A dynamic environment map updating method and device, a mobile device, and a storage medium

Abstract

The application relates to the technical field of robots and discloses a dynamic environment map updating method and device, a mobile device and a storage medium, which are applied to the mobile device and comprise the following steps: in the process of driving the mobile device based on a global map, whether the mobile device reaches a variable area is detected, the variable area being a local area in the global map where environment changes are prone to occur; if the variable area is reached, map data corresponding to the variable area is acquired when the variable area is crossed; and after triggering map updating, a local map corresponding to the variable area in the global map is updated according to the map data, so that an updated global map is obtained. The application can realize accurate and localized map updating of the variable area in the dynamic environment, does not need manual participation in data collection and map correction, greatly reduces the time and resource cost of map updating, improves the automation degree of map updating, improves the positioning and navigation precision of the mobile device based on the map, and meets the demand of long-term autonomous operation of the mobile device in the dynamic scene.

Description

Technical Field

[0001] This invention relates to the field of robotics, specifically to a method, apparatus, mobile device, and storage medium for updating dynamic environment maps. Background Technology

[0002] Simultaneous Localization and Mapping (SLAM) is a core technology for robots to achieve autonomous navigation and environmental perception. Current mainstream SLAM methods are generally based on the assumption of a static environment, constructing a global map through a single full-scene data acquisition. This static map serves as the benchmark for subsequent robot localization and navigation. However, in real-world application scenarios such as offices, shopping malls, and warehouses, the environment is dynamically changing, with objects easily shifting, doors and windows opening and closing, and temporary obstacles appearing. The map contains volatile areas where these environmental changes occur frequently. Although these areas only constitute a small portion of the global map, they significantly reduce its spatial accuracy. When a robot performs localization based on such outdated static global maps, significant pose estimation errors occur in these volatile areas, leading to localization failure and even interrupting the robot's navigation task.

[0003] To address the aforementioned technical issues, existing technologies typically employ methods such as manually re-collecting full-scene data and reconstructing a global map, or manually marking erroneous areas of the map and making local corrections. However, both of these methods require significant manual intervention, which is not only time-consuming and labor-intensive, resulting in low map update efficiency, but also fails to achieve automated and intelligent map updates, making it difficult to meet the practical needs of robots operating autonomously in dynamic environments for extended periods. Summary of the Invention

[0004] This invention provides a dynamic environment map update method, apparatus, mobile device, and storage medium to solve the problems of existing map update schemes that require manual intervention, global reconstruction is time-consuming and labor-intensive, cannot achieve automated and intelligent local updates, and are difficult to meet the needs of robots to operate autonomously in dynamic scenarios for a long time.

[0005] In a first aspect, the present invention provides a dynamic environment map update method applied to a mobile device. The method includes: during the movement of the mobile device based on a global map, detecting whether the mobile device has reached a volatile area, where the volatile area is a local area in the global map that is prone to environmental changes; if the volatile area is reached, acquiring the map data corresponding to the volatile area when traversing the volatile area; and when a map update is triggered, updating the local map corresponding to the volatile area in the global map according to the map data to obtain the updated global map.

[0006] The dynamic environment map update method provided by this invention acquires map data of a volatile area when a mobile device travels through it based on a global map and reaches such an area. Upon triggering a map update, the local map corresponding to the volatile area in the global map is updated based on the local map data, resulting in an updated global map. This invention, by defining volatile areas prone to environmental changes and selectively collecting map data from these areas during the mobile device's movement, performs local updates to the global map instead of reconstructing the entire map. This achieves accurate and localized map updates for volatile areas in dynamic environments, eliminating the need for manual data collection and map correction throughout the process. This significantly reduces the time and resource costs of map updates, increases the automation level of map updates, and avoids pose estimation errors and positioning / navigation failures caused by environmental changes in volatile areas. This effectively improves the map-based positioning and navigation accuracy of mobile devices, meeting the needs of long-term autonomous operation of mobile devices in dynamic scenarios.

[0007] In one optional implementation, the mobile device is equipped with a laser device and an odometer. When traversing a volatile zone, it acquires map data corresponding to the volatile zone, including: after the mobile device enters the volatile zone, acquiring laser data collected by the laser device and driving information collected by the odometer; determining surrounding object information of the mobile device based on the laser data, and determining the pose information of the mobile device based on the laser data and driving information; after the mobile device leaves the volatile zone, using the laser data and pose information as map data for this traversal of the volatile zone; and acquiring multiple sets of map data after traversing the volatile zone multiple times.

[0008] This invention, through dual-sensor fusion and collaborative data acquisition, ensures the accuracy and spatial correlation of map data, providing precise reference for data matching of the global map. It collects map data in a "drive-in collection, drive-out generation" manner and supports obtaining multiple sets of local data after multiple traversals, enabling the understanding of environmental changes in volatile areas. This lays a multi-dimensional data foundation for subsequent occupancy probability calculations, avoids the random errors of single collections, improves the integrity and reliability of map data, and provides core data support for accurate map updates of volatile areas.

[0009] In one optional implementation, updating the local map corresponding to the volatile area in the global map based on map data to obtain an updated global map includes: determining a first local map corresponding to the volatile area in the global map based on pose information in the latest set of map data; converting laser data in the latest set of map data into a raster map, and updating the first local map based on the raster map to obtain a second local map; and replacing the first local map in the global map with the second local map to obtain an updated global map.

[0010] This invention uses the latest pose information as an anchor point, which can ensure the accuracy of the updated area and avoid update errors caused by positioning offset in volatile areas. Furthermore, the local replacement map update method only modifies the local map corresponding to the volatile area, without affecting other fixed areas of the global map. While ensuring the effectiveness of the update, it significantly reduces the amount of computation and improves the execution efficiency of map updates.

[0011] In one optional implementation, updating the first local map based on the grid map to obtain the second local map includes: using the first local map as a reference, determining the occupied area of ​​the latest obstacle in the variable zone each time the variable zone is traversed based on the laser data in each group of map data; determining the occupancy probability of each grid cell in the grid map based on the occupied area of ​​the latest obstacle corresponding to all groups of map data; if the occupancy probability is higher than a preset threshold, the grid cell is regarded as a valid grid cell of the grid map, otherwise it is regarded as an invalid grid cell of the grid map; updating the corresponding grid cells of the first local map based on the valid grid cells, and maintaining the data of the corresponding grid cells of the first local map based on the invalid grid cells, to obtain the second local map.

[0012] This invention uses a baseline map as a reference and focuses on the real-time environmental changes in volatile areas by limiting the latest obstacles. It can objectively quantify the probability of a grid being occupied by an obstacle by the occupancy probability, so that only relatively fixed scene changes are retained when the map is updated. The differentiated rules of effective grid coverage and invalid grid retention not only ensure the real-time synchronization of environmental changes in volatile areas, but also retain the original map data of unchanged areas, further reducing the amount of computation. The final generated second local map can accurately reflect the current actual environmental state of the volatile area, greatly improving the accuracy and adaptability of map updates.

