Car-based slope detection method, device and computer-readable storage medium

Abstract

The present invention discloses a vehicle-based slope detection method, device, and computer-readable storage medium. The vehicle-based slope detection method comprises: obtaining geographic information around the vehicle to generate a three-dimensional spatial model of a target slope; obtaining geometric parameters of the target slope based on the three-dimensional spatial model; planning a detection route for the vehicle based on the geometric parameters and detection parameters of a radar detector carried by the vehicle; controlling the vehicle to automatically patrol the target slope along the detection route, and detecting the target slope surface on the target slope using the radar detector. This method achieves automatic slope detection using mechanical equipment, achieving better detection results than manual detection while reducing safety risks for detection personnel.

Description

Technical Field

[0001] The present invention relates to the field of slope surface detection, and in particular to a vehicle-based slope surface detection method, device and computer-readable storage medium. Background Art

[0002] Currently, most slope radar systems used for slope inspection rely on manual two-dimensional radar inspections, lacking a comprehensive, full-coverage inspection solution. Furthermore, manual methods are time-consuming and labor-intensive. Furthermore, manual methods pose significant safety risks for inspectors when dealing with steep slopes and large drop heights. Furthermore, they have significant limitations in terms of slope inspection coverage and functionality. Due to human error, there's a high probability of missing a slope or erroneously inspecting the angle. Therefore, manual slope inspections are less than ideal.

[0003] The above content is only used to assist in understanding the technical solution of the present invention and does not constitute an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of the present invention is to provide a slope detection method based on a trolley, aiming to solve the technical problem that the effect of slope edge detection using manual labor is not ideal.

[0005] To achieve the above object, the present invention provides a slope detection method based on a trolley, the slope detection method based on a trolley comprising the following steps:

[0006] Obtain geographic information around the vehicle to generate a three-dimensional spatial model of the target slope;

[0007] Acquiring geometric parameters of the target slope according to the three-dimensional spatial model, and planning a detection route of the vehicle based on the geometric parameters and detection parameters of a radar detector carried by the vehicle;

[0008] The trolley is controlled to perform automatic inspection on the target slope according to the detection route, and the target slope surface on the target slope is detected by the radar detector.

[0009] Furthermore, the detection parameters include a detection area of ​​the radar detector, the geometric parameters include a target slope area, and the step of planning a detection route of the vehicle based on the geometric parameters and the detection parameters of the radar detector carried by the vehicle includes:

[0010] generating a first motion trajectory of the radar detector relative to the target slope surface according to the target slope surface area and the detection area;

[0011] A detection route for the vehicle is generated based on the first motion trajectory and a preset vehicle motion direction.

[0012] Furthermore, the detection parameters also include an activity range parameter of the radar detector, and the step of completing the detection of the target slope surface on the target slope by the radar detector includes:

[0013] generating a second motion trajectory of the radar detector relative to the vehicle according to the first motion trajectory of the target slope and the activity range parameter;

[0014] The radar detector is controlled to move according to the second motion trajectory to detect the target slope.

[0015] Furthermore, the geometric parameter includes the target slope, and the step of detecting the target slope includes:

[0016] generating a current detection angle of the radar detector according to the position of the radar detector on the target slope and the slope of the target slope;

[0017] The target slope is detected based on the current detection angle.

[0018] Furthermore, the step of controlling the vehicle to automatically inspect the target slope according to the inspection route includes:

[0019] Controlling the car to move along the detection route, and obtaining obstacle information of obstacles around the car in real time through a distance measurement module carried by the car;

[0020] Generate the shortest distance between the surrounding obstacles and the vehicle based on the obstacle information;

[0021] When the closest distance is less than the preset safety distance, the vehicle stops moving and enters a waiting state, and determines whether the current waiting time for the vehicle to enter the waiting state is greater than or equal to the preset waiting time;

[0022] When the current waiting time is greater than or equal to the preset waiting time, an optimized detection route for the car is generated based on the first motion trajectory, the preset car motion direction and the obstacle information, and the car is controlled to move according to the optimized detection route.

