A robot earthquake warning method, electronic device, storage medium and program product

Abstract

This invention discloses a robot earthquake early warning method, electronic device, storage medium, and program product. By analyzing earthquake early warning information, it determines the actual impact on a target area and matches differentiated warning content accordingly, helping to make the warning information more aligned with specific risk levels. Dynamically determining the target broadcast area based on the real-time location and crowd density of the mobile robot allows the robot's actions to focus more on areas where people are currently gathered, thereby optimizing the allocation of warning resources. Planning a movement path for each robot to its target area and controlling its continuous broadcasting during movement enables the warning information to proactively cover a wider area as the robot moves, helping to reduce potential coverage blind spots in fixed early warning equipment.

Description

Technical Field

[0001] This invention relates to the field of earthquake early warning technology, and in particular to a robotic earthquake warning method, electronic device, storage medium, and program product. Background Technology

[0002] Traditional earthquake early warning systems primarily rely on fixed terminal devices (such as broadcasts and mobile apps) for information dissemination. These fixed terminals are typically deployed at limited locations, and their warning range is physically limited, making it difficult to cover all areas inside buildings, especially complex spaces such as multi-story underground locations, densely packed office buildings, or the atriums of large shopping malls. During a sudden earthquake, the warning signal cannot quickly and evenly reach all personnel in these blind spots, resulting in some areas not receiving timely warnings and delaying emergency response. Improving the coverage of earthquake warning areas is a pressing issue that needs to be addressed. Summary of the Invention

[0003] This application provides a robot earthquake alarm method, electronic device, storage medium, and program product, which solves the technical problem in the prior art that fixed early warning terminals have limited alarm coverage and are difficult to quickly and effectively cover all areas within a building, especially structurally complex areas or areas with dynamic population distribution. It achieves the technical effect of significantly expanding the physical coverage of the early warning by scheduling multiple mobile robots and dynamically planning patrol and broadcasting paths based on real-time location and population density, thereby improving the timeliness and uniformity of alarm information transmission within the target jurisdiction area.

[0004] In a first aspect, this application provides a robot earthquake alarm method, applied to a control platform corresponding to a target jurisdiction area, the control platform communicating with at least one mobile robot in the target jurisdiction area, the method comprising: After receiving earthquake early warning information, the actual impact of the earthquake on the target jurisdiction area is determined based on the earthquake early warning information, which includes the earthquake magnitude and the distance to the epicenter. Based on the preset correlation between the degree of impact and the alarm content, as well as the actual degree of impact, the target alarm content is determined, and the target alarm content is sent to each mobile robot in the target jurisdiction area; Based on the distribution location of each mobile robot in the target jurisdiction area and the pedestrian density data within a preset distance range of each mobile robot, the target broadcast area corresponding to each mobile robot is determined; Based on the current location of each mobile robot, determine the movement path of each mobile robot in the corresponding target broadcast area; Each mobile robot is controlled to move along a corresponding path, and during the movement, the target alarm content is broadcast to achieve earthquake alarm for the target jurisdiction area.

[0005] Secondly, this application provides an electronic device, comprising: processor; Memory used to store the processor's executable instructions; The processor is configured to execute a robot earthquake alarm method as provided in the first aspect.

[0006] Thirdly, this application provides a non-transitory computer-readable storage medium, wherein when the instructions in the storage medium are executed by the processor of an electronic device, the electronic device is able to execute a robot earthquake alarm method as provided in the first aspect.

[0007] Fourthly, this application provides a computer program product including computer instructions that are executed by a processor to implement a robot earthquake alarm method as provided in the first aspect.

[0008] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: This application's embodiments, through the collaboration of a control platform and multiple mobile robots, can improve the efficiency and targeting of earthquake early warning. By analyzing earthquake early warning information to determine the actual impact on the target area and matching differentiated warning content accordingly, it helps to make the warning information more aligned with specific risk levels. Dynamically determining the target broadcast area based on the real-time location and population density of the mobile robots allows the robots to focus their actions on areas where people are currently concentrated, thereby optimizing the allocation of warning resources. Planning a movement path for each robot to its target area and controlling its continuous broadcasting during movement enables the warning information to proactively cover a wider area as the robots move, helping to reduce potential coverage blind spots of fixed early warning equipment. Overall, this method, through the dynamic patrol and broadcasting of mobile robots, provides a feasible implementation for improving the coverage and timeliness of earthquake early warning information within the target jurisdiction area. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1A flowchart illustrating a robot earthquake alarm method provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0011] This application provides a robot earthquake alarm method, electronic device, storage medium, and program product, which solves the technical problem in the prior art that fixed early warning terminals have limited alarm coverage and are difficult to quickly and effectively cover all areas inside a building, especially areas with complex structures or areas with dynamic distribution of people.