[0013] In one optional implementation, the method further includes: obtaining the current time; if the current time reaches a preset time, triggering a map update operation; and / or obtaining the positioning quality of the volatile area; if the positioning quality is lower than a preset threshold, triggering a map update operation; and / or detecting whether a manual triggering instruction has been received; if a manual triggering instruction has been received, triggering a map update operation.

[0014] This invention, by setting multiple triggering methods, can avoid automatically updating the map after each crossing, which would affect the operating efficiency of the mobile device. At the same time, by setting regular automatic updates, automatic updates when the map fails, and manual emergency updates, it can improve the automation of map updates, take into account the flexibility of scene adaptation, and ensure the navigation continuity of the mobile device in different application scenarios.

[0015] In one optional implementation, during the movement of the mobile device based on the global map, detecting whether the mobile device has reached a volatile zone includes: obtaining the location information of the mobile device and determining whether the location information is in a preset location area in the global map, wherein the volatile zone and the preset location area have a one-to-one correspondence, and the number of both the volatile zone and the preset location area is at least one; if the location information is in the preset location area, then it is determined that the mobile device has reached the volatile zone corresponding to the preset location area.

[0016] This invention can complete the detection simply by matching the location information with the preset area by pre-setting the location of the volatile zone. The logic is simple and the amount of calculation is small. It can be completed in real time and efficiently while the mobile device is in motion. Moreover, the one-to-one correspondence can avoid confusion between different volatile zones and ensure the accuracy of volatile zone determination.

[0017] In one alternative implementation, after obtaining the updated global map, the method further includes: adjusting the local pose information of the mobile device in the volatile area based on the updated global map.

[0018] This invention utilizes updated, accurate maps to adjust the local pose of mobile devices, eliminating pose errors caused by outdated maps. This ensures that the device's pose information closely matches the actual environment, guaranteeing the positioning and navigation accuracy of mobile devices in volatile areas. It also avoids problems such as navigation path errors and task interruptions caused by pose deviations, thereby improving the stability and reliability of mobile devices operating autonomously in dynamic environments.

[0019] Secondly, the present invention provides a dynamic environment map updating device applied to a mobile device. The device includes: a location detection module, used to detect whether the mobile device has reached a variable area during the movement of the mobile device based on a global map. The variable area is a local area in the global map that is prone to environmental changes; a data acquisition module, used to acquire map data corresponding to the variable area when traversing the variable area if the variable area is reached; and a map updating module, used to update the local map corresponding to the variable area in the global map based on the map data in response to a triggered map update operation, so as to obtain an updated global map.

[0020] Thirdly, the present invention provides a mobile device, including: a controller, a laser device, and an odometer, wherein the controller is connected to the laser device and the odometer; the controller includes: a memory and a processor, which are communicatively connected to each other; the memory stores computer instructions, and the processor executes the computer instructions to perform the dynamic environment map update method of the first aspect or any corresponding embodiment described above.

[0021] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the dynamic environment map update method of the first aspect or any corresponding embodiment described above. Attached Figure Description

[0022] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0023] Figure 1 This is a schematic diagram of the structure of a mobile device according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the first process of the dynamic environment map updating method according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the global map before updating according to the dynamic environment map updating method of the present invention; Figure 4 This is a schematic diagram of the updated global map using the dynamic environment map update method according to an embodiment of the present invention; Figure 5 This is a schematic diagram of a second process for a dynamic environment map updating method according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the third process of the dynamic environment map updating method according to an embodiment of the present invention; Figure 7 This is a structural block diagram of a dynamic environment map updating device according to an embodiment of the present invention; Figure 8 This is a schematic diagram of the hardware structure of the controller according to an embodiment of the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0026] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0027] As an optional application scenario of this invention, such as Figure 1 As shown, the mobile device 1 is equipped with a controller 10, a laser device 20, and an odometer 30. The controller 10 establishes a communication connection with the laser device 20 and the odometer 30 to receive and process the data collected by the laser device 20 and the odometer 30, and to coordinate and control the robot to complete autonomous driving and environmental perception related operations.

[0028] In existing technologies, the working process and map maintenance schemes of such robots mainly fall into two categories, both of which have significant technical defects, as follows: The first type is the one-time mapping and global reconstruction scheme, which is the most basic and widely used scheme. The robot performs a complete traversal of the environment in the initial stage, using algorithms such as Gmapping and Cartographer to fuse sensor data collected by the laser device 20 and the odometer 30 to generate a global static map (such as a grid-based map). Figure 1 Once generated, the data is permanently stored as a benchmark for the robot's long-term localization and path planning. The robot initiates autonomous driving tasks based on this static global map. During the driving process, the controller 10 continuously controls the laser device 20 and the odometer 30 to be in working condition. The odometer 30 collects the robot's driving information in real time, including driving distance, speed, and turning angle. The laser device 20 collects laser data around the robot in real time. The controller 10 receives the above driving information and laser data. On the one hand, it combines the two types of data to calculate the robot's pose information. On the other hand, it compares the data with the preset static global map to determine whether its driving position is within a specific area marked on the map.

[0029] When a map becomes invalid due to environmental changes, the standard solution is to perform a global reconstruction. This involves the operator controlling the robot to re-collect comprehensive data on the entire environment and running a mapping algorithm to regenerate a completely new global map to replace the old one. The second approach is a manual intervention solution for local map adjustments. This solution addresses the problem of the large workload associated with global reconstruction and is considered an auxiliary improvement. It allows for manual intervention when local map inaccuracies are detected. For example, operators can manually erase or modify areas deemed changed (such as moving obstacles) in map editing software. Furthermore, operators can manually control the robot to rescan only specific "problem areas" and replace the newly scanned small local map patches with the corresponding positions on the original global map, thus achieving local correction.

