Method for collaborative spraying and fault self-recovery of pressure vessel based on multi-robot formation

Abstract

The application relates to the fields of intelligent manufacturing and multi-agent collaborative control, and discloses a pressure container collaborative spraying and fault self-recovery method based on multi-robot formation, three-dimensional geometric information of the pressure container is acquired, a to-be-sprayed surface is divided into topological operation units and distributed to spraying robots in the formation; each spraying robot periodically uploads state parameter data for synchronous scheduling of a central controller; a dynamic safety interval is calculated according to a spraying robot movement speed, when a conflict risk is predicted, a movement time sequence, a speed or a local path is adjusted to perform active avoidance; an abnormal state is detected in real time to determine an unfinished breakpoint area, a replacement cost is calculated based on path distances of available candidate spraying robots, paint remaining amount and current load health degree to select a replacement robot; the replacement robot sets a backtracking overlapping section before the unfinished breakpoint area, so that spraying gun flow is gradually recovered from zero to full operation flow and then spraying is continued.

Description

Technical Field

[0001] This invention relates to the field of intelligent manufacturing and multi-agent collaborative control technology, specifically to a method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formations. Background Technology

[0002] Pressure vessels and large storage and transportation containers typically require anti-corrosion or functional coatings on their outer surfaces. Due to the large size of pressure vessels and the presence of structural accessories such as pipes, manholes, and supports on their surfaces, single-robot spraying can result in frequent repositioning, long work cycles, and difficulty in ensuring continuous operation. To improve the efficiency of large-scale surface treatment, using multiple robots in parallel operation formations for collaborative spraying has become the main way in the industry to meet the coating needs of large equipment.

[0003] In existing multi-robot parallel spraying applications, the surface of the pressure vessel is usually pre-divided into several fixed working areas, and a fixed range of activity and execution order are assigned to each spraying robot. When multiple robots work in the same work scene, the system often sets a fixed static physical safety distance parameter. Each spraying robot independently executes the spraying instructions according to the pre-programmed trajectory, and when they get close to each other to the safety distance threshold, they rely on the basic distance judgment logic to trigger a stop or wait action, thereby maintaining the basic operational safety of the equipment in the shared space.

[0004] However, in actual operations, multiple painting robots need to share a limited and constrained three-dimensional work space. When the robots' trajectories intersect near the area boundary or complex attachments, existing technologies rely solely on fixed safety distances or simple stop-and-wait strategies, which cannot adapt to the changes in the robot's three-dimensional motion speed and the need for forward braking at different times. This spatial interference handling method causes robots to frequently stop abruptly when they approach each other, easily leading to spatial interference and deadlock shutdowns in confined spaces or when multiple devices converge simultaneously, making it impossible to maintain physical space utilization while ensuring the safety of parallel painting. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formation. This method solves the problems of collision interference easily occurring in the shared space during parallel spraying operations of multiple robots on large pressure vessels, and the lack of efficient task redistribution and smooth process connection mechanisms when a single robot malfunctions.

[0006] The first aspect of this invention provides a method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formation, the method being executed in a unified manner by a central controller, comprising:

[0007] The three-dimensional geometric information of the pressure vessel and the reachability of each spraying robot are obtained. The surface to be sprayed is divided into multiple topological operation units with spatial adjacency, and the topological operation units are assigned to the spraying robots in the formation.

[0008] Each painting robot uploads status parameter data to the central controller at a preset cycle. The central controller maintains the formation operation status based on the status parameter data and performs synchronous scheduling of each painting robot.

[0009] The central controller predicts the spatial position of each painting robot within the safe look-ahead time, calculates the corresponding dynamic safety interval based on the movement speed of the painting robot, and adjusts the movement sequence, movement speed, or local movement path of at least one painting robot when a conflict risk is predicted.

[0010] Real-time detection of abnormal states of each painting robot; when an abnormal state is detected, the corresponding unfinished breakpoint area is determined; the replacement price is calculated based on the path distance, paint balance and current load health of available candidate painting robots; and the candidate painting robot with the smallest replacement price is selected as the replacement robot to take over the unfinished breakpoint area.

[0011] The replacement robot sets a backtracking overlap section before the unfinished breakpoint area, so that the spray gun flow rate gradually recovers from zero to full working flow rate within the backtracking overlap section before continuing spraying.

[0012] Preferably, dividing the surface to be coated into multiple topological operation units with spatial adjacency specifically includes:

[0013] The working boundary is determined based on the geometric continuity characteristics of the outer surface of the pressure vessel and the natural boundary formed by structural attachments;

[0014] A robot kinematics model based on the DH parameter method is used to perform accessibility detection on each region within the work boundary, the surface to be sprayed is divided into multiple topological work units, and the area of ​​a single topological work unit is controlled within the range of 2 square meters to 8 square meters.

[0015] When the topology operation unit needs to be split, the area of ​​the sub-operation unit generated after splitting is controlled within the range of 2 square meters to 5 square meters, while the geometric complexity deviation between each sub-operation unit is controlled to not exceed 20%.