[0012] The technical solution of this application embodiment is to solve the above-mentioned technical problems, and the general idea is as follows: This application's embodiments, through the collaboration of a control platform and multiple mobile robots, can improve the efficiency and targeting of earthquake early warning. By analyzing earthquake early warning information to determine the actual impact on the target area and matching differentiated warning content accordingly, it helps to make the warning information more aligned with specific risk levels. Dynamically determining the target broadcast area based on the real-time location and population density of the mobile robots allows the robots to focus their actions on areas where people are currently concentrated, thereby optimizing the allocation of warning resources. Planning a movement path for each robot to its target area and controlling its continuous broadcasting during movement enables the warning information to proactively cover a wider area as the robots move, helping to reduce potential coverage blind spots of fixed early warning equipment. Overall, this method, through the dynamic patrol and broadcasting of mobile robots, provides a feasible implementation for improving the coverage and timeliness of earthquake early warning information within the target jurisdiction area.

[0013] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0014] First, it should be clarified that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0015] This application provides a robot earthquake alarm method, which includes steps S11-S15, for details of which can be found in the following embodiments. Figure 1 As shown.

[0016] Step S11: After receiving the earthquake early warning information, determine the actual impact of the earthquake on the target jurisdiction area based on the earthquake early warning information, wherein the earthquake early warning information includes the earthquake magnitude and the distance to the epicenter; Step S12: Based on the preset correlation between the degree of impact and the alarm content, as well as the actual degree of impact, determine the target alarm content and send the target alarm content to each mobile robot in the target jurisdiction area; Step S13: Based on the distribution location of each mobile robot in the target jurisdiction area and the pedestrian density data within a preset distance range of each mobile robot, determine the target broadcast area corresponding to each mobile robot; Step S14: Based on the current location of each mobile robot, determine the movement path of each mobile robot in the corresponding target broadcast area; Step S15: Control each mobile robot to move according to the corresponding movement path, and broadcast the target alarm content during the movement to realize the earthquake alarm for the target jurisdiction area.

[0017] This application provides a robot earthquake alarm method that can be applied to a control platform corresponding to a target jurisdiction area, and the control platform communicates with at least one mobile robot in the target jurisdiction area.

[0018] The robotic earthquake alarm method described in this application can be operated primarily by a control platform. This control platform typically manages a specific target area, such as coordinating alarms within a building, a floor, or a park. Within this area, mobile robots are deployed, and the control platform establishes a communication connection with these robots, enabling it to send commands and receive status information. This approach allows alarm tasks to be performed by mobile robots, rather than being limited to fixed locations, providing a foundation for dynamically transmitting early warning information within the area.

[0019] Regarding step S11, after receiving the earthquake early warning information, the actual impact of the earthquake on the target jurisdiction area is determined based on the earthquake early warning information, which includes the earthquake magnitude and the distance to the epicenter.

[0020] After acquiring early warning information containing core parameters such as earthquake magnitude and focal distance, the control platform analyzes and processes it to assess the specific impact level that the earthquake event may have on the target jurisdiction area it is responsible for.

[0021] One relatively conventional method for determining the degree of impact, which may be used in some existing systems, is to directly classify the impact level based on the two parameters of magnitude and epicentral distance, according to a pre-defined simplified correspondence table. For example, the system stores a table that cross-matches different magnitude ranges (e.g., 4.0-5.0, 5.0-6.0) with different distance ranges (e.g., 0-50 km, 50-100 km). Each "magnitude-distance" combination corresponds to a pre-defined impact level (e.g., "mild," "moderate," "severe"). After receiving an early warning, the platform can directly output a judgment result by querying this table. This method focuses on achieving rapid response, and its judgment process typically does not involve detailed consideration of complex factors such as regional geological conditions, building structures, or real-time pedestrian flow.

[0022] Furthermore, the actual degree of impact can also be determined in the following manner, specifically including steps S111-S114.

[0023] Step S111: Input the earthquake early warning information into a preset earthquake intensity attenuation model to determine the theoretical earthquake intensity at a preset reference location in the target jurisdiction area.

