CN113378750A - Charging pile docking method and device, computer equipment and storage medium - Google Patents
Charging pile docking method and device, computer equipment and storage medium Download PDFInfo
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- G05D1/02—Control of position or course in two dimensions
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- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
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Abstract
The invention discloses a charging pile docking method and device, computer equipment and a storage medium. The method is performed by a robot, and comprises the following steps: acquiring an environment map, and generating a traveling instruction according to the charging pile position information in the environment map; if the situation that the vehicle travels to meet the preset distance range condition is determined, acquiring a depth image and a three-channel color image, and calculating to obtain current pose information of the charging pile according to the depth image and the three-channel color image; and determining a docking posture according to the current pose information of the charging pile so as to dock with the charging pile. By using the technical scheme of the invention, the butt joint of the robot and the charging pile can be automatically, accurately and dynamically realized.
Description
Technical Field
The embodiment of the invention relates to a computer vision technology, in particular to a charging pile docking method and device, computer equipment and a storage medium.
Background
With the popularization of robots requiring autonomous charging, such as floor sweeping robots and meal delivery robots, the autonomous charging function is particularly important, and in order to achieve autonomous charging, the robots are required to find charging seats in relatively complex environments.
Among the prior art, the robot seeks to fill electric pile and recharges, mainly fixes a position charging pile through laser sensor, and the robot is advanced to near the back of filling electric pile according to the position of filling electric pile, and rethread infrared sensor, ultrasonic sensor, bluetooth etc. continue to send the signal to the robot, and the robot is according to received signal adjustment route, the realization and fill the butt joint of electric pile. However, signals sent by the infrared sensor are easily shielded in a complex environment, when the signals sent by the ultrasonic sensor are applied to a moving object, the positioning accuracy can be affected by the jitter in the moving process, and the distance limit exists in the use of the Bluetooth. Therefore, the mode of realizing and filling the electric pile butt joint through the sensor among the prior art, the suitability is relatively poor in complicated environment, influences the robot and carries out the accuracy of fixing a position to filling electric pile.
Disclosure of Invention
The embodiment of the invention provides a charging pile docking method, a charging pile docking device, computer equipment and a storage medium, so that automatic, accurate and dynamic docking with a charging pile is realized.
In a first aspect, an embodiment of the present invention provides a method for docking a charging pile, where the method includes:
acquiring an environment map, and generating a traveling instruction according to the charging pile position information in the environment map;
if the situation that the vehicle travels to meet the preset distance range condition is determined, acquiring a depth image and a three-channel color image, and calculating to obtain current pose information of the charging pile according to the depth image and the three-channel color image;
and determining a docking posture according to the current pose information of the charging pile so as to dock with the charging pile.
In a second aspect, an embodiment of the present invention further provides a device for docking a charging pile, where the device includes:
the environment map acquisition module is used for acquiring an environment map and generating a traveling instruction according to the charging pile position information in the environment map;
the current pose information acquisition module is used for acquiring a depth image and a three-channel color image if the fact that the vehicle travels to meet the preset distance range condition is determined, and calculating to obtain the current pose information of the charging pile according to the depth image and the three-channel color image;
and the charging pile docking module is used for determining a docking posture according to the current pose information of the charging pile so as to dock with the charging pile.
In a third aspect, an embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the charging pile docking method according to any one of the embodiments of the present invention.
In a fourth aspect, embodiments of the present invention further provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform the charging pile docking method according to any one of the embodiments of the present invention.
According to the embodiment of the invention, the environment map is obtained, the charging pile is advanced according to the charging pile position information in the environment map, when the robot is determined to advance to meet the preset distance range condition, the current pose information of the charging pile is determined according to the depth image and the three-channel color image containing the charging pile, the docking attitude is adjusted according to the current pose information, and docking with the charging pile is realized. The problems that in the prior art, the method for docking with the charging pile is poor in applicability in a complex environment and low in docking accuracy are solved, and automatic, accurate and dynamic docking with the charging pile is achieved.
