Methods, electronic devices and systems for assessing the quality of robot navigation data

Abstract

This application relates to the field of mobile robot technology, and in particular to a method, electronic device, and system for quality assessment of robot navigation data. In embodiments of this application, the electronic device can assess the quality of navigation data. If substandard data is found, its location is marked on a first navigation map. The electronic device can also display the marked first navigation map (i.e., a second navigation map) through a human-machine interface, allowing technicians to quickly identify the location of the substandard data on the map using the markers, thus facilitating correction. Furthermore, since the electronic device can perform navigation data quality assessment based on a static first navigation map, the robot does not need to re-enter the working environment to determine the substandard data.

Description

Technical Field

[0001] This application relates to the field of mobile robot technology, and in particular to a method, electronic device and system for quality assessment of robot navigation data. Background Technology

[0002] Mobile robots have wide applications in various fields such as industrial production, daily life services, and environmental monitoring. A mobile robot is a robotic system that uses sensors and other technologies to perceive its environment and its own state, enabling autonomous navigation and movement towards a target in obstacle-filled environments to complete predetermined tasks.

[0003] When a robot first arrives at its work environment, it first needs to use sensors to generate a navigation map of the environment and then perform global path planning. However, due to the complexity and diversity of the work environment, the navigation map built by the robot inevitably contains areas with inaccurate mapping, resulting in inconsistent quality of the navigation map. Summary of the Invention

[0004] This application provides a method, electronic device, and system for quality assessment of robot navigation data. It can assess the quality of navigation data and mark the corresponding locations of problematic data on the navigation map, so that technicians can correct the problematic data and improve the quality of the robot navigation map.

[0005] In the first aspect of the application, a method for quality assessment of robot navigation data is provided, applied to an electronic device. The method includes the following steps: acquiring robot navigation data, the navigation data including a static first navigation map; performing a quality assessment on the navigation data, and if there is substandard data in the navigation data, marking the location corresponding to the substandard data in the first navigation map to obtain a second navigation map; and displaying the second navigation map through a human-computer interaction interface.

[0006] In the embodiments of this application, the electronic device can perform a quality assessment of the navigation data. If there is substandard data in the navigation data, the location of the substandard data is marked on the first navigation map. The electronic device can also display the marked first navigation map (i.e., the second navigation map) through a human-computer interaction interface, so that technicians can quickly identify the location of the substandard data on the map through the marks in the second navigation map, thereby facilitating the correction of the substandard data by technicians. In addition, since the electronic device can perform a quality assessment of the navigation data based on the static first navigation map, it is not necessary for the robot to re-enter the working environment to locate the substandard data.

[0007] In some embodiments, the navigation data further includes navigation path data. The step of quality assessment of the navigation data, whereby if there is substandard data in the navigation data, the location corresponding to the substandard data is marked in the first navigation map, includes: assessing the composition quality of the first navigation map; if there is a substandard area in the first navigation map, the location of the substandard area is marked in the first navigation map; and / or, assessing the quality of the navigation path data; if there is substandard path data in the navigation path data, the location of the path segment corresponding to the substandard path data is marked in the first navigation map.

[0008] In some embodiments, the navigation path data includes preset travel patterns for the robot in each path segment; the quality assessment of the navigation data includes: determining the travel width of the path segment and the surrounding environment of the path segment; determining the ideal travel pattern of the robot in the path segment based on the travel width and the surrounding environment; if the preset travel pattern and the ideal travel pattern do not match, then the preset travel pattern is determined to be the problematic path data.

[0009] In some embodiments, determining the ideal passage mode of the robot on the path segment based on the passage width and the surrounding environment includes: if the passage width is less than a preset width threshold and the surrounding environment includes a preset environment, then the ideal passage mode of the path segment is determined to be a narrow path mode; wherein the preset environment includes a drop-off environment.

