Methods and apparatus for detecting regional boundaries

Abstract

This invention discloses a method and apparatus for detecting regional boundaries, applicable to autonomous driving and smart mining. The method includes: responding to a received input command, constructing a set of line segments to be detected corresponding to the regional boundary based on the start and end positions carried in the input command; multiple line segments to be detected in the set constitute the regional boundary; controlling a data acquisition vehicle to start driving along the regional boundary, and determining the current detection progress of the regional boundary based on the vehicle's trajectory whenever the vehicle meets preset detection conditions; the current detection progress characterizes the proportion of a target line segment among the multiple line segments to be detected, and the target line segment characterizes the line segment for which the vehicle has successfully acquired perception data; and outputting the current detection progress of the regional boundary. This invention solves the technical problem in related technologies where repeated acquisition of perception data for regional boundaries is required, resulting in low update efficiency for regional boundaries.

Description

Technical Field

[0001] This invention relates to the fields of autonomous driving and smart mining, and more specifically, to a method and apparatus for detecting area boundaries. Background Technology

[0002] In soil dumping operations, the outer edge of the work area is the soil dumping line, and near the soil dumping line are designated dumping positions for vehicles to dump soil. During the dumping process, the work area continuously expands, causing the position of the soil dumping line to change. Therefore, the soil dumping line needs to be updated with high precision to ensure the safety of vehicles during soil dumping operations.

[0003] Currently, data collection vehicles can be used to collect perception data of the work area boundary, thereby generating a high-precision area boundary. However, during the process of collecting perception information, data loss often occurs, resulting in poor integrity of the collected perception data. This requires data collection personnel to collect data repeatedly, leading to low efficiency in updating the area boundary.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a method and apparatus for detecting regional boundaries, which at least solves the technical problem in related technologies that requires repeated collection of perception data of regional boundaries, resulting in low update efficiency of regional boundaries.

[0006] According to one aspect of the present invention, a method for detecting a region boundary is provided, comprising: responding to a received input instruction, constructing a set of line segments to be detected corresponding to the region boundary based on a start position and an end position carried in the input instruction, wherein the start position is used to characterize the start point of the region boundary, the end position is used to characterize the end point of the region boundary, and the multiple line segments to be detected included in the set of line segments to be detected constitute the region boundary; controlling a collection vehicle to start driving along the region boundary, and determining the current detection progress of the region boundary based on the driving trajectory of the collection vehicle whenever the collection vehicle meets a preset detection condition, wherein the collection vehicle is used to collect perception data of the region boundary during the process of driving along the region boundary, the current detection progress is used to characterize the proportion of a target line segment among the multiple line segments to be detected, and the target line segment is used to characterize the line segment whose perception data has been successfully collected by the collection vehicle; and outputting the current detection progress of the region boundary.

[0007] Furthermore, based on the vehicle's driving trajectory, the current detection progress of the area boundary is determined, including: based on the vehicle's driving trajectory, determining a first parameter corresponding to at least one trajectory segment in the driving trajectory, wherein the type of the first parameter includes one of the following: vertical direction vector, orientation angle; based on the first parameter corresponding to at least one trajectory segment, determining a target line segment from multiple line segments to be detected; and obtaining the current detection progress based on the number of target line segments and the number of multiple line segments to be detected.

[0008] Furthermore, when the type of the first parameter includes a vertical direction vector, determining the target line segment from multiple line segments to be detected based on the first parameter corresponding to at least one trajectory segment includes: determining the intersection of the first parameter corresponding to each trajectory segment with each line segment to be detected; determining the first distance between the driving trajectory and the line segment to be detected based on the first parameter corresponding to the trajectory segment; and determining that the line segment to be detected is the target line segment when the first parameter corresponding to the trajectory segment intersects with the line segment to be detected and the first distance is less than a first preset distance.

[0009] Further, based on the vehicle's driving trajectory, the current detection progress of the area boundary is determined, including: acquiring the historical detection progress of the area boundary, wherein the historical detection progress is used to characterize the detection progress determined when the vehicle previously met the preset detection conditions, and the historical detection progress is the preset progress when the vehicle first meets the preset detection conditions; determining a second parameter of the driving trajectory based on the current trajectory point in the vehicle's driving trajectory and a previous historical trajectory point, wherein the second parameter includes one of the following: a vertical direction vector and an orientation angle; determining a target line segment from multiple line segments to be detected based on the second parameter; and adjusting the historical detection progress based on the number of target line segments to obtain the current detection progress.

[0010] Further, based on the second parameter, the target line segment is determined from multiple line segments to be detected, including: determining at least one candidate line segment marked with a preset state from multiple line segments to be detected, wherein the preset state is used to characterize that at least one candidate line segment has not been successfully collected by the acquisition vehicle, and when the acquisition vehicle meets the preset detection conditions for the first time, multiple line segments to be detected are marked with the preset state; determining the target line segment from at least one candidate line segment based on the second parameter; and clearing the preset state marked for the target line segment.

[0011] Furthermore, after controlling the data collection vehicle to start traveling along the area boundary, the method also includes: acquiring the current trajectory point of the data collection vehicle; determining a second distance between the current trajectory point and the historical trajectory point of the data collection vehicle; and determining that the data collection vehicle meets the preset detection conditions if the second distance is greater than a second preset distance.

[0012] Furthermore, based on the start and end positions carried in the input instructions, a set of line segments to be detected corresponding to the region boundary is constructed, including: determining whether historical sensing data of the region boundary exists, wherein the historical sensing data includes sensing data of multiple historical detection points; if historical sensing data exists, the multiple historical detection points are clipped based on the start and end positions to obtain a clipped detection point set, and a set of line segments to be detected is constructed based on the clipped detection point set; if historical sensing data does not exist, interpolation is performed between the start and end positions to generate a set of line segments to be detected.

