Construction site-oriented multi-robot distributed control method and system

Abstract

The application provides a construction site-oriented multi-robot distributed control method and system, relates to the technical field of robot control, and comprises the following steps: acquiring a plurality of static geometric shape information of a plurality of robots distributed in a construction area, analyzing and determining a plurality of geometric centers, modeling a plurality of first electronic fences, and pre-storing to a control terminal; updating the first electronic fence according to a plurality of dynamic geometric shape information corresponding to a plurality of real-time motion states to obtain a plurality of second electronic fences; performing electronic fence contact detection on the plurality of robots according to the plurality of second electronic fences; if the contact detection return result is not empty, determining an identified robot group with a collision risk, and performing obstacle avoidance control on the identified robot group. Through the application, the technical effects of improving the obstacle avoidance reaction speed of the robot, reducing misjudgment and missed judgment, and ensuring the safe and efficient collaborative work of the multi-robot in the construction site can be achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of robot control, and particularly relates to a multi-robot distributed control method and system for a construction site. BACKGROUND

[0002] In modern construction sites, with the continuous improvement of intelligentization and automation level, mobile robots are widely used in material transportation, environment monitoring, collaborative work and other scenes. However, the construction environment is complex, the space is small, and the personnel are dense. The safety hazards brought by multiple robots running at the same time are increasingly prominent, especially the high collision risk between robots in the moving process. In order to reduce such risks, the existing technology usually adopts a static electronic fence setting method, that is, a fixed safety boundary is preset for each robot, and whether the actual distance between the robots is less than the sum of the radii of the two static boundaries is judged to trigger the obstacle avoidance response. Although this way realizes the basic collision detection and obstacle avoidance control, it essentially relies on a static model and fails to fully consider the dynamic changes of the geometric shape, speed change and actual motion trajectory of the robot in the motion process, and has certain limitations.

[0003] At present, the existing static electronic fence cannot accurately reflect the dynamic shape change of the robot in the process of high-speed movement or turning. For example, when the robot accelerates, decelerates, makes sharp turns and the like, its motion path and geometric envelope change significantly, and the static radius cannot effectively cover the actual space occupation brought by these changes, which is easy to cause misjudgment or omission. Secondly, the current obstacle avoidance mechanism mostly only judges whether it is close according to the preset distance, lacks comprehensive evaluation of the current task urgency, size and past interaction experience of the robot, and leads to the problem that the obstacle avoidance strategy does not have priority division when multiple robots run at the same time, which is easy to cause chaotic or repeated avoidance. In addition, the control decision generally relies on a centralized server for scheduling, and has the problems of response delay and strong communication dependence, which is difficult to meet the high-frequency obstacle avoidance demand.

[0004] In summary, the existing technology has the problems of static fixation of the electronic fence model, single obstacle avoidance logic, lack of priority judgment, centralized control mode, and the like, which leads to the technical problems that the response cannot be made in time and accurately in the face of high-speed motion of the robot, complex trajectory change and multi-robot collaborative obstacle avoidance scene, and further affects the safety, collaboration of the robot in the construction site and the real-time and stability of the whole system. SUMMARY

[0005] The purpose of the present application is to provide a multi-robot distributed control method and system for construction sites, which solves the technical problems in the prior art that due to the static fixation of electronic fence models, the single obstacle avoidance logic and the lack of priority judgment, the centralized control mode, etc., the response cannot be made in time and accurately in the face of high-speed motion of robots, complex trajectory changes and multi-robot cooperative obstacle avoidance scenes, further affecting the safety, collaboration of robots in the construction site and the real-time and stability of the whole system.

[0006] In view of the above problems, the present application provides a multi-robot distributed control method and system for construction sites.

[0007] In the first aspect, the present application provides a multi-robot distributed control method for construction sites, which is realized by a multi-robot distributed control system for construction sites, comprising: acquiring a plurality of static geometric shape information of a plurality of robots distributed in a construction area; analyzing the plurality of static geometric shape information according to a geometric modeling algorithm to determine a plurality of geometric centers, and determining a plurality of first electronic fences according to the plurality of geometric centers, and pre-storing the first electronic fences to the control terminals corresponding to the plurality of robots respectively; identifying a plurality of real-time motion states of the plurality of robots by the control terminals, updating the first electronic fences according to a plurality of dynamic geometric shape information corresponding to the plurality of real-time motion states to obtain a plurality of second electronic fences; and performing electronic fence contact detection on the plurality of robots by the control terminals corresponding to the plurality of robots respectively according to the plurality of second electronic fences, and if the contact detection returns a result, determining an identified robot group with collision risk, and performing obstacle avoidance control on the identified robot group.

