Multi-machine cooperative mobile measurement robot path control method

Abstract

The invention discloses a multi-machine collaborative mobile measurement robot path control method, which belongs to the technical field of path planning, and specifically comprises the following steps: collecting surface height information of a target area, and binding the surface height information with geographic coordinates to generate a simplified three-dimensional model; based on the sun moving trajectory data in the current season, calculating an accumulated time length distribution diagram of receiving direct sunlight by each coordinate point on the ground in the current time period; dividing a high sunlight intensity region and a continuous shadow region according to the cumulative duration distribution diagram, and carrying out topological association on the coordinates of the target point to be measured and the continuous shadow region; establishing a dynamic path distribution protocol in a multi-robot communication network, enabling each robot to select a non-overlapping measurement path in a path network formed by continuous shadow areas according to a real-time position and a task queue, and updating a path occupation state through periodic broadcast; according to the invention, the path planning of the mobile measurement robot in the urban high-temperature environment is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of path planning, and in particular to a multi-machine collaborative mobile measurement robot path control method. Background Art

[0002] As global urbanization continues to accelerate, the demand for urban infrastructure construction and renovation is increasing, placing higher demands on refined surveying in urban areas. Traditional surveying methods, which primarily rely on manual mapping or fixed surveying equipment, are not only inefficient but also struggle to adapt to the complex and varied terrain and densely populated buildings of modern urban environments. Against this backdrop, mobile surveying robots, with their autonomous mobility, flexible deployment, and efficient operation, are becoming a crucial technology in urban surveying and mapping. In particular, mobile surveying robots demonstrate significant advantages in applications such as 3D modeling of large urban areas, municipal facility inspections, and road network mapping.

[0003] However, in actual application, mobile measurement robots face severe challenges in high-temperature environments in summer. When the robot works for a long time in an area exposed to direct sunlight, its internal electronic components and core sensors will cause the temperature to rise due to continuous heat accumulation. This may not only cause problems such as equipment performance degradation and measurement data drift, but in severe cases, it may even cause system failure or hardware damage. This problem is particularly prominent in southern my country, where high temperatures last for a long time in summer and the intensity of solar radiation is high. In addition, the heat island effect that is prevalent in urban environments further exacerbates the risk of equipment overheating. Therefore, how to effectively reduce the heat load of the equipment by optimizing the robot's movement path while ensuring the smooth completion of the measurement task has become a key issue that needs to be urgently addressed in the current development of mobile measurement robot technology. Summary of the Invention

[0004] The purpose of the present invention is to provide a multi-machine collaborative mobile measurement robot path control method to solve the following technical problems: When the robot's path is mostly in direct sunlight, it may affect the operation of the equipment.

[0005] The purpose of the present invention can be achieved through the following technical solutions: A multi-machine collaborative mobile measurement robot path control method includes the following steps: Collect surface height information of the target area and bind it to geographic coordinates to generate a simplified 3D model that includes building edges, tree canopies, and the tops of fixed equipment. Based on the sun's trajectory data for the current season, calculate the cumulative duration distribution of direct sunlight received by each coordinate point on the ground during the current time period; According to the cumulative duration distribution map, high sunshine intensity areas and continuous shadow areas are divided, and the coordinates of the target point to be measured are topologically associated with the continuous shadow area; A dynamic path allocation protocol is established in a multi-robot communication network, which enables each robot to select a non-overlapping measurement route in a path network consisting of continuous shadow areas according to its real-time position and task queue, and update the path occupancy status through periodic broadcasting.

[0006] As a further solution of the present invention: the generation process of the simplified three-dimensional model is: The surface height information of the target area is collected by a first robot and a second robot. The first robot moves along the centerline of the road and collects the vertical height profiles of the buildings on both sides. The second robot rotates and scans at a fixed point at the intersection to obtain the horizontal projection shape of the tree canopy. When using polygonal prisms for spatial fitting of building outlines, the bottom boundary of the prism is aligned with the building base in the satellite map, and the top height is corrected layer by layer based on the vertical scanning data; when calculating the minimum enclosing cone for the projected shape of the tree canopy, the bottom diameter of the cone is determined according to the maximum extension distance of the projection, and the vertex height is taken from the actual measured value of the highest point of the canopy; after superimposing the prism and cone models according to geographic coordinates, the spatial overlapping area between the models is detected, the redundant volume of the overlapping part of the prism and cone is deleted, and the independent structure is retained to form a three-dimensional spatial topological structure with object type identification.