[0030] However, both of the above-mentioned existing solutions have significant drawbacks that are difficult to overcome, which severely restrict the long-term autonomy of robots in dynamic scenarios, as follows: ① Lacking adaptability and unable to cope with dynamic environments, the core flaw of both schemes lies in their reliance on static environment assumptions. Once the real environment changes, the pre-built static map becomes outdated, leading to a sharp drop in robot positioning accuracy or even complete failure, resulting in poor system robustness. ② High maintenance costs and low efficiency. For one-time mapping and global reconstruction solutions, global reconstruction requires full coverage data collection of the entire environment again. Regardless of the size of the changed area, it requires the same time and workload as the first mapping, resulting in huge waste of resources and extremely low efficiency. Moreover, the robot cannot perform autonomous driving tasks normally during reconstruction, which seriously affects the continuity of work. ③ It relies on human intervention and lacks automation. Although the local map adjustment scheme with human intervention avoids global reconstruction, it heavily depends on the judgment and manual operation of operators. From identifying the changed area and controlling the robot to rescan, to manually performing map replacement, the entire process requires human participation. This not only increases labor costs, but also introduces subjective errors in manual operation, making it difficult to guarantee the accuracy of correction. It cannot be automated and is not suitable for unattended long-term operation scenarios. ④ The update strategy is rigid and not intelligent enough. The two existing methods are both passive and retrospective updates. They only take remedial measures when obvious errors occur in the positioning. They lack the ability to actively and automatically detect environmental changes and intelligently and seamlessly complete local map updates during the robot's daily operation. This is the key to achieving truly long-term autonomous navigation.

[0031] Furthermore, the global map relied upon by both schemes is essentially a static map. When the robot travels to an area where the environment is prone to change (i.e., a changeable area), although the laser device 20 and the odometer 30 will continuously collect data, in the existing technology, the robot will only use the collected data for real-time positioning and will not specifically store the local data of the area. Once the changeable area experiences environmental changes such as object displacement or the appearance of temporary obstacles, the static map will become disconnected from the actual environment, which will lead to deviations in the pose information calculated by the controller 10, causing problems such as positioning failure and navigation interruption, further highlighting the impact of the above-mentioned shortcomings.

[0032] To address the shortcomings of existing technologies, such as robots relying on static global maps, the failure of positioning and navigation due to changes in volatile environments, and the inability to autonomously update maps in volatile areas, this invention provides a dynamic environment map updating method. By updating local maps in volatile areas, this method reduces the time and resource costs of map updates, improves the automation level of map updates, and enhances the map-based positioning and navigation accuracy of mobile devices.

[0033] According to an embodiment of the present invention, a dynamic environment map update method embodiment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0034] This embodiment provides a dynamic environment map update method, which can be used in the aforementioned mobile devices, such as robots. Figure 2 This is a flowchart of a dynamic environment map update method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps: Step S201: During the process of the mobile device traveling based on the global map, detect whether the mobile device has reached a volatile area. The volatile area is a local area in the global map that is prone to environmental changes.

[0035] Specifically, in this embodiment of the invention, taking a robot as an example, the robot generates a global map of the overall environment (such as a grid-based map) by traversing the environment in the initial stage. This map serves as the reference for the robot's movement and positioning, covering the entire area where the robot works. Operators can pre-mark specific areas prone to environmental changes (not the entire area of ​​the global map) on the global map, using these as variable areas of the global map, such as... Figure 3In the global map shown, the areas marked with boxes are variable zones. For example, if the robot's working scenario is a warehouse, areas such as goods stacking areas and temporary passageways in the warehouse are prone to environmental changes such as goods shifting or temporary obstacles (such as forklift parking). These areas can be set as variable zones, and the number of variable zones can be set according to needs. On the other hand, areas such as walls and fixed shelves in the warehouse have a relatively stable environment and are not considered variable zones.

[0036] After identifying the global map and its volatile zones, the robot can move autonomously based on the global map during operation. During movement, the robot's controller 10 receives sensor data to determine whether its current position has entered a volatile zone. For example, a warehouse robot follows a preset path from the warehouse entrance to the goods outbound area. When it reaches the boundary line of the goods stacking area (volatile zone), it is determined to have entered the volatile zone. If it is moving in a non-volatile zone such as a fixed shelf, it continues to move according to the global map.

[0037] Step S202: If a volatile zone is reached, the map data corresponding to the volatile zone is obtained when traversing the volatile zone.

[0038] Specifically, in this embodiment of the invention, when the controller 10 determines that the robot has reached the volatile zone, it will control the laser device 20 and the odometer 30 to continuously collect data during the period when the robot crosses the volatile zone (i.e., the entire movement process from entering the boundary of the volatile zone to leaving the boundary of the volatile zone, such as the entire process of a warehouse robot traveling from the entrance of the goods stacking area to the exit).

[0039] If the robot stores multiple global maps, it maintains at least one historical local map file library containing multiple traversal records for each map. If the global map contains multiple volatile zones, it maintains multiple historical local map file libraries for this global map. When the robot performs a task and determines that it has entered a volatile zone based on its positioning information, it automatically starts recording map data. When the robot leaves the volatile zone, it automatically stops recording and saves the recorded data packet as an independent local map file to the corresponding historical local map file library. The file is named with a timestamp. This process only saves data and does not modify the current global map, ensuring that the navigation task is not interrupted.

[0040] For example, when a warehouse robot traverses a goods storage area, the laser device collects laser data such as the position and shape of the goods in the area in real time, the odometer collects driving information such as the robot's speed and turning angle, and the controller 10 controls the start and stop of data collection. All data from this traverse is named as an independent file with a timestamp and stored in the file library. The active map currently in use is not modified throughout the process to ensure that the goods handling navigation task proceeds normally until the robot drives out of the boundary of the goods storage area, at which point the data collection and saving operation stops.

[0041] Step S203: In response to triggering a map update operation, update the local map corresponding to the volatile area in the global map based on the map data to obtain the updated global map.

[0042] Specifically, in this embodiment of the invention, to avoid map updates affecting the robot's current operation, a trigger signal for the map update operation is pre-set. Map updates are only performed when the trigger signal is met, thus avoiding map updates every time the robot passes through a volatile area. When the controller 10 receives the trigger signal for the map update operation, it uses the previously collected and stored map data corresponding to the volatile area as a basis to correct and update the local map portion in the global map that completely corresponds to the location of the volatile area, rather than reconstructing the entire global map. This results in an updated global map where only the local map of the volatile area is updated, while the maps of the remaining non-volatile areas remain unchanged. Figure 4 In the global map shown, the boxes mark the volatile areas and Figure 3 The environment changes in the volatile zones, while it remains unchanged in the non-volatile zones. During subsequent autonomous movement, the robot will navigate based on the updated global map and continue to collect map data of the volatile zones as it passes through them, repeating this cycle to meet the robot's long-term autonomous operation and dynamic environment adaptation requirements.

[0043] For example, after the warehouse robot completes the passage through the goods stacking area and stores the map data, if the map update trigger condition is met, the controller 10 will call the stored map data, find the local map part in the global map that corresponds to the goods stacking area, and use the newly collected data to correct the environmental changes such as the position of the moved goods in the area. After the local map is updated, a brand new global map of the warehouse is formed, which is used for the robot's subsequent positioning and autonomous driving.