[0013] Further, multiple historical detection points are cropped based on the start and end positions to obtain a cropped set of detection points. This includes: searching among multiple historical detection points based on the start position to determine a first target detection point, wherein the distance between the first target detection point and the start position is less than the distance between the first other detection points and the start position, and the first other detection points are used to represent detection points among multiple historical detection points other than the first target detection point; searching among multiple historical detection points based on the end position to determine a second target detection point, wherein the distance between the second target detection point and the end position is less than the distance between the second other detection points and the end position, and the second other detection points are used to represent detection points among multiple historical detection points other than the second target detection point; determining candidate detection points located between the first target detection point and the second target detection point from among multiple historical detection points; and cropping the detection points among multiple historical detection points other than the candidate detection points to obtain a cropped set of detection points.

[0014] Furthermore, a set of line segments to be detected is constructed based on the clipped set of detection points, including: determining the target spacing between detection points based on the task scenario corresponding to the region boundary; performing interpolation processing on the clipped set of detection points according to the target spacing to generate the set of line segments to be detected; and segmenting the line connecting two adjacent detection points in the set of line segments to be detected to obtain the set of line segments to be detected.

[0015] Furthermore, interpolation is performed between the starting and ending positions to generate a set of line segments to be detected, including: determining the target spacing between detection points based on the task scenario corresponding to the region boundary; performing interpolation between the starting and ending positions according to the target spacing to generate a set of points to be detected; and segmenting the lines connecting two adjacent detection points in the set of points to be detected to obtain a set of line segments to be detected.

[0016] Furthermore, the current detection progress of the output region boundary can be achieved by one of the following: displaying the current detection progress of the region boundary in the interactive interface; or playing the current detection progress of the region boundary via voice announcement.

[0017] Furthermore, the method also includes: outputting the historical detection progress of the area boundary when the vehicle being collected does not meet the preset detection conditions.

[0018] Furthermore, the method also includes: outputting line segments marked with preset states among multiple line segments to be detected; and controlling the acquisition vehicle to re-acquire the perception data of the line segments marked with preset states.

[0019] According to another aspect of the present invention, a region boundary detection device is also provided, comprising: a construction module, configured to, in response to a received input instruction, construct a set of line segments to be detected corresponding to the region boundary based on a start position and an end position carried in the input instruction, wherein the start position is used to characterize the start point of the region boundary, the end position is used to characterize the end point of the region boundary, and the multiple line segments to be detected included in the set of line segments to be detected constitute the region boundary; a determination module, configured to control a collection vehicle to start driving along the region boundary, and determine the current detection progress of the region boundary based on the driving trajectory of the collection vehicle whenever the collection vehicle meets a preset detection condition, wherein the collection vehicle is used to collect perception data of the region boundary during the process of driving along the region boundary, the current detection progress is used to characterize the proportion of a target line segment among the multiple line segments to be detected, and the target line segment is used to characterize the line segment whose perception data has been successfully collected by the collection vehicle; and an output module, configured to output the current detection progress of the region boundary.

[0020] According to another aspect of the present invention, an electronic device is also provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods of various embodiments of the present invention during runtime.

[0021] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is executed, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of the present invention.

[0022] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the methods of various embodiments of the present invention.

[0023] According to another aspect of the present invention, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods of various embodiments of the present invention.

[0024] According to another aspect of the present invention, a computer program is also provided, which, when executed by a processor, implements the methods of the various embodiments of the present invention.

[0025] In this embodiment of the invention, in response to a received input command, a set of line segments to be detected corresponding to the region boundary is constructed based on the start and end positions carried in the input command. Then, the data acquisition vehicle is controlled to start traveling along the region boundary. Whenever the data acquisition vehicle meets preset detection conditions, the current detection progress of the region boundary is determined based on the vehicle's travel trajectory, and the current detection progress of the region boundary is output, thus achieving the purpose of progress detection during real-time data acquisition. It is noteworthy that since the current detection progress is executed when the data acquisition vehicle meets the preset detection conditions, and the current detection progress can be output in real time when it is determined to be lagging, real-time coverage detection of the region boundary can be performed during the process of sensing data acquisition of the region boundary. This facilitates progress reporting to the data acquisition personnel, achieving the technical effect of ensuring the integrity of the acquired data and improving the acquisition efficiency. This solves the technical problem in related technologies where sensing data of the region boundary needs to be repeatedly acquired, resulting in low update efficiency of the region boundary. Attached Figure Description

[0026] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0027] Figure 1 This is a flowchart of a method for detecting a region boundary according to an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of a method for detecting a region boundary according to an embodiment of the present invention;

[0029] Figure 3 This is a schematic diagram of a region boundary detection device according to an embodiment of the present invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] According to an embodiment of the present invention, a method for detecting a region boundary is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0033] Figure 1 This is a flowchart of a method for detecting region boundaries according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0034] Step S102: In response to the received input instruction, based on the start position and end position carried in the input instruction, construct a set of line segments to be detected corresponding to the region boundary. The start position is used to characterize the start of the region boundary, and the end position is used to characterize the end of the region boundary. The multiple line segments to be detected contained in the set of line segments to be detected constitute the region boundary.

[0035] The aforementioned input commands can be commands entered by people in the vehicle on the vehicle's central control screen, commands entered by people in the vehicle through an APP on an electronic device, or commands entered by operators in the cloud, but are not limited to these.

[0036] In one alternative embodiment, when it is necessary to update the area boundary using a data collection vehicle, personnel on the vehicle can operate the app to select the start and end points of the boundary area, thereby generating input instructions carrying the start and end positions. The app can send the input instructions to the data collection vehicle via the network, thereby controlling the vehicle to collect sensing data of the area boundary. Alternatively, the app can send the input instructions to the cloud via the network, allowing the cloud to control the data collection vehicle to collect sensing data of the area boundary.

[0037] In another alternative embodiment, when it is necessary to update the area boundary by a data collection vehicle, the operator in the cloud can input the start and end points of the boundary area to generate an input command carrying the start and end points. Then, the cloud controls the data collection vehicle to collect sensing data of the area boundary, or sends the input command to the data collection vehicle via the network to control the data collection vehicle to collect sensing data of the area boundary.

