Intelligent shopping mall inspection robot system based on hierarchical map dynamic switching and distributed task cooperation

Abstract

This invention provides an intelligent shopping mall inspection robot system based on hierarchical map dynamic switching and distributed task collaboration. It includes a scheduling terminal, a server, and multiple robot nodes. The scheduling terminal broadcasts task instructions, including store IDs, to the robot nodes, selects the optimal robot based on response signals, and sends inspection instructions. It also updates and sends new map information to the server. The server updates the corresponding local map and synchronously updates the global map. Based on the two-layer architecture of the global and local maps, the robot nodes navigate to the anchor point coordinates corresponding to the store ID in the global map, switch to the local map, and update their positioning origin to the anchor point coordinates, achieving a seamless transition. They then inspect the local map according to a preset path. This invention reduces map maintenance costs, improves task allocation response speed, enhances multi-robot collaboration efficiency, and enables map switching without complex coordinate transformations, effectively avoiding positioning loss.

Description

Technical Field

[0001] This invention relates to an intelligent shopping mall inspection robot system based on dynamic switching of layered maps and distributed task collaboration, belonging to the field of intelligent inspection robot technology. Background Technology

[0002] Currently, shopping mall inspection robot systems typically adopt a "cloud-edge-device" technical architecture. The device itself (the robot) is responsible for execution and real-time perception, using multi-sensor fusion technology such as LiDAR, depth cameras, and ultrasonic sensors to achieve autonomous navigation, obstacle avoidance, and image acquisition. The scheduling platform (the "on-site commander") acts as the robot's task scheduling, path planning, remote monitoring, and multi-robot collaboration. The cloud, the AI ​​brain, is the system's "intelligence center." All the massive amounts of data collected by the robots are uploaded to the cloud-based AI platform for in-depth analysis and model training, generating operational reports, insights, and decision-making suggestions, which are then distributed to the device and edge for execution, forming a continuously evolving closed loop.

[0003] However, existing shopping mall inspection robot systems have shortcomings in the following aspects: 1. Complex map management: When the mall layout changes frequently, the global map needs to be rebuilt, resulting in high maintenance costs; 2. Low task allocation efficiency: Relies on centralized scheduling, resulting in high communication pressure and response delay; 3. Poor multi-robot collaboration: The lack of an efficient task matching mechanism for robots on different floors can easily lead to resource waste or task conflicts. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent shopping mall inspection robot system based on hierarchical map dynamic switching and distributed task collaboration, which can achieve efficient task allocation, rapid map switching and flexible map updates, and solve the problems of difficult map maintenance, slow task response and low collaboration efficiency in the existing technology.

[0005] The technical solution of this invention is: An intelligent shopping mall inspection robot system based on hierarchical map dynamic switching and distributed task collaboration includes a scheduling terminal, a server terminal, and multiple robot nodes. The dispatcher is used to broadcast task instructions, including the store ID, to robot nodes; select the optimal robot based on the response signal and send inspection instructions to the corresponding robot node; and update and send new map information to the server. Server-side: After receiving new map information, the server updates the corresponding local map, updates the global map synchronously, and sends the new map information to the robot nodes. Robot Node: Upon receiving new map information, it updates both the local and global maps. Upon receiving a task instruction, it parses the store ID and compares it with locally stored information. If the comparison fails, it silently ignores the task and maintains the original inspection path. If the comparison succeeds, it sends a return response signal and robot ID to the scheduling terminal. Upon receiving an inspection instruction, based on the two-layer architecture of the global and local maps, it loads the corresponding local map from local storage, navigates to the anchor point coordinates corresponding to the store ID in the global map, switches to the local map, updates the positioning origin to the anchor point coordinates, achieving a seamless transition, and inspects according to the preset path in the local map.

[0006] Furthermore, the global map includes anchor coordinates for the mall's public areas and store entrances, while the local map consists of independent high-precision maps for each store.

[0007] Furthermore, in the scheduling terminal, the optimal robot is selected based on the response signal, specifically by selecting the first responder or allocating the optimal robot according to a preset strategy.

[0008] Furthermore, in the dispatching terminal, if no response signal is received from the robot node within a preset time after broadcasting the task instruction, it is determined that the store does not exist and an error message is displayed.

