High-throughput double-arm internet-of-things cooperation method and system

Abstract

The invention discloses a high-throughput double-arm internet-of-things cooperation method and system. The method comprises the steps that a motion path of a main mechanical arm and a motion path of a cooperative mechanical arm are constructed respectively; a bounding box model of the main mechanical arm and a bounding box model of the cooperative mechanical arm are constructed, and the bounding box models corresponding to the main mechanical arm and the cooperative mechanical arm on the motion path are projected on the three main planes and then are projected on the three main coordinate axes; whether the main mechanical arm and the cooperative mechanical arm can collide or not is judged; in response to collision between the main mechanical arm and the cooperative mechanical arm, delay operation time of the cooperative mechanical arm is obtained, and after the main mechanical arm operates the delay operation time of the cooperative mechanical arm, the cooperative mechanical arm starts to operate; and in response to the situation that the main mechanical arm and the cooperative mechanical arm do not collide, the main mechanical arm and the cooperative mechanical arm start to operate at the same time. By means of the scheme, collision between the main mechanical arm and the cooperative mechanical arm can be effectively avoided, and the cooperative working efficiency between the main mechanical arm and the cooperative mechanical arm is maximized.

Description

Technical Field

[0001] This application generally relates to the technical field of robotic arm anti-collision. More specifically, this application relates to a high-throughput dual-arm Internet of Things collaboration method and system. Background Art

[0002] In intelligent laboratories and some other automated water sample detection devices, water samples are placed in reagent bottles on a detection platform. A robotic arm grips the reagent bottle and places it in the detection area for testing. After the test is completed, the robotic arm is used to move the reagent bottle to the empty bottle area for storage. In the case where the detection platform has a large area and there are a large number of reagent bottles on the detection platform, multiple robotic arms need to cooperate jointly. For the scenario of multiple robotic arms cooperating jointly, anti-collision technology needs to be adopted to achieve better cooperation among multiple robotic arms.

[0003] In the prior art, the commonly used anti-collision technology can only generate obstacle avoidance paths for stationary obstacles, and the generated trajectories will cause serious jitter during the operation of the robotic arm. However, in the actual application process, in the scenario of dual robotic arms working together, an obstacle for one robotic arm is the other robotic arm, and the other robotic arm is in a continuous movement process. Therefore, it is impossible to achieve better cooperation among multiple other robotic arms.

[0004] In view of this, there is an urgent need to provide a dual-arm Internet of Things collaboration solution that can prevent collisions between dual robotic arms and achieve high-efficiency collaborative operation between dual robotic arms. Summary of the Invention

[0005] In order to solve at least one or more of the above-mentioned technical problems, this application proposes a fault-tolerant operation solution for an inertia flywheel system in multiple aspects.

[0006] In the first aspect, this application provides a high-throughput dual-arm Internet of Things collaboration method, including: respectively constructing a motion path of a main robotic arm and a motion path of a collaborative robotic arm based on all reagent bottles to be gripped; constructing a bounding box model of the main robotic arm and a bounding box model of the collaborative robotic arm, and projecting the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path onto three main planes, and then projecting them onto three main coordinate axes; judging whether the main robotic arm and the collaborative robotic arm will collide based on the projections of the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path; in response to the main robotic arm and the collaborative robotic arm being likely to collide, obtaining the delay running time of the collaborative robotic arm, and after the main robotic arm runs for the delay running time of the collaborative robotic arm, the collaborative robotic arm starts to run; in response to the main robotic arm and the collaborative robotic arm not being likely to collide, the main robotic arm and the collaborative robotic arm start to run simultaneously.

[0007] In some embodiments, in the process of projecting the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path onto three main planes and then onto three main coordinate axes, the following steps are executed: Obtain the common space of the main robotic arm and the collaborative robotic arm on the motion path; Map the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm in the common space on the motion path to each plane in the Cartesian coordinate system to obtain the two-dimensional projection diagrams corresponding to the bounding box model of the main robotic arm and the two-dimensional projection diagrams corresponding to the bounding box model of the collaborative robotic arm; Map the two-dimensional projection diagrams corresponding to the bounding box model of the main robotic arm and the two-dimensional projection diagrams corresponding to the bounding box model of the collaborative robotic arm to each coordinate axis in the Cartesian coordinate system to obtain the projections of the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path on each coordinate axis.

[0008] In some embodiments, in the process of determining whether the main robotic arm and the collaborative robotic arm will collide, the following steps are executed: Judge whether the main robotic arm and the collaborative robotic arm have a collision risk based on the projections of the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path; In response to the main robotic arm and the collaborative robotic arm not having a collision risk, judge that the main robotic arm and the collaborative robotic arm will not collide; In response to the main robotic arm and the collaborative robotic arm having a collision risk, perform an intersection test on the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path, and judge whether the main robotic arm and the collaborative robotic arm will collide based on the intersection test result.

[0009] In some embodiments, when there are no overlapping points between the projections respectively corresponding to all the bounding box models corresponding to the main robotic arm on the motion path and all the bounding box models corresponding to the collaborative robotic arm on the motion path on any coordinate axis, it is judged that the main robotic arm and the collaborative robotic arm do not have a collision risk.

[0010] In some embodiments, the bounding box model includes a sphere model and a capsule model.

[0011] In some embodiments, during the intersection test of the sphere model of the main robotic arm and the sphere model of the collaborative robotic arm, the following steps are performed: When the distance between the projections of the centers of the sphere models of the main robotic arm and the collaborative robotic arm on the corresponding coordinate axes is greater than the sum of the radii of the sphere models of the main robotic arm and the collaborative robotic arm, it is determined that the main robotic arm and the collaborative robotic arm will not collide; When the distance between the projections of the centers of the sphere models of the main robotic arm and the collaborative robotic arm on the corresponding coordinate axes is less than the sum of the radii of the sphere models of the main robotic arm and the collaborative robotic arm, it is determined whether the distance between the projections of the centers of the sphere models of the main robotic arm and the collaborative robotic arm on the other coordinate axes is less than the sum of the radii of the sphere models of the main robotic arm and the collaborative robotic arm; In response to the distance between the projections of the centers of the sphere models of the main robotic arm and the collaborative robotic arm on the other coordinate axes being less than the sum of the radii of the sphere models of the main robotic arm and the collaborative robotic arm, it is determined that the main robotic arm and the collaborative robotic arm will collide; In response to the distance between the projections of the centers of the sphere models of the main robotic arm and the collaborative robotic arm on any one of the other coordinate axes being not less than the sum of the radii of the sphere models of the main robotic arm and the collaborative robotic arm, it is determined that the main robotic arm and the collaborative robotic arm will not collide.

