Method for coordinated operation of multiple gantry cranes at a distance

Abstract

The application relates to the technical field of crane control and discloses a remote distance multi-gantry crane cooperative operation method, which comprises the following steps: constructing a global coordinate system; acquiring position data of dynamic equipment of each crane in real time and mapping the position data to the global coordinate system to form an equipment coordinate set; synchronously processing all the equipment coordinates through a central processor to generate a position sharing data set; simultaneously collecting environmental obstacle data and mapping the environmental obstacle data to the global coordinate system to establish a space constraint condition; generating a first path scheme by using a cooperative planning algorithm based on the position sharing data and the space constraint condition; monitoring a running deviation in real time during execution, and obtaining an optimized second path scheme through deviation correction; and finally, dynamically monitoring environmental changes, triggering obstacle avoidance path updating when a preset threshold is exceeded, and outputting a cooperative operation scheme. The method disclosed by the application realizes multi-crane cooperative path planning and dynamic obstacle avoidance under a cross-space scale, reduces conflict risks, and improves operation continuity and safety.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of crane control, in particular to a method for cooperative operation of multiple gantry cranes at a long distance. BACKGROUND

[0002] In large-scale engineering construction (such as port loading and unloading, nuclear power installation, bridge prefabrication, etc.), multiple (≥3) gantry cranes often need to be cooperatively operated in a long-distance (>1km) and cross-region scenario. Each crane relies on an independent local coordinate system, which makes it impossible to directly correlate the cross-machine position data. When the operation radius exceeds 500 meters, the coordinate conversion error accumulates to more than ±0.5m, causing path conflicts or lifting deviations. In addition, the path planning mostly uses a static map preloading mode, which requires manual updating of obstacle data. When temporary cargo (such as a sudden stack of containers) or sudden wind speed changes cause the boom to swing, the system cannot adaptively adjust the path, resulting in downtime and waiting. In actual operation of the crane, systematic shifts (such as a 0.3m lateral shift after 10m of gantry walking) may occur due to track settlement and load deformation. The traditional method needs to recalculate the path globally, which takes more than 30 seconds and interrupts the operation process. Therefore, due to the large spatial span and high equipment dynamics, path conflicts, obstacle avoidance failures, and poor real-time performance are caused. SUMMARY

[0003] Therefore, the purpose of the present application is to solve the problem of path conflicts, obstacle avoidance failures, and poor real-time performance caused by the large spatial span and high equipment dynamics in the cooperative operation of multiple gantry cranes at a long distance in the prior art, and to provide a method for cooperative operation of multiple gantry cranes at a long distance, which realizes multi-machine cooperative path planning and dynamic obstacle avoidance across spatial scales, reduces conflict risks, and improves operation continuity and safety.

[0004] To solve the above technical problems, the present application provides a method for cooperative operation of multiple gantry cranes at a long distance, comprising:

[0005] constructing a global coordinate system;

[0006] obtaining real-time position data of the gantry crane including dynamic equipment, mapping the real-time position data to the global coordinate system, and obtaining a set of equipment coordinates;

[0007] synchronously transmitting the set of equipment coordinates of all gantry cranes to a central processor to obtain a set of position sharing data;

[0008] obtaining obstacle position data in the operation environment, mapping the obstacle position data to the global coordinate system, and obtaining spatial constraints;

[0009] The position sharing dataset and the space constraint condition are combined to perform cooperative path planning on the multiple gantry cranes to obtain a first path scheme;

[0010] The first path scheme is run, and running deviations of the dynamic devices are obtained. The first path scheme is corrected based on the running deviations to obtain a second path scheme;

[0011] The second path scheme is run, and environmental changes of the working environment are monitored. If the monitored environmental changes exceed a preset threshold, an obstacle avoidance path update is triggered to obtain a cooperative working scheme of the multiple gantry cranes at a long distance.

[0012] Preferably, a global coordinate system is constructed, including: obtaining initial position data of the multiple gantry cranes, extracting physical coordinates of local origins of the gantry cranes in a global space from the initial position data; calculating minimum distances between devices and standard deviations of coordinates in each direction according to the physical coordinates; determining whether the distribution of the multiple gantry cranes meets a preset uniformity condition according to the minimum distances and the standard deviations of the coordinates in each direction; if the uniformity condition is met, calculating an average of all the physical coordinates as an origin of the global coordinate system; if the uniformity condition is not met, calculating a weighted average of all the physical coordinates as the origin of the global coordinate system according to a preset weight; wherein the preset weight is determined according to a load capacity of the gantry crane.

[0013] Preferably, the uniformity condition includes: min ≥D* and ;

[0014] wherein D min represents the minimum distance between devices; D* represents a safety distance threshold; represents a standard deviation of X-direction coordinates; represents a standard deviation of Y-direction coordinates; represents a standard deviation threshold.

