A global visualization method for detecting the working state of a combination detector on the moon surface

Abstract

The application relates to a global visualization method for detecting the lunar surface working state of a combination body probe, belonging to the field of space technology. According to the data of the motion range of a mechanical arm, the field of view of a camera, the size of the probe and the like, the global visualization accessibility is analyzed and judged, and the virtual imaging points for acquiring the global image are calculated and selected; in combination with the camera configuration of the combination body probe, the visualization path is designed, and according to the three-dimensional relationship between the global image image points and the local image image points in the three-dimensional coordinate system at the virtual imaging points, the mapping relationship between the global image image points and the local image is calculated; the local imaging of the probe is carried out according to the planned shooting position and shooting posture of the camera carried by the combination body probe, the mapping relationship between the global image image points and the local image is utilized, the local image image points matched with the global image image points are searched, and the complete combination body global image with rich details is spliced.

Description

Technical Field

[0001] This invention relates to a global visualization method for the operational status of a combined lunar probe, belonging to the field of space technology. Background Technology

[0002] When spacecraft operate on the lunar surface, they need to verify the status of their equipment. This can be done by monitoring changes in voltage, current, and temperature of relevant equipment and comparing these changes with expected results to determine if they are functioning correctly. However, combined spacecraft operating on the lunar surface face challenges such as a complex working environment, numerous onboard moving mechanisms, and multiple constraints on those mechanisms. Traditional telemetry methods are increasingly revealing their limitations, such as limited information acquisition and inability to directly reflect the spacecraft's status, making them less and less able to meet the requirements of space missions.

[0003] Visualization technology, by imaging equipment, enables ground personnel to assess equipment status and provide mission support through visual representations. Besides providing crucial support for command execution effectiveness evaluation, spacecraft health monitoring, and fault diagnosis and troubleshooting, the acquired images can also be used for mission visualization and planning. Therefore, this technology is increasingly being applied in space missions. my country's Chang'e series probes, Shenzhou spacecraft, the US Curiosity rover, and the European Space Agency's Sentinel series satellites have all successfully utilized this technology in orbit, achieving excellent results.

[0004] However, current visualization methods are mostly localized. For global visualization of large spacecraft, the methods and means of information acquisition are limited, and each method has its own limitations. Considering the structural layout and mission characteristics of the combined spacecraft, the main current global visualization telemetry methods and their existing problems are as follows:

[0005] (1) Due to limited resources, it is difficult to take photos from a third-party perspective. For deep space exploration missions, the weight and volume of spacecraft are very precious resources. Unless necessary, they will not carry other independent spacecraft such as rovers. Therefore, it is difficult to establish a third-party perspective to visualize the spacecraft globally.

[0006] (2) If a third-party spacecraft is deployed, it will be unable to capture details due to the large distance between the third-party spacecraft and the combined object; the imaging angle of the third-party spacecraft will be limited, and it will be unable to acquire certain surface information of the combined object. The combined object detector is characterized by its large size, numerous surface devices, and multiple motion mechanisms. To acquire more information, the third-party spacecraft needs to be sufficiently far from the combined object, which will result in the loss of many details and make it difficult to reflect the state of the combined object; due to limitations of terrain, lighting conditions, shooting time, and the height of the third-party spacecraft, the third-party imaging can only take pictures within a certain angle range, which will make it difficult to acquire complete global information of the combined object;

[0007] (3) Acquiring local images through its own camera has problems such as difficulty in showing the overall complex state and insufficient utilization of local image information. Due to the complexity of the combined spacecraft, there are many states that need to be confirmed and the range is large. Therefore, local images are insufficient to reflect the complex state and there are problems such as insufficient utilization of local visualization information. Summary of the Invention

[0008] The technical problem solved by this invention is to overcome the shortcomings of existing technologies and provide a global visualization method for the operational status of a combined lunar probe.

[0009] The technical solution of this invention is: a method for global visualization of the lunar surface operational status of a combined probe, comprising:

[0010] Using the visualization equipment configured on the combined detector, determine the necessity of global visualization; if necessary, select virtual imaging points for the global image.