[0012] In some embodiments, during the intersection test of the sphere model of the master manipulator and the capsule model of the collaborative manipulator, or during the intersection test of the capsule model of the master manipulator and the sphere model of the collaborative manipulator, the following steps are performed: when the distance between the projection of the center of the sphere model of the master manipulator on the corresponding coordinate axis and the center of any end sphere of the capsule model of the collaborative manipulator or the projection of the center of any end sphere of the capsule model of the master manipulator on the corresponding coordinate axis and the center of the sphere model of the collaborative manipulator is greater than the sum of the radius of the sphere model and the radius of the end sphere of the capsule model, it is determined that the master manipulator and the collaborative manipulator will not collide; when the distance between the projection of the center of the end sphere of the capsule model on the corresponding coordinate axis and the center of the sphere model on the corresponding coordinate axis is less than the sum of the radius of the sphere model and the radius of the end sphere of the capsule model, it is determined whether the distance between the projection of the center of the corresponding end sphere of the capsule model on the other coordinate axes and the center of the sphere model on the other coordinate axes is less than the sum of the radius of the sphere model and the radius of the corresponding end sphere of the capsule model; in response to the distance between the projection of the center of the corresponding end sphere of the capsule model on the other coordinate axes and the center of the sphere model on the other coordinate axes being less than the sum of the radius of the sphere model and the radius of the end sphere of the capsule model, it is determined that the master manipulator and the collaborative manipulator will collide; in response to the distance between the projection of the center of the corresponding end sphere of the capsule model on any other coordinate axis and the center of the sphere model on the other coordinate axis being not less than the sum of the radius of the sphere model and the radius of the end sphere of the capsule model, it is determined that the master manipulator and the collaborative manipulator will not collide.

[0013] In some embodiments, during the intersection test of the capsule model of the main robotic arm and the capsule model of the collaborative robotic arm, the following steps are performed: When the distance between the projections of the centers of the two end spheres of the capsule model of the main robotic arm and the capsule model of the collaborative robotic arm on the corresponding coordinate axes is greater than the sum of the radii of the end spheres of the capsule model of the main robotic arm and the end spheres of the capsule model of the collaborative robotic arm, it is determined that the main robotic arm and the collaborative robotic arm will not collide; When the distance between the projections of the centers of the two end spheres of the capsule model of the main robotic arm and the capsule model of the collaborative robotic arm on the corresponding coordinate axes is less than the sum of the radii of the end spheres of the capsule model of the main robotic arm and the end spheres of the capsule model of the collaborative robotic arm, it is determined whether the distance between the projections of the centers of the two end spheres of the capsule model of the main robotic arm and the capsule model of the collaborative robotic arm on the other coordinate axes is less than the sum of the radii of the end spheres of the capsule model of the main robotic arm and the end spheres of the capsule model of the collaborative robotic arm; In response to the distance between the projections of the centers of the two end spheres of the capsule model of the main robotic arm and the capsule model of the collaborative robotic arm on the other coordinate axes being less than the sum of the radii of the end spheres of the capsule model of the main robotic arm and the end spheres of the capsule model of the collaborative robotic arm, it is determined that the main robotic arm and the collaborative robotic arm will collide; In response to the distance between the projections of the centers of the two end spheres of the capsule model of the main robotic arm and the capsule model of the collaborative robotic arm on any other coordinate axis being not less than the sum of the radii of the end spheres of the capsule model of the main robotic arm and the end spheres of the capsule model of the collaborative robotic arm, it is determined that the main robotic arm and the collaborative robotic arm will not collide.

[0014] In some embodiments, during the process of obtaining the delayed running time of the collaborative robotic arm, the following steps are performed: Taking the first preset time as the current delayed running time, and determining whether the main robotic arm and the collaborative robotic arm will collide at the current delayed running time; In response to the main robotic arm and the collaborative robotic arm not colliding at the current delayed running time, taking the current delayed running time as the delayed running time of the collaborative robotic arm; In response to the main robotic arm and the collaborative robotic arm colliding, adding the second preset time to the current delayed running time until the main robotic arm and the collaborative robotic arm do not collide.

[0015] In some embodiments, the second preset time is greater than the time required to determine whether the main robotic arm and the collaborative robotic arm will collide.

[0016] In a second aspect, the present application provides a high-throughput dual-arm IoT collaboration system, which performs dual-arm IoT collaboration using the high-throughput dual-arm IoT collaboration method described in any embodiment of the first aspect. The system includes: a motion path acquisition module for respectively constructing the motion path of the main robotic arm and the motion path of the collaborative robotic arm based on all reagent bottles to be clamped; a bounding box model acquisition module for constructing the bounding box model of the main robotic arm and the bounding box model of the collaborative robotic arm, and projecting the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path onto three main planes, and then projecting them onto three main coordinate axes; a collision determination module for determining whether the main robotic arm and the collaborative robotic arm will collide based on the projections of the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path; an operation module for, in response to the main robotic arm and the collaborative robotic arm being likely to collide, obtaining the delayed operation time of the collaborative robotic arm, and after the main robotic arm operates for the delayed operation time of the collaborative robotic arm, the collaborative robotic arm starts to operate; in response to the main robotic arm and the collaborative robotic arm not being likely to collide, the main robotic arm and the collaborative robotic arm start to operate simultaneously.

[0017] Through the dual-arm IoT collaboration solution provided above, in the embodiments of the present application, it is determined whether the main robotic arm and the collaborative robotic arm will collide based on the projections of the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path. In response to the main robotic arm and the collaborative robotic arm being likely to collide, the delayed operation time of the collaborative robotic arm is obtained, and after the main robotic arm operates for the delayed operation time of the collaborative robotic arm, the collaborative robotic arm starts to operate, which can effectively avoid collisions between the main robotic arm and the collaborative robotic arm, and maximize the collaborative work efficiency between the main robotic arm and the collaborative robotic arm on the premise of ensuring no collisions. At the same time, by adjusting the starting timing of the collaborative robotic arm to solve the problem, this not only helps to keep the original path design unchanged, but also simplifies the need to re-plan a new path, thereby improving the flexibility of the entire system. In addition, by setting an appropriate delayed operation time for the collaborative robotic arm, the downtime caused by unexpected situations can be reduced without affecting the overall operation progress, ensuring the collaborative safety and accuracy between the main robotic arm and the collaborative robotic arm. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features, and advantages of the exemplary embodiments of the present application will become readily understood. In the drawings, several embodiments of the present application are shown in an exemplary rather than restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0019] Figure 1 An exemplary flowchart of the high-throughput dual-arm IoT collaboration method according to the embodiment of the present application is shown;