Drawings
Fig. 1 is a flowchart of a charging pile docking method according to a first embodiment of the present invention;
fig. 2 is a flowchart of a charging pile docking method according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a charging pile docking device according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a computer device in the fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of a charging pile docking method according to an embodiment of the present invention, where the method is applicable to a situation where a robot and a charging pile are docked, and the method may be executed by a charging pile docking device, where the device may be implemented by software and/or hardware and is generally integrated in the robot.
As shown in fig. 1, the technical solution of the embodiment of the present invention specifically includes the following steps:
and S110, acquiring an environment map, and generating a traveling instruction according to the charging pile position information in the environment map.
The environment map is generated by the robot according to an environment image obtained by shooting in advance, and the robot scans the surrounding environment through a depth camera carried by a machine body and establishes the environment map according to the environment image in the process of traveling. And meanwhile, carrying out feature recognition on the environment image, and recording the identification information and the position information of the charging pile into an environment map when the charging pile is recognized.
When the robot enters an idle mode or the electric quantity is insufficient and the charging pile needs to be returned, a pre-established environment map is loaded, the charging pile position information recorded in the environment map is obtained, a return route and a traveling instruction are generated according to the current position information of the robot and the charging pile position information, the traveling instruction is sent to the power device controller, and the power device is controlled to travel to the charging pile along the return route. The embodiment of the invention does not limit the specific way of planning the return route, and simultaneously, the navigation obstacle avoidance module can be started to avoid the obstacles on the return route in the process of advancing to the charging pile along the return route.
In the embodiment of the invention, when the robot returns to the charging pile, the environment map is loaded, the charging pile position information in the environment map is obtained, and the robot moves to the charging pile position.
And S120, if the situation that the vehicle travels to meet the preset distance range condition is determined, acquiring a depth image and a three-channel color image, and calculating to obtain the current pose information of the charging pile according to the depth image and the three-channel color image.
The condition that the preset distance range is met means that the distance between the robot and the charging pile is smaller than or equal to the preset distance, and the distance between the robot and the charging pile is updated in real time in the process of returning along the returning route. When the distance of the user is advanced to a preset distance of the charging pile, the depth image and the three-channel color image obtained by shooting the charging pile are obtained through the depth camera. Depth images, also known as range images, refer to images that take as pixel values the distance (depth) from an image grabber to each point in a scene, which directly reflects the geometry of the visible surface of an object. The depth camera can output a depth image and an RGB (Red, Green, Blue, Red, Green and Blue) image, namely the depth image and a three-channel color image, can acquire feature points according to the depth image and the three-channel color image, and calculates pose information of the feature points. In the embodiment of the invention, the pose information of the charging pile can be obtained based on the depth image and the RGB image, but the adopted pose estimation algorithm is not limited in the embodiment.
The pose information comprises position information and attitude information, and the current pose information of the charging pile can be used for representing the distance and the angle between the charging pile and the robot. In the embodiment of the invention, when the robot travels to the preset distance range of the charging pile along the return route, the depth image of the charging pile is shot through the depth camera, and the current pose information of the charging pile is obtained according to the depth image.
S130, determining a docking posture according to the current pose information of the charging pile so as to dock with the charging pile.
In the embodiment of the invention, expected pose information of the robot and the charging pile in the butt joint process can be predetermined, namely the pose information of the charging pile relative to the robot when the robot and the charging pile are in the butt joint process successfully. According to the current pose information and the expected pose information of the charging pile, the docking posture of the robot when the robot is docked with the charging pile can be adjusted, and the position and/or posture of the charging pile can also be adjusted.
In the embodiment of the invention, in the process of docking the robot and the charging pile, the depth image is obtained in real time, the current pose information of the charging pile is obtained in real time, and the docking posture is continuously adjusted according to the current pose information of the charging pile obtained in real time until the robot and the charging pile are successfully docked.