[0038] Considering that the length of the region boundary is usually quite long, to avoid data loss during the acquisition process, we can first determine the line segment between the start and end positions as the region boundary. Then, the complete line segment can be divided into multiple segments to be detected, and each segment is detected sequentially. For example, ... Figure 2 As shown, after inputting the start position (start) and the end position (end), the boundary between the two positions can be divided, resulting in a region consisting of 30 line segments (e.g., ...). Figure 2 The set of line segments to be detected (shown as the line segments between the solid triangles in the middle).

[0039] Step S104: Control the acquisition vehicle to start driving along the area boundary, and whenever the acquisition vehicle meets the preset detection conditions, determine the current detection progress of the area boundary based on the driving trajectory of the acquisition vehicle. The acquisition vehicle is used to acquire the perception data of the area boundary while driving along the area boundary. The current detection progress is used to represent the proportion of the target line segment among the multiple line segments to be detected. The target line segment is used to represent the line segment for which the acquisition vehicle has successfully acquired perception data.

[0040] The aforementioned data collection vehicle can be an autonomous vehicle or a manually driven vehicle. This vehicle is equipped with various types of sensors, which can perceive the boundary of a region and collect perception data of that boundary. This perception data can be point cloud data collected by lidar sensors, millimeter-wave radar sensors, etc., or image data collected by cameras, fisheye cameras, etc., but is not limited to these. In this embodiment, various types of data are used as examples for illustration.

[0041] Considering that the data collection vehicle can collect sensing data of the area boundary in real time during its journey from the starting point to the ending point, to avoid data loss during real-time collection, the collected sensing data can be verified in real time to determine the data coverage, that is, to determine the detection progress of the area boundary. Given the relatively long length of the area boundary, if verification is performed in real time, the detection progress of the area boundary will not change significantly when the vehicle's travel distance is short, thus wasting computational resources. Therefore, in this embodiment, the detection progress of the area boundary can be determined only after the vehicle meets certain conditions. The aforementioned preset detection conditions can be the travel distance or travel time of the vehicle when the detection progress changes significantly; that is, the preset detection conditions can be the vehicle's travel distance exceeding a distance threshold or the vehicle's travel time exceeding a time threshold, but are not limited to these. The specific values ​​of these two thresholds can be limited according to the actual situation, and this application does not impose such limitations.

[0042] The aforementioned current detection progress can be the progress of the data acquisition vehicle accurately collecting data, that is, the probability of no data loss. Since the area boundary has been divided into multiple line segments to be detected, the current detection progress can be used as the proportion of line segments that have successfully acquired sensing data among the multiple line segments to be detected. For example, the current detection progress can be the ratio of the number of target line segments to the total number of multiple line segments to be detected, or the ratio of the length of the target line segment to the total length of the multiple line segments to be detected, but it is not limited to these.

[0043] In one optional embodiment, after determining the starting and ending positions, the data acquisition vehicle can be controlled to travel along the area boundary. During the travel, the detection progress can be determined each time the data acquisition vehicle meets the preset detection conditions. At this time, the current detection progress of the area boundary can be determined based on the travel trajectory of the data acquisition vehicle. That is, based on the travel trajectory of the data acquisition vehicle, the target line segment for which the data acquisition vehicle has successfully acquired the sensing data can be determined, and then the proportion of the target line segment in the multiple line segments to be detected can be determined to obtain the current detection progress.

[0044] For example, let's take the case where the preset detection condition is that the vehicle's travel distance exceeds a distance threshold (e.g., 2m) as an example. Figure 2 As shown, the data collection vehicle travels from right to left along the area boundary (e.g., ...). Figure 2 After (as shown by the middle arrow), determine the travel distance of the data collection vehicle (e.g., ...). Figure 2If the line segment between the two solid rectangles (shown in the image) reaches 2m, then the detection progress is determined based on the vehicle's trajectory. The vehicle then continues to travel, and the distance traveled by the vehicle relative to the previous detection position is determined to be 10m. If so, a new detection progress is determined again based on the vehicle's trajectory. This process continues until the vehicle has completely collected the perception data of the area boundary or the vehicle has reached the endpoint.

[0045] Optionally, since the vehicle is constantly moving during the data acquisition process, its trajectory is continuously accumulating. If the detection progress is determined based on this trajectory, the calculation becomes redundant, leading to wasted computational resources. To further avoid this waste, the determined detection progress can be stored as historical progress for the next iteration. Based on this historical progress, only the newly acquired line segments need to be identified during the current detection process as target segments. The historical progress is then updated based on the number of target segments to obtain the current detection progress.

[0046] For example, such as Figure 2 As shown, if it is determined that 20 out of 30 line segments have successfully acquired sensing data, that is, 20 line segments are target line segments, then the current detection progress can be determined as: 20 / 30 = 66.67%.

[0047] In step S104, the current detection progress of the output region boundary is displayed.

[0048] In one optional embodiment, the current detection progress can be output via text, images, or voice, facilitating personnel on the data collection vehicle or cloud operators to determine if data loss has occurred. This allows for immediate re-collection of the line segments where data loss has occurred. The text here can be the text corresponding to the current detection progress, such as "66.67%"; the image here can be an image reflecting the current detection progress, such as a progress bar; the voice here can be a voice announcement of the current detection progress, such as "The current detection progress is 66.67%", but is not limited to these.

[0049] For personnel in the data collection vehicle, if they generate input commands by operating the vehicle's central control screen, the current detection progress can be displayed on the screen or played back via the vehicle's speakers. If they generate input commands by operating an app, the current detection progress can be displayed on the app or played back via an electronic device with the app installed. For cloud-based operators, the current detection progress can be displayed on the electronic device they are using or played back via that device.

[0050] Through the above steps, in response to the received input command, a set of line segments to be detected corresponding to the region boundary is constructed based on the start and end positions carried in the input command. Then, the data acquisition vehicle is controlled to start traveling along the region boundary. Whenever the data acquisition vehicle meets the preset detection conditions, the current detection progress of the region boundary is determined based on the vehicle's travel trajectory, and the current detection progress of the region boundary is output, thus achieving the purpose of progress detection in the real-time data acquisition process. It is worth noting that since the current detection progress is executed under the condition that the data acquisition vehicle meets the preset detection conditions, and the current detection progress can be output in real time when it is determined to be lagging, real-time coverage detection of the region boundary can be performed during the perception data acquisition of the region boundary. This facilitates progress reporting to the data acquisition personnel, achieving the technical effect of ensuring the integrity of the acquired data and improving the acquisition efficiency. In turn, it solves the technical problem in related technologies that require repeated acquisition of perception data of the region boundary, resulting in low update efficiency of the region boundary.