[0020] Figure 2 An exemplary flowchart showing the bounding box models corresponding to the main robotic arm and the collaborative robotic arm projected onto three main planes and then onto three main coordinate axes in the embodiments of the present application;

[0021] Figure 3 An exemplary flowchart showing the determination of whether the main robotic arm and the collaborative robotic arm will collide in the embodiments of the present application;

[0022] Figure 4 An exemplary flowchart showing the intersection test of the sphere model of the main robotic arm and the sphere model of the collaborative robotic arm in the embodiments of the present application;

[0023] Figure 5 An exemplary flowchart showing the intersection test of the sphere model and the capsule model in the embodiments of the present application;

[0024] Figure 6 An exemplary flowchart showing the intersection test of the capsule model of the main robotic arm and the capsule model of the collaborative robotic arm in the embodiments of the present application;

[0025] Figure 7 An exemplary flowchart showing the acquisition of the delayed operation time of the collaborative robotic arm in the embodiments of the present application;

[0026] Figure 8 A schematic diagram showing the composition of the high-throughput dual-arm Internet of Things collaborative system in the embodiments of the present application. Detailed implementation manners

[0027] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present application.

[0028] It should be understood that the terms "including" and "comprising" used in the specification and claims of the present application indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0029] It should also be understood that the terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. As used in the specification and claims of this application, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms. It should also be further understood that the term "and / or" used in the specification and claims of this application refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0030] As used in this specification and the claims, the term "if" may be interpreted as "when" or "once" or "in response to determining" or "in response to detecting" depending on the context. Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be interpreted as meaning "once determined" or "in response to determining" or "once [the described condition or event] is detected" or "in response to detecting [the described condition or event]" depending on the context.

[0031] The specific embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0032] Figure 1 An exemplary flowchart of the high-throughput dual-arm IoT collaboration method 100 according to an embodiment of this application is shown

[0033] As Figure 1 shown, in step S110, the movement paths of the main robotic arm and the collaborative robotic arm are respectively constructed based on all reagent bottles to be clamped.

[0034] In the embodiments of this application, in order to improve the working efficiency and capacity of the automated water sample detection device, a high-throughput detection module with IoT collaboration is provided. This module can be directly externally connected beside the existing automated water sample detection device. It not only provides additional large-scale reagent bottle storage space, but also is equipped with a set of specially designed main robotic arm and collaborative robotic arm to assist the operation of the automated water sample detection device. Through the communication network established by the Internet of Things (IoT) technology, this module ensures seamless docking and efficient collaboration between the new and old devices, and can play the role of closely cooperating with the original automated water sample detection device to transfer reagent bottles.

[0035] Specifically, the high-throughput detection module includes multiple sample areas and multiple empty bottle areas. The sample areas are used for placing water sample reagent bottles, and the empty bottle areas are used for placing empty reagent bottles after detection. And the high-throughput detection module uses a six-axis robotic arm as the main robotic arm to clamp the water sample reagent bottles. To expand the working range of the six-axis robotic arm, a parallel slide rail is installed in the high-throughput module. The base of the main robotic arm is installed on the slide rail and can be translated left and right along the slide rail so that its clamping range covers the entire high-throughput module. The reagent bottle in the sample area is clamped by the main robotic arm and placed in the placement slot of the automated detection device. The robotic arm equipped with the automated detection device completes subsequent steps such as transportation, barcode scanning and recording, opening the lid, sampling, closing the lid, etc. Finally, the empty reagent bottle is transported back to the empty bottle area in the high-throughput module by the main robotic arm equipped on the high-throughput module.

[0036] Specifically, the movement path of the main robotic arm is the movement path when the main robotic arm clamps the reagent bottle in the sample area and places it in the placement slot of the automated detection device. The movement path of the collaborative robotic arm is the movement path when the collaborative robotic arm clamps the empty reagent bottle in the placement slot of the automated detection device and places it in the empty bottle area.

[0037] In the embodiment of the present application, the movement paths of the main robotic arm and the collaborative robotic arm are planned by B-spline curves. Specifically, the trend and boundary range of the B-spline curve are locally controlled by control points. Let there be P 0 , P 1 , P 2 ,..., P n A total of n + 1 control points, then the definition of the k-order B-spline curve with n + 1 control points is:

[0038] Among them, B i,k (u) is the i-th k-order B-spline basis function, corresponding to the control point P i , k ≥ 1, and u is the independent variable.

[0039] Specifically, the basis function has the following de Boor-Cox recurrence formula:

[0040]

[0041] The k-order B-spline is a curve of degree k - 1 with respect to u (that is, the degree of the basis function is k - 1). Suppose it is necessary to calculate B i,2 (u), then it is necessary to know B i,1 (u) and B i+1,1 (u). Therefore, we need to first calculate B 0,1 (u), B 1,1 (u), B 1,2 (u)……, and then correspondingly calculate B 0,2 (u), B 1,2(u), …… Then place all the calculated B i,2 (u) in the third column, and so on, place B i,3 (u) in the fourth column. Continue this process until all the required B i,k (u) are calculated.

[0042] After performing step S110, in step S120, construct the bounding box models of the main robotic arm and the collaborative robotic arm, and project the corresponding bounding box models of the main robotic arm and the collaborative robotic arm on the three main planes along the motion paths, and then project them on the three main coordinate axes.

[0043] In the embodiments of the present application, the bounding box model includes a sphere model and a capsule model. Specifically, use the capsule model to closely wrap the main robotic arm and the link of the main robotic arm, and use the sphere model to closely wrap the joints of the main robotic arm and the main robotic arm.

[0044] When each robotic arm is simplified and represented as a series of sphere models or capsule models as its bounding box, these shapes can be used for rapid collision detection. Thus, the collision detection process can be greatly simplified, saving a large amount of computing time.

[0045] In the embodiments of the present application, for the specific process of projecting the corresponding bounding box models of the main robotic arm and the collaborative robotic arm on the three main planes along the motion paths, and then projecting them on the three main coordinate axes, reference can be made to Figure 2 .

[0046] Figure 2 Shows an exemplary flowchart of projecting the corresponding bounding box models of the main robotic arm and the collaborative robotic arm on the three main planes along the motion paths, and then projecting them on the three main coordinate axes in the embodiments of the present application.