[0044] The dynamic environment map update method provided by this invention acquires map data corresponding to a volatile area when a mobile device travels through it based on a global map and reaches such an area. Upon triggering a map update, the local map corresponding to the volatile area in the global map is updated based on this map data, resulting in an updated global map. This invention, by defining volatile areas prone to environmental changes and selectively collecting map data corresponding to these areas during the mobile device's movement, performs local updates to the global map instead of reconstructing the entire map. This enables accurate and localized map updates for volatile areas in dynamic environments, eliminating the need for manual data collection and map correction throughout the process. This significantly reduces the time and resource costs of map updates, increases the automation level of map updates, and avoids pose estimation errors and positioning / navigation failures caused by environmental changes in volatile areas. This effectively improves the map-based positioning and navigation accuracy of mobile devices, meeting the needs of long-term autonomous operation of mobile devices in dynamic scenarios.

[0045] This embodiment provides a dynamic environment map update method, which can be used in the aforementioned mobile devices, such as robots. Figure 5 This is a flowchart of a dynamic environment map update method according to an embodiment of the present invention, such as... Figure 5 As shown, the process includes the following steps: Step S501: During the mobile device's movement based on the global map, detect whether the mobile device has reached a volatile area. A volatile area is a local region in the global map where environmental changes are likely to occur. For details, please refer to [link to relevant documentation]. Figure 2 Step S201 of the illustrated embodiment will not be described again here.

[0046] Step S502: If a volatile zone is reached, the map data corresponding to the volatile zone is obtained when traversing the volatile zone.

[0047] Specifically, step S502 above includes: Step S5021: After the mobile device enters the volatile zone, acquire the laser data collected by the laser device and the driving information collected by the odometer.

[0048] Specifically, in this embodiment of the invention, the controller 10 immediately triggers a data acquisition start command the instant the robot determines that it has entered the boundary of the variable zone based on its positioning information. This precisely controls the laser device 20 and the odometer 30 to enter the working state synchronously, ensuring the timeliness and synchronization of data acquisition. The laser device 20 emits a laser beam in real time and receives reflected signals according to a preset acquisition frequency (e.g., 10Hz-20Hz), collecting environmental laser data within a 360° range around the robot. This laser data includes key information such as the distance and outline of various objects (e.g., cargo, temporary obstacles, ground markings, etc.) within the variable zone, clearly reflecting the real-time environmental characteristics of the variable zone. Simultaneously, the odometer 30 synchronously collects the robot's driving information, specifically including parameters such as driving distance, real-time driving speed, turning angle, and acceleration, accurately recording the robot's movement trajectory and motion state within the variable zone, providing reliable kinematic data support for subsequent pose calculation.

[0049] Step S5022: Determine the surrounding object information of the mobile device based on the laser data, and determine the pose information of the mobile device based on the laser data and driving information.

[0050] Specifically, in this embodiment of the invention, the controller 10 continuously receives real-time data transmitted from the laser device 20 and the odometer 30, and performs preliminary preprocessing on the data to remove abnormal data caused by sensor noise and environmental interference, ensuring the accuracy and effectiveness of the collected data. Furthermore, the controller 10 further analyzes the preprocessed laser data, using algorithms such as laser point cloud clustering and feature extraction to accurately determine the specific information of objects around the robot, including key features such as the object's three-dimensional position coordinates, shape outline, size, and relative distance between the object and the robot, thus clarifying the distribution of obstacles in the variable area. Simultaneously, the controller 10 combines the preprocessed laser data and the driving information collected by the odometer, using pose calculation algorithms commonly used in the SLAM field (such as the Iterative Closest Point (ICP) algorithm and the Extended Kalman Filter (EKF) algorithm) to calculate the robot's real-time pose information in the variable area. This pose information includes parameters such as the robot's planar coordinates and heading angle, accurately reflecting the robot's actual position and attitude in the variable area, ensuring that the collected map data accurately corresponds to the robot's actual motion state, laying the foundation for subsequent matching of map data with the global map.

[0051] Step S5023: After the mobile device leaves the volatile zone, the laser data and pose information are used as map data for this crossing of the volatile zone.

[0052] Specifically, in this embodiment of the invention, when the robot's positioning information shows that it has completely crossed the boundary of the volatile zone, the controller 10 immediately sends a data acquisition stop command to control the laser device 20 and the odometer 30 to stop data acquisition, avoiding the acquisition of redundant data from non-volatile zones and reducing system storage pressure and data processing costs. Subsequently, the controller 10 integrates and encapsulates all valid laser data and real-time pose information acquired during the crossing of the volatile zone, forming a complete and independent set of map data according to a preset data format (such as PCD format for storing laser point cloud data and TXT format for storing pose information), ensuring data integrity and readability.

[0053] Furthermore, the controller 10 transmits the map data obtained from this traverse to the historical local map file library maintained by the system for the current global map for storage. When storing, the file name is the timestamp of the current traverse (accurate to milliseconds), which facilitates the quick retrieval and retrieval of map data at different time points based on the time dimension, and can also clearly distinguish the collection records of multiple traverses.

[0054] Step S5024: After traversing the volatile zone multiple times, obtain multiple sets of map data.

[0055] Specifically, in this embodiment of the invention, if the robot traverses the volatile zone again during subsequent autonomous driving tasks, the controller 10 will repeat the above-mentioned complete data acquisition, preprocessing, parsing, pose calculation, integration and encapsulation and storage process, sequentially acquiring and saving multiple sets of map data. These multiple sets of map data can comprehensively reflect the environmental changes in the volatile zone at different points in time, providing sufficient and comprehensive data source support for subsequent map update operations, and ensuring the accuracy and reliability of map updates.

[0056] Step S503: In response to triggering a map update operation, update the local map corresponding to the volatile area in the global map based on the map data to obtain the updated global map.

[0057] Specifically, step S503 includes: Step S5031: Determine the first local map corresponding to the volatile area in the global map based on the pose information in the latest set of map data.

[0058] Specifically, in this embodiment of the invention, when the controller 10 receives a trigger signal for a map update operation, it will accurately update the corresponding volatile area in the global map based on multiple sets of collected map data. The controller 10 retrieves the latest set of map data, parses the pose information contained therein, and uses this as a reference to accurately locate and match the first local map corresponding to the volatile area in the global map, thus establishing the map area range to be updated.

[0059] Step S5032: Convert the laser data in the latest set of map data into a raster map, and update the first local map according to the raster map to obtain the second local map.

[0060] Specifically, in this embodiment of the invention, the controller 10 converts the laser data in the latest set of map data into a raster map format, and then updates the first local map according to the raster map to obtain a second local map after environmental changes. This map update process can update the local maps of multiple volatile areas simultaneously, while the maps corresponding to non-volatile areas remain unchanged.

