Navigation control method, device and equipment of robot and medium

Abstract

The invention discloses a navigation control method, device and equipment for a robot and a medium, and the method comprises the steps: obtaining working environment data obtained through scanning of a first laser radar module in the robot, and constructing an environment map based on the working environment data; generating a global motion path according to the environment map and a preset target point, and taking the global motion path as a current motion path; the motion state of the robot is controlled according to the current motion path, first ranging data, obstacle data and second ranging data obtained through current scanning of the robot and a motion control strategy; wherein the first ranging data is data obtained by scanning a floor boundary by the first laser radar module, the obstacle data is data obtained by scanning a dynamic obstacle by the auxiliary obstacle avoidance module, and the second ranging data is data obtained by scanning a floor ground by the second laser radar module. The collision and falling risks of the robot can be avoided, and the safety of the robot is improved.

Description

Technical Field

[0001] The present invention relates to the field of positioning and navigation technology, and in particular to a navigation control method, device, equipment and medium for a robot. Background Art

[0002] In the current prefabricated building construction process, a large number of lightweight strips are used for the assembly of exterior walls. For example, the on-site assembly of the currently widely used autoclaved aerated concrete panels (ALC strips) requires adjusting the strips from horizontal sideways to vertical upright positions, transporting the strips to the installation location, adjusting the positions with the adjacent strips, and finally completing the slurry squeezing of the joints between the strips. At present, on-site construction generally uses manual labor or auxiliary equipment to achieve the installation of strips, but due to the large size and weight of the strips, it generally requires 5 to 7 people to complete the lifting and adjustment of the strips. Therefore, the manual installation of strips has problems such as high labor intensity, low efficiency and high installation risks.

[0003] Therefore, the market urgently needs an exterior wall panel installation robot to reduce manual labor and improve work efficiency. However, the current exterior wall panel installation robots have two major problems in the operation process: first, due to the complex exterior wall installation environment, there may be a risk of human error causing the robot to collide; second, there may be a risk of collision and fall when the robot approaches the floor structure boundary. Summary of the invention

[0004] The embodiments of the present invention provide a navigation control method, device, equipment and medium for a robot, aiming to solve the problem in the prior art that exterior wall panel installation robots are prone to collision risks and falling risks in complex construction environments.

[0005] In a first aspect, an embodiment of the present invention provides a navigation control method of a robot, comprising: Acquire working environment data scanned by a first laser radar module in the robot, and construct an environment map based on the working environment data; Generate a global motion path according to the environment map and the preset target point, and use the global motion path as the current motion path; Acquire the first ranging data, obstacle data, and second ranging data currently scanned by the robot; wherein the first ranging data is data obtained by the first laser radar module scanning the floor boundary, the obstacle data is data obtained by the auxiliary obstacle avoidance module in the robot scanning the dynamic obstacles, and the second ranging data is data obtained by the second laser radar module in the robot scanning the floor; The motion state of the robot is controlled according to the current motion path, the first distance measurement data, the obstacle data, the second distance measurement data and a preset motion control strategy.

[0006] In a second aspect, an embodiment of the present invention provides a navigation control device for a robot, comprising: A map construction unit, used to obtain working environment data scanned by a first laser radar module in the robot, and to construct an environment map based on the working environment data; A path generation unit, used to generate a global motion path according to the environment map and a preset target point, and use the global motion path as a current motion path; A data acquisition unit, used to acquire first ranging data, obstacle data, and second ranging data currently scanned by the robot; wherein the first ranging data is data obtained by the first laser radar module scanning the floor boundary, the obstacle data is data obtained by the auxiliary obstacle avoidance module in the robot scanning the dynamic obstacles, and the second ranging data is data obtained by the second laser radar module in the robot scanning the floor; A motion control unit is used to control the motion state of the robot according to the current motion path, the first distance measurement data, the obstacle data, the second distance measurement data and a preset motion control strategy.

[0007] In a third aspect, an embodiment of the present invention provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the navigation control method of the robot described in the first aspect when executing the computer program.

[0008] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor causes the processor to execute the navigation control method of the robot described in the first aspect above.

[0009] The embodiment of the present invention provides a navigation control method, device, equipment and medium of a robot, the method comprising obtaining working environment data scanned by a first laser radar module in the robot, and constructing an environment map based on the working environment data; generating a global motion path according to the environment map and a preset target point, and using the global motion path as the current motion path; according to the current motion path, the first ranging data, obstacle data and second ranging data currently scanned by the robot, and the motion control strategy control the motion state of the robot; wherein the first ranging data is data obtained by the first laser radar module scanning the floor boundary, the obstacle data is data obtained by the auxiliary obstacle avoidance module scanning the dynamic obstacle, and the second ranging data is data obtained by the second laser radar module scanning the floor. The present invention can enable the robot to avoid collision and falling risks and improve the safety of the robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0011] Figure 1 A schematic flow chart of a navigation control method for a robot provided by an embodiment of the present invention; Figure 2 A schematic block diagram of a navigation control device for a robot provided in one embodiment of the present invention; Figure 3 A schematic block diagram of a computer device provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0012] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not 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.

[0013] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0014] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0015] It should be further understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0016] See also Figure 1 The robot navigation control method provided by the embodiment of the present invention includes steps S11 to S14, wherein the robot specifically refers to an exterior wall panel installation robot.

[0017] S11. Acquire working environment data scanned by a first laser radar module in the robot, and construct an environment map based on the working environment data.

[0018] In this embodiment, the robot is provided with a first laser radar module, which is located on the front end surface of the robot chassis. The first laser radar module is used to scan the floor boundary to obtain the distance information between the robot and the floor boundary, wherein the floor boundary includes static obstacles and environmental boundaries (such as floor walls). Specifically, the user controls the robot through the remote control terminal to first circle around the boundary of the working environment space for scanning, and then moves to the unscanned space for focused scanning. During this movement, the robot completes the scanning of the working environment information through the first laser radar module, and uses the scanning data of the first laser radar module in this process as the working environment data, and then constructs an environmental map based on the working environment data, so as to facilitate the subsequent planning of the robot's movement path and accurately locate the robot's position in the working environment space.