[0047] As Figure 2 shown, in step S210, obtain the common space of the main robotic arm and the collaborative robotic arm along the motion paths. In step S220, map the corresponding bounding box models of the main robotic arm and the collaborative robotic arm in the common space along the motion paths to each plane in the Cartesian coordinate system to obtain the two-dimensional projection diagrams corresponding to the bounding box model of the main robotic arm and the two-dimensional projection diagrams corresponding to the bounding box model of the collaborative robotic arm. In step S230, map the two-dimensional projection diagrams corresponding to the bounding box model of the main robotic arm and the two-dimensional projection diagrams corresponding to the bounding box model of the collaborative robotic arm to each coordinate axis in the Cartesian coordinate system to obtain the projections of the corresponding bounding box models of the main robotic arm and the collaborative robotic arm on each coordinate axis along the motion paths.

[0048] In the embodiments of the present application, various existing technologies can be adopted in the process of obtaining the common space of the master manipulator and the collaborative manipulator on the motion path, and the present application does not limit this here. For example, first, clarify the structural parameters of the master manipulator and the collaborative manipulator, including the lengths of each link, the type of joint (rotation or translation), the stroke range of the slide rail, etc. Then, according to the specific structure of the master manipulator and the collaborative manipulator, determine its state space, that is, the set of all possible joint angle configurations. For the master manipulator including a slide rail, in addition to the conventional joint angles, the position of the slide rail needs to be added as an additional state variable. Then, use the method of random sampling to generate a large number of sample points, and each sample represents a possible posture combination. For each sample point, check whether it meets the physical limitations (such as joint limits) of the master manipulator or the collaborative manipulator, and record those valid postures. For each valid posture, calculate the positions and orientations of the ends of the master manipulator and the collaborative manipulator in the Cartesian coordinate system. Collect all these positions to form a set, and obtain the reachable workspace of the master manipulator and the reachable workspace of the collaborative manipulator. Finally, take the intersection of the reachable workspace of the master manipulator and the reachable workspace of the collaborative manipulator to obtain the common space of the master manipulator and the collaborative manipulator on the motion path.

[0049] By obtaining the common space of the master manipulator and the collaborative manipulator on the motion path, when subsequently determining whether the master manipulator and the collaborative manipulator will collide, it can be determined only within the common space of the master manipulator and the collaborative manipulator on the motion path. Thus, subsequent collision detection is concentrated in the overlapping area of the motion paths of the master manipulator and the collaborative manipulator, rather than performing a full-range scan in the entire workspace. This not only reduces the unnecessary computational burden, but also can more accurately locate potential collision points, ensuring the safety and reliability of the manipulator operation.

[0050] In the embodiments of the present application, the projection of the sphere models respectively corresponding to the master manipulator and the collaborative manipulator on the motion path is a point, and the projection of the capsule models of the sphere models respectively corresponding to the master manipulator and the collaborative manipulator on the motion path is a line segment, and the two endpoints of the line segment are respectively the two ends of the capsule model.

[0051] After performing step S120, in step S130, it is determined whether the master manipulator and the collaborative manipulator will collide based on the projections of the bounding box models respectively corresponding to the master manipulator and the collaborative manipulator on the motion path.

[0052] In the embodiments of the present application, for the specific process of determining whether the master manipulator and the collaborative manipulator will collide, reference can be made to Figure 3 .

[0053] Figure 3Shows an exemplary flowchart for determining whether the main robotic arm and the collaborative robotic arm will collide according to an embodiment of the present application.

[0054] As Figure 3 shown, in step S310, it is determined whether there is a collision risk between the main robotic arm and the collaborative robotic arm based on the projections of the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path. In step S320, in response to the main robotic arm and the collaborative robotic arm not having a collision risk, it is determined that the main robotic arm and the collaborative robotic arm will not collide. In step S330, in response to the main robotic arm and the collaborative robotic arm having a collision risk, an intersection test is performed on the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path, and it is determined whether the main robotic arm and the collaborative robotic arm will collide based on the intersection test result.

[0055] In an embodiment of the present application, when there are no overlapping points between the projections respectively corresponding to all the bounding box models corresponding to the main robotic arm on the motion path and all the bounding box models corresponding to the collaborative robotic arm on the motion path on any coordinate axis, it is determined that the main robotic arm and the collaborative robotic arm do not have a collision risk. On the contrary, when there are overlapping points between the projections respectively corresponding to all the bounding box models corresponding to the main robotic arm on the motion path and all the bounding box models corresponding to the collaborative robotic arm on the motion path on a certain coordinate axis, it is determined that the main robotic arm and the collaborative robotic arm have a collision risk.

[0056] By first determining whether the main robotic arm and the collaborative robotic arm have a collision risk based on overlapping points, in response to the main robotic arm and the collaborative robotic arm not having a collision risk, it is determined that the main robotic arm and the collaborative robotic arm will not collide, and in response to the main robotic arm and the collaborative robotic arm having a collision risk, an intersection test is then performed on the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path, the collision test can be processed in layers, which not only includes quickly excluding obvious non-collision situations, but also covers detailed analysis for those with collision risks. This way of layered processing not only improves the speed and accuracy of detection, but also helps to ensure the safe operation of the main robotic arm and the collaborative robotic arm in a complex environment.

[0057] In an embodiment of the present application, during the process of performing an intersection test on the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path, an intersection test is respectively performed on the sphere model of the main robotic arm and the sphere model of the collaborative robotic arm, the sphere model of the main robotic arm and the capsule model of the collaborative robotic arm, the capsule model of the main robotic arm and the sphere model of the collaborative robotic arm, and the capsule model of the main robotic arm and the capsule model of the collaborative robotic arm.

[0058] In an embodiment of the present application, for the specific process of performing an intersection test on the sphere model of the main robotic arm and the sphere model of the collaborative robotic arm, reference can be made to Figure 4。

[0059] Figure 4 Shows an exemplary flowchart of the intersection test of the sphere model of the master manipulator and the sphere model of the collaborative manipulator in the embodiments of the present application.

[0060] As Figure 4 shown, in step S410, it is determined whether the distance between the projections of the centers of the sphere models of the master manipulator and the collaborative manipulator on the corresponding coordinate axes respectively is greater than the sum of the radii of the sphere models of the master manipulator and the collaborative manipulator. In response to the distance between the projections of the centers of the sphere models of the master manipulator and the collaborative manipulator on the corresponding coordinate axes respectively being greater than the sum of the radii of the sphere models of the master manipulator and the collaborative manipulator, in step S420, it is determined that the master manipulator and the collaborative manipulator will not collide. In response to the distance between the projections of the centers of the sphere models of the master manipulator and the collaborative manipulator on the corresponding coordinate axes respectively not being greater than the sum of the radii of the sphere models of the master manipulator and the collaborative manipulator, in step S430, it is determined whether the distance between the projections of the centers of the sphere models of the master manipulator and the collaborative manipulator on the corresponding coordinate axes respectively is less than the sum of the radii of the sphere models of the master manipulator and the collaborative manipulator.