[0061] In some optional implementations, step S5032 above includes: Step a1: Based on the first local map, determine the area occupied by the newest obstacle in the variable zone each time the variable zone is traversed, according to the laser data in each group of map data.

[0062] Step a2: Determine the occupancy probability of each grid cell in the grid map based on the occupied area of ​​the latest obstacle corresponding to all group map data.

[0063] Step a3: If the occupancy probability is higher than the preset threshold, the grid cell is considered a valid grid cell in the grid map; otherwise, it is considered an invalid grid cell in the grid map.

[0064] Step a4: Update the corresponding grids of the first local map based on the valid grids, and preserve the data of the corresponding grids of the first local map based on the invalid grids, to obtain the second local map.

[0065] Specifically, in this embodiment of the invention, before updating the first local map based on the raster map of the latest set of map data, the controller 10 calls all the group map data stored in the historical local map file library, and uses the first local map corresponding to the volatile area in the global map as the update benchmark to ensure that the update process has a clear spatial reference and avoid the problem of update area offset. After the benchmark is established, the controller 10 parses the laser data in each group of map data one by one, and combines it with the timestamp information of each crossing of the volatile area to trace and determine the occupied area of ​​the latest obstacle in the volatile area during each crossing. Herein, the latest obstacle refers to the obstacle that did not exist in the volatile area during the previous crossing but actually exists in the volatile area during the current crossing, such as a temporary shelf added or a moved item during a certain crossing. The controller 10 accurately delineates the specific occupied range of these obstacles in space during each crossing through the contour recognition and position matching of the laser point cloud, and clarifies the distribution changes of obstacles in the volatile area at different time points.

[0066] For example, the warehouse robot traverses the goods stacking area (volatile area) three times. During the first traverse, the goods are neatly stacked and occupy the area around shelf A. During the second traverse, some goods are moved to the side of shelf B, creating a new temporary occupying area. During the third traverse, the temporary shelf is removed, and the occupied area returns to the area around shelf A. The controller 10 will determine the latest obstacle occupying area for each of these three traverses, forming multiple sets of occupying area data.

[0067] After determining the latest obstacle-occupied areas for all traversals, the controller 10 precisely matches this occupied area data with the converted grid map. Using a probabilistic statistical algorithm, it comprehensively determines the occupancy probability of each grid cell in the grid map based on all sets of data. Specifically, for each grid cell in the grid map, the controller 10 calculates parameters such as the frequency of the cell appearing in the latest obstacle-occupied areas across all traversals and the number of laser point hits. Combining this with a preset probability calculation model, it calculates the overall probability that the grid cell is actually occupied by an obstacle. The higher the probability value, the greater the likelihood that an obstacle exists in the grid cell.

[0068] Furthermore, the controller 10 calls a preset occupancy probability threshold (which can be adjusted according to the actual application scenario, such as setting it to 70%) to classify and determine each grid: if the occupancy probability of a grid is higher than the preset threshold, the grid is determined to be a valid grid, meaning that the area corresponding to the grid does indeed have relatively fixed obstacles, and is consistent with the actual environment of the current volatile area, and needs to be bypassed on the next pass; if the occupancy probability of a grid is lower than or equal to the preset threshold, the grid is determined to be an invalid grid, meaning that the area corresponding to the grid does not have obstacles, or the probability of obstacles is extremely low, or the obstacles are temporary obstacles, such as pedestrians passing by, and do not need to be updated.

[0069] Based on the warehouse example above, for a grid cell in the goods stacking area grid map, if the grid cell is determined to have goods (occupied) twice in the area occupied by the latest obstacle traversed three times, the calculated occupation probability is 67%, which is lower than the preset threshold of 70%, then the grid cell is an invalid grid cell; if it is determined to have goods twice and temporary shelves once, the calculated occupation probability is 85%, which is higher than the preset threshold, then the grid cell is a valid grid cell.

[0070] After determining the grid type, the controller 10 uses the first local map as a reference and performs a differentiated update operation to obtain the second local map. Specifically, for areas determined to be valid grids, the controller 10 uses the latest data of that grid in the grid map (reflecting the actual obstacle distribution in the current volatile area) to overwrite and update the corresponding grid in the first local map, ensuring that the updated local map perfectly matches the current environment of the volatile area. For areas determined to be invalid grids, the controller 10 does not modify the corresponding grid in the first local map, keeping the original map data unchanged to avoid deviations in map information for obstacle-free areas due to erroneous updates.

[0071] Based on the warehouse example above, the goods relocation area and temporary shelf area corresponding to the valid grid will be covered with the latest laser data to update the position of the goods and temporary shelves in the first local map; while the open area and fixed shelf area corresponding to the invalid grid will keep the original data in the first local map unchanged. Finally, through this differentiated update method, a second local map that can accurately reflect the current actual environment of the volatile area is obtained.

[0072] Step S5033: Replace the first local map in the global map with the second local map to obtain the updated global map.

[0073] Specifically, in this embodiment of the invention, after the map update process completes the correction of the first local map and generates the final second local map, the controller 10 accurately locates the geographic boundary corresponding to the first local map in the raster index of the global map based on the previously parsed pose information. This boundary is a predefined volatile rectangular or polygonal region with a clear range of row and column coordinates. Furthermore, all raster data blocks in this specific region are quickly located using a spatial index (such as an R-tree or grid index), defining a precise operation range for the replacement operation.

[0074] Controller 10 completely overwrites the corresponding position of the first local map in the global map with the second map data block to be updated. This is an incremental update, meaning that only the changed, volatile areas are replaced, and all raster data in other non-volatile areas of the global map will remain completely unchanged without any read / write changes. This replacement strategy greatly improves update efficiency and avoids the resource consumption of a full rewrite of the entire global map (which may contain tens of thousands or even millions of rasters).

[0075] As the physical data replacement is completed, controller 10 must synchronously update the metadata records of the global map. Specifically, the system will update the last update timestamp of the volatile area in the map metadata to keep it consistent with the generation time of the second local map; at the same time, it will refresh the map's feature index to ensure that the robot can directly retrieve the latest second map data through the index when performing path planning or localization, rather than reading the outdated first local map cache.

[0076] At this point, the partial replacement operation of the global map is complete. The original partial map, containing outdated environmental information, has been completely replaced by a second partial map that accurately reflects the actual state of the current volatile area. The system defines this integrated map as the updated global map. This updated global map not only retains the original large-scale environmental information of the global map, but more importantly, its internal volatile area partial maps are now aligned with the real-time environment. During subsequent autonomous navigation, the robot can load and use this updated global map to effectively avoid the risk of positioning drift caused by environmental changes and achieve long-term stable autonomous navigation.