[0007] As a further solution of the present invention: during the scanning process of the horizontal projection shape of the tree canopy, a multi-height layer scanning strategy is adopted for densely arranged tree groups, specifically: The first layer of scanning is performed on a plane below the height of the lowest branch of the crown to obtain the distribution position of the tree trunks and the outer contours of the tree group; the second layer of scanning is performed at the middle height of the crown to capture the extension direction of the main branches and the distribution of the canopy gaps; the third layer of scanning is performed at the height of the top of the crown to record the concave and convex characteristics of the canopy surface; based on the three-layer scanning data, a composite cone model is constructed, and the actual crown is decomposed into a superimposed structure of multiple sub-cones. The axis position of the sub-cone is offset according to the branch extension direction, and the bottom diameter is segmented according to the maximum extension value of the scan contour of each layer, so that the projection range of the combined model matches the actual shadow shape.

[0008] As a further solution of the present invention: the calculation process of the cumulative duration distribution graph is: The target area is divided into equally spaced grids, with each grid node associated with geographic coordinate information. For each grid node, the changing sequence of the sun's azimuth and altitude angles during the target time period is traversed. Based on the spatial position and shape parameters of each object in the 3D model, the time interval during which the node is covered by the projections of different objects is calculated. For the building prism model, parallel light is projected along the direction of the sun's azimuth angle, and a dynamic projection trajectory is generated based on the geometric parameters of the prism's side edges, and the coverage time of the projection trajectory on the ground grid nodes is recorded. For the tree cone model, the ground projection area is dynamically adjusted according to the geometric relationship between the cone apex angle and the solar altitude angle, and the fuzzy transition range of the projection edge is calculated in combination with the canopy density coefficient. The projection coverage time of each object is superimposed and counted according to the grid nodes to generate the cumulative time data of each node not covered by any projection, forming a ground illumination heat map that changes over time.

[0009] As a further solution of the present invention: in the process of generating the illumination heat map, real-time meteorological data is introduced to dynamically correct the projection calculation: when cloud coverage forecast appears in the target time period, the transmittance parameter is matched according to the cloud type code, and the cumulative duration data of the grid node is attenuated in the corresponding time interval; in response to sudden local cloud changes, the cloud movement speed and coverage range are obtained through the meteorological data interface, and the movement trajectory of the cloud projection is simulated in the three-dimensional model space. The projection is regarded as a temporary virtual object and added to the projection calculation queue, and is superimposed and analyzed with the original fixed object projection, and the cumulative duration data of the affected grid nodes is updated, triggering the reconstruction of the local heat map and the real-time adjustment of the path network.

[0010] As a further solution of the present invention: the process of topological association is: Virtual measurement path nodes are established within continuous shadow areas. The node spacing is dynamically adjusted based on the geometric shape of the shadow area. For strip-shaped shadow areas, main nodes are evenly spaced along their long axis, and oblique connecting branches are inserted between the main nodes. For measurement points that must pass through areas of high sunlight intensity, the distribution of surrounding shadow areas is analyzed, and multiple candidate connection paths are constructed between adjacent shadow areas. The path priority is adjusted based on the spatial relationship between the current solar altitude angle and the direction of the candidate paths. When the solar altitude angle exceeds the set critical value, the path segment in the connecting path that is perpendicular to the solar azimuth angle is selected as the priority route; when the solar altitude angle is lower than the critical value, the path segment in the connecting path that is consistent with the extension direction of the building projection is selected, and the temporary shadow coverage time window is associated for dynamic path switching.

[0011] As a further solution of the present invention: the construction of the candidate connection path specifically includes: The boundary directions of adjacent shadow areas in high-insolation areas are analyzed. When the extension trends of the boundaries of the two shadow areas meet the angle condition, a virtual shadow corridor is created in the intersection area of ​​the extension direction. The path validity duration of the virtual shadow corridor is calculated based on the relationship between the changing rate of the solar azimuth angle and the corridor direction. When the angle between the changing direction of the solar azimuth angle and the corridor direction decreases, the validity duration of the corridor is extended. When selecting the path, the virtual shadow corridor is topologically connected with the actual shadow area to generate a composite path that spans the sunlight area. Before the end of the corridor validity duration, a path failure warning is sent to the robot to trigger the dynamic switching of subsequent path segments.