[0061] In response to the distance between the projections of the centers of the sphere models of the manipulator and the collaborative manipulator on the corresponding coordinate axes respectively being less than the sum of the radii of the sphere models of the master manipulator and the collaborative manipulator, in step S440, it is determined whether the distance between the projections of the centers of the sphere models of the master manipulator and the collaborative manipulator on the other coordinate axes respectively is less than the sum of the radii of the sphere models of the master manipulator and the collaborative manipulator. In response to the distance between the projections of the centers of the sphere models of the master manipulator and the collaborative manipulator on the other coordinate axes respectively being less than the sum of the radii of the sphere models of the master manipulator and the collaborative manipulator, in step S450, it is determined that the master manipulator and the collaborative manipulator will collide. In response to the distance between the projections of the centers of the sphere models of the master manipulator and the collaborative manipulator on any one of the other coordinate axes respectively not being less than the sum of the radii of the sphere models of the master manipulator and the collaborative manipulator, in step S460, it is determined that the master manipulator and the collaborative manipulator will not collide.

[0062] When the distance between the projections of the center of the sphere model of the main robotic arm and the center of the sphere model of the collaborative robotic arm on the corresponding coordinate axes is greater than the sum of the radii of the sphere model of the main robotic arm and the sphere model of the collaborative robotic arm, it is determined that the main robotic arm and the collaborative robotic arm will not collide. There is no need to further determine the relationship between the distance between the projections of the center of the sphere model of the main robotic arm and the center of the sphere model of the collaborative robotic arm on other coordinate axes and the sum of the radii. Thus, unnecessary calculation steps are significantly reduced, and the effectiveness and accuracy of the detection results can be ensured.

[0063] In the embodiments of the present application, for the intersection test of the sphere model of the main robotic arm and the capsule model of the collaborative robotic arm, or for the specific process of the intersection test of the capsule model of the main robotic arm and the sphere model of the collaborative robotic arm, reference can be made to Figure 5 .

[0064] As Figure 5 shown, in step S510, it is determined whether the distance between the projection of the center of the sphere model of the main robotic arm and the center of either end sphere of the capsule model of the collaborative robotic arm or the projection of the center of either end sphere of the capsule model of the main robotic arm and the center of the sphere model of the collaborative robotic arm on the corresponding coordinate axes is greater than the sum of the radius of the sphere model and the radius of the end sphere of the capsule model. In response to the distance between the projection of the center of the sphere model of the main robotic arm and the center of either end sphere of the capsule model of the collaborative robotic arm or the projection of the center of either end sphere of the capsule model of the main robotic arm and the center of the sphere model of the collaborative robotic arm on the corresponding coordinate axes being greater than the sum of the radius of the sphere model and the radius of the end sphere of the capsule model, in step S520, it is determined that the main robotic arm and the collaborative robotic arm will not collide. In response to the distance between the projection of the center of the sphere model of the main robotic arm and the center of either end sphere of the capsule model of the collaborative robotic arm or the projection of the center of either end sphere of the capsule model of the main robotic arm and the center of the sphere model of the collaborative robotic arm on the corresponding coordinate axes not being greater than the sum of the radius of the sphere model and the radius of the end sphere of the capsule model, in step S530, it is determined whether there is a distance between the center of the end sphere of the capsule model and the projection of the center of the sphere model on the corresponding coordinate axes that is less than the sum of the radius of the sphere model and the radius of the end sphere of the capsule model.

[0065] In response to the distance between the projection of the center of the end sphere of the capsule model and the center of the sphere model on the corresponding coordinate axes being less than the sum of the radius of the sphere model and the radius of the end sphere of the capsule model, in step S540, it is determined whether the distance between the projection of the corresponding end sphere center of the capsule model and the center of the sphere model on other coordinate axes is less than the sum of the radius of the sphere model and the radius of the corresponding end sphere of the capsule model. In response to the distance between the projection of the corresponding end sphere center of the capsule model and the center of the sphere model on other coordinate axes being less than the sum of the radius of the sphere model and the radius of the end sphere of the capsule model, in step S550, it is determined that the main robotic arm and the collaborative robotic arm will collide. In response to the distance between the projection of the corresponding end sphere center of the capsule model and the center of the sphere model on any other coordinate axis being not less than the sum of the radius of the sphere model and the radius of the end sphere of the capsule model, in step S560, it is determined that the main robotic arm and the collaborative robotic arm will not collide.

[0066] When the distance between the projection of the center of the sphere model of the main robotic arm and the center of any end sphere of the capsule model of the collaborative robotic arm or the projection of the center of any end sphere of the capsule model of the main robotic arm and the center of the sphere model of the collaborative robotic arm on the corresponding coordinate axes is greater than the sum of the radius of the sphere model and the radius of the end sphere of the capsule model, it is determined that the main robotic arm and the collaborative robotic arm will not collide, and there is no need to further determine the relationship between the distance between the projection of the center of the sphere model of the main robotic arm and the center of any end sphere of the capsule model of the collaborative robotic arm or the projection of the center of any end sphere of the capsule model of the main robotic arm and the center of the sphere model of the collaborative robotic arm on other coordinate axes and the sum of the radii. Thus, significantly reducing unnecessary calculation steps and ensuring the effectiveness and accuracy of the detection results.

[0067] In the embodiments of the present application, the specific process of performing the intersection test on the capsule models of the main robotic arm and the collaborative robotic arm can refer to Figure 6 .

[0068] Figure 6 Fig. shows an exemplary flowchart of performing an intersection test on the capsule models of the main robotic arm and the collaborative robotic arm in the embodiments of the present application.

