Charging port searching method and device, computer device, and storage medium

Abstract

Embodiments of the present application disclose a charging port searching method and device, computer equipment and a storage medium. The method is used for searching a target charging port of a target charging vehicle in a target parking space, a charging cover of the target charging vehicle being in an open state. The method comprises: acquiring a first point cloud image of a region corresponding to the target parking space through a first camera; performing identification processing on a charging port region of the target charging vehicle through a field potential method and the first point cloud image to obtain a charging port region position, the charging port region comprising the charging cover and the target charging port; moving a charging mechanical arm to an image acquisition region corresponding to the charging port region position; acquiring a second point cloud image through a second camera in the charging mechanical arm when the charging mechanical arm is in the image acquisition region; and performing charging port position identification processing on the target charging port according to a preset charging port standard model and the second point cloud image to obtain a target charging port position. The present application can automatically search for a charging port of an electric vehicle.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of artificial intelligence, and in particular to a charging port searching method and device, a computer device and a storage medium. BACKGROUND

[0002] With the increase in the number of electric vehicles, the rapid development of electric vehicles provides new opportunities for the charging facility industry. When a traditional electric vehicle is charging, the docking process of the charging port needs to be completed manually, and improper manual operation may damage the charging port. Manual operation has potential electric shock safety hazards.

[0003] To solve the above problems, an unmanned automatic charging technology for automatically plugging and unplugging a charging gun is needed, and accurately identifying a charging port is a key technology for unmanned automatic charging. In order to realize the unmanned automatic charging technology for automatically plugging and unplugging a charging gun, a method for automatically searching for an electric vehicle charging port is urgently needed. SUMMARY

[0004] The present application provides a charging port searching method and device, a computer device and a storage medium, which can automatically search for a charging port of an electric vehicle.

[0005] In a first aspect, the present application provides a charging port searching method, which is used to search for a target charging port of a target charging vehicle. The target charging vehicle is a to-be-charged vehicle parked in a target parking space, and a charging cover of the target charging vehicle is in an open state. The method comprises the following steps:

[0006] obtaining a first point cloud image of a region corresponding to the target parking space through a first camera;

[0007] performing a charging port region identification process on the target charging vehicle through a preset field potential method and the first point cloud image, to obtain a charging port region position corresponding to the charging port region, wherein the charging port region comprises the charging cover and the target charging port;

[0008] moving a charging mechanical arm to an image acquisition region corresponding to the charging port region position;

[0009] obtaining a second point cloud image through a second camera in the charging mechanical arm when the charging mechanical arm is in the image acquisition region;

[0010] performing a charging port position identification process on the target charging port according to a preset charging port standard model and the second point cloud image, to obtain a target charging port position.

[0011] In some embodiments, the charging port region of the target charging vehicle is identified by the preset field potential method and the first point cloud image, and a charging port region position corresponding to the charging port region is obtained, including:

[0012] The first point cloud image is cropped according to a depth dimension image in the first point cloud image, and a cropped first point cloud image is obtained.

[0013] The point clouds in the transverse dimension image and the longitudinal dimension image in the cropped first point cloud image are traversed to extract a plurality of first transition points.

[0014] According to a preset first transition threshold interval, non-target points in the plurality of first transition points are filtered, and a plurality of candidate transition point sets are obtained by clustering.

[0015] Discrete centers of the plurality of candidate transition point sets are determined.

[0016] The distance values between the transition centers of each candidate transition point set and the discrete centers are calculated respectively.

[0017] According to a preset distance threshold and the distance values respectively corresponding to each candidate transition point set, a target transition point set is determined from the plurality of candidate transition point sets, and a position of the target transition point set is determined as the charging port region position.

[0018] In some embodiments, the target transition point set is determined from the plurality of candidate transition point sets according to the preset distance threshold and the distance values respectively corresponding to each candidate transition point set, including:

[0019] The candidate transition point sets whose distance values are greater than the distance threshold are filtered from the plurality of candidate transition point sets, and a filtered candidate transition point set is obtained.

[0020] If there are a plurality of filtered candidate transition point sets, the filtered candidate transition point set with the largest number of transition points is determined as the target transition point set.

[0021] If there is only one filtered candidate transition point set, the filtered candidate transition point set is determined as the target transition point set.

[0022] In some embodiments, the target charging port position is obtained by performing charging port position identification processing on the target charging port according to a preset charging port standard model and the second point cloud image, including:

[0023] A charging port center position in a depth dimension image of the second point cloud image is determined according to a scalable 2D model of the charging port standard model and a depth dimension image in the second point cloud image.

[0024] constructing a charging port target search area in a depth dimension image of the second point cloud image with a preset area size, centered on the charging port center position;

[0025] extracting a charging port contour from the charging port target search area according to a preset charging port depth threshold;

[0026] mapping the charging port contour to corresponding point clouds in the second point cloud image to convert the charging port contour into a 3D object model;

[0027] finding the charging port standard model in the 3D object model and determining a model center of the charging port standard model in the 3D object model;

[0028] determining a position corresponding to the model center as the target charging port position.

[0029] In some embodiments, after the target charging port position is obtained by performing the charging port position identification processing on the target charging port according to the preset charging port standard model and the second point cloud image, the method further comprises:

[0030] determining a target spatial position coordinate of the charging port relative to the charging robot arm according to a preset coordinate conversion relationship between the camera and the robot arm and the target charging port position;

[0031] generating a motion path of the charging robot arm according to the target spatial position coordinate;

[0032] controlling the charging robot arm to move to the target charging port position through the motion path to perform a charging operation on the target charging vehicle.