According to the technical scheme, the environment map is acquired, the charging pile is advanced according to the position information of the charging pile in the environment map, when the robot is determined to advance to meet the preset distance range condition, the current pose information of the charging pile is determined according to the depth image and the three-channel color image containing the charging pile, the docking posture is adjusted according to the current pose information, and docking with the charging pile is achieved. The problems that in the prior art, the method for docking with the charging pile is poor in applicability in a complex environment and low in docking accuracy are solved, and automatic, accurate and dynamic docking with the charging pile is achieved.
Example two
Fig. 2 is a flowchart of a charging pile docking method according to a second embodiment of the present invention, which further embodies a process of adjusting a docking posture based on the second embodiment of the present invention, and adds a process of finding a charging pile according to predicted location information, a process of generating an environment image, and a process of marking charging pile location information and predicted location information in an environment map.
Correspondingly, as shown in fig. 2, the technical solution of the embodiment of the present invention specifically includes the following steps:
s210, obtaining a depth image and a three-channel color image, calculating pose information of the feature points according to the depth image and the three-channel color image, and obtaining point cloud data according to the depth image.
For example, a Depth camera RGB-D (RGB image sensor + Depth sensor) may be respectively disposed at the front and the rear of the robot body, and during the mapping process of the robot, an image of the environment around the robot is acquired by the Depth camera. The method comprises the steps of obtaining characteristic points according to a depth image and a three-channel color image, calculating pose information of the characteristic points, obtaining point cloud data according to the depth image, wherein the point cloud is a massive point set which expresses target space distribution and target surface characteristics under the same space reference system.
The pose information of the robot can be estimated according to the depth image and the three-channel color image, and the specific mode of pose estimation according to the depth image is not limited in the embodiment.
And S220, generating an environment map according to the point cloud data and the pose information of the feature points.
Specifically, a three-dimensional sparse map can be established according to pose information of the feature points, and the map construction mode is not limited in the embodiment. After the three-dimensional sparse map is generated, the three-dimensional sparse map can be used for positioning of the robot, the three-dimensional dense map is further generated according to the pose information, and the three-dimensional dense map is used as an environment map, so that a target area where the charging pile can be placed is conveniently found, and the predicted position of the charging pile is determined.
And S230, judging whether the charging pile identification exists according to the three-channel color image, if so, executing S240, and if not, returning to execute S230.
The charging pile identification can be bar code information such as a two-dimensional code and a bar code, and also can be characteristic information of the charging pile.
The robot carries out feature recognition on the obtained RGB images while constructing the environment map, and determines a target RGB image including the charging pile identifier.
S240, determining the position information of the charging pile according to the three-channel color image and the depth image, and marking the charging pile identification and the position information of the charging pile in the environment map.
The position and pose estimation is carried out on the three-channel color image containing the charging pile identification in combination with the depth image, the position of the charging pile is determined, and the charging pile identification and the charging pile position information are recorded into an environment map, so that when a robot searches for the charging pile, the robot can directly search for the charging pile according to the stored charging pile position information, and whether the charging pile actually exists in the charging pile position stored in the environment map can be judged according to the stored charging pile identification.
And S250, judging whether the target area of the environment map meets the charging pile placement condition, if so, executing S260, and otherwise, executing S270.
And in the process of constructing the environment map, the robot identifies the characteristics of the environment and takes the identified wall surface area as a target area. The predicted position information of the charging pile is determined according to the target area meeting the charging pile placing condition, and the specific mode of environment recognition is not limited in the embodiment.
Accordingly, S250 may further include:
and S251, judging whether the height of the target area is greater than that of the charging pile, if so, executing S252, and otherwise, executing S270.