[0012] As a further solution of the present invention: when the dynamic path allocation protocol is executed, each robot sends a path update message containing the shadow zone number of the current location, the task progress, and the request for the next target shadow zone to the central coordinator; the central coordinator maintains a global shadow zone occupancy status table, which records the current occupied robot identifier and expected release time of each shadow zone; When receiving entry requests from multiple robots to the same shadow area, the remaining task queue of each requesting robot is extracted, the number of continuous connections in the shadow area in its subsequent path is calculated, and robots with fewer shadow area connections are preferentially assigned to enter the target area; alternative path instructions are sent to robots that are not assigned. The alternative path is generated by the central coordinator by recombining the connection nodes of adjacent idle shadow areas according to the current shadow area occupancy status, and is accompanied by time synchronization information for path switching.

[0013] As a further solution of the present invention: the generation process of the alternative path instruction is: The central coordinator retrieves the set of currently unoccupied shadow areas, and searches for continuous path segments that meet the task progress requirements in the idle shadow areas based on the current position of the requesting robot and the distribution of the target points to be measured. When a continuous path cannot be formed in the idle shadow areas, the path bridging mode is activated to search for transition path segments that meet the temporary shadow coverage time window in the sunlit area. The selection of transition path segments is based on the geometric relationship between the current solar altitude angle and the height of surrounding buildings. The theoretical shadow coverage rate of the transition path segment within the specified time window is calculated, and only the sections with coverage that meet the standard are selected to be added to the alternative path sequence, forming a composite traffic route with mixed shadows and temporary shadow coverage.

[0014] Beneficial effects of the present invention: This invention effectively addresses the technical challenge of overheating for mobile measurement robots in high-temperature urban environments by combining multi-robot collaborative measurement with intelligent path planning. By innovatively capturing the vertical profiles of buildings and the horizontal projections of tree canopies, a simplified three-dimensional model with precise object type identification is constructed. Secondly, based on the sun's trajectory and the cumulative duration distribution map calculated from the three-dimensional model, the proposed method dynamically and accurately delineates ground shadow areas, overcoming the inaccurate projection calculations of irregular objects such as trees, often associated with existing techniques. Finally, through the establishment of a dynamic path allocation protocol and shadow area topology association mechanism, multiple robots can intelligently allocate shadow resources and plan non-overlapping measurement routes, effectively avoiding the conflicts and shadow resource competition inherent in traditional methods. In particular, the proposed method's multi-height tree scanning strategy and composite cone modeling significantly improve the accuracy of tree shade calculations. Innovative mechanisms such as virtual shadow corridors and path fallback compensation ensure optimal paths when crossing sunlit areas. The synergistic effect of these key technical features enables the measurement robots to minimize direct sunlight exposure while ensuring mission integrity, significantly reducing equipment thermal load and improving system stability. The overall solution achieves significant improvement in equipment thermal management through intelligent path optimization without the need for additional heat dissipation equipment, and has outstanding technical advantages and application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below with reference to the accompanying drawings.