[0008] In a second aspect, the application also provides a construction site-oriented multi-robot distributed control system for executing the construction site-oriented multi-robot distributed control method as described in the first aspect, comprising: an information acquisition module for acquiring a plurality of static geometric shape information of a plurality of robots distributed in a construction area; a fence determination module for analyzing the plurality of static geometric shape information according to a geometric modeling algorithm, determining a plurality of geometric centers, and determining a plurality of first electronic fences according to the plurality of geometric centers, and pre-storing the first electronic fences to control terminals corresponding to the plurality of robots respectively; a fence updating module for identifying a plurality of real-time motion states of the plurality of robots by the control terminals, updating the first electronic fences according to a plurality of dynamic geometric shape information corresponding to the plurality of real-time motion states, and obtaining a plurality of second electronic fences; and an obstacle avoidance control module for the control terminals corresponding to the plurality of robots to perform electronic fence contact detection on the plurality of robots according to the plurality of second electronic fences, and if the contact detection returns a result, determining an identified robot group with collision risk, and performing obstacle avoidance control on the identified robot group.

[0009] The technical solutions provided in the application have at least the following technical effects or advantages: by achieving the technical goal of constructing electronic fences based on dynamic geometric shapes and real-time motion states of robots and performing distributed obstacle avoidance control, the technical effect of improving the obstacle avoidance response speed of robots, reducing misjudgment and omission, and ensuring safe and efficient collaborative operation of multiple robots in a construction site is achieved.

[0010] The above description is only a summary of the technical solutions of the application. In order to enable one skilled in the art to better understand the technical means of the application, the application can be implemented according to the content of the specification, and in order to enable the above and other purposes, features and advantages of the application to be more obvious and easy to understand, the following specific embodiments of the application are described. It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of the application, nor is it intended to limit the scope of the application. Other features of the application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the application or the prior art, the following will briefly introduce the drawings needed in the embodiments or the prior art description. Obviously, the drawings in the following description are only exemplary, and those skilled in the art can obtain other drawings without creative labor on the basis of the provided drawings.

[0012] Figure 1 Flowchart of the construction site-oriented multi-robot distributed control method of the application;

[0013] Figure 2Fig. 1 is a structural schematic diagram of a multi-robot distributed control system for a construction site according to the present application.

[0014] Reference signs: information acquisition module 11, fence determination module 12, fence update module 13, obstacle avoidance control module 14. DETAILED DESCRIPTION

[0015] The present application provides a multi-robot distributed control method and system for a construction site, which solves the technical problems in the prior art that due to the static fixation of the electronic fence model, the single obstacle avoidance logic and the lack of priority judgment, the centralized control mode, etc., the response cannot be made in time and accurately in the face of high-speed motion of robots, complex trajectory changes and multi-robot cooperative obstacle avoidance scenes, further affecting the safety, collaboration of robots in the construction site and the real-time and stability of the whole system. The technical goal of constructing an electronic fence based on the dynamic geometric shape and real-time motion state of the robot and performing distributed obstacle avoidance control is achieved, and the technical effects of improving the obstacle avoidance response speed of the robot, reducing misjudgment and omission and ensuring the safe and efficient performance of the multi-robot cooperative operation in the construction site are achieved.

[0016] Hereinafter, the technical solutions in the present application will be described clearly and completely with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the scope of protection of the present application. In addition, it should be noted that, for the convenience of description, only parts related to the present application are shown in the drawings, rather than all.

[0017] Embodiment one, please refer to the accompanying Figure 1 The present application provides a multi-robot distributed control method for a construction site, which is applied to a multi-robot distributed control system for a construction site, and specifically includes the following steps:

[0018] S1: acquiring a plurality of static geometric shape information of a plurality of robots distributed in a construction area.

[0019] Specifically, a plurality of static geometric shape information of a plurality of robots distributed in a construction area is collected by sensors, cameras or background control systems. The construction area refers to a work site where building, paving or installation work is being carried out, which can include floors, foundation pits, roads and other sites. There are a plurality of robots in the construction area, which are scattered in different corners of the construction area at certain intervals or rules, and can perform different tasks such as cleaning, transportation, welding and detection. The static geometric shape information refers to the size structure of each robot in a non-motion state, such as length, width, height, shape contour or land boundary, which does not change frequently with the action of the robot and has stability.

[0020] S2: analyzing the plurality of static geometric shape information according to a geometric modeling algorithm, determining a plurality of geometric centers, modeling a plurality of first electronic fences according to the plurality of geometric centers, and pre-storing the first electronic fences to the control terminals corresponding to the plurality of robots respectively.

[0021] Specifically, the geometric modeling algorithm refers to a calculation method for describing the shape structure of an object in a mathematical way, including convex hull algorithm, bounding box algorithm, polygon fitting algorithm and the like, which is used to express and process the shape and spatial features of an object in a computer. According to the geometric modeling algorithm, the plurality of static geometric shape information is analyzed, that is, a point representing the spatial position of each robot is found in each robot, so as to judge the actual occupation, direction of the robot in space and the relative distance with other objects. Among them, the geometric center refers to the centroid, barycenter or geometric symmetry center of the shape.

[0022] According to the plurality of geometric centers, the electronic fence modeling is performed to determine a plurality of first electronic fences. The electronic fence modeling refers to constructing a boundary model for obstacle avoidance control using the geometric center and related radius information, which can be in the form of a circle, a polygon and the like. The purpose is to delimit the safety area of the robot during operation, and finally generate a set of boundary areas corresponding to each geometric center as an electronic safety control range, which is used for subsequent obstacle avoidance and path judgment.

