Indoor mobile robot navigation system and method based on BIM

Abstract

The invention discloses a BIM-based indoor mobile robot navigation system and method. The BIM-based indoor mobile robot navigation system comprises an edge computing gateway host analysis module, a navigation information storage and call list module, a man-machine interaction cloud analysis module and navigation parameter setting modules on different line change position deployment and control points, determining safe forward speed and direction according to the standard navigation position monitoring point, and determining whether navigation parameter control is needed or not based on the safe forward speed and direction; different steering angle radiuses are obtained by analyzing unit distance navigation starting point and target point information of different line change position distribution control points, and then real-time advancing speed and direction change visualization charts are obtained through arrangement, and navigation parameters to be regulated and controlled and control frequency are determined; the method is better in path smoothness, dynamic obstacle avoidance capability and adaptability, and an efficient and intelligent solution is provided for indoor navigation.

Description

Technical Field

[0001] The present invention relates to the field of indoor mobile robot navigation parameter control, and in particular to a BIM-based indoor mobile robot navigation system and method. 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. BIM models not only contain the geometric structure of buildings, but also integrate 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, visual sensors and map building technologies (such as SLAM) for positioning and path planning. However, these methods are often limited by the dynamic nature of the environment and the accuracy of sensor data, resulting in insufficient navigation accuracy or inefficient path planning. By combining BIM models, robots can understand detailed information about the interior of the building in advance, 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 preset maps. Autonomous navigation methods such as SLAM use lidar or visual sensors to build maps and locate in real time, but are limited by the accuracy of sensors and environmental interference. For example, lidar may fail in front of highly reflective materials, and visual 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 preset maps, such as two-dimensional plane maps, can provide more efficient path planning, but lack the ability to adapt to environmental changes. If there are dynamic obstacles or temporary changes in the building, such methods usually require frequent map updates, resulting in high maintenance costs and insufficient flexibility of the navigation system, and cannot achieve precise control of navigation parameters. Summary of the invention

[0004] In order to overcome the shortcomings and deficiencies of the prior art, the present invention proposes a BIM-based indoor mobile robot navigation system and method, which is used to solve the problem that the prior art needs to perform a large amount of data processing when controlling navigation parameters, and cannot reasonably determine the timing of navigation parameter control, and cannot achieve precise control of navigation parameters.

[0005] To achieve the above-mentioned object, the first aspect of the present invention provides a BIM-based indoor mobile robot navigation system, comprising 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; Navigation information storage and call list module: During the navigation operation of the indoor mobile robot at different line change positions, the navigation parameter setting module connected to it collects the unit distance navigation starting point and target point information of the unit distance indoor mobile robot navigation parameters, and transmits it to the edge computing gateway host analysis module; Edge computing gateway host analysis module: uses the BIM model module to collect the safe forward speed and direction of the control points at different line change positions, determines the real-time navigation forward speed and direction according to the path passability, and compares 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 continues according to the navigation setting value; and 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 real-time forward speed and direction change is drawn for different sizes of steering angle radius. The real-time visual chart of forward speed and direction change is compared and analyzed with the preset visual chart of forward speed and direction change to determine the navigation parameters of the controlled indoor mobile robot. The preset visual chart of forward speed and direction change is obtained using the BIM model module.

[0006] Furthermore, 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 and the navigation parameter setting module at different line change position control points transmit data bidirectionally; and the navigation parameter setting module matches different navigation stages of the unit distance indoor mobile robot navigation parameters.

[0007] Furthermore, 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 determine whether navigation parameter control is required, including: Connect the BIM model module and calculate the optimal path flatness within a unit distance of the standard navigation position control point; the control points of different line change positions have the same funds as the standard navigation position control points or contain the same indoor mobile robot navigation parameters; Obtain the navigation unit time forward speed and direction path flatness parameters of different optimal path flatness, recorded as safe forward speed and direction; obtain the optimal path flatness of the control points at different line change positions, recorded as 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.