[0019] Furthermore, the first laser radar module includes two laser radars, which are respectively located on the left and right sides of the front end surface of the chassis of the robot, and the working environment data includes scanning data obtained by the two laser radars. When executing the step of constructing an environment map based on the working environment data, the following steps are specifically included: (1) For the scanning data obtained by each laser radar, invalid points in the scanning data are filtered out, and the filtered scanning data is preprocessed; wherein the data preprocessing is to synchronize the timestamps of the scanning data of the two laser radars by interpolation or time alignment. (2) The preprocessed scanning data corresponding to the two laser radars are converted to the same coordinate system, wherein the same coordinate system can be a three-dimensional coordinate system in a Cartesian coordinate system. (3) The scanning data corresponding to the two laser radars converted to the same coordinate system are fused, and the fused data are de-noised and filtered to obtain the target environment data. (4) The environment map is constructed based on the target environment data and a preset synchronous positioning and mapping algorithm. wherein the synchronous positioning and mapping algorithm can adopt the Cartographer algorithm, which is based on an optimized laser SLAM algorithm and can construct a large-scale map in real time.

[0020] In one embodiment, before step S11, it also includes: initializing the robot system, and starting the first laser radar module, the auxiliary obstacle avoidance module and the second laser radar module. Specifically, during initialization, the robot is first mechanically inspected to confirm that the mechanical structure is firm, the wiring of each part is correct, the equipment is sufficiently charged, and there are no safety hazards. After connecting the power supply, check whether there are any functional and hardware connection abnormalities. If there are no abnormalities after the inspection, the robot is connected to the remote control terminal and the robot enters the working state. If there are abnormalities in the inspection, the fault is manually troubleshooted. Next, the first laser radar module, the auxiliary obstacle avoidance module and the second laser radar module are set, specifically, the first laser radar module, the auxiliary obstacle avoidance module and the second laser radar module are set to appropriate scanning angles, scanning ranges, working serial ports and baud rates, respectively, to ensure the stability and accuracy of the scanned data, and ensure normal data transmission.

[0021] S12: Generate a global motion path according to the environment map and a preset target point, and use the global motion path as a current motion path.

[0022] In this embodiment, global path planning is performed based on the environment map and the preset target point, and a motion path is preliminarily planned for the robot, thereby generating a global motion path, and the global motion path is used as the current motion path, so as to facilitate the subsequent control of the robot to move to the target point along the current motion path. Specifically, the global path planning can use the A* algorithm, which is a heuristic path search algorithm. The algorithm evaluates each search position in the state space, and after obtaining the current best position, searches from this position until the final target point is reached, and obtains a preliminary global optimal route, that is, the global motion path.

[0023] S13. Obtain the first ranging data, obstacle data and second ranging data currently scanned by the robot; wherein the first ranging data is data obtained by the first laser radar module scanning the floor boundary, the obstacle data is data obtained by the auxiliary obstacle avoidance module in the robot scanning the dynamic obstacles, and the second ranging data is data obtained by the second laser radar module in the robot scanning the floor.

[0024] S14. Control the motion state of the robot according to the current motion path, the first distance measurement data, the obstacle data, the second distance measurement data and a preset motion control strategy.

[0025] In this embodiment, the robot is provided with a first laser radar module, an auxiliary obstacle avoidance module and a second laser radar module. The first laser radar module is located on the front end surface of the robot chassis, and is used to scan the floor boundary to obtain the distance information between the robot and the floor boundary; the multiple auxiliary obstacle avoidance sensors in the auxiliary obstacle avoidance module are distributed around the robot chassis, and the auxiliary obstacle avoidance module scans the dynamic obstacles in the working environment space to detect whether there are dynamic obstacles, and obtains the distance information between the robot and the dynamic obstacles, thereby avoiding the robot from colliding with the dynamic obstacles; the second laser radar module is located in the center of the robot chassis, and is used to scan the floor to detect whether there are dynamic obstacles on the floor. The first ranging data, obstacle data and second ranging data currently scanned by the robot are acquired in real time, and the motion state of the robot is controlled according to the current motion path, the first ranging data, the obstacle data, the second ranging data and the preset motion control strategy, that is, the motion state of the robot is controlled by combining the current motion path with the corresponding information of floor boundaries, dynamic obstacles and floor surfaces in a complex construction environment detected in real time, thereby realizing autonomous navigation and preventing the robot from the risk of accidents caused by being too close to floor boundaries and dynamic obstacles or approaching empty areas without floor surfaces during operation, thereby ensuring the safe operation of the robot and greatly improving the safety and stability of the robot's operation.

[0026] In one embodiment, step S14 includes: If the dynamic obstacle is not detected according to the obstacle data, and the floor edge is not detected according to the second distance measurement data, then obtaining the distance between the robot and the floor boundary according to the first distance measurement data and using it as the current edge distance, and adjusting the driving speed of the robot along the current motion path based on the current edge distance; If the dynamic obstacle is detected according to the obstacle data, a local motion path is generated according to the obstacle data and the current motion path, the current motion path is updated using the local motion path, and the step of obtaining the first ranging data, obstacle data, and second ranging data currently scanned by the robot is returned to be executed; If the floor edge is detected according to the second ranging data, the robot is controlled to stop moving.

[0027] In this embodiment, if no dynamic obstacle is detected according to the obstacle data and no floor edge is detected according to the second ranging data, it means that the robot is not close to a dynamic obstacle and is not close to an empty area without a floor at its current position during the movement. Then, the distance between the robot and the floor boundary is obtained according to the first ranging data, and the distance between the robot and the floor boundary is used as the current edge distance. The driving speed of the robot along the current motion path is adjusted based on the current edge distance. By accurately judging the distance between the robot's own position and the floor boundary to control the robot's driving speed, the safe operation of the robot can be ensured, the risk of collision that may occur when the robot approaches the floor boundary can be reduced, and construction safety can be further ensured.