[0024] Step S111 describes the process of estimating theoretical seismic intensity using a seismic intensity attenuation model. This model is typically a mathematical or statistical model built upon a large amount of historical earthquake observation data. Its framework includes functions reflecting the attenuation of seismic energy with distance, such as using magnitude, focal distance, or epicentral distance as input parameters, and outputting a theoretical intensity estimate for a specific location. The model training process relies on the processing of historical earthquake events, i.e., collecting actual recorded seismic intensity data at different magnitudes and distances, and fitting the model parameters through methods such as regression analysis to approximately reflect the general law of seismic motion intensity variation with geographic space.

[0025] Step S112: Determine the site building parameters of the target jurisdiction area from the local geological condition database associated with the target jurisdiction area.

[0026] Step S112 involves accessing a local geological condition database to obtain site building parameters for the target jurisdiction area. This database typically stores pre-stored geological and architectural environmental information related to the target area. The site building parameters mainly include two categories: first, site category parameters (such as soil type, soil shear wave velocity, etc.), which reflect the amplification or attenuation effect of surface geological conditions on seismic waves; and second, building structural characteristic parameters (such as main building structure type, average floor height, etc.), which reflect the overall seismic performance and vibration response characteristics of the building complex within the area. These parameters serve to provide a basis for subsequent intensity correction that reflects specific local conditions.

[0027] Step S113: Correct the theoretical seismic intensity based on the site building parameters to obtain the expected seismic intensity.

[0028] Step S113 explains the principle and process of correcting theoretical seismic intensity using site building parameters. The basic principle of correction is that the theoretical attenuation model provides an intensity estimate under general or regional average conditions, while specific site conditions and the built environment significantly alter local seismic intensity. The correction process typically involves converting site building parameters into one or more correction coefficients or adjustments, which are then applied to the theoretical seismic intensity value through weighting or superposition. For example, a soft soil site might correspond to a positive correction value to reflect an amplification effect, while a densely built area with good seismic resistance might correspond to a negative correction value to reflect a certain damping effect, thus obtaining an expected seismic intensity that more closely reflects the actual situation in the target area.

[0029] Step S114: Based on the preset correlation between earthquake intensity and impact level, determine the actual impact level of the earthquake on the target jurisdiction area.

[0030] Step S114 explains how to ultimately determine the actual impact level based on the expected earthquake intensity. The system pre-defines a correspondence between earthquake intensity and impact level, for example, mapping different intensity ranges in the earthquake intensity table (I-XII degrees) to operational impact levels such as "low impact," "moderate impact," and "high impact." After obtaining the corrected expected earthquake intensity, this mapping relationship can be queried to convert it into an actual impact level determination result to guide subsequent warning actions.

[0031] For example, suppose an earthquake event occurs, and the earthquake early warning information received by the control platform shows a magnitude of 6.5, with the epicenter approximately 80 kilometers from a preset reference location within the target jurisdiction area. In step S111, this information is input into a preset earthquake intensity attenuation model, which calculates, based on its inherent statistical laws, that at the current distance, the theoretical earthquake intensity that this magnitude earthquake might cause at the reference location is approximately VII.

[0032] In step S112, the system queries the local geological condition database associated with the target jurisdiction area. The database records show that the site category for this area is Class II (representing medium-soft soil), and its main building structure type is brick-concrete structure. This site category and building structure type information together constitute the site building parameters for this location.

[0033] In step S113, the system corrects the theoretical intensity according to preset rules. Since Class II sites amplify seismic waves, a correction value of +0.5 degrees may be assigned; however, the seismic resistance of brick-concrete structures is relatively limited, so no damping correction may be applied. Therefore, the theoretical intensity VII (7 degrees) is added to the site correction value of +0.5 degrees to obtain the expected seismic intensity of the area as strong VII (approximately 7.5 degrees).

[0034] Finally, in step S114, the system makes a judgment based on a preset mapping relationship (for example, an expected intensity ≥ VII corresponds to "high impact"). Based on the calculated expected intensity of approximately 7.5 (VII strong), the system determines that the actual impact of this earthquake on the target jurisdiction area is "high impact".

[0035] Regarding step S12, based on the preset correlation between the degree of impact and the alarm content, as well as the actual degree of impact, the target alarm content is determined, and the target alarm content is sent to each mobile robot in the target jurisdiction area.

[0036] Step S12 describes the process by which the control platform transforms the analysis results of the earthquake impact into specific action instructions. Based on pre-defined rules (e.g., mapping "height impact" to "immediate evacuation" instructions), the platform matches the determined actual impact level with the corresponding alarm content. Subsequently, the platform sends this determined alarm content as a unified instruction to all online mobile robots within the target jurisdiction area, providing a consistent information basis for their subsequent dynamic broadcasting.

