BIM-Based Indoor Mobile Robot Navigation System and Method

Abstract

The present invention discloses an indoor mobile robot navigation system and method based on BIM, including an edge computing gateway host analysis module, a navigation information storage and call list module, a human-computer interaction cloud analysis module, and a navigation parameter setting module at layout points with different line change positions; determining a safe forward speed and direction according to the standard navigation position layout points, and determining whether navigation parameter control is required based on the safe forward speed and direction; obtaining different turning angle radius sizes by analyzing the unit distance navigation starting point and target point information of layout points with different line change positions, and then sorting out and obtaining a real-time forward speed and direction change visualization chart, determining the navigation parameters to be regulated and the control frequency; the present invention performs better in terms of path smoothness, dynamic obstacle avoidance ability and adaptability, providing an efficient and intelligent solution for indoor navigation.

Description

Technical Field

[0001] The present invention relates to the field of indoor mobile robot navigation parameter control, and particularly to an indoor mobile robot navigation system and method based on BIM. Background Art

[0002] With the popularization of Building Information Modeling (BIM), its application in building design, construction, and operation and maintenance has become the core technology of digital buildings. The BIM model not only contains the geometric structure of the building but also integrates topological relationships, functional areas, and material properties, providing an accurate data basis for the efficient navigation of indoor mobile robots. In traditional navigation methods, robots rely on lidar, vision sensors, and map construction technologies (such as SLAM) for positioning and path planning. However, these methods are usually limited by the dynamics of the environment and the accuracy of sensor data, resulting in insufficient navigation accuracy or inefficient path planning. By integrating the BIM model, robots can pre-understand the detailed information inside the building, achieving more accurate positioning, more efficient path planning, and dynamic obstacle avoidance.

[0003] Existing indoor robot navigation methods mainly rely on two types of technologies: sensor-based autonomous navigation and path planning based on a preset map. Autonomous navigation methods such as SLAM use lidar or vision sensors to build a map and position in real time, but are limited by the accuracy of the sensors and environmental interference. For example, lidar may fail in front of highly reflective materials, while vision navigation performs poorly in low-light conditions. In addition, autonomous navigation consumes high computing resources and cannot provide global path planning support for complex building structures. Navigation methods based on a preset map, such as a two-dimensional plane map, although can provide relatively efficient path planning, lack the ability to adapt to environmental changes. If there are dynamic obstacles or temporary changes in the building, these methods usually require frequent map updates, resulting in high maintenance costs and insufficient flexibility of the navigation system, and unable to achieve precise control of navigation parameters. Summary of the Invention

[0004] In order to overcome the disadvantages and deficiencies existing in the prior art; for this purpose, the present invention proposes an indoor mobile robot navigation system and method based on BIM, which is used to solve the problems that a large amount of data processing is required when the prior art performs navigation parameter control, and the timing of navigation parameter control cannot be reasonably determined, and precise control of navigation parameters cannot be achieved.

[0005] To achieve the above object, the first aspect of the present invention provides an indoor mobile robot navigation system based on BIM, including an edge computing gateway host analysis module, and a navigation information storage and call list module and a human-computer interaction cloud analysis module connected thereto; and the navigation information storage and call list module is connected to a navigation parameter setting module at different line change position control points;

[0006] Navigation information storage and call list module: During the navigation operation of the indoor mobile robot at the control points arranged at different line change positions, the unit distance navigation starting point and target point information of the unit distance indoor mobile robot navigation parameters are collected through the connected navigation parameter setting module and transmitted to the edge computing gateway host analysis module;

[0007] Edge computing gateway host analysis module: Using the BIM model module to collect the safe forward speed and direction of the control points at different line change positions, determining the real-time navigation forward speed and direction according to the path passability, comparing the safe forward speed, direction with the real-time navigation forward speed and direction to determine whether navigation parameter control is required; if control is required, collect the unit distance navigation starting point and target point information of the unit distance indoor mobile robot navigation parameters, if control is not required, continue navigation according to the navigation set value; and

[0008] Calculating and obtaining the turning angle radius size of the unit distance of the unit distance indoor mobile robot navigation parameters according to the unit distance navigation starting point and target point information; drawing a visual chart of the real-time forward speed and direction change for different turning angle radius sizes, and comparing and analyzing the visual chart of the real-time forward speed and direction change with the preset visual chart of the forward speed and direction change to determine the indoor mobile robot navigation parameters to be controlled; the preset visual chart of the forward speed and direction change is obtained using the BIM model module.

