not coincide with the second connecting part center line of the joint corresponding to the preset identification pattern, but the second connecting part center line of the joint corresponding to the preset identification pattern coincides with the axis of the binocular camera, the coordinates of the upper end point A(x A ,y A ,z A ) of the bottom surface circular arc segment of the second connecting part of the joint, the lower end point B(x B ,y B ,z B ) and the circular arc center point M(x M ,y M ,z M ) of the bottom surface circular arc segment are obtained.

[0089] S2232, the intersection point coordinates O(xO ,y O ,z O ), wherein the line segment AM is composed of the upper end point and the arc center point, and the line segment BM is composed of the lower end point and the arc center point;

[0090] S2233、the intersection coordinates O(x O ,y O ,z O ) are moved along the central axis of the second connecting part, and in the direction from the bottom surface of the second connecting part to the top surface of the second connecting part of the same joint, by a distance h / 2, to obtain the center coordinates of the joint, wherein h is the generatrix length of the second connecting part.

[0091] Specifically, in the embodiment, the first median S1 passes through the midpoint of the line segment AM The direction vector of the line segment AM is From the basic property of the median, it can be obtained that the direction vector of the line segment AM is the normal vector of the median S1, that is, The equation expression of the median S1 can be obtained from the point-slope form of a straight line as follows:

[0092] Similarly, the median S2 passes through the midpoint of the line segment BM The direction vector of the line segment BM is The equation expression of the median S2 can be obtained from the point-slope form of a straight line as follows:

[0093] To solve the circle center O(x O ,y O ,z O ), the basic property of a circle needs to be applied. From the fact that the distance from each point on a circle to the center is equal, the following can be obtained: d A-O =d B-O =d C-O ;

[0094] After substituting the coordinates of each point and calculating the numerical values, the following is obtained:

[0095] In order to facilitate the transformation of coordinates and the calculation of numerical values, the medians S1 and S2 are simplified into the general expression of a straight line in a plane. It is assumed that:

[0096] In this way, the complex problem is transformed into a simple equation solving problem, and the medians S1 and S2 are further simplified as follows:

[0097] Since these are three coordinate points in space, the plane position of the circle can be determined as long as they are not on a straight line. Therefore, the third equation should be a plane constraint equation, that is:

[0098] Similarly, simplifying the plane constraint equations into general homogeneous forms, we assume:

[0099] The general form of the plane constraint equation can be obtained: A3x + B3y + C3z + D3 = 0;

[0100] Combining the formulas, we can form a system of linear algebraic equations about the spatial coordinates of the circle's center:

[0101] Based on Cramer's rule, the coordinates O(x) of the center of the base of the spatial cylinder were further calculated. O ,y O ,z O ):

[0102] Since the midline of the joint coincides with the camera's axis, the direction vector of the midline of the second joint connection can be determined. The direction vector of the axis in the second connecting part can be used as a vector perpendicular to the camera's axis. The conclusion is:

[0103] The center coordinates of the joint can be moved by a distance h / 2 from the center coordinates of the bottom surface along the direction vector of the central axis of the second connecting part.

[0104] In one specific embodiment, step S22, which calculates the center coordinates of the joints corresponding to each of the preset identifier graphics based on the judgment result, includes:

[0105] S2241. Referring to Figure 4(d), if the centerline of the preset identifier graphic does not coincide with the centerline of the second connecting part of the joint corresponding to the preset identifier graphic, and the centerline of the second connecting part of the joint corresponding to the preset identifier graphic does not coincide with the axis of the binocular camera, then obtain the coordinate A(x) of the upper endpoint of the bottom arc segment of the second connecting part of the joint. A ,y A ,z A The coordinates B(x) of the lower endpoint of the bottom arc segment. B ,y B ,z B ), and the coordinates M(x) of the center point of the arc of the bottom arc segment. M ,y M ,z M );

[0106] S2242, Calculate the coordinates O(x) of the intersection point of the first perpendicular bisector of line segment AM and the second perpendicular bisector of line segment BM. O ,y O ,z O The line segment AM is formed by connecting the upper endpoint and the center point of the arc, and the line segment BM is formed by connecting the lower endpoint and the center point of the arc.