[0051] In the above embodiments of this application, determining the current detection progress of the area boundary based on the driving trajectory of the collected vehicle includes: determining a first parameter corresponding to at least one trajectory segment in the driving trajectory based on the driving trajectory of the collected vehicle, wherein the type of the first parameter includes one of the following: vertical direction vector, orientation angle; determining a target line segment from multiple line segments to be detected based on the first parameter corresponding to at least one trajectory segment; and obtaining the current detection progress based on the number of target line segments and the number of multiple line segments to be detected.

[0052] The aforementioned driving trajectory can be the path traveled by the data collection vehicle from the start of its journey until it meets the preset detection conditions. It includes multiple trajectory points, each representing one instance of the vehicle meeting the preset detection conditions. The line segment between two adjacent trajectory points is called a trajectory segment, representing the path traveled by the data collection vehicle between two determined detection progress points. Therefore, the driving trajectory of the data collection vehicle contains one or more trajectory segments.

[0053] During operation, the data acquisition vehicle is typically oriented parallel to the area boundary. Therefore, if a segment of the vehicle's trajectory is parallel to a line segment to be detected, the vehicle can be considered to have successfully acquired the sensing data corresponding to that line segment. Furthermore, considering the limited data acquisition range of the sensors mounted on the vehicle, to ensure successful data acquisition, it is necessary not only to determine whether the trajectory segment and the line segment to be detected are parallel, but also to determine whether the distance between them is less than the sensor's maximum detection distance, i.e., the distance threshold.

[0054] In one optional embodiment, the vertical direction vector corresponding to a trajectory segment can be determined based on the coordinates of the two endpoints of that trajectory segment. Further, it can be determined whether the vertical direction vector intersects with a line segment to be detected, and whether the distance between the trajectory segment and the line segment to be detected is less than a certain value. If they intersect, the trajectory segment is determined to be parallel to the line segment to be detected, and thus the line segment to be detected is identified as the target line segment. If they do not intersect, the trajectory segment is determined to be non-parallel to the line segment to be detected, the vehicle has not successfully acquired the perception data corresponding to the line segment to be detected, and the line segment to be detected is not the target line segment.

[0055] In another optional embodiment, during the generation of a trajectory segment, the orientation angle corresponding to the trajectory segment can be determined, and further, based on the orientation angle, it can be determined whether the trajectory segment is parallel to the line segment to be detected. If they are parallel, the line segment to be detected can be determined to be the target line segment; if they are not parallel, it can be determined that the acquisition vehicle has not successfully acquired the perception data corresponding to the line segment to be detected, and the line segment to be detected is not the target line segment.

[0056] After identifying the target line segments, the ratio of the number of target line segments to the total number of line segments to be detected can be obtained to determine the current detection progress. For example, ... Figure 2 As shown, if 20 out of 30 line segments are identified as target line segments, then the current detection progress can be determined as: 20 / 30 = 66.67%.

[0057] In the above embodiments of this application, when the type of the first parameter includes a vertical direction vector, determining a target line segment from multiple line segments to be detected based on the first parameter corresponding to at least one trajectory segment includes: determining the intersection of the first parameter corresponding to each trajectory segment with each line segment to be detected; determining a first distance between the driving trajectory and the line segment to be detected based on the first parameter corresponding to the trajectory segment; and determining that the line segment to be detected is a target line segment when the first parameter corresponding to the trajectory segment intersects with the line segment to be detected and the first distance is less than a first preset distance.

[0058] The aforementioned first preset distance can be the maximum detection distance of the sensor installed on the vehicle, or it can be the detection distance of the sensor when ensuring that the accuracy of the perception data collected by the sensor meets certain accuracy requirements, but it is not limited to this and can be determined according to actual needs.

[0059] In one optional embodiment, after obtaining the vertical direction vector of a certain trajectory segment, the vertical direction vector can be intersected with each line segment to be detected. The specific judgment process can be implemented using algorithms in related technologies, and this application does not specifically limit it. In addition, the distance between the trajectory segment and the line segment to be detected can be further determined, that is, the first distance mentioned above. If the vertical direction vector intersects with a line segment to be detected, and the first distance is less than a first preset distance, then the line segment to be detected is determined to be the target line segment; if the vertical direction vector does not intersect with a line segment to be detected, or the first distance is greater than the first preset distance, then the line segment to be detected is determined not to be the target line segment.

[0060] In the above embodiments of this application, determining the current detection progress of the area boundary based on the driving trajectory of the acquisition vehicle includes: obtaining the historical detection progress of the area boundary, wherein the historical detection progress is used to characterize the detection progress determined when the acquisition vehicle met the preset detection conditions last time, and the historical detection progress is the preset progress when the acquisition vehicle meets the preset detection conditions for the first time; determining a second parameter of the driving trajectory based on the current trajectory point in the driving trajectory of the acquisition vehicle and a historical trajectory point before the current trajectory point, wherein the second parameter includes one of the following: a vertical direction vector and an orientation angle; determining a target line segment from multiple line segments to be detected based on the second parameter; and adjusting the historical detection progress based on the number of target line segments to obtain the current detection progress.

[0061] The aforementioned historical detection progress can be the detection progress determined by the above method when the vehicle met the preset detection conditions in the last time. When the vehicle meets the preset detection conditions for the first time, since the detection progress has not been determined before, it can be assumed that the vehicle has not yet successfully collected the perception data of the line segment to be detected. Therefore, the historical detection progress at this time can be considered to be 0, which is the aforementioned preset progress, but it is not limited to this.