[0016] Preferably, the step of assigning the topology work unit to the painting robots within the formation specifically includes:

[0017] Select at least three parameters from the following: distance to reach, paint balance, current load health, lifting device travel time, or energy consumption to construct the allocation cost calculation rule;

[0018] The specific calculation logic of the allocation cost calculation rule is as follows: the shorter the arrival distance, the more paint remaining, the better the current load health, and the lower the moving time or energy consumption of the lifting device, the smaller the corresponding allocation cost value.

[0019] Calculate the allocation cost value of each painting robot corresponding to the current topology work unit, and preferentially allocate the topology work unit to the painting robot with the smaller allocation cost value.

[0020] Preferably, the central controller maintains the formation operation status based on the status parameter data and performs synchronous scheduling of each painting robot, specifically including:

[0021] The system compares the real-time paint balance of the painting robot with the paint load capacity, and compares the real-time energy status with the total energy status. When it is determined that the paint balance of a painting robot is less than 15% of the paint load capacity, or the energy status is less than 20% of the total energy status, the painting robot that does not meet the numerical conditions is removed from the new task candidate set, and the removed painting robot is allowed to continue to complete the finishing processing operation of the current local path.

[0022] Calculate the remaining working time of each painting robot in the current topology work unit. According to the principle of the shortest remaining working time, allocate the higher spatial passage priority to the painting robot that completes the current local task first, and issue an instruction to reduce the global speed limit of other painting robots that have not obtained higher priority to avoid spatial interference.

[0023] Preferably, the step of calculating the corresponding dynamic safety interval based on the movement speed of the painting robot and adjusting it when a conflict risk is predicted specifically includes:

[0024] Predict the spatial position of each painting robot within the safe look-ahead time based on the current spatial coordinates and three-dimensional motion velocity vector;

[0025] The composite three-dimensional motion velocity is obtained by calculating the scalar magnitude from the three-dimensional motion velocity vector of the painting robot;

[0026] The dynamic safety interval is obtained by adding the set basic safety distance value and the product value obtained by multiplying the synthetic three-dimensional motion speed by the safety look-ahead time. The basic safety distance value is set to 0.8 meters and the safety look-ahead time value is set to 0.5 seconds.

[0027] When the calculated Euclidean distance between any two painting robots is less than the sum of the dynamic safety intervals corresponding to the two painting robots, it is determined that there is a risk of conflict.

[0028] Preferably, adjusting the motion sequence, speed, or local motion path of at least one painting robot specifically includes:

[0029] When there is normal lifting space above the workspace, priority is assigned and the low-priority painting robot is controlled to lift vertically by 50 mm to 100 mm along the normal direction of the current work surface to perform a hovering action in place. After the high-priority painting robot passes through the conflict area, the low-priority painting robot is controlled to reset along the original path at a speed of 0.2 m / s and continue to work.

[0030] When the working space height is less than 0.5 meters or there is no normal lifting space, the low-priority painting robot is controlled to reduce its moving speed to 30% of its original working speed before entering the conflict area, and a temporary offset path that deviates more than 50 mm from the main conflict area is replanned to avoid it. After the high-priority painting robot passes, it returns to the original working trajectory.

[0031] When it is predicted that three or more painting robots will converge in the same spatial area, the painting robot that completes its current local task first is given higher priority according to the principle of the shortest remaining operation time. The global speed limit of non-emergency painting robots is temporarily reduced so that non-emergency painting robots form a waiting sequence outside the conflict area.

[0032] Preferably, abnormal states of each painting robot are detected in real time, and the judgment criteria include:

[0033] If no status parameter data for a painting robot is received for five consecutive upload cycles, a communication disconnection abnormality is determined to have occurred.

[0034] When the deviation of the real-time spraying pressure of a certain spraying robot from the preset process pressure value of the system exceeds 10%, it is determined that an abnormal spraying pressure state has occurred.

[0035] Preferably, the calculation of the replacement price based on the path distance, paint balance, and current load health of available candidate painting robots is specifically calculated as follows:

[0036] The input parameters for calculating the replacement price include the path distance from the end of the candidate painting robot to the fault breakpoint, the maximum allowable migration distance set by the system, the paint balance of the candidate painting robot, the paint load capacity of the candidate painting robot, the current load health penalty of the candidate painting robot, and the corresponding weight coefficient.

[0037] The longer the path distance of the candidate painting robot, the less paint remaining, or the worse the current load health, the larger the value of the current load health penalty item, and the larger the value of the calculated replacement price.

[0038] When multiple painting robots are detected to be in abnormal states at the same time, replacement robots are assigned in sequence according to the task priority of the unfinished breakpoint area and the replacement price value. During the assignment process, it is ensured that the same replacement robot can only take on one unfinished breakpoint area at any given time and must complete the finishing action of the current local path.

[0039] Preferably, the calculation process for the current load health status specifically includes:

[0040] The operating current, motor temperature, and end-effector vibration amplitude of the motors at each joint of the painting robot are collected in real time.