[0023] The first electronic fence is pre-stored to the control terminal corresponding to the plurality of robots respectively. Pre-storing means that the boundary data is stored in the corresponding position in advance before the robot performs the task. The control terminal refers to a control device for managing the running logic of the robot, which can be an embedded system, an upper computer or a mobile terminal, and has the functions of processing boundary information, receiving motion data, controlling running path and the like.

[0024] S3: identifying a plurality of real-time motion states of the plurality of robots by the control terminal, updating the first electronic fence according to a plurality of dynamic geometric shape information corresponding to the plurality of real-time motion states, and obtaining a plurality of second electronic fences.

[0025] Specifically, the control terminal identifies the real-time motion states of the plurality of robots, that is, the control terminal logically identifies and processes the input data to obtain a set of data such as the positions, speeds, directions, and postures of the plurality of robots at a certain time. The real-time motion states are dynamically changing, and need to be fed back to the control terminal in real time through sensors or communication modules for decision-making.

[0026] The plurality of dynamic geometric shape information corresponding to the plurality of real-time motion states refers to the changes in the physical shape in the modeling calculation during the movement of the robot, such as the extended edge when turning and the inertia tail when accelerating. These changes are dynamic and generated in real time. The plurality of second electronic fences are obtained by updating the first electronic fence according to the plurality of dynamic geometric shape information corresponding to the plurality of real-time motion states, which means recalculating the shape, radius, or boundary range of the first electronic fence to adapt to the changes in the current real-time dynamic information. The plurality of second electronic fences are new rounds of electronic fences generated based on the current real-time motion state and dynamic geometric shape, and have higher accuracy and timeliness than the first electronic fence, and are used to more accurately perform obstacle avoidance judgment.

[0027] S4: The control terminal corresponding to each of the plurality of robots performs electronic fence contact detection on the plurality of robots according to the plurality of second electronic fences. If the contact detection returns a result, it is determined that there is a collision risk of the identified robot group, and the identified robot group is controlled to avoid obstacles.

[0028] Specifically, different machines and equipment are distributed in the construction site, and each robot has its own running and control system. The control terminal corresponding to each of the plurality of robots performs electronic fence contact detection on the plurality of robots according to the plurality of second electronic fences. If the contact detection returns a result, it is determined that there is a collision risk of the identified robot group, that is, it is identified that the electronic fences of some robots have contacted and the safety boundaries have overlapped. The collision risk refers to the fact that if two or more robots continue to run according to the current trajectory, they are likely to physically contact in space. The identified robot group refers to the set of robots identified as having a risk relationship in this detection.

[0029] The identified robot group is controlled to avoid obstacles, which means that a certain strategy (such as changing the path, adjusting the speed, or temporarily stopping) is used to make the robot avoid collision. The obstacle avoidance process may involve trajectory adjustment, priority judgment, and other algorithms working together to ensure that the plurality of robots can safely and cooperatively run in a limited space.

[0030] Further, the application also includes: performing priority factor analysis on each robot in the identified robot group, the priority factors including task urgency, robot volume, and historical interaction data, wherein the number of the identified robot group is at least 2; calculating the obstacle avoidance priority of each robot in the identified robot group based on the task urgency, robot volume, and historical interaction data; determining the obstacle avoidance execution robot of the identified robot group according to the size of the obstacle avoidance priority, and controlling the obstacle avoidance execution robot to execute the obstacle avoidance strategy.

[0031] Specifically, the priority factor analysis on each robot in the identified robot group refers to identifying and quantifying a plurality of key parameters that affect the order of robot obstacle avoidance, so as to determine the robot that needs to give way first when encountering potential conflicts, and the robot that can maintain the current path unchanged.

[0032] The priority factors include task urgency, robot volume, and historical interaction data, which clearly define the reference parameters for calculating the priority. The task urgency refers to the time limit requirement or importance of the current task of the robot, the more urgent the task, the higher the priority; the robot volume refers to the size of the robot itself in the physical space, the larger the volume, the more difficult the movement adjustment, and the path should be kept stable; the historical interaction data represents the frequency of yielding or conflict in the obstacle avoidance process of the robot with other robots in the past period of time, which can be used to learn and optimize the obstacle avoidance behavior. The number of the identified robot group is at least 2, which means that the judgment scenario is based on the premise that two or more robots exist potential interference or intersection.

[0033] The obstacle avoidance priority of each robot in the identified robot group is calculated based on the task urgency, robot volume, and historical interaction data. The obstacle avoidance priority is a ranking standard for measuring whether each robot should actively give way in the obstacle avoidance conflict. For example, the higher the score of a robot, the more inclined it is to keep the path unchanged when encountering conflicts, and the lower priority robots give way.