[0037] For example, when the actual impact is low, waiting in place will be determined as the target alarm content; when the actual impact is moderate, following the guide to move in an orderly manner to the preset safe area will be determined as the target alarm content; when the actual impact is high, immediate emergency evacuation will be determined as the target alarm content.

[0038] When the actual impact is determined to be low, the warning message is "wait in place." This usually means that the estimated earthquake intensity is weak or the risk is limited. The primary goal is to maintain order at the scene and avoid accidents or chaos that may be caused by unnecessary movement. At the same time, personnel are required to be vigilant and prepared to receive further information.

[0039] When the actual impact is determined to be moderate, the warning message is "Follow the guide and move in an orderly manner to the pre-set safe area." This applies to situations that involve some risk but are not extremely urgent. This instruction aims to guide personnel to systematically and smoothly move to a pre-assessed relatively safe location indoors or within a building (such as next to a sturdy shelter or under a load-bearing wall) to avoid potential hazards such as falling non-structural components. Its core principles are "orderly" and "guided," balancing safety and order.

[0040] When the actual impact is determined to be high, the alert message is "Immediate Emergency Evacuation." This corresponds to a scenario anticipated to cause severe damage. At this point, the core objective is to act quickly, utilizing the limited warning time, to guide personnel to evacuate rapidly through safe evacuation routes to open areas outside the building, maximizing personal safety. This instruction emphasizes the urgency and directness of the action.

[0041] Regarding step S13, based on the distribution location of each mobile robot in the target jurisdiction area and the pedestrian density data within a preset distance range of each mobile robot, the target broadcast area corresponding to each mobile robot is determined.

[0042] Step S13 determines the method for assigning specific broadcast areas to each mobile robot. This method comprehensively considers the real-time geographical location of each robot and the real-time population gathering situation within a certain surrounding range. Its purpose is to dynamically allocate limited robot resources to sub-areas where people are relatively concentrated or more likely to require early warning services, thereby attempting to improve the overall efficiency and population coverage of alarm information transmission.

[0043] Specifically, the target broadcast area can be determined in any of the following three ways.

[0044] The first method: For each mobile robot, multiple sub-regions with human density data are identified within a preset distance range corresponding to that mobile robot; The sub-regions are pieced together to form the target broadcast area corresponding to the mobile robot, arranged in order of increasing distance from each other.

[0045] The first approach follows a "distance-first" principle. For each robot, within its preset effective range, the system identifies all sub-regions containing pedestrian traffic data. Then, the system sorts these sub-regions based on their physical distance from the robot's current location, prioritizing the inclusion of the closest sub-regions in its broadcast task sequence. This approach emphasizes the timeliness of robot actions, allowing the robot to begin broadcasting with a shorter initial movement time, potentially proving efficient in the initial stages requiring rapid response.

[0046] For example, suppose a mobile robot is located in the center of the lobby on the first floor of a building, with a preset effective radius of 50 meters. Within this radius, the system detects three sub-areas with pedestrian traffic data: Area A (5 meters away), adjacent to the lobby; Area B (30 meters away), located on the other side of the same floor; and Area C (45 meters away), accessible via a passageway. Using the first approach, the system will sort these areas from closest to furthest: Area A (5 meters) → Area B (30 meters) → Area C (45 meters). Therefore, the target broadcast area planned for the robot will be pieced together in this order, and the robot will first go to the nearest area, Area A, to broadcast.

[0047] The second method: For each mobile robot, multiple sub-regions with human density data are identified within a preset distance range corresponding to that mobile robot; Based on the descending order of pedestrian density data for each sub-region, the sub-regions are pieced together to form the target broadcast area corresponding to the mobile robot.

[0048] The second approach follows a "density-first" principle. Similarly, the system first identifies all relevant sub-areas within the effective range of each robot. The sorting is no longer based on distance, but rather on real-time pedestrian density data for each sub-area. The system prioritizes sending robots to the most densely populated sub-areas to broadcast alerts. This approach focuses on the efficiency of alert information delivery to the largest possible population, aiming to allow a limited number of robots to serve the largest possible number of people, thereby potentially improving the overall public benefit of the alert.

[0049] For example, in a scenario similar to the first method described above, the system obtains the following real-time pedestrian density data for each sub-area: Area A has a low density in the corridor (approximately 2 people / 100 square meters), Area B has a medium density in the rest area (approximately 10 people / 100 square meters), and Area C, where an event is being held in the multi-functional hall, has a very high density (approximately 50 people / 100 square meters). Using the second method, the system will sort the pedestrian density from highest to lowest: Area C (50 people / 100 square meters) → Area B (10 people / 100 square meters) → Area A (2 people / 100 square meters). Therefore, the robot will be prioritized for Area C, where the population density is highest, and the stitching order of its target broadcast area will prioritize coverage of high-density areas.