[0016] Figure 1 It is a schematic flow diagram of the present invention. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0018] See also Figure 1 As shown, the present invention is a multi-machine collaborative mobile measurement robot path control method, comprising the following steps: First, a multi-robot collaborative model was employed to collect surface height information and construct a model of the target area. The first robot moved along the road centerline, utilizing its high-precision LiDAR and image acquisition equipment to vertically scan buildings on both sides of the road, acquiring vertical height profile data. The second robot, stationed at the intersection, performed a 360-degree rotational scan to precisely capture the horizontal projection of the tree canopy. After accurately binding the collected surface height information to geographic coordinates, a polygonal prism was used to spatially fit the building outlines. The prism's base boundary was strictly aligned with the building base as seen in the high-resolution satellite image. The top height was then adjusted layer by layer based on the vertical scan data to ensure the model matched the actual building height. For the tree canopy projection, a minimum enclosing cone was calculated. The cone's base diameter was determined based on the maximum projection distance, and the vertex height was taken from the measured value at the highest point of the canopy. After overlaying the prism and cone models according to geographic coordinates, a spatial analysis algorithm was used to detect overlap between the models, removing redundant volumes while retaining independent structures. This resulted in a simplified 3D model with precise object type identification, providing an accurate data foundation for subsequent calculations. Next, based on the current season's solar trajectory data, the target area is divided into equally spaced grids, with detailed geographic coordinate information associated with each grid node. For each grid node, the changing sequence of the sun's azimuth and altitude angles during the target time period is traversed, and combined with the spatial position and shape parameters of each object in the 3D model, the time interval during which the node is covered by the projections of different objects is calculated. For the building prism model, parallel rays are projected along the sun's azimuth angle, and dynamic projection trajectories are generated based on the geometric parameters of the prism's side edges. For the tree cone model, the ground projection area is dynamically adjusted based on the geometric relationship between the cone's apex angle and the sun's altitude angle, and the fuzzy transition range of the projection edge is calculated based on the canopy density coefficient. The projection coverage time of each object is superimposed and counted by grid node, generating data on the cumulative duration that each node is not covered by any projection. This data then creates a distribution map of the cumulative duration of direct sunlight received by each ground coordinate point over time. Subsequently, based on the cumulative duration distribution graph, a threshold determination method was used to delineate high-intensity sunlight areas and continuous shadow areas. Virtual measurement path nodes were established within the continuous shadow area, and the node spacing was dynamically adjusted based on the shadow area's geometry. For measurement points that must pass through high-intensity sunlight areas, the distribution of the surrounding shadow areas was analyzed to construct multiple candidate connection paths. The path priorities were adjusted based on the spatial relationship between the current solar altitude angle and the candidate path directions, achieving a topological association between the coordinates of the target point to be measured and the continuous shadow area. Finally, a dynamic path allocation protocol is established within the multi-robot communication network. Each robot sends a path update message to the central coordinator in real time, including the shadow zone number of its current location, task progress, and a request for the next target shadow zone. The central coordinator maintains a global shadow zone occupancy status table, recording the identity of the currently occupying robot and the expected release time for each shadow zone. When multiple robots request to enter the same shadow zone, the central coordinator extracts the remaining task queue of each requesting robot, calculates the number of consecutive shadow zone connections in its subsequent path, and prioritizes assigning tasks to robots with the fewest connections. Simultaneously, the central coordinator generates alternative path instructions for robots that have not yet been assigned, ensuring that each robot selects a non-overlapping measurement route within the path network consisting of consecutive shadow zones based on its real-time location and task queue. Path occupancy status is updated through periodic broadcasts, enabling efficient multi-robot collaborative operation.

[0019] In a preferred embodiment of the present invention, the generation process of the simplified three-dimensional model is: During the data collection phase, a dual-robot collaborative model was employed. The first robot, responsible for collecting building outlines, steadily moved along the road's centerline. Using its high-precision LiDAR and image acquisition equipment, it performed a full-scale vertical scan of the buildings on both sides of the road. During the scan, the equipment continuously collected distance and position information from various points on the building's surface, accurately outlining the building's vertical height profile. The second robot, stationed at the intersection, performed a 360-degree rotational scan centered on itself. Its specialized scanning device enabled it to quickly and comprehensively acquire horizontal projection data of the tree canopy's shape, recording its canopy's extent from various angles. The two robots tightly linked the collected surface height information to geographic coordinates, laying a solid data foundation for subsequent modeling.

[0020] Entering the model construction phase, polygonal prisms are used for spatial fitting of the building outline. The bottom boundary of the prism is precisely aligned with the building base in the high-precision satellite map to ensure the accuracy of the model's plane position; based on the detailed data obtained from the vertical scan, the height of the top of the prism is carefully corrected layer by layer to make the model height consistent with the actual building height. For the tree canopy, the model is constructed by calculating the minimum enclosing cone. The diameter of the cone base is determined according to the maximum extension distance of the canopy projection, and the vertex height directly uses the measured value of the highest point of the canopy to form a preliminary tree model. Subsequently, the building prism model and the tree cone model are superimposed and integrated according to the geographic coordinates. A special detection algorithm is used to identify the spatial overlap between the models, and the redundant volume of the overlapping part is decisively deleted, retaining only independent and accurate structures, and finally forming a three-dimensional spatial topological structure with a clear object type identification.

[0021] Faced with densely packed tree groups, an innovative multi-height layer scanning strategy was adopted when scanning the horizontal projection shape of the tree canopy. The first layer of scanning was carried out on a plane lower than the lowest branch height of the canopy, which could clearly obtain the distribution position of the tree trunks and the outer contour shape of the entire tree group; the second layer of scanning was carried out at the middle height of the canopy, focusing on capturing the extension direction of the main branches and the distribution of the canopy gaps; the third layer of scanning was carried out at the height of the top of the canopy to carefully record the concave and convex features of the canopy surface. Based on the data obtained from these three layers of scanning, a composite cone model was constructed, which cleverly decomposed the actual tree canopy into a superimposed structure of multiple sub-cones. The axis position of the sub-cone was flexibly offset according to the branch extension direction, and the bottom diameter was set in segments according to the maximum extension value of the scan contour of each layer, so that the projection range of the combined model was highly matched with the actual shadow shape, greatly improving the restoration and accuracy of the model for complex tree shapes.