[0033] In some embodiments, before the first point cloud image of the target parking space corresponding area is obtained by the first camera, the method further comprises:

[0034] obtaining a third point cloud image of the target parking space corresponding area by the first camera;

[0035] determining a projection angle between a vehicle body of the target charging vehicle and a parking line of the target parking space through the third point cloud image;

[0036] adjusting an image acquisition angle of the first camera according to the projection angle.

[0037] In some embodiments, the projection angle between the vehicle body of the target charging vehicle and the parking line of the target parking space is determined through the third point cloud image, comprising:

[0038] According to a depth dimension image in the third point cloud image, the third point cloud image is cropped to obtain a cropped third point cloud image;

[0039] Points in a lateral dimension image in the cropped third point cloud image are traversed to extract a plurality of second transition points;

[0040] According to a preset second transition threshold interval, the plurality of second transition points are filtered to obtain a plurality of filtered second transition points;

[0041] The plurality of filtered second transition points are subjected to linear fitting processing to obtain a fitted straight line;

[0042] The fitted straight line is mapped to the third point cloud image to obtain a spatial fitted straight line, and the spatial fitted straight line is a vehicle body of the target charging vehicle;

[0043] The parking space line in the third point cloud image is identified;

[0044] By a preset inverse perspective method and projection principle, the projection angle between the spatial fitted straight line and the parking space line is calculated.

[0045] In a second aspect, the embodiments of the present application further provide a charging port searching device, which is used for searching a target charging port of a target charging vehicle, the target charging vehicle is a to-be-charged vehicle parked in a target parking space, and a charging cover of the target charging vehicle is in an open state, and the charging port searching device comprises:

[0046] A transceiving unit is configured to acquire a first point cloud image of a region corresponding to the target parking space by a first camera;

[0047] A processing unit is configured to perform identification processing on a charging port region of the target charging vehicle by a preset field potential method and the first point cloud image to obtain a charging port region position corresponding to the charging port region, the charging port region comprises the charging cover and the target charging port, and move a charging mechanical arm to an image acquisition region corresponding to the charging port region position;

[0048] The transceiving unit is further configured to acquire a second point cloud image by a second camera in the charging mechanical arm when the charging mechanical arm is in the image acquisition region;

[0049] The processing unit is further configured to perform charging port position identification processing on the target charging port according to a preset charging port standard model and the second point cloud image to obtain a target charging port position.

[0050] In a third aspect, the embodiments of the present application further provide a computer device, which comprises a memory and a processor, the memory stores a computer program, and the processor implements the above method when executing the computer program.

[0051] In a fourth aspect, the embodiments of the present application further provide a computer readable storage medium, which stores a computer program, the computer program comprises program instructions, and the program instructions can implement the above method when executed by a processor.

[0052] The embodiments of the present application provide a charging port searching method and device, a computer device and a storage medium. The method is used for searching a target charging port of a target charging vehicle, the target charging vehicle is a to-be-charged vehicle parked in a target parking space, and a charging cover of the target charging vehicle is in an open state. The method comprises the following steps: acquiring a first point cloud image of a region corresponding to the target parking space through a first camera; performing identification processing on a charging port region of the target charging vehicle through a preset field potential method and the first point cloud image to obtain a charging port region position corresponding to the charging port region, the charging port region comprising the charging cover and the target charging port; moving a charging mechanical arm to an image acquisition region corresponding to the charging port region position; acquiring a second point cloud image through a second camera in the charging mechanical arm when the charging mechanical arm is in the image acquisition region; and performing charging port position identification processing on the target charging port according to a preset charging port standard model and the second point cloud image to obtain a target charging port position. The embodiments of the present application first perform coarse positioning on the charging port through the field potential method to obtain the charging port region position, and then perform accurate positioning on the charging port based on the image re-acquired based on the charging port region position, so as to obtain an accurate charging port position. BRIEF DESCRIPTION OF DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiment description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0054] Figure 1 A flowchart of the charging port searching method provided by the embodiments of the present application is shown in the figure.

[0055] Figure 2 An image diagram of the charging port searching process in the charging port searching method provided by the embodiments of the present application is shown in the figure.

[0056] Figure 3 Another image diagram of the charging port searching process in the charging port searching method provided by the embodiments of the present application is shown in the figure.

[0057] Figure 4 Another image schematic diagram of the charging port searching process in the charging port searching method provided by the embodiment of the present application is shown in FIG. 6;

[0058] Figure 5 A sub-flow schematic diagram of the charging port searching method provided by the embodiment of the present application is shown in FIG. 7;

[0059] Figure 6 Another image schematic diagram of the charging port searching process in the charging port searching method provided by the embodiment of the present application is shown in FIG. 6;

[0060] Figure 7 Another sub-flow schematic diagram of the charging port searching method provided by the embodiment of the present application is shown in FIG. 8;

[0061] Figure 8 Another image schematic diagram of the charging port searching process in the charging port searching method provided by the embodiment of the present application is shown in FIG. 6;

[0062] Figure 9 Another image schematic diagram of the charging port searching process in the charging port searching method provided by the embodiment of the present application is shown in FIG. 6;

[0063] Figure 10 A schematic block diagram of the charging port searching device provided by the embodiment of the present application is shown in FIG. 9;

[0064] Figure 11 A schematic block diagram of the computer device provided by the embodiment of the present application is shown in FIG. 10. DETAILED DESCRIPTION

[0065] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0066] It should be understood that, when used in the specification and the appended claims, the terms "comprise" and "include" indicate the presence of described features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0067] It should also be understood that the terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and the appended claims of the present application, the singular forms "a", "an" and "the" are intended to include the plural forms, unless the context clearly indicates otherwise.