[0050] The third method: For each mobile robot, multiple sub-regions with human density data are identified within a preset distance range corresponding to that mobile robot; Based on the first weight corresponding to the distance between each sub-region and the mobile robot, and the second weight of each sub-region with respect to the pedestrian density data, the splicing order between each sub-region is determined, and the sub-regions are spliced ​​together into the target broadcast area corresponding to the mobile robot according to the splicing order.

[0051] The third approach is a weighted comprehensive strategy that integrates distance and density factors. When ranking sub-regions, the system considers both "distance" and "people density" dimensions, assigning a configurable weight coefficient to each. A comprehensive evaluation function (e.g., converting distance to cost and density to benefit) calculates a comprehensive priority score for each sub-region, and the order is determined based on this score. This approach attempts to strike a balance between the goals of "arrival speed" and "coverage of people" to accommodate more diverse task requirements.

[0052] For example, under the same environment and data, the system sets the first weight of the distance factor to 0.4 and the second weight of the pedestrian density factor to 0.6. It first normalizes the distance and density data for each sub-region, then calculates the comprehensive score for each region (score = 0.4 * distance score + 0.6 * density score, where closer distances result in higher scores, and higher density results in higher scores). Assuming that after calculation, region B scores the highest due to its relatively balanced distance and density, region C scores the second highest due to its extremely high density but furthest distance, and region A scores the lowest due to its very low density, then the final stitching order will be region B → region C → region A. This result reflects the system's balanced consideration of the two objectives of "arrival speed" and "covered population" under the given weights.

[0053] Of these three approaches, the first (distance priority) and the second (density priority) are two basic strategies with different focuses, while the third (weighted synthesis) can be regarded as an extension and generalization of the first two approaches. By adjusting the weights, it can be biased towards distance or density, or even degenerate into a situation similar to the first two approaches.

[0054] The first method (distance priority) has the advantage of simple path and fast response, making it suitable for scenarios that are sensitive to initial reaction time or where people are relatively evenly distributed in the area.

[0055] The advantage of the second method (density priority) is that it can cover more people more quickly on a global scale, and is suitable for situations where the distribution of people is highly uneven and there are obvious gathering points (such as halls and entrances).

[0056] The third approach (weighted synthesis) is advantageous due to its flexibility and configurability. It is suitable for situations with combined requirements for response efficiency and pedestrian coverage, or where environmental and task objectives may change. For example, when the warning time window is very tight, the distance weight can be increased; when personnel safety is of paramount importance, the density weight can be increased. This approach provides the system with the possibility of adapting to different strategy orientations.

[0057] Regarding step S14, based on the current location of each mobile robot, determine the movement path of each mobile robot in the corresponding target broadcast area.

[0058] Step S14 involves planning a specific travel route for each robot after the target broadcast area (usually composed of several sub-regions pieced together in sequence) that it needs to cover has been determined. Its core is to generate a coherent, feasible, and as efficient as possible physical movement path based on the robot's current starting position and the positions and access order of the various sub-regions it needs to visit and execute the broadcast, ensuring that the robot can completely traverse all the areas it has been assigned.

[0059] This application provides three different methods for determining movement paths and their specific processes.

[0060] Method 1: Sequential shortest path connection method.

[0061] This method plans paths according to the pre-defined sequence of sub-regions within the target broadcast area. The process is as follows: First, the robot's current location is used as the starting point of the path. Then, the first sub-region to be visited is abstracted into one or more necessary path points (e.g., the center point of the sub-region's entrance). Next, a path planning algorithm (such as A* or Dijkstra's algorithm) is invoked to calculate the collision-free shortest path from the starting point to the target point of the first sub-region, based on the robot's built-in environment map or one obtained from the control platform, and this path segment is added to the overall movement path. Afterward, the target point of the first sub-region is used as the new starting point, and the above process is repeated to calculate the path segments leading to the next sub-region, and these segments are then sequentially concatenated. This process continues until all sub-regions have been planned. The final complete route, formed by sequentially connecting the path segments, is the robot's movement path.