[0015] Preferably, the position sharing dataset and the space constraint condition are combined to perform cooperative path planning on the multiple gantry cranes to obtain a first path scheme, including:

[0016] Step 1: generating an initial path point sequence for each of the gantry cranes according to the device coordinate set and the space constraint condition;

[0017] Step 2: predicting multiple-machine motion trajectories in a future time period and detecting space conflicts and time conflicts according to the initial path point sequence and the position sharing dataset;

[0018] Step three: for the detected conflict gantry crane, determining crane priority according to load capacity of the gantry crane, executing adjustment strategy according to the crane priority, and obtaining temporary path point sequence;

[0019] Step four: combining the temporary path point sequence and space constraint condition, avoiding static obstacles by using path planning algorithm, avoiding dynamic obstacles by inserting deceleration path points or detour path points, and obtaining first path point sequence;

[0020] Step five: verifying the first path point sequence for conflict, returning to step two if the verification fails, iterating until the conflict is cleared, and obtaining the first path scheme.

[0021] Preferably, the adjustment strategy includes: freezing the path point adjustment authority of the crane with high crane priority; and inserting new path points for the crane with low crane priority.

[0022] Preferably, inserting new path points for the crane with low crane priority includes inserting at least three new path points, and the three new path points are uniformly distributed around the conflict area.

[0023] Preferably, the first path scheme is corrected based on the running deviation to obtain a second path scheme, including: analyzing the running deviation to obtain a deviation type; the deviation type includes a system deviation, a local deviation, and a dynamic deviation; and the first path scheme is corrected according to the deviation type to obtain a second path scheme.

[0024] For the system deviation, a global offset is calculated, and all path points in the first path scheme are translated and corrected by the global offset; for the local deviation, a compensation path point is inserted in the path segment corresponding to the local deviation; and for the dynamic deviation, a local obstacle avoidance planning is called to update the path segment corresponding to the dynamic deviation.

[0025] Preferably, the compensation path point is generated by a cubic spline curve.

[0026] Preferably, the environmental changes of the working environment are monitored, including: monitoring the Euclidean distance between the current position of the static obstacle and the initial position of the static obstacle; monitoring the minimum distance between the current position of the dynamic obstacle and the path point contained in the second path scheme; and monitoring the current speed change rate of the dynamic obstacle.

[0027] Preferably, if the Euclidean distance between the current position of the static obstacle and the initial position of the static obstacle exceeds 1.2-1.5 m, the minimum distance between the current position of the dynamic obstacle and the path point contained in the second path scheme exceeds 0.5-0.8 m, and the current speed change rate of the dynamic obstacle exceeds 0.1-0.3 m / s, any one of the three meets the obstacle avoidance path update.

[0028] The above technical solutions of the present application have the following beneficial effects compared with the prior art:

[0029] The remote multi-gantry crane cooperative operation method provided by the present application realizes multi-machine cooperative path planning and dynamic obstacle avoidance under cross-space scale, reduces conflict risk, and improves operation continuity and safety.

[0030] Among them, by constructing a global coordinate system to real-time position data mapping, and then to central processor centralized synchronization, the multiple gantry cranes originally dispersed in a hundred meters or even kilometers of operation range are unified to the same space-time reference, the local coordinate system error accumulation is eliminated, the global position data consistency is improved, and the data foundation for multi-machine cooperation is laid.

[0031] The device coordinates of all cranes are continuously aggregated to the central processor to form a position sharing data set, and any change in the position of any device is globally visible, avoiding "blind cooperation" and significantly reducing the collision risk caused by information lag.

[0032] In the path planning stage, the obstacle position data in the operation environment is mapped as a spatial constraint condition in the global coordinate system, and the environmental changes are continuously monitored in the running stage; when the environmental changes exceed the preset threshold, the obstacle avoidance path is updated, the closed-loop mechanism upgrades the traditional static pre-planning to dynamic self-adaptation, realizes the synchronous avoidance of static and dynamic obstacles, and guarantees the operation continuity.

[0033] After running the first path scheme, the running deviation of each dynamic device is collected in real time, including position deviation and time deviation, and a second path scheme is generated accordingly; if the environment changes again, the iteration update is performed again; the closed-loop process of "running-detection-correction-re-running" compresses the error correction time from the traditional tens of seconds to seconds, avoids global downtime recalculation, and significantly improves the operation efficiency and safety.

[0034] Through unified path planning in the global coordinate system, hard boundary restriction of spatial constraint conditions, and real-time deviation correction, the space-time conflicts between multiple machines and between devices and obstacles are systematically eliminated, and the conflict risk is close to zero. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to make the content of the present application more easily understood, the present application will be further described in detail below according to specific embodiments of the present application and in conjunction with the drawings, in which:

[0036] Figure 1 The flowchart of the remote multi-gantry crane cooperative operation method in the preferred embodiment of the present application;

[0037] Figure 2A flow chart for constructing a global coordinate system in a preferred embodiment of the present application;

[0038] Figure 3 A flow chart for obtaining a first path scheme in a preferred embodiment of the present application. DETAILED DESCRIPTION

[0039] The present application will be further described below in conjunction with the drawings and specific embodiments, so that those skilled in the art can better understand the present application and implement it.