[0028] If a dynamic obstacle is detected according to the obstacle data, it means that a dynamic obstacle appears in the working environment space, and the robot is close to the dynamic obstacle at the current position during the movement. Then, a local movement path is generated according to the obstacle data and the current movement path, and a local path planning is performed for the dynamic obstacle. The local movement path is the optimal path closest to the current movement path. The current movement path is updated using the local movement path, and the robot returns to execute step S13, thereby controlling the robot to move along the updated path to avoid the dynamic obstacle, thereby avoiding the robot from colliding with the dynamic obstacle. Further, the local path planning can adopt the TEB algorithm, which is an obstacle avoidance idea based on the elastic band collision constraint theory, and can enable the robot to avoid dynamic obstacles in real time during the movement. When performing local path planning according to the obstacle data and the current movement path, specifically, time constraints, speed constraints and collision constraints are added to the current movement path according to the obstacle data, and an optimization problem is constructed, and then the optimization problem is solved to obtain an optimal feasible path as the local movement path.

[0029] If the edge of the floor is detected according to the second distance measurement data, it means that the robot is approaching an empty area without a floor when it is currently in motion, and then a stop command is triggered to control the robot to stop moving immediately, thereby avoiding the risk of the robot falling when it approaches the edge of the floor. After the stop command is triggered, the robot can also enter a preset safety mode to keep the robot in a stopped state to prevent accidental movement due to inertial sliding. At the same time, an alarm mechanism can also be activated to notify the operator that there is a risk of falling in the area.

[0030] In one embodiment, obtaining the distance between the robot and the floor boundary according to the first distance measurement data and using it as the current edge distance, and adjusting the driving speed of the robot along the current motion path based on the current edge distance, includes: Processing the first distance measurement data to obtain a floor fitting boundary; Obtaining the current position of the robot according to the first ranging data and the environment map, and calculating the current edge distance according to the current position and the floor fitting boundary; The current edge distance is matched with at least one preset distance interval to obtain a target distance interval to which the current edge distance belongs, and the driving speed of the robot along the current motion path is adjusted according to the target distance interval.

[0031] In this embodiment, the first distance measurement data is first processed to obtain a floor fitting boundary, which reflects the position and shape of the floor boundary in front of the robot. Then, the current position of the robot is accurately located based on the first distance measurement data and the environment map collected in real time. The current position and the floor fitting boundary are in the same coordinate system. The current edge distance is obtained by geometrically calculating the current position and the floor fitting boundary, that is, the distance between the robot and the floor boundary is accurately obtained. Then, the current edge distance is matched with at least one preset distance interval to obtain the target distance interval to which the current edge distance belongs, so as to adjust the driving speed of the robot along the current motion path according to the target distance interval. During the robot movement, different driving limit controls are used according to the different distances between the robot and the floor boundary to ensure the safe walking of the robot near the floor boundary and avoid the risk of collision between the robot and the floor boundary.

[0032] In one embodiment, matching the current edge distance with at least one preset distance interval to obtain a target distance interval to which the current edge distance belongs, and adjusting the driving speed of the robot along the current motion path according to the target distance interval includes: If it is determined that the target distance interval is the first preset distance interval, the driving speed of the robot is adjusted to a preset normal speed to control the robot to move at a uniform speed along the current motion path; wherein the first preset distance interval is (d1, +∞), and d1 is a first preset distance; If it is determined that the target distance interval is the second preset distance interval, the driving speed of the robot is reduced to a preset safety speed to control the robot to perform deceleration movement along the current motion path; wherein the second preset distance interval is [d2, d1], and d2 is the second preset distance; If it is determined that the target distance interval is the third preset distance interval, the robot is controlled to stop moving; wherein the third preset distance interval is [0, d2).

[0033] In this embodiment, if the target distance interval to which the current edge distance belongs is the first preset distance interval, that is, the current edge distance is greater than the first preset distance, indicating that the robot is not close to the floor boundary, the robot's driving speed is adjusted to the preset normal speed, so that the robot moves at a uniform speed along the current motion path, even if the robot maintains normal motion along the current motion path. If the target distance interval to which the current edge distance belongs is the second preset distance interval, that is, the current edge distance is less than or equal to the first preset distance and greater than or equal to the second preset distance, indicating that the robot is already close to the floor boundary, the deceleration instruction is triggered to reduce the robot's driving speed to the preset safety speed, so that the robot moves at a decelerated speed along the current motion path, so that the robot has a higher safety redundancy when approaching the floor boundary. If the target distance interval to which the current edge distance belongs is the third preset distance interval, that is, the current edge distance is less than the second preset distance, indicating that the robot is already very close to the floor boundary, the robot is immediately controlled to stop moving to prevent the robot from accidentally touching the floor boundary. Preferably, the first preset distance can be set to 1.5 meters, and the second preset distance can be set to 300 mm.

[0034] In one embodiment, the processing the first ranging data to obtain a floor fitting boundary includes: Acquire initial ranging data of the first laser radar module, and obtain a distance reference value according to the initial ranging data and preset floor boundary characteristic parameters; Performing filtering and fusion processing on the first ranging data to obtain fused ranging data; Filtering the fused distance measurement data based on the distance reference value to obtain first target distance measurement data; Performing fitting processing on the first target ranging data to obtain an initial fitting boundary; The characteristic parameters of the initial fitting boundary are acquired, and the floor fitting boundary is obtained by screening the initial fitting boundary according to the characteristic parameters.