[0034] The obstacle avoidance execution robot of the identified robot group is determined according to the size of the obstacle avoidance priority, and the obstacle avoidance execution robot is controlled to execute the obstacle avoidance strategy, which determines which robot needs to actually execute the obstacle avoidance behavior. The obstacle avoidance execution robot refers to the robot that is determined to need to yield or replan the path in the current conflict situation. The obstacle avoidance strategy is a specific action mode, including operations such as deceleration, pause, detour, etc., and the control refers to issuing specific execution instructions through the control terminal to make the robot complete the obstacle avoidance action according to the priority logic.

[0035] Further, the application further comprises: determining a motion trajectory of the obstacle avoidance execution robot; taking the contact detection return result as null as an optimization target, adjusting the motion trajectory according to an A-star pathfinding algorithm, and calculating cost data of the adjusted motion trajectory through a heuristic cost function, and if the cost data meets a convergence condition, a converged motion trajectory is obtained; and controlling the obstacle avoidance execution robot according to the converged motion trajectory as an obstacle avoidance strategy.

[0036] Specifically, a motion trajectory of the obstacle avoidance execution robot is determined, the motion trajectory being an expected moving path of the robot from a current position to a target position, composed of a series of continuous spatial coordinate points, representing a moving route of the robot in the motion process.

[0037] The contact detection return result is taken as null as an optimization target, and the motion trajectory is adjusted according to the A-star pathfinding algorithm. The contact detection return result as null means that there is no contact between the safety fences of all robots under the current motion trajectory, i.e., there is no potential collision risk. The optimization target means the final desired result of the algorithm or decision. The A-star pathfinding algorithm is a commonly used path planning algorithm, which can efficiently find the optimal path from the starting point to the ending point in a complex environment. The trajectory adjustment means optimizing the original straight line or existing path to complete the target navigation under the premise of not overlapping with the electronic fences of other robots.

[0038] The cost data of the adjusted motion trajectory is calculated through a heuristic cost function. The heuristic cost function is a method for estimating the cost of the shortest path from the current position to the target position, which is used in the A-star algorithm to improve the search efficiency. The cost data of the path change is obtained by mathematical means. The cost data refers to the cost required for trajectory adjustment, including path length, number of obstacle avoidance turns, speed loss, etc. The smaller the value, the more ideal the path, and the higher the cost, the greater the impact on the original task in the obstacle avoidance process.

[0039] If the cost data meets the convergence condition, a converged motion trajectory is obtained, indicating that the current cost data has tended to be stable or has reached a preset threshold and no longer changes significantly. The converged motion trajectory represents a final determined stable and reasonable obstacle avoidance path, which no longer needs to be adjusted and meets the requirements of obstacle avoidance target and efficiency.

[0040] The converged motion trajectory is taken as an obstacle avoidance strategy to control the obstacle avoidance execution robot, indicating that the finally obtained safe and stable path is taken as the basis for execution. The obstacle avoidance strategy refers to a specific scheme for controlling the robot to perform the avoidance behavior.

[0041] Further, the application also includes: performing contour extraction according to the plurality of static geometric shape information, judging whether the contours of the plurality of robots are regular; if the contours of the plurality of robots are regular, performing radius expansion on the plurality of geometric centers respectively by using an outward expansion radius, and outputting a plurality of first electronic fences; and if the plurality of robots are of irregular geometric types, calculating buffer radii of the plurality of robots according to a convex hull algorithm, performing radius expansion on the plurality of geometric centers respectively by using the buffer radii, and outputting a plurality of first electronic fences.

[0042] Specifically, contour extraction is performed according to the plurality of static geometric shape information. Contour extraction refers to identifying the outer boundary or outer shape structure of a robot from the plurality of static geometric shape information by using edge detection, point set fitting, polygon approximation and the like, and then obtaining clear outer contour lines in two-dimensional or three-dimensional space, so as to obtain the real shape distribution of each robot.

[0043] After contour extraction, it is judged whether the contours of the plurality of robots are regular. That is, structural analysis of the contour shape itself is performed by analyzing contour features, to obtain contour judgment results of the plurality of robots. If the contours of the plurality of robots are regular, they can include features such as boundary smoothness, symmetry, consistent side length, angle standardization and the like, while irregular contours can be in the form of a polygon, a special-shaped structure or a contour with complex edge undulations.

[0044] If the contours of the plurality of robots are regular, that is, the outer shape boundary of the robot has standardization and symmetry, such as smooth edges, a rectangular shape, a circular shape or other geometric standard shapes, without obvious protrusions or depressions, then radius expansion is performed on the plurality of geometric centers respectively by using an outward expansion radius, and a plurality of first electronic fences are outputted, which are used for visual display or obstacle avoidance decision. The outward expansion radius is a value obtained based on the maximum edge distance of the robot, and represents a buffer range extending outward from the geometric center, which is used to ensure a certain safety distance from the periphery during normal operation of the robot.