[0040] The purpose of the embodiment of the present application is to solve the problems of path conflict, obstacle avoidance failure and poor real-time performance caused by large space span and high equipment dynamicity when multiple gantry cranes work cooperatively at a long distance, and to provide a method for cooperative work of multiple gantry cranes at a long distance, to realize multi-machine cooperative path planning and dynamic obstacle avoidance under cross-space scale, to reduce conflict risk, and to improve work continuity and safety.

[0041] Embodiment one: refer to Figure 1 The embodiment of the present application discloses a method for cooperative work of multiple gantry cranes at a long distance, comprising:

[0042] S100, constructing a global coordinate system;

[0043] S200, obtaining real-time position data of the gantry crane including dynamic equipment, mapping the real-time position data to the global coordinate system, and obtaining a device coordinate set;

[0044] S300, synchronously transmitting the device coordinate sets of all gantry cranes to a central processor to obtain a position sharing data set;

[0045] S400, obtaining obstacle position data in the work environment, mapping the obstacle position data to the global coordinate system, and obtaining a space constraint condition;

[0046] S500, combining the position sharing data set and the space constraint condition, performing cooperative path planning for multiple gantry cranes, and obtaining a first path scheme;

[0047] S600, running the first path scheme, obtaining the running deviation of each dynamic equipment, correcting the first path scheme based on the running deviation, and obtaining a second path scheme;

[0048] S700, running the second path scheme, monitoring the environmental changes of the work environment, and if the monitored environmental changes exceed a preset threshold, triggering obstacle avoidance path update, and obtaining a cooperative work scheme of multiple gantry cranes at a long distance.

[0049] In a specific application scenario, when multiple gantry cranes are operating at a long distance, each uses a local coordinate system (origin usually located at the single machine base), and there is a lack of a unified global reference frame, which leads to the inability to directly correlate the position data of different cranes, causing coordinate system offset error accumulation, affecting the precision and safety of collaborative work; for example, the "origin (0, 0, 0)" of crane A and the "origin (0, 0, 0)" of crane B may be hundreds of meters apart in actual physical location, leading to position data conflicts when planning the path, and causing the risk of crane collision or overlapping of work areas when multiple cranes collaborate. Based on this, in the embodiment scheme of the present application, the initial position data of the base of each gantry crane is obtained through GPS positioning, and a global coordinate system is constructed according to the initial position data of the base of each gantry crane, realizing the unification of the spatial reference of multiple devices; the global coordinate system here is the same spatial reference system established for the collaborative work of multiple gantry cranes, unifying the reference frame, including defining the standard axis (usually X axis pointing to the east, Y axis pointing to the north, Z axis vertically upward) with the work area fixed point (such as the control tower) or the device group center as the origin (0, 0, 0). By constructing the global coordinate system, the multiple gantry cranes originally scattered in a work range of hundreds of meters or even kilometers are unified to the same space-time reference, eliminating the accumulation of local coordinate system errors and improving the consistency of global position data, laying a data foundation for multi-machine collaboration.

[0050] The position and state data of dynamic devices is the basis for realizing the safety and efficiency of gantry crane collaborative work, and the real-time position data of the dynamic devices of each gantry crane is obtained through multi-sensor fusion (inertial measurement unit IMU + laser radar + encoder), and the dynamic devices of the gantry crane refer to the components whose position or state changes dynamically during crane operation, including the hoist, the lifting mechanism, the trolley running mechanism, etc., and the hoist is the terminal component that directly carries the cargo, directly affecting the work precision and safety. The position data of the dynamic devices is the core input of path planning and conflict detection, for example, by monitoring the Z-axis height difference of each crane hoist in real time, vertical collision during lifting is avoided; the position change of the dynamic device needs to be combined with the load capacity weight to optimize the path priority, for example, a fully loaded crane prioritizes low-speed path planning. In order to accurately obtain the position of the dynamic device, high-precision sensors are configured, absolute value encoders monitor the drum angle and convert the length of the steel wire rope; laser range finders or encoders combined with track limit switches monitor the position of the trolley / car mechanism, and inclination sensors monitor the swing angle of the hoist to compensate for horizontal deviation.

[0051] Mapping the real-time position data to the global coordinate system obtains a device coordinate set. By mapping the real-time position data to the global coordinate system, the local position data of all devices is converted into a unified absolute coordinate, eliminating the cumulative error caused by the non-uniformity of the coordinate system, and ensuring the spatial consistency of the position data of multiple machines.