[0107] S2243. Obtain the leftmost spatial coordinates b(x) of the preset identifier graphic. b ,y b ,z b ) and the rightmost spatial coordinates d(x) d ,y d ,z d ), calculate vector The vector The first connecting part is parallel to the central axis of the two connecting parts, and is located to the left of the second connecting part;

[0108] S2244, Based on the intersection point coordinates O(x) O ,y O ,z O ) and the vector The direction vector of the central axis of the second connecting part is obtained and converted into a straight line expression for the central axis;

[0109] S2245, and the spatial coordinates a(x) of the topmost element of the preset identifier graphic. a ,y a ,z a The lowest spatial coordinate c(x) c ,y c ,z c The leftmost spatial coordinate b(x) b ,y b ,z b ) and the rightmost spatial coordinate d(x) d ,y d ,z d The center of the circle passing through the preset marker graphic is calculated and perpendicular to it. and The normal vector of the determined plane, where And the normal vector is converted into a normal line expression;

[0110] S2246. Based on the expression of the central axis line and the expression of the normal line, calculate the coordinates of the intersection point of the central axis and the normal line. The coordinates of the intersection point are the center coordinates of the joint corresponding to the preset identification graphic.

[0111] Specifically, in this embodiment, the position information of the cylindrical bottom surface is first obtained through a binocular camera, and the coordinates A(x) of the upper endpoint of the arc are selected. A ,y A ,z A The coordinates of the lower endpoint B(x) B ,y B ,z B ), and the coordinates M(x) of the center point of the arc of the bottom arc segment. M ,y M ,z M Since the three points are not on the same straight line, the center O(x) of the circle is determined by using the three points in space to define the circle. O ,y O ,z O Secondly, the location information of the marker points is obtained through a stereo camera, and the vector is calculated. Thus, the direction vector of the second connection of the joint is obtained. Finally, to distinguish the relationship between the center of the circle and the line point, the coordinates of the center of the circle are specialized to O(x0,y0,z0), and the expression of the central axis of the second connection part of the joint is obtained by describing the spatial line in a point-direction manner:

[0112] To facilitate calculation and solution, a parameter ε is introduced, transforming the representation of the straight line into:

[0113] Then, by detecting the position of the marker points using binocular vision, the spatial coordinates a(x) of the four points are obtained. a ,y a ,z a b(x) b ,y b ,z b ), c(x) c ,y c ,z c ) and d(x d ,y d ,z d Then, the center coordinates of the marker point are obtained. To distinguish the relationship between the center point and the line points, the center point coordinates are specialized into O1(x). 01 ,y 01 ,z 01 Secondly, the direction vector is calculated using this spatial coordinate information. and direction vector Cross product yields normal vector Finally, the expression for the line containing the normal of the marker point is obtained by describing the spatial line using the point-direction method:

[0114] Similarly, by introducing a parameter η, the expression for a straight line is transformed into:

[0115] Solve the parametric equations of the two lines simultaneously, and the intersection of the two lines is the point we are looking for, which is the spatial coordinate of the center point of the second connection of the joint.

[0116] In a specific embodiment, referring to FIG5, step S2, which calculates the center coordinates of each joint based on the first image and the second image respectively, includes:

[0117] S23. Perform image preprocessing on the first image and the second image to obtain a grayscale image;

[0118] S24. Extract the edges of each joint from the grayscale image;

[0119] S25. Draw the circumscribed rectangle that is circumscribed to the edge of the joint;

[0120] S26. Calculate the centroid coordinates of the circumscribed rectangle and use the centroid coordinates as the center coordinates of the joint.

[0121] Specifically, step S23 described above can reduce noise and unnecessary details in the image while enhancing the features of the joint region to facilitate subsequent edge detection and shape analysis. The preprocessing steps include image grayscale conversion, image filtering, Gaussian blurring, image denoising, corner detection, and edge detection.

[0122] In step S24 above, the edges of the joints are extracted from the preprocessed grayscale image. Edges are the areas in an image where brightness changes most drastically, typically corresponding to the contours of an object. Commonly used edge detection algorithms include the Canny edge detector, the Sobel operator, and the Prewitt operator. These algorithms can identify areas in the image with significant brightness changes, i.e., the edges of the joints. To remove some unnecessary edges (such as edges caused by noise), the edge detection results can be thresholded, retaining only those edges whose intensity exceeds a certain threshold.