[0022] In another preferred embodiment of the present invention, the calculation process of the cumulative duration distribution graph is: First, the target area is divided into a regular grid matrix at a resolution of 5 meters by 5 meters. Each grid node is precisely associated with geographic coordinates and elevation information. For each grid node, the changing sequence of the solar azimuth and altitude angles within the target time period (e.g., 8:00 AM to 6:00 PM) is traversed with a 10-minute time step. Using the precise geometric parameters of each object in the 3D model, a ray tracing algorithm is used to calculate the time interval within each time step that the node is covered by the projections of different objects.

[0023] For building prism models, parallel light beams are projected along the solar azimuth. Based on the geometric parameters of the prism's side edges, dynamic projection trajectories are generated using spatial analytical geometry. The system records the time the projection trajectories cover ground grid nodes in real time, forming a spatiotemporal distribution dataset of building shadows. For tree cone models, the major and minor axis parameters of the ground projection ellipse are dynamically adjusted based on the geometric relationship between the cone's apex angle and the solar altitude. Furthermore, a Gaussian blur algorithm is used to calculate the illumination attenuation transition range at the projection edge, combining it with the canopy density coefficient (obtained through inversion of laser point cloud echo intensity), ensuring that shadow simulation more closely resembles the real environment.

[0024] After calculating the shadows of individual objects, the system performs spatiotemporal statistics on the shadow coverage time of each object, per grid node. Boolean operations are used to integrate building and tree shadow data to generate the cumulative duration of time each grid node was not covered by any shadows during the target time period. Using heat map visualization technology, this cumulative duration data is mapped to different color gradients, creating a heat map that intuitively reflects the distribution of ground light.

[0025] During the generation of the illumination heat map, an innovative dynamic correction mechanism based on real-time meteorological data is introduced. When the weather forecast system detects cloud cover during the target time period, it automatically matches the corresponding transmittance parameter (ranging from 0.2 to 0.8) based on the cloud type code (e.g., cumulus, stratus, etc.). During the cloud cover period, the accumulated duration data of the corresponding grid node is attenuated, with the correction factor being inversely proportional to the cloud transmittance.

[0026] To address sudden localized cloud changes, the system uses a meteorological data interface to obtain real-time data on cloud movement speed, direction, and coverage. Within the 3D model space, cloud projections are abstracted as virtual objects with dynamic boundaries, and a particle system is used to simulate the movement of cloud projections. The cloud projections are then analyzed in spatiotemporal overlay with existing fixed object projections, updating the cumulative duration data for affected grid nodes. When changes in localized lighting conditions exceed a preset threshold (e.g., cumulative duration change rate >15%), the system automatically triggers rapid reconstruction of the local heat map and adjusts the path network in real time to accommodate the dynamic changes in lighting conditions.

[0027] Through this method of multi-dimensional spatiotemporal analysis and dynamic data fusion, the present invention significantly improves the accuracy of shadow area division, especially in complex urban environments. It can effectively cope with the dynamic changes of building and tree shadows and cloud interference, provide mobile measurement robots with accurate lighting environment information, and support their intelligent path planning decisions under high temperature conditions.

[0028] In another preferred embodiment of the present invention, the process of topological association is: 1. Path node layout strategy for continuous shadow areas In continuous shadow areas, an adaptive node spacing algorithm is used: Geometric feature recognition: Through morphological analysis algorithms, geometric parameters such as the aspect ratio and compactness of the shadow area are identified to determine whether it is a strip (aspect ratio > 3:1), block, or irregular shape.

[0029] Dynamic deployment of master nodes: For strip-shaped shadow areas, master nodes are placed at intervals of 3-5 meters along the long axis to ensure continuous movement of the robot within the shadow. For block-shaped shadow areas, a triangular meshing method is used to place nodes in the center of the area and at the edges with greater curvature to optimize path selection flexibility.

[0030] Branch connection optimization: Diagonal branches are inserted between main nodes to form a redundant path network. The branch angle is dynamically adjusted based on the curvature of the shadow area boundary to ensure that the path angle between adjacent nodes is ≥ 60°, avoiding the loss of movement efficiency caused by sharp turns.