[0008] Further, when it is determined that navigation parameter control needs to be performed on the control points at different route change positions, the navigation parameter setting module arranged at the control points at different route change positions collects and acquires the information of the navigation start point and target point of the unit distance; 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 include the three-dimensional coordinate data of all objects in the navigation space and the path flatness dynamic obstacle data.

[0009] Furthermore, 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: Extracting the path flatness dynamic obstacle data of the unit distance indoor mobile robot navigation parameters from the unit distance navigation starting point and target point information, and calculating the turning angle radius of the unit distance indoor mobile robot navigation parameters within the unit distance using the path flatness dynamic obstacle data; For different steering angle radius sizes, an independent variable is established according to the navigation position, and the steering angle radius size is used as the dependent variable to fit and draw the real-time forward speed and direction change visualization chart.

[0010] Furthermore, 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 the different standard navigation position control points by 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.

[0011] 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 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.

[0012] A second aspect of the present invention provides a BIM-based indoor mobile robot navigation system, comprising: Using the standard navigation position control points and the corresponding optimal path flatness recorded in the BIM model module, the safe forward speed and direction are obtained based on the navigation unit time forward speed and direction path flatness parameters of different optimal path flatnesses; Collect the real-time navigation forward speed and direction of the control 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 perform navigation parameter control on the control 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 setting value; The turning angle radius of the unit distance indoor mobile robot navigation parameters is calculated based on the collected unit distance navigation starting point and target point information, and then the real-time forward speed and direction change visualization chart is obtained; the real-time forward speed and direction change visualization chart is compared with the preset forward speed and direction change visualization chart to determine and control the indoor mobile robot navigation parameters.

[0013] Beneficial effects: The present invention proposes a navigation system and method for an indoor mobile robot based on BIM, determines the safe forward speed and direction according to the standard navigation position control point, determines whether navigation parameter control is required based on the safe forward speed and direction; obtains different turning angle radius sizes by analyzing the unit distance navigation starting point and target point information of different line change position control points, and then sorts out and obtains real-time forward speed and direction change visualization charts; compares the real-time forward speed and direction change visualization chart with the preset forward speed and direction change visualization chart obtained through the standard navigation position control point to determine the navigation parameters to be regulated and the control frequency; and then improves the navigation parameters. The present invention can not only determine which indoor mobile robot navigation parameters need to be adjusted by comparing the real-time forward speed and direction change visualization chart with the preset forward speed and direction change visualization chart, but also determine the adjustment range, speeding up the starting point and target point of navigation parameter control; and after completing the navigation parameters at different line change position control points, the relevant data can also be uploaded to the BIM model module to adjust the standard navigation position control points, which helps to improve the timeliness of navigation parameter control and make the efficiency of path flatness more reasonable, thereby ensuring the effective navigation. The BIM model provides accurate building geometry and spatial topology information, allowing robots to obtain global environmental 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 buildings, making it easier for robots to plan optimal paths and flexibly adapt to a variety of task requirements. In addition, combined with real-time sensor data, BIM can dynamically update the robot's understanding of the environment, effectively compensating for the limitations of sensors in complex or changing environments. The BIM-based navigation system performs better in path smoothness, dynamic obstacle avoidance and adaptability, while reducing map maintenance costs, providing an efficient and intelligent solution for indoor navigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the system module composition of the present invention; Figure 2 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION

[0015] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0016] like Figure 1As shown, the first embodiment of the present invention provides a BIM-based indoor mobile robot navigation system, 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; Navigation information storage and call list module: During the navigation operation of the indoor mobile robot at different line change positions, the navigation parameter setting module connected to it collects the unit distance navigation starting point and target point information of the unit distance indoor mobile robot navigation parameters, and transmits it to the edge computing gateway host analysis module; Edge computing gateway host analysis module: uses the BIM model module to collect the safe forward speed and direction of the control points at different line change positions, determines the real-time navigation forward speed and direction according to the path passability, and compares 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 continues according to the navigation setting value; and 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 real-time forward speed and direction change is drawn for different sizes of steering angle radius. The real-time visual chart of forward speed and direction change is compared and analyzed with the preset visual chart of forward speed and direction change to determine the navigation parameters of the controlled indoor mobile robot. The preset visual chart of forward speed and direction change is obtained using the BIM model module.