[0062] In an optional embodiment, considering that the line segments to be detected used to determine the current detection progress may be repeated each time the vehicle meets the preset detection conditions, in order to reduce computational resource consumption and save detection time, historical detection progress can be obtained to avoid repeating the judgment of line segments that have already been judged. Based on this, when the vehicle meets the preset detection conditions, the historical detection progress is first obtained, and a current trajectory segment is constructed based on the current position of the vehicle (i.e., the current trajectory point mentioned above) and the position of the vehicle when it last met the predicted detection conditions (i.e., the historical trajectory point mentioned above). The second parameter of the current trajectory segment is determined, and then the target line segment is determined based on the second parameter using the method of determining the target line segment based on the first parameter in the above embodiment.

[0063] After identifying the target line segments, the historical detection progress can be updated based on the number or length of the target line segments. For example, the current detection progress can be determined based on the proportion of the target line segments among multiple line segments to be detected, and then the sum of the current detection progress and the historical detection progress can be obtained to get the current detection progress. Alternatively, the target line segments identified this time can be summarized with the target line segments in the historical detection progress to determine the total number of target line segments, and the proportion of the total number of target line segments among multiple line segments to be detected can be determined to obtain the current detection progress.

[0064] In the above embodiments of this application, determining a target line segment from multiple line segments to be detected based on a second parameter includes: determining at least one candidate line segment marked with a preset state from the multiple line segments to be detected, wherein the preset state is used to characterize that at least one candidate line segment has not been successfully collected by the acquisition vehicle, and when the acquisition vehicle meets the preset detection conditions for the first time, multiple line segments to be detected are all marked with a preset state; determining a target line segment from at least one candidate line segment based on the second parameter; and clearing the preset state marked for the target line segment.

[0065] The aforementioned candidate line segments can be line segments to be detected marked with a special state. For example, the state of the line segment to be detected can be set to a special value, thereby indicating that the vehicle has not successfully collected perception data for the candidate line segment. The aforementioned clearing of the preset state can clear the aforementioned special state. For example, the state of the line segment to be detected can be set to a preset value, or the state of the line segment to be detected can be not limited, but is not limited thereto. In the embodiments of this application, line segments to be detected that have not successfully collected perception data can be marked as uncovered, and line segments to be detected that have successfully collected perception data can be marked as covered.

[0066] In one optional embodiment, the orientation of the data acquisition vehicle may change during its journey, causing undetected line segments to appear randomly at non-fixed locations. Furthermore, the vehicle can repeatedly acquire data from previously undetected line segments at any time during its journey; therefore, whether a line segment is a target line segment may change during any given assessment.

[0067] Building upon this, to avoid repeatedly judging target line segments, we can mark the line segments to be detected, assigning different states to target and non-target line segments. This allows us to judge only non-target line segments (i.e., those marked with a preset state) during the target line segment determination process. All other line segments to be detected can be considered target line segments. After identifying the target line segment from at least one candidate segment, its preset state can be cleared. For example, during the target line segment determination process, we can judge only the line segments whose state is "uncovered," and after determining that a line segment is a target segment, set its state to "covered."

[0068] In the above embodiments of this application, after controlling the data collection vehicle to start driving along the area boundary, the method further includes: obtaining the current trajectory point of the data collection vehicle; determining a second distance between the current trajectory point and the historical trajectory point of the data collection vehicle; and determining that the data collection vehicle meets the preset detection conditions if the second distance is greater than a second preset distance.

[0069] In one optional embodiment, to avoid wasting computing resources by determining the detection progress in real time, the current position of the data collection vehicle can be determined in real time or periodically during the vehicle's movement. This current position is then compared with the historical trajectory point that previously met the preset detection conditions. The distance between the two trajectory points (i.e., the second distance mentioned above) is calculated. If the second distance is greater than the second preset distance, the data collection vehicle is determined to meet the preset detection conditions, and the detection progress can be determined. If the second distance is less than or equal to the second preset distance, the data collection vehicle is determined not to meet the preset detection conditions, and there is no need to determine the detection progress.

[0070] In the above embodiments of this application, based on the start and end positions carried in the input command, a set of line segments to be detected corresponding to the region boundary is constructed, including: determining whether there is historical sensing data of the region boundary, wherein the historical sensing data includes sensing data of multiple historical detection points; if historical sensing data exists, the multiple historical detection points are clipped based on the start and end positions to obtain a clipped detection point set, and a set of line segments to be detected is constructed based on the clipped detection point set; if there is no historical sensing data, interpolation is performed between the start and end positions to generate a set of line segments to be detected.

[0071] In one optional embodiment, considering that the data collection vehicle will continuously collect sensing data about the area boundary, after receiving the input command, it can first determine whether historical sensing data exists, that is, whether there is a sensing result of the area boundary. This could be a historical vector line of the area boundary (often a sparse curve), which can be stored on the data collection vehicle or in the cloud. If historical sensing data is determined to exist, to improve the accuracy of determining the progress of the current detection, the points on the historical vector line can be clipped based on the start and end positions. Then, the clipped set of detection points can be segmented to obtain trajectory segments of uniform length, thereby constructing a set of line segments to be detected. If no historical sensing data exists, an interpolation process can be performed between the start and end positions to generate a line between them by inserting points. This line can then be segmented to obtain trajectory segments of uniform length, thereby constructing a set of line segments to be detected.

[0072] In the above embodiments of this application, multiple historical detection points are cropped based on the start position and the end position to obtain a cropped set of detection points. This includes: searching among multiple historical detection points based on the start position to determine a first target detection point, wherein the distance between the first target detection point and the start position is less than the distance between the first other detection points and the start position, and the first other detection points are used to represent detection points among multiple historical detection points other than the first target detection point; searching among multiple historical detection points based on the end position to determine a second target detection point, wherein the distance between the second target detection point and the end position is less than the distance between the second other detection points and the end position, and the second other detection points are used to represent detection points among multiple historical detection points other than the second target detection point; determining candidate detection points located between the first target detection point and the second target detection point from among multiple historical detection points; and cropping the detection points among multiple historical detection points other than the candidate detection points to obtain a cropped set of detection points.