[0010] In some embodiments, the first navigation map includes a passable area and a restricted area. The evaluation of the composition quality of the first navigation map includes: determining multiple target point locations that the robot needs to reach in the first navigation map based on the navigation path data; determining whether the passable area includes an area that the robot does not need to reach based on the target point locations; if so, determining the area that the robot does not need to reach as the problem area; and / or setting the colors of the passable area and the restricted area to a first color and a second color respectively; if the passable area of ​​the first color has scattered points of the second color, then determining the area where the scattered points are located as the problem area.

[0011] In some embodiments, evaluating the composition quality of the first navigation map further includes: determining the boundary line between the passable area and the restricted area based on the first navigation map; determining whether the boundary line includes a boundary line segment with substandard quality; if so, determining the area where the substandard boundary line segment is located as the problem area.

[0012] In some embodiments, the second navigation map further includes prompt information. Before obtaining the second navigation map, the method further includes: marking the prompt information in the first navigation map, wherein the prompt information is used to indicate the reason why the problem data is of substandard quality.

[0013] In some embodiments, after displaying the second navigation map through the human-computer interaction interface, the method further includes: receiving user operations on the second navigation map through the human-computer interaction interface, and correcting the problematic data in response to the user operations.

[0014] In a second aspect of this application, an electronic device is also provided, the electronic device comprising: a processor, and a memory storing instructions, which, when executed by the processor, cause the electronic device to perform the method as described in the first aspect.

[0015] In a third aspect of this application, a quality assessment system for robot navigation data is also provided, the system comprising a mobile robot and an electronic device as described in the second aspect, the mobile robot and the electronic device being communicatively connected.

[0016] It should be understood that the description in the Summary Section is not intended to limit the key or essential features of this disclosure, nor is it intended to restrict the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments of this application will be briefly described below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a robot navigation data quality assessment method provided in some embodiments of this application;

[0019] Figure 2 This is a flowchart of a robot navigation data quality assessment method provided in some other embodiments of this application;

[0020] Figure 3 This is a schematic diagram of the structure of a robot navigation data quality assessment device provided in some embodiments of this application;

[0021] Figure 4 This is a schematic diagram of the structure of a robot navigation data quality assessment device provided in some other embodiments of this application;

[0022] Figure 5This is a schematic diagram of the hardware structure of an electronic device for performing a quality assessment method for robot navigation data, provided in some embodiments of this application.

[0023] Figure 6 This is a schematic diagram of the structure of a robot navigation data quality assessment system provided in some embodiments of this application. Detailed Implementation

[0024] The principles and spirit of this disclosure will be described below with reference to several exemplary embodiments illustrated in the accompanying drawings. It should be understood that these specific embodiments are described merely to enable those skilled in the art to better understand and implement this disclosure, and are not intended to limit the scope of this disclosure in any way. In the following description and claims, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art.

[0025] As used herein, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "an embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc., may refer to different or the same objects and are used only to distinguish the objects referred to, without implying a particular spatial order, temporal order, order of importance, etc., of the objects referred to.

[0026] As used herein, the term "determine" can encompass a wide variety of actions. For example, "determine" can include operations, calculations, processing, deriving, investigation, searching (e.g., looking in a table, database, or other data structure), ascertaining, etc. Furthermore, "determine" can include receiving (e.g., receiving information), accessing (e.g., accessing data in memory), etc. Moreover, "determine" can include parsing, selecting, choosing, building, etc.

[0027] The robot in this embodiment can be any suitable type of mobile robot, such as a delivery robot or a cleaning robot. This embodiment uses a delivery robot as an example to illustrate how to automatically deliver goods to their destination. The working environment of the delivery robot can be a shopping mall, supermarket, hospital, hotel, or KTV, etc. When the robot first arrives at the working environment, it first needs to acquire navigation data and reach its destination based on the navigation data. Navigation data can be, for example, navigation map data and navigation path data. To obtain navigation data, the robot needs to create a map, that is, the robot scans the surrounding environment through sensors to obtain a static navigation map. By setting the target point location (i.e., the business point) and the walking path on the navigation map, the set navigation path data can be obtained. Then, the robot can work according to the navigation map and navigation path data.