[0062] For example, suppose a mobile robot is currently located at the nurses' station (location S) in a hospital ward floor scenario. Its target broadcast area is sequentially pieced together as follows: first, it moves to the nearest ward 101 area (sub-area A), then to the more distant ward 105 area (sub-area B), and finally to the activity room at the end of the corridor (sub-area C). When planning the path using this method, the system strictly follows the order A→B→C. It first plans the shortest feasible path from the nurses' station S to the entrance of ward 101 A (e.g., going straight along the main corridor and turning right), and then records this path as the first segment. Next, starting from the entrance of ward 101, it plans the shortest path to the entrance of ward 105 B (e.g., returning to the main corridor and continuing forward), as the second segment. Finally, it plans the shortest path from the entrance of ward 105 to the entrance of activity room C (e.g., going forward to the end and turning left), as the third segment. The robot will move and broadcast strictly according to the path S→A→B→C formed by connecting these three segments in sequence.

[0063] Method 2: Global Optimization Cruise Path Method.

[0064] This method is not entirely limited to a preset sub-region order, but seeks a globally optimized path with a shorter total distance while ensuring that all specified sub-regions are visited at least once. The process is as follows: The system treats the robot's current position and all the sub-regions that need to be visited (each sub-region is also abstracted as one or more representative points) as "nodes" that must be traversed. Then, it models this as a "Traveling Salesman Problem (TSP)" or a variant thereof in graph theory. The system estimates or calculates the feasible distance between every two nodes (the distance cost can be pre-calculated or obtained by planning local paths in real time), and uses appropriate heuristic algorithms (such as genetic algorithms, ant colony algorithms) or exact algorithms (for a small number of nodes) to solve for the shortest loop visiting all nodes or the shortest Hamiltonian path from a specified starting point. The final node visit sequence and the straight lines or preset channels connecting them constitute the robot's optimized cruising path.

[0065] For example, in an open-plan office park, a robot starts from the central control room (starting point S) and needs to cover the dispersed R&D area A, testing area B, and meeting area C. Simply planning the path in the order A→B→C might result in a long total path. Using a global optimization method, the system treats S, A, B, and C as four nodes and calculates the feasible distances between each pair (e.g., S to A is 80 meters, S to B is 100 meters, A to B is 30 meters, B to C is 50 meters, and C to S is 90 meters). By solving the Traveling Salesman Problem, the system might find that the total path of the access sequence S→A→B→C→S is 260 meters, while the total path of the sequence S→A→C→B→S is 270 meters. Therefore, the shorter total path S→A→B→C is chosen as the optimized access sequence, and the final movement path connecting each node is generated accordingly.

[0066] Method 3: Coverage path method within sub-regions.

[0067] This method not only connects sub-regions but also plans the robot's detailed coverage path within each sub-region to enhance the broadcasting effect. The process is as follows: For each sub-region requiring broadcasting, the system predefines or generates a coverage pattern in real-time based on its shape, size, and internal obstacle distribution, such as a "bow-shaped" round-trip path or a spiral path inward along the boundary. When determining the overall movement path, a similar approach to Method 1 or Method 2 is used to determine the macroscopic order and connecting channels for visiting each sub-region. However, when the path enters a sub-region, it no longer simply connects a representative point but inserts the pre-defined detailed coverage path within that sub-region as a whole "segment" into the macroscopic path. The robot will slowly move along this internal coverage path and continuously broadcast, completing detailed coverage of the region before exiting and proceeding to the next sub-region along the connecting channel. This method generates a more precise movement path, ensuring that the broadcasting is comprehensive within the sub-region.

[0068] For example, in a large shopping mall, a robot needs to broadcast in the atrium (sub-area A) and two main shelving areas (sub-areas B and C). Using this method, the system first determines the macro-order of access, such as A→B→C. When planning to enter atrium A, the system doesn't simply guide the robot to the edge of the atrium; instead, it plans a "bow-shaped" path covering the entire atrium. The robot will slowly traverse each aisle along this path, continuously broadcasting. After completing atrium coverage, the robot exits the atrium and moves along the main aisle to the entrance of shelving area B. Then, within shelving area B, it may execute a looping path along the main aisle for coverage broadcasting. In this way, within each sub-area, the robot executes a pre-set detailed path designed to maximize coverage of the area's internal space, forming a complete movement scheme combining "macro-connection paths" and "internal coverage paths."

[0069] Regarding step S15, each mobile robot is controlled to move according to the corresponding movement path, and the target alarm content is broadcast during the movement to realize the earthquake alarm for the target jurisdiction area.