[0073] In one optional embodiment, considering that the region boundary is often constantly changing and there is a difference between the historical sensing data and the actual location of the region boundary, the point with the closest horizontal position can be searched near the starting and ending positions to serve as the starting and ending points. The historical detection points outside the starting and ending points in the historical sensing data are then deleted, and only the historical detection points between the starting and ending points are retained as the clipped detection point set. This further reduces the number of line segments to be detected that need to be judged and ensures the accuracy of the retained line segments to be detected.

[0074] In the above embodiments of this application, constructing a set of line segments to be detected based on the clipped set of detection points includes: determining the target spacing between detection points based on the task scenario corresponding to the region boundary; performing interpolation processing on the clipped set of detection points according to the target spacing to generate a set of line segments to be detected; and performing segmentation processing on the line connecting two adjacent detection points in the set of line segments to be detected to obtain a set of line segments to be detected.

[0075] In one optional embodiment, when historical sensing data exists, the clipped set of detection points can be interpolated at certain intervals to obtain the final set of points to be detected. Then, by segmenting the set of points to be detected, a set of line segments to be detected can be obtained. Furthermore, considering that the accuracy requirements for progress detection differ in different work scenarios—for example, the accuracy requirements for progress detection are higher in soil dumping operations and lower in road construction operations—the target interval used in the interpolation process can be determined based on the work scenario. This ensures that the final set of line segments to be detected matches the work scenario and does not affect the execution efficiency or safety of the work.

[0076] In the above embodiments of this application, interpolation processing is performed between the starting position and the ending position to generate a set of line segments to be detected, including: determining the target spacing between detection points based on the task scenario corresponding to the region boundary; performing interpolation processing between the starting position and the ending position according to the target spacing to generate a set of points to be detected; and segmenting the line connecting two adjacent detection points in the set of points to be detected to obtain a set of line segments to be detected.

[0077] In an optional embodiment, if there is no historical sensing data, the technical solution in the above embodiment can still be used to determine the target spacing used in the interpolation process based on the task scenario, thereby ensuring that the final set of line segments to be detected matches the task scenario and does not affect the execution efficiency, security, etc. of the task.

[0078] In the above embodiments of this application, the current detection progress of the output region boundary includes one of the following: displaying the current detection progress of the region boundary in the interactive interface; or playing the current detection progress of the region boundary by voice broadcast.

[0079] In one optional embodiment, the current detection progress can be displayed on the interactive interface by showing text or images. This interactive interface can be the interface on the central control screen of the data acquisition vehicle, where personnel in the vehicle can operate and generate the aforementioned input commands; it can also be the interface displayed on an electronic device used by personnel in the data acquisition vehicle, i.e., an app interface, where personnel in the vehicle can operate and generate the aforementioned input commands; or it can be the interface displayed on an electronic device used by cloud-based operators, such as a webpage, where cloud-based operators can operate and generate the aforementioned input commands.

[0080] In another alternative embodiment, the personnel on the data collection vehicle may not be able to view the interactive interface in a timely manner. In order to enable the personnel to know the current detection progress in a timely manner, the current detection progress can be broadcast through the speaker on the data collection vehicle, or through the speaker of the electronic device used by the personnel on the data collection vehicle, but it is not limited to this.

[0081] In the above embodiments of this application, the method further includes: outputting the historical detection progress of the area boundary when the vehicle does not meet the preset detection conditions.

[0082] In one optional embodiment, if the vehicle being collected does not meet the preset detection conditions, since the current detection progress is no longer determined at this time, the previously determined detection progress, i.e., the historical detection progress, can be directly used as the current detection progress and output, thereby ensuring that the output of the detection progress is real-time and that there will be no problem of the detection progress not being output.

[0083] In the above embodiments of this application, the method further includes: outputting line segments marked with preset states among multiple line segments to be detected; and controlling the acquisition vehicle to re-acquire the perception data of the line segments marked with preset states.

[0084] In one optional embodiment, to avoid the vehicle repeatedly collecting sensing data, the line segments for which sensing data was not successfully collected can be displayed or announced at the same time or after the current detection progress is output. This allows the vehicle to collect sensing data only for the line segments without having to collect data for other line segments, thereby improving the collection efficiency.

[0085] According to an embodiment of the present invention, an embodiment of a device for detecting regional boundaries is provided. It should be noted that the device can be used to perform the above-described method for detecting regional boundaries. Figure 3 This is a schematic diagram of a region boundary detection device according to an embodiment of the present invention, as shown below. Figure 3 As shown, the device includes:

[0086] The construction module 32 is used to respond to the received input instruction and construct a set of line segments to be detected corresponding to the region boundary based on the start position and end position carried in the input instruction. The start position is used to characterize the start of the region boundary, and the end position is used to characterize the end of the region boundary. The multiple line segments to be detected contained in the set of line segments to be detected constitute the region boundary.

[0087] The determination module 34 is used to control the acquisition vehicle to start driving along the area boundary, and whenever the acquisition vehicle meets the preset detection conditions, it determines the current detection progress of the area boundary based on the driving trajectory of the acquisition vehicle. The acquisition vehicle is used to acquire the perception data of the area boundary while driving along the area boundary. The current detection progress is used to represent the proportion of the target line segment among the multiple line segments to be detected. The target line segment is used to represent the line segment for which the acquisition vehicle has successfully acquired perception data.

[0088] Output module 36 is used to output the current detection progress of the region boundary.

[0089] In the above embodiments of this application, the determining module includes: a first determining unit, configured to determine a first parameter corresponding to at least one trajectory segment in the driving trajectory based on the driving trajectory of the collected vehicle, wherein the type of the first parameter includes one of the following: vertical direction vector, orientation angle; a second determining unit, configured to determine a target line segment from multiple line segments to be detected based on the first parameter corresponding to at least one trajectory segment; and a third determining unit, configured to obtain the current detection progress based on the number of target line segments and the number of multiple line segments to be detected.

[0090] In the above embodiments of this application, when the type of the first parameter includes a vertical direction vector, the second determining unit is further configured to: determine the intersection of the first parameter corresponding to each trajectory segment with each line segment to be detected; determine the first distance between the driving trajectory and the line segment to be detected based on the first parameter corresponding to the trajectory segment; and determine that the line segment to be detected is a target line segment when the first parameter corresponding to the trajectory segment intersects with the line segment to be detected and the first distance is less than a first preset distance.