[0041] Calculate the ratio of the operating current to the preset rated maximum current, the ratio of the motor temperature to the preset rated maximum temperature, and the ratio of the end vibration amplitude to the preset rated maximum amplitude, respectively.

[0042] Assign corresponding weight coefficients to each ratio and perform a weighted sum to obtain the current load health value; wherein, the larger the weighted sum value, the worse the current load health is determined to be.

[0043] Preferably, the process of the replacement robot setting a backtracking overlap section before the unfinished breakpoint area and continuing spraying specifically includes:

[0044] The trajectory coordinates and area boundaries of the unfinished tasks in the pre-assigned tasks of the abnormal spraying robot are extracted and determined as the corresponding unfinished breakpoint areas.

[0045] The replacement robot backtracks 20 to 50 millimeters backward along the original spraying trajectory of the abnormal robot as the backtracking overlap section. From the point where the backtracking action stops at the backtracking overlap section, it moves forward along the original spraying trajectory. Within a 200-millisecond time window, it controls the spray gun flow rate to linearly increase from zero to full working flow rate.

[0046] When it is determined that the remaining paint of the replacement robot is insufficient to complete the painting task of all the unfinished breakpoint areas, the unfinished breakpoint areas are divided into multiple sub-breakpoint areas according to the maximum sustainable painting area, a replacement robot is assigned to each sub-breakpoint area, and an additional 5% trajectory overlap width is added at the boundary of adjacent sub-breakpoint areas.

[0047] Preferably, for circumferential segmented formation and collaborative scenarios involving large spherical tank-type pressure vessels with a diameter of 10 meters or more, the method further includes:

[0048] The surface to be sprayed is divided into multiple topological operation units along different longitude sectors, and a dynamic boundary buffer with a width of 0.3 meters is set between the topological operation units of adjacent longitude sectors.

[0049] When the difference in longitude between the ends of any two painting robots on the sphere is less than 5 degrees and the difference in latitude is less than 10 degrees, the low-priority painting robot is controlled to pause its feeding action and retreat 0.1 meters along the direction of the center of the sphere. The advance operation is resumed after the other painting robot passes.

[0050] When a fault occurs and the task is migrated across sectors, the candidate painting robot in the same or adjacent sectors is selected as the replacement robot. If the replacement path crosses other sectors, a temporary cross-sector channel is established and the painting robots on both sides of the cross-sector channel are coordinated to perform deceleration or waiting actions. The cross-sector channel is closed after the replacement robot has passed through.

[0051] This invention provides a method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formation. It has the following beneficial effects:

[0052] 1. This invention predicts the spatial position of each painting robot within a safe look-ahead time and calculates the dynamic safety interval based on the synthesized three-dimensional motion speed. Combined with active avoidance control logic such as normal lifting to perform in-situ hovering, deceleration and replanning temporary offset paths, and reducing the global speed limit, it avoids the risk of spatial interference when multiple robots meet in a shared work space, avoids frequent sudden stops of robots at the area boundary, and ensures the process safety and physical space utilization of multi-robot parallel painting operations.

[0053] 2. This invention divides the surface to be sprayed into topological operation units with spatial adjacency and constructs allocation cost calculation rules by integrating the robot's arrival distance, paint balance, and current load health. At the same time, it eliminates unqualified robot candidates based on periodically uploaded status parameter data and adjusts the global speed limit. This enables the resource allocation and global synchronous scheduling of multiple robots performing spraying tasks in formation, avoiding local downtime due to insufficient resources of a single device and maintaining the continuity of multi-robot operation.

[0054] 3. This invention calculates the replacement robot based on path distance, paint balance, and current load health when an abnormality is detected in the spraying robot, selects a replacement robot, and controls the replacement robot to backtrack along the original spraying trajectory to set a backtracking overlap section. This allows the spray gun flow rate to gradually recover from zero to full working flow rate when the backtracking action stops and moves forward. This enables the migration of spraying tasks in the unfinished breakpoint area when a single machine fails and exits, avoids defects such as missed spraying or sudden thickness changes at the direct connection of tasks, and ensures the consistency of coating thickness.

[0055] 4. This invention calculates the current load health status by weighting multi-dimensional sensor data such as motor current, temperature and end vibration. It can accurately quantify and evaluate the real-time physical limits of the equipment in complex and confined spaces. Compared with a single fault alarm, this quantitative evaluation mechanism makes the allocation and succession of tasks more scientific and reasonable, thereby significantly reducing the secondary failure rate during operation. Attached Figure Description

[0056] Figure 1 This is a flowchart illustrating the overall process of multi-robot formation collaborative operation according to the present invention.

[0057] Figure 2 This is a schematic diagram of the fault breakpoint task migration of the present invention;

[0058] Figure 3 This is a schematic diagram of the dynamic safety interval and active obstacle avoidance of the present invention. Detailed Implementation

[0059] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0060] Example:

[0061] The system implementing this method includes a central controller and multiple spraying robots. The multiple spraying robots form a parallel operation formation and establish a two-way communication connection with the central controller. Each spraying robot can collect and upload its own posture, movement speed, operation progress, spraying pressure, paint balance and energy status data to the central controller in real time. The pressure vessel is the object of operation, and its outer surface includes structural accessories such as cylinder, head, nozzle, manhole and support.