[0052] The local control of each gantry crane binds the obtained device coordinates with a timestamp and a crane ID, encapsulates them into a standard data packet, and transmits the compressed and encrypted data packet to the central processor using a DDS or TSN protocol to ensure the real-time performance and accuracy of multi-crane data transmission. Each crane sends a data packet to the central processor every 100 ms, and the bandwidth occupied by the compressed data is not more than 1 Mbps per crane. The central processor synchronizes the multi-crane data packets based on the timestamp to ensure that all data is based on the same time reference. The global coordinate system origin of each crane is checked for consistency with the central system reference, and the synchronized coordinate data is stored by crane ID to form a position sharing data set. The synchronized transmission of device coordinate sets to the central processor is the "nerve center" of the gantry crane cooperative operation, and its core value lies in converting dispersed multi-crane data into a globally unified real-time situational awareness capability, providing an irreplaceable data foundation for high-precision path planning, dynamic obstacle avoidance, and task coordination.

[0053] Obtaining obstacle position data in the working environment includes static obstacle data collection and dynamic obstacle data collection. Static obstacle data is collected by a laser scanner fixedly installed on the crane or around the working area to generate point cloud data of the working area. The physical coordinates of fixed obstacles such as buildings and pillars are also manually calibrated by a total station. The position data of moving objects such as vehicles and personnel are tracked in real time by multi-sensor fusion (visual camera + millimeter wave radar + UWB), and the real-time position and speed of mobile devices such as AGVs and trucks are collected by GPS / RTK. When mapping static obstacles, if the obstacle coordinates have been obtained by RTK-GPS or total station, they are directly converted to the global coordinate system. If the obstacle coordinates are obtained by point cloud data, the ICP (Iterative Closest Point) algorithm is used to align the local point cloud to the global coordinate system. When mapping dynamic obstacles, the GPS / RTK data of dynamic devices is directly superimposed on the global coordinate system offset. The dynamic targets detected by vision / radar are obtained by multi-sensor data fusion to obtain their global coordinates.

[0054] By constructing a global coordinate system to real-time position data mapping and then synchronizing to the central processor, the multiple gantry cranes originally dispersed in a working range of hundreds or even thousands of meters are unified to the same time and space reference, eliminating the accumulation of local coordinate system errors and improving the consistency of global position data, thereby laying a data foundation for multi-crane cooperation.

[0055] The spatial constraint condition refers to a set of three-dimensional space restriction rules formed by the position, shape, and motion state of static and dynamic obstacles in the environment of multiple gantry cranes working collaboratively, which is used to define the safety boundary and dynamic avoidance requirements that the crane and its sling must comply with during the operation process. Static obstacles (such as buildings, piers, and fixed equipment bases) define the space range they occupy through three-dimensional coordinates and geometric shapes (such as cuboids, cylinders, and irregular polygons); the crane sling and the surface of the static obstacle need to maintain a minimum safety distance to avoid collision risks. The position of dynamic obstacles (such as AGVs, transport vehicles, and personnel) changes over time, and their constraint conditions are defined by predicted trajectories; based on real-time speed and direction, linear extrapolation or kinematic models (such as uniform acceleration motion) are used to predict the position sequence in the future time period, and the minimum distance between the crane path point and the predicted trajectory of the dynamic obstacle needs to be greater than the safety threshold.

[0056] The real-time position coordinates, running state, and timestamp of each crane dynamic device are obtained from the position sharing dataset; the boundary coordinate set and safety distance threshold of static obstacles, the real-time position and predicted trajectory of dynamic obstacles, the minimum safety distance between cranes, and the priority rules are obtained according to the spatial constraint condition. Combined with the position sharing dataset and the spatial constraint condition, a path planning algorithm is used to collaboratively plan the paths of multiple gantry cranes, generating an initial path point sequence for each crane that meets the spatial constraint condition and obtains a first path solution. Global path planning is used to avoid physical collisions between cranes and between cranes and obstacles.

[0057] The central processor sends operation instructions (target position, speed, acceleration) to each crane controller according to the timestamp, and the crane servo system executes motion control to drive the sling, trolley, and car to move according to the first path solution, and obtains the real-time motion state of the crane, including real-time position, acceleration, and speed; the position deviation and time deviation of the real-time position from the corresponding path point in the first path solution are calculated, and the path point sequence in the first path solution is corrected according to the position deviation and time deviation to obtain a second path solution. Through real-time monitoring and correction, it is ensured that the actual motion trajectory of the crane is consistent with the planned path, and cumulative errors that may cause collisions or task failures are avoided.

[0058] The central processing unit sends operating instructions (target position, speed, acceleration) to each crane controller according to a timestamp. The crane servo system executes motion control, driving the spreader, trolley, and crane to move according to the second path scheme, and acquires the real-time motion status of the crane, including real-time position, acceleration, and speed. The latest positions of static obstacles in the work area are acquired through a laser scanner or vision camera, and the Euclidean distance between the current static obstacle position and the initial recorded position is calculated. The position and speed of moving objects are tracked in real time through multi-sensor fusion, and the minimum distance between dynamic obstacles and each path point in the second path scheme and the rate of change of dynamic obstacle speed are calculated to obtain an environmental change dataset. It is then determined whether the Euclidean distance between the current static obstacle position and the initial recorded position, the minimum distance between dynamic obstacles and each path point in the second path scheme, and the rate of change of dynamic obstacle speed exceed thresholds. When a threshold is detected, obstacle avoidance path updates are triggered, resulting in the final collaborative operation scheme.