The target area satisfies fills electric pile and places the condition, needs to ensure that the length and the height of target area are greater than the length and the height that fill electric pile, and to the height of target area, as long as be greater than the height that fills electric pile, can guarantee to fill electric pile and can place. Meanwhile, if the height of the charging pile is lower than that of the robot, the height of the target area needs to be ensured to be larger than that of the robot, so that the robot can be successfully docked with the charging pile for charging.
And S252, judging whether the difference value between the length of the target area and the length of the charging pile is larger than or equal to a preset value, if so, executing S253, otherwise, executing S270.
For the length of the target area, as a space needs to be reserved for the robot and the charging pile during butt joint charging, the length of the target area needs to be larger than the length of the charging pile for a certain distance, and similarly, if the length of the charging pile is smaller than the length of the robot, the difference value between the length of the target area and the length of the robot needs to be larger than or equal to a preset value, so that the robot can be ensured to be successfully in butt joint charging with the charging pile.
And S253, determining that the target area meets the charging pile placing condition.
And S260, determining the predicted position information of the charging pile according to the target area, and marking the predicted position information in the environment map.
After a target area meeting the placing condition of the charging pile is selected, the predicted position of the charging pile can be determined according to the target area, and the predicted position is marked in an environment map, so that when the robot cannot find the charging pile according to the position information of the charging pile in the environment map, namely when the position of the charging pile is changed, the robot can address the charging pile according to the predicted position information.
Accordingly, S260 may further include:
and S261, determining a prediction point in the target area, and taking the position information of the prediction point as the predicted position information of the charging pile.
For example, a central point of a bottom edge of the target area may be used as a prediction point, and if a divisor of the length of the target area and the length of the charging pile is greater than or equal to 2, points whose number is the length of the target area and the divisor of the length of the charging pile may also be selected as the prediction points, which is not limited in this embodiment.
And S262, marking the predicted position information in the environment map.
After the predicted point is determined, the predicted position information is recorded in the environment map.
And S270, acquiring an environment map, and generating a traveling instruction according to the charging pile position information in the environment map.
In the embodiment of the invention, when the robot finishes working or the electric quantity is insufficient and needs to be in butt joint with the charging pile, the environment map is loaded at first, the charging pile position information in the environment map is obtained, the return route is determined according to the charging pile position and the current position of the robot, and the robot travels to the charging pile position along the return route.
And S280, acquiring a depth image and a three-channel color image in real time.
And on the way of returning the robot, acquiring a depth image and an RGB image in real time, performing feature recognition on the RGB image, calculating and updating charging pile position information according to the depth image and the three-channel color image if the target RGB image comprises a charging pile identifier, and performing butt joint according to the updated charging pile position information.
And S290, judging whether the three-channel color image comprises a charging pile mark, if so, executing S2100, and otherwise, executing S2110.
S2100, determining the position information of the charging pile according to the depth image and the three-channel color image, and updating the position information of the charging pile in the environment map.
After the fact that the three-channel color image comprises the charging pile identification is determined, pose estimation is carried out on the charging pile in the three-channel color image according to the depth image, the charging pile position information is obtained, and the charging pile position information which is originally stored in the environment map is updated to be the currently obtained position information.
And S2110, judging whether the vehicle travels to a position meeting a preset distance range condition, if so, executing S2120, and if not, returning to execute S2110.
No matter whether the robot returns to update on the way and fills electric pile position information, when the robot travels to the preset distance away from the position of the electric pile, feature recognition is carried out on the obtained depth image, whether the depth image comprises the electric pile or not is judged, when the depth image comprises the electric pile, the docking pose is adjusted according to the depth image, and when the depth image does not comprise the electric pile, the electric pile is searched according to the predicted position information in the environment map.
And S2120, judging whether the three-channel color image comprises the charging pile, if so, executing S2130, and otherwise, executing S2150.
And S2130, calculating to obtain current pose information of the charging pile according to the depth image and the three-channel color image.