[0062] See attached document Figure 1 , Figure 1 This is a flowchart of a multi-robot formation collaborative operation according to an embodiment of the present invention. The method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formation is executed by a central controller and specifically includes steps S1 to S5.

[0063] Step S1: Obtain the three-dimensional geometric information of the pressure vessel and the reachability of each spraying robot, divide the surface to be sprayed into multiple topological operation units with spatial adjacency, and assign the topological operation units to the spraying robots in the formation.

[0064] In step S2, each painting robot uploads its pose, movement speed, work progress, paint balance, energy status, and painting pressure to the central controller at a preset cycle. The central controller maintains the formation operation status based on the uploaded information and performs synchronous scheduling of each painting robot.

[0065] Step S3: The central controller predicts the spatial position of each painting robot within the safe look-ahead time, calculates the dynamic safety interval based on the movement speed, and adjusts the movement sequence, movement speed, or local movement path of at least one painting robot when a conflict risk is predicted.

[0066] Step S4: Real-time detection of abnormal states of each painting robot. When an abnormal state is detected, the corresponding unfinished breakpoint area is determined. The replacement cost is calculated based on the path distance of available painting robots, paint balance, and load health. The painting robot with the lowest replacement cost is selected to take over the unfinished breakpoint area.

[0067] Step S5: Before the robot finishes the breakpoint area, it sets a backtracking overlap section so that the spray gun flow rate gradually recovers from zero to the working flow rate within the backtracking overlap section before continuing to spray.

[0068] Step S1 is further broken down into the following sub-steps:

[0069] Step S101: Obtain the three-dimensional geometric information of the pressure vessel by reading the computer-aided design model data or the point cloud data collected by the three-dimensional scanning equipment. The central controller extracts the position coordinates of the structural accessories on the outer surface of the pressure vessel. The structural accessories include the cylinder, head, nozzle, manhole and support. The central controller determines the working boundary of the spraying operation based on the geometric continuity characteristics of the outer surface of the pressure vessel and the natural boundary formed by the structural accessories.

[0070] In step S102, the central controller uses a robot kinematics model based on the DH parameter method to perform accessibility detection on each area within the work boundary. Combined with the work boundary, the surface to be sprayed is divided into multiple topological work units with spatial adjacency and within the reach of the spraying robot. The central controller controls the area of ​​a single topological work unit within the range of 2 square meters to 8 square meters. When a topological work unit in a certain area needs to be split up by two or more spraying robots to complete the spraying in sections, the central controller controls the area of ​​the sub-work units generated after splitting within the range of 2 square meters to 5 square meters, while controlling the geometric complexity deviation between each sub-work unit to not exceed 20%.

[0071] In step S103, when the central controller performs the initial task allocation, it constructs an allocation cost for each painting robot in the formation. The calculation indicators of the allocation cost include the distance from the end of the painting robot to the entrance point of the topology work unit, the paint balance of the painting robot, and the current load health of the painting robot. For painting robots equipped with a lifting platform or a moving guide rail with additional displacement device, the calculation indicators of the allocation cost also include the lifting device's movement time or energy consumption. The central controller selects at least three parameters from the distance, paint balance, current load health, and lifting device's movement time or energy consumption to construct the allocation cost calculation rules. The calculation logic of the allocation cost is: the shorter the distance, the more paint balance, the better the current load health, and the lower the lifting device's movement time or energy consumption, the smaller the corresponding allocation cost value. The central controller calculates the allocation cost value of each painting robot for the current topology work unit and prioritizes allocating the topology work unit to the painting robot with the smaller allocation cost value.

[0072] Step S2 is further broken down into the following sub-steps:

[0073] In step S201, after the painting robot starts the operation, it continuously uploads status parameter data to the central controller at a preset period of 50 milliseconds. The uploaded status parameter data specifically includes the current spatial pose of the painting robot, three-dimensional motion speed, operation progress, spraying pressure of the nozzle, paint balance in the paint tank, and energy status. The central controller receives all status parameter data and uses the status parameter data to update and maintain the overall operation status of the multi-robot formation in real time.

[0074] Furthermore, the status parameter data of the painting robot also includes the current load health status; the current load health status is obtained by comprehensively evaluating the real-time operating current, motor temperature and end-effector vibration frequency of each joint motor of the painting robot through a preset weighted algorithm; when the current or temperature exceeds the rated threshold, the health status value decreases and the corresponding health status penalty value increases.

[0075] Specifically, the current load health status (denoted as...) By acquiring the real-time operating current of the motors at each joint of the painting robot. Real-time motor temperature and the amplitude of the end vibration The specific calculation formula is as follows:

[0076] in, , , These are the system's preset maximum rated current, maximum rated temperature, and maximum rated vibration amplitude, respectively. , , The preset weighting coefficients are used, and they satisfy the following conditions: When the calculated The larger the value, the worse the load health of the painting robot, and the larger the corresponding current load health penalty value when calculating the replacement cost.