[0059] After running the first path scheme, the operating deviations of each dynamic device are collected in real time, including positional deviations and time deviations, and a second path scheme is generated accordingly. If the environment changes again, it is iterated and updated again. This closed-loop process of "run-detect-correct-rerun" compresses the error correction time from tens of seconds to seconds, avoids global shutdown and recalculation, and significantly improves work efficiency and safety.

[0060] By using unified path planning in a global coordinate system, hard boundary constraints of spatial conditions, and real-time deviation correction, spatiotemporal conflicts between multiple machines and between equipment and obstacles are systematically eliminated, bringing the risk of conflict close to zero.

[0061] If the initial positions of the cranes are unevenly distributed (e.g., locally clustered or dispersed), simply taking the average of the physical coordinates as the origin will cause the origin to deviate from the actual work center, further amplifying the path planning error. Specifically, densely populated areas of cranes have an excessive impact on the origin, while sparse areas are ignored, resulting in significant deviations in path planning for cranes far from densely populated areas. During dynamic operations, the origin deviation accumulates over time, increasing the risk of collisions. Based on this, and referring to the above embodiments... Figure 2 As shown, constructing a global coordinate system includes: acquiring initial position data of multiple gantry cranes; extracting the physical coordinates of the local origin of all gantry cranes in the global space from the initial position data; calculating the minimum distance between the equipment and the standard deviation of coordinates in each direction based on the physical coordinates; determining whether the distribution of multiple gantry cranes meets the preset uniformity conditions based on the minimum distance and the standard deviation of coordinates in each direction: if it meets the uniformity conditions, the average value of all physical coordinates is calculated as the origin of the global coordinate system; if it does not meet the uniformity conditions, the weighted average value of all physical coordinates is calculated according to the preset weights as the origin of the global coordinate system; wherein, the preset weights are determined according to the load capacity of the gantry cranes.

[0062] In a specific application scenario, the initial position data of the portal crane refers to the three-dimensional coordinates of the base of the crane in the global space collected before the start of work, which is used as the initial input for constructing the global coordinate system, for subsequent calculation of device distribution and coordinate system origin. The origin of each crane local coordinate system (i.e., local origin) is mapped to the global coordinate system to obtain the physical coordinates in the global space. If the base of the crane is displaced due to wind or foundation settlement, the initial position data is updated. The minimum distance between devices is the minimum value of the three-dimensional Euclidean distance of the local origins of multiple portal cranes in the global space, i.e., the shortest spatial distance between any two cranes, which reflects the spatial closeness between the cranes and directly affects the coordinate system uniformity judgment. If the minimum distance is too small, the global origin needs to be optimized by weighted average to avoid local aggregation leading to coordinate system deviation. The coordinate standard deviation in each direction is the dispersion of the local origins of the cranes in the global space in the X, Y, and Z coordinate axis directions. The X-axis and Y-axis standard deviations reflect the dispersion of the cranes in the horizontal plane, and the Z-axis standard deviation reflects the height difference in the vertical direction. If the standard deviation in a certain direction is too large, it indicates that the cranes are unevenly distributed in that direction, and the origin position needs to be optimized by weighted average.

[0063] By mapping the local origin coordinates to the global coordinate system and selecting arithmetic mean or weighted mean to calculate the origin based on uniformity judgment, the local coordinate system deviation error is eliminated. When uniformly distributed, the arithmetic mean origin ensures balanced weight of each crane position, and the path planning deviation is <0.2m. When unevenly distributed, the load weight optimizes the origin position, and the path accuracy of high-load cranes is improved by more than 30% (positioning error is reduced from ±0.5m to ±0.3m). The global origin is updated regularly to adapt to the crane position drift caused by foundation settlement, wind influence, etc., and the long-term operation accuracy is maintained within ±0.2m.

[0064] Specifically, the uniformity condition includes: D min ≥D* and ;

[0065] wherein, D min represents the minimum distance between devices; D* represents the safety distance threshold, which is 5-10m; represents the X-direction coordinate standard deviation; represents the Y-direction coordinate standard deviation; represents the standard deviation threshold, which is 1-1.5m.

[0066] On the basis of the above embodiments, referring to Figure 3 , in combination with the position sharing data set and the spatial constraint condition, the collaborative path planning of multiple portal cranes is performed to obtain a first path scheme, including:

[0067] Step one: generate an initial path point sequence for each gantry crane according to the device coordinate set and the space constraint condition;

[0068] Step two: predict the multi-machine motion trajectory in the future time period according to the initial path point sequence and the position sharing data set, and detect space conflicts and time conflicts;

[0069] Step three: for the gantry crane with detected conflicts, determine the crane priority according to the load capacity of the gantry crane, execute the adjustment strategy according to the crane priority, and obtain a temporary path point sequence;

[0070] Step four: combine the temporary path point sequence and the space constraint condition, use the path planning algorithm to avoid static obstacles, and avoid dynamic obstacles by inserting deceleration path points or detour path points to obtain a first path point sequence;

[0071] Step five: verify the first path point sequence for conflicts, if it fails the verification, return to step two and iterate until the conflicts are cleared to obtain a first path solution.