[0028] The working environment in which robots perform tasks can be complex (e.g., environments with many corridors and rooms, such as shopping malls, supermarkets, hospitals, hotels, or KTVs). Furthermore, the working environment may change during the robot's mapping process; for example, the robot may encounter temporarily placed objects or pedestrians, leading to inaccuracies in the robot's navigation map and walking path data. To help technicians identify problematic data in the navigation data and facilitate its correction, this application provides a method, electronic device, and system for quality assessment of robot navigation data. This system can assess the quality of navigation data and, when problematic data is found, mark the corresponding location on the navigation map and display the marked navigation map through a human-computer interaction interface. This allows technicians to correct the navigation data based on the markings on the navigation map, improving the accuracy of the navigation data. To facilitate understanding of this application, specific embodiments are described below.

[0029] For example, Figure 1 The flowchart of a navigation data quality assessment method provided in this application is presented. This method is applied to electronic devices, such as... Figure 1 As shown, the method includes the following steps:

[0030] Step 11: Electronic devices acquire robot navigation data;

[0031] In this embodiment, the electronic device can acquire the robot's navigation data. The navigation data includes a pre-acquired static navigation map, also known as a first navigation map. Specifically, this first navigation map can be a navigation map created by the robot using sensors (e.g., vision sensors or LiDAR) to scan the working environment. The vision sensor can specifically be a camera, and the LiDAR can specifically be a 2D or 3D LiDAR. After creating the first navigation map, the robot can send it to the electronic device. The first navigation map can be a two-dimensional or three-dimensional map, and its type can specifically be any one of a grid map, a feature map, or a topological map.

[0032] In other embodiments, the navigation data also includes pre-acquired navigation path data. This navigation path data is obtained through path planning based on a first navigation map. Specifically, the navigation path data may include the location coordinates of multiple target points that the robot needs to reach, the robot's walking path, and / or the robot's travel patterns in each path segment. The walking path can be the path between two adjacent target points, or it can be the collective term for all paths the robot takes in the first navigation map. The travel path includes multiple path segments, each distributed at different locations in the first navigation map.

[0033] Step 12: Perform a quality assessment on the navigation data. If there is substandard data in the navigation data, mark the location corresponding to the substandard data in the first navigation map to obtain a second navigation map.

[0034] In this embodiment, the electronic device can perform a quality assessment on navigation data (e.g., a first navigation map and / or navigation path data) based on preset quality assessment standards to obtain a quality assessment result. If there is problematic data in the navigation data that fails the quality assessment, the electronic device determines the location of the problematic data in the first navigation map and marks the location of the problematic data in the first navigation map, thereby obtaining a second navigation map. The second navigation map is used to represent the first navigation map with the markings. Technicians can quickly obtain the problematic data in the navigation data based on the markings on the second navigation map.

[0035] Typically, to correct navigation data, the robot needs to re-map the map in the working environment, perform global path planning, then avoid obstacles during autonomous navigation, re-plan the path, and repeat this process until the target point is reached, resulting in significant time and space complexity. Furthermore, if technicians manually assess the quality of the navigation data, individual differences among technicians (e.g., variations in skill and attention to detail) and the potential for oversights in manual assessments can lead to inaccurate results and inconsistent quality of the corrected navigation maps. In this embodiment, however, the electronic device can assess the quality of the navigation data based on existing static data, eliminating the need for the robot to re-enter the working environment and reacquire navigation data. Moreover, compared to manual assessment, intelligent quality assessment via electronic equipment improves the accuracy of the assessment results.

[0036] Specifically, in some embodiments, step 12 includes the following steps:

[0037] Step 121: Evaluate the composition quality of the first navigation map. If there are substandard areas in the first navigation map, mark the location of the substandard areas in the first navigation map.

[0038] In this embodiment, the first navigation map is pre-set with passable areas and prohibited areas. Passable areas represent areas where the robot can pass, while prohibited areas represent areas where the robot is prohibited from passing. In some embodiments of this application, to facilitate the distinction between passable and prohibited areas, the electronic device can also set the passable and prohibited areas to a first color and a second color, respectively; wherein the first color and the second color can be any two different colors. For example, the first color can be white, and the second color can be black or gray.