[0070] Step S15 is the final execution stage of the entire method. Its function is to transform the results of the aforementioned analysis, decision-making, and planning into concrete physical actions, thereby achieving the alarm objective. This step begins with the control platform issuing its own movement path instructions and target alarm content to be broadcast to each mobile robot. After receiving the instructions, the robot's autonomous navigation system begins to drive it along the designated path. During this process, the robot integrates environmental perception data from LiDAR and visual sensors in real time, avoiding dynamic obstacles on the path to ensure the continuity and safety of movement. Simultaneously, the robot continuously broadcasts alarm voice messages according to the instructions, and can also simultaneously activate screen displays and light prompts, forming a mobile, multimodal alarm information source. In this way, alarm information is dynamically carried to various parts of the target area along with the robot's movement, thus attempting to achieve a more proactive and broader-coverage emergency early warning.

[0071] Specifically, step S15 can control each mobile robot to move cyclically according to the corresponding movement path, and broadcast the target alarm content during the movement until an earthquake early warning cancellation command is received, and then control each mobile robot to stop broadcasting the target alarm content.

[0072] After activation, the robot does not simply move unidirectionally along its path and broadcast once, but may circulate repeatedly within its assigned target broadcast area or along the planned path. This cyclical movement is designed to address the characteristic of earthquake early warning events typically lasting for a period of time, providing continuous alerts to people within the area and adapting to potential changes in people's locations. Simultaneously, the mechanism establishes a clear stopping condition: the control platform issues a stop broadcasting and standby command to the robot only after receiving an official earthquake early warning cancellation instruction. This ensures that the activation and termination of the entire alarm process are synchronized with the status of the authoritative warning information, forming a complete and controlled process with a beginning and an end, theoretically enhancing the standardization of system management and the adaptability to various response scenarios.

[0073] In summary, the embodiments of this application, through the collaboration of a control platform and multiple mobile robots, can improve the efficiency and targeting of earthquake early warning. By analyzing earthquake early warning information to determine the actual impact on the target area and matching differentiated warning content accordingly, it helps to make the warning information more aligned with specific risk levels. Dynamically determining the target broadcast area based on the real-time location and population density of the mobile robots allows the robots to focus their actions on areas where people are currently gathered, thereby optimizing the allocation of warning resources. Planning a movement path for each robot to its target area and controlling its continuous broadcasting during movement enables the warning information to proactively cover a wider area as the robots move, helping to reduce potential coverage blind spots of fixed early warning equipment. Overall, this method, through the dynamic patrol and broadcasting of mobile robots, provides a feasible implementation for improving the coverage and timeliness of earthquake early warning information within the target jurisdiction area.

[0074] This application's embodiments comprehensively enhance the systematicness, adaptability, and execution efficiency of the earthquake early warning and response process. By receiving and analyzing earthquake early warning information to determine the actual impact on the target area, and combining this with preset rules to match differentiated alarm commands, it helps to achieve the correspondence between risk classification and alarm strategies. Furthermore, based on the real-time distribution of mobile robots and the dynamic allocation of broadcast areas and planning of movement paths according to population density, alarm resources can be dynamically allocated towards areas with high population density, thereby improving the population coverage efficiency of alarm information. The robots perform multimodal broadcasts while moving along the planned path and can dynamically adjust their behavior through environmental perception and interactive feedback, enhancing the flexibility and on-site adaptability of the alarm process. In addition, the local autonomy mechanism and multi-robot collaborative scheduling capabilities involved in the solution provide support for maintaining the continuity of system functions in complex or restricted environments, helping to achieve more stable and scalable mobile alarm coverage in multiple scenarios. Overall, this solution, by integrating earthquake analysis, path planning, dynamic broadcasting, and collaborative control, provides a feasible approach for constructing a mobile, schedulable, and hierarchical earthquake alarm execution system in densely populated areas.

[0075] Based on the same inventive concept, the embodiments of this application provide, as follows: Figure 2 An electronic device (specifically, the aforementioned control platform) is shown, comprising: Processor 21; Memory 22 is used to store executable instructions of the processor 21; The processor 21 is configured to execute a robot earthquake alarm method as described above.

[0076] Based on the same inventive concept, embodiments of this application provide a non-transitory computer-readable storage medium, which, when the instructions in the storage medium are executed by the processor of an electronic device, enables the electronic device to execute a robot earthquake alarm method as described above.

[0077] Based on the same inventive concept, embodiments of this application provide a computer program product, including computer instructions, which are executed by a processor to implement a robot earthquake alarm method as described above.

[0078] Since the electronic device described in this embodiment is an electronic device used to implement the information processing method in the embodiments of this application, those skilled in the art can understand the specific implementation methods and various variations of the electronic device in this embodiment based on the information processing method described in the embodiments of this application. Therefore, how the electronic device implements the method in the embodiments of this application will not be described in detail here. Any electronic device used by those skilled in the art to implement the information processing method in the embodiments of this application falls within the scope of protection of this application.

