CN116993789A - Relative positioning method, device, equipment and medium based on point cloud registration - Google Patents
Relative positioning method, device, equipment and medium based on point cloud registration Download PDFInfo
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Abstract
The application provides a relative positioning method, a relative positioning device, relative positioning equipment and a relative positioning medium based on point cloud registration, which are realized by acquiring first point cloud data of a shore bridge; registering the first point cloud data of the shore bridge with a pre-acquired point cloud map of the shore bridge to obtain second point cloud data corresponding to the registered first point cloud data; acquiring a first current position of a vehicle, and determining a first coordinate position of the vehicle in a quay crane coordinate system according to the first current position and second point cloud data, wherein a quay crane point cloud map comprises coordinate positions of the quay crane in the quay crane coordinate system; and converting the first coordinate position according to the pre-acquired coordinate position of the quay bridge in the wharf coordinate system to obtain a second coordinate position of the vehicle in the wharf coordinate system. The embodiment of the application can improve the accuracy of vehicle positioning.
Description
Technical Field
The application relates to the technical field of automatic driving, in particular to a relative positioning method, device, equipment and medium based on point cloud registration.
Background
In order to improve the accuracy of vehicle positioning, vehicles are often provided with various vehicle-mounted positioning devices, such as a differential global positioning system (Global Positioning System, GPS), an inertial navigation measurement unit (Inertial Measurement Unit, IMU), a camera, a laser radar and the like, and the position coordinates of the vehicles are finally determined by fusing positioning information fed back by the vehicle-mounted positioning devices.
The laser radar sensor is one of important sensors on the automatic driving vehicle, can acquire point cloud information of surrounding environment and is used for sensing, positioning and other functions. At present, point cloud data of a laser radar is mainly used for vehicle positioning, however, in a code head face quay bridge application scene, the quay bridge can be adjusted and moved for a plurality of times according to the position of a container in the real ship operation process, when the position of the quay bridge changes, the actual point cloud position of the quay bridge on the code head face is not consistent with the position of the quay bridge in a point cloud map of the code head face, the positioning result is affected, even positioning fails, and positioning accuracy is poor.
Disclosure of Invention
The relative positioning method, the relative positioning device, the relative positioning equipment and the relative positioning medium based on the point cloud registration can improve the accuracy of vehicle positioning.
In a first aspect, an embodiment of the present application provides a relative positioning method based on point cloud registration, where the method includes:
acquiring first point cloud data of a shore bridge;
registering the first point cloud data of the shore bridge with a pre-acquired point cloud map of the shore bridge to obtain second point cloud data corresponding to the registered first point cloud data;
acquiring a first current position of a vehicle, and determining a first coordinate position of the vehicle in a quay crane coordinate system according to the first current position and second point cloud data, wherein a quay crane point cloud map comprises coordinate positions of the quay crane in the quay crane coordinate system;
And converting the first coordinate position according to the pre-acquired coordinate position of the quay bridge in the wharf coordinate system to obtain a second coordinate position of the vehicle in the wharf coordinate system.
In a second aspect, the present application provides a positioning device comprising:
the acquisition module is used for acquiring first point cloud data of the shore bridge;
the registration module is used for registering the first point cloud data of the shore bridge with the pre-acquired point cloud map of the shore bridge to obtain second point cloud data corresponding to the registered first point cloud data;
the system comprises a determining module, a determining module and a control module, wherein the determining module is used for acquiring a first current position of a vehicle and determining a first coordinate position of the vehicle in a quay coordinate system according to the first current position and second point cloud data, and the quay point cloud map comprises coordinate positions of the quay in the quay coordinate system;
the conversion module is used for converting the first coordinate position according to the pre-acquired coordinate position of the quay bridge in the wharf coordinate system to obtain a second coordinate position of the vehicle in the wharf coordinate system.
In a third aspect, an embodiment of the present application provides an electronic device, including: a processor and a memory storing computer program instructions;
the processor when executing the computer program instructions implements a relative positioning method based on point cloud registration as in any of the embodiments of the first aspect.
In a fourth aspect, embodiments of the present application provide a computer storage medium having stored thereon computer program instructions which, when executed by a processor, implement a method of relative positioning based on point cloud registration as in any of the embodiments of the first aspect.
In a fifth aspect, embodiments of the present application provide a computer program product, instructions in which, when executed by a processor of an electronic device, cause the electronic device to perform a relative positioning method implementing a point cloud registration based on any of the embodiments of the first aspect described above.