[0023] Furthermore, after the step of determining whether the current waiting time of the vehicle entering the waiting state is greater than or equal to the preset waiting time, the method further includes:

[0024] When the current waiting time is less than the preset waiting time, and the closest distance is changed to be greater than or equal to the preset safety distance, the vehicle is continued to be controlled to move along the detection route.

[0025] Furthermore, before the step of acquiring geographic information around the vehicle to generate a three-dimensional spatial model of the target slope, the method further includes:

[0026] The visual sensor on the vehicle acquires an image of the vehicle's surrounding environment, and inputs the image of the surrounding environment into a preset image recognition model;

[0027] The target slope surface is identified from the surrounding environment image by using the preset image recognition model, and the target slope surface area is marked to generate a marked area.

[0028] Furthermore, the step of obtaining geographic information around the vehicle to generate a three-dimensional spatial model of the target slope includes:

[0029] The three-dimensional point cloud data of the surrounding environment is acquired by a laser radar carried by the vehicle, and a three-dimensional spatial model of the target slope is generated according to the three-dimensional point cloud data of the marked area, wherein the surrounding environment includes the marked area.

[0030] In addition, to achieve the above-mentioned purpose, the present invention also provides a trolley-based slope detection device, which includes: a memory, a processor, and a trolley-based slope detection program stored in the memory and runnable on the processor. When the trolley-based slope detection program is executed by the processor, the steps of the trolley-based slope detection method as described above are implemented.

[0031] In addition, to achieve the above-mentioned purpose, the present invention also provides a readable storage medium, on which a trolley-based slope detection program is stored. When the trolley-based slope detection program is executed by a processor, the steps of the trolley-based slope detection method as described above are implemented.

[0032] The present invention proposes a cart-based slope detection method. Using multiple sensors mounted on the cart, the method acquires a three-dimensional spatial model of the slope to be detected. From this model, the method also obtains geometric parameters of the slope. Based on these parameters and the detection parameters of a radar detector mounted on the cart, the method plans the trajectory of the cart and radar detector. The method then controls the cart and radar detector to follow the generated trajectory and detect the target slope. This method achieves automated slope detection using mechanical equipment, achieving superior detection results compared to manual inspection while reducing safety risks for inspectors. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 Schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present invention;

[0034] Figure 2This is a flow chart of a first embodiment of a vehicle-based slope detection method according to the present invention;

[0035] Figure 3 This is a flow chart of a second embodiment of the slope detection method based on a trolley according to the present invention;

[0036] Figure 4 The figure is a schematic diagram of the motion trajectory of the radar detector in the slope detection method based on the vehicle of the present invention.

[0037] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0038] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0039] like Figure 1 As shown, Figure 1 It is a schematic diagram of the terminal structure of the hardware operating environment involved in the embodiment of the present invention.

[0040] The device in the embodiment of the present invention can be a small car, or it can be an electronic terminal device such as a robot, PC, smart phone, tablet computer, portable computer, etc. with data collection, data processing and data output functions.

[0041] like Figure 1 As shown, the device may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0042] Optionally, the device may also include a camera, RF (Radio Frequency) circuit, sensor, audio circuit, WiFi module, etc. Among them, sensors include light sensors, motion sensors and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor can adjust the brightness of the display screen according to the brightness of the ambient light, and the proximity sensor can turn off the display screen and / or backlight when the mobile terminal is moved to the ear. As a type of motion sensor, the gravity acceleration sensor can detect the magnitude of acceleration in all directions (generally three axes), and can detect the magnitude and direction of gravity when stationary. It can be used for applications that identify the posture of the mobile terminal (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc.; of course, the mobile terminal can also be equipped with other sensors such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., which will not be repeated here.

[0043] Those skilled in the art will understand that Figure 1 The device structure shown in the figure does not constitute a limitation of the device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0044] like Figure 1 As shown, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a vehicle-based slope detection program.

[0045] exist Figure 1 In the device shown, the network interface 1004 is mainly used to connect to the backend server and communicate data with the backend server; the user interface 1003 is mainly used to connect to the client (user end) and communicate data with the client; and the processor 1001 can be used to call the vehicle-based slope detection program stored in the memory 1005 and perform the following operations:

[0046] Obtain geographic information around the vehicle to generate a three-dimensional spatial model of the target slope;

[0047] Acquiring geometric parameters of the target slope according to the three-dimensional spatial model, and planning a detection route of the vehicle based on the geometric parameters and detection parameters of a radar detector carried by the vehicle;

[0048] The trolley is controlled to perform automatic inspection on the target slope according to the detection route, and the target slope surface on the target slope is detected by the radar detector.