[0123] In step S25 above, the circumscribed rectangle is preferably the minimum circumscribed rectangle. For example, the method for drawing the minimum circumscribed rectangle includes the following steps: First, use the algorithm for a simple polygonal circumscribed rectangle. A simple circumscribed rectangle is a circumscribed rectangle whose sides are parallel to the x-axis or y-axis. Extract the maximum value x of the edge coordinate points in the x-axis and y-axis directions. max y max and minimum value x min y min A simple bounding rectangle may not be the minimum bounding rectangle, but it is a very easy bounding rectangle to find, which lays the groundwork for subsequent steps. Based on the symmetry and geometric principles of solids of revolution, the coordinates of each pixel in the rotated image are calculated. The length of the bounding rectangle is L = x.max -x min Width W = y max -y min Area S = L × W, rotation angle θ = 0°, current minimum area S min =S. The second step is to rotate the target joint's contour clockwise by a small angle Δθ, then the current angle θ = Δθ. Find the simple bounding rectangle after each degree of rotation, and record the coordinates of the points on the simple bounding rectangle and the degree of rotation at that point. If the current area is less than the initial S... min Then let the current area be the new minimum area S. min Conversely, maintain S. min The value remains unchanged. Third step: Repeat step two until θ > 90°. The minimum area at this point is the area S of the minimum circumscribed rectangle. min This allows you to obtain the vertex coordinates and rotation angle of the simple bounding rectangle.

[0124] In step S26 above, after obtaining the pixel coordinates of the four corner points of the minimum bounding rectangle of the target joint, its centroid coordinates can be obtained.

[0125] In one specific embodiment, step S3, which determines the configuration of the coaxial cable-driven robotic arm based on the center coordinates of each of the joints, further includes:

[0126] S31. Determine the spatial pose of each joint based on the center coordinates of each joint and the central axis of the second connecting part of each joint.

[0127] The center coordinates of each joint and the central axis information of the second connection of each joint are calculated using the method described in the foregoing embodiments. Since the shape of the second connection of the coaxial cable-driven robotic arm joint is approximately a spatial cylinder, a cylinder is used for geometric calculations to simplify the spatial shape of the joint in order to facilitate the solution of the joint's pose in space. The central axis of the joint is simplified to the central axis of the spatial cylinder of the second connection.

[0128] Determining the spatial pose of a joint can be exemplified by the following calculation method: A local coordinate system is established for each joint, for example, with the joint's center as the origin and the direction of the central axis as the positive direction of a certain coordinate axis (such as the Z-axis). The directions of other coordinate axes (such as the X-axis and Y-axis) are determined based on design or actual measurements. Using the joint's center coordinates and the local coordinate system, a transformation matrix from the global coordinate system to each joint's local coordinate system can be calculated. This transformation matrix includes two parts: translation (given by the center coordinates) and rotation (determined by the direction of the central axis and other coordinate axes). Through the transformation matrix, points or vectors in each joint's local coordinate system can be transformed to the global coordinate system, thereby determining the accurate position and orientation of each joint in three-dimensional space, i.e., its spatial pose.

[0129] For example, the expression for the central axis of the second connecting spatial cylinder can also be obtained using the following method:

[0130] Where q0(x0,y0,z0) is a known point on the central axis of the cylinder. The geometric relationship of the central axis in space is shown in Figure 6.

[0131] The unit vector along the central axis is:

[0132] Where α is the angle between the projection l' of the central axis l onto the plane XOY and the X-axis.

[0133] β is the angle between the central axis l and the plane XOY.

[0134] Suppose there is an unknown point p(x,y,z) on the cylinder, such that pm⊥l, as shown in Figure 7.

[0135] Therefore, the distance from the unknown point p(x,y,z) to the central axis of the cylinder is: d p-l =r = pq sin(θ);

[0136] Where θ is the angle between pq0 and the central axis l.

[0137] From the Euclidean distance formula and the principle of linear symmetry equations, we can obtain:

[0138] The direction vector of line segment pq0 is:

[0139] In the constructed triangle, use the law of cosines to solve for the included angle θ:

[0140] The following can be obtained from the geometric relationships within the constructed triangle:

[0141] The distance to pm can be obtained from the Euclidean distance formula:

[0142] Based on geometric relationships, we can obtain the following from the constructed triangle:

[0143] Two different expressions for cosθ were obtained using the two different methods described above. Combining these expressions, we get:

[0144] The equation of the cylinder is obtained by simplifying and solving:

[0145] From the unit vector of the central axis, we can know l 2 +m 2+n 2 =1, therefore, simplifying, we get:

[0146] In one specific embodiment, after step S31 of determining the spatial pose of each joint based on the center coordinates of each joint and the central axis of the second connecting portion of each joint, the method further includes:

[0147] S32. Based on the spatial pose of each joint, present the configuration of the coaxial cable-driven robotic arm in a three-dimensional diagram.