[0068] It should be further understood that the term "and / or" used in the description and claims of the application means one or more of the associated listed items as well as all possible combinations of the items and includes these combinations.

[0069] The embodiments of the present application provide a charging port searching method and device, computer equipment and a storage medium.

[0070] The execution subject of the charging port searching method can be a charging port searching device provided by the embodiments of the present application, or a computer equipment integrated with the charging port searching device, wherein the charging port searching device can be realized in the form of hardware or software, and the computer equipment can be a terminal or a server.

[0071] Specifically, the computer equipment is in communication connection with the control of the first camera, the second camera and the charging mechanical arm. The first camera and the second camera can be the same camera, or can be different cameras. When they are different cameras, the second camera is arranged on the charging mechanical arm, while the first camera can be arranged on the charging mechanical arm or separated from the charging mechanical arm. At this time, it can be arranged in a region capable of acquiring a target parking space image. When the first camera is separated from the charging mechanical arm, the first camera can be responsible for image acquisition of one or more charging parking spaces. At this time, the first camera is a large field of view 3D camera, which can observe objects within 0.3-20m, and the second camera is a high-precision 3D camera.

[0072] When the first camera and the second camera are the same camera, the camera is arranged on the charging mechanical arm. At this time, the camera is a 3D camera that takes into account both large field of view and high precision.

[0073] The charging port searching method provided by the embodiments of the present application is used to search for a target charging port of a target charging vehicle, the target charging vehicle is a to-be-charged vehicle parked in a target parking space, and a charging cover of the target charging vehicle is in an open state. At this time, after a user parks the target charging vehicle into the target parking space and opens the charging cover, the computer equipment provided by the embodiments of the present application can automatically identify the position of the target charging port in the target charging vehicle, so as to control the charging mechanical arm to aim the charging gun at the target charging vehicle based on the position of the target charging port, and perform automatic plug and unplug operations of the charging gun on the target charging vehicle. The user does not need to operate the charging gun, thereby avoiding the problems of damage to the charging port caused by improper manual operation and the safety hazard of electric shock caused by manual operation.

[0074] Figure 1 is a flowchart of the charging port searching method provided by the embodiments of the present application. As shown in Figure 1 the method comprises the following steps S110-S150.

[0075] S110, acquire a first point cloud image of the target parking space corresponding area through the first camera.

[0076] In this embodiment, when it is detected that the target parking space is parked with a target charging vehicle, and a charging instruction for the target charging vehicle in the target parking space is received, the computer device acquires a first point cloud image of the target parking space corresponding area through the first camera.

[0077] In some embodiments, in order to improve the acquisition accuracy of the first point cloud image, the first camera of the present application first determines the angle between the vehicle and the parking line before acquiring the first point cloud image, and then adjusts the collection angle of the first camera based on the angle. When the first camera is located on the charging mechanical arm (such as the end of the mechanical arm), the charging mechanical arm is adjusted by adjusting the angle of the charging mechanical arm. Specifically, before step S110, the method further comprises: acquiring a third point cloud image of the target parking space corresponding area through the first camera; determining the projection angle between the body of the target charging vehicle and the parking line of the target parking space through the third point cloud image; and adjusting the image collection angle of the first camera according to the projection angle.

[0078] The third point cloud image is processed by cropping according to the depth dimension image in the third point cloud image to obtain a cropped third point cloud image; the point cloud in the transverse dimension image in the cropped third point cloud image is traversed to extract a plurality of second transition points; the plurality of second transition points are filtered according to a preset second transition threshold interval to obtain a plurality of filtered second transition points; the plurality of filtered second transition points are subjected to straight line fitting processing to obtain a fitting straight line; the fitting straight line is mapped into the third point cloud image to obtain a spatial fitting straight line, and the spatial fitting straight line is the body of the target charging vehicle; the parking line in the third point cloud image is identified; and the projection angle between the spatial fitting straight line and the parking line is calculated through a preset inverse perspective method and projection principle.

[0079] The third point cloud image is processed by cropping according to the depth dimension image in the third point cloud image to obtain a cropped third point cloud image; the point cloud in the transverse dimension image in the cropped third point cloud image is traversed to extract a plurality of second transition points; the plurality of second transition points are filtered according to a preset second transition threshold interval to obtain a plurality of filtered second transition points; the plurality of filtered second transition points are subjected to straight line fitting processing to obtain a fitting straight line; the fitting straight line is mapped into the third point cloud image to obtain a spatial fitting straight line, and the spatial fitting straight line is the body of the target charging vehicle; the parking line in the third point cloud image is identified; and the projection angle between the spatial fitting straight line and the parking line is calculated through a preset inverse perspective method and projection principle.