[0009] Furthermore, after the robot node inspects the local map along a preset path, it switches back to the global map and resumes regular patrols.

[0010] The beneficial effects of this invention are: I. This intelligent shopping mall inspection robot system based on dynamic switching of layered maps and distributed task collaboration can reduce map maintenance costs, improve task allocation response speed, improve multi-machine collaboration efficiency, and achieve map switching without complex coordinate transformation, effectively avoiding positioning loss. It is suitable for indoor inspection scenarios such as shopping malls where layout changes are frequent.

[0011] Second, this invention employs a two-layer architecture of global and local maps, achieving seamless map switching through anchor point coordinates; it utilizes distributed task broadcasting and local matching mechanisms to improve multi-machine collaboration efficiency and reduce communication dependencies; it supports incremental hot-loading map updates and features handling for unresponsive exceptions. Incremental updates simplify maintenance, support plug-and-play map usage, and the exception feedback mechanism enhances system fault tolerance. Attached Figure Description

[0012] Figure 1 This is an illustrative diagram illustrating the intelligent shopping mall inspection robot system based on dynamic switching of layered maps and distributed task collaboration according to an embodiment of the present invention. Figure 2 This is an illustrative diagram illustrating the dynamic switching and inspection based on a two-layer architecture of global and local maps in the embodiment. Figure 3 This is a schematic diagram illustrating the distributed task collaboration of robot nodes in the embodiment. Detailed Implementation

[0013] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0014] This embodiment provides an intelligent shopping mall inspection robot system based on hierarchical map dynamic switching and distributed task collaboration, such as... Figure 1 and Figure 2 It includes a scheduling terminal, a server terminal, and multiple robot nodes.

[0015] The dispatcher is used to broadcast task instructions, including the store ID, to robot nodes, select the optimal robot based on the response signal, and send inspection instructions to the corresponding robot node; it also updates and sends new map information to the server.

[0016] In the scheduling terminal, the optimal robot is selected based on the response signal, specifically by selecting the first responder or allocating the optimal robot according to a preset strategy.

[0017] In the dispatching system, if no response signal is received from the robot node within a preset time after broadcasting the task instruction, the system determines that the store does not exist and displays an error message. This no-response exception handling mechanism facilitates subsequent troubleshooting of missing maps or incorrect task instructions.

[0018] Server-side: After receiving new map information, the server updates the corresponding local map, updates the global map synchronously, and sends the new map information to the robot nodes.

[0019] Robot node: After receiving new map information, it updates the local and global maps; after receiving task instructions, such as... Figure 3 The system parses the store ID and compares it with the information stored locally. If the comparison fails, the task is silently ignored, and the original inspection path is maintained. If the comparison is successful, a return response signal and robot ID are sent to the scheduling terminal. After receiving the inspection instruction, based on the two-layer architecture of global map and local map, the corresponding local map stored locally is loaded, the system navigates to the anchor point coordinates corresponding to the store ID in the global map, switches to the local map, updates the positioning origin to the anchor point coordinates, and achieves a seamless transition. The system then inspects according to the preset path in the local map.

[0020] The global map includes anchor point coordinates for the mall's public areas and store entrances. The public areas include corridors, elevators, etc. Local maps are independent, high-precision maps for each store. When parsing store IDs and comparing them with locally stored information, robot nodes can use spatial indexing algorithms to accelerate local matching of store IDs.

[0021] This intelligent shopping mall inspection robot system, based on dynamic switching of layered maps and distributed task collaboration, can reduce map maintenance costs, improve task allocation response speed, enhance multi-machine collaboration efficiency, and achieve map switching without complex coordinate transformation, effectively avoiding positioning loss. It is suitable for indoor inspection scenarios such as shopping malls where layout changes are frequent.

[0022] This invention employs a two-tier architecture of global and local maps, achieving seamless map switching through anchor point coordinates. It utilizes distributed task broadcasting and local matching mechanisms to improve multi-machine collaboration efficiency and reduce communication dependencies. It supports incremental hot-loading map updates and features handling for unresponsive exceptions. Incremental updates simplify maintenance, support plug-and-play map usage, and the exception feedback mechanism enhances system fault tolerance.