[0049] Furthermore, the processor 1001 may call the vehicle-based slope detection program stored in the memory 1005 and perform the following operations:

[0050] The detection parameters include the detection area of ​​the radar detector, the geometric parameters include the target slope area, and the step of planning the detection route of the vehicle based on the geometric parameters and the detection parameters of the radar detector carried by the vehicle includes:

[0051] generating a first motion trajectory of the radar detector relative to the target slope surface according to the target slope surface area and the detection area;

[0052] A detection route for the vehicle is generated based on the first motion trajectory and a preset vehicle motion direction.

[0053] Furthermore, the processor 1001 may call the vehicle-based slope detection program stored in the memory 1005 and perform the following operations:

[0054] The detection parameters also include an activity range parameter of the radar detector. The step of completing the detection of the target slope surface on the target slope by the radar detector includes:

[0055] generating a second motion trajectory of the radar detector relative to the vehicle according to the first motion trajectory of the target slope and the activity range parameter;

[0056] The radar detector is controlled to move according to the second motion trajectory to detect the target slope.

[0057] Furthermore, the processor 1001 may call the vehicle-based slope detection program stored in the memory 1005 and perform the following operations:

[0058] The geometric parameters include the target slope, and the step of detecting the target slope includes:

[0059] generating a current detection angle of the radar detector according to the position of the radar detector on the target slope and the slope of the target slope;

[0060] The target slope is detected based on the current detection angle.

[0061] Furthermore, the processor 1001 may call the vehicle-based slope detection program stored in the memory 1005 and perform the following operations:

[0062] The step of controlling the vehicle to automatically inspect the target slope along the inspection route includes:

[0063] Controlling the car to move along the detection route, and obtaining obstacle information of obstacles around the car in real time through a distance measurement module carried by the car;

[0064] Generate the shortest distance between the surrounding obstacles and the vehicle based on the obstacle information;

[0065] When the closest distance is less than the preset safety distance, the vehicle stops moving and enters a waiting state, and determines whether the current waiting time for the vehicle to enter the waiting state is greater than or equal to the preset waiting time;

[0066] When the current waiting time is greater than or equal to the preset waiting time, an optimized detection route for the car is generated based on the first motion trajectory, the preset car motion direction and the obstacle information, and the car is controlled to move according to the optimized detection route.

[0067] Furthermore, the processor 1001 may call the vehicle-based slope detection program stored in the memory 1005 and perform the following operations:

[0068] After the step of determining whether the current waiting time for the vehicle to enter the waiting state is greater than or equal to the preset waiting time, the method includes:

[0069] When the current waiting time is less than the preset waiting time, and the closest distance is changed to be greater than or equal to the preset safety distance, the vehicle is continued to be controlled to move along the detection route.

[0070] Furthermore, the processor 1001 may call the vehicle-based slope detection program stored in the memory 1005 and perform the following operations:

[0071] Before the step of acquiring geographic information around the vehicle to generate a three-dimensional spatial model of the target slope, the method includes:

[0072] The visual sensor on the vehicle acquires an image of the vehicle's surrounding environment, and inputs the image of the surrounding environment into a preset image recognition model;

[0073] The target slope surface is identified from the surrounding environment image by using the preset image recognition model, and the target slope surface area is marked to generate a marked area.

[0074] Furthermore, the processor 1001 may call the vehicle-based slope detection program stored in the memory 1005 and perform the following operations:

[0075] The step of obtaining geographic information around the vehicle to generate a three-dimensional spatial model of the target slope includes:

[0076] The three-dimensional point cloud data of the surrounding environment is acquired by a laser radar carried by the vehicle, and a three-dimensional spatial model of the target slope is generated according to the three-dimensional point cloud data of the marked area, wherein the surrounding environment includes the marked area.