In the relative positioning method, device, equipment and medium based on point cloud registration provided by the embodiment of the application, first point cloud data of a shore bridge are obtained; registering the first point cloud data of the shore bridge with a pre-acquired point cloud map of the shore bridge to obtain second point cloud data corresponding to the registered first point cloud data; acquiring a first current position of a vehicle, and determining a first coordinate position of the vehicle in a quay crane coordinate system according to the first current position and second point cloud data, wherein a quay crane point cloud map comprises coordinate positions of the quay crane in the quay crane coordinate system; and converting the first coordinate position according to the pre-acquired coordinate position of the quay bridge in the wharf coordinate system to obtain a second coordinate position of the vehicle in the wharf coordinate system. By means of the method, the first point cloud data of the shore bridge and the point cloud map of the shore bridge are registered to obtain the actual shore bridge map (namely the second point cloud data), so that the first coordinate position of the vehicle under the coordinate system of the shore bridge can be determined according to the actual point cloud map of the shore bridge and the current position of the vehicle, the relative position of the vehicle and the shore bridge can be determined according to the first coordinate position and the coordinate position of the shore bridge in the coordinate system of the shore bridge, the second coordinate position of the vehicle under the coordinate system of the dock can be determined according to the obtained coordinate position of the shore bridge under the coordinate system of the dock, and therefore the accuracy of vehicle positioning can be improved according to the first coordinate position of the vehicle under the coordinate system of the shore bridge and the coordinate position of the shore bridge under the coordinate system of the shore bridge (namely the relative position of the vehicle to the shore bridge) and the coordinate position of the shore bridge under the coordinate system of the dock bridge.
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In order to more clearly illustrate the technical solution of the embodiments of the present application, the drawings that are needed to be used in the embodiments of the present application will be briefly described, and it is possible for a person skilled in the art to obtain other drawings according to these drawings without inventive effort.
FIG. 1 is a flow chart of a relative positioning method based on point cloud registration according to an embodiment of the present application;
FIG. 2 is a schematic illustration of a position of a vehicle and a quay bridge in an application scenario according to an embodiment of the present application;
FIG. 3 is a schematic illustration of another location of a vehicle and a quay bridge in an application scenario provided by an embodiment of the present application;
FIG. 4 is a schematic structural view of a positioning device according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order that the above objects, features and advantages of the present disclosure may be more clearly understood, a further description of aspects of the present disclosure will be provided below. It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced otherwise than as described herein; it will be apparent that the embodiments in the specification are only some, but not all, embodiments of the disclosure.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
In the prior art, a laser radar sensor is one of important sensors on an automatic driving vehicle, can acquire point cloud information of surrounding environment, and is used for sensing, positioning and other functions. At present, two main ways of using point cloud data of a laser radar to locate are adopted, one way is as an odometer, the method does not need to collect a high-precision point cloud map in advance, only the point cloud data collected by the laser radar can provide a locating result in a short time, and a serious drifting phenomenon exists when the method is used for a long time. The method is to use a point cloud registration algorithm to match with a pre-acquired high-precision point cloud map to obtain a relative position compared with the map, and the method needs to pre-acquire the high-precision point cloud map as an object to be registered, so that a globally consistent positioning result can be provided. In addition, in the prior art of the point cloud registration method applied to the port bridge, a pre-acquired high-precision bridge point cloud map is arranged at each position of the code head face to form a point cloud map of the code head face according to the position of the bridge before entering the code head face, and then real-time point cloud data acquired by a laser radar and the code head face point cloud map are used for registration and positioning. For a code head surface quay bridge scene, the quay bridge can be adjusted and moved for a plurality of times according to the position of a container in the real-ship operation process, and a high-precision point cloud map of the quay bridge cannot be moved in real time according to the position of the quay bridge. In the current technical method, when the position of the quay bridge changes, the actual point cloud position of the quay bridge on the code head surface is inconsistent with the position of the quay bridge in the point cloud map of the code head surface, and the positioning result is affected at the moment, even the positioning fails.
In order to solve the problems in the prior art, the embodiment of the application provides a relative positioning method, a device, equipment and a medium based on point cloud registration. The following first describes a relative positioning method based on point cloud registration provided by the embodiment of the present application.
Fig. 1 is a flow chart illustrating a relative positioning method based on point cloud registration according to an embodiment of the present application. As shown in fig. 1, the method specifically may include the following steps:
s101, acquiring first point cloud data of a shore bridge.
Alternatively, in embodiments of the present application, the quay bridge refers to a mechanical device for transporting cargo, typically a large crane, mounted on a quay, movable on the water surface for transporting the cargo. Therefore, the position of the quay bridge may change in practical application. Point cloud data is a collection of data consisting of a large number of points in three-dimensional space. Each point contains location information and optionally other attribute information such as color, normal vector, intensity, reflectivity, etc. The first point cloud data of the shore bridge is a data set of the shore bridge in the three-dimensional space.
Alternatively, in the embodiment of the present application, the point cloud data may be acquired in various manners, for example, the point cloud data may be acquired by a lidar, where the lidar is a sensor mainly used for acquiring the point cloud data. It can generate a three-dimensional point cloud by emitting a laser beam and measuring its return time. The point cloud data can also be obtained through the camera, the depth information of the scene can be captured by using the depth camera or the stereo camera, and then the depth information is converted into the point cloud data by using a computer algorithm. Or acquire point cloud data using a radar that can detect objects in a scene by sending radio waves and measuring their return time. These data can be used to create a point cloud. Common radars are millimeter wave radars and the above-mentioned lidars. Optionally, in the embodiment of the present application, the point cloud data is generally transmitted to a computer or a cloud server for processing, so as to extract scene information, and be used to implement automatic driving of the vehicle.