[0017] The navigation parameter control in the prior art mainly controls the various parameters of the navigation parameters, generally by comparing the path flatness dynamic obstacle data of the navigation parameters with the optimal real-time parameters for comparison and adjustment. However, this method is only effective for the control of a single navigation parameter, and the effect is not good when multiple navigation parameters need to be implemented in coordination. A particle swarm model can also be established based on the combination of the optimal parameters of the navigation parameters, and the particle swarm model is used to search in the constructed search space to complete the control of multiple navigation parameters. This method requires a lot of data preparation work, which affects the forward speed, direction and accuracy of the navigation parameter control.

[0018] The present invention application first determines the safe forward speed and direction according to the standard navigation position control points, and determines whether navigation parameter control is needed based on the safe forward speed and direction; obtains different turning angle radii by analyzing the unit distance navigation starting point and target point information of different line change position control points, and then compiles and obtains real-time forward speed and direction change visualization charts; compares the real-time forward speed and direction change visualization charts with the preset forward speed and direction change visualization charts obtained through the standard navigation position control points to determine the navigation parameters to be adjusted and the control frequency; reduces the data processing amount while ensuring the accuracy of navigation parameter control, thereby improving the navigation parameters.

[0019] In the application of the present invention, 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 the control points at different line change positions; and the navigation parameter setting module matches different navigation stages of the navigation parameters of the indoor mobile robot per unit distance.

[0020] 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 starting point and target point information of the control points at different line change positions, and interacts 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, forward speed, direction sensor, etc., which can be set next to the indoor mobile robot navigation parameters, and can be installed inside the indoor mobile robot navigation parameters if necessary.

[0021] In the application of the present invention, 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 judges whether navigation parameter control is needed based on the safe forward speed and direction, including: connecting the BIM model module, and calculating the optimal path flatness within the unit distance of the standard navigation position control point; obtaining the navigation unit time forward speed and direction path flatness parameters of different optimal path flatnesses, recorded as the safe forward speed and direction; collecting the optimal path flatness of the control points at different line change positions, recorded 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 needed for the control points at different line change positions; otherwise, it is determined that navigation parameter control is not needed for the control points at different line change positions.

[0022] After connecting the BIM model module, the optimal path flatness corresponding to different standard navigation position control points is obtained, and the safe forward speed and direction are determined based on the distribution characteristics of each optimal path flatness. If the real-time navigation forward speed and direction of the control points at different line change positions are less than the safe forward speed and direction, it can be understood that the overall path flatness of the control points at different line change positions is lower than the average level, or is not in the optimal state. At this moment, navigation parameter control is required.

[0023] The control points at different line change positions have the same funds as the control points at standard navigation positions or contain the same navigation parameters for indoor mobile robots. It is generally believed that the control points at different line change positions and the control points at standard navigation positions are exactly the same, that is, different navigation position control points with the same path flatness. The BIM model module can also be used as a data service platform established by the manufacturer immediately. It should be understood that after obtaining the optimal 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, and avoid the influence of extreme values ​​on the rationality of the safe forward speed and direction.

[0024] When it is determined that navigation parameter control is required for control points at different line change positions, the present invention application collects and obtains unit distance navigation starting point and target point information through a navigation parameter setting module set at control points at different line change positions; and the unit distance navigation starting point and target point information are screened and transmitted to the edge computing gateway host analysis module.