[0077] Reference Figure 2 The first embodiment of the slope detection method based on a trolley of the present invention comprises:

[0078] Step S10, obtaining geographic information around the vehicle to generate a three-dimensional spatial model of the target slope;

[0079] In this embodiment, the vehicle-based slope detection method is performed by a vehicle, and the target slope is the area to be inspected. A slope refers to a slope with a certain gradient created on both sides of a roadbed to ensure roadbed stability. Taking urban slopes as an example, some urban slopes are reinforced with cement or protective nets to prevent natural disasters such as landslides. While these reinforcements provide a reinforcement effect, they also mask some safety hazards. The target slope that subsequently appears is the reinforced slope. A detection radar can obtain the internal geological structure of the slope, and based on this internal geological structure, determine whether the slope being inspected has hazards such as collapse, rockfall, or landslides. The aforementioned surrounding geographic information can include the vehicle's location (the vehicle is equipped with RTK (Real-time Kinematic, carrier phase differential technology) to obtain its own positioning, such as latitude and longitude), or image information of the surrounding environment. A three-dimensional spatial model of the target slope can be generated based on the geographic information collected by the car, or an already constructed three-dimensional spatial model can be directly input into the car. It can be understood that the three-dimensional spatial model is a digitized target slope with multiple geometric parameters of the target slope, such as the overall extension length of the slope, the height difference of the slope, the slope gradient, and the area of ​​the slope surface.

[0080] Furthermore, the surrounding environment image of the car is obtained by the visual sensor carried by the car, and the surrounding environment image is input into a preset image recognition model; the target slope surface is identified from the surrounding environment image by the preset image recognition model, and the target slope surface area is marked to generate a marking area.

[0081] Specifically, the visual sensor carried by the car can be a camera, which will be used to obtain information about the surrounding environment of the car (such as collecting 360-degree images or videos around the car). After the car is started, the camera of the car collects images of the surrounding environment, and puts the collected image data into a pre-trained image recognition algorithm model for slope recognition. In addition, to train the image recognition algorithm model, it is only necessary to input the slope image that has been marked as the target slope as a training sample into the image recognition algorithm model to complete the training. There is currently a relatively mature image recognition technology, which will not be described here. By identifying the surrounding environment image, the area of ​​the target slope can be determined, and it can be marked to generate a marked area, so as to facilitate the subsequent generation of a three-dimensional model of the target slope.

[0082] Furthermore, three-dimensional point cloud data of the surrounding environment is acquired by a laser radar carried by the vehicle, and a three-dimensional spatial model of the target slope is generated based on the three-dimensional point cloud data of the marked area, wherein the surrounding environment includes the marked area.

[0083] Specifically, the vehicle is equipped with a laser radar, which can generate a set of points with three-dimensional coordinates (i.e., three-dimensional point cloud data) based on the surrounding terrain environment, and generate a three-dimensional spatial model of the target slope based on the three-dimensional point cloud data of the area marked as the target slope.

[0084] Step S20, obtaining geometric parameters of the target slope according to the three-dimensional spatial model, and planning a detection route of the vehicle based on the geometric parameters and detection parameters of a radar detector carried by the vehicle;

[0085] Furthermore, the detection parameters include the detection area of ​​the radar detector, the geometric parameters include the target slope area, and the step of planning the detection route of the vehicle based on the geometric parameters and the detection parameters of the radar detector carried by the vehicle includes: generating a first motion trajectory of the radar detector relative to the target slope according to the target slope area and the detection area; and generating the detection route of the vehicle based on the first motion trajectory and the preset vehicle motion direction.