[0035] In this embodiment, the initial ranging data of the first laser radar module is obtained, and the initial ranging data is the data obtained by scanning the first laser radar module when the robot is in the reference position. The deviation of the initial ranging data is corrected according to the preset floor boundary characteristic parameters to obtain the distance reference value. Among them, the floor boundary characteristic parameters include the height, material, shape, etc. of the floor boundary. If the height of the floor boundary is different, the data returned by the first laser radar module will change. It is necessary to record the average height of different areas of the floor boundary to correct the ranging deviation of the first laser radar module. In addition, for each laser radar in the first laser radar module, it is necessary to set the corresponding independent reference value to form the distance reference value to ensure the accuracy of multi-sensor ranging. Kalman filtering is used to smooth the first ranging data to remove sudden noise and outliers, thereby reducing the ranging fluctuation caused by environmental changes and laser reflections, and ensuring the continuity and stability of the data. And on the basis of the filtered first ranging data, the first ranging data points are mapped to a unified two-dimensional plane for fusion processing to obtain fused ranging data. Based on the distance reference value, the fused ranging data is screened to obtain the first target ranging data, and the data with a large deviation from the distance reference value in the fused ranging data is removed, and the invalid ranging data in the fused ranging data, such as invalid ranging data from the protruding parts of the building or the reflection of small objects, is eliminated to ensure the accuracy of the data. According to the error between the ranging data in the first target ranging data, a suitable fitting algorithm is determined, and the first target ranging data obtained after screening is fitted using a suitable fitting algorithm to identify and fit the straight line structure of the floor boundary to obtain the initial fitting boundary. For the first target distance measurement data with small errors between the distance measurement data, the least square method is used for linear fitting to minimize the total error from the laser point to the fitting line, and a smooth initial fitting boundary is obtained; for the first target distance measurement data with large errors between the distance measurement data, that is, there is a lot of noise or interference in the working environment, the RANSAC (Random Sample Consensus) algorithm is used to randomly sample a group of laser points, and through multiple iterations, it is determined whether it conforms to the floor boundary form, and abnormal points (such as corners or protruding obstacles) are removed to achieve a robust fitting of the boundary. The initial fitting boundary is screened according to the characteristic parameters of the initial fitting boundary, and the validity of the line segments in the initial fitting boundary is further verified, so as to automatically select the line segments that fit the real contour of the floor boundary as the floor fitting boundary, so as to calculate the distance between the robot and the floor boundary. Among them, the characteristic parameters include length, angle, etc.

[0036] In one embodiment, detecting the floor edge according to the second ranging data includes: If it is determined according to the second ranging data that the floor area in front of the robot is an empty area, the robot is controlled to start a preset secondary scanning confirmation mode, and a scanning data set obtained by the robot in the secondary scanning confirmation mode is obtained; If it is determined that the floor area in front of the robot is an empty area according to each set of scanning data in the scanning data set, it is determined that the floor edge is detected.

[0037] In this embodiment, the second ranging data is preprocessed. Specifically, the second ranging data is first filtered to remove noise, and then the filtered data is smoothed to reduce misjudgment caused by short-term jitter. At the same time, by calculating the difference between data points, abnormal data with significant differences from surrounding data is screened out, thereby preprocessing the second ranging data. The preprocessed second ranging data is used to determine whether the floor area in front of the robot is an empty area. The preprocessed second ranging data is analyzed. If it is detected that there are multiple consecutive ranging data that significantly increase or lose signals in the second ranging data, it means that the floor area in front of the robot is preliminarily determined to be an empty area. In order to reduce the risk of misjudgment, the robot is controlled to start the preset secondary scanning confirmation mode, so that the robot repeatedly scans the same position multiple times. The scanning data set obtained by the robot in the secondary scanning confirmation mode is obtained. If it is determined that the floor area in front of the robot is an empty area according to each set of scanning data in the scanning data set, it is determined that the floor edge is detected, ensuring the accuracy of the detection.

[0038] In one embodiment, the failure to detect the floor edge according to the second ranging data includes: If it is determined according to the second ranging data that the floor area in front of the robot is not an empty area, or if it is determined according to at least one set of scanning data in the scanning data set that the floor area in front of the robot is not an empty area, it is determined that the floor edge is not detected.

[0039] In this embodiment, the pre-processed second ranging data is analyzed, and if no significant increase or loss of signal of multiple consecutive ranging data is detected in the second ranging data, it is determined that the floor area in front of the robot is not an empty area, and it is determined that the floor edge is not detected at this time. In addition, after the floor area in front of the robot is initially determined to be an empty area and the robot is controlled to start the preset secondary scanning confirmation mode, if it is determined that the floor area in front of the robot is not an empty area based on at least one set of scanning data of the scanning data set obtained by the robot in the secondary scanning confirmation mode, it is also determined that the floor edge is not detected at this time.

[0040] The navigation control method of the robot provided in an embodiment of the present invention uses a first laser radar module, an auxiliary obstacle avoidance module and a second laser radar module to respectively scan the floor boundaries, dynamic obstacles and floor surfaces in a complex construction environment, and then controls the movement state of the robot in combination with the current motion path and the information corresponding to the floor boundaries, dynamic obstacles and floor surfaces detected in real time, thereby realizing autonomous navigation and preventing the robot from colliding and falling due to being too close to floor boundaries and dynamic obstacles or approaching empty areas without floor surfaces during operation, thereby improving the safety of the robot.

[0041] The embodiment of the present invention further provides a navigation control device for a robot, the navigation control device for the robot is used to execute any embodiment of the navigation control method for the robot described above. Figure 2 , Figure 2 This is a schematic block diagram of a navigation control device for a robot provided in an embodiment of the present invention. The navigation control device for a robot provided in an embodiment of the present invention includes a map construction unit 11, a path generation unit 12, a data acquisition unit 13 and a motion control unit 14.

[0042] The map construction unit 11 is used to obtain the working environment data scanned by the first laser radar module in the robot, and construct an environment map based on the working environment data.

[0043] In this embodiment, the robot is provided with a first laser radar module, which is located on the front end surface of the robot chassis. The first laser radar module is used to scan the floor boundary to obtain the distance information between the robot and the floor boundary, wherein the floor boundary includes static obstacles and environmental boundaries (such as floor walls). Specifically, the user controls the robot through the remote control terminal to first circle around the boundary of the working environment space for scanning, and then moves to the unscanned space for focused scanning. During this movement, the robot completes the scanning of the working environment information through the first laser radar module, and uses the scanning data of the first laser radar module in this process as the working environment data, and then constructs an environmental map based on the working environment data, so as to facilitate the subsequent planning of the robot's movement path and accurately locate the robot's position in the working environment space.