[0091] In the above embodiments of this application, the determining module includes: an acquisition unit, used to acquire the historical detection progress of the area boundary, wherein the historical detection progress is used to characterize the detection progress determined when the vehicle met the preset detection conditions in the last acquisition, and the historical detection progress is the preset progress when the vehicle meets the preset detection conditions for the first time; a fourth determining unit, used to determine a second parameter of the driving trajectory based on the current trajectory point in the driving trajectory of the acquisition vehicle and a historical trajectory point before the current trajectory point, wherein the second parameter includes one of the following: a vertical direction vector and an orientation angle; a fifth determining unit, used to determine a target line segment from multiple line segments to be detected based on the second parameter; and an adjustment unit, used to adjust the historical detection progress based on the number of target line segments to obtain the current detection progress.

[0092] In the above embodiments of this application, the fifth determining unit is further configured to: determine at least one candidate line segment marked with a preset state among a plurality of line segments to be detected, wherein the preset state is used to characterize that at least one candidate line segment has not been successfully collected by the collecting vehicle for sensing data, and when the collecting vehicle meets the preset detection conditions for the first time, the plurality of line segments to be detected are all marked with the preset state; determine the target line segment from at least one candidate line segment based on the second parameter; and clear the preset state marked for the target line segment.

[0093] In the above embodiments of this application, the device further includes: an acquisition module, used to acquire the current trajectory point of the acquisition vehicle after controlling the acquisition vehicle to start driving along the area boundary; a distance determination module, used to determine a second distance between the current trajectory point and the historical trajectory point of the acquisition vehicle; and a condition determination module, used to determine that the acquisition vehicle meets a preset detection condition if the second distance is greater than a second preset distance.

[0094] In the above embodiments of this application, the construction module includes: a sixth determining unit, used to determine whether there is historical sensing data of the regional boundary, wherein the historical sensing data includes sensing data of multiple historical detection points; a first construction unit, used to, in the case of the existence of historical sensing data, trim multiple historical detection points based on the start position and the end position to obtain a trimmed detection point set, and construct a set of line segments to be detected based on the trimmed detection point set; and a second construction unit, used to, in the case of the absence of historical sensing data, perform interpolation processing between the start position and the end position to generate a set of line segments to be detected.

[0095] In the above embodiments of this application, the first construction unit is further configured to: search among multiple historical detection points based on the starting position to determine a first target detection point, wherein the distance between the first target detection point and the starting position is less than the distance between the first other detection points and the starting position, and the first other detection points are used to characterize the detection points among the multiple historical detection points other than the first target detection point; search among multiple historical detection points based on the ending position to determine a second target detection point, wherein the distance between the second target detection point and the ending position is less than the distance between the second other detection points and the ending position, and the second other detection points are used to characterize the detection points among the multiple historical detection points other than the second target detection point; determine candidate detection points located between the first target detection point and the second target detection point from the multiple historical detection points; and prune the detection points among the multiple historical detection points other than the candidate detection points to obtain a pruned set of detection points.

[0096] In the above embodiments of this application, the first construction unit is further configured to: determine the target spacing between detection points based on the task scenario corresponding to the region boundary; perform interpolation processing on the clipped detection point set according to the target spacing to generate a set of detection points; and perform segmentation processing on the line connecting two adjacent detection points in the set of detection points to obtain a set of line segments to be detected.

[0097] In the above embodiments of this application, the second construction unit is further configured to: determine the target spacing between detection points based on the task scenario corresponding to the region boundary; perform interpolation processing between the starting position and the ending position according to the target spacing to generate a set of detection points; and perform segmentation processing on the line connecting two adjacent detection points in the set of detection points to obtain a set of line segments to be detected.

[0098] In the above embodiments of this application, the output module includes one of the following: a display unit, used to display the current detection progress of the region boundary in the interactive interface; and a playback unit, used to play the current detection progress of the region boundary by voice broadcast.

[0099] In the above embodiments of this application, the output module is also used to output the historical detection progress of the area boundary when the vehicle being collected does not meet the preset detection conditions.

[0100] In the above embodiments of this application, the output module is further used to output line segments marked with preset states among multiple line segments to be detected; the device also includes: a control module, used to control the acquisition vehicle to re-acquire the perception data of the line segments marked with preset states.

[0101] Embodiments of this application also provide an electronic device, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of the present invention during runtime.

[0102] Embodiments of this application also provide a computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of the present invention.

[0103] Embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the methods of various embodiments of the present invention.

[0104] Embodiments of this application also provide a computer program product, including a non-volatile computer-readable storage medium for storing a computer program that, when executed by a processor, implements the methods in various embodiments of the present invention.

[0105] Embodiments of this application also provide a computer program that, when executed by a processor, implements the methods described in the various embodiments of the present invention.

[0106] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0107] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0108] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0109] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0110] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, 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. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0111] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method of detecting a region boundary, characterized by, The method comprises: in response to the received input instruction, constructing a set of to-be-detected line segments corresponding to the region boundary based on a start position and an end position carried in the input instruction, wherein the start position is used to represent a start point of the region boundary, the end position is used to represent an end point of the region boundary, and a plurality of to-be-detected line segments included in the set of to-be-detected line segments constitute the region boundary; controlling a collection vehicle to start driving along the region boundary, and determining a current detection progress of the region boundary based on a driving track of the collection vehicle whenever the collection vehicle meets a preset detection condition, wherein the collection vehicle is used to collect perception data of the region boundary in the process of driving along the region boundary, and the current detection progress is used to represent a proportion of a target line segment in the plurality of to-be-detected line segments, wherein the target line segment is used to represent a line segment successfully collected by the collection vehicle, and the target line segment is a to-be-detected line segment parallel to any one of the trajectory segments in the driving track; outputting the current detection progress of the region boundary.