[0011] To address the need for confirming the operational status on the lunar surface, the optimal visualization path was determined by considering factors such as the imaging capabilities of the combined probe's cameras and the range of motion of the mechanisms.

[0012] Using the Pro / E model, the global image is acquired at the virtual imaging point of the global image, and all local images are acquired according to the optimal visualization path. A coordinate system is established at the virtual imaging point of the global image, and the mapping relationship between the global image image point and the local image is calculated in the coordinate system.

[0013] The on-orbit controlled robotic arm acquires all local images along the optimal visualization path, and then completes the stitching of the real global image based on the mapping relationship between the global image image points and the local images, thus realizing the global visualization of the detector.

[0014] Furthermore, the method for determining the necessity of global visualization includes:

[0015] The robotic arm is extended to its limit position and moved sequentially in the XOY, YOZ, and XOZ planes of space to image the detector.

[0016] The detector components requiring visualization are sorted by importance, and the total number is denoted as N. F ;

[0017] Based on the reachable space of the robotic arm, camera imaging capabilities, structural occlusion, and the parts that need to be visualized, the camera simulates imaging to determine whether a feature can be imaged. Then, the parts that can be captured are reordered according to their importance, and the total number is denoted as N. F′ ;

[0018] The necessity of global display is determined based on the detector parts that require visualization, the parts that can be captured, the two total numbers, and the preset necessity judgment criteria.

[0019] Furthermore, the preset necessity judgment criteria include:

[0020] Judging by the proportion of the number of display areas, if They believe that visualization is necessary;

[0021] Judging by the importance of the displayed parts, if the most important F1 can be imaged, it is considered necessary to display it globally.

[0022] Furthermore, the method for selecting virtual imaging points in the global image includes:

[0023] The virtual point coordinates are changed according to the set step size, and the global view is captured. The percentage of the number of parts that can be displayed in the view is calculated as η. When η > 80%, a suitable virtual imaging point position is found. The virtual imaging angle is selected as 90°.

[0024] Furthermore, in determining the optimal visual path, the path planning process for the four-joint robotic arm includes:

[0025] Let the rotation angle of the first joint be alpha, and the rotation angles of the second and third joints beta+gamma; perform N uniform samplings in the alpha direction and M uniform samplings in the beta direction, for a total of N*M samplings. For each sampling point:

[0026] alpha=alpha_min+i / N*(alpha_max–alpha_min)

[0027] beta=beta_min+j / M*(beta_max–beta_min)

[0028] gamma = 180

[0029] Where i = 0…N-1, j = 0…M-1; the first joint is an axial rotation; the second and third joints are the furthest reachable paths within the working plane determined by the first joint; the fourth joint has a rotation angle of 90 degrees;

[0030] Local images are acquired sequentially according to the above postures. Then, the coverage σ of all local images to the detector as a whole is calculated. If σ ≥ 0.98, downsampling is performed until σ < 0.98. The posture sequence with the fewest local images (less than 30 images) and σ > 0.98 is selected as the optimal path.

[0031] Furthermore, the formula for calculating the coverage σ of the local image to the global image is as follows:

[0032] ST pixel =S1 pixel ∪S2 pixel ∪…U Sn pixel -SR pixel

[0033]

[0034] Among them, ST pixel Sn represents the number of effective pixels in all local images. pixel SR represents the number of effective pixels in the nth local image. pixel G represents the repeated valid pixels in a local image. pixel This represents the number of pixels in the global image.