[0009] Further, the edge computing gateway host analysis module performs two-way data transmission with the navigation information storage and call list module and the human-computer interaction cloud analysis module respectively; and the human-computer interaction cloud analysis module includes a 5G signal control interface;

[0010] The navigation information storage and call list module performs two-way data transmission with the navigation parameter setting module at the control points at different line change positions; and the navigation parameter setting module matches different navigation stages of the unit distance indoor mobile robot navigation parameters.

[0011] Further, the edge computing gateway host analysis module uses the BIM model module to match and collect the safe forward speed and direction of the control points at different line change positions, and uses the safe forward speed and direction to judge whether navigation parameter control is required, including:

[0012] Connect to the BIM model module and calculate the best path flatness within the unit distance of the standard navigation position control point; the control points at different line change positions are the same as the standard navigation position control point in terms of funds or contain the same indoor mobile robot navigation parameters;

[0013] Obtain the forward speed per unit time of the navigation unit and the path flatness parameters of the direction path for different optimal path flatness, denoted as the safe forward speed and direction; obtain the optimal path flatness of the control points arranged at different line change positions, denoted as the real-time navigation forward speed and direction; the forward speed per unit time of the navigation unit and the path flatness parameters of the direction path include the path flatness smoothing factor or the path curvature of the path flatness.

[0014] When the real-time navigation forward speed and direction are less than the safe forward speed and direction, it is determined that navigation parameter control needs to be performed on the control points arranged at different line change positions; otherwise, it is determined that navigation parameter control does not need to be performed on the control points arranged at different line change positions.

[0015] Further, when it is determined that navigation parameter control needs to be performed on the control points arranged at different line change positions, the navigation parameter setting module arranged on the control points arranged at different line change positions is used to collect and obtain the information of the starting point and the target point of the navigation per unit distance; and

[0016] After screening the information of the starting point and the target point of the navigation per unit distance, it is transmitted to the edge computing gateway host analysis module; the information of the starting point and the target point of the navigation per unit distance includes the three-dimensional coordinate data of all objects in the navigation space and the path flatness dynamic obstacle data.

[0017] Further, the edge computing gateway host analysis module extracts the size of the turning radius corresponding to the navigation parameters of the indoor mobile robot per unit distance from the information of the starting point and the target point of the navigation per unit distance, and draws a visualization chart of the change of the real-time forward speed and direction based on different sizes of the turning radius, including:

[0018] Extract the path flatness dynamic obstacle data of the navigation parameters of the indoor mobile robot per unit distance from the information of the starting point and the target point of the navigation per unit distance, and calculate the size of the turning radius of the navigation parameters of the indoor mobile robot per unit distance within the unit distance by using the path flatness dynamic obstacle data;

[0019] Establish independent variables according to the navigation positions for different sizes of the turning radius, and fit and draw a visualization chart of the change of the real-time forward speed and direction with the size of the turning radius as the dependent variable.

[0020] Further, the edge computing gateway host analysis module obtains the preset forward speed and direction change visualization chart based on the information of the starting point and the target point of the navigation per unit distance corresponding to different standard navigation position control points when reaching the optimal path flatness, including:

[0021] Select at least one standard navigation position control point from different standard navigation position control points according to the optimal path flatness, and mark the corresponding unit-distance navigation starting point and target point information as the preset navigation starting point and target point information;

[0022] Obtain the turning radius size of the unit-distance indoor mobile robot navigation parameter from the preset navigation starting point and target point information, and mark it as the preset path flatness turning radius; draw the abscissa according to different preset path flatness turning radii per unit distance, and obtain the preset forward speed and direction change visualization chart.