[0077] In step S202, the central controller dynamically evaluates the eligibility of each painting robot to undertake a new task based on the paint balance and energy status in the status parameter data. The central controller compares the real-time paint balance of the painting robot with the paint load, and compares the real-time energy status with the total energy status. When the central controller determines that the paint balance of a painting robot is less than 15% of the paint load, or determines that the energy status is less than 20% of the total energy status, the central controller removes the painting robot that does not meet the numerical conditions from the new task candidate set and prohibits the removed painting robot from undertaking the next topology operation unit. In order to ensure the continuity of the coating on the pressure vessel surface, the central controller retains the current execution authority of the removed painting robot and allows the removed painting robot to continue to complete the finishing processing operation of the current local path.

[0078] In step S203, the central controller, in conjunction with the remaining working time of each topology work unit, performs global timing and speed synchronization scheduling for the painting robots in the formation. Based on the work progress in the status parameter data, the central controller calculates the remaining working time of each painting robot in the current topology work unit. According to the calculation results of the remaining working time, the central controller dynamically adjusts the passage order and global speed limit of the painting robots in the shared work space. During the adjustment process, the central controller follows the principle of the shortest remaining task time and assigns higher spatial passage priority to the painting robot that completes the current local task first. For other painting robots that do not obtain higher priority, the central controller issues instructions to reduce the global speed limit of other painting robots. By using speed differences and the adjustment of passage order, spatial interference between multiple painting robots at the area boundary or intersection area is avoided.

[0079] See attached document Figure 3 , Figure 3 This is a schematic diagram of dynamic safety interval and active obstacle avoidance according to an embodiment of the present invention.

[0080] Step S3 is further broken down into the following sub-steps:

[0081] In step S301, after receiving the current spatial position and three-dimensional motion speed of multiple painting robots, the central controller predicts the spatial position of each painting robot within the safe look-ahead time based on the current spatial position coordinates and the three-dimensional motion speed vector. The safe look-ahead time parameter set by the central controller is 0.5 seconds.

[0082] In step S302, the central controller calculates the corresponding dynamic safety interval based on the three-dimensional movement speed of the painting robot. The formula for calculating the dynamic safety interval is:

[0083] in, Indicates dynamic safety interval. This indicates the basic safety distance, which is set at 0.8 meters. This represents the calculated composite 3D motion velocity of the painting robot, which is derived from the scalar value of the painting robot's 3D motion velocity vector. This indicates the safety look-ahead time, which is set to 0.5 seconds.

[0084] In step S303, the central controller calculates the Euclidean distance between any two painting robots in real time. The central controller compares the calculated Euclidean distance with the sum of the dynamic safety intervals corresponding to the two painting robots. When the Euclidean distance is less than the sum of the dynamic safety intervals corresponding to the two painting robots, the central controller determines that there is a risk of conflict between the two painting robots.

[0085] In step S304, when the central controller predicts a conflict risk, it adjusts the motion sequence, speed or local motion path of the relevant painting robot according to the physical conditions of the workspace, and controls the painting robot to perform active avoidance operation.

[0086] The central controller assigns priority to painting robots with conflict risk based on the principle of shortest remaining operation time. When there is normal lifting space above the work area, the central controller issues a command to control the low-priority painting robot to lift vertically by 50 mm to 100 mm along the normal direction of the current work surface, and controls the low-priority painting robot to perform a hovering action in the current position. After the high-priority painting robot passes through the conflict area, the central controller controls the low-priority painting robot to reset along the original path at a speed of 0.2 m / s, and recalibrates the spray gun posture to continue the painting operation.

[0087] When the working space height is less than 0.5 meters or there is no normal lifting space, the central controller issues a command to control the low-priority painting robot to decelerate before entering the conflict area, reducing the moving speed to 30% of the original working speed. The central controller replans a temporary offset path for the low-priority painting robot in a local area. The temporary offset path deviates from the main conflict area by more than 50 mm. After the high-priority painting robot passes, the low-priority painting robot returns to the original working trajectory to continue working.

[0088] When the central controller predicts that three or more painting robots will converge in the same spatial area, the central controller dynamically determines the passing order of the relevant painting robots according to the principle of the shortest remaining operation time. The central controller sets the painting robot that completes the current local task first as a higher priority, and at the same time temporarily reduces the global speed limit of non-emergency painting robots, so that non-emergency painting robots form a waiting sequence outside the conflict area to avoid congestion.

[0089] See attached document Figure 2 , Figure 2 This is a schematic diagram of fault breakpoint task migration according to an embodiment of the present invention.