[0035] Furthermore, the method for establishing the mapping relationship between global image points and local images includes:

[0036] Establish a coordinate system ψ at the virtual image point. g ;

[0037] Using the Pro / E model, a global image is acquired at the virtual imaging point location. Based on the pinhole imaging model, the two-dimensional image point at ψ is calculated point by point. g The three-dimensional coordinates below;

[0038] Using the Pro / E model, local images are captured sequentially according to the planned visualization path, and a coordinate system ψ is established at each local imaging point. s For each local image, a pinhole imaging model is established, and the two-dimensional image points are calculated point by point in ψ. s The three-dimensional coordinates (x) below s ,y s ,z s );

[0039] Calculate ψ s To ψ g rotation matrix R s2g Translation vector t s2g The image point coordinate transformation is performed according to the following calculation formula:

[0040]

[0041] Calculate the IP of global image pixels g Euclidean distance to local image points:

[0042]

[0043] When the number of image points in the local image Ps minimizes d, then the number of image points IP in the global image... gSave the correspondence with the local image Ps; perform a traversal operation on all points in the global image to search for the correspondence with the local image.

[0044] Furthermore, the real global image stitching includes:

[0045] 1) Using the imaging equipment on the combined detector, local images are obtained sequentially according to the planned visualization path;

[0046] 2) Create a blank image I of the same size as the global image. new ;

[0047] 3) Select I new Image IP in g ′;Utilize the mapping relationship between global image points and local images to select the corresponding local image Ps';

[0048] 4) Calculate IP g The Euclidean distance d' between the image points P' and Ps' is minimized when the matching local image point IP is found. s ′, will IP s Assign the RGB value of IP' to IP' g ;

[0049] 5) to I new Repeat steps 3) and 4) for all image points to complete the image stitching.

[0050] A computer-readable storage medium storing a computer program, wherein when executed by a processor, the computer program implements the steps of a method for global visualization of the lunar surface working status of a combined probe.

[0051] A global visualization device for the lunar surface operational status of a combined probe includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the global visualization method for the lunar surface operational status of the combined probe.

[0052] The advantages of this invention compared to the prior art are:

[0053] a) Global visualization was achieved using equipment carried by the combined detector itself without increasing additional weight or volume resources;

[0054] b) This method can provide both rapid global visualization of the detector's status and the presentation of local details. Attached Figure Description

[0055] Figure 1Flowchart of a method for global visualization of the combined lunar probe's operational status on the lunar surface;

[0056] The implementation process of a global visualization method for the lunar surface operational status of the combined probe is described.

[0057] Figure 2 : Schematic diagram of virtual imaging point selection;

[0058] The calculation rules for selecting virtual imaging points are described.

[0059] Figure 3 A diagram illustrating the relationship between pixels and images;

[0060] The process of establishing a table relating pixels to an image is described.

[0061] Figure 4 A schematic diagram of stitching together an actual image based on a pixel-image relationship table;

[0062] The process of image stitching using pixel-image relationship tables and local images is described.

[0063] Figure 5 Table: Schematic diagram of the first joint of the sampling robotic arm;

[0064] The range of motion of the first joint of the sampling robotic arm is described.

[0065] Figure 6 Table: Schematic diagram of the furthest reachable path of the first and second joints of the sampling robotic arm;

[0066] The maximum reachable range of the first and second joints of the sampling robotic arm is described.

[0067] Figure 7 Table: Schematic diagram of the furthest reachable path of the second and third joints of the sampling robotic arm;

[0068] The maximum reachable range of the second and third joints of the sampling robotic arm is described. Detailed Implementation

[0069] To better understand the above technical solutions, the technical solutions of this application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of this application and the specific features in the embodiments are detailed descriptions of the technical solutions of this application, rather than limitations on the technical solutions of this application. In the absence of conflict, the embodiments of this application and the technical features in the embodiments can be combined with each other.

[0070] The following description, in conjunction with the accompanying drawings, provides a more detailed explanation of a global visualization method for the lunar surface operational status of a combined probe, as provided in this application. Specific implementation methods may include (e.g.) Figures 1-7 As shown):

[0071] (1) Global Visualization Analysis of the Detector

[0072] Based on the layout and technical status of the visualization equipment configured on the combined detector, a global accessibility analysis of the visualization equipment's field of view to the detector is performed; its ability to display local parts is analyzed to determine the necessity of global visualization; and suitable virtual imaging points for the global image are selected. Specifically, this can involve analyzing and judging the global visualization accessibility based on data such as the robotic arm's range of motion, camera field of view, and detector size.