[0023] Furthermore, the edge computing gateway host analysis module compares the real-time forward speed and direction change visualization chart with the preset forward speed and direction change visualization chart, and controls the unit-distance indoor mobile robot navigation parameter according to the comparison result, including:

[0024] Compare the real-time forward speed and direction change visualization chart with the preset forward speed and direction change visualization chart, determine the indoor mobile robot navigation parameters corresponding to the completely identical parts of the horizontal and vertical coordinates of the two change visualization charts, and mark them as the navigation parameters to be regulated;

[0025] Determine the path flatness error of the navigation parameter to be regulated according to the real-time forward speed and direction change visualization chart and the preset forward speed and direction change visualization chart; adjust the path flatness dynamic obstacle data of the navigation parameter to be regulated in the three-dimensional coordinate data of all objects in the navigation space to reduce the path flatness error.

[0026] The second aspect of the present invention provides an indoor mobile robot navigation system based on BIM, including:

[0027] Utilize the standard navigation position control points recorded in the BIM model module and the corresponding optimal path flatness to obtain the safe forward speed and direction based on the navigation unit-time forward speed and direction path flatness parameters of different optimal path flatnesses;

[0028] Collect the real-time navigation forward speed and direction of different line change position control points; compare the real-time navigation forward speed and direction with the safe forward speed and direction to determine whether to control the navigation parameters of different line change position control points; if control is required, proceed to the next step; if control is not required, continue navigation according to the navigation set value;

[0029] Calculate the turning radius of the navigation parameters of the indoor mobile robot per unit distance based on the collected information of the navigation starting point and the target point per unit distance, and then obtain a visual chart of the real-time forward speed and direction change; compare the visual chart of the real-time forward speed and direction change with the preset forward speed and direction change visual chart to determine and control the navigation parameters of the indoor mobile robot.

[0030] Advantageous effects:

[0031] The present invention proposes a BIM-based indoor mobile robot navigation system and method. Determine the safe forward speed and direction based on the standard navigation position layout points, and determine whether navigation parameter control is required based on the safe forward speed and direction; obtain different turning radius sizes by analyzing the unit distance navigation starting point and target point information of the layout points at different line change positions, and then organize and obtain a visual chart of the real-time forward speed and direction change; compare the visual chart of the real-time forward speed and direction change with the preset forward speed and direction change visual chart obtained through the standard navigation position layout points to determine the navigation parameters to be adjusted and the control frequency; thereby improving the navigation parameters. By comparing the visual chart of the real-time forward speed and direction change with the preset forward speed and direction change visual chart, the present invention can not only determine which indoor mobile robot navigation parameters need to be adjusted, but also determine the adjustment range, and accelerate the starting point and target point of the navigation parameter control; and after completing the navigation parameters at the layout points at different line change positions, relevant data can also be uploaded to the BIM model module to adjust the standard navigation position layout points, which helps to improve the timeliness of the navigation parameter control, make the efficiency of the path flatness more reasonable, and thus ensure the effective progress of the navigation. The BIM model provides accurate building geometry and spatial topology information, enabling the robot to obtain global environment data without relying entirely on sensors, thereby improving the accuracy and efficiency of positioning and path planning. BIM integrates the functional areas, material properties, and channel structures of the building, facilitating the robot to plan the optimal path and flexibly adapt to various task requirements. In addition, combined with real-time sensor data, BIM can dynamically update the robot's perception of the environment, effectively making up for the limitations of sensors in complex or changing environments. The BIM-based navigation system performs better in terms of path smoothness, dynamic obstacle avoidance ability, and adaptability, while reducing the map maintenance cost, providing an efficient and intelligent solution for indoor navigation. Description of the Drawings

[0032] Figure 1 It is a schematic diagram of the system module composition of the present invention;

[0033] Figure 2 It is a schematic diagram of the method flow of the present invention. Detailed Embodiments

[0034] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0035] As Figure 1 shown, an embodiment of the first aspect of the present invention provides an indoor mobile robot navigation system based on BIM, including an edge computing gateway host analysis module, and a navigation information storage and call list module and a human-computer interaction cloud analysis module connected thereto; and the navigation information storage and call list module is connected to a navigation parameter setting module at different line change position control points.