[0044] Furthermore, the first laser radar module includes two laser radars, which are respectively located on the left and right sides of the front end surface of the chassis of the robot, and the working environment data includes the scanning data obtained by the two laser radars. When the map construction unit 11 executes the step of constructing the environment map based on the working environment data, it specifically includes the following steps: (1) for the scanning data obtained by each laser radar, filter out invalid points in the scanning data, and perform data preprocessing on the filtered scanning data; wherein the data preprocessing is to synchronize the timestamps of the scanning data of the two laser radars by interpolation or time alignment. (2) convert the preprocessed scanning data corresponding to the two laser radars to the same coordinate system, wherein the same coordinate system can be a three-dimensional coordinate system in a Cartesian coordinate system. (3) perform data fusion on the scanning data corresponding to the two laser radars converted to the same coordinate system, and remove noise and filter the fused data to obtain the target environment data. (4) construct the environment map based on the target environment data and the preset synchronous positioning and mapping algorithm. Among them, the simultaneous positioning and mapping algorithm can adopt the Cartographer algorithm, which is based on the optimized laser SLAM algorithm and can build large-scale maps in real time.

[0045] In one embodiment, the navigation control device of the robot provided in the embodiment of the present invention further includes an initialization unit. Before the map construction unit 11 executes the step of obtaining the working environment data scanned by the first laser radar module in the robot and constructing the environment map based on the working environment data, the initialization unit is specifically used to: initialize the robot system, and start the first laser radar module, the auxiliary obstacle avoidance module and the second laser radar module. Specifically, during initialization, the robot is first inspected for mechanical structure to confirm that the mechanical structure is firm, the wiring of each part is correct, the equipment has sufficient power, and there are no safety hazards. After connecting the power supply, check whether there are functional and hardware connection abnormalities. If there is no abnormality after the inspection, the robot is connected to the remote control terminal and the robot enters the working state. If there is an abnormality in the inspection, the fault is manually eliminated. Next, the first laser radar module, the auxiliary obstacle avoidance module and the second laser radar module are set, specifically, the first laser radar module, the auxiliary obstacle avoidance module and the second laser radar module are set to appropriate scanning angles, scanning ranges, working serial ports and baud rates respectively to ensure the stability and accuracy of the scanned data and ensure normal data transmission.

[0046] The path generation unit 12 is used to generate a global motion path according to the environment map and a preset target point, and use the global motion path as a current motion path.

[0047] In this embodiment, global path planning is performed based on the environment map and the preset target point, and a motion path is preliminarily planned for the robot, thereby generating a global motion path, and the global motion path is used as the current motion path, so as to facilitate the subsequent control of the robot to move to the target point along the current motion path. Specifically, the global path planning can use the A* algorithm, which is a heuristic path search algorithm. The algorithm evaluates each search position in the state space, and after obtaining the current best position, searches from this position until the final target point is reached, and obtains a preliminary global optimal route, that is, the global motion path.

[0048] The data acquisition unit 13 is used to acquire the first ranging data, obstacle data and second ranging data currently scanned by the robot; wherein the first ranging data is the data obtained by the first laser radar module scanning the floor boundary, the obstacle data is the data obtained by the auxiliary obstacle avoidance module in the robot scanning the dynamic obstacles, and the second ranging data is the data obtained by the second laser radar module in the robot scanning the floor.

[0049] The motion control unit 14 is used to control the motion state of the robot according to the current motion path, the first distance measurement data, the obstacle data, the second distance measurement data and a preset motion control strategy.

[0050] In this embodiment, the robot is provided with a first laser radar module, an auxiliary obstacle avoidance module and a second laser radar module. The first laser radar module is located on the front end surface of the robot chassis, and is used to scan the floor boundary to obtain the distance information between the robot and the floor boundary; the multiple auxiliary obstacle avoidance sensors in the auxiliary obstacle avoidance module are distributed around the robot chassis, and the auxiliary obstacle avoidance module scans the dynamic obstacles in the working environment space to detect whether there are dynamic obstacles, and obtains the distance information between the robot and the dynamic obstacles, thereby avoiding the robot from colliding with the dynamic obstacles; the second laser radar module is located in the center of the robot chassis, and is used to scan the floor to detect whether there are dynamic obstacles on the floor. The first ranging data, obstacle data and second ranging data currently scanned by the robot are acquired in real time, and the motion state of the robot is controlled according to the current motion path, the first ranging data, the obstacle data, the second ranging data and the preset motion control strategy, that is, the motion state of the robot is controlled by combining the current motion path with the corresponding information of floor boundaries, dynamic obstacles and floor surfaces in a complex construction environment detected in real time, thereby realizing autonomous navigation and preventing the robot from the risk of accidents caused by being too close to floor boundaries and dynamic obstacles or approaching empty areas without floor surfaces during operation, thereby ensuring the safe operation of the robot and greatly improving the safety and stability of the robot's operation.

[0051] In one embodiment, the motion control unit 14 is specifically used for: If the dynamic obstacle is not detected according to the obstacle data, and the floor edge is not detected according to the second distance measurement data, then obtaining the distance between the robot and the floor boundary according to the first distance measurement data and using it as the current edge distance, and adjusting the driving speed of the robot along the current motion path based on the current edge distance; If the dynamic obstacle is detected according to the obstacle data, a local motion path is generated according to the obstacle data and the current motion path, the current motion path is updated using the local motion path, and the step of obtaining the first ranging data, obstacle data, and second ranging data currently scanned by the robot is returned to be executed; If the floor edge is detected according to the second ranging data, the robot is controlled to stop moving.

[0052] In this embodiment, if no dynamic obstacle is detected according to the obstacle data and no floor edge is detected according to the second ranging data, it means that the robot is not close to a dynamic obstacle and is not close to an empty area without a floor at its current position during the movement. Then, the distance between the robot and the floor boundary is obtained according to the first ranging data, and the distance between the robot and the floor boundary is used as the current edge distance. The driving speed of the robot along the current motion path is adjusted based on the current edge distance. By accurately judging the distance between the robot's own position and the floor boundary to control the robot's driving speed, the safe operation of the robot can be ensured, the risk of collision that may occur when the robot approaches the floor boundary can be reduced, and construction safety can be further ensured.