If the three-channel color image contains the charging pile, the charging pile is not changed in position. And performing pose estimation according to the three-channel color image and the depth image acquired in real time, and determining the current pose information of the charging pile.
S2140, obtaining expected pose information of the charging pile, and determining a docking posture according to the current pose information and the expected pose information.
And the expected pose information is the pose information of the charging pile relative to the robot when the charging pile is successfully docked with the robot, a docking route is generated according to the current pose information and the expected pose information, the position and the orientation of the robot are adjusted, and the robot moves along the docking route. The robot acquires the depth image in real time, calculates the current pose information of the charging pile in real time, and continuously adjusts the docking route until the docking of the robot and the charging pile is finally realized.
S2150, obtaining the predicted position information of the charging pile in the environment map, and generating an addressing route according to the predicted position information.
When the depth image does not include the charging pile, the predicted position information in the environment map is obtained, an addressing route is generated, the robot travels along the addressing route until the charging pile is found, and then the robot is in butt joint with the charging pile in a mode of S2110-S2140. The present embodiment does not limit the manner in which the address route is generated from the predicted position information of each predicted point.
In the embodiment of the invention, the predicted position is recorded in the environment map in advance, and when the charging pile moves, a new position of the charging pile can be found according to the predicted position, so that the moving situation of the charging pile can be flexibly responded.
S2160, traveling along the addressed route. Return to execution S2110.
The technical scheme of the embodiment includes that a depth image and a three-channel color image are obtained in real time, an environment map is built in advance, position information and predicted position information of a charging pile are recorded while the environment map is built, the environment map is loaded when the environment map is required to be in butt joint with the charging pile, the charging pile is advanced according to the position information of the charging pile in the environment map, the position information of the charging pile is updated if the charging pile is identified according to the three-channel color image in the advancing process, when the robot is determined to advance to a preset distance range from the charging pile, if the three-channel color image comprises the charging pile, the current position information of the charging pile is determined according to the depth image and the three-channel color image, the butt joint posture is adjusted according to the current position information, the butt joint with the charging pile is achieved, if the three-channel color image does not comprise the charging pile, addressing of the charging pile is carried out according to the predicted position information in the environment map, after the charging pile is found, the current pose information of the charging pile is determined according to the depth image and the three-channel color image, the docking posture is adjusted according to the current pose information, and docking with the charging pile is achieved. The problems that in the prior art, the method for docking with the charging pile is poor in applicability in a complex environment and low in docking accuracy are solved, and automatic, accurate and dynamic docking with the charging pile is achieved.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a charging pile docking device in a third embodiment of the present invention, the charging pile docking device is disposed in a robot, and the charging pile docking device includes: the system comprises an environment map acquisition module 310, a current pose information acquisition module 320 and a charging pile docking module 330. Wherein:
the environment map acquiring module 310 is configured to acquire an environment map and generate a travel instruction according to charging pile position information in the environment map;
the current pose information acquisition module 320 is used for acquiring a depth image and a three-channel color image if the situation that the vehicle travels to meet the preset distance range condition is determined, and calculating to obtain the current pose information of the charging pile according to the depth image and the three-channel color image;
and the charging pile docking module 330 is configured to determine a docking posture according to the current pose information of the charging pile, so as to dock with the charging pile.
According to the technical scheme, the environment map is acquired, the charging pile is advanced according to the position information of the charging pile in the environment map, when the robot is determined to advance to meet the preset distance range condition, the current pose information of the charging pile is determined according to the depth image and the three-channel color image containing the charging pile, the docking posture is adjusted according to the current pose information, and docking with the charging pile is achieved. The problems that in the prior art, the method for docking with the charging pile is poor in applicability in a complex environment and low in docking accuracy are solved, and automatic, accurate and dynamic docking with the charging pile is achieved.