[0086] Specifically, the geometric parameters of the three-dimensional spatial model include the target slope area, and the detection parameters include the detection area of ​​the radar detector. The detection area is the figure that the radar detector can detect in one detection. The target slope area of ​​the target slope is obtained according to the three-dimensional model of the target slope, and the first motion trajectory of the radar detector relative to the target slope is generated according to the target slope area and the detection area. It can be understood that under normal circumstances, the target slope area is a rectangle. When the detection radar is fixed on a trolley and the trolley travels in a fixed direction parallel to the slope, the area swept by the detection radar is also a rectangle, such as Figure 4The schematic diagram of the radar detector's motion trajectory is shown. In the figure, the x-axis and the y-axis coincide with the two sides of the target slope. The target slope area is a rectangle including side A and side B. The detection area is also a rectangle including side a and side b. The trajectory composed of the dotted arrows and the solid arrows in the figure is the movement trajectory of the detection area on the target slope and is also the movement trajectory of the detection radar. The minimum number of detections of the radar detector on the target slope can be determined by side a and side A (such as the minimum number of detections can be obtained by dividing the length of side A by the length of side a). The longest moving distance of the detection radar can be determined based on side B (the length of a dotted line in the figure), and the minimum moving distance of the detection radar can be determined by side a (the length of a solid line in the figure). Thus, the first motion trajectory (the trajectory composed of the dotted arrows and the solid arrows in the figure) can be obtained. The detection route of the car is generated based on the above-mentioned first motion trajectory combined with the preset car movement direction. Similarly, Figure 4 As mentioned above, the preset direction of movement of the vehicle can be selected as the x-axis or the y-axis. The x-axis is selected as an example for explanation. Figure 4 The dotted part of the first motion trajectory is used as the motion trajectory of the car, and the preset motion direction of the car is selected as the x-axis. Therefore, the actual detection route of the car is to move back and forth along the B side of the target slope to detect the longest moving distance of the radar. It should be noted that Figure 4 The radar detection motion trajectory shown does not limit the first motion trajectory of this embodiment. The specific trajectory can be set according to actual needs (except Figure 4 In addition to the first motion trajectory shown, during the detection process, the radar detector can also complete the detection of the area within its own activity range parameters and then move the car. After the car moves a preset distance, the radar detector then completes the detection of the area within its own activity range parameters, and so on (it will not be repeated here). The detection area can be of any shape, and the initial and end positions of the detection can be set according to actual needs.

[0087] Furthermore, the detection parameters also include the activity range parameters of the radar detector. The step of completing the detection of the target slope surface on the target slope by the radar detector includes: generating a second motion trajectory of the radar detector relative to the vehicle based on the first motion trajectory of the target slope surface and the activity range parameters; controlling the radar detector to move according to the second motion trajectory to detect the target slope surface.

[0088] Specifically, the detection parameters also include the range parameters of the radar detector. It is understandable that the radar detector is usually not fixed on the car. For example, a cantilever is set between the radar detector and the car, so the radar detector can have a certain range of movement relative to the car. Figure 4 For example, the range parameter is actually the maximum distance that can be moved in the y-axis direction, and the range parameter is determined by the connection structure between the detection radar and the car. Figure 4 The solid arrow portion of the first motion trajectory serves as the second motion trajectory of the detection radar relative to the vehicle, and the second motion trajectory should be within the activity range parameters of the radar detector (if the second motion trajectory exceeds the activity range parameters of the radar detector, it is necessary to change the initial position of the vehicle and re-plan the first motion trajectory). Therefore, during the actual scanning process of the detection radar, each time the vehicle changes its direction of movement, the detection radar moves the length of the solid arrow in the y-axis direction. It can be understood that when the minimum number of radar detector movements is the goal, Figure 4 The length of a solid arrow is the length of side a. In actual applications, the length of the solid arrow can be set according to needs. For example, to avoid scanning omissions when the length is the length of side a, the length of the solid arrow is set to a distance less than the length of side a.

[0089] It should be noted that in the above examples Figure 4 Explain the generation process of the first motion trajectory, the second motion trajectory and the detection route of the car, but Figure 4 It does not constitute a restriction on its generation process.

[0090] Step S30: Control the trolley to automatically inspect the target slope along the inspection route, and complete the inspection of the target slope surface on the target slope through the radar detector.

[0091] Furthermore, the geometric parameters include the slope of the target slope, and the step of detecting the target slope includes: generating a current detection angle of the radar detector based on the position of the radar detector on the target slope and the slope of the target slope; and detecting the target slope based on the current detection angle.