[0072] In a specific application scenario, the sling of each crane is moved from the current position to the target work point, which meets the kinematic constraint and the space constraint condition, and the rapid expansion random number algorithm is used, with the key parameters set as the expansion step δ = 0.5m; the target bias probability p goal = 0.3 (guide the tree to grow towards the target point); the iteration number N = 1000 (ensure the convergence of the path). In the expansion process, nodes with a boundary distance from static obstacles less than a safety distance threshold are removed, nodes that may collide in the future ΔT time are removed according to the predicted trajectory of dynamic obstacles, and nodes with a distance from other crane path points less than a multi-machine safety distance are removed, to obtain an initial path point sequence.

[0073] Space conflict refers to the situation where the three-dimensional positions of the dynamic devices of multiple gantry cranes approach each other at a certain time or in a certain time period during operation, resulting in a minimum distance less than the multi-machine safety distance, which may cause a risk of physical collision. Specifically, if the coordinate difference between the slings of two cranes in X, Y and Z directions is less than the safety distance, it is determined as a space conflict. By detecting space conflicts, direct collisions between cranes or between cranes and fixed structures can be avoided, ensuring operation safety.

[0074] Time conflict refers to the state that multiple gantry cranes' dynamic devices are not only close in space (satisfy the space conflict condition) but also overlap in time dimension during the movement process, that is, two cranes reach the same space position or cross the path point in the same time period, resulting in a potential collision risk. Specifically, crane A reaches path point P1 at time t1, and crane B reaches path point P2 (spatially close to P1) at time t2. If the absolute value of t1-t2 is less than a preset time difference (such as 30 seconds), it is determined that there is a time conflict. By detecting the time conflict, dynamic collision caused by overlapping movement timing (such as rear-end collision or lateral impact of one crane due to delayed deceleration) is prevented.

[0075] When a space or time conflict is detected, the path of a low-priority crane is dynamically adjusted according to a pre-set crane priority to generate a new temporary path node sequence, so as to avoid the conflict and maintain the efficiency of multi-crane cooperation. The adjustment strategy includes: freezing the path point adjustment authority of a crane with high priority, ensuring that it is executed according to the original plan; inserting new path points for a crane with low priority, including inserting at least three new path points, and the three new path points are evenly distributed around the conflict area, guiding the low-priority crane to detour or decelerate. While ensuring the progress of high-priority tasks, the path adjustment cost of low-priority cranes is minimized to maintain overall work efficiency.

[0076] Inserting a deceleration path point: When a dynamic obstacle (such as a moving vehicle) or a time conflict risk is detected, a node with reduced speed is inserted at a specific position in the crane path, so that the crane decelerates in advance to avoid collision with the obstacle or high-priority crane. Specifically, a deceleration point is inserted before the conflict area to reduce the speed to a safe speed, thereby reducing the braking distance by reducing the speed to avoid load shaking or equipment impact caused by emergency stop.

[0077] Detour path point: In the overlapping area of static obstacles (such as newly added containers) or dynamic obstacle trajectories, a new node deviating from the original path is inserted to guide the crane to detour around the obstacle and re-plan a safe path.

[0078] After the path point is adjusted, the new path point sequence is re-detected for global or local collision risk to confirm whether there is still a space conflict, time conflict, and to ensure the safety and feasibility of the path scheme. Specifically, the minimum distance between all crane path points is recalculated, the movement of multiple cranes is simulated and estimated, and whether the time window overlap is eliminated is checked. Based on the latest obstacle position and speed prediction, it is confirmed whether the deceleration or detour path point effectively avoids the risk.

[0079] On the basis of the above embodiments, the first path scheme is corrected based on the running deviation to obtain a second path scheme, including: analyzing the running deviation to obtain a deviation type; the deviation type includes system deviation, local deviation and dynamic deviation; the first path scheme is corrected according to the deviation type to obtain the second path scheme; wherein, for the system deviation, a global offset is calculated, and all path points in the first path scheme are translated and corrected through the global offset; for the local deviation, a compensation path point is inserted in the path segment corresponding to the local deviation; and for the dynamic deviation, a local obstacle avoidance planning is called to update the path segment corresponding to the dynamic deviation.

[0080] In a specific application scenario, the deviation type refers to the difference type between the actual motion trajectory and the planned path when the multi-gantry crane executes the first path scheme, which is divided into three categories according to the deviation source and the influence range:

[0081] System deviation: global coordinate system origin drift, clock synchronization error or global positioning system overall deviation caused by multi-machine path global deviation; it is manifested that all cranes are offset in the same direction or distance, but the local trajectory shape is unchanged.

[0082] Local deviation: single-machine sensor noise, actuator hysteresis (such as motor response delay) or local environmental interference (such as wind causing the spreader to swing) caused by single crane path local deviation, which is manifested as path point jitter or deviation in local area, but the overall trend is unchanged.