[0090] Step S4 is further broken down into the following sub-steps:

[0091] Step S401: The central controller monitors the working status of each painting robot in the formation in real time and determines whether the painting robot has an abnormal state. The judgment indicators for the abnormal state include communication status indicators and process pressure indicators. When the central controller does not receive status parameter data of a certain painting robot for 5 consecutive upload cycles, the central controller determines that a communication loss abnormal state has occurred. When the central controller detects that the real-time painting pressure of a certain painting robot deviates from the preset process pressure value of the system by more than 10%, the central controller determines that a painting pressure abnormal state has occurred.

[0092] Step S402: When the central controller detects that the painting robot is in an abnormal state, the central controller immediately stops the action command of the abnormal painting robot and extracts the trajectory coordinates and area boundaries of the pre-assigned tasks of the abnormal painting robot that have not yet been completed. The central controller determines the trajectory coordinates and area boundaries of the uncompleted tasks as the corresponding uncompleted breakpoint areas.

[0093] Step S403: The central controller calculates the replacement price for candidate painting robots in a healthy and usable state within the formation, based on the candidate painting robot's path distance, paint balance, and load health. The formula for calculating the replacement price is as follows:

[0094] in, This indicates the numerical result of the substitution price calculation. This represents the path distance from the end effector of the candidate painting robot to the fault breakpoint. This indicates the maximum allowed migration distance set by the system. This indicates the remaining paint level for the candidate painting robot. This indicates the paint load capacity of the candidate painting robot. This indicates the current load health penalty for the candidate painting robot. , , To calculate the weighting coefficients and , , The sum of their values ​​is 1.

[0095] In the evaluation logic of replacement price, the longer the path distance of the candidate painting robot, the less paint remaining, or the worse the current load health, the larger the value of the current load health penalty item, and the larger the calculated replacement price value. After the central controller completes the cost calculation of all candidate painting robots, it sorts the values ​​and selects the candidate painting robot with the smallest replacement price value as the replacement robot, which takes over the painting task of the unfinished breakpoint area.

[0096] In step S404, when the central controller detects that multiple painting robots are in abnormal states at the same time, the central controller extracts multiple corresponding unfinished breakpoint areas. The central controller assigns a replacement robot to each unfinished breakpoint area in turn according to the task priority order of the unfinished breakpoint areas and the replacement cost value evaluation. During the assignment process, the central controller ensures that the same replacement robot can only take on one unfinished breakpoint area at a time. Before accepting a newly assigned unfinished breakpoint area task, the replacement robot must continue to execute and complete the finishing action of the current local path to prevent frequent task switching from causing new coating seam defects.

[0097] Step S5 is further broken down into the following sub-steps:

[0098] In step S501, after receiving the coordinates of the unfinished breakpoint area, the replacement robot controls the robotic arm of the replacement robot to move to the location where the fault occurred. In order to avoid the phenomenon of missed spraying caused by direct task connection, the replacement robot does not start spraying directly at the breakpoint of the unfinished breakpoint area. The replacement robot backtracks 20 mm to 50 mm backward along the original spraying trajectory of the abnormal robot. The central controller sets the backward backtracking path segment as the backtracking overlap segment and sets the stop point of the backtracking action as the starting point for the replacement robot to continue spraying.

[0099] In step S502, the replacement robot starts working from the starting point and moves forward along the original spraying trajectory. At the same time, it implements flow compensation control for the spray gun within the backtracking overlap section. The replacement robot controls the spray gun flow to increase linearly from zero to full working flow within a 200-millisecond time window. The linearly increased spray gun flow ensures that the coating newly sprayed by the replacement robot and the old coating left by the abnormal robot are smoothly connected within the backtracking overlap section, avoiding sudden changes in coating thickness in the incomplete breakpoint area.

[0100] In step S503, the central controller compares the remaining paint of the replacement robot with the spraying demand of the unfinished breakpoint area in real time. When the central controller determines that the remaining paint of the replacement robot is insufficient to complete the spraying task of all unfinished breakpoint areas, the central controller divides the unfinished breakpoint area into multiple sub-breakpoint areas according to the maximum sustainable spraying area of ​​the replacement robot. The central controller re-evaluates and assigns subsequent replacement robots to each sub-breakpoint area. Each replacement robot starts working from its corresponding starting point. The central controller adds an extra 5% trajectory overlap width at the boundary of adjacent sub-breakpoint areas to compensate for the coating seam thickness error caused by the division of the unfinished breakpoint area.

[0101] For circumferential segmented formation and collaborative scenarios of large spherical pressure vessels with a diameter of 10 meters or more, the following adaptation method can be adopted based on the above general method: The central controller divides the surface to be painted into multiple topological operation units along different longitude sectors, and sets a dynamic boundary buffer with a width of 0.3 meters between the topological operation units of adjacent longitude sectors. When it is detected that the longitude difference between the ends of any two painting robots on the spherical surface is less than 5 degrees and the latitude difference is less than 10 degrees, the lower priority painting robot is controlled to pause its feeding action and retreat 0.1 meters along the direction of the center of the sphere. After another painting robot passes, it resumes its advance. When a fault occurs and the task is migrated across sectors, the candidate painting robot in the same sector or adjacent sector is selected first to take over. If it is necessary to cross other sectors, the central controller temporarily establishes a cross-sector channel, coordinates the painting robots on both sides to slow down or wait, and closes the cross-sector channel and resumes normal operation after the replacement robot passes.