[0036] Navigation information storage and call list module: During the navigation operation of the indoor mobile robot at different line change position control points, it collects the unit distance navigation starting point and target point information of the unit distance navigation parameters of the indoor mobile robot through the connected navigation parameter setting module, and transmits them to the edge computing gateway host analysis module.

[0037] Edge computing gateway host analysis module: Using the BIM model module to collect the safe forward speed and direction of different line change position control points, determining the real-time navigation forward speed and direction according to the path passability, comparing the safe forward speed, direction with the real-time navigation forward speed and direction to determine whether navigation parameter control is required; if control is required, it collects the unit distance navigation starting point and target point information of the unit distance navigation parameters of the indoor mobile robot, if control is not required, it continues navigation according to the navigation set value; and

[0038] Calculating the turning radius size of the unit distance of the unit distance navigation parameters of the indoor mobile robot according to the unit distance navigation starting point and target point information; drawing a real-time forward speed and direction change visualization chart for different turning radius sizes, and comparing and analyzing the real-time forward speed and direction change visualization chart with a preset forward speed and direction change visualization chart to determine the navigation parameters of the controlled indoor mobile robot; the preset forward speed and direction change visualization chart is obtained using the BIM model module.

[0039] The navigation parameter control in the prior art mainly controls each parameter of the navigation parameter. Generally, it adjusts by comparing the path flatness dynamic obstacle data of the navigation parameter with the optimal real-time parameter. However, this method is only effective for controlling a single navigation parameter, and the effect is not good when multiple navigation parameters need to be coordinated; it is also possible to establish a particle swarm model according to the combination of the optimal parameters of the navigation parameter, and search in the constructed search space through the particle swarm model to complete the control of multiple navigation parameters. This method requires a large amount of data preparation work, which affects the forward speed, direction and accuracy of the navigation parameter control.

[0040] In the present invention application, the safe forward speed and direction are first determined according to the standard navigation position layout points, and it is determined whether navigation parameter control is required based on the safe forward speed and direction; by analyzing the unit distance navigation start point and target point information of the layout points at different line change positions, different turning radius sizes are obtained, and then a visual chart of the real-time forward speed and direction changes is sorted out and obtained; the visual chart of the real-time forward speed and direction changes is compared with the preset visual chart of the forward speed and direction changes obtained through the standard navigation position layout points to determine the navigation parameters to be regulated and the control frequency; while ensuring the accuracy of the navigation parameter control, the data processing volume is reduced, and thus the navigation parameter is improved.

[0041] In the present invention application, the edge computing gateway host analysis module performs two-way data transmission with the navigation information storage and call list module and the human-computer interaction cloud analysis module respectively; and the human-computer interaction cloud analysis module includes a 5G signal control interface; the navigation information storage and call list module performs two-way data transmission with the navigation parameter setting module on the layout points at different line change positions; and the navigation parameter setting module matches different navigation stages of the unit distance indoor mobile robot navigation parameters.

[0042] The edge computing gateway host analysis module mainly performs data processing and interacts with the navigation information storage and call list module and the human-computer interaction cloud analysis module. The human-computer interaction cloud analysis module is used to display the navigation parameter control process and display the control suggestions to the staff. The navigation information storage and call list module is mainly used to collect the unit distance navigation start point and target point information of the layout points at different line change positions and interact with the navigation parameter setting module and the edge computing gateway host analysis module. It should be noted that the navigation parameter setting module includes a camera, a forward speed, a direction sensor, etc., and can be set beside the indoor mobile robot navigation parameter, and can be installed inside the indoor mobile robot navigation parameter when necessary.