[0025] The screening of the unit distance navigation starting point and target point information mentioned here is mainly to remove outliers. 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. The standard implementation limit is the limit value of the operation of the indoor mobile robot navigation parameters, such as the smoothing factor limit value; the path flatness dynamic obstacle data is the ratio of the number of path flatness damages of the control points at different line change positions during operation to the total path flatness. 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 an early warning is issued in time. In the application of the present invention, the edge computing gateway host analysis module extracts the steering angle radius corresponding to the unit distance indoor mobile robot navigation parameters from the unit distance navigation starting point and target point information, and obtains real-time forward speed and direction change visualization charts based on different steering 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 based on the path flatness dynamic obstacle data; for different steering angle radii, independent variables are established according to the navigation position, and the steering angle radius is used as the dependent variable to fit to obtain a visual chart of the real-time forward speed and direction change.

[0026] Different indoor mobile robot navigation parameters are obtained by dividing the control points at different line change positions. The indoor mobile robot navigation parameters here are preferably navigation parameters that can be automatically adjusted in real time, so as to realize automatic control of navigation parameters through the edge computing gateway host analysis module. The turning angle radius of the indoor mobile robot navigation parameters per unit distance is calculated through the path flatness dynamic obstacle data, and the numbers are sorted from large to small, and then fitted to obtain a visual chart of real-time forward speed and direction changes. It should be understood that there is a linear or nonlinear relationship between the turning angle radius of the indoor mobile robot navigation parameters at the same navigation position control point.

[0027] The edge computing gateway host analysis module in the application of the present invention obtains a 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: based on the optimal path flatness, at least one standard navigation position control point is selected from different standard navigation position control points, and the corresponding unit distance navigation starting point and target point information is marked as the preset navigation starting point and target point information; the steering angle radius size of the unit distance indoor mobile robot navigation parameter 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 drawn for different preset path flatness steering angle radii according to the unit distance to obtain the preset forward speed and direction change visualization chart.

[0028] In order to improve the overall path smoothness of the control points at different line change positions, it is necessary to provide data reference for their navigation parameter control, that is, to reasonably select an optimal path smoothness from the BIM model module (generally better than the real-time navigation forward speed and direction of the control points at different line change positions), and mark the corresponding unit distance navigation starting point and target point information as the preset navigation starting point and target point information, so that the preset forward speed and direction change visualization chart can be obtained accordingly.

[0029] It is worth noting 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 indoor mobile robot navigation parameters per unit distance of the control points at different route change positions be improved, but also the real-time forward speed and direction of the indoor mobile robot navigation parameters per unit distance of the control points at different route change positions can be reasonably reduced when necessary; this adjustment method is suitable for scenarios where the control points at different route change positions need to be adjusted at any time.

[0030] The edge computing gateway host analysis module in the present invention 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 results, 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 the navigation parameters to be adjusted; determine the path flatness error of the navigation parameter to be adjusted based on 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.

[0031] When comparing the real-time forward speed and direction change visualization chart with the preset forward speed and direction change visualization chart, first determine which positions of the two do not overlap, and 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. The specific degree of adjustment of the navigation parameters to be adjusted is based on the error between the two change visualization charts.

[0032] like Figure 2 As shown, the second embodiment of the present invention provides a BIM-based indoor mobile robot navigation method, comprising: 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.

[0033] Working principle of the present invention: By using the standard navigation position control points and the corresponding optimal path flatness recorded in the BIM model module, the safe forward speed and direction are obtained based on the navigation unit time forward speed and direction path flatness parameters of different optimal path flatnesses.

[0034] Collect the real-time navigation speed and direction of the control points at different route change positions; compare the real-time navigation speed and direction with the safe 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.

[0035] The turning angle radius of the unit distance indoor mobile robot navigation parameters is calculated based on the collected unit distance navigation starting point and target point information, and then the real-time forward speed and direction change visualization chart is obtained; the real-time forward speed and direction change visualization chart is compared with the preset forward speed and direction change visualization chart to determine and control the indoor mobile robot navigation parameters.

[0036] 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 skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents 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.

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 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.

5. 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.

6. 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.

7. The BIM-based indoor mobile robot navigation system according to any one of claims 1 to 6, 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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