2. The method of claim 1, wherein, The method further comprises: determining a first parameter corresponding to at least one trajectory segment in the driving track of the collection vehicle based on the driving track, wherein the type of the first parameter comprises one of the following: a vertical direction vector and an orientation angle; determining the target line segment from the plurality of to-be-detected line segments based on the first parameter corresponding to the at least one trajectory segment; obtaining the current detection progress based on the number of the target line segments and the number of the plurality of to-be-detected line segments.

3. The method of claim 2, wherein, In a case where the type of the first parameter comprises a vertical direction vector, the method further comprises: performing intersection judgment between the first parameter corresponding to each trajectory segment and each to-be-detected line segment; determining a first distance between the driving track and the to-be-detected line segment based on the first parameter corresponding to the trajectory segment; in a case where the first parameter corresponding to the trajectory segment intersects with the to-be-detected line segment and the first distance is less than a first preset distance, determining that the to-be-detected line segment is the target line segment.

4. The method of claim 1, wherein, The method further comprises: obtaining a historical detection progress of the region boundary, wherein the historical detection progress is used to represent a detection progress determined in a case where the collection vehicle meets the preset detection condition last time, and the historical detection progress is a preset progress in a case where the collection vehicle meets the preset detection condition for the first time; determining a second parameter of the driving track based on a current trajectory point in the driving track of the collection vehicle and a historical trajectory point before the current trajectory point, wherein the second parameter comprises one of the following: a vertical direction vector and an orientation angle; determining the target line segment from the plurality of to-be-detected line segments based on the second parameter. Adjust the historical detection progress based on the number of the target line segments, to obtain the current detection progress.

5. The method of claim 4, wherein, The determining the target line segment from the plurality of to-be-detected line segments based on the second parameter comprises: determining at least one candidate line segment marked with a preset state from the plurality of to-be-detected line segments, wherein the preset state is used to represent that the at least one candidate line segment is not successfully collected by the collection vehicle to perception data, and the plurality of to-be-detected line segments are all marked with the preset state in a case that the collection vehicle meets the preset detection condition for the first time; determining the target line segment from the at least one candidate line segment based on the second parameter; clearing the preset state marked for the target line segment.

6. The method of claim 1, wherein, After controlling the collection vehicle to start driving along the region boundary, the method further comprises: obtaining a current trajectory point of the collection vehicle; determining a second distance between the current trajectory point and a historical trajectory point of the collection vehicle; in a case that the second distance is greater than a second preset distance, determining that the collection vehicle meets the preset detection condition.

7. The method of claim 1, wherein, The constructing a to-be-detected line segment set corresponding to the region boundary based on the start position and the end position carried in the input instruction comprises: determining whether there is historical perception data of the region boundary, wherein the historical perception data contains perception data of a plurality of historical detection points; in a case that there is the historical perception data, performing clipping on the plurality of historical detection points based on the start position and the end position to obtain a clipped detection point set, and constructing the to-be-detected line segment set based on the clipped detection point set; in a case that there is no historical perception data, performing interpolation processing between the start position and the end position to generate the to-be-detected line segment set.

8. The method of claim 7, wherein, The clipping the plurality of historical detection points based on the start position and the end position to obtain a clipped detection point set comprises: searching for a first target detection point in the plurality of historical detection points based on the start position, wherein a distance between the first target detection point and the start position is less than a distance between a first other detection point and the start position, and the first other detection point is used to represent a detection point other than the first target detection point in the plurality of historical detection points; searching for a second target detection point in the plurality of historical detection points based on the end position, wherein a distance between the second target detection point and the end position is less than a distance between a second other detection point and the end position, and the second other detection point is used to represent a detection point other than the second target detection point in the plurality of historical detection points; determining a candidate detection point between the first target detection point and the second target detection point from the plurality of historical detection points; clipping detection points other than the candidate detection point in the plurality of historical detection points to obtain the clipped detection point set.

9. The method of claim 7, wherein, The constructing the to-be-detected line segment set based on the clipped detection point set comprises: Determine a target interval between detection points based on a work task scenario corresponding to the region boundary; Perform interpolation processing on the cropped detection point set according to the target interval to generate a to-be-detected point set; Segment a line between two adjacent detection points in the to-be-detected point set to obtain the to-be-detected line segment set.

10. The method of claim 7, wherein, The interpolation processing between the start point position and the end point position to generate the to-be-detected line segment set includes: Determine a target interval between detection points based on a work task scenario corresponding to the region boundary; Perform interpolation processing between the start point position and the end point position according to the target interval to generate a to-be-detected point set; Segment a line between two adjacent detection points in the to-be-detected point set to obtain the to-be-detected line segment set.

11. The method according to any one of claims 1 to 10, characterized in that, The output of the current detection progress of the region boundary includes one of the following: Display the current detection progress of the region boundary in an interactive interface; Play the current detection progress of the region boundary through voice broadcast.

12. The method according to any one of claims 1 to 10, characterized in that, The method further includes: In the case where the collection vehicle does not meet the preset detection condition, output the historical detection progress of the region boundary.

13. The method according to any one of claims 1 to 10, characterized in that, The method further includes: Output a line segment in the plurality of to-be-detected line segments that is marked with a preset state; Control the collection vehicle to re-collect perception data of the line segment that is marked with the preset state.

14. An apparatus for detecting a region boundary, characterized by It includes: A construction module is configured to, in response to a received input instruction, construct a to-be-detected line segment set corresponding to a region boundary based on a start point position and an end point position carried in the input instruction, wherein the start point position is used to represent a start point of the region boundary, the end point position is used to represent an end point of the region boundary, and a plurality of to-be-detected line segments included in the to-be-detected line segment set constitute the region boundary; A determination module is configured to control a collection vehicle to start driving along the region boundary, and determine a current detection progress of the region boundary based on a driving track of the collection vehicle whenever the collection vehicle meets a preset detection condition, wherein the collection vehicle is configured to collect perception data of the region boundary during driving along the region boundary, and the current detection progress is used to represent a proportion of a target line segment in the plurality of to-be-detected line segments, wherein the target line segment is a line segment successfully collected by the collection vehicle, and the target line segment is a to-be-detected line segment parallel to any one of the track segments in the driving track; An output module is configured to output the current detection progress of the region boundary.

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