[0039] In some embodiments, the electronic device can determine, based on navigation path data, whether the passable area of ​​the first navigation map includes areas that the robot does not need to reach. If so, the area that the robot does not need to reach is identified as a problem area. Specifically, the electronic device can first determine the area that the robot needs to reach within the passable area based on the navigation path data, and then determine the area within the passable area other than the area that the robot needs to reach as the area that the robot does not need to reach. For example, the electronic device can first determine the area that the robot needs to reach within the passable area based on the position coordinates of each target point and / or the robot's walking path.

[0040] In some embodiments, if the passage area of ​​the first color is distributed with scattered dots of the second color, the electronic device determines that the area where the scattered dots are located is the problem area. If the robot encounters temporarily placed items or pedestrians during the mapping process, although the temporarily placed items or pedestrians will leave, the passage area in the first navigation map constructed by the robot will correspondingly be distributed with some scattered dots; in addition, due to the inherent characteristics of radar, scattered dots (i.e., noise) will be generated on the first navigation map during scanning. These scattered dots will all cause the first navigation map to be inaccurate. This embodiment can easily identify the scattered dots distributed in the passage area.

[0041] In some embodiments, the electronic device may also determine the boundary line between the passable area and the restricted area based on the first navigation map, and determine whether the boundary line includes a boundary line segment with substandard quality. If so, the area where the substandard boundary line segment is located is determined to be a problem area.

[0042] Specifically, in some embodiments, the boundary segments include virtual wall lines. To prevent the robot from falling or colliding due to ambient light during movement, laser stickers are pre-attached to areas where the robot is prohibited from passing. Specifically, the laser stickers are pre-attached to prohibited areas for the robot, such as stairwells and entrances to restricted passages. During map exploration, the robot can emit laser signals via a laser emitter and receive the reflected laser signals from the laser stickers via a laser receiver. The robot forms virtual wall lines in the current environment map (i.e., the first navigation map) based on the reflected laser signals. The electronic device can determine the actual length of each virtual wall line segment based on the first navigation map and the ideal length of the virtual wall line based on its surrounding environment. If the actual length of the virtual wall line does not match the ideal length, the virtual wall line is deemed substandard, and the area where the virtual wall line is distributed in the first navigation map is a problem area. For example, regarding laser wall lines located at stairwells: if the actual length of the laser wall line is too short, it cannot close the stairwell, posing a risk of the robot falling; if the actual length of the laser wall line is too long, extending into the passageway, it will affect the robot's movement in the passageway and reduce the robot's work efficiency.

[0043] In some embodiments, step 12 further includes the following steps:

[0044] Step 122: Evaluate the quality of the navigation path data. If there is substandard data in the navigation path data, mark the location of the path segment corresponding to the substandard data in the first navigation map.

[0045] Specifically, the step of performing a quality assessment on the navigation data includes:

[0046] Step 1221: Determine the passage width of the path segment and the surrounding environment of the path segment;

[0047] Step 1222: Determine the ideal travel mode of the robot on the path segment based on the path width and the surrounding environment;

[0048] Step 1223: If the preset traffic mode and the ideal traffic mode do not match, then the preset traffic mode is determined to be the problem path data.

[0049] In this embodiment, the electronic device can perform quality assessment on the robot's passage patterns in various path segments. The robot's passage patterns specifically include wide-path passage patterns and narrow-path passage patterns. In this embodiment, a narrow path can be defined as a path channel with a passage width less than a preset width threshold. Narrow paths include, but are not limited to, narrow passageways, automatic turnstiles, and narrow doors. A wide path is defined as a path channel with a passage width not less than a preset width threshold. The width threshold can be set according to actual conditions, and this embodiment does not specifically limit its setting.