[0148] In this embodiment, a 3D model of the coaxial cable-driven robotic arm can be created using 3D modeling software or graphics libraries (such as OpenGL, DirectX, Unity 3D, etc.).

[0149] The spatial pose of each joint calculated in step S31 is applied to the corresponding three-dimensional coordinates in the three-dimensional model, thereby presenting the configuration of the coaxial cable-driven robotic arm in a three-dimensional diagram. The adjusted robotic arm model can also be further rendered and displayed in a three-dimensional graphics environment.

[0150] Specifically, the solution method for 3D coordinates is as follows, and the matrix transformation required to convert the pixel coordinates of a point into world coordinates is as follows.

[0151] The formula can be transformed into its general form as follows:

[0152] For a specific spatial point P, the image plane points p1 and p2 obtained by the left and right cameras are the same corresponding points of that specific point P. Their correspondence follows the formula above, namely:

[0153] Where (U1,V1,1) and (U2,V2,1) are the homogeneous coordinates of points p1 and p2 in their respective camera images, respectively, in the image coordinate system of their respective camera images. W ,Y W Z W ,1) are the homogeneous coordinates of point P in the world coordinate system.

[0154] Eliminating Z from both expressions c1 and Z c2 Two sets of equations were then obtained regarding the unknowns:

[0155] The problem of solving for this unknown is an overdetermined problem, where there is no solution for Ax = b, thus requiring a least squares problem. However, for this matrix, it is difficult to find its inverse matrix. Therefore, we use singular value decomposition (SVD) to turn to a least squares problem at the solution space points.

[0156] According to this method, the matrix needs to be decomposed, that is, the target matrix needs to be decomposed into: A = UΣV T ;

[0157] Where U is a 3×3 matrix, Σ is a 3×4 singular value matrix, and V is a 4×4 matrix.

[0158] For this decomposition matrix, every element on the main diagonal of the singular value matrix Σ is a singular value and is 0 except for the elements on the diagonal. Matrix U and matrix V are both unitary matrices.

[0159] For the target matrix A, a square matrix A needs to be constructed. T A is then subjected to eigenvalue decomposition. The resulting eigenvalues ​​λ are... i With each feature vector v i For: (A) T A)v i =λ i v i ;

[0160] All feature vectors v i Forming a square matrix, we get the matrix V, which is the result of the objective matrix decomposition, containing each eigenvector v. i Let be the right singular vector of the target matrix A.

[0161] Similarly, for the target matrix A, a square matrix AA also needs to be constructed. T Therefore, eigenvalues ​​are decomposed into their eigenvalues. The resulting eigenvalues ​​λ... i With each feature vector u i For: (AA) T )u i =λ i u i ;

[0162] All feature vectors u i Forming a square matrix, we get the matrix U of the target matrix decomposition, which contains each eigenvector u. i Let be the left singular vector of the target matrix A.

[0163] Combining the above three formulas, we get:

[0164] Each singular value σ i They all form the diagonal elements of the singular value matrix Σ.

[0165] The singular value matrix Σ is a diagonal matrix, and the elements of its generalized inverse matrix Σ+ are the reciprocals of matrix Σ. Based on the results of singular value decomposition, the generalized inverse matrix A of the target matrix A can be easily calculated. + That is: A + =(UΣVT ) + =(ΣV T ) + U -1 =VΣ + U T ;

[0166] The generalized inverse matrix A of the target matrix A is obtained by singular value decomposition (SVD). + For a point P in space, the two straight lines originating from the left and right cameras passing through p1 and p2 must intersect at a point in space, and this intersection is unique. Therefore, the three-dimensional coordinates of the point in space are obtained by solving the least squares problem.

[0167] Referring to Figure 8, an embodiment of the present invention also provides a coaxial cable-driven robotic arm configuration detection device based on binocular vision. The coaxial cable-driven robotic arm includes multiple joints, and the device includes:

[0168] Module 10 acquires the first and second images of the coaxial cable-driven robotic arm captured by a binocular camera.