[0069] As Figure 6As shown, in step S610, it is determined whether the distance between the projections of the centers of the two end balls of the capsule model of the master manipulator and the capsule model of the slave manipulator, which are relatively close, on the corresponding coordinate axes respectively is greater than the sum of the radii of the end ball of the capsule model of the master manipulator and the end ball of the capsule model of the slave manipulator. In response to the distance between the projections of the centers of the two end balls of the capsule model of the master manipulator and the capsule model of the slave manipulator, which are relatively close, on the corresponding coordinate axes respectively being greater than the sum of the radii of the end ball of the capsule model of the master manipulator and the end ball of the capsule model of the slave manipulator, in step S620, it is determined that the master manipulator and the slave manipulator will not collide. In response to the distance between the projections of the centers of the two end balls of the capsule model of the master manipulator and the capsule model of the slave manipulator, which are relatively close, on the corresponding coordinate axes respectively not being greater than the sum of the radii of the end ball of the capsule model of the master manipulator and the end ball of the capsule model of the slave manipulator, in step S630, it is determined whether the distance between the projections of the centers of the two end balls of the capsule model of the master manipulator and the capsule model of the slave manipulator, which are relatively close, on the corresponding coordinate axes respectively is less than the sum of the radii of the end ball of the capsule model of the master manipulator and the end ball of the capsule model of the slave manipulator.

[0070] In response to the distance between the projections of the centers of the two end balls of the capsule model of the master manipulator and the capsule model of the slave manipulator, which are relatively close, on the corresponding coordinate axes respectively being less than the sum of the radii of the end ball of the capsule model of the master manipulator and the end ball of the capsule model of the slave manipulator, in step S640, it is determined whether the distance between the projections of the centers of the two end balls of the capsule model of the master manipulator and the capsule model of the slave manipulator, which are relatively close, on the other coordinate axes respectively is less than the sum of the radii of the end ball of the capsule model of the master manipulator and the end ball of the capsule model of the slave manipulator. In response to the distance between the projections of the centers of the two end balls of the capsule model of the master manipulator and the capsule model of the slave manipulator, which are relatively close, on the other coordinate axes respectively being less than the sum of the radii of the end ball of the capsule model of the master manipulator and the end ball of the capsule model of the slave manipulator, in step S650, it is determined that the master manipulator and the slave manipulator will collide. In response to the distance between the projections of the centers of the two end balls of the capsule model of the master manipulator and the capsule model of the slave manipulator, which are relatively close, on the other coordinate axes respectively not being less than the sum of the radii of the end ball of the capsule model of the master manipulator and the end ball of the capsule model of the slave manipulator, in step S660, it is determined that the master manipulator and the slave manipulator will not collide.

[0071] When the distance between the projections of the centers of the two end balls with relatively close distances between the capsule models of the robotic arm and the collaborative robotic arm on the corresponding coordinate axes is greater than the sum of the radii of the end balls of the capsule model of the main robotic arm and the capsule model of the collaborative robotic arm, it is determined that the main robotic arm and the collaborative robotic arm will not collide, and there is no need to further determine the relationship between the distance between the projections of the centers of the two end balls with relatively close distances between the capsule models of the robotic arm and the collaborative robotic arm on other coordinate axes and the sum of the radii. Thus, unnecessary calculation steps are significantly reduced, and the effectiveness and accuracy of the detection results can be ensured.

[0072] After step S130 is executed, in response to the main robotic arm and the collaborative robotic arm being likely to collide, in step S140, the delayed running time of the collaborative robotic arm is obtained. After the main robotic arm runs for the delayed running time of the collaborative robotic arm, the collaborative robotic arm starts to run.

[0073] In the embodiments of the present application, the specific process of obtaining the delayed running time of the collaborative robotic arm can refer to Figure 7 .

[0074] Figure 7 An exemplary flowchart of obtaining the delayed running time of the collaborative robotic arm in the embodiments of the present application is shown.

[0075] As Figure 7 shown, in step S710, the first preset time is used as the current delayed running time. In step S720, it is determined whether the main robotic arm and the collaborative robotic arm will collide at the current delayed running time. In response to the main robotic arm and the collaborative robotic arm not colliding at the current delayed running time, in step S730, the current delayed running time is used as the delayed running time of the collaborative robotic arm. In response to the main robotic arm and the collaborative robotic arm colliding, a new previous delayed running time is obtained by adding the second preset time to the current delayed running time, and the process returns to step S720 to determine again whether the main robotic arm and the collaborative robotic arm will collide. When it is determined again that the main robotic arm and the collaborative robotic arm do not collide, in step S730, the new current delayed running time is used as the delayed running time of the collaborative robotic arm. When it is determined again that the main robotic arm and the collaborative robotic arm collide, the second preset time is added to the new current delayed running time again, and the cycle continues until the main robotic arm and the collaborative robotic arm do not collide.

[0076] In the embodiments of the present application, the first preset time can be set according to actual needs and application scenarios, and the present application does not limit this here.

[0077] In an embodiment of the present application, the second preset time is greater than the time required to determine whether the master robotic arm and the collaborative robotic arm will collide. By making the second preset time greater than the time required to determine whether the master robotic arm and the collaborative robotic arm will collide, it is possible to avoid the problem that when the second preset time is less than or equal to the time required to determine whether the master robotic arm and the collaborative robotic arm will collide, after adding the second preset time to the current delayed running time of the master robotic arm and the collaborative robotic arm, and then determining again whether the master robotic arm and the collaborative robotic arm will collide, the second preset time has been consumed, and at this time, the master robotic arm and the collaborative robotic arm will still collide.

[0078] In an embodiment of the present application, during the process of determining whether the master robotic arm and the collaborative robotic arm will collide under the delayed running time of the collaborative robotic arm, obtain the common space of the master robotic arm and the collaborative robotic arm under the delayed running time of the collaborative robotic arm, and execute the steps involved in the aforementioned step S120 and step S130. The specific execution process can refer to the foregoing, and will not be elaborated here.

[0079] By obtaining the delayed running time of the collaborative robotic arm that enables the master robotic arm and the collaborative robotic arm not to collide, it is possible to ensure that there will be no collision between the master robotic arm and the collaborative robotic arm when the collaborative robotic arm starts running after the master robotic arm runs for the delayed running time of the collaborative robotic arm. This not only improves the safety of the working process of the master robotic arm and the collaborative robotic arm, but also optimizes the collaboration efficiency between the master robotic arm and the collaborative robotic arm.

[0080] After step S130 is executed, in response to the fact that the master robotic arm and the collaborative robotic arm will not collide, in step S150, the master robotic arm and the collaborative robotic arm start running simultaneously.