[0045] If the plurality of robots are of irregular geometric types, buffer radii of the plurality of robots are calculated according to a convex hull algorithm, and a plurality of first electronic fences are outputted. The irregular geometric types refer to the outer shape boundary of the plurality of robots without symmetry or standard shape, which can have features such as unequal sides, multiple corners, protruding accessories and the like. The convex hull algorithm is a commonly used method in computational geometry, which is used to wrap a group of boundary points into a smallest convex polygon, so as to simplify the processing mode of a complex shape and to be used for approximate modeling of irregular outer contours. The buffer radius refers to the distance from the geometric center to the farthest point on the boundary based on the approximate contour formed by the convex hull, which represents the minimum safety protection radius required by the robot in space, to ensure that the device body is covered in any direction.

[0046] The buffer radius is used to expand the radius of each geometric center, indicating that each geometric center generates a circular protection area outward with its own buffer radius, and can form a corresponding electronic fence for each irregular robot to meet the safety coverage requirements of its asymmetric structure. Finally, a plurality of first electronic fences are output for display, system call or collision detection.

[0047] Further, the application also includes: obtaining regular robot regular contour data; determining the first radius of the regular robot according to the distance between the regular contour data and the geometric center, expanding the radius of the plurality of geometric centers with the first radius as the expansion radius, and outputting a plurality of first electronic fences; wherein the first radius is the maximum radius in the regular contour data from the geometric center.

[0048] Specifically, the regular robot refers to a robot with a regular contour. The regular contour data of the regular robot is obtained by sensor acquisition and other methods to obtain the shape boundary information of the regular robot.

[0049] Then, the geometric center is the central position of each regular robot in the space in the static state, which is a point calculated by a modeling algorithm. According to the distance between the regular contour data and the geometric center, the first radius of the regular robot is determined to obtain the straight line distance between the geometric center and each point of the outer contour.

[0050] Then, the expansion radius refers to the distance extending outward on the basis of the original boundary. The first radius is taken as the expansion radius to expand the radius of the plurality of geometric centers with the geometric center as the center, and a plurality of first electronic fences are output for constructing a safety buffer zone.

[0051] The point in the regular contour data has multiple distance values from the geometric center, the first radius is the maximum radius in the regular contour data from the geometric center, representing the distance between the farthest boundary of the robot and the geometric center, and is used to determine the robot expansion range, so as to ensure that the robot has sufficient safety buffer zone in any direction.

[0052] Further, the application also includes: obtaining non-regular robot non-regular contour data; calculating approximate outer contour data of the non-regular contour data according to a convex hull algorithm; determining the first radius of the regular robot according to the distance between the approximate outer contour data and the geometric center, expanding the radius of the plurality of geometric centers with the first radius as the expansion radius, and outputting a plurality of first electronic fences; wherein the first radius is the maximum radius in the approximate outer contour data from the geometric center.

[0053] Specifically, the irregular robot refers to a robot with an asymmetric shape, a complex edge, or multiple structural protrusions, such as a mechanical arm, a special-shaped inspection robot, or a work robot with an attached device. The irregular outer contour data of the irregular robot is obtained by methods such as sensors, three-dimensional scanning, or vision systems. The irregular outer contour data refers to the actual boundary point information of the irregular robot, which is used to describe the space region actually occupied by the robot.

[0054] The convex hull algorithm is a computational geometry method that can enclose all boundary points and construct a smallest convex polygon to approximate the overall contour of a complex object, simplifying the analysis complexity of the original shape. The approximate outer contour data of the irregular outer contour data is calculated according to the convex hull algorithm. The approximate outer contour data refers to the simplified version obtained by the convex hull algorithm, which although not equal to the true boundary, can better reflect the overall contour shape and be used for the next step of calculation and modeling.

[0055] According to the distance between the approximate outer contour data and the geometric center, the first radius of the regular robot is determined. The first radius is the maximum radius in the approximate outer contour data from the geometric center, i.e., the maximum value of the distance from all points of the simplified contour to the center point, ensuring that the generated circular electronic fence is sufficient to cover the entire irregular robot, even if there are edge protrusions in the original shape.

[0056] Subsequently, the first radius is used as an expansion radius to expand the radius of the multiple geometric centers, i.e., a circular region is drawn with the geometric center as the center and the first radius as the radius, and multiple first electronic fences are output to form a safety buffer zone for subsequent obstacle avoidance control or path planning.

[0057] Further, the present application also includes: identifying the outer contour data corresponding to the first electronic fence; judging the multiple real-time motion states, the parameters of the real-time motion state including motion speed, motion degree of freedom, and motion load size, obtaining a compensation radius according to the motion speed, motion degree of freedom, and motion load size, and updating the outer contour data of the current first electronic fence according to the compensation radius.

[0058] Specifically, the outer contour data corresponding to the first electronic fence is identified by image processing, edge detection, or geometric operation, i.e., the specific shape, coordinate point set, or curve data of the initial boundary generated based on the geometric center and the buffer radius are extracted and analyzed.

[0059] The input dynamic information is logically analyzed to obtain real-time motion state parameters including motion speed, motion degree of freedom and motion load size. The real-time motion state parameters include motion speed, motion degree of freedom and motion load size. The motion speed refers to the moving distance of the robot in unit time, which directly affects the time demand for its obstacle avoidance reaction; the motion degree of freedom refers to the number of spatial dimensions in which the robot can freely move, which is usually a combination of translation and rotation dimensions in three-dimensional space; and the motion load size refers to the weight of the load carried or borne by the robot, which may affect its braking ability and motion inertia in high-speed or heavy-load conditions.