On the basis of the above embodiment, the apparatus further includes:
the data acquisition module is used for acquiring a depth image and a three-channel color image, calculating pose information of the feature points according to the depth image and the three-channel color image, and acquiring point cloud data according to the depth image;
the environment map generation module is used for generating an environment map according to the point cloud data and the pose information of the feature points;
and the charging pile marking module is used for determining the position information of the charging pile according to the three-channel color image and the depth image if the charging pile identifier is determined to exist according to the three-channel color image, and marking the charging pile identifier and the charging pile position information in the environment map.
On the basis of the above embodiment, the apparatus further includes:
the addressing route generating module is used for acquiring the predicted position information of the charging pile in the environment map and generating an addressing route according to the predicted position information if the charging pile is determined not to be included in the three-channel color image;
and the charging pile addressing module is used for advancing along the addressing route and acquiring a three-channel color image when a preset distance range condition is met until the three-channel color image comprises the charging pile.
On the basis of the above embodiment, the apparatus further includes:
and the predicted position information marking module is used for determining the predicted position information of the charging pile according to the target area and marking the predicted position information in the environment map if the target area of the environment map is determined to meet the charging pile placing condition.
On the basis of the above embodiment, the predicted location information labeling module includes:
the charging pile placement condition judging unit is used for determining that the target area meets the charging pile placement condition if the height of the target area is larger than the height of the charging pile and the difference value between the length of the target area and the length of the charging pile is larger than or equal to a preset value;
and the predicted position information determining unit is used for determining a predicted point in the target area and taking the position information of the predicted point as the predicted position information of the charging pile.
On the basis of the above embodiment, charging pile docking module 330 includes:
and the docking attitude determining unit is used for acquiring expected pose information of the charging pile and determining a docking attitude according to the current pose information and the expected pose information.
On the basis of the above embodiment, the apparatus further includes:
and the charging pile position information updating module is used for acquiring the depth image and the three-channel color image in real time, determining charging pile position information according to the depth image and the three-channel color image if the three-channel color image comprises a charging pile identifier, and updating the charging pile position information in the environment map.
The charging pile docking device provided by the embodiment of the invention can execute the charging pile docking method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example four
Fig. 4 is a schematic structural diagram of a computer apparatus according to a fourth embodiment of the present invention, as shown in fig. 4, the computer apparatus includes a processor 70, a memory 71, an input device 72, and an output device 73; the number of processors 70 in the computer device may be one or more, and one processor 70 is taken as an example in fig. 4; the processor 70, the memory 71, the input device 72 and the output device 73 in the computer apparatus may be connected by a bus or other means, and the connection by the bus is exemplified in fig. 4.
The memory 71 serves as a computer-readable storage medium, and may be used to store software programs, computer-executable programs, and modules, such as the modules corresponding to the charging pile docking method in the embodiment of the present invention (for example, the environment map acquisition module 310, the current pose information acquisition module 320, and the charging pile docking module 330 in the charging pile docking apparatus). The processor 70 executes various functional applications and data processing of the computer device by executing the software programs, instructions and modules stored in the memory 71, so as to implement the charging pile docking method. The method comprises the following steps:
acquiring an environment map, and generating a traveling instruction according to the charging pile position information in the environment map;
if the situation that the vehicle travels to meet the preset distance range condition is determined, acquiring a depth image and a three-channel color image, and calculating to obtain current pose information of the charging pile according to the depth image and the three-channel color image;
and determining a docking posture according to the current pose information of the charging pile so as to dock with the charging pile.
The memory 71 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 71 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the memory 71 may further include memory located remotely from the processor 70, which may be connected to a computer device over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 72 may be used to receive input numeric or character information and generate key signal inputs relating to user settings and function controls of the computer apparatus. The output device 73 may include a display device such as a display screen.