[0081] In summary, through the dual-arm IoT collaboration solution provided above, the embodiment of the present application determines whether the master robotic arm and the collaborative robotic arm will collide by projecting the bounding box models respectively corresponding to the master robotic arm and the collaborative robotic arm on the movement path. In response to the fact that the master robotic arm and the collaborative robotic arm will collide, obtain the delayed running time of the collaborative robotic arm. After the master robotic arm runs for the delayed running time of the collaborative robotic arm, the collaborative robotic arm starts running, which can effectively avoid the collision between the master robotic arm and the collaborative robotic arm, and maximize the collaborative working efficiency between the master robotic arm and the collaborative robotic arm on the premise of ensuring no collision. At the same time, by adjusting the starting timing of the collaborative robotic arm to solve the problem, this not only helps to keep the original path design unchanged, but also simplifies the need to re-plan a new path, thereby improving the flexibility of the entire system. In addition, by setting an appropriate delayed running time for the collaborative robotic arm, it is possible to reduce the downtime caused by unexpected situations without affecting the overall operation progress, and ensure the collaboration safety and accuracy between the master robotic arm and the collaborative robotic arm.

[0082] The embodiment of the present application also provides a high-throughput dual-arm Internet of Things collaboration system, which can perform dual-arm Internet of Things collaboration by using the aforementioned high-throughput dual-arm Internet of Things collaboration method 100, or can also use other methods for dual-arm Internet of Things collaboration, and the present application does not limit this here.

[0083] Figure 8 The composition schematic diagram of the high-throughput dual-arm Internet of Things collaboration system 800 according to the embodiment of the present application is shown.

[0084] As Figure 8 shown, the system 800 includes a motion path acquisition module 810, a bounding box model acquisition module 820, a collision judgment module 830, and an operation module 840.

[0085] Specifically, the motion path acquisition module 810 is used to construct the motion path of the main robotic arm and the motion path of the collaborative robotic arm respectively based on all reagent bottles to be clamped.

[0086] Specifically, the bounding box model acquisition module 820 is used to construct the bounding box model of the main robotic arm and the bounding box model of the collaborative robotic arm, and project the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path onto three main planes, and then project them onto three main coordinate axes.

[0087] Specifically, the collision judgment module 830 is used to judge whether the main robotic arm and the collaborative robotic arm will collide based on the projections of the bounding box models respectively corresponding to the main robotic arm and the collaborative robotic arm on the motion path.

[0088] Specifically, the operation module 840 is used to respond to the situation that the main robotic arm and the collaborative robotic arm will collide, obtain the delayed operation time of the collaborative robotic arm, and after the main robotic arm runs for the delayed operation time of the collaborative robotic arm, the collaborative robotic arm starts to run. In response to the situation that the main robotic arm and the collaborative robotic arm will not collide, the main robotic arm and the collaborative robotic arm start to run simultaneously.

[0089] When the system 400 performs dual-arm Internet of Things collaboration by using the aforementioned high-throughput dual-arm Internet of Things collaboration method 100, the motion path acquisition module 810 executes the aforementioned step S110, the bounding box model acquisition module 820 executes the aforementioned step S120, the collision judgment module 830 executes the aforementioned step S130, and the operation module 840 executes the aforementioned step S140 and step S150. The specific execution process can refer to the foregoing, and will not be elaborated here.

[0090] Although several embodiments of the present application have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many changes, variations, and alternative methods may occur to those skilled in the art without departing from the spirit and scope of the present application. It should be understood that various alternatives to the embodiments of the present application described herein may be employed in practicing the present application. The appended claims are intended to define the scope of the present application and thus cover equivalents or alternatives within the scope of these claims.

Claims

1. A high-throughput dual-arm IoT collaboration method, characterized in that: include: Based on all the reagent bottles to be clamped, the motion path of the main robot arm and the motion path of the collaborative robot arm are respectively constructed; Construct a bounding box model of the main robot arm and a bounding box model of the collaborative robot arm, and project the bounding box models corresponding to the main robot arm and the collaborative robot arm on the motion path onto three main planes, and then onto three main coordinate axes; Based on the projections of the bounding box models corresponding to the main robot arm and the collaborative robot arm on the motion paths on the three main coordinate axes, it is determined whether the main robot arm and the collaborative robot arm will collide; In response to a collision between the main robot arm and the collaborative robot arm, a delayed running time of the collaborative robot arm is obtained, and after the main robot arm runs the delayed running time of the collaborative robot arm, the collaborative robot arm starts running; In response to the fact that there will be no collision between the main robot arm and the collaborative robot arm, the main robot arm and the collaborative robot arm start to operate simultaneously.

2. The high-throughput dual-arm IoT collaboration method according to claim 1, characterized in that: In the process of projecting the bounding box models corresponding to the main robot arm and the collaborative robot arm on the motion path onto the three main planes and then onto the three main coordinate axes, the following steps are performed: Obtain the common space of the main robot arm and the collaborative robot arm on the motion path; Mapping the bounding box models corresponding to the main robot arm and the collaborative robot arm in the common space on the motion path to each plane in the Cartesian coordinate system, and obtaining a two-dimensional projection image corresponding to the bounding box model of the main robot arm and a two-dimensional projection image corresponding to the bounding box model of the collaborative robot arm; The two-dimensional projection images corresponding to the bounding box models of the main robot arm and the collaborative robot arm are mapped to each coordinate axis in the Cartesian coordinate system to obtain the projections of the bounding box models corresponding to the main robot arm and the collaborative robot arm on each coordinate axis on the motion path.

3. The high-throughput dual-arm IoT collaboration method according to claim 1, characterized in that: In the process of determining whether the main robot arm and the collaborative robot arm will collide, perform the following steps: Based on the projections of the bounding box models corresponding to the main robot arm and the collaborative robot arm on the motion paths, it is determined whether the main robot arm and the collaborative robot arm have a collision risk; In response to the main robot arm and the collaborative robot arm not having a collision risk, determining that the main robot arm and the collaborative robot arm will not collide; In response to the risk of collision between the main robotic arm and the collaborative robotic arm, an intersection test is performed on the bounding box models corresponding to the main robotic arm and the collaborative robotic arm on the motion path, and based on the intersection test result, it is determined whether the main robotic arm and the collaborative robotic arm will collide.

4. The high-throughput dual-arm IoT collaboration method according to claim 3, characterized in that: When there are no overlapping points between the projections of all bounding box models corresponding to the main robot arm on the motion path and all bounding box models corresponding to the collaborative robot arm on the motion path on any coordinate axis, it is determined that there is no collision risk between the main robot arm and the collaborative robot arm.

5. The high-throughput dual-arm IoT collaboration method according to claim 3, characterized in that: The bounding box model includes a sphere model and a capsule model.