[0102] For the inverse kinematics solution of the painting robot arm and the specific control program for precise adjustment of the spray gun flow, those skilled in the art can make conventional selections and configurations based on existing technologies. The underlying technical implementation methods are well-known technologies in this field and will not be elaborated here.

[0103] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formation, wherein the method is executed in a unified manner by a central controller, characterized in that... Includes the following steps: Step S1: Obtain the three-dimensional geometric information of the pressure vessel and the reachable range of each spraying robot, divide the surface to be sprayed into multiple topological operation units with spatial adjacency, and assign the topological operation units to the spraying robots in the formation. In step S2, each painting robot uploads status parameter data to the central controller at a preset cycle. The central controller maintains the formation operation status based on the status parameter data and performs synchronous scheduling of each painting robot. Step S3: The central controller predicts the spatial position of each painting robot within the safe look-ahead time, calculates the corresponding dynamic safety interval based on the movement speed of the painting robot, and adjusts the movement sequence, movement speed or local movement path of at least one painting robot when a conflict risk is predicted. Step S4: Real-time detection of abnormal states of each painting robot. When an abnormal state is detected, the corresponding unfinished breakpoint area is determined. The replacement price is calculated based on the path distance, paint balance and current load health of available candidate painting robots. The candidate painting robot with the smallest replacement price value is selected as the replacement robot to take over the unfinished breakpoint area. Step S5: The replacement robot sets a backtracking overlap section before the unfinished breakpoint area, so that the spray gun flow rate of the replacement robot gradually recovers from zero to full working flow rate within the backtracking overlap section before continuing to spray.

2. The method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formation according to claim 1, characterized in that, In step S1, the surface to be sprayed is divided into multiple topological operation units with spatial adjacency relationships, specifically including: The working boundary is determined based on the geometric continuity characteristics of the outer surface of the pressure vessel and the natural boundary formed by structural attachments; A robot kinematics model based on the DH parameter method is used to perform accessibility detection on each region within the work boundary, the surface to be sprayed is divided into multiple topological work units, and the area of ​​a single topological work unit is controlled within the range of 2 square meters to 8 square meters. When the topology operation unit needs to be split, the area of ​​the sub-operation unit generated after splitting is controlled within the range of 2 square meters to 5 square meters, while the geometric complexity deviation between each sub-operation unit is controlled to not exceed 20%.

3. The method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formation according to claim 1, characterized in that, In step S1, assigning the topology work unit to the painting robots within the formation specifically includes: Select at least three parameters from the following: distance to reach, paint balance, current load health, lifting device travel time, or energy consumption to construct the allocation cost calculation rule; The specific calculation logic of the allocation cost calculation rule is as follows: the shorter the arrival distance, the more paint remaining, the better the current load health, and the lower the moving time or energy consumption of the lifting device, the smaller the corresponding allocation cost value. Calculate the allocation cost value of each painting robot corresponding to the current topology work unit, and preferentially allocate the topology work unit to the painting robot with the smaller allocation cost value.

4. The method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formation according to claim 1, characterized in that, In step S2, the central controller maintains the formation operation status based on the status parameter data and performs synchronous scheduling of each painting robot, specifically including: The real-time paint balance of the spraying robot is compared with the paint load, and the real-time energy status is compared with the total energy status. When it is determined that the paint balance of a certain spraying robot is less than 15% of the paint load, or the energy status is less than 20% of the total energy status, the spraying robot that does not meet the numerical conditions is disqualified from undertaking the new topology operation unit, and is only allowed to continue to complete the finishing processing operation of the current local path. Calculate the remaining working time of each painting robot in the current topology work unit. According to the principle of the shortest remaining working time, allocate the higher spatial passage priority to the painting robot that completes the current local task first, and issue an instruction to reduce the global speed limit of other painting robots that have not obtained higher priority to avoid spatial interference.

5. The method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formation according to claim 1, characterized in that, In step S3, the corresponding dynamic safety interval is calculated based on the movement speed of the painting robot, and adjustments are made when a conflict risk is predicted. Specifically, this includes: Predict the spatial position of each painting robot within the safe look-ahead time based on the current spatial coordinates and three-dimensional motion velocity vector; The composite three-dimensional motion velocity is obtained by calculating the scalar magnitude from the three-dimensional motion velocity vector of the painting robot; The dynamic safety interval is obtained by adding the set basic safety distance value and the product value obtained by multiplying the synthetic three-dimensional motion speed by the safety look-ahead time. The basic safety distance value is set to 0.8 meters and the safety look-ahead time value is set to 0.5 seconds. When the calculated Euclidean distance between any two painting robots is less than the sum of the dynamic safety intervals corresponding to the two painting robots, it is determined that there is a risk of conflict.