[0043] In the edge computing gateway host analysis module of the present invention application, the BIM model module is used to match and collect the safe forward speed and direction of the control points at the changing positions of different lines, and based on the safe forward speed and direction, it is judged whether navigation parameter control is required, including: connecting to the BIM model module, and calculating the best path flatness within the unit distance of the standard navigation position control point from it; obtaining the navigation unit time forward speed and direction path flatness parameters of different best path flatness, denoted as the safe forward speed and direction; collecting the best path flatness of the control points at the changing positions of different lines, denoted as the real-time navigation forward speed and direction; when the real-time navigation forward speed and direction are less than the safe forward speed and direction, it is determined that navigation parameter control is required for the control points at the changing positions of different lines; otherwise, it is determined that navigation parameter control is not required for the control points at the changing positions of different lines.

[0044] After connecting to the BIM model module, obtain the best path flatness corresponding to different standard navigation position control points from it, and determine the safe forward speed and direction based on the distribution characteristics of each best path flatness. If the real-time navigation forward speed and direction of the control points at the changing positions of different lines are less than the safe forward speed and direction, it can be understood that the overall path flatness of the control points at the changing positions of different lines is lower than the average level, or not in the optimal state, and at this moment, navigation parameter control is required.

[0045] The control points at the changing positions of different lines are the same as the standard navigation position control points in terms of funds or contain the same indoor mobile robot navigation parameters. Generally, it is considered that the control points at the changing positions of different lines and the standard navigation position control points are exactly the same, that is, different navigation position control points with a path flatness. The BIM model module can also immediately establish a data service platform for the manufacturer. It should be understood that after obtaining the best path flatness of different standard navigation position control points, reasonable navigation unit time forward speed and direction path flatness parameters should be used to determine the safe forward speed and direction to avoid the influence of extreme values on the rationality of the safe forward speed and direction.

[0046] When it is determined in the present invention application that navigation parameter control is required for the control points at the changing positions of different lines, the navigation parameter setting module set at the control points at the changing positions of different lines is used to collect and obtain the unit distance navigation starting point and target point information; and after screening the unit distance navigation starting point and target point information, it is transmitted to the edge computing gateway host analysis module.

[0047] The screening of the starting point and target point information for unit - distance navigation mentioned here mainly aims to remove outliers. The starting point and target point information for unit - distance navigation includes the three - dimensional coordinate data of all objects in the navigation space and the path flatness dynamic obstacle data. The standard implementation limit is the limit value for the operation of the indoor mobile robot navigation parameters, such as the limit value of the smoothing factor; the path flatness dynamic obstacle data is the ratio of the number of damaged path flatness at the control points at different line change positions during operation to the total number of path flatness degrees. The path flatness dynamic obstacle data should be within the range of the implementation limit, otherwise it is determined that the navigation parameter setting module or the indoor mobile robot navigation parameters are abnormal, and a warning is given in a timely manner. In the application of this invention, the edge - computing gateway host analysis module extracts the turning - angle radius corresponding to the unit - distance indoor mobile robot navigation parameters from the starting point and target point information for unit - distance navigation, and obtains a real - time forward speed and direction - change visualization chart based on different turning - angle radius sizes, including:

[0048] Extract the path flatness dynamic obstacle data of the unit - distance indoor mobile robot navigation parameters from the starting point and target point information for unit - distance navigation, calculate the turning - angle radius size of the unit - distance indoor mobile robot navigation parameters within the unit distance based on the path flatness dynamic obstacle data; establish independent variables according to the navigation position for different turning - angle radius sizes, and fit to obtain a real - time forward speed and direction - change visualization chart with the turning - angle radius size as the dependent variable.