[0053] If a dynamic obstacle is detected according to the obstacle data, it means that a dynamic obstacle appears in the working environment space, and the robot is close to the dynamic obstacle at the current position during the movement. Then, a local movement path is generated according to the obstacle data and the current movement path, and a local path planning is performed for the dynamic obstacle. The local movement path is the optimal path closest to the current movement path. The current movement path is updated using the local movement path, and the step of obtaining the first ranging data, obstacle data and second ranging data currently scanned by the robot is returned to execute, so as to control the robot to move along the updated path to avoid the dynamic obstacle and avoid the robot from colliding with the dynamic obstacle. Further, the local path planning can adopt the TEB algorithm, which is an obstacle avoidance idea based on the elastic band collision constraint theory, and can enable the robot to avoid dynamic obstacles in real time during the movement. When the local path planning is performed according to the obstacle data and the current movement path, the time constraint, speed constraint and collision constraint are specifically added to the current movement path according to the obstacle data, and an optimization problem is constructed, and then the optimization problem is solved to obtain an optimal feasible path as the local movement path.

[0054] If the edge of the floor is detected according to the second distance measurement data, it means that the robot is approaching an empty area without a floor when it is currently in motion, and then a stop command is triggered to control the robot to stop moving immediately, thereby avoiding the risk of the robot falling when it approaches the edge of the floor. After the stop command is triggered, the robot can also enter a preset safety mode to keep the robot in a stopped state to prevent accidental movement due to inertial sliding. At the same time, an alarm mechanism can also be activated to notify the operator that there is a risk of falling in the area.

[0055] In one embodiment, when the motion control unit 14 executes the step of obtaining the distance between the robot and the floor boundary according to the first distance measurement data and using the distance as the current edge distance, and adjusting the driving speed of the robot along the current motion path based on the current edge distance, it is specifically configured to: Processing the first distance measurement data to obtain a floor fitting boundary; Obtaining the current position of the robot according to the first ranging data and the environment map, and calculating the current edge distance according to the current position and the floor fitting boundary; The current edge distance is matched with at least one preset distance interval to obtain a target distance interval to which the current edge distance belongs, and the driving speed of the robot along the current motion path is adjusted according to the target distance interval.

[0056] In this embodiment, the first distance measurement data is first processed to obtain a floor fitting boundary, which reflects the position and shape of the floor boundary in front of the robot. Then, the current position of the robot is accurately located based on the first distance measurement data and the environment map collected in real time. The current position and the floor fitting boundary are in the same coordinate system. The current edge distance is obtained by geometrically calculating the current position and the floor fitting boundary, that is, the distance between the robot and the floor boundary is accurately obtained. Then, the current edge distance is matched with at least one preset distance interval to obtain the target distance interval to which the current edge distance belongs, so as to adjust the driving speed of the robot along the current motion path according to the target distance interval. During the robot movement, different driving limit controls are used according to the different distances between the robot and the floor boundary to ensure the safe walking of the robot near the floor boundary and avoid the risk of collision between the robot and the floor boundary.

[0057] In one embodiment, when the motion control unit 14 performs the step of matching the current edge distance with at least one preset distance interval to obtain the target distance interval to which the current edge distance belongs, and adjusting the driving speed of the robot along the current motion path according to the target distance interval, it is specifically used to: If it is determined that the target distance interval is the first preset distance interval, the driving speed of the robot is adjusted to a preset normal speed to control the robot to move at a uniform speed along the current motion path; wherein the first preset distance interval is (d1, +∞), and d1 is a first preset distance; If it is determined that the target distance interval is the second preset distance interval, the driving speed of the robot is reduced to a preset safety speed to control the robot to perform deceleration movement along the current motion path; wherein the second preset distance interval is [d2, d1], and d2 is the second preset distance; If it is determined that the target distance interval is the third preset distance interval, the robot is controlled to stop moving; wherein the third preset distance interval is [0, d2).

[0058] In this embodiment, if the target distance interval to which the current edge distance belongs is the first preset distance interval, that is, the current edge distance is greater than the first preset distance, indicating that the robot is not close to the floor boundary, the robot's driving speed is adjusted to the preset normal speed, so that the robot moves at a uniform speed along the current motion path, even if the robot maintains normal motion along the current motion path. If the target distance interval to which the current edge distance belongs is the second preset distance interval, that is, the current edge distance is less than or equal to the first preset distance and greater than or equal to the second preset distance, indicating that the robot is already close to the floor boundary, the deceleration instruction is triggered to reduce the robot's driving speed to the preset safety speed, so that the robot moves at a decelerated speed along the current motion path, so that the robot has a higher safety redundancy when approaching the floor boundary. If the target distance interval to which the current edge distance belongs is the third preset distance interval, that is, the current edge distance is less than the second preset distance, indicating that the robot is already very close to the floor boundary, the robot is immediately controlled to stop moving to prevent the robot from accidentally touching the floor boundary. Preferably, the first preset distance can be set to 1.5 meters, and the second preset distance can be set to 300 mm.

[0059] In one embodiment, when the motion control unit 14 executes the step of processing the first ranging data to obtain the floor fitting boundary, it is specifically used to: Acquire initial ranging data of the first laser radar module, and obtain a distance reference value according to the initial ranging data and preset floor boundary characteristic parameters; Performing filtering and fusion processing on the first ranging data to obtain fused ranging data; Filtering the fused distance measurement data based on the distance reference value to obtain first target distance measurement data; Performing fitting processing on the first target ranging data to obtain an initial fitting boundary; The characteristic parameters of the initial fitting boundary are acquired, and the floor fitting boundary is obtained by screening the initial fitting boundary according to the characteristic parameters.