[0073] Assuming the detector envelope size is L×W×H, camera parameters are: field of view α×β, focal length f, and the reachable space of the robotic arm. The lengths of the robotic arms are r1, r2, r3…r n .

[0074] 1) When the robotic arm is extended to its limit position, the maximum imaging distance is r1 + r2 + ... + r n-1 The coverage area of ​​a single image is approximately αβ(r1+r2+…+r n-1 ) 2 .like Figure 2 The robotic arm moves sequentially within the XOY, YOZ, and XOZ planes in space to image the detector. The movement rule is that the overlap rate of the coverage area of ​​two adjacent images is no greater than 20%. If the robotic arm can cover more than 80% of the detector area in fewer than 30 total movements, it is considered to be globally visualized.

[0075] 2) Detector components requiring visualization are sorted by importance: F1, F2, F3…F n The quantity is denoted as N. F ;

[0076] 3) Taking into account the reachable space of the robotic arm, camera imaging capabilities, structural occlusion, and the parts that need to be visualized, simulate imaging with the camera to determine whether the feature can be imaged. Then, the parts that can be captured are reordered according to their importance: F1', F2', F3'…F n The quantity is denoted as N. F′ ;

[0077] 4) Two criteria are set for determining the necessity of global display: based on the proportion of display areas, if... If visualization is deemed necessary, then it is deemed necessary to display the entire image if the most important F1 element can be imaged. The appropriate judgment criteria can be chosen based on the specific circumstances.

[0078] The selection of virtual imaging points, such as Figure 2As shown, to ensure maximum coverage of the detector area, the projection of the virtual imaging point onto the XOY plane should lie on line l (or line l'). Assuming it lies on l, the coordinates should satisfy |Ix|>|Ux|, |Iy|>|Uy|, and the height direction should satisfy |Iz|>H. The virtual point coordinates are changed by a set step size, and a global view is captured. The percentage η of the number of visible parts included in the view is calculated until η>80%, at which point a suitable virtual imaging point position is found. The virtual imaging angle is selected as 90°.

[0079] (2) Visualized path planning

[0080] To address the need for confirming the operational status on the lunar surface, the optimal visualization path was determined by considering factors such as the imaging capabilities of the combined probe's cameras and the range of motion of the mechanisms. Taking a four-jointed robotic arm as an example, the path planning process is as follows:

[0081] 1) The first joint rotates axially, which determines the working planes of the other joints, such as... Figure 5 As shown:

[0082] 2) The furthest reachable path of the second and third joints within this working plane, such as... Figure 6 As shown, this is a circular arc with radius r1+r2, where r1 is the length of the second joint and r2 is the length of the third joint.

[0083] 3) The rotation angle of the fourth joint (±180 degrees) determines the camera's shooting angle, which is fixed at 90 degrees here, so that the camera points towards the center point of the joint to shoot. Combining the rotations of the first three joints, the camera's position can be distributed on a local spherical surface (e.g., Figure 7 ).

[0084] 4) Let the rotation angle of the first joint be alpha, and the rotation angles of the second and third joints beta+gamma. Perform N uniform samplings in the alpha direction and M uniform samplings in the beta direction, for a total of N*M samplings. For each sampling point:

[0085] alpha=alpha_min+i / N*(alpha_max–alpha_min)

[0086] beta=beta_min+j / M*(beta_max–beta_min)

[0087] gamma = 180

[0088] Where i = 0…N-1, j = 0…M-1.

[0089] Local images are acquired sequentially according to the above poses. The coverage σ of all local images to the overall detector is then calculated. If σ ≥ 0.98, downsampling is performed until σ < 0.98. The pose sequence with the fewest local images (less than 30 images) and satisfying σ > 0.98 is selected as the optimal path. The formula for calculating the coverage σ of local images to the global image is as follows:

[0090] ST pixel =S1 pixel ∪S2 pixel ∪…U Sn pixel -SR pixel

[0091]

[0092] Among them, ST pixel Sn represents the number of effective pixels in all local images. pixel SR represents the number of effective pixels in the nth local image. pixel G represents the repeated valid pixels in a local image. pixel This represents the number of pixels in the global image.