[0050] Specifically, in some embodiments, in narrow path mode, multiple robots are not allowed to travel side-by-side. This ensures that only robots traveling in the same direction can exist in any narrow section of the target path, thus avoiding congestion caused by two or more robots traveling towards each other in the same narrow path, which could lead to prolonged delays and effectively reduce the time it takes for robots to reach their target location, improving robot efficiency. In wide path mode, however, multiple robots can travel side-by-side. For example, consider a narrow passage next to a staircase where a robot needs to pass very close to the staircase. If the robot is blocked by a person (or another robot) and has to avoid it, it might rotate to see the staircase. If the robot determines that the staircase is more than a preset threshold away from it, it will report a fall error and brake without moving, affecting the robot's task execution success rate. Therefore, in such special scenarios, the path segment needs to be configured as narrow path mode.

[0051] In some embodiments, the electronic device can determine a preset passage mode for each path segment based on navigation path data, wherein the preset passage mode is a narrow path passage mode or a wide path passage mode. The electronic device can also determine the passage width of each path segment and the surrounding environment of each path segment based on a first navigation map, and determine the ideal passage mode for the robot on the path segment based on the path width and the surrounding environment. For example, if the path width is less than a preset width threshold, and the surrounding environment includes a preset environment, the electronic device determines that the ideal passage mode for that path segment is a narrow path mode; wherein the preset environment includes a drop environment (such as stairs). If the preset passage mode and the ideal passage mode do not match, the preset passage mode is determined to be the problematic path data. In some embodiments, when the distance between a preset environment and a path segment is less than a preset distance threshold, the electronic device determines that the preset environment is the surrounding environment of that path segment.

[0052] Specifically, in some embodiments, the electronic device first determines the passage width of each path segment. If the passage width is less than a first width threshold, the electronic device determines that the ideal passage mode for that path segment is a narrow path mode. If the passage width is not less than a second width threshold, the electronic device determines that the ideal passage mode for that path segment is a wide path mode. If the passage width is not less than the first width threshold but less than the second width threshold, the electronic device acquires the surrounding environment of the path segment and determines the ideal passage mode for that path segment based on the surrounding environment. If the surrounding environment of the path segment includes a preset environment, the electronic device determines that the ideal passage mode for that path segment is a narrow path mode; if the surrounding environment does not include the preset environment, the electronic device determines that the passage mode for that path segment is a wide path mode.

[0053] In embodiments of this application, the electronic device can perform quality assessments on the first navigation map and navigation path data to identify problem areas with substandard composition quality in the first navigation map, and to identify problematic path data within the navigation path data. The electronic device can not only mark the locations of problem areas in the first navigation map, but also mark the locations of path segments corresponding to the problematic path data, thereby assisting technicians in identifying problematic data.

[0054] In some embodiments, the second navigation map further includes prompt information. Before obtaining the second navigation map, the method further includes marking the prompt information in the first navigation map, wherein the prompt information is used to indicate the reason for the substandard quality of the problematic data. In this embodiment, if there is substandard problematic data in the navigation data, the electronic device marks the location corresponding to the problematic data in the first navigation map and adds prompt information to the first navigation map, thereby obtaining the second navigation map. Based on the markings and prompt information in the second navigation map, technicians can easily determine the location of the problematic data in the first navigation map and the reason for the substandard quality of the problematic data.

[0055] For example, prompts can appear in the second navigation map in the form of text or symbols. For instance, when the actual traffic pattern of a path segment differs from the ideal traffic pattern, the electronic device can mark the location of that path segment on the first navigation map. Marking can be done by circling the area containing the path segment with lines (e.g., circles or squares), or by any other suitable marking method. The electronic device can use text to label the path segment with any suitable prompt, such as "Traffic mode error" or "Traffic mode error, needs to be configured to narrow path traffic mode"; the electronic device can also label the path segment with specific symbols to indicate a traffic mode error. In some embodiments of this application, when the user clicks the symbol, the electronic device can play an audio message explaining the reason for the substandard data quality, such as an audio message announcing "Traffic mode error." When a problem area with substandard mapping quality appears in the first navigation map, the electronic device can circle the location of the problem area with lines on the first navigation map and mark the problem area with prompts, such as: "The robot does not need to reach this area," "Laser wall line too long," or "Laser wall line too short."