[0079] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0080] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations 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, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0081] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0082] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0083] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0084] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A robot earthquake alarm method, characterized in that, The method is applied to a control platform corresponding to a target jurisdiction area, the control platform communicating with at least one mobile robot within the target jurisdiction area, and includes: After receiving earthquake early warning information, the actual impact of the earthquake on the target jurisdiction area is determined based on the earthquake early warning information, which includes the earthquake magnitude and the distance to the epicenter. Based on the preset correlation between the degree of impact and the alarm content, as well as the actual degree of impact, the target alarm content is determined, and the target alarm content is sent to each mobile robot in the target jurisdiction area; Based on the distribution location of each mobile robot in the target jurisdiction area and the pedestrian density data within a preset distance range of each mobile robot, the target broadcast area corresponding to each mobile robot is determined; Based on the current location of each mobile robot, determine the movement path of each mobile robot in the corresponding target broadcast area; Each mobile robot is controlled to move along a corresponding path, and during the movement, the target alarm content is broadcast to achieve earthquake alarm for the target jurisdiction area.

2. The robot earthquake alarm method as described in claim 1, characterized in that, Based on the preset correlation between the degree of impact and the alarm content, as well as the actual degree of impact, the target alarm content is determined, including: When the actual impact level is low, the target alarm content will be determined as "wait in place". When the actual impact level is moderate, the target alarm content will be determined by the orderly movement of the guide personnel to the preset safe area. When the actual impact level is high, an immediate emergency evacuation will be identified as the target alarm content.

3. The robot earthquake alarm method as described in claim 1, characterized in that, Based on the distribution location of each mobile robot in the target jurisdiction area and the pedestrian density data within a preset distance range of each mobile robot, the target broadcast area corresponding to each mobile robot is determined, including: For each mobile robot, multiple sub-regions with human density data are identified within a preset distance range corresponding to that mobile robot; The sub-regions are pieced together to form the target broadcast area corresponding to the mobile robot, arranged in order of increasing distance from each other.

4. The robot earthquake alarm method as described in claim 1, characterized in that, Based on the distribution location of each mobile robot in the target jurisdiction area and the pedestrian density data within a preset distance range of each mobile robot, the target broadcast area corresponding to each mobile robot is determined, including: For each mobile robot, multiple sub-regions with human density data are identified within a preset distance range corresponding to that mobile robot; Based on the descending order of pedestrian density data for each sub-region, the sub-regions are pieced together to form the target broadcast area corresponding to the mobile robot.

5. The robot earthquake alarm method as described in claim 1, characterized in that, Based on the distribution location of each mobile robot in the target jurisdiction area and the pedestrian density data within a preset distance range of each mobile robot, the target broadcast area corresponding to each mobile robot is determined, including: For each mobile robot, multiple sub-regions with human density data are identified within a preset distance range corresponding to that mobile robot; Based on the first weight corresponding to the distance between each sub-region and the mobile robot, and the second weight of each sub-region with respect to the pedestrian density data, the splicing order between each sub-region is determined, and the sub-regions are spliced ​​together into the target broadcast area corresponding to the mobile robot according to the splicing order.

6. The robot earthquake alarm method as described in claim 1, characterized in that, Determining the actual impact of an earthquake on the target jurisdiction area based on the earthquake early warning information includes: The earthquake early warning information is input into a preset earthquake intensity attenuation model to determine the theoretical earthquake intensity at a preset reference location in the target jurisdiction area. The site building parameters of the target jurisdiction area are determined from the local geological condition database associated with the target jurisdiction area; The theoretical seismic intensity is corrected based on the site building parameters to obtain the expected seismic intensity; Based on the pre-defined correlation between earthquake intensity and impact level, the actual impact of the earthquake on the target jurisdiction area is determined.

7. The robot earthquake alarm method as described in claim 1, characterized in that, Control each mobile robot to move along a corresponding movement path, and broadcast the target alarm content during the movement, including: Each mobile robot is controlled to move cyclically along its corresponding path, broadcasting the target alarm content during the movement until an earthquake early warning cancellation command is received. Then, each mobile robot is controlled to stop broadcasting the target alarm content.

8. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute a robot earthquake alarm method as described in any one of claims 1 to 7.

9. A non-transitory computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device is able to perform a robot earthquake alarm method as described in any one of claims 1 to 7.

10. A computer program product, characterized in that, It includes computer instructions, which are executed by a processor to implement a robot earthquake alarm method as described in any one of claims 1 to 7.

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