[0060] Next, a compensation radius is obtained according to the motion speed, the motion degree of freedom and the motion load size, which is used to expand the original electronic fence to adapt to potential errors or deviations caused by the current motion state of the robot, for example, the faster the motion speed, the larger the required compensation radius, to prevent the robot from moving too fast and not reacting in time to cause boundary crossing; the larger the load, the additional safety distance is also required to avoid inertia sliding. Table 1 is a record of the last time the outer contour data of the current first electronic fence was updated, which can show that as the speed increases, the degree of freedom increases, and the load increases, the compensation radius shows a linear growth trend, thereby gradually expanding the radius of the updated electronic fence, ensuring that the robot is still within the safety boundary under complex motion state.

[0061] Table 1: Record of the last time the outer contour data of the current first electronic fence was updated

[0062]

[0063] The first electronic fence currently refers to the originally generated static safety range. The outer contour data of the first electronic fence is updated according to the compensation radius, and the original data is expanded, enlarged or modified to form a dynamically adaptive state boundary, so that the electronic fence has real-time and changeability.

[0064] Further, the application also includes: if d < (R1+R2), the contact detection return result is not empty; if d ≥ (R1+R2), the contact detection return result is empty; wherein d is the real-time distance between the first robot and the second robot, R1 is the radius of the second electronic fence corresponding to the first robot, and R2 is the radius of the second electronic fence corresponding to the second robot.

[0065] Specifically, d is the real-time distance between the first robot and the second robot calculated by the positioning system or sensor. R1 is the radius of the second electronic fence corresponding to the first robot, and R2 is the radius of the second electronic fence corresponding to the second robot. Contact detection means analyzing whether the boundaries of the two robots overlap or intersect. If the distance between the first robot and the second robot is less than the sum of the fence radii of the first robot and the second robot, the contact detection returns a result that is not empty, indicating that an intersection is detected, i.e., the two robot fences contact or overlap, and relevant information such as a touch warning or obstacle avoidance instruction will be output.

[0066] If the real-time distance between the two robots is greater than or equal to the sum of their fence radii, the contact detection returns a result that is empty, meaning that no contact or boundary crossing behavior is detected, and the robots can continue to move according to the current path without triggering an obstacle avoidance response.

[0067] Further, the application also includes that the control terminal is an edge computing unit distributed locally on the robot for real-time processing of electronic fence data and obstacle avoidance decision.

[0068] Specifically, the control terminal refers to a device that controls and manages the operation of the robot, and is a key part of intelligent decision-making and execution. The control terminal is an edge computing unit distributed locally on the robot. Distributed deployment means that the control terminal is not running on a central server, but is installed locally on each robot, has independent running capability, and helps to improve system response speed and stability. Local to the robot means that the terminal device is directly installed on the hardware platform of each specific robot, and can directly obtain its own sensor data and motion state. The edge computing unit refers to a small computing device with certain data processing and computing capabilities, which can complete computing tasks directly near the data source, avoiding the delay and network pressure caused by data transmission to a remote server, and thus is more suitable for time-sensitive application scenarios.

[0069] The control terminal is used for real-time processing of electronic fence data and obstacle avoidance decision, which means that the control terminal can analyze and respond at the first time of data generation, process electronic fence data and obstacle avoidance decision. Electronic fence data refers to the dynamic safety range information of the current fence radius, outer contour boundary coordinates, geometric center, etc. of each robot; obstacle avoidance decision refers to the behavior strategy of moving direction adjustment, speed control or braking made by the terminal when discovering fence overlap or potential collision risk, which is used to ensure the relative safety between robots.

[0070] In summary, the construction site-oriented multi-robot distributed control method provided in the application has the following technical effects: by achieving the technical goal of constructing an electronic fence based on the dynamic geometry and real-time motion state of the robot and performing distributed obstacle avoidance control, the reaction speed of the robot is improved, the misjudgment and missed judgment are reduced, and the safety and efficiency of the collaborative work of the multi-robot in the construction site are ensured.

[0071] In the second embodiment, based on the same inventive concept as the construction site-oriented multi-robot distributed control method in the foregoing embodiments, the application also provides a construction site-oriented multi-robot distributed control system, please refer to the accompanying drawings Figure 2 , comprising: an information acquisition module 11, configured to acquire a plurality of static geometric shape information of a plurality of robots distributed in a construction area; a fence determination module 12, configured to analyze the plurality of static geometric shape information according to a geometric modeling algorithm, determine a plurality of geometric centers, and determine a plurality of first electronic fences according to the plurality of geometric centers; the first electronic fence is pre-stored in the control terminal corresponding to the plurality of robots respectively; a fence updating module 13, configured to identify a plurality of real-time motion states of the plurality of robots by the control terminal, update the first electronic fence according to a plurality of dynamic geometric shape information corresponding to the plurality of real-time motion states, and obtain a plurality of second electronic fences; an obstacle avoidance control module 14, configured to perform electronic fence contact detection on the plurality of robots by the control terminal corresponding to the plurality of robots according to the plurality of second electronic fences, and if the contact detection return result is not empty, determine an identified robot group with collision risk, and perform obstacle avoidance control on the identified robot group.