[0080] Specifically, there is a preset depth interval of the target charging vehicle in the target parking space, and the point cloud data outside the depth interval is deleted to obtain a cropped third point cloud image (the cropped image is as shown in Figure 2 The transition data is traversed according to the transverse dimension in the cropped third point cloud image corresponding area, the area image gradient is calculated, and the transition point (such as Figure 3As shown, the red dots are transition points), and then high and low thresholds are set to filter the extracted points, filter out the discrete points, highlight the image edges, and then use the least squares method to fit a straight line (the fitted straight line is shown in FIG. 6C). Figure 4 As shown, the red dots are transition points), and then high and low thresholds are set to filter the extracted points, filter out the discrete points, highlight the image edges, and then use the least squares method to fit a straight line (the fitted straight line is shown in FIG. 6C).

[0081] The projection angle is a quantitative measure of the degree of vehicle "parking deviation", and in combination with the projection angle of the vehicle and the known general size model of the vehicle, the three-dimensional spatial coordinate range of the "charging port approximate area" in the robot coordinate system can be further estimated to adjust the position of the first camera to obtain a first point cloud image with higher precision.

[0082] In other implementations, the degree of vehicle "parking deviation" (projection angle) can also be determined by judging the positions of the front and rear wheels of the target charging vehicle. Specifically, a fourth point cloud image of the target parking space corresponding region is obtained through the first camera; the same side front and rear wheel center points of the target charging vehicle are determined through the fourth point cloud image, and the identified front and rear wheel center points are connected to obtain the actual parking axis of the vehicle, and then the actual parking axis is compared with the standard direction of the charging pile connecting line or the suspension rail or other fixed reference object to calculate the parking deflection angle (projection angle) of the vehicle.

[0083] The step of calculating the vehicle "parking deviation" by the positions of the front and rear wheels can be performed after the "parking line" is not identified through the third point cloud image, or can be directly performed (i.e., without performing the vehicle "parking deviation" calculation through the "parking line").

[0084] This scheme completely relies on the visual recognition capability of the first camera and does not rely on the specific identification of the parking line, thereby ensuring that the parking deflection angle of the target charging vehicle can be accurately obtained in various parking lot environments.

[0085] Further, the first camera is used to obtain a fifth point cloud image, and the distance between the target charging vehicle and the adjacent vehicle or other obstacles is determined based on the fifth point cloud image. If the distance is less than a predetermined safety threshold (such as 0.5 meters), the subsequent operation is suspended and an alarm is issued to ensure the charging operation space of the mechanical arm. Otherwise, if the distance meets the requirements, the next step is allowed to be performed, and step S120 is entered.

[0086] S120, the charging port area of the target charging vehicle is identified through a preset field potential method and the first point cloud image to obtain a charging port area position corresponding to the charging port area, and the charging port area includes the charging cover and the target charging port.

[0087] In some embodiments, as shown in Figure 5 Step S120 includes:

[0088] S1201, cropping the first point cloud image according to a depth dimension image in the first point cloud image to obtain a cropped first point cloud image;

[0089] S1202, traversing point clouds in a lateral dimension image and a longitudinal dimension image in the cropped first point cloud image to extract a plurality of first transition points;

[0090] S1203, filtering non-target points in the plurality of first transition points according to a preset first transition threshold interval, and obtaining a plurality of candidate transition point sets through clustering;

[0091] S1204, determining discrete centers of the plurality of candidate transition point sets;

[0092] S1205, respectively calculating distance values between transition centers of each candidate transition point set and the discrete centers;

[0093] S1206, determining a target transition point set from the plurality of candidate transition point sets according to a preset distance threshold and the distance values respectively corresponding to each candidate transition point set, and determining a position of the target transition point set as the charging port region position.

[0094] In some embodiments, the determining of the target transition point set from the plurality of candidate transition point sets according to the preset distance threshold and the distance values respectively corresponding to each candidate transition point set includes:

[0095] filtering candidate transition point sets with distance values greater than the distance threshold in the plurality of candidate transition point sets to obtain filtered candidate transition point sets; if there are a plurality of filtered candidate transition point sets, the filtered candidate transition point set with the most transition points is determined as the target transition point set; if there is only one filtered candidate transition point set, the filtered candidate transition point set is determined as the target transition point set.

[0096] Specifically, the collected first point cloud image is disassembled into a lateral dimension image, a longitudinal dimension image, and a depth dimension image, and then the first point cloud image is cropped based on the depth dimension image to reduce the amount of calculation. Specifically, a depth interval of a target charging vehicle in a target parking space can be preset, and then point cloud data outside the depth interval in the depth dimension image is deleted. Then, transition data is traversed in the cropped region according to the lateral and longitudinal dimensions to extract transition points (e.g., the transition points in FIG. 4). Figure 6As shown, the color points around the charging cover are transition points, and the final extracted transition points can also be the transition points corresponding to the charging port. Here, only the transition points corresponding to the charging cover are taken as an example for illustration), and based on a pre-set first transition threshold interval (such as a depth change of less than 20 cm of the transition point), non-target points caused by factors such as tires are filtered out, and then a plurality of candidate transition point sets are obtained by clustering, and the transition point set is extracted, the transition center of each transition point set is extracted, the distance between each transition center and the discrete center is calculated, and finally a high and low threshold is set to filter out the discrete points, and the relatively concentrated point set is reserved, and the point set region center is determined as the center of the charging port region position.

[0097] S130, moving the charging robot arm to an image acquisition region corresponding to the charging port region position.

[0098] The image acquisition region is located near the charging port region position, and when the charging robot arm is in the image acquisition region, the second camera is directly opposite the charging port region position.