[0049] Divide the control points at different line change positions to obtain different indoor mobile robot navigation parameters. The indoor mobile robot navigation parameters here are preferably real - time parameters that can be automatically adjusted for the convenience of realizing the automatic control of the navigation parameters through the edge - computing gateway host analysis module. Calculate the turning - angle radius size of the unit - distance indoor mobile robot navigation parameters through the path flatness dynamic obstacle data, number them after sorting from large to small, and then fit to obtain a real - time forward speed and direction - change visualization chart. It should be understood that there is a linear or non - linear relationship between the turning - angle radius sizes of the indoor mobile robot navigation parameters at the same navigation - position control points.

[0050] In the edge computing gateway host analysis module of this invention application, a visualization chart of preset forward speed and direction change is obtained based on the information of the starting point and target point of unit distance navigation corresponding to different standard navigation position control points when the best path flatness is reached, including: selecting at least one standard navigation position control point from different standard navigation position control points based on the best path flatness, and marking the corresponding starting point and target point information of unit distance navigation as preset navigation starting point and target point information; obtaining the turning radius size of the navigation parameters of the indoor mobile robot of unit distance from the preset navigation starting point and target point information, and marking it as the turning radius of the preset path flatness; plotting the abscissa according to different preset path flatness turning radii per unit distance to obtain a visualization chart of preset forward speed and direction change.

[0051] To improve the overall path flatness of control points at different line change positions, it is necessary to provide data reference for the control of its navigation parameters, that is, reasonably select a best path flatness from the BIM model module (generally better than the real-time navigation forward speed and direction of control points at different line change positions), and mark the corresponding starting point and target point information of unit distance navigation as preset navigation starting point and target point information, then a visualization chart of preset forward speed and direction change can be correspondingly obtained.

[0052] It should be noted that by reasonably selecting the preset navigation starting point and target point information, not only can the real-time forward speed and direction of the navigation parameters of the indoor mobile robot of unit distance at different line change positions be improved, but also the real-time forward speed and direction of the navigation parameters of the indoor mobile robot of unit distance at different line change positions can be reasonably reduced when necessary; this adjustment method is suitable for scenarios where the control points at different line change positions need to be adjusted at any time.

[0053] In the edge computing gateway host analysis module of this invention application, the real-time forward speed and direction change visualization chart is compared with the preset forward speed and direction change visualization chart, and the navigation parameters of the indoor mobile robot of unit distance are controlled according to the comparison result, including:

[0054] Comparing the real-time forward speed and direction change visualization chart with the preset forward speed and direction change visualization chart, determining the navigation parameters of the indoor mobile robot corresponding to the completely identical part of the abscissa and ordinate of the two change visualization charts, and marking them as navigation parameters to be regulated; determining the path flatness error of the navigation parameters to be regulated according to the real-time forward speed and direction change visualization chart and the preset forward speed and direction change visualization chart; adjusting the path flatness dynamic obstacle data of the navigation parameters to be regulated within the three-dimensional coordinate data of all objects in the navigation space to reduce the path flatness error.

[0055] When comparing the real-time forward speed and direction change visualization chart with the preset forward speed and direction change visualization chart, first determine the positions where the two do not overlap. The corresponding indoor mobile robot navigation parameters can be determined through the numbers of these positions, and these indoor mobile robot navigation parameters are the navigation parameters to be adjusted. As for the degree of adjustment required for the navigation parameters to be adjusted, it depends on the error between the two change visualization charts.

[0056] As Figure 2 shown, the second aspect embodiment of the present invention provides a BIM-based indoor mobile robot navigation method, including:

[0057] Step A1: Based on the layout points of each standard navigation position recorded in the BIM model module and the corresponding best path flatness, obtain the safe forward speed and direction based on the navigation unit time forward speed and direction path flatness parameters with different best path flatnesses.

[0058] Step A2: Collect the real-time navigation forward speed and direction of the layout points at different line change positions; compare the real-time navigation forward speed and direction with the safe forward speed and direction to determine whether to control the navigation parameters for the layout points at different line change positions; if control is required, proceed to the next step; if control is not required, continue navigation according to the navigation set value.