[0072] Further, the construction site-oriented multi-robot distributed control system is also used for: performing priority factor analysis on each robot in the identified robot group, the priority factors including task urgency, robot volume and historical interaction data, wherein the number of the identified robot group is at least 2; calculating the obstacle avoidance priority of each robot in the identified robot group based on the task urgency, robot volume and historical interaction data; determining an obstacle avoidance execution robot of the identified robot group according to the size of the obstacle avoidance priority, and controlling the obstacle avoidance execution robot to execute an obstacle avoidance strategy.

[0073] Further, the construction site-oriented multi-robot distributed control system is also used for: determining a motion trajectory of the obstacle avoidance execution robot; taking the contact detection return result as empty as an optimization target, adjusting the motion trajectory according to an A-star pathfinding algorithm, and calculating the cost data of the adjusted motion trajectory through a heuristic cost function, if the cost data meets the convergence condition, a converged motion trajectory is obtained; taking the converged motion trajectory as the obstacle avoidance strategy to control the obstacle avoidance execution robot.

[0074] Further, the construction site-oriented multi-robot distributed control system is further used for: contour extraction according to the plurality of static geometric shape information, judging whether the contours of the plurality of robots are regular; if the contours of the plurality of robots are regular, respectively expanding radii of the plurality of geometric centers by using an outward expansion radius, and outputting a plurality of first electronic fences; if the plurality of robots are of irregular geometric types, calculating buffer radii of the plurality of robots according to a convex hull algorithm, respectively expanding radii of the plurality of geometric centers by using the buffer radii, and outputting a plurality of first electronic fences.

[0075] Further, the construction site-oriented multi-robot distributed control system is further used for: obtaining regular outer contour data of a regular robot; determining a first radius of the regular robot according to a distance between the regular outer contour data and a geometric center, and respectively expanding radii of the plurality of geometric centers by using the first radius as an outward expansion radius, and outputting a plurality of first electronic fences; wherein the first radius is a maximum radius in the regular outer contour data from the geometric center.

[0076] Further, the construction site-oriented multi-robot distributed control system is further used for: obtaining irregular outer contour data of an irregular robot; calculating approximate outer contour data of the irregular outer contour data according to a convex hull algorithm; determining a first radius of the regular robot according to a distance between the approximate outer contour data and a geometric center, and respectively expanding radii of the plurality of geometric centers by using the first radius as an expansion radius, and outputting a plurality of first electronic fences; wherein the first radius is a maximum radius in the approximate outer contour data from the geometric center.

[0077] Further, the construction site-oriented multi-robot distributed control system is further used for: identifying outer contour data corresponding to the first electronic fence; judging a plurality of real-time motion states, parameters of the real-time motion states including motion speed, motion degree of freedom and motion load size, obtaining a compensation radius according to the motion speed, the motion degree of freedom and the motion load size, and updating outer contour data of the current first electronic fence according to the compensation radius.

[0078] Further, the construction site-oriented multi-robot distributed control system is further used for: if d < (R1+R2), the contact detection return result is not empty; if d ≥ (R1+R2), the contact detection return result is empty; wherein d is a real-time distance between a first robot and a second robot, R1 is a radius of a second electronic fence corresponding to the first robot, and R2 is a radius of a second electronic fence corresponding to the second robot.

[0079] Further, the construction site-oriented multi-robot distributed control system is also used for: the control terminal is an edge computing unit distributed at the local robot, used for processing electronic fence data and obstacle avoidance decision in real time.

[0080] The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The construction site-oriented multi-robot distributed control method and specific examples in the foregoing embodiment one are also applicable to the construction site-oriented multi-robot distributed control system of the present embodiment. Through the foregoing detailed description of the construction site-oriented multi-robot distributed control method, those skilled in the art can clearly know the construction site-oriented multi-robot distributed control system of the present embodiment. Therefore, for the sake of brevity of the specification, the construction site-oriented multi-robot distributed control system will not be described in detail here.

[0081] The above description of disclosed embodiments enables those skilled in the art to carry out or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0082] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. A multi-robot distributed control method for a construction site, characterized in that the method The method comprises the following steps: acquiring a plurality of static geometric shape information of a plurality of robots in a construction area; analyzing the plurality of static geometric shape information according to a geometric modeling algorithm to determine a plurality of geometric centers, and determining a plurality of first electronic fences according to the plurality of geometric centers, and pre-storing the first electronic fences to the control terminals corresponding to the plurality of robots respectively; identifying a plurality of real-time motion states of the plurality of robots by the control terminals, updating the first electronic fences according to a plurality of dynamic geometric shape information corresponding to the plurality of real-time motion states to obtain a plurality of second electronic fences; the control terminals corresponding to the plurality of robots respectively perform electronic fence contact detection on the plurality of robots according to the plurality of second electronic fences, if the contact detection returns a result, it is determined that there is a collision risk of an identified robot group, and the identified robot group is controlled to avoid obstacles; the step of updating the first electronic fences according to the plurality of dynamic geometric shape information corresponding to the plurality of real-time motion states comprises: identifying the outer contour data corresponding to the first electronic fence; judging the plurality of real-time motion states, the parameters of the real-time motion state including motion speed, motion degree of freedom and motion load size, acquiring a compensation radius according to the motion speed, motion degree of freedom and motion load size, and updating the outer contour data of the current first electronic fence according to the compensation radius.