[0169] The center coordinate calculation module 20 is used to calculate the center coordinates of each joint based on the first image and the second image, respectively.

[0170] Configuration determination module 30 is used to determine the configuration of the coaxial cable-driven robotic arm based on the center coordinates of each joint.

[0171] In this embodiment, the specific implementation of each module in the above device embodiment is described in the above method embodiment, and will not be repeated here.

[0172] An embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method. It is understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0173] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the present invention and embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM, etc.

[0174] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0175] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for detecting a coaxial rope-driven manipulator configuration based on binocular vision, characterized in that, The coaxial rope-driven mechanical arm comprises a plurality of joints, and the method comprises: acquiring a first image and a second image of the coaxial rope-driven mechanical arm taken by a binocular camera; calculating the center coordinates of each joint according to the first image and the second image, respectively; determining the configuration of the coaxial rope-driven mechanical arm according to the center coordinates of each joint.

2. The binocular vision-based configuration detection method of the coaxial rope-driven mechanical arm according to claim 1, wherein the joint comprises a first connecting part and a second connecting part connected to each other, the second connecting part comprises opposite top and bottom surfaces, the top surface is adjacent to the first connecting part of the same joint, and the bottom surface is adjacent to another joint; two adjacent joints are connected by sleeving the first connecting part of one joint into the second connecting part of another joint, and a plurality of joints are sequentially connected to form the coaxial rope-driven mechanical arm; the second connecting part is cylindrical, and a preset identification pattern is arranged on the outer surface of the second connecting part; the binocular camera is arranged at a preset distance from the side of the coaxial rope-driven mechanical arm, and the side of the coaxial rope-driven mechanical arm is the side from which the binocular camera can capture the preset identification pattern.

3. The binocular vision based in-line rope-driven manipulator configuration detection method of claim 2, wherein, the preset identification pattern is a circle, and the step of calculating the center coordinates of each joint according to the first image and the second image comprises: judging whether the axis of each preset identification pattern and the center line of the second connecting part of the joint corresponding to the preset identification pattern coincide, and whether the center line of the second connecting part of the joint corresponding to the preset identification pattern and the axis of the binocular camera coincide according to the first image and the second image, respectively; calculating the center coordinates of the joint corresponding to the preset identification pattern according to the judgment result.

4. The binocular vision based in-line rope-driven manipulator configuration detection method of claim 3, wherein, the step of calculating the center coordinates of the joint corresponding to the preset identification pattern according to the judgment result comprises: If the centerline of the preset logo coincides with the centerline of the second connecting part of the joint corresponding to the preset logo, then the spatial coordinates a(x) of the uppermost part of the preset logo are calculated based on the first image and the second image. a ,y a ,z a The lowest spatial coordinate c(x) c ,y c ,z c The leftmost spatial coordinate b(x) b ,y b ,z b ) and the rightmost spatial coordinate d(x) d ,y d ,z d ); by the uppermost spatial coordinates a(x a ,y a ,z a ) and the lowermost spatial coordinates c(x c ,y c ,z c ), a first identification center coordinate moving the first identification center coordinates along the normal vector direction of the preset identification pattern by a distance r to obtain the center coordinates of the joint corresponding to the preset identification pattern, wherein the direction of the normal vector is perpendicular from the center of the preset identification pattern to the central axis of the second connecting part, and r is the outer diameter of the cross section of the second connecting part; or by the leftmost spatial coordinates b(x b ,y b ,z b ) and the rightmost spatial coordinates d(x d ,y d ,z d ), the second identification center coordinates moving the second identification center coordinates along the normal vector direction of the preset identification pattern by a distance r to obtain the center coordinates of the joint corresponding to the preset identification pattern; or averaging the first and second identification center coordinates to calculate a third identification center coordinate moving the third identification center coordinates along the normal vector direction of the preset identification pattern by a distance r to obtain the center coordinates of the joint corresponding to the preset identification pattern.