[0056] Step 13: Display the second navigation map through the human-computer interaction interface.

[0057] Step 14: Receive user operations on the second navigation map through the human-computer interaction interface, and correct the problematic data in response to the user operations.

[0058] In some embodiments, the electronic device can display a second navigation map via a human-computer interaction interface. The human-computer interaction interface includes a display screen and buttons. The buttons can be mechanical buttons, such as a mouse and keyboard; or they can be touch buttons. The display screen is used to display the second navigation map. The electronic device can receive user operations on the second navigation map through the human-computer interaction interface (such as buttons), and in response to the user operations, the electronic device corrects problematic data.

[0059] For example, when there are problematic areas with substandard mapping quality in the first navigation map, technicians can perform user operations (e.g., image editing) through a human-computer interaction interface based on the markings and prompts on the second navigation map displayed on the screen. This allows the electronic device to respond to the user operation and correct the problematic areas in the first navigation map based on the second navigation map, thus obtaining a corrected first navigation map. For instance, the electronic device can respond to user operation by setting areas (target areas) that the robot does not need to reach within the passable area as prohibited areas. When the colors of the passable area and the prohibited area are a first color and a second color, respectively, the electronic device can set the color of the target area to the second color. The electronic device can also set virtual wall lines at the boundary between the target area and the modified passable area. In other embodiments, the electronic device can respond to user operation by removing scattered points distributed throughout the passable area, ensuring that each path segment is free of noise or obstacle points within a certain range. When the actual passable mode of a path segment differs from the ideal passable mode, the electronic device can also respond to user operation by modifying the passable mode of the path segment to the ideal passable mode.

[0060] This application provides a method, electronic device, and system for quality assessment of robot navigation data. In this embodiment, the electronic device can assess the quality of navigation data. If substandard data is found, its location is marked on a first navigation map. The electronic device can also display the marked first navigation map (i.e., a second navigation map) through a human-machine interface, allowing technicians to quickly identify the location of the substandard data on the map, facilitating correction. Furthermore, since the electronic device can assess navigation data quality based on a static first navigation map, the robot does not need to re-enter the working environment to identify substandard data. This method is used for self-inspection or remote review of navigation data by technicians.

[0061] Please see Figure 3 This application also provides a device for quality assessment of robot navigation data, such as... Figure 3 As shown, the device 300 includes: an acquisition module 301, an evaluation module 302, and a display module 303. Specifically, the acquisition module 301 is used to acquire robot navigation data, which includes a static first navigation map; the evaluation module 302 is used to evaluate the quality of the navigation data, and if there is substandard data in the navigation data, the location corresponding to the substandard data is marked in the first navigation map to obtain a second navigation map; the display module 303 is used to display the second navigation map through a human-computer interaction interface.

[0062] In some embodiments, the navigation data further includes navigation path data. The evaluation module 302 is specifically used to evaluate the composition quality of the first navigation map. If there is a substandard area in the first navigation map, the location of the substandard area is marked in the first navigation map. And / or, it is used to evaluate the quality of the navigation path data. If there is substandard path data in the navigation path data, the location of the path segment corresponding to the substandard path data is marked in the first navigation map.

[0063] In some embodiments, the navigation path data includes preset travel patterns for the robot in each path segment; the quality assessment of the navigation data includes: determining the travel width of the path segment and the surrounding environment of the path segment; determining the ideal travel pattern of the robot in the path segment based on the travel width and the surrounding environment; if the preset travel pattern and the ideal travel pattern do not match, then the preset travel pattern is determined to be the problematic path data.

[0064] In some embodiments, determining the ideal passage mode of the robot on the path segment based on the passage width and the surrounding environment includes: if the passage width is less than a preset width threshold and the surrounding environment includes a preset environment, then the ideal passage mode of the path segment is determined to be a narrow path mode; wherein the preset environment includes a drop-off environment.