2. The method of claim 1, wherein, The method for controlling the identified robot group to avoid obstacles comprises: analyzing priority factors of each robot in the identified robot group, the priority factors including task urgency, robot volume and historical interaction data, wherein the number of the identified robot group is at least 2; calculating the obstacle avoidance priority of each robot in the identified robot group based on the task urgency, robot volume and historical interaction data; determining an obstacle avoidance execution robot of the identified robot group according to the size of the obstacle avoidance priority, and controlling the obstacle avoidance execution robot to execute an obstacle avoidance strategy.

3. The method of claim 2, wherein, The method for acquiring the obstacle avoidance strategy comprises: determining a motion trajectory of the obstacle avoidance execution robot; taking the contact detection return result as null as an optimization target, adjusting the motion trajectory according to an A-star pathfinding algorithm, and calculating the cost data of the adjusted motion trajectory through a heuristic cost function, if the cost data meets a convergence condition, a converged motion trajectory is obtained; controlling the obstacle avoidance execution robot according to the converged motion trajectory as the obstacle avoidance strategy.

4. The method of claim 1, wherein, The method for determining a plurality of first electronic fences according to the plurality of geometric centers comprises: extracting contours according to the plurality of static geometric shape information, and judging whether the contours of the plurality of robots are regular; if the contours of the plurality of robots are regular, expanding the radii of the plurality of geometric centers respectively by an outer expansion radius, and outputting a plurality of first electronic fences; if the plurality of robots are of irregular geometric types, calculating a buffer radius of the plurality of robots according to a convex hull algorithm, expanding the radii of the plurality of geometric centers respectively by the buffer radius, and outputting a plurality of first electronic fences.

5. The method of claim 4, wherein, The method involves expanding the radius of the plurality of geometric centers by an outward expansion radius, including: Obtain the regular outer contour data of the rule-based robot; Based on the distance between the outer contour data of the rule and the geometric center, the first radius of the rule robot is determined, and the first radius is used as the expansion radius to expand the radius of the multiple geometric centers respectively, thereby outputting multiple first electronic fences; Wherein, the first radius is the radius that is the largest distance from the geometric center in the regular outer contour data.

6. The method of claim 4, wherein, The buffer radius of the multiple robots is calculated according to the convex hull algorithm, and the buffer radius is used to expand the radius of the multiple geometric centers respectively. The method includes: Acquire irregular outer contour data of an irregular robot; The approximate outer contour data of the irregular outer contour data is calculated based on the convex hull algorithm; Based on the distance between the approximate outer contour data and the geometric center, the first radius of the regular robot is determined, and the first radius is used as the expansion radius to expand the radius of the multiple geometric centers respectively, thereby outputting multiple first electronic fences; Wherein, the first radius is the radius that is the largest distance from the geometric center in the approximate outer contour data.

7. The method of claim 1, wherein, The control terminals corresponding to the multiple robots perform electronic fence contact detection on the multiple second electronic fences, the method including: If d < (R1 + R2), the contact detection result is not empty; If d ≥ (R1 + R2), the contact detection result is empty; Where d is the real-time distance between the first robot and the second robot, R1 is the radius of the second electronic fence corresponding to the first robot, and R2 is the radius of the second electronic fence corresponding to the second robot.

8. The method of claim 1, wherein, The control terminal is a distributed edge computing unit deployed locally on the robot, used for real-time processing of electronic fence data and obstacle avoidance decisions.

9. A multi-robot distributed control system for a construction site, characterized by, The system is used to implement the multi-robot distributed control method for construction sites according to any one of claims 1 to 8, wherein the system comprises: The information acquisition module is used to acquire multiple static geometric shape information of multiple robots distributed in the construction area; The fence determination module is used to analyze the multiple static geometric morphology information according to the geometric modeling algorithm, determine multiple geometric centers, perform electronic fence modeling based on the multiple geometric centers to determine multiple first electronic fences, and pre-store the first electronic fences to the control terminals corresponding to the multiple robots respectively. The fence update module is used by the control terminal to identify multiple real-time motion states of the multiple robots, and update the first electronic fence according to multiple dynamic geometric shape information corresponding to the multiple real-time motion states to obtain multiple second electronic fences; the obstacle avoidance control module is used by the control terminals corresponding to the multiple robots to perform electronic fence contact detection on the multiple robots according to the multiple second electronic fences. If the contact detection return result is not empty, the group of robots with collision risk is identified, and obstacle avoidance control is performed on the group of robots with collision risk.

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