[0099] S140, when the charging robot arm is in the image acquisition region, acquiring a second point cloud image through the second camera in the charging robot arm.

[0100] When the charging robot arm is in the image acquisition region, the image of the charging port is acquired by the second camera, which improves the charging port recognition accuracy.

[0101] S150, performing charging port position recognition processing on the target charging port according to a pre-set charging port standard model and the second point cloud image to obtain a target charging port position.

[0102] In some embodiments, as Figure 7 As shown, step S150 includes:

[0103] S1501, determining a charging port center position in a depth dimension image of the second point cloud image according to a scalable 2D model of the charging port standard model and the depth dimension image in the second point cloud image;

[0104] S1502, constructing a charging port target search region in the depth dimension image of the second point cloud image with the charging port center position as the center and with a pre-set region size;

[0105] S1503, extracting a charging port contour from the charging port target search region according to a pre-set charging port depth threshold;

[0106] S1504, mapping the charging port contour to the corresponding point cloud in the second point cloud image to convert the charging port contour into a 3D object model;

[0107] S1505, searching for the charging port standard model in the 3D object model, and determining the model center of the charging port standard model in the 3D object model;

[0108] S1506, determining the position corresponding to the model center as the target charging port position.

[0109] Specifically, the charging port standard model is as shown in Figure 8 The model only retains the common features of various vehicle fast charging ports. Since direct full-image searching in 3D space is very time-consuming, the embodiment first performs fast coarse positioning on a 2D depth image (determining the charging port center position in the depth dimension image of the second point cloud image according to the scalable 2D model of the charging port standard model and the depth dimension image in the second point cloud image, as shown in Figure 9 Figure 9 The color part is the charging port position matched in coarse positioning), and specifically, the similarity (such as the correlation coefficient) under each position and each scaling ratio can be calculated, and then the position and scaling ratio with the highest similarity are found. The center point of the position is the center coordinate of the charging port in the 2D image, that is, the charging port center position (2D center point) in the depth dimension image. Then, a region is drawn based on the 2D center point (for example, a cuboid region of interest with a side length of 5 cm is created). All subsequent 3D processing operations will only be performed on the point cloud in this region, rather than all point cloud data, thereby reducing the amount of calculation. Then, since the charging port is recessed, the depth value is different from that of the vehicle body. At this time, the depth threshold of the charging port can be set to extract the charging port contour, and then the points of the charging port contour extracted in the previous step are mapped from the 2D image coordinates back to their original 3D coordinates to form a 3D object model that only belongs to the recessed part of the charging port. Finally, the charging port standard model is searched (matched) in the generated 3D object model, and the position corresponding to the model center of the charging port standard model in the 3D object model is determined as the target charging port position.

[0110] After obtaining the target charging port position, a rigid affine transformation or the like is performed to calculate the spatial coordinates of the model center relative to the robot, and the charging robot is driven based on the spatial coordinates to perform a charging operation on the target charging vehicle. Specifically, after obtaining the target charging port position, the method further includes: determining the target spatial position coordinates of the charging port relative to the charging robot according to a preset coordinate conversion relationship between the camera and the robot and the target charging port position; generating a motion path of the charging robot according to the target spatial position coordinates; controlling the charging robot to move to the target charging port position through the motion path to perform a charging operation on the target charging vehicle.

[0111] ​To sum up, the method provided by the embodiment of the present application is used for searching a target charging port of a target charging vehicle, the target charging vehicle is a to-be-charged vehicle parked in a target parking space, and a charging cover of the target charging vehicle is in an open state. The method comprises the following steps: acquiring a first point cloud image of a region corresponding to the target parking space through a first camera; performing identification processing on a charging port region of the target charging vehicle through a preset field potential method and the first point cloud image to obtain a charging port region position corresponding to the charging port region, the charging port region comprising the charging cover and the target charging port; moving a charging mechanical arm to an image acquisition region corresponding to the charging port region position; acquiring a second point cloud image through a second camera in the charging mechanical arm when the charging mechanical arm is in the image acquisition region; and performing charging port position identification processing on the target charging port according to a preset charging port standard model and the second point cloud image to obtain a target charging port position. The embodiment of the present application firstly performs coarse positioning on the charging port through the field potential method to obtain the charging port region position, and then performs accurate positioning on the charging port based on the image re-acquired based on the charging port region position, so that an accurate charging port position is obtained.

[0112] Figure 10 is a schematic block diagram of a charging port searching device provided by the embodiment of the present application. As shown in Figure 10 corresponding to the above charging port searching method, the present application further provides a charging port searching device 1000. The charging port searching device 1000 comprises units for executing the above charging port searching method. The charging port searching device 1000 can be configured in a terminal or a server, and is used for searching a target charging port of a target charging vehicle, the target charging vehicle being a to-be-charged vehicle parked in a target parking space, and a charging cover of the target charging vehicle being in an open state. Specifically, please refer to Figure 10 , the charging port searching device 1000 comprises a transceiver unit 1001 and a processing unit 1002, wherein:

[0113] The transceiver unit 1001 is used for acquiring a first point cloud image of a region corresponding to the target parking space through a first camera.

[0114] The processing unit 1002 is used for performing identification processing on a charging port region of the target charging vehicle through a preset field potential method and the first point cloud image to obtain a charging port region position corresponding to the charging port region, the charging port region comprising the charging cover and the target charging port; and moving a charging mechanical arm to an image acquisition region corresponding to the charging port region position.