[0093] (3) Establish the mapping relationship between global image points and local images.

[0094] 1) Establish a coordinate system ψ at the virtual image point. g ;

[0095] 2) Using the Pro / E model, acquire the global image at the virtual imaging point location, and calculate the two-dimensional image point at ψ point by point according to the pinhole imaging model. g The three-dimensional coordinates below;

[0096] 3) Using the Pro / E model, following the visualization path planned in (2), capture local images sequentially, and establish a coordinate system ψ at the local imaging points. s For each local image, a pinhole imaging model is established, and the two-dimensional image points are calculated point by point in ψ. s The three-dimensional coordinates (x) below s ,y s ,z s );

[0097] 4) Calculate ψ s To ψ g rotation matrix R s2g Translation vector t s2g The image point coordinate transformation is performed according to the following calculation formula:

[0098]

[0099] 5) Calculate the IP of global image pixels. gEuclidean distance to local image points:

[0100]

[0101] When the number of image points in the local image Ps minimizes d, then the number of image points IP in the global image... g The correspondence between the local image Ps and the local image Ps is saved.

[0102] 6) Perform the same steps as in step 5) on all points in the global image to search for their correspondence with the local image.

[0103] (4) Real global image stitching

[0104] 1) Using the imaging equipment on the combined detector, local images are obtained sequentially according to the planned visualization path.

[0105] 2) Create a blank image I of the same size as the global image. new ;

[0106] 3) Select I new Image IP in g Using the mapping relationship between global image points and local images obtained in step (3), select the corresponding local image Ps';

[0107] 4) Calculate IP g The Euclidean distance d' between the image points P' and Ps' is minimized when the matching local image point IP is found. s ′, will IP s Assign the RGB value of IP' to IP' g ;

[0108] 5) to I new Repeat steps 3) and 4) for all image points to complete the image stitching.

[0109] Since the matching process for each pixel is independent, this method leverages the parallel computing advantages of GPUs, migrating the matching calculation process to the GPU, thus significantly improving computational efficiency. This completes the entire process of acquiring globally visualized telemetry information about the operational status of the combined lunar probe.

[0110] In the solution provided in this application embodiment, the acquisition of global visual telemetry information on the lunar surface operational status by a certain type of probe assembly includes the following steps:

[0111] (1) Based on the mission, the following key parts need to be confirmed (arranged in descending order of priority): the deployed national flag; the alignment mechanism in its obstacle avoidance state; the ascender's main engine; the ascender's sealing device status; the ascender's solar panels; the connection position between the lander and the ascender; and the attitude control thrusters. Analysis shows that, except for the ascender's main engine, which is difficult to display in the global view due to obstruction, all other parts can be displayed.

[0112] The lander dimensions are 3039mm×3039mm×4339mm, and the maximum envelope of the antenna in the Y direction is 3400mm. Therefore, the selected virtual imaging point coordinates are (-3500mm, 3500mm, 4550mm).

[0113] (2) Using the combined Pro / E model, the visualization path was planned. It was finally determined that photos needed to be taken at 18 locations to obtain comprehensive global visualization information.