[0023] This intelligent shopping mall inspection robot system, based on dynamic switching of layered maps and distributed task collaboration, is illustrated below, taking the task of "inspecting store A" as an example: The dispatcher broadcasts the task instruction, including the ID of store A, to all robot nodes. Each robot node independently determines whether its local map library contains the target store: robot nodes other than robot R2 do not contain the target store, silently ignore the task, and maintain the original inspection path. Robot R2 on the second floor detects the presence of a "store A.map" file in its local storage and returns "R2 is executable" to the dispatcher. The dispatcher selects the optimal robot based on the response signal and sends the inspection instruction to the corresponding robot node. After receiving the inspection instruction, R2 plans a path to the anchor point (X,Y) of store A in the global map and navigates there. Upon reaching the anchor point, it switches to the local map of store A, sets the origin as the anchor point coordinates, and inspects the store along a preset path. After inspection, it switches back to the global map and resumes regular patrols. If the store A map is updated, the "store A.map" file in robot R2 is replaced, and the new map is automatically loaded.

[0024] This intelligent shopping mall inspection robot system, based on dynamic switching of layered maps and distributed task collaboration, employs an incremental map update strategy as follows: When a store map changes, the administrator uploads a new store map file (e.g., "Store A.map") to the server via the backend; the server pushes the new file to the robot's storage directory on the corresponding floor, directly overwriting the old file; after detecting the file change, the robot node automatically refreshes the map index, achieving "hot loading." While updating the local store map, the corresponding store name or anchor point coordinates in the global map are simultaneously modified. Since map file transmission may be interrupted, encrypted transmission and verification mechanisms are used to ensure file integrity.

[0025] The above are merely preferred embodiments of the present invention and do not constitute any limitation on the present invention. Any equivalent substitutions or modifications made by those skilled in the art to the technical solutions and content disclosed in the present invention without departing from the scope of the present invention shall be deemed to have remained within the scope of protection of the present invention.

Claims

1. An intelligent shopping mall inspection robot system based on hierarchical map dynamic switching and distributed task collaboration, characterized in that: This includes the scheduling terminal, the server terminal, and multiple robot nodes. The dispatcher is used to broadcast task instructions, including the store ID, to robot nodes; select the optimal robot based on the response signal and send inspection instructions to the corresponding robot node; and update and send new map information to the server. Server-side: After receiving new map information, the server updates the corresponding local map, updates the global map synchronously, and sends the new map information to the robot nodes. Robot Node: Upon receiving new map information, it updates both the local and global maps. Upon receiving a task instruction, it parses the store ID and compares it with locally stored information. If the comparison fails, it silently ignores the task and maintains the original inspection path. If the comparison succeeds, it sends a return response signal and robot ID to the scheduling terminal. Upon receiving an inspection instruction, based on the two-layer architecture of the global and local maps, it loads the corresponding local map from local storage, navigates to the anchor point coordinates corresponding to the store ID in the global map, switches to the local map, updates the positioning origin to the anchor point coordinates, achieving a seamless transition, and inspects according to the preset path in the local map.

2. The intelligent shopping mall inspection robot system based on hierarchical map dynamic switching and distributed task collaboration as described in claim 1, characterized in that: The global map includes anchor point coordinates for the mall's public areas and store entrances, while the local map consists of independent high-precision maps for each store.

3. The intelligent shopping mall inspection robot system based on hierarchical map dynamic switching and distributed task collaboration as described in claim 1, characterized in that: In the scheduling terminal, the optimal robot is selected based on the response signal, specifically by selecting the first responder or allocating the optimal robot according to a preset strategy.

4. The intelligent shopping mall inspection robot system based on hierarchical map dynamic switching and distributed task collaboration as described in any one of claims 1-3, characterized in that: In the dispatching terminal, if no response signal is received from the robot node within a preset time after broadcasting the task instruction, the store is determined to not exist and an error message is displayed.

5. The intelligent shopping mall inspection robot system based on hierarchical map dynamic switching and distributed task collaboration as described in any one of claims 1-3, characterized in that: After inspecting the local map along a preset path, the robot node switches back to the global map and resumes regular patrols.

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