[0065] In some embodiments, the first navigation map includes a passable area and a restricted area. Evaluating the composition quality of the first navigation map includes: determining multiple target point locations that the robot needs to reach in the first navigation map based on the navigation path data; determining whether the passable area includes an area that the robot does not need to reach based on the target point locations; if so, determining the area that the robot does not need to reach as the problem area; and / or setting the colors of the passable area and the restricted area to a first color and a second color respectively; if the passable area of ​​the first color has scattered points of the second color, then determining the area where the scattered points are located as the problem area.

[0066] In some embodiments, evaluating the composition quality of the first navigation map further includes: determining the boundary line between the passable area and the restricted area based on the first navigation map; determining whether the boundary line includes a boundary line segment with substandard quality; if so, determining the area where the substandard boundary line segment is located as the problem area.

[0067] Please see Figure 4In some embodiments, the second navigation map further includes prompt information, and the device 300 further includes a labeling module 304, which is used to: label the first navigation map with prompt information before obtaining the second navigation map, wherein the prompt information is used to indicate the reason why the problem data quality is unqualified.

[0068] Please continue reading. Figure 4 In some embodiments, the device 300 further includes a correction module 305, which is configured to: after the second navigation map is displayed through the human-computer interaction interface, receive user operations on the second navigation map through the human-computer interaction interface, and correct the problematic data in response to the user operations.

[0069] Please see Figure 5 , Figure 5 This is a schematic diagram of the hardware structure of an electronic device that performs the above method according to an embodiment of this application, as shown below. Figure 5 As shown, the electronic device 100 includes at least one processor 101 and a memory 102. Figure 5 Taking a processor 101 as an example, the processor 101 and the memory 102 can be connected via a bus or other means. Figure 5 Taking a bus connection as an example, memory 102, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the methods in the embodiments of this application. Processor 101 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions, and modules stored in memory 102, thereby implementing the methods provided in the above-described method embodiments.

[0070] The memory 102 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the path selection device of the mobile robot. Furthermore, the memory 102 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 102 may optionally include memory remotely located relative to the processor 101, and these remote memories can be connected to the path selection device of the mobile robot via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0071] The one or more modules are stored in the memory 102. When executed by the at least one processor 101, they perform the methods in any of the above method embodiments, for example, the methods described above. Figure 1 Method steps S11-S13, Figure 2 Method steps S11-S14, and execution Figure 3 Modules 301-303 in the middle, Figure 4 The functions of modules 301-305 in the document.

[0072] Please see Figure 6 This application also provides a robot navigation data quality assessment system, such as... Figure 6 As shown, the system 60 includes a mobile robot 61 and an electronic device 62 (the electronic device 62 may be...). Figure 5 The mobile robot 61 and the electronic device 62 are communicatively connected; wherein the electronic device includes a human-machine interface (e.g., a display and buttons). In some embodiments, the mobile robot 61 can send navigation data to the electronic device 62, so that the electronic device 62 can perform a quality assessment of the navigation data according to the method provided in the above embodiments. In other embodiments, when the electronic device 62 receives a user operation on a second navigation map through the human-machine interface, and in response to the user operation, corrects problematic data in the navigation data, the electronic device 62 can also send the corrected navigation data to the mobile robot 61, so that the mobile robot 61 can navigate according to the corrected navigation data.

[0073] The above-described product can perform the methods provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects for performing the methods. Technical details not described in detail in this embodiment can be found in the methods provided in the embodiments of this application.

[0074] The electronic devices in this application can exist in various forms, including but not limited to mobile phones, tablets, computers, and other electronic devices with data interaction functions.

[0075] This application provides a non-volatile computer-readable storage medium storing computer-executable instructions. These instructions are executed by an electronic device using the path selection method for a mobile robot in any of the above-described method embodiments, for example, executing the methods described above. Figure 1 Method steps S11-S13, Figure 2 Method steps S11-S14, and execution Figure 3 Modules 301-303 in the middle, Figure 4 The functions of modules 301-305 in the document.