EXAMPLE five
An embodiment of the present invention further provides a storage medium containing computer-executable instructions, where the computer-executable instructions are executed by a computer processor to perform a charging pile docking method, and the method includes:
acquiring an environment map, and generating a traveling instruction according to the charging pile position information in the environment map;
if the situation that the vehicle travels to meet the preset distance range condition is determined, acquiring a depth image and a three-channel color image, and calculating to obtain current pose information of the charging pile according to the depth image and the three-channel color image;
and determining a docking posture according to the current pose information of the charging pile so as to dock with the charging pile.
Of course, the storage medium provided by the embodiment of the present invention includes computer-executable instructions, and the computer-executable instructions are not limited to the method operations described above, and may also perform related operations in the charging pile docking method provided by any embodiment of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the embodiment of the charging pile docking device, each included unit and module are only divided according to functional logic, but are not limited to the above division, as long as the corresponding function can be realized; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method of docking a charging pile, the method being performed by a robot, the method comprising:
acquiring an environment map, and generating a traveling instruction according to the charging pile position information in the environment map;
if the situation that the vehicle travels to meet the preset distance range condition is determined, acquiring a depth image and a three-channel color image, and calculating to obtain current pose information of the charging pile according to the depth image and the three-channel color image;
and determining a docking posture according to the current pose information of the charging pile so as to dock with the charging pile.
2. The method of claim 1, prior to obtaining the environmental map, further comprising:
acquiring a depth image and a three-channel color image, calculating pose information of the feature points according to the depth image and the three-channel color image, and acquiring point cloud data according to the depth image;
generating an environment map according to the point cloud data and the pose information of the feature points;
and if the charging pile identification is determined to exist according to the three-channel color image, determining the charging pile position information according to the three-channel color image and the depth image, and marking the charging pile identification and the charging pile position information in the environment map.
3. The method of claim 2, before calculating current pose information of the charging pile according to the depth image and the three-channel color image, further comprising:
if the three-channel color image is determined not to include the charging pile, acquiring predicted position information of the charging pile in the environment map, and generating an addressing route according to the predicted position information;
and advancing along the addressing route, and acquiring a three-channel color image when a preset distance range condition is met until the three-channel color image comprises the charging pile.
4. The method of claim 3, further comprising, after tagging charging post identification and charging post location information in the environment map:
and if the target area of the environment map meets the charging pile placement condition, determining the predicted position information of the charging pile according to the target area, and marking the predicted position information in the environment map.
5. The method of claim 4, wherein determining that the target area of the environment map satisfies the charging post placement condition comprises:
if the height of the target area is larger than that of the charging pile, and the difference value between the length of the target area and the length of the charging pile is larger than or equal to a preset value, determining that the target area meets the charging pile placing condition;
the method for determining the predicted position information of the charging pile according to the target area comprises the following steps:
and determining a prediction point in the target area, and using the position information of the prediction point as the predicted position information of the charging pile.
6. The method of claim 1, wherein determining a docking attitude from the current pose information of the charging post comprises:
and acquiring expected pose information of the charging pile, and determining a docking attitude according to the current pose information and the expected pose information.
7. The method of claim 1, after obtaining the environment map, further comprising:
and acquiring a depth image and a three-channel color image in real time, if the three-channel color image comprises a charging pile identifier, determining the position information of the charging pile according to the depth image and the three-channel color image, and updating the position information of the charging pile in the environment map.
8. A charging pile docking device, the device being provided in a robot, the device comprising:
the environment map acquisition module is used for acquiring an environment map and generating a traveling instruction according to the charging pile position information in the environment map;
the current pose information acquisition module is used for acquiring a depth image and a three-channel color image if the fact that the vehicle travels to meet the preset distance range condition is determined, and calculating to obtain the current pose information of the charging pile according to the depth image and the three-channel color image;
and the charging pile docking module is used for determining a docking posture according to the current pose information of the charging pile so as to dock with the charging pile.
9. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the charging pile docking method according to any one of claims 1 to 7.
10. A storage medium containing computer-executable instructions for performing the charging post docking method of any one of claims 1-7 when executed by a computer processor.
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