[0031] 2. Candidate Path Construction Method in High Sunlight Areas For measurement points that must pass through high-insolation areas, a three-level candidate path system is constructed: Shadow area boundary analysis: The feature point set of the boundary of adjacent shadow areas is extracted, and the curvature change rate of the boundary curve is calculated.

[0032] When the angle between the extension directions of the boundaries of the two shadow areas is within the range of 45°-135°, it is determined that the angle condition is met.

[0033] Virtual shadow corridor generation: At the intersection area in the direction of boundary extension, a virtual shadow corridor with a width of 1.5 times the width of the robot is created.

[0034] The corridor length L is dynamically adjusted according to the solar altitude angle. The calculation formula is: L=H×tan(90°-α)×K, where H is the building height, α is the solar altitude angle, and K is the safety factor (taken as 1.2-1.5).

[0035] Path effectiveness evaluation: The cosine of the angle between the rate of change of the solar azimuth and the direction of the corridor is calculated in real time. As the cosine increases, the corridor's effective duration is extended. A sliding time window is used to predict corridor expiration, triggering a route replanning warning 10 minutes before expiration.

[0036] 3. Dynamic Path Priority Adjustment Mechanism Dual-mode path selection strategy based on solar altitude angle: High sun mode (α ≥ 45°): Prioritizes path segments perpendicular to the sun's azimuth, taking advantage of "shadow walls" formed by lateral building shadows. Enables a fast traversal algorithm to reduce exposure time by accelerating through high-sunlight areas.

[0037] Low sun mode (α < 45°): Select a path segment that aligns with the direction of the building's shadow projection to fully utilize long-distance shadow projections. Associate the temporary shadow coverage time window to accurately calculate the passable time window and initiate traversal at the moment of shadow coverage.

[0038] Path switching decision: When the expected exposure time of a path segment exceeds the thermal tolerance threshold, a path switch is triggered. Using an improved version of the Dijkstra algorithm, a temperature cumulative penalty term is added to the path planning. The calculation formula is: Cost = Distance × (1 + k × T), where Cost represents the total cost of the path and is a path evaluation metric calculated based on the improved Dijkstra algorithm. k is the temperature impact coefficient, Distance is the length of the path segment, and T is the average temperature of the path segment.

[0039] 4. Composite Path Generation and Dynamic Maintenance The virtual shadow corridor is topologically connected with the actual shadow area to form a composite path across the sunlight area: Corridor entrance optimization: Set buffer nodes at the connection between the two ends of the virtual corridor and the actual shadow area to ensure a smooth transition.

[0040] Real-time status monitoring: A network of light sensors deployed on top of buildings verifies the actual shadow effects of corridors in real time. If the measured light intensity deviates from the predicted value by more than 20%, a reassessment of corridor effectiveness is triggered.

[0041] Failure response strategies: Five minutes before the corridor fails, the backup path plan is activated to guide the robot to turn in advance. A bidirectional search algorithm is used to simultaneously calculate the shortest path to the target point and the optimal path for heat load, and the selection is dynamic based on the real-time thermal status.

[0042] In another preferred embodiment of the present invention, a dynamic path allocation protocol utilizes efficient communication and intelligent scheduling mechanisms to rationally allocate and utilize shadow zone resources among multiple mobile measurement robots. During operation, each robot continuously sends path update messages to the central coordinator. These messages detail the robot's current shadow zone number, task completion progress, and the target shadow zone request for the next phase, allowing the central coordinator to monitor each robot's operating status in real time. The central coordinator is responsible for maintaining a global shadow zone occupancy status table, which clearly identifies the robot currently occupying each shadow zone. It also estimates the expected release time of each shadow zone based on the robot's travel speed and task plan, providing comprehensive data support for subsequent path allocation.

[0043] When multiple robots apply to enter the same shadow area at the same time, the central coordinator will quickly extract the remaining task queues of each applying robot and conduct an in-depth analysis of the number of shadow areas that need to be passed through continuously in its subsequent measurement tasks. Based on this analysis result, the target shadow area is preferentially assigned to the robot with a smaller number of consecutive shadow area connections in the subsequent path. Doing so can reduce the situation where the robot frequently adjusts its route due to path conflicts in the future, ensuring that its measurement tasks can proceed more smoothly. For those robots that are not assigned, the central coordinator will promptly send alternative path instructions. The alternative path included in the instruction is generated by the coordinator combining the real-time occupancy status of the current shadow area and reintegrating the connection nodes of adjacent idle shadow areas. At the same time, it also provides accurate path switching time synchronization information to ensure that the robot can seamlessly switch to the new path and continue to perform the measurement task efficiently.