[0083] Dynamic deviation: real-time path conflict caused by dynamic obstacles (such as AGV, personnel) moving or environmental changes (such as temporary stacking of goods), which is manifested as the intersection risk between the original planned path and the future trajectory of the dynamic obstacle, which needs to be dynamically adjusted to avoid the path.

[0084] The compensation path point is inserted in the path segment corresponding to the local deviation, the real-time position data is compared with the planned path to identify the path segment whose deviation exceeds the threshold (such as 0.2m), at least three new path points are inserted before and after the deviation segment by using cubic spline interpolation, and the path smooth transition is ensured: the interpolation point coordinates are calculated by local trajectory fitting, the jerk is less than or equal to 5m / s 3 , the interval between the inserted points is less than or equal to 0.5m, and the deviation area is covered. By inserting the compensation path point, the spreader swing or positioning jitter caused by sensor noise is suppressed, and the path smoothness is significantly improved.

[0085] Call local obstacle avoidance planning, update the path segment corresponding to the dynamic deviation: based on the dynamic obstacle prediction trajectory (linear extrapolation or Kalman filter), locate the path segment within the future time period AT intersecting with the crane path, insert a deceleration path point before the intersection point to reduce the speed to a safe speed, call the A* algorithm (A-Star Algorithm) to generate a sub-path that avoids the dynamic obstacle, and insert 3-5 new path points.

[0086] Wherein, the inserted compensation path points are generated by a cubic spline curve, which has specific physical meaning: first, the curve passes through all compensation points, ensuring that the path is not broken and the crane spreader moves strictly according to the planned trajectory, avoiding position jumps; second, the first derivative of the cubic spline curve is continuous, the tangent direction is smoothly transitioned, the velocity change rate is continuous, and the crane speed is not abrupt, reducing motor impact and load inertia force; third, the second derivative of the cubic spline curve is continuous, the curvature changes smoothly, and the jerk is limited, reducing mechanical structure stress, avoiding load swinging, and improving motion stability. In addition, only a small number of compensation points need to be inserted in the deviation segment, which has high calculation efficiency, quickly responds to local deviations, and does not affect the efficiency of global path planning.

[0087] On the basis of the above embodiments, the environmental changes of the working environment are monitored, including: monitoring the Euclidean distance between the current position of the static obstacle and the initial position of the static obstacle; monitoring the minimum distance between the current position of the dynamic obstacle and the path points contained in the second path scheme; monitoring the current velocity change rate of the dynamic obstacle.

[0088] In specific application scenarios, by monitoring the Euclidean distance between the current position of the static obstacle and the initial position of the static obstacle, it is determined whether the static obstacle has deviated due to external forces (such as wind, mechanical vibration) or human operation, avoiding the conflict between the crane path and the actual position of the obstacle, if the Euclidean distance between the current position of the static obstacle and the initial position of the static obstacle exceeds 1.2-1.5 m, the path re-planning is triggered to ensure the minimum safety distance between the crane and the obstacle.

[0089] By monitoring the minimum distance between the current position of the dynamic obstacle and the path points contained in the second path scheme, it is determined whether the dynamic obstacle invades the safety area of the crane, if the minimum distance between the current position of the dynamic obstacle and the path points contained in the second path scheme exceeds 0.5-0.8 m, the path re-planning is triggered to ensure that the crane path avoids the moving target in real time.

[0090] By continuously measuring the speed of the dynamic obstacle, the speed change amount of the dynamic obstacle in a unit time, i.e., a speed change rate, is calculated, a speed mutation (such as sudden acceleration or sudden deceleration) of the dynamic obstacle is identified, uncertainty of a future trajectory of the dynamic obstacle is predicted, and the crane is adjusted in advance to avoid obstacles; if the current speed change rate of the dynamic obstacle exceeds 0.1-0.3 m / s, it is determined that the speed is mutated, the obstacle avoidance path is updated, and the crane is suddenly stopped or drastically adjusted due to the trajectory mutation of the obstacle.

[0091] In summary, the remote multi-gantry crane cooperative operation method provided by the application realizes multi-crane cooperative path planning and dynamic obstacle avoidance under cross-space scales, reduces conflict risks, and improves operation continuity and safety.

[0092] Those skilled in the art will understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0093] The present application is described with reference to flowcharts and / or block diagrams according to the methods, devices (systems), and computer program products of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that carries out the functions specified in one or more flows and / or blocks.

[0094] These computer program instructions can also be stored in a computer-readable memory that can direct the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including instruction apparatus, which implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that carries out the functions specified in one or more flows and / or blocks.