[0115] The transceiver unit 1001 is further used for acquiring a second point cloud image through a second camera in the charging mechanical arm when the charging mechanical arm is in the image acquisition region.

[0116] The processing unit 1002 is further configured to perform charging port position identification processing on the target charging port according to a preset charging port standard model and the second point cloud image, to obtain a target charging port position.

[0117] In some embodiments, when performing the step of identifying the charging port area of the target charging vehicle according to the preset field potential method and the first point cloud image to obtain a charging port area position corresponding to the charging port area, the processing unit 1002 is specifically configured to:

[0118] perform cropping processing on the first point cloud image according to a depth dimension image in the first point cloud image, to obtain a cropped first point cloud image;

[0119] perform traversal on point clouds in a lateral dimension image and a longitudinal dimension image in the cropped first point cloud image, to extract a plurality of first transition points;

[0120] filter non-target points in the plurality of first transition points according to a preset first transition threshold interval, and obtain a plurality of candidate transition point sets through clustering;

[0121] determine discrete centers of the plurality of candidate transition point sets;

[0122] calculate distance values between transition centers of each candidate transition point set and the discrete centers, respectively;

[0123] determine a target transition point set from the plurality of candidate transition point sets according to a preset distance threshold and the distance values respectively corresponding to each candidate transition point set, and determine a position of the target transition point set as the charging port area position.

[0124] In some embodiments, when performing the step of determining a target transition point set from the plurality of candidate transition point sets according to a preset distance threshold and the distance values respectively corresponding to each candidate transition point set, the processing unit 1002 is specifically configured to:

[0125] filter candidate transition point sets with distance values greater than the distance threshold from the plurality of candidate transition point sets, to obtain filtered candidate transition point sets;

[0126] if there are a plurality of filtered candidate transition point sets, determine a filtered candidate transition point set with the largest number of transition points from the plurality of filtered candidate transition point sets as the target transition point set;

[0127] if there is only one filtered candidate transition point set, determine the filtered candidate transition point set as the target transition point set.

[0128] In some embodiments, the processing unit 1002, in the step of performing the charging port position recognition processing on the target charging port according to the preset charging port standard model and the second point cloud image, is specifically configured to:

[0129] determine a charging port center position in a depth dimension image of the second point cloud image according to the scalable 2D model of the charging port standard model and the depth dimension image in the second point cloud image;

[0130] construct a charging port target search area in the depth dimension image of the second point cloud image with the charging port center position as the center and with a preset area size;

[0131] extract a charging port contour from the charging port target search area according to a preset charging port depth threshold;

[0132] map the charging port contour to corresponding point clouds in the second point cloud image to convert the charging port contour into a 3D object model;

[0133] find the charging port standard model in the 3D object model and determine a model center of the charging port standard model in the 3D object model;

[0134] determine a position corresponding to the model center as the target charging port position.

[0135] In some embodiments, the processing unit 1002, after the step of performing the charging port position recognition processing on the target charging port according to the preset charging port standard model and the second point cloud image, is further configured to:

[0136] determine a target space position coordinate of the charging port relative to the charging robot arm according to a preset coordinate conversion relationship between the camera and the robot arm and the target charging port position;

[0137] generate a motion path of the charging robot arm according to the target space position coordinate;

[0138] control the charging robot arm to move to the target charging port position through the motion path to perform a charging operation on the target charging vehicle.

[0139] In some embodiments, the transceiver unit 1001, before the step of acquiring the first point cloud image of the target parking space corresponding area through the first camera, is further configured to:

[0140] acquire a third point cloud image of the target parking space corresponding area through the first camera;

[0141] The processing unit 1002 determines a projection angle between a body of the target charging vehicle and a parking line of the target parking space through the third point cloud image; and adjusts an image collection angle of the first camera according to the projection angle.

[0142] In some embodiments, when performing the step of determining the projection angle between the body of the target charging vehicle and the parking line of the target parking space through the third point cloud image, the processing unit 1002 is specifically configured to:

[0143] cropping the third point cloud image according to a depth dimension image in the third point cloud image to obtain a cropped third point cloud image;

[0144] traversing point clouds in a lateral dimension image in the cropped third point cloud image to extract a plurality of second transition points;

[0145] filtering the plurality of second transition points according to a preset second transition threshold interval to obtain a plurality of filtered second transition points;

[0146] performing linear fitting processing on the plurality of filtered second transition points to obtain a fitting straight line;

[0147] mapping the fitting straight line into the third point cloud image to obtain a spatial fitting straight line, the spatial fitting straight line being the body of the target charging vehicle;

[0148] recognizing the parking line in the third point cloud image;

[0149] calculating the projection angle between the spatial fitting straight line and the parking line through a preset inverse perspective method and projection principle.

[0150] In summary, the embodiments of the present application first coarsely locate the charging port through the field potential method to obtain the position of the charging port region, and then accurately position the charging port based on the image re-collected based on the position of the charging port region, so as to obtain the accurate position of the charging port.

[0151] It should be noted that those skilled in the art can clearly understand the specific implementation process of the above charging port searching device 1000 and each unit, which can refer to the corresponding description in the foregoing method embodiments. For the convenience and brevity of description, it will not be repeated here.

[0152] The charging port searching device 1000 described above can be implemented in the form of a computer program, which can run on a computer device as shown in Figure 11 .