[0092] Specifically, the geometric parameters of the target slope include the target slope gradient. It is understandable that the actual target slope is not a regular three-dimensional spatial model. Therefore, the slope may be different at different locations on the target slope. The radar detector positioning position can be obtained through the RTK sensor carried by the above-mentioned vehicle, and the three-dimensional spatial model of the target slope generated by the three-dimensional point cloud data also carries position information. It is understandable that when the radar detection position and the position information carried by the three-dimensional spatial model have the same positioning standard, the relative position of the detector and the target slope can be determined. Based on the relative position, the slope of the area being scanned by the radar detector can be obtained at this time. The slope of the area being scanned is used as the current detection angle of the radar detector. The radar detector scanning angle is adjusted to the current detection angle, so that the scanning surface of the radar detector is parallel to the target slope to improve the detection effect.

[0093] Optionally, to avoid frequent adjustment of the scanning angle of the radar detector, before adjustment, the current scanning angle of the radar detector is compared with the slope of the scanning area (current detection angle). When the current scanning angle differs from the slope of the scanning area by a preset angle (such as 20°), the scanning angle of the radar detector is adjusted to the current detection angle.

[0094] In this embodiment, a trolley uses various sensors mounted on it to obtain a 3D spatial model of the slope to be detected. From this model, the trolley's geometric parameters are derived. Based on these parameters and the detection parameters of a radar detector mounted on the trolley, the trolley and radar detector's trajectory is planned. The trolley and radar detector are then controlled to follow the generated trajectory and detect the target slope. This allows for automated slope detection using mechanical equipment, resulting in superior results compared to manual inspection while also reducing safety risks for inspectors.

[0095] Reference Figure 3 The present invention is based on the second embodiment of the slope detection method of a vehicle. Based on the first embodiment, step S30 includes:

[0096] Step S31: Control the vehicle to move along the detection route, and obtain obstacle information of obstacles around the vehicle in real time through a distance measurement module carried by the vehicle; and generate the closest distance between the surrounding obstacles and the vehicle based on the obstacle information;

[0097] Specifically, when controlling the car to move along the detection route, the obstacle information of the obstacles around the car will be obtained in real time through the ranging module carried by the car. The obstacle information is the distance between the car and the surrounding obstacles, and the smallest distance is selected as the closest distance between the surrounding obstacles and the car.

[0098] Step S32, when the closest distance is less than the preset safety distance, the vehicle stops moving and enters a waiting state, and determines whether the current waiting time of the vehicle entering the waiting state is greater than or equal to the preset waiting time;

[0099] Specifically, the closest distance is compared with the preset safety distance. When the closest distance is less than the safety distance, the car is controlled to stop moving and enter a waiting state to avoid a collision. The waiting state is also timed and compared with the preset waiting time.

[0100] Step S321, when the current waiting time is greater than or equal to the preset waiting time, an optimized detection route for the car is generated based on the first motion trajectory, the preset car motion direction and the obstacle information, and the car is controlled to move according to the optimized detection route.

[0101] Specifically, when the time the car enters the waiting state is greater than or equal to the preset waiting time, the car is controlled to bypass the obstacle based on the car's adaptive edge control algorithm and the running trajectory is recorded. When the running trajectory generated by the adaptive edge control algorithm coincides with the above-mentioned detection route, the car moves again along the above-mentioned detection route and resumes the detection of the radar detector. It can be understood that the optimized detection route is actually the obstacle-avoiding portion of the running trajectory generated by the adaptive edge control algorithm on the road section where there is an obstacle (this portion is the portion of the running trajectory generated by the adaptive edge control algorithm that does not coincide with the detection route). The non-obstacle road section is the detection route. When driving around the obstacle, the radar detector will stop detecting, and the undetected portion of the target slope will also be marked.

[0102] Step S322: When the current waiting time is less than the preset waiting time and the closest distance is changed to be greater than or equal to the preset safety distance, the vehicle is continued to be controlled to move along the detection route.

[0103] In this embodiment, the vehicle also sets a safety distance. As it travels along the planned detection route, it acquires real-time information about the distances to surrounding obstacles. If an obstacle is closer than the safety distance, the vehicle begins to maneuver around it, generating an optimized detection route. This allows the vehicle to detect slope edges even in complex terrain, improving its adaptability.

[0104] In addition, this embodiment also provides a trolley-based slope detection device, which includes: a memory, a processor, and a trolley-based slope detection program stored in the memory and runnable on the processor. When the trolley-based slope detection program is executed by the processor, the steps of the trolley-based slope detection method described above are implemented.