[0059] Step A3: Calculate and obtain the turning radius size of the unit distance indoor mobile robot navigation parameters based on the collected unit distance navigation start point and target point information, and then obtain the real-time forward speed and direction change visualization chart; compare the real-time forward speed and direction change visualization chart with the preset forward speed and direction change visualization chart to determine and control the indoor mobile robot navigation parameters.

[0060] The working principle of the present invention:

[0061] Based on the layout points of each standard navigation position recorded in the BIM model module and the corresponding best path flatness, obtain the safe forward speed and direction based on the navigation unit time forward speed and direction path flatness parameters with different best path flatnesses.

[0062] Collect the real-time navigation forward speed and direction of the layout points at different line change positions; compare the real-time navigation forward speed and direction with the safe forward speed and direction to determine whether to control the navigation parameters for the layout points at different line change positions; if control is required, proceed to the next step; if control is not required, continue navigation according to the navigation set value.

[0063] Calculate the turning radius of the navigation parameters of the indoor mobile robot per unit distance based on the collected information of the starting point and the target point of the navigation per unit distance, and then obtain the visual chart of the real-time forward speed and the direction change; compare the visual chart of the real-time forward speed and the direction change with the preset forward speed and the visual chart of the direction change to determine and control the navigation parameters of the indoor mobile robot.

[0064] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. The BIM-based indoor mobile robot navigation system is characterized by: The system includes an edge computing gateway host analysis module, a navigation information storage and call list module, a human-computer interaction cloud analysis module, and a navigation parameter setting module at different route change position control points; The navigation information storage and call list module is used to collect the unit distance navigation starting point and target point information of the unit distance indoor mobile robot navigation parameters through the navigation parameter setting module connected thereto during the navigation operation of the indoor mobile robot at the control points of different line change positions, and transmit it to the edge computing gateway host analysis module; The edge computing gateway host analysis module is used to collect the safe forward speed and direction of the control points at different line change positions using the BIM model module, determine the real-time navigation forward speed and direction according to the path passability, and compare the safe forward speed and direction with the real-time navigation forward speed and direction to determine whether navigation parameter control is required; If control is required, the unit distance navigation starting point and target point information of the unit distance indoor mobile robot navigation parameters are collected; if control is not required, navigation is continued according to the navigation setting value; The navigation parameters of the indoor mobile robot per unit distance are calculated based on the information of the navigation starting point and target point of the unit distance; a visual chart of the real-time forward speed and direction change is drawn for different sizes of the steering angle radius, and the visual chart of the real-time forward speed and direction change is compared and analyzed with the preset visual chart of the forward speed and direction change to determine the navigation parameters of the indoor mobile robot to be controlled; The preset forward speed and direction change visualization chart is obtained using the BIM model module; The edge computing gateway host analysis module extracts the turning angle radius corresponding to the unit distance indoor mobile robot navigation parameter from the unit distance navigation starting point and target point information, and draws the real-time forward speed and direction change visualization chart based on different turning angle radius sizes, including: The path flatness dynamic obstacle data of the unit distance indoor mobile robot navigation parameters are extracted from the unit distance navigation starting point and target point information, and the turning angle radius of the unit distance indoor mobile robot navigation parameters within the unit distance is calculated using the path flatness dynamic obstacle data.