[0114] The close-up camera is located at the tail end of the sampling robotic arm, which has four joints. The pose and sequence of the image capture positions were determined through calculation, as shown in the table below:

[0115] Table 1. Visualized telemetry path planning results (robotic arm imaging angle)

[0116] 1. 0 -90 60 125 Photo 1 2. 0 -90 60 100 Photo 2 3. -40 -90 60 124 Photo 3 4. -120 -90 60 140 Photo 4 5. -150 -90 60 140 Photo 5 6. -150 -90 60 130 Photo 6 7. -175 -90 60 130 Photo 7 8. -120 -34 -60 -110 Photo 8 9. -120 -34 -60 -120 Photo 9 10 -120 -34 -60 -140 10 photos 11 -150 -34 -60 -110 Photo 11 12 -150 -34 -60 -125 Photo 12 13 -150 -34 -60 -140 Photo 13 14 -170 -34 -60 -125 Photo 14 15 -170 -34 -60 -130 15 photos 16 -175 -34 -60 -105 Photo 16 17 -175 -34 -60 -115 Photo 17 18 -175 -34 -60 -140 Photo 18

[0117] (3) Using the combined Pro / E model, a global image is obtained at the virtual imaging point; 18 local images are obtained according to the path determined in (2); and the mapping relationship between the global image points and the local images is established.

[0118] Step 1: Using the combined Pro / E model, establish a coordinate system ψ at the virtual imaging point location. greal Obtain a global image and calculate the position of each pixel in ψ. greal The coordinates;

[0119] Step 2: Using the combined Pro / E model, acquire 18 local images sequentially along the planned path, and establish a coordinate system ψ at each local imaging point. sreali And solve ψ sreali To ψ greal The rotation matrix and translation vector; transform each pixel of the local image to the coordinate system ψ. greal Down.

[0120] Step 3: Select a pixel in the global image and calculate its position in ψ. greal The Euclidean distance between the local image pixel and the local image pixel is calculated, and the local image pixel with the smallest Euclidean distance is selected to establish a mapping relationship with the pixel pixel.

[0121] Step 4: Perform the operation of step 3 on all pixels in the global image and save the mapping relationship with the local image.

[0122] (4) When the Chang'e 5 lander assembly is working on the lunar surface, it uses a close-up camera to image the lander assembly from 18 positions according to the process determined in (2), and then combines the image points obtained in (3) with the mapping relationship between the local images to complete the stitching of the global image.

[0123] Step 1: Using a close-up camera installed on the sampling robotic arm, take pictures at 18 locations in sequence according to the plan in Step 2 to obtain 18 partial images;

[0124] Step 2: According to the mapping relationship between image points and local images established in (3), search in the local image corresponding to the global image image point P. When an image point is in ψ greal If the Euclidean distance between the image point P and the image point is minimized, then the local image image point Q corresponding to the image point P is found; the color information of the image point Q is assigned to P, thus obtaining the information of the global image image point P.

[0125] Step 3: Perform the above search operation on all pixels of the global image to complete the global image stitching. To improve computation speed, GPU parallel computing can be used.

[0126] This application provides a computer-readable storage medium storing computer instructions that, when executed on a computer, cause the computer to perform... Figure 1 The method described.

[0127] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0128] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0129] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0130] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0131] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0132] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

[0133] The contents not described in detail in this specification are common knowledge to those skilled in the art.

Claims

1. A method for global visualization of the lunar surface operational status of a combined probe, characterized in that... include: Using the visualization equipment configured on the combined detector, determine the necessity of global visualization; if necessary, select virtual imaging points for the global image. To address the need for confirming the operational status on the lunar surface, the optimal visualization path was determined by considering factors such as the imaging capabilities of the combined probe's cameras and the range of motion of the mechanisms. Using the Pro / E model, the global image is acquired at the virtual imaging point of the global image, and all local images are acquired according to the optimal visualization path. A coordinate system is established at the virtual imaging point of the global image, and the mapping relationship between the global image image point and the local image is calculated in the coordinate system. The on-orbit control robot arm acquires all local images along the optimal visualization path, and then completes the stitching of the real global image based on the mapping relationship between global image points and local images to achieve global visualization of the detector. The path planning process for the four-joint robotic arm, in determining the optimal visual path, includes: 1) The first joint is axially rotating, which determines the working plane of the other joints; 2) The furthest reachable path of the second and third joints in this working plane is an arc with a radius of r1+r2, where r1 is the length of the second joint and r2 is the length of the third joint; 3) The fourth joint rotates at an angle of 90 degrees, so that the camera is pointed at the center point of the joint to take pictures; combining the rotations of the first three joints, the camera positions are distributed on the local spherical surface. 4) Let the rotation angle alpha of the first joint be , and the rotation angles of the second and third joints be alpha. Perform N uniform samplings in the alpha direction. Perform M uniform samplings in the direction, for a total of N*M samplings. For each sampling point: Where i = 0…N-1, j = 0…M-1; Local images are acquired sequentially, and then the coverage of all local images to the overall detector is calculated. ,like Then downsampling is performed until... Select the fewest local images, less than 30 images, while also satisfying the following conditions: The pose sequence is used as the optimal path; the coverage of the local image to the global image. The calculation formula is as follows: in, This represents the number of effective pixels in all local images. This represents the number of valid pixels in the nth local image. Represents repeated valid pixels in a local image. This represents the number of pixels in the global image.