6. The high-throughput dual-arm IoT collaboration method according to claim 5, characterized in that: During the intersection test of the spherical model of the main robot arm and the spherical model of the collaborative robot arm, perform the following steps: When the distance between the projections of the center of the spherical model of the main robot arm and the center of the spherical model of the collaborative robot arm on the corresponding coordinate axes is greater than the sum of the radii of the spherical model of the main robot arm and the spherical model of the collaborative robot arm, it is determined that the main robot arm and the collaborative robot arm will not collide; When the distance between the corresponding projections of the center of the spherical model of the main robotic arm and the center of the spherical model of the collaborative robotic arm on the corresponding coordinate axes is less than the sum of the radii of the spherical model of the main robotic arm and the spherical model of the collaborative robotic arm, determine whether the distance between the corresponding projections of the center of the spherical model of the main robotic arm and the center of the spherical model of the collaborative robotic arm on other coordinate axes is less than the sum of the radii of the spherical model of the main robotic arm and the spherical model of the collaborative robotic arm; In response to the distance between the projections of the center of the spherical model of the main robotic arm and the center of the spherical model of the collaborative robotic arm on other coordinate axes being smaller than the sum of the radii of the spherical model of the main robotic arm and the spherical model of the collaborative robotic arm, it is determined that the main robotic arm and the collaborative robotic arm will collide; In response to the fact that the distance between the corresponding projections of the center of the spherical model of the main robotic arm and the center of the spherical model of the collaborative robotic arm on any other coordinate axis is not less than the sum of the radii of the spherical model of the main robotic arm and the spherical model of the collaborative robotic arm, it is determined that the main robotic arm and the collaborative robotic arm will not collide.

7. The high-throughput dual-arm IoT collaboration method according to claim 5, characterized in that: During the intersection test of the spherical model of the main robot arm and the capsule model of the collaborative robot arm, or during the intersection test of the capsule model of the main robot arm and the spherical model of the collaborative robot arm, perform the following steps: When the distance between the projections of the center of the spherical model of the main robot arm and the center of any end ball of the capsule model of the collaborative robot arm or the center of any end ball of the capsule model of the main robot arm and the center of the spherical model of the collaborative robot arm on the corresponding coordinate axes is greater than the sum of the radius of the spherical model and the radius of the end ball of the capsule model, it is determined that the main robot arm and the collaborative robot arm will not collide; When the distance between the center of the end ball of the capsule model and the projections of the center of the sphere model on the corresponding coordinate axis is less than the sum of the radius of the sphere model and the radius of the end ball of the capsule model, determine whether the distance between the center of the corresponding end ball of the capsule model and the projections of the center of the sphere model on other coordinate axes is less than the sum of the radius of the sphere model and the radius of the corresponding end ball of the capsule model; In response to the distance between the center of the corresponding end ball of the capsule model and the projection of the center of the sphere model on other coordinate axes being less than the sum of the radius of the sphere model and the radius of the end ball of the capsule model, it is determined that the main robot arm and the cooperative robot arm will collide; In response to the fact that the distance between the center of the corresponding end ball of the capsule model and the corresponding projection of the center of the spherical model on any other coordinate axis is not less than the sum of the radius of the spherical model and the radius of the end ball of the capsule model, it is determined that the main robotic arm and the collaborative robotic arm will not collide.

8. The high-throughput dual-arm IoT collaboration method according to claim 5, characterized in that: During the intersection test of the capsule model of the main robot and the capsule model of the collaborative robot, the following steps are performed: When the distance between the projections of the two end balls of the capsule model of the main robot arm and the capsule model of the collaborative robot arm that are closer to each other on the corresponding coordinate axes is greater than the sum of the radii of the end balls of the capsule model of the main robot arm and the end balls of the capsule model of the collaborative robot arm, it is determined that the main robot arm and the collaborative robot arm will not collide; When the distance between the projections of the two end ball centers of the capsule body model of the main robot arm and the capsule body model of the collaborative robot arm on the corresponding coordinate axes are less than the sum of the radii of the end ball of the capsule body model of the main robot arm and the end ball of the capsule body model of the collaborative robot arm, determine whether the distance between the projections of the two end ball centers of the capsule body model of the main robot arm and the capsule body model of the collaborative robot arm on other coordinate axes are less than the sum of the radii of the end ball of the capsule body model of the main robot arm and the end ball of the capsule body model of the collaborative robot arm; In response to the fact that the distance between the projections of the two end ball centers of the capsule model of the main robot arm and the capsule model of the collaborative robot arm that correspond to each other on other coordinate axes is less than the sum of the radii of the end ball of the capsule model of the main robot arm and the end ball of the capsule model of the collaborative robot arm, it is determined that the main robot arm and the collaborative robot arm will collide; In response to the fact that the distance between the projections corresponding to the centers of the two end balls of the capsule model of the main robotic arm and the capsule model of the collaborative robotic arm on any other coordinate axis is not less than the sum of the radii of the end balls of the capsule model of the main robotic arm and the end balls of the capsule model of the collaborative robotic arm, it is determined that the main robotic arm and the collaborative robotic arm will not collide.

9. The high-throughput dual-arm IoT collaboration method according to claim 1, characterized in that: To obtain the delayed running time of the collaborative robot, perform the following steps: Taking the first preset time as the current delayed running time, determining whether the main robot arm and the collaborative robot arm will collide under the current delayed running time; In response to the fact that the main robot arm and the collaborative robot arm will not collide under the current delayed running time, the current delayed running time is used as the delayed running time of the collaborative robot arm; In response to the main robot arm and the cooperative robot arm colliding, a second preset time is added to the current delayed operation time until the main robot arm and the cooperative robot arm do not collide; Among them, the second preset time is greater than the time required to determine whether the main robot arm and the collaborative robot arm will collide.

10. A high-throughput dual-arm IoT collaboration system, characterized in that: The high-throughput dual-arm IoT collaboration method according to any one of claims 1 to 9 is used to perform dual-arm IoT collaboration, and the system comprises: A motion path acquisition module is used to construct the motion path of the main robot arm and the motion path of the collaborative robot arm based on all reagent bottles to be clamped; A bounding box model acquisition module is used to construct a bounding box model of the main robot arm and a bounding box model of the collaborative robot arm, and project the bounding box models corresponding to the main robot arm and the collaborative robot arm on the motion path onto three main planes and then onto three main coordinate axes; A collision judgment module is used to judge whether the main robot arm and the collaborative robot arm will collide based on the projections of the bounding box models corresponding to the main robot arm and the collaborative robot arm on the motion path; An operation module is used to obtain the delayed operation time of the collaborative robot arm in response to a collision between the main robot arm and the collaborative robot arm. After the main robot arm runs the delayed operation time of the collaborative robot arm, the collaborative robot arm starts to run; in response to no collision between the main robot arm and the collaborative robot arm, the main robot arm and the collaborative robot arm start to run at the same time.

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