2. The BIM-based indoor mobile robot navigation system according to claim 1, characterized in that: The edge computing gateway host analysis module transmits data bidirectionally with the navigation information storage and call list module and the human-computer interaction cloud analysis module respectively; and the human-computer interaction cloud analysis module includes a 5G signal control interface; The navigation information storage and call list module transmits data bidirectionally with the navigation parameter setting module at different line change position control points; and the navigation parameter setting module matches different navigation stages of the unit distance indoor mobile robot navigation parameters; The edge computing gateway host analysis module uses the BIM model module to match and collect the safe forward speed and direction of different line change position control points, and uses the safe forward speed and direction to determine whether navigation parameter control is required, including: connecting the BIM model module, and calculating the optimal path flatness within a unit distance of the standard navigation position control point; the indoor mobile robot navigation parameters of the different line change position control points and the standard navigation position control points are the same; the navigation unit time forward speed and direction path flatness parameters of the optimal path flatness are obtained, recorded as the safe forward speed and direction; the optimal path flatness of the different line change position control points is obtained, recorded as the real-time navigation forward speed and direction; the navigation unit time forward speed and direction path flatness parameters include path flatness smoothing factor or path flatness path curvature; When the real-time navigation forward speed and direction are less than the safe forward speed and direction, it is determined that navigation parameter control is required for the control points at different route change positions; otherwise, it is determined that navigation parameter control is not required for the control points at different route change positions.

3. The BIM-based indoor mobile robot navigation system according to claim 2, characterized in that: When it is determined that navigation parameter control is required for the control points at different line change positions, the navigation parameter setting module set at the control points at different line change positions collects and obtains the unit distance navigation starting point and target point information; and the unit distance navigation starting point and target point information are filtered and transmitted to the edge computing gateway host analysis module; The unit distance navigation starting point and target point information includes the three-dimensional coordinate data of all objects in the navigation space and the path flatness dynamic obstacle data.

4. The BIM-based indoor mobile robot navigation system according to claim 1, characterized in that: The edge computing gateway host analysis module obtains the preset forward speed and direction change visualization chart based on the unit distance navigation starting point and target point information corresponding to different standard navigation position control points when the optimal path flatness is achieved, including: Selecting at least one standard navigation position control point from different standard navigation position control points using the optimal path flatness, and marking the corresponding unit distance navigation starting point and target point information as preset navigation starting point and target point information; The steering angle radius of the indoor mobile robot navigation parameter per unit distance is obtained from the preset navigation starting point and target point information, and marked as the preset path flatness steering angle radius; the horizontal coordinate is plotted according to the unit distance for different preset path flatness steering angle radii to obtain the preset forward speed and direction change visualization chart.

5. The BIM-based indoor mobile robot navigation system according to claim 1, characterized in that: The edge computing gateway host analysis module compares the real-time forward speed and direction change visualization chart with the preset forward speed and direction change visualization chart, and controls the navigation parameters of the unit distance indoor mobile robot according to the comparison result, including: Compare the real-time forward speed and direction change visualization chart with the preset forward speed and direction change visualization chart, determine the indoor mobile robot navigation parameters corresponding to the parts with exactly the same horizontal and vertical coordinates in the two change visualization charts, and mark them as navigation parameters to be adjusted; Determine the path flatness error of the navigation parameter to be adjusted according to the real-time forward speed and direction change visualization chart and the preset forward speed and direction change visualization chart; adjust the path flatness dynamic obstacle data of the navigation parameter to be adjusted in the three-dimensional coordinate data of all objects in the navigation space to reduce the path flatness error.

6. The BIM-based indoor mobile robot navigation system according to any one of claims 1 to 5, characterized in that: The system is implemented by a BIM-based indoor mobile robot navigation method, which includes: Step A1, using each standard navigation position control point recorded in the BIM model module and the corresponding optimal path flatness, based on the navigation unit time forward speed and direction path flatness parameters of different optimal path flatnesses, obtain the safe forward speed and direction; Step A2, collecting the real-time navigation forward speed and direction of the control points at different route change positions; comparing the real-time navigation forward speed and direction with the safe forward speed and direction to determine whether to perform navigation parameter control on the control points at different route change positions; if control is required, proceed to the next step; if control is not required, continue navigation according to the navigation setting value; Step A3, calculate the turning angle radius of the unit distance indoor mobile robot navigation parameters based on the collected unit distance navigation starting point and target point information, and then obtain the real-time forward speed and direction change visualization chart; compare the real-time forward speed and direction change visualization chart with the preset forward speed and direction change visualization chart to determine and control the indoor mobile robot navigation parameters.

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