[0060] In this embodiment, the initial ranging data of the first laser radar module is obtained, and the initial ranging data is the data obtained by scanning the first laser radar module when the robot is in the reference position. The deviation of the initial ranging data is corrected according to the preset floor boundary characteristic parameters to obtain the distance reference value. Among them, the floor boundary characteristic parameters include the height, material, shape, etc. of the floor boundary. If the height of the floor boundary is different, the data returned by the first laser radar module will change. It is necessary to record the average height of different areas of the floor boundary to correct the ranging deviation of the first laser radar module. In addition, for each laser radar in the first laser radar module, it is necessary to set the corresponding independent reference value to form the distance reference value to ensure the accuracy of multi-sensor ranging. Kalman filtering is used to smooth the first ranging data to remove sudden noise and outliers, thereby reducing the ranging fluctuation caused by environmental changes and laser reflections, and ensuring the continuity and stability of the data. And on the basis of the filtered first ranging data, the first ranging data points are mapped to a unified two-dimensional plane for fusion processing to obtain fused ranging data. Based on the distance reference value, the fused ranging data is screened to obtain the first target ranging data, and the data with a large deviation from the distance reference value in the fused ranging data is removed, and the invalid ranging data in the fused ranging data, such as invalid ranging data from the protruding parts of the building or the reflection of small objects, is eliminated to ensure the accuracy of the data. According to the error between the ranging data in the first target ranging data, a suitable fitting algorithm is determined, and the first target ranging data obtained after screening is fitted using a suitable fitting algorithm to identify and fit the straight line structure of the floor boundary to obtain the initial fitting boundary. For the first target distance measurement data with small errors between the distance measurement data, the least square method is used for linear fitting to minimize the total error from the laser point to the fitting line, and a smooth initial fitting boundary is obtained; for the first target distance measurement data with large errors between the distance measurement data, that is, there is a lot of noise or interference in the working environment, the RANSAC (Random Sample Consensus) algorithm is used to randomly sample a group of laser points, and through multiple iterations, it is determined whether it conforms to the floor boundary form, and abnormal points (such as corners or protruding obstacles) are removed to achieve a robust fitting of the boundary. The initial fitting boundary is screened according to the characteristic parameters of the initial fitting boundary, and the validity of the line segments in the initial fitting boundary is further verified, so as to automatically select the line segments that fit the real contour of the floor boundary as the floor fitting boundary, so as to calculate the distance between the robot and the floor boundary. Among them, the characteristic parameters include length, angle, etc.

[0061] In one embodiment, when the motion control unit 14 executes the step of detecting the floor edge according to the second ranging data, it is specifically configured to: If it is determined according to the second ranging data that the floor area in front of the robot is an empty area, the robot is controlled to start a preset secondary scanning confirmation mode, and a scanning data set obtained by the robot in the secondary scanning confirmation mode is obtained; If it is determined that the floor area in front of the robot is an empty area according to each set of scanning data in the scanning data set, it is determined that the floor edge is detected.

[0062] In this embodiment, the second ranging data is preprocessed. Specifically, the second ranging data is first filtered to remove noise, and then the filtered data is smoothed to reduce misjudgment caused by short-term jitter. At the same time, by calculating the difference between data points, abnormal data with significant differences from surrounding data is screened out, thereby preprocessing the second ranging data. The preprocessed second ranging data is used to determine whether the floor area in front of the robot is an empty area. The preprocessed second ranging data is analyzed. If it is detected that there are multiple consecutive ranging data that significantly increase or lose signals in the second ranging data, it means that the floor area in front of the robot is preliminarily determined to be an empty area. In order to reduce the risk of misjudgment, the robot is controlled to start the preset secondary scanning confirmation mode, so that the robot repeatedly scans the same position multiple times. The scanning data set obtained by the robot in the secondary scanning confirmation mode is obtained. If it is determined that the floor area in front of the robot is an empty area according to each set of scanning data in the scanning data set, it is determined that the floor edge is detected, ensuring the accuracy of the detection.

[0063] In one embodiment, when the motion control unit 14 executes the step of failing to detect the floor edge according to the second ranging data, it is specifically configured to: If it is determined according to the second ranging data that the floor area in front of the robot is not an empty area, or if it is determined according to at least one set of scanning data in the scanning data set that the floor area in front of the robot is not an empty area, it is determined that the floor edge is not detected.

[0064] In this embodiment, the pre-processed second ranging data is analyzed, and if no significant increase or loss of signal of multiple consecutive ranging data is detected in the second ranging data, it is determined that the floor area in front of the robot is not an empty area, and it is determined that the floor edge is not detected at this time. In addition, after the floor area in front of the robot is initially determined to be an empty area and the robot is controlled to start the preset secondary scanning confirmation mode, if it is determined that the floor area in front of the robot is not an empty area based on at least one set of scanning data of the scanning data set obtained by the robot in the secondary scanning confirmation mode, it is also determined that the floor edge is not detected at this time.

[0065] The navigation control device of the robot provided in an embodiment of the present invention is used to execute the navigation control method of the robot provided in any of the aforementioned embodiments, and scans the floor boundaries, dynamic obstacles and floor surfaces in a complex construction environment respectively through a first laser radar module, an auxiliary obstacle avoidance module and a second laser radar module, and then controls the motion state of the robot in combination with the current motion path and the information corresponding to the floor boundaries, dynamic obstacles and floor surfaces detected in real time, thereby realizing autonomous navigation and preventing the robot from colliding and falling due to being too close to floor boundaries and dynamic obstacles or approaching empty areas without floor surfaces during operation, thereby improving the safety of the robot.

[0066] The above robot navigation control method can be implemented in the form of a computer program. The computer program can be used in Figure 3 Runs on the computer device shown.

[0067] See also Figure 3 , Figure 3 5 is a schematic block diagram of a computer device provided by an embodiment of the present invention. The computer device 500 includes a processor 502 , a memory and a network interface 505 connected via a device bus 501 , wherein the memory may include a storage medium 503 and an internal memory 504 .

[0068] The storage medium 503 can store an operating device 5031 and a computer program 5032. When the computer program 5032 is executed, the processor 502 can execute a navigation control method of a robot.

[0069] The processor 502 is used to provide computing and control capabilities to support the operation of the entire computer device 500 .

[0070] The internal memory 504 provides an environment for the operation of the computer program 5032 in the storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute the navigation control method of the robot.

[0071] The network interface 505 is used for network communication, such as providing data information transmission, etc. Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device 500 to which the solution of the present invention is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0072] The processor 502 is used to run the computer program 5032 stored in the memory to implement the navigation control method of the robot disclosed in the embodiment of the present invention.

[0073] Those skilled in the art will understand that Figure 3 The embodiments of the computer device shown in the figure do not constitute a limitation on the specific composition of the computer device. In other embodiments, the computer device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. For example, in some embodiments, the computer device may only include a memory and a processor. In such embodiments, the structure and function of the memory and the processor are the same as those of the embodiment of the present invention. Figure 3 The embodiments shown are consistent and will not be described again here.