2. The global visualization method for the lunar surface working status of a combined probe according to claim 1, characterized in that, The methods for determining the necessity of global visualization include: The robotic arm is extended to its limit position and moved sequentially in the XOY, YOZ, and XOZ planes of space to image the detector. Detector components requiring visualization are sorted by importance, and the total number is denoted as follows: ; Based on the reachable space of the robotic arm, camera imaging capabilities, structural occlusion, and the parts that need to be visualized, simulated imaging is used to determine whether a feature can be imaged. Then, the parts that can be captured are reordered according to their importance, and the total number is denoted as [missing information]. ; The necessity of global display is determined based on the detector parts that require visualization, the parts that can be captured, the two total numbers, and the preset necessity judgment criteria.

3. The global visualization method for the lunar surface working status of a combined probe according to claim 2, characterized in that, The preset necessity judgment criteria include: Judging by the proportion of the number of display areas, if Therefore, visualization is considered necessary. Judging by the importance of the displayed area, if the most important It can be imaged, so it is considered necessary to display it globally.

4. The global visualization method for the lunar surface operating status of a combined probe according to claim 1, characterized in that, The method for selecting virtual imaging points in the global image includes: The virtual point coordinates are changed according to the set step size, and the global view is captured. The percentage of the number of parts that can be displayed in the view is calculated, η. When η > 80%, a suitable virtual imaging point position is found. The virtual imaging angle is selected as 90°.

5. The global visualization method for the lunar surface operating status of a combined probe according to claim 1, characterized in that, Methods for establishing the mapping relationship between global image points and local images include: Establish a coordinate system at the virtual image point. ; Using the Pro / E model, a global image is acquired at the virtual imaging point location. Based on the pinhole imaging model, the two-dimensional image points are calculated point by point. The three-dimensional coordinates below; Using the Pro / E model, local images are captured sequentially according to the planned visualization path, and a coordinate system is established at each local imaging point. For each local image, a pinhole imaging model is established, and the two-dimensional image points are calculated point by point. Three-dimensional coordinates ; calculate arrive rotation matrix Translation vector The image point coordinate transformation is performed according to the following calculation formula: Calculate global image points Euclidean distance to local image points: When local image Ps The image points in the image make d The minimum value is the number of global image points. With local images Ps The system corresponds and stores the correspondence; it iterates through all points in the global image to search for the correspondence with the local image.

6. The global visualization method for the lunar surface operational status of a combined probe according to claim 1, characterized in that, The real global image stitching includes: 1) Using the imaging equipment on the combined detector, local images are obtained sequentially according to the planned visualization path; 2) Create a blank image of the same size as the global image. ; 3) Select Image points in By utilizing the mapping relationship between global image points and local images, the corresponding local image is selected. Ps' ; 4) Calculation and Ps' Euclidean distance between points ,when The smallest value will find the matching local image point. ,Will Assign RGB values ​​to ; 5) To Repeat steps 3) and 4) for all image points to complete the image stitching.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 6.

8. A global visualization device for the lunar surface operational status of a combined probe, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 6.

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