[0044] When generating an alternative path instruction, the central coordinator first searches for a set of currently unoccupied shadow areas. Then, based on the requesting robot's current position and the distribution of the target points to be measured, it screens and combines these available shadow areas, attempting to find a continuous path segment that meets the robot's task schedule. However, if a continuous path cannot be formed within the available shadow areas, the central coordinator activates path bridging mode, turning its attention to sunlit areas. Within sunlit areas, the coordinator accurately identifies transitional path segments that meet the temporary shadow coverage time window based on the current sun altitude and the height of surrounding buildings. Only those segments that meet the theoretical shadow coverage requirements within the specified time window are selected for the alternative path sequence. Ultimately, a composite route is formed that combines the conventional shadow area path with the temporary shadow coverage segments. This ensures that even when the robot cannot rely entirely on continuous shadow areas, it can complete the measurement task while minimizing thermal load.

[0045] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A multi-machine collaborative mobile measurement robot path control method, characterized in that: The following steps are involved: Collect surface height information of the target area and bind it to geographic coordinates to generate a simplified 3D model that includes building edges, tree canopies, and the tops of fixed equipment. Based on the sun's trajectory data for the current season, calculate the cumulative duration distribution of direct sunlight received by each coordinate point on the ground during the current time period; According to the cumulative duration distribution map, high sunshine intensity areas and continuous shadow areas are divided, and the coordinates of the target point to be measured are topologically associated with the continuous shadow area; A dynamic path allocation protocol is established in a multi-robot communication network, which enables each robot to select a non-overlapping measurement route in a path network consisting of continuous shadow areas according to its real-time position and task queue, and update the path occupancy status through periodic broadcasting.

2. The multi-machine collaborative mobile measurement robot path control method according to claim 1, characterized in that: The generation process of the simplified three-dimensional model is as follows: The surface height information of the target area is collected by a first robot and a second robot. The first robot moves along the centerline of the road and collects the vertical height profiles of the buildings on both sides. The second robot rotates and scans at a fixed point at the intersection to obtain the horizontal projection shape of the tree canopy. When using polygonal prisms for spatial fitting of building outlines, the bottom boundary of the prism is aligned with the building base in the satellite map, and the top height is corrected layer by layer based on the vertical scanning data; when calculating the minimum enclosing cone for the projected shape of the tree canopy, the bottom diameter of the cone is determined according to the maximum extension distance of the projection, and the vertex height is taken from the actual measured value of the highest point of the canopy; after superimposing the prism and cone models according to geographic coordinates, the spatial overlapping area between the models is detected, the redundant volume of the overlapping part of the prism and cone is deleted, and the independent structure is retained to form a three-dimensional spatial topological structure with object type identification.

3. The multi-machine collaborative mobile measurement robot path control method according to claim 2, characterized in that: During the scanning process of the horizontal projection shape of the tree canopy, a multi-height layer scanning strategy is adopted for densely arranged tree groups, specifically: The first layer of scanning is performed on a plane below the height of the lowest branch of the crown to obtain the distribution position of the tree trunks and the outer contours of the tree group; the second layer of scanning is performed at the middle height of the crown to capture the extension direction of the main branches and the distribution of the canopy gaps; the third layer of scanning is performed at the height of the top of the crown to record the concave and convex characteristics of the canopy surface; based on the three-layer scanning data, a composite cone model is constructed, and the actual crown is decomposed into a superimposed structure of multiple sub-cones. The axis position of the sub-cone is offset according to the branch extension direction, and the bottom diameter is segmented according to the maximum extension value of the scan contour of each layer, so that the projection range of the combined model matches the actual shadow shape.

4. The multi-machine collaborative mobile measurement robot path control method according to claim 1, characterized in that: The calculation process of the cumulative duration distribution graph is as follows: The target area is divided into equally spaced grids, with each grid node associated with geographic coordinate information. For each grid node, the changing sequence of the sun's azimuth and altitude angles during the target time period is traversed. Based on the spatial position and shape parameters of each object in the 3D model, the time interval during which the node is covered by the projections of different objects is calculated. For the building prism model, parallel light is projected along the direction of the sun's azimuth angle, and a dynamic projection trajectory is generated based on the geometric parameters of the prism's side edges, and the coverage time of the projection trajectory on the ground grid nodes is recorded. For the tree cone model, the ground projection area is dynamically adjusted according to the geometric relationship between the cone apex angle and the solar altitude angle, and the fuzzy transition range of the projection edge is calculated in combination with the canopy density coefficient. The projection coverage time of each object is superimposed and counted according to the grid nodes to generate the cumulative time data of each node not covered by any projection, forming a ground illumination heat map that changes over time.