[0074] It should be understood that in the embodiment of the present invention, the processor 502 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0075] In another embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the navigation control method of the robot disclosed in the embodiment of the present invention is implemented.

[0076] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the above-described equipment, devices and units can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. Those of ordinary skill in the art can appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to the function. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0077] In the several embodiments provided by the present invention, it should be understood that the disclosed equipment, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. Units with the same function may also be combined into one unit. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices or units, or may be an electrical, mechanical or other form of connection.

[0078] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0079] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0080] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a backend server, or a network device, etc.) to perform all or part of the steps of the methods of various embodiments of the present invention. The aforementioned storage medium includes: U disk, sports hard disk, read-only memory (ROM, Read-Only Memory), disk or optical disk and other media that can store program codes.

[0081] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A navigation control method for a robot, characterized in that: include: Acquire working environment data scanned by a first laser radar module in the robot, and construct an environment map based on the working environment data; Generate a global motion path according to the environment map and the preset target point, and use the global motion path as the current motion path; Acquire the first ranging data, obstacle data, and second ranging data currently scanned by the robot; wherein the first ranging data is data obtained by the first laser radar module scanning the floor boundary, the obstacle data is data obtained by the auxiliary obstacle avoidance module in the robot scanning the dynamic obstacles, and the second ranging data is data obtained by the second laser radar module in the robot scanning the floor; The motion state of the robot is controlled according to the current motion path, the first distance measurement data, the obstacle data, the second distance measurement data and a preset motion control strategy.

2. The robot navigation control method according to claim 1, characterized in that: The controlling the motion state of the robot according to the current motion path, the first distance measurement data, the obstacle data, the second distance measurement data and a preset motion control strategy comprises: If the dynamic obstacle is not detected according to the obstacle data, and the floor edge is not detected according to the second distance measurement data, then obtaining the distance between the robot and the floor boundary according to the first distance measurement data and using it as the current edge distance, and adjusting the driving speed of the robot along the current motion path based on the current edge distance; If the dynamic obstacle is detected according to the obstacle data, a local motion path is generated according to the obstacle data and the current motion path, the current motion path is updated using the local motion path, and the step of obtaining the first ranging data, obstacle data, and second ranging data currently scanned by the robot is returned to be executed; If the floor edge is detected according to the second ranging data, the robot is controlled to stop moving.

3. The robot navigation control method according to claim 2, characterized in that: The method of obtaining the distance between the robot and the floor boundary according to the first distance measurement data and using the distance as the current edge distance, and adjusting the speed of the robot moving along the current motion path based on the current edge distance, comprises: Processing the first distance measurement data to obtain a floor fitting boundary; Obtaining the current position of the robot according to the first ranging data and the environment map, and calculating the current edge distance according to the current position and the floor fitting boundary; The current edge distance is matched with at least one preset distance interval to obtain a target distance interval to which the current edge distance belongs, and the driving speed of the robot along the current motion path is adjusted according to the target distance interval.

4. The robot navigation control method according to claim 3, characterized in that: The matching of the current edge distance with at least one preset distance interval to obtain a target distance interval to which the current edge distance belongs, and adjusting the driving speed of the robot along the current motion path according to the target distance interval, includes: If it is determined that the target distance interval is the first preset distance interval, the driving speed of the robot is adjusted to a preset normal speed to control the robot to move at a uniform speed along the current motion path; wherein the first preset distance interval is (d1, +∞), and d1 is a first preset distance; If it is determined that the target distance interval is the second preset distance interval, the driving speed of the robot is reduced to a preset safety speed to control the robot to perform deceleration movement along the current motion path; wherein the second preset distance interval is [d2, d1], and d2 is the second preset distance; If it is determined that the target distance interval is the third preset distance interval, the robot is controlled to stop moving; wherein the third preset distance interval is [0, d2).

5. The robot navigation control method according to claim 3, characterized in that: The processing of the first ranging data to obtain a floor fitting boundary includes: Acquire initial ranging data of the first laser radar module, and obtain a distance reference value according to the initial ranging data and preset floor boundary characteristic parameters; Performing filtering and fusion processing on the first ranging data to obtain fused ranging data; Filtering the fused distance measurement data based on the distance reference value to obtain first target distance measurement data; Performing fitting processing on the first target ranging data to obtain an initial fitting boundary; The characteristic parameters of the initial fitting boundary are acquired, and the floor fitting boundary is obtained by screening the initial fitting boundary according to the characteristic parameters.

6. The robot navigation control method according to claim 2, characterized in that: The detecting the floor edge according to the second ranging data comprises: If it is determined according to the second ranging data that the floor area in front of the robot is an empty area, the robot is controlled to start a preset secondary scanning confirmation mode, and a scanning data set obtained by the robot in the secondary scanning confirmation mode is obtained; If it is determined that the floor area in front of the robot is an empty area according to each set of scanning data in the scanning data set, it is determined that the floor edge is detected.

7. The robot navigation control method according to claim 6, characterized in that: The failing to detect the floor edge according to the second ranging data comprises: If it is determined according to the second ranging data that the floor area in front of the robot is not an empty area, or if it is determined according to at least one set of scanning data in the scanning data set that the floor area in front of the robot is not an empty area, it is determined that the floor edge is not detected.

8. A navigation control device for a robot, characterized in that: include: A map construction unit, used to obtain working environment data scanned by a first laser radar module in the robot, and to construct an environment map based on the working environment data; A path generation unit, used to generate a global motion path according to the environment map and a preset target point, and use the global motion path as a current motion path; A data acquisition unit, used to acquire first ranging data, obstacle data, and second ranging data currently scanned by the robot; wherein the first ranging data is data obtained by the first laser radar module scanning the floor boundary, the obstacle data is data obtained by the auxiliary obstacle avoidance module in the robot scanning the dynamic obstacles, and the second ranging data is data obtained by the second laser radar module in the robot scanning the floor; A motion control unit is used to control the motion state of the robot according to the current motion path, the first distance measurement data, the obstacle data, the second distance measurement data and a preset motion control strategy.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the navigation control method of the robot according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, causes the processor to perform the navigation control method of a robot according to any one of claims 1 to 7.

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