[0153] Please refer to Figure 11 ,Figure 11 is a schematic block diagram of a computer device provided by an embodiment of the present application. The computer device 1100 can be a terminal or a server, wherein the computer device 1100 is configured to search for a target charging port of a target charging vehicle, the target charging vehicle being a to-be-charged vehicle parked in a target parking space, and a charging cover of the target charging vehicle being in an open state.

[0154] Referring to Figure 11 The computer device 1100 includes a processor 1102, a memory, and a network interface 1105 connected through a system bus 1101, wherein the memory can include a non-volatile storage medium 1103 and an internal memory 1104.

[0155] The non-volatile storage medium 1103 can store an operating system 11031 and a computer program 11032. The computer program 11032 includes program instructions which, when executed, can cause the processor 1102 to perform a charging port search method.

[0156] The processor 1102 is configured to provide computing and control capabilities to support the operation of the entire computer device 1100.

[0157] The internal memory 1104 provides an environment for the execution of the computer program 11032 in the non-volatile storage medium 1103, which, when executed by the processor 1102, can cause the processor 1102 to perform a charging port search method.

[0158] The network interface 1105 is configured to perform network communication with other devices. Those skilled in the art can understand that Figure 11 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device 1100 to which the scheme of the present application is applied. The specific computer device 1100 can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0159] The processor 1102 is configured to run the computer program 11032 stored in the memory to implement the following steps:

[0160] obtain a first point cloud image of the target parking space corresponding region through the first camera;

[0161] perform charging port region identification processing on the target charging vehicle through a preset field potential method and the first point cloud image to obtain a charging port region position corresponding to the charging port region, the charging port region including the charging cover and the target charging port;

[0162] move the charging mechanical arm to an image acquisition area corresponding to the charging port area position;

[0163] acquire a second point cloud image through a second camera in the charging mechanical arm when the charging mechanical arm is in the image acquisition area;

[0164] perform charging port position identification processing on the target charging port according to a preset charging port standard model and the second point cloud image, to obtain a target charging port position.

[0165] It should be understood that, in the embodiments of the present application, the processor 1102 can be a central processing unit (CPU), and the processor 1102 can also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0166] It can be understood by those skilled in the art that all or part of the processes in the above-mentioned embodiments can be completed by a computer program instructing related hardware. The computer program includes program instructions, and the computer program can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the above-mentioned embodiments.

[0167] Therefore, the present application also provides a storage medium. The storage medium can be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. The program instructions are executed by the processor to make the processor perform the following steps:

[0168] acquire a first point cloud image of an area corresponding to the target parking space through the first camera;

[0169] perform identification processing on the target charging vehicle through a preset field potential method and the first point cloud image to obtain a charging port area position corresponding to the charging port area, and the charging port area includes the charging cover and the target charging port;

[0170] move the charging mechanical arm to an image acquisition area corresponding to the charging port area position;

[0171] When the charging robot arm is in the image acquisition area, a second point cloud image is acquired by a second camera in the charging robot arm.

[0172] According to a preset charging port standard model and the second point cloud image, a target charging port position is recognized to obtain a target charging port position.

[0173] The storage medium can be a U disk, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk, and various computer readable storage media that can store program codes.

[0174] Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been described in the above description in general terms. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0175] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. For example, the apparatus embodiments described above are only schematic. For example, the division of each unit is only a logical function division, and actual implementation can have another division manner. For example, a plurality of units or components can be combined or integrated into another system, or some features can be omitted or not executed.

[0176] The steps in the method embodiments of the present application can be adjusted, combined and reduced in sequence according to actual needs. The units in the apparatus embodiments of the present application can be combined, divided and reduced according to actual needs. In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit.

[0177] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a storage medium. Based on such an understanding, the technical solutions of the present application essentially or say the part that contributes to the prior art, or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application.

[0178] The above merely provides a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present application, and these modifications or replacements shall be encompassed within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A charging port search method characterized by comprising: The method is used for searching a target charging port of a target charging vehicle, the target charging vehicle is a to-be-charged vehicle parked in a target parking space, and a charging cover of the target charging vehicle is in an open state. The method comprises the following steps: obtaining a first point cloud image of a region corresponding to the target parking space through a first camera; performing charging port region identification processing on the target charging vehicle through a preset field potential method and the first point cloud image to obtain a charging port region position corresponding to a charging port region of the target charging vehicle, wherein the charging port region comprises the charging cover and the target charging port; moving a charging mechanical arm to an image acquisition region corresponding to the charging port region position; obtaining a second point cloud image through a second camera in the charging mechanical arm when the charging mechanical arm is in the image acquisition region; performing charging port position identification processing on the target charging port according to a preset charging port standard model and the second point cloud image to obtain a target charging port position; the method for searching a target charging port of a target charging vehicle, the target charging vehicle is a to-be-charged vehicle parked in a target parking space, and a charging cover of the target charging vehicle is in an open state. The method comprises the following steps: performing cropping processing on the first point cloud image according to a depth dimension image in the first point cloud image to obtain a cropped first point cloud image; performing traversal on point clouds in a horizontal dimension image and a vertical dimension image in the cropped first point cloud image to extract a plurality of first transition points; filtering non-target points in the plurality of first transition points according to a preset first transition threshold interval, and obtaining a plurality of candidate transition point sets through clustering; determining discrete centers of the plurality of candidate transition point sets; respectively calculating distance values between transition centers of each candidate transition point set and the discrete centers; determining a target transition point set from the plurality of candidate transition point sets according to a preset distance threshold and the distance values respectively corresponding to each candidate transition point set, and determining a position of the target transition point set as the charging port region position.