[0076] This application provides a computer program product, including a computing program stored on a non-volatile computer-readable storage medium. The computer program includes program instructions that, when executed by a computer, cause the computer to perform the path selection method for a mobile robot in any of the above method embodiments, for example, to perform the above-described... Figure 1 Method steps S11-S13, Figure 2 Method steps S11-S14, and execution Figure 3 Modules 301-303 in the middle, Figure 4 The functions of modules 301-305 in the document.

[0077] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0078] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software and a general-purpose hardware platform, or it can be implemented using hardware. Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and not to limit them; under the concept of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of this application as described above, which are not provided in detail for the sake of brevity; although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for quality assessment of robot navigation data, applied to electronic devices, characterized in that, The method comprises: obtaining robot navigation data, the navigation data comprising navigation path data, a static first navigation map comprising a passable area and a non-passable area; performing quality assessment on the navigation data, and if there is problem data of unqualified quality in the navigation data, marking the position corresponding to the problem data in the first navigation map to obtain a second navigation map; displaying the second navigation map through a man-machine interaction interface; wherein the performing quality assessment on the navigation data, and if there is problem data of unqualified quality in the navigation data, marking the position corresponding to the problem data in the first navigation map comprises: determining a plurality of target point positions that the robot needs to reach in the first navigation map based on the navigation path data, determining whether the passable area includes an area that the robot does not need to reach based on the target point positions, and if yes, determining the area that the robot does not need to reach as a problem area; and / or, setting the colors of the passable area and the non-passable area as a first color and a second color respectively, and if the passable area of the first color is distributed with scattered points of the second color, determining the area where the scattered points are located as the problem area; determining a boundary line between the passable area and the non-passable area based on the first navigation map, determining whether the boundary line includes a boundary line segment of unqualified quality, and if yes, determining the area where the boundary line segment of unqualified quality is located as the problem area; if there is a problem area of unqualified quality in the first navigation map, marking the position where the problem area is located in the first navigation map.

2. The method of claim 1, wherein, The performing quality assessment on the navigation data, and if there is problem data of unqualified quality in the navigation data, marking the position corresponding to the problem data in the first navigation map further comprises: performing quality assessment on the navigation path data, and if there is problem path data of unqualified quality in the navigation path data, marking the position where the path segment corresponding to the problem path data is located in the first navigation map.

3. The method of claim 2, wherein, The navigation path data comprises a preset passable mode of the robot at each path segment; The performing quality assessment on the navigation data comprises: determining the passable width of the path segment and the peripheral environment of the path segment; determining the ideal passable mode of the robot at the path segment based on the passable width and the peripheral environment; if the preset passable mode and the ideal passable mode do not match, determining the preset passable mode as the problem path data.

4. The method of claim 3, wherein, The determining the ideal passable mode of the robot at the path segment based on the passable width and the peripheral environment comprises: if the passable width is less than a preset width threshold and the peripheral environment comprises a preset environment, determining the ideal passable mode of the path segment as a narrow path mode; wherein the preset environment comprises a drop-off environment.

5. The method according to any one of claims 1 to 4, characterized in that, The second navigation map further comprises prompt information, and before obtaining the second navigation map, the method further comprises: Mark a prompt information in the first navigation map, wherein the prompt information is used to prompt the reason of the unqualified problem data quality.

6. The method according to any one of claims 1 to 4, characterized in that, After the second navigation map is displayed through the human-computer interaction interface, the method further comprises: Receiving a user operation of a user on the second navigation map through the human-computer interaction interface, and correcting the problem data in response to the user operation.

7. An electronic device, comprising: The electronic device comprises a processor and a memory storing instructions, which, when executed by the processor, cause the electronic device to perform the method according to any one of claims 1 to 6.

8. A system for quality assessment of robot navigation data, characterized by The system comprises a mobile robot and the electronic device of claim 7, and the mobile robot and the electronic device are communicatively connected.

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