5. The binocular vision based in-line rope-driven manipulator configuration detection method of claim 3, wherein, the step of calculating the center coordinates of the joint corresponding to the preset identification pattern according to the judgment result comprises: If the axis of the preset identifier graphic does not coincide with the centerline of the second connecting part of the joint corresponding to the preset identifier graphic, but the centerline of the second connecting part of the joint corresponding to the preset identifier graphic coincides with the axis of the binocular camera, then obtain the coordinate A(x) of the upper endpoint of the bottom arc segment of the second connecting part of the joint. A ,y A ,z A The coordinates of the lower endpoint B(x) B ,y B ,z B ), and the coordinates M(x) of the center point of the arc of the bottom arc segment. M ,y M ,z M ); calculating the coordinates O(x O ,y O ,z O ) of the intersection point of the first median of the line segment AM and the second median of the line segment BM, wherein the line segment AM is composed of the upper end point and the arc center point, and the line segment BM is composed of the lower end point and the arc center point; moving the intersection coordinates o(x, y, z) along the central axis of the second connecting part and in the direction from the bottom surface of the second connecting part of the same joint to the top surface of the second connecting part by a distance h / 2 to obtain the center coordinates of the joint, wherein h is the generatrix length of the second connecting part.

6. The binocular vision based in-line rope-driven manipulator configuration detection method of claim 3, wherein, The step of calculating the center coordinates of the joints corresponding to the preset identification patterns according to the judgment result comprises: If the axis of the preset identification pattern and the second connection part center line of the joint corresponding to the preset identification pattern do not coincide, and the second connection part center line of the joint corresponding to the preset identification pattern and the axis of the binocular camera also do not coincide, the coordinates A(x A ,y A ,z A ) of the upper end point of the bottom surface arc segment of the second connection part of the joint, the coordinates B(x B ,y B ,z B ) of the lower end point of the bottom surface arc segment, and the coordinates M(x M ,y M ,z M ) of the arc center point of the bottom surface arc segment are obtained. A A A B B B M M M < / s> calculating the coordinates O(x O ,y O ,z O ) of the intersection point of the first median of the line segment AM and the second median of the line segment BM, wherein the line segment AM is composed of the upper end point and the arc center point, and the line segment BM is composed of the lower end point and the arc center point; acquiring a space coordinate b(x b ,yb,z b ) of a leftmost side of the preset identification pattern and a space coordinate d(x d ,y d ,z d ) of a rightmost side of the preset identification pattern, and calculating a vector The vector The first connecting part is located to the left of the second connecting part; According to the intersection coordinates O(x O ,y O ,z O ) and the vector A direction vector of the central axis of the second connecting part is obtained and converted into a central axis straight line expression; and according to the space coordinates a(x a ,y a ,z a ) of the uppermost, c(x c ,y c ,z c ) of the lowermost, b(x b ,y b ,z b ) of the leftmost and d(x d ,y d ,z d ) of the rightmost of the preset identification pattern, the center of the circle passing through the preset identification pattern is calculated, and is perpendicular to and a normal vector of the determined plane, wherein The normal vector is converted into a normal straight line expression; According to the central axis straight line expression and the normal straight line expression, the intersection coordinates of the central axis and the normal are calculated, and the intersection coordinates are the center coordinates of the joints corresponding to the preset identification patterns.

7. The binocular vision based in-line rope-driven manipulator configuration detection method of claim 1, wherein, The step of calculating the center coordinates of the joints according to the first image and the second image comprises: Image preprocessing is performed on the first image and the second image to obtain a gray image; The edges of the joints are extracted from the gray image; An external rectangle circumscribed around the edges of the joints is drawn; The centroid coordinates of the external rectangle are calculated, and the centroid coordinates are taken as the center coordinates of the joints.

8. The binocular vision based in-line rope-driven manipulator configuration detection method of claim 1, wherein, The step of determining the configuration of the coaxial rope-driven manipulator according to the center coordinates of the joints further comprises: According to the center coordinates of the joints and the central axis of the second connecting part of each joint, the spatial pose of each joint is determined.

9. The binocular vision based in-line rope-driven manipulator configuration detection method of claim 8, wherein, The step of determining the spatial pose of each joint according to the center coordinates of the joints and the central axis of the second connecting part of each joint further comprises: According to the spatial pose of each joint, the configuration of the coaxial rope-driven manipulator is presented in a three-dimensional graph.

10. A coaxial rope-driven manipulator configuration detection device based on binocular vision, characterized in that, The coaxial rope-driven manipulator comprises a plurality of joints, and the device comprises: An acquisition module acquires a first image and a second image of a coaxial rope-driven manipulator taken by a binocular camera; A center coordinate calculation module calculates the center coordinates of the joints according to the first image and the second image; A configuration determination module determines the configuration of the coaxial rope-driven manipulator according to the center coordinates of the joints.

Images