[0077] For example, taking a warehouse robot as an example, the system locks a rectangular area in the global map with coordinates ranging from (X1, Y1) to (X2, Y2), which is the goods stacking area (first local map). The controller 10 writes the newly generated second local map (containing updated grid data), reflecting the latest goods placement, into the (X1, Y1)-(X2, Y2) memory block of the global map, updates the last update time of this area, and clears the cached markers of old data. Therefore, the entire warehouse map is a perfect combination of old wall / aisle information and new goods stacking information, such as... Figure 4 As shown, this is the final updated global map.

[0078] Step S504: Adjust the local pose information of the mobile device in the volatile area according to the updated global map.

[0079] Specifically, in this embodiment of the invention, after the map update is completed, the controller 10 immediately initiates the robot's local pose adjustment process in the volatile area. The core purpose is to eliminate pose deviations caused by the failure of the old map, ensure that the robot's real-time pose is highly matched with the actual environment of the volatile area in the updated global map, and guarantee the accuracy and stability of subsequent autonomous driving, positioning, and navigation. The specific adjustment process is as follows: The controller 10 first retrieves the second map data corresponding to the volatile area in the updated global map, and at the same time continuously receives real-time data collected by the laser device 20 and the odometer 30, including the robot's current driving information, surrounding environment laser data, and local pose information before the update, to construct a model of the robot's current motion state and environmental characteristics.

[0080] Furthermore, the controller 10 accurately matches the environmental features of the variable area in the updated second local map (such as updated obstacle positions, outlines, ground markings, etc.) with the laser point cloud data of the variable area collected in real time by the laser device 20. Using pose calculation algorithms commonly used in the SLAM field (such as the Iterative Closest Point (ICP) algorithm and the Extended Kalman Filter (EKF) algorithm), it compares and analyzes the differences between the map data before and after the update, locating the deviation between the robot's current pose and the updated map environment. This deviation includes positional deviation (such as planar coordinate offset) and attitude deviation (such as heading angle offset). For example, before the map update in the goods stacking area (variable area), the warehouse robot experienced a 5cm positional offset and a 3° heading angle deviation due to goods displacement. After the map update, the controller 10 accurately calculates this deviation by comparing the actual position of the goods after the update with the real-time laser-collected goods position.

[0081] After determining the deviation, the controller 10, combined with the real-time driving information collected by the odometer 30, generates targeted pose adjustment commands to dynamically correct the robot's driving state. For positional deviations, the controller 10 gradually corrects the coordinate offset by adjusting the robot's driving speed and steering angle, ensuring that the robot's actual position is precisely aligned with the corresponding position in the volatile area of ​​the updated global map. For posture deviations, the controller 10 adjusts the robot's steering mechanism to correct the heading angle, ensuring that the robot's driving direction is consistent with the path planning in the updated map. The entire adjustment process is a real-time dynamic adjustment. The controller 10 continuously compares the matching degree between the robot's real-time pose and the updated map until the deviation is reduced to within the preset allowable error range (e.g., positional deviation ≤ 2cm, posture deviation ≤ 1°), at which point the adjustment stops.

[0082] It should be noted that this pose adjustment process only applies to the robot's local pose in volatile areas and does not affect its pose in non-volatile areas. Furthermore, the adjustment process is performed synchronously with the robot's autonomous navigation task, without interrupting normal workflow. For example, after updating the map of the goods stacking area, a warehouse robot can simultaneously adjust its pose while continuing to perform goods handling tasks. This corrects positioning deviations caused by goods displacement, ensuring accurate docking at designated locations and avoiding collisions and navigation path deviations caused by pose errors. This further enhances the stability and reliability of the robot's autonomous operation in dynamic environments.

[0083] The dynamic environment map update method provided by this invention acquires map data corresponding to a volatile area when a mobile device travels through it based on a global map and reaches such an area. Upon triggering a map update, the local map corresponding to the volatile area in the global map is updated based on this map data, resulting in an updated global map. This invention, by defining volatile areas prone to environmental changes and selectively collecting map data from these areas during the mobile device's movement, performs local updates to the global map instead of reconstructing the entire map. This enables accurate and localized map updates for volatile areas in dynamic environments, eliminating the need for manual data collection and map correction throughout the process. This significantly reduces the time and resource costs of map updates, increases the automation level of map updates, and avoids pose estimation errors and positioning / navigation failures caused by environmental changes in volatile areas. This effectively improves the map-based positioning and navigation accuracy of mobile devices, meeting the needs of long-term autonomous operation of mobile devices in dynamic scenarios.

[0084] This embodiment provides a dynamic environment map update method, which can be used in the aforementioned mobile devices, such as robots. Figure 6 This is a flowchart of a dynamic environment map update method according to an embodiment of the present invention, such as... Figure 6 As shown, the process includes the following steps: Step S601: During the process of the mobile device traveling based on the global map, detect whether the mobile device has reached a volatile area. The volatile area is a local area in the global map that is prone to environmental changes.

[0085] Specifically, step S601 includes: Step S6011: Obtain the location information of the mobile device and determine whether the location information is in a preset location area in the global map. The variable area and the preset location area have a one-to-one correspondence, and the number of both the variable area and the preset location area is at least one.

[0086] Specifically, in this embodiment of the invention, taking a robot as an example, during the process of performing navigation tasks based on a global map, the robot's built-in positioning module (such as a SLAM positioning system combining sensor data from LiDAR, odometry, etc.) can calculate and obtain the robot's current precise position information in real time. This position information is typically represented as a two-dimensional coordinate point (X, Y) based on the global map coordinate system. Therefore, the controller 10 can perform a spatial logical comparison between the acquired real-time position information and the preset position areas pre-defined and stored in the global map. It should be noted that in this embodiment of the invention, a strict one-to-one correspondence is established between the preset position areas in the global map and the pre-set volatile areas, and the number of both is at least one. This means that multiple independent preset position areas can be divided in the global map, and each area uniquely corresponds to a specific volatile area. For example, in the global map, preset area A can correspond to volatile area 1, preset area B can correspond to volatile area 2, and so on, ensuring accurate mapping between spatial division and areas to be updated.

[0087] Step S6012: If the location information is in a preset location area, then it is determined that the mobile device has reached the volatile area corresponding to the preset location area.

[0088] Specifically, in this embodiment of the invention, when the comparison results show that the robot's real-time location information falls within the geographical boundary of a preset location area, it can be directly and clearly determined that the robot has reached the volatile zone corresponding to that preset location area. By pre-defining the volatile zone as a specific coordinate range (i.e., a preset location area) in the global map, this embodiment of the invention enables proactive and forward-looking identification of hotspots in dynamic environmental changes. This allows for identification to be completed the moment the mobile device enters the volatile zone, laying a solid foundation for subsequent automatic data collection, ensuring uninterrupted navigation tasks, and ultimately achieving accurate local map updates. This enhances the system's adaptability and automation level to dynamic environments.