6. The method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formation according to claim 1, characterized in that, In step S3, adjusting the motion sequence, speed, or local motion path of at least one painting robot specifically includes: When there is normal lifting space above the workspace, priority is assigned and the low-priority painting robot is controlled to lift vertically by 50 mm to 100 mm along the normal direction of the current work surface to perform a hovering action in place. After the high-priority painting robot passes through the conflict area, the low-priority painting robot is controlled to reset along the original path at a speed of 0.2 m / s and continue to work. When the working space height is less than 0.5 meters or there is no normal lifting space, the low-priority painting robot is controlled to reduce its moving speed to 30% of its original working speed before entering the conflict area, and a temporary offset path that deviates more than 50 mm from the main conflict area is replanned to avoid it. After the high-priority painting robot passes, it returns to the original working trajectory. When it is predicted that three or more painting robots will converge in the same spatial area, the painting robot that completes its current local task first is given higher priority according to the principle of the shortest remaining operation time. The global speed limit of non-emergency painting robots is temporarily reduced so that non-emergency painting robots form a waiting sequence outside the conflict area.

7. The method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formation according to claim 1, characterized in that, In step S4, abnormal states of each painting robot are detected in real time, and the judgment conditions include: If no status parameter data for a painting robot is received for five consecutive upload cycles, a communication disconnection abnormality is determined to have occurred. When the deviation of the real-time spraying pressure of a certain spraying robot from the preset process pressure value of the system exceeds 10%, it is determined that an abnormal spraying pressure state has occurred.

8. The method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formation according to claim 1, characterized in that, In step S4, the replacement cost is calculated based on the path distance, paint balance, and current load health of available candidate painting robots. The specific calculation logic is as follows: The input parameters for calculating the replacement price include the path distance from the end of the candidate painting robot to the fault breakpoint, the maximum allowable migration distance set by the system, the paint balance of the candidate painting robot, the paint load capacity of the candidate painting robot, the current load health penalty of the candidate painting robot, and the corresponding weight coefficient. The longer the path distance of the candidate painting robot, the less paint remaining, or the worse the current load health, the larger the value of the current load health penalty item, and the larger the value of the calculated replacement price. When multiple painting robots are detected to be in an abnormal state at the same time, replacement robots are assigned in sequence according to the task priority order of the unfinished breakpoint area and the replacement price value. During the assignment process, it is ensured that the same replacement robot can only take on one unfinished breakpoint area at any given time and must complete the finishing action of the current local path. The calculation process for the current load health status specifically includes: The operating current, motor temperature, and end-effector vibration amplitude of the motors at each joint of the painting robot are collected in real time. Calculate the ratio of the operating current to the preset rated maximum current, the ratio of the motor temperature to the preset rated maximum temperature, and the ratio of the end vibration amplitude to the preset rated maximum amplitude, respectively. Assign corresponding weight coefficients to each ratio and perform a weighted sum to obtain the current load health value; wherein, the larger the weighted sum value, the worse the current load health is determined to be.

9. The method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formation according to claim 1, characterized in that, In step S5, the process of the replacement robot setting a back overlap section before the unfinished breakpoint area and continuing spraying specifically includes: Extract the trajectory coordinates and area boundaries of the pre-assigned tasks of the painting robot that have not yet been completed in the abnormal state and determine them as the corresponding unfinished breakpoint areas; The replacement robot reverses the original spraying trajectory of the spraying robot that experienced the abnormal state by 20 to 50 millimeters as the reverse overlap section. From the point where the reverse reverse action stops at the reverse overlap section, it moves forward along the original spraying trajectory and controls the spray gun flow rate to linearly increase from zero to full working flow rate within a 200-millisecond time window. When it is determined that the remaining paint of the replacement robot is insufficient to complete the painting task of all the unfinished breakpoint areas, the unfinished breakpoint areas are divided into multiple sub-breakpoint areas according to the maximum sustainable painting area, a replacement robot is assigned to each sub-breakpoint area, and an additional 5% trajectory overlap width is added at the boundary of adjacent sub-breakpoint areas.

10. The method for collaborative spraying and fault self-recovery of pressure vessels based on multi-robot formation according to claim 1, characterized in that, For circumferential segmented formation and collaborative scenarios involving large spherical pressure vessels with a diameter of 10 meters or more, the method further includes: The surface to be sprayed is divided into multiple topological operation units along different longitude sectors, and a dynamic boundary buffer with a width of 0.3 meters is set between the topological operation units of adjacent longitude sectors. When the difference in longitude between the ends of any two painting robots on the sphere is less than 5 degrees and the difference in latitude is less than 10 degrees, the low-priority painting robot is controlled to pause its feeding action and retreat 0.1 meters along the direction of the center of the sphere. The advance operation is resumed after the other painting robot passes. When a fault occurs and the task is migrated across sectors, the candidate painting robot in the same or adjacent sectors is selected as the replacement robot. If the replacement path crosses other sectors, a temporary cross-sector channel is established and the painting robots on both sides of the cross-sector channel are coordinated to perform deceleration or waiting actions. The cross-sector channel is closed after the replacement robot has passed through.

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