[0095] These computer program instructions can also be loaded into a computer or other programmable data processing devices, so that a series of operational steps are performed on the computer or other programmable data processing devices to generate computer-implemented processes, thus the instructions executed on the computer or other programmable data processing devices provide processes for implementing the functions specified in the flowchart Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0096] Obviously, the above embodiments are only examples for clearly illustrating the present application, and are not intended to limit the embodiments. Based on the above description, other different forms of changes or variations can be made by those skilled in the art. Here, all the embodiments are not required to be exhausted, and the obvious changes or variations derived therefrom are still within the protection scope of the present application.

Claims

1. A method for coordinated operation of a plurality of gantry cranes at a distance, characterized in that The method comprises the following steps: The method comprises the following steps: acquiring initial position data of multiple portal cranes; extracting physical coordinates of local origins of the portal cranes in a global space from the initial position data; calculating minimum distances between devices and standard deviations of coordinates in each direction according to the physical coordinates; judging whether the distribution of the multiple portal cranes meets a preset uniformity condition according to the minimum distances and the standard deviations of the coordinates in each direction; if the uniformity condition is met, calculating an average value of all the physical coordinates as an origin of the global coordinate system; if the uniformity condition is not met, calculating a weighted average value of all the physical coordinates as the origin of the global coordinate system according to a preset weight; wherein the preset weight is determined according to a load capacity of the portal crane; and the uniformity condition comprises: D min ≥ D* and max ; D min represents the minimum distance between devices; D* represents a safety distance threshold; represents the standard deviation of the X-direction coordinates; represents the standard deviation of the Y-direction coordinates; represents a standard deviation threshold. Obtaining real-time position data of gantry cranes containing dynamic devices, mapping the real-time position data to the global coordinate system, and obtaining a device coordinate set; Synchronously transmitting the device coordinate sets of all gantry cranes to a central processor to obtain a position sharing data set; Obtaining obstacle position data in a working environment, mapping the obstacle position data to the global coordinate system, and obtaining a space constraint condition; Combining the position sharing data set and the space constraint condition, performing cooperative path planning on the gantry cranes to obtain a first path scheme; the cooperative path planning comprises the following steps: step 1, generating an initial path point sequence for each gantry crane according to the device coordinate set and the space constraint condition; step 2, predicting the motion trajectories of the gantry cranes in a future time period according to the initial path point sequence and the position sharing data set, and detecting space conflicts and time conflicts; step 3, for the gantry cranes with conflicts, determining crane priorities according to the load capacities of the gantry cranes, and performing an adjustment strategy according to the crane priorities to obtain a temporary path point sequence; step 4, combining the temporary path point sequence and the space constraint condition, avoiding static obstacles by using a path planning algorithm, and avoiding dynamic obstacles by inserting deceleration path points or detour path points to obtain a first path point sequence; and step 5, verifying the first path point sequence for conflicts, and if the verification fails, returning to step 2 and iterating until the conflicts are cleared to obtain the first path scheme; Running the first path scheme, obtaining running deviations of the dynamic devices, and correcting the first path scheme based on the running deviations to obtain a second path scheme; the method comprises the following steps: analyzing the running deviations to obtain a deviation type; the deviation type comprises a system deviation, a local deviation and a dynamic deviation; correcting the first path scheme according to the deviation type to obtain a second path scheme; for the system deviation, calculating a global offset, and performing a translation correction on all path points in the first path scheme by using the global offset; for the local deviation, inserting a compensation path point in a path segment corresponding to the local deviation; and for the dynamic deviation, calling a local obstacle avoidance planning to update a path segment corresponding to the dynamic deviation; Running the second path scheme and monitoring environmental changes of the working environment, and if the monitored environmental changes exceed a preset threshold, triggering an obstacle avoidance path update to obtain a cooperative working scheme of a plurality of gantry cranes at a long distance.

2. The method according to claim 1, c h a r a c t e r i z e d b y The adjustment strategy comprises freezing the path point adjustment authority of a crane with a high crane priority, and inserting a new path point for a crane with a low crane priority.

3. The method according to claim 2, c h a r a c t e r i z e d b y The insertion of the new path point for the crane with the low crane priority comprises inserting at least three new path points, and the three new path points are uniformly distributed around a conflict area.

4. The method for remote coordinated work of a plurality of portal cranes according to claim 1, characterized in that, The compensation path point is generated by a cubic spline curve.

5. The method for remote coordinated work of a plurality of portal cranes according to claim 1, characterized in that The method for monitoring the environmental changes of the working environment comprises the following steps: Monitoring the Euclidean distance between a current position of a static obstacle and an initial position of the static obstacle; Monitoring the minimum distance between a current position of a dynamic obstacle and a path point included in the second path scheme; The current speed change rate of the dynamic obstacle is monitored.

6. The method for remote coordinated work of a plurality of portal cranes according to claim 5, characterized in that, If the Euclidean distance between the current position of the static obstacle and the initial position of the static obstacle exceeds 1.2-1.5 m, the minimum distance between the current position of the dynamic obstacle and the path point included in the second path scheme exceeds 0.5-0.8 m, and the current speed change rate of the dynamic obstacle exceeds 0.1-0.3 m / s, any one of the three satisfies the condition, the obstacle avoidance path update is triggered.

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