[0089] Step S602: If a volatile zone is reached, obtain the map data corresponding to the volatile zone while traversing it. For details, please refer to [link to relevant documentation]. Figure 5 Step S502 of the illustrated embodiment will not be described again here.

[0090] Step S603: Obtain the current time. If the current time reaches the preset time, trigger the map update operation.

[0091] Specifically, in this embodiment of the invention, a time-triggered mechanism for map update operations is pre-set. In this mechanism, the system calls an internal clock or an external time synchronization service to obtain the accurate current time. Simultaneously, the global map configuration information presets at least one update time point. This time point can be pre-set based on the frequency of environmental changes in volatile areas, peak business periods, or system maintenance cycles. For example, for goods storage areas in a warehouse where there is high foot traffic in the afternoon and the environmental layout is prone to temporary adjustments, 2:00 AM can be preset as the update time daily.

[0092] Once the controller compares the current time with the preset time and confirms that they match perfectly or that the preset time window has been reached, the system will automatically and unconditionally trigger a map update operation. The core value of this mechanism lies in achieving periodic proactive updates, ensuring that even if the robot does not enter a volatile area or the positioning quality is good, the system can still perform regular data refreshes and environmental calibrations for volatile areas according to a predetermined plan. This guarantees the long-term effectiveness of the map from a time perspective and avoids environmental information lag caused by a lack of updates over a long period.

[0093] Step S604: Obtain the positioning quality of the volatile area. If the positioning quality is lower than a preset threshold, trigger a map update operation.

[0094] Specifically, in this embodiment of the invention, a positioning quality triggering mechanism for map update operations is pre-set. This mechanism, based on the robot's real-time positioning performance, is a key line of defense for ensuring navigation safety. Specifically, the controller continuously analyzes and obtains the positioning quality indicators of the mobile device within the current volatile area. These indicators can be quantified in various ways, including: the matching score between LiDAR and odometry data, the covariance value of the positioning error, and the success rate of feature point matching. Lower positioning quality indicates a greater deviation between the robot's actual position and map coordinates, and thus a higher risk to navigation reliability.

[0095] The system presets a localization quality threshold as a safety threshold for determining whether an update is needed. When the controller detects that the real-time localization quality value in a volatile area is lower than this threshold, it means that the current map information may have deviated significantly from the actual environment. Continued use may lead to localization drift, path planning errors, or even navigation task failure. In this case, the system will immediately trigger a map update operation, collecting the latest map data to correct the map information in the volatile area, thereby quickly restoring and improving localization quality and ensuring the robot's operational safety and navigation stability in dynamic environments.

[0096] Step S605: Detect whether a manual trigger command has been received. If a manual trigger command has been received, then trigger the map update operation.

[0097] Specifically, in this embodiment of the invention, a pre-set manual triggering mechanism for map update operations is provided. This mechanism offers a flexible and controllable means of manual intervention to address special, non-periodic, or urgent environmental change scenarios. The controller monitors the system's input interface in real time to detect whether it has received a manual triggering command from an operator or external management platform. This command can be a manual click through the human-machine interface, sent via a specific wireless communication protocol, or a control command issued by a cloud server.

[0098] Once a valid manual trigger command is detected, the controller will immediately respond and trigger a map update operation. This mechanism gives the system unexpected flexibility and controllability. For example, when large-scale adjustments to the layout of goods are made in the warehouse, new fixed obstacles are added, or operators discover obvious errors in the map data of a volatile area, this method can force an immediate update, ensuring that the map data is completely consistent with the actual environment and compensating for the limitations of time-based and location-quality-based automatic triggering mechanisms in terms of response timeliness and scenario adaptability.

[0099] Step S606: In response to the triggered map update operation, the local map corresponding to the volatile area in the global map is updated based on the map data to obtain the updated global map. For details, please refer to [link to relevant documentation]. Figure 5 Step S503 of the illustrated embodiment will not be described again here.

[0100] The dynamic environment map update method provided by this invention acquires map data corresponding to a volatile area when a mobile device travels through it based on a global map and reaches such an area. Upon triggering a map update, the local map corresponding to the volatile area in the global map is updated based on this map data, resulting in an updated global map. This invention, by defining volatile areas prone to environmental changes and selectively collecting map data from these areas during the mobile device's movement, performs local updates to the global map instead of reconstructing the entire map. This enables accurate and localized map updates for volatile areas in dynamic environments, eliminating the need for manual data collection and map correction throughout the process. This significantly reduces the time and resource costs of map updates, increases the automation level of map updates, and avoids pose estimation errors and positioning / navigation failures caused by environmental changes in volatile areas. This effectively improves the map-based positioning and navigation accuracy of mobile devices, meeting the needs of long-term autonomous operation of mobile devices in dynamic scenarios.

[0101] This embodiment also provides a dynamic environment map updating device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0102] This embodiment provides a dynamic environment map updating device, such as... Figure 7 As shown, it includes: The location detection module 701 is used to detect whether the mobile device has reached a changeable area during the process of the mobile device traveling based on the global map. The changeable area is a local area in the global map that is prone to environmental changes.

[0103] The data acquisition module 702 is used to acquire the map data corresponding to the volatile area when crossing the volatile area if the volatile area is reached.

[0104] The map update module 703 is used to respond to the triggered map update operation, update the local map corresponding to the volatile area in the global map based on the map data, and obtain the updated global map.

[0105] In some alternative implementations, the position detection module 701 includes: The location information acquisition unit is used to acquire the location information of the mobile device and determine whether the location information is in a preset location area in the global map. The variable area and the preset location area have a one-to-one correspondence, and the number of both the variable area and the preset location area is at least one.

[0106] The location information comparison unit is used to determine that the mobile device has reached the volatile area corresponding to the preset location area if the location information is in the preset location area.

[0107] In some alternative implementations, the data acquisition module 702 includes: The sensor data acquisition unit is used to acquire laser data collected by the laser device and driving information collected by the odometer after the mobile device enters a volatile area.

[0108] The pose information determination unit is used to determine the surrounding object information of the mobile device based on laser data, and to determine the pose information of the mobile device based on laser data and driving information.

[0109] The single-pass data acquisition unit is used to use laser data and pose information as map data for this pass through the volatile zone after the mobile device leaves the volatile zone.

[0110] The multiple traversal data acquisition unit is used to obtain multiple sets of map data after traversing volatile areas multiple times.

[0111] In some alternative implementations, the map update module 703 includes: The local map determination unit is used to determine the first local map corresponding to the volatile area in the global map based on the pose information in the latest set of map data.

[0112] The local map update unit is used to convert laser data in the latest set of map data into a raster map, and update the first local map according to the raster map to obtain the second local map.