2. The method of claim 1, wherein, the method for searching a target charging port of a target charging vehicle, the target charging vehicle is a to-be-charged vehicle parked in a target parking space, and a charging cover of the target charging vehicle is in an open state. The method comprises the following steps: filtering candidate transition point sets with distance values greater than the distance threshold from the plurality of candidate transition point sets to obtain filtered candidate transition point sets; if there are a plurality of filtered candidate transition point sets, determining a filtered candidate transition point set with the largest number of transition points from the plurality of filtered candidate transition point sets as the target transition point set; if there is only one filtered candidate transition point set, determining the filtered candidate transition point set as the target transition point set.

3. The method of claim 1, wherein, the method for searching a target charging port of a target charging vehicle, the target charging vehicle is a to-be-charged vehicle parked in a target parking space, and a charging cover of the target charging vehicle is in an open state. The method comprises the following steps: determining a charging port center position in a depth dimension image of the second point cloud image according to a scalable 2D model of the charging port standard model and a depth dimension image in the second point cloud image; constructing a charging port target search area in a depth dimension image of the second point cloud image with a preset area size, with the center position of the charging port as the center; extracting a charging port contour from the charging port target search area according to a preset charging port depth threshold value; mapping the charging port contour to corresponding point clouds in the second point cloud image to convert the charging port contour into a 3D object model; finding the charging port standard model in the 3D object model and determining a model center of the charging port standard model in the 3D object model; determining a position corresponding to the model center as the target charging port position.

4. The method of claim 1, wherein, After the target charging port position is obtained through the charging port position identification processing of the target charging port according to the preset charging port standard model and the second point cloud image, the method further includes: determining a target space position coordinate of the charging port relative to the charging robot arm according to a preset coordinate conversion relationship between the camera and the robot arm and the target charging port position; generating a motion path of the charging robot arm according to the target space position coordinate; controlling the charging robot arm to move to the target charging port position through the motion path to perform a charging operation on the target charging vehicle.

5. The method according to any one of claims 1 to 4, characterized in that, Before the first point cloud image of the target parking space corresponding area is obtained through the first camera, the method further includes: obtaining a third point cloud image of the target parking space corresponding area through the first camera; determining a projection angle between a vehicle body of the target charging vehicle and a parking line of the target parking space through the third point cloud image; adjusting an image acquisition angle of the first camera according to the projection angle.

6. The method of claim 5, wherein, The projection angle between the vehicle body of the target charging vehicle and the parking line of the target parking space is determined through the third point cloud image, including: performing cropping processing on the third point cloud image according to a depth dimension image in the third point cloud image to obtain a cropped third point cloud image; iterating point clouds in a transverse dimension image in the cropped third point cloud image to extract a plurality of second transition points; performing filtering processing on a plurality of the second transition points according to a preset second transition threshold interval to obtain a plurality of filtered second transition points; performing straight line fitting processing on the plurality of filtered second transition points to obtain a fitting straight line; mapping the fitting straight line into the third point cloud image to obtain a space fitting straight line, the space fitting straight line being the vehicle body of the target charging vehicle; recognizing the parking line in the third point cloud image; calculating the projection angle between the space fitting straight line and the parking line through a preset inverse perspective method and projection principle.

7. A charging port searching apparatus characterized by comprising: The charging port searching device is used for searching a target charging port of a target charging vehicle, the target charging vehicle being a to-be-charged vehicle parked in a target parking space, and a charging cover of the target charging vehicle being in an open state, and the charging port searching device includes: a transceiving unit configured to obtain a first point cloud image of a target parking space corresponding area through a first camera; The processing unit is configured to perform charging port area identification processing on the target charging vehicle by using a preset field potential method and the first point cloud image, to obtain a charging port area position corresponding to the charging port area, wherein the charging port area includes the charging cover and the target charging port; and move a charging mechanical arm to an image acquisition area corresponding to the charging port area position. The transceiving unit is further configured to acquire a second point cloud image by using a second camera in the charging mechanical arm when the charging mechanical arm is in the image acquisition area. The processing unit is further configured to perform target charging port position identification processing on the target charging port according to a preset charging port standard model and the second point cloud image, to obtain a target charging port position. When performing the step of performing charging port area identification processing on the target charging vehicle by using a preset field potential method and the first point cloud image, to obtain a charging port area position corresponding to the charging port area, the processing unit is specifically configured to: perform cropping processing on the first point cloud image according to a depth dimension image in the first point cloud image, to obtain a cropped first point cloud image; perform iteration on point clouds in a horizontal dimension image and a vertical dimension image in the cropped first point cloud image, to extract a plurality of first transition points; filter non-target points in the plurality of first transition points according to a preset first transition threshold interval, and obtain a plurality of candidate transition point sets by clustering; determine discrete centers of the plurality of candidate transition point sets; calculate distance values between transition centers of each candidate transition point set and the discrete centers, respectively; determine a target transition point set from the plurality of candidate transition point sets according to a preset distance threshold and the distance values corresponding to each candidate transition point set, respectively, and determine a position of the target transition point set as the charging port area position.

8. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the charging port search method in any one of claims 1-6 when executing the computer program.

9. A storage medium, characterized by The storage medium stores a computer program, and the computer program includes program instructions which, when executed by a processor, cause the processor to perform the charging port search method in any one of claims 1-6.

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