[0105] In addition, this embodiment also provides a readable storage medium, which stores a trolley-based slope detection program. When the trolley-based slope detection program is executed by the processor, the steps of the trolley-based slope detection method as described above are implemented.

[0106] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0107] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0108] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0109] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A slope detection method based on a car, characterized in that: The slope detection method based on the trolley comprises the following steps: Obtain geographic information around the vehicle to generate a three-dimensional spatial model of the target slope; Acquiring geometric parameters of the target slope according to the three-dimensional spatial model, and planning a detection route of the vehicle based on the geometric parameters and detection parameters of a radar detector carried by the vehicle; Controlling the trolley to automatically patrol the target slope along the detection route, and completing detection of the target slope surface on the target slope through the radar detector; The detection parameters include the detection area of ​​the radar detector, the geometric parameters include the target slope area, and the step of planning the detection route of the vehicle based on the geometric parameters and the detection parameters of the radar detector carried by the vehicle includes: generating a first motion trajectory of the radar detector relative to the target slope surface according to the target slope surface area and the detection area; Generating a detection route for the vehicle based on the first motion trajectory and a preset vehicle motion direction; The detection parameters also include an activity range parameter of the radar detector, and the step of completing the detection of the target slope surface on the target slope by the radar detector includes: generating a second motion trajectory of the radar detector relative to the vehicle according to the first motion trajectory of the target slope and the activity range parameter; The radar detector is controlled to move along the second motion trajectory to detect the target slope.

2. The vehicle-based slope detection method according to claim 1, wherein: The geometric parameters include the target slope, and the step of detecting the target slope includes: generating a current detection angle of the radar detector according to the position of the radar detector on the target slope and the slope of the target slope; The target slope is detected based on the current detection angle.

3. The vehicle-based slope detection method according to claim 1, wherein: The step of controlling the vehicle to automatically inspect the target slope along the inspection route includes: Controlling the car to move along the detection route, and obtaining obstacle information of obstacles around the car in real time through a distance measurement module carried by the car; Generate the shortest distance between the surrounding obstacles and the vehicle based on the obstacle information; When the closest distance is less than the preset safety distance, the vehicle stops moving and enters a waiting state, and determines whether the current waiting time for the vehicle to enter the waiting state is greater than or equal to the preset waiting time; When the current waiting time is greater than or equal to the preset waiting time, an optimized detection route for the car is generated based on the first motion trajectory, the preset car motion direction and the obstacle information, and the car is controlled to move according to the optimized detection route.

4. The vehicle-based slope detection method according to claim 3, wherein: After the step of determining whether the current waiting time for the vehicle to enter the waiting state is greater than or equal to the preset waiting time, the method includes: When the current waiting time is less than the preset waiting time, and the closest distance is changed to be greater than or equal to the preset safety distance, the vehicle is continued to be controlled to move along the detection route.

5. The vehicle-based slope detection method according to claim 1, wherein: Before the step of acquiring geographic information around the vehicle to generate a three-dimensional spatial model of the target slope, the method includes: The visual sensor on the vehicle acquires an image of the vehicle's surrounding environment, and inputs the image of the surrounding environment into a preset image recognition model; The target slope surface is identified from the surrounding environment image by using the preset image recognition model, and the target slope surface area is marked to generate a marked area.

6. The vehicle-based slope detection method according to claim 5, characterized in that: The step of obtaining geographic information around the vehicle to generate a three-dimensional spatial model of the target slope includes: The three-dimensional point cloud data of the surrounding environment is acquired by a laser radar carried by the vehicle, and a three-dimensional spatial model of the target slope is generated according to the three-dimensional point cloud data of the marked area, wherein the surrounding environment includes the marked area.

7. A slope detection device based on a trolley, characterized in that: The trolley-based slope detection device includes: a memory, a processor, and a trolley-based slope detection program stored in the memory and executable on the processor. When the trolley-based slope detection program is executed by the processor, the steps of the trolley-based slope detection method as described in any one of claims 1 to 6 are implemented.

8. A readable storage medium, characterized in that: The readable storage medium stores a vehicle-based slope detection program, which, when executed by a processor, implements the steps of the vehicle-based slope detection method according to any one of claims 1 to 6.

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