[0113] The local map replacement unit is used to replace the first local map in the global map with the second local map to obtain the updated global map.

[0114] In some optional implementations, the local map update unit includes: The occupied area determination sub-unit is used to determine the occupied area of ​​the newest obstacle in the variable area each time it is traversed, based on the laser data in each group of map data, using the first local map as a reference.

[0115] The occupancy probability determination sub-unit is used to determine the occupancy probability of each grid cell in the grid map based on the occupancy area of ​​the latest obstacle corresponding to all group map data.

[0116] The "Occupy Grid Determination Sub-cell" is used to determine whether a grid cell is an effective grid cell in the grid map if its occupancy probability is higher than a preset threshold, and otherwise as an invalid grid cell in the grid map.

[0117] The local raster update subunit is used to update the corresponding raster of the first local map based on the valid raster and to preserve the data of the corresponding raster of the first local map based on the invalid raster, so as to obtain the second local map.

[0118] In some alternative embodiments, the apparatus further includes: The time-triggered module is used to obtain the current time. If the current time reaches the preset time, a map update operation is triggered.

[0119] The quality trigger module is used to obtain the positioning quality of volatile areas. If the positioning quality is lower than a preset threshold, a map update operation is triggered.

[0120] The manual trigger module is used to detect whether a manual trigger command has been received. If a manual trigger command is received, the map update operation is triggered.

[0121] In some optional implementations, the apparatus further includes a pose update module for adjusting the local pose information of the mobile device in the volatile area based on the updated global map.

[0122] The dynamic environment map updating apparatus provided in this embodiment of the invention can execute the dynamic environment map updating method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0123] Figure 8 This is a schematic diagram of the structure of a controller provided in an embodiment of the present invention.

[0124] The following is a detailed reference. Figure 8 The diagram illustrates a structural schematic suitable for implementing a controller in an embodiment of the present invention. The controller may include a processor (e.g., a central processing unit, a graphics processing unit, etc.) 801, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 802 or a program loaded from memory 808 into random access memory (RAM) 803. The RAM 803 also stores various programs and data required for controller operation. The processor 801, ROM 802, and RAM 803 are interconnected via bus 804. An input / output (I / O) interface 805 is also connected to bus 804.

[0125] Typically, the following devices can be connected to I / O interface 805: input devices 806 including, for example, a touchscreen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 807 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; memory 808 including, for example, magnetic tape, hard disk, etc.; and communication devices 809. Communication device 809 allows the controller to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 8 A controller with various devices is shown, but it should be understood that it is not required to implement or have all of the devices shown, and may alternatively implement or have more or fewer devices.

[0126] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 809, or installed from a memory 808, or installed from a ROM 802. When the computer program is executed by the processor 801, it performs the functions defined in the dynamic environment map update method of the embodiments of the present invention.

[0127] Figure 8The controller shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0128] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the dynamic environment map update method shown in the above embodiments is implemented.

[0129] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0130] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A dynamic environment map update method, applied to mobile devices, characterized in that, The method includes: During the movement of the mobile device based on the global map, it is detected whether the mobile device has reached a volatile area, which is a local area in the global map that is prone to environmental changes; If the volatile zone is reached, the map data corresponding to the volatile zone is obtained when traversing the volatile zone. In response to the triggered map update operation, the local map corresponding to the volatile area in the global map is updated based on the map data to obtain the updated global map.

2. The method according to claim 1, characterized in that, The mobile device is equipped with a laser device and an odometer. When traversing the volatile zone, acquiring map data corresponding to the volatile zone includes: After the mobile device enters the volatile zone, the laser data collected by the laser device and the driving information collected by the odometer are acquired. The surrounding object information of the mobile device is determined based on the laser data, and the pose information of the mobile device is determined based on the laser data and the driving information. After the mobile device leaves the volatile zone, the laser data and the pose information are used as map data for this crossing of the volatile zone; After traversing the volatile zone multiple times, multiple sets of map data were obtained.

3. The method according to claim 2, characterized in that, The step of updating the local map corresponding to the volatile area in the global map based on the map data to obtain the updated global map includes: Based on the pose information in the latest set of map data, determine the first local map in the global map corresponding to the volatile area; The laser data in the latest set of map data is converted into a raster map, and the first local map is updated according to the raster map to obtain the second local map; The first local map in the global map is replaced with the second local map to obtain the updated global map.

4. The method according to claim 3, characterized in that, The step of updating the first local map based on the raster map to obtain the second local map includes: Based on the first local map, the area occupied by the newest obstacle in the volatile zone is determined according to the laser data in each group of map data each time the volatile zone is traversed; The occupancy probability of each grid cell in the grid map is determined based on the occupied area of ​​the latest obstacle corresponding to the map data of all groups. If the occupancy probability is higher than a preset threshold, the grid cell is considered a valid grid cell in the grid map; otherwise, it is considered an invalid grid cell in the grid map. The first local map is updated by covering the corresponding grids of the first local map based on the valid grids, and the data of the corresponding grids of the first local map is preserved based on the invalid grids to obtain the second local map.

5. The method according to claim 1, characterized in that, The method further includes: Get the current time; if the current time reaches a preset time, trigger a map update operation. And / or, obtain the positioning quality of the volatile area; if the positioning quality is lower than a preset threshold, trigger a map update operation. And / or, detect whether a manual trigger command has been received; if the manual trigger command is received, then trigger a map update operation.

6. The method according to claim 1, characterized in that, The step of detecting whether the mobile device has reached a volatile area during the process of the mobile device traveling based on a global map includes: The location information of the mobile device is obtained, and it is determined whether the location information is in a preset location area in the global map. The volatile area and the preset location area have a one-to-one correspondence, and the number of both the volatile area and the preset location area is at least one. If the location information is within the preset location area, then it is determined that the mobile device has reached the volatile area corresponding to the preset location area.

7. The method according to any one of claims 1 or 5, characterized in that, After obtaining the updated global map, the method further includes: The local pose information of the mobile device in the volatile area is adjusted based on the updated global map.

8. A dynamic environment map updating device, applied to a mobile device, characterized in that, The device includes: The location detection module is used to detect whether the mobile device has reached a changeable area during the process of the mobile device traveling based on the global map. The changeable area is a local area in the global map that is prone to environmental changes. The data acquisition module is used to acquire map data corresponding to the volatile area when traversing the volatile area if the volatile area is reached. The map update module is used to update the local map corresponding to the volatile area in the global map based on the map data in response to the triggered map update operation, so as to obtain the updated global map.

9. A mobile device, characterized in that, include: A controller, a laser device, and an odometer, wherein the controller is connected to the laser device and the odometer; The controller includes a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the dynamic environment map update method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a computer to perform the dynamic environment map update method according to any one of claims 1 to 7.

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