5. The multi-machine collaborative mobile measurement robot path control method according to claim 4, characterized in that: During the generation of the illumination heat map, real-time meteorological data is introduced to dynamically correct the projection calculation: when cloud cover is forecasted within the target time period, the transmittance parameter is matched according to the cloud type code, and the accumulated duration data of the grid nodes within the corresponding time interval is attenuated. In response to sudden local cloud changes, the cloud movement speed and coverage range are obtained through the meteorological data interface, and the movement trajectory of the cloud projection is simulated in the three-dimensional model space. The projection is regarded as a temporary virtual object and added to the projection calculation queue. It is then superimposed and analyzed with the original fixed object projection, and the accumulated duration data of the affected grid nodes is updated, triggering the reconstruction of the local heat map and the real-time adjustment of the path network.

6. The multi-machine collaborative mobile measurement robot path control method according to claim 1, characterized in that: The process of topological association is as follows: Virtual measurement path nodes are established within continuous shadow areas. The node spacing is dynamically adjusted based on the geometric shape of the shadow area. For strip-shaped shadow areas, main nodes are evenly spaced along their long axis, and oblique connecting branches are inserted between the main nodes. For measurement points that must pass through areas of high sunlight intensity, the distribution of surrounding shadow areas is analyzed, and multiple candidate connection paths are constructed between adjacent shadow areas. The path priority is adjusted based on the spatial relationship between the current solar altitude angle and the direction of the candidate paths. When the solar altitude angle exceeds the set critical value, the path segment in the connecting path that is perpendicular to the solar azimuth angle is selected as the priority route; when the solar altitude angle is lower than the critical value, the path segment in the connecting path that is consistent with the extension direction of the building projection is selected, and the temporary shadow coverage time window is associated for dynamic path switching.

7. The multi-machine coordinated mobile measurement robot path control method according to claim 6, characterized in that: The construction of the candidate connection path specifically includes: The boundary directions of adjacent shadow areas in high-insolation areas are analyzed. When the extension trends of the boundaries of the two shadow areas meet the angle condition, a virtual shadow corridor is created in the intersection area of ​​the extension direction. The path validity duration of the virtual shadow corridor is calculated based on the relationship between the changing rate of the solar azimuth angle and the corridor direction. When the angle between the changing direction of the solar azimuth angle and the corridor direction decreases, the validity duration of the corridor is extended. When selecting the path, the virtual shadow corridor is topologically connected with the actual shadow area to generate a composite path that spans the sunlight area. Before the end of the corridor validity duration, a path failure warning is sent to the robot to trigger the dynamic switching of subsequent path segments.

8. The multi-machine coordinated mobile measurement robot path control method according to claim 1, characterized in that: When the dynamic path allocation protocol is executed, each robot sends a path update message containing the shadow zone number of the current location, the task progress, and the request for the next target shadow zone to the central coordinator; the central coordinator maintains a global shadow zone occupancy status table, which records the current occupied robot ID and expected release time of each shadow zone; When receiving entry requests from multiple robots to the same shadow area, the remaining task queue of each requesting robot is extracted, the number of continuous connections in the shadow area in its subsequent path is calculated, and robots with fewer shadow area connections are preferentially assigned to enter the target area; alternative path instructions are sent to robots that are not assigned. The alternative path is generated by the central coordinator by recombining the connection nodes of adjacent idle shadow areas according to the current shadow area occupancy status, and is accompanied by time synchronization information for path switching.

9. The multi-machine coordinated mobile measurement robot path control method according to claim 8, characterized in that: The generation process of the alternative path instruction is as follows: The central coordinator retrieves the set of currently unoccupied shadow areas, and searches for continuous path segments that meet the task progress requirements in the idle shadow areas based on the current position of the requesting robot and the distribution of the target points to be measured. When a continuous path cannot be formed in the idle shadow areas, the path bridging mode is activated to search for transition path segments that meet the temporary shadow coverage time window in the sunlit area. The selection of transition path segments is based on the geometric relationship between the current solar altitude angle and the height of surrounding buildings. The theoretical shadow coverage rate of the transition path segment within the specified time window is calculated, and only the sections with coverage that meet the standard are selected to be added to the alternative path sequence, forming a composite traffic route with mixed shadows and temporary shadow coverage.

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