S102, registering the first point cloud data of the shore bridge with a pre-acquired point cloud map of the shore bridge to obtain second point cloud data corresponding to the registered first point cloud data.
Optionally, in the embodiment of the present application, a laser radar or other sensors may be installed on the shore bridge, to collect point cloud data of the shore bridge. Combining this data with the data of GPS or other positioning systems, a point cloud map of the quay bridge can be generated. Feature points or feature lines, such as building corner points or road boundary lines, are then extracted from the two data sets (the quay point cloud map and the first point cloud data). And matching features in the quay bridge point cloud map and the first point cloud data using an algorithm, such as a least squares or random sample consistency algorithm. And obtaining a transformation matrix between the first point cloud data and the quay bridge point cloud map by carrying out transformation calculation on the matched characteristic points. And carrying out coordinate transformation on the first point cloud data by using a transformation matrix to realize registration with the shore bridge point cloud map, and obtaining registered second point cloud data. Through the steps, the registration of the shore bridge point cloud data can be realized, the registered second point cloud data is obtained, and basic data support is provided for subsequent analysis and application.
S103, acquiring a first current position of the vehicle, and determining a first coordinate position of the vehicle in a quay coordinate system according to the first current position and the second point cloud data, wherein the quay point cloud map comprises coordinate positions of the quay in the quay coordinate system.
Alternatively, in one possible implementation manner of the present application, the first current position of the vehicle may be obtained by acquiring sensor data of the vehicle, for example, a laser radar or a camera, and by processing the sensor data, point cloud data of the vehicle at a current time point may be obtained. And filtering, registering and the like are carried out on the point cloud data of the vehicle so as to acquire the current position of the vehicle. Of course, the current position of the vehicle can also be obtained directly by GPS or other positioning tools. In the embodiment of the application, the coordinate position of the vehicle in the shore bridge coordinate system can be calculated by measuring the distance and the direction between the vehicle and the shore bridge because the shore bridge point cloud map comprises the coordinate position of the shore bridge in the shore bridge coordinate system. And precisely positioning according to the second point cloud data, and finding a first coordinate position of the vehicle in a quay crane coordinate system.
S104, converting the first coordinate position according to the pre-acquired coordinate position of the quay bridge in the quay coordinate system to obtain a second coordinate position of the vehicle in the quay coordinate system.
Alternatively, in one possible implementation of the application, the coordinate transformation matrix between the quay and quay coordinate systems may be determined by measuring the relative positional relationship between the quay and quay. For example, GPS or other measurement tools may be used to measure the position coordinates of the quay and quay, thereby calculating a coordinate transformation matrix between the quay coordinate system and the quay coordinate system. Multiplying the first coordinate position of the vehicle in the quay coordinate system by the coordinate transformation matrix to obtain the second coordinate position of the vehicle in the quay coordinate system. It should be noted that, when performing coordinate transformation and alignment, the influence of factors such as sensor errors, inconsistent coordinate systems and the like need to be considered, so as to ensure the accuracy and precision of the algorithm.
Alternatively, in another possible implementation of the present application, as shown in fig. 2, after the coordinate position of the quay bridge in the quay coordinate system is obtained, the second coordinate position of the vehicle in the quay coordinate system may be calculated according to the following formula (1).
pos p ＝pos r +pos c (1)
Wherein pos p Representing the position of the vehicle under the code head face coordinate system, pos r Representing the relative positioning result (namely the first coordinate position of the vehicle in the quay coordinate system and the coordinate position of the quay in the quay coordinate system) based on the point cloud registration, pos c Representing the real-time position of the quay (i.e. the real-time position of the quay in the quay coordinate system).
In one embodiment, wherein pos r During calculation, decoupling from a wharf coordinate system, inputting a coordinate position of a vehicle under a quay coordinate system as a registration initial value in a relative positioning process, registering a real-time point cloud acquired by a laser radar with the quay point cloud, and continuously outputting a relative positioning result, as shown in the following figure 3.
When the vehicle is not moving, the position of the shore bridge changes by delta pos c When the vehicle is stationary and the quay is moving, the position of the vehicle relative to the quay is pos r -Δpos c The position of the quay bridge in the wharf coordinate system is pos c +Δpos c The position of the vehicle in the code head face coordinate system is:
when the vehicle is not moving and the quay moves, the vehicle is still not moving under the code head face coordinate system, so that the influence of the quay movement on registration and positioning is avoided.
When the quay crane does not move, the vehicle advances by delta pos r At this time, the position of the vehicle in the code head face coordinate system is:
when the quay vehicles move simultaneously:
from the above, no matter how the shore bridge moves, the relative position of the vehicle compared with the shore bridge can be obtained, and then the vehicle coordinate is converted to the code head face coordinate system according to the real-time position of the shore bridge, so that the relative positioning method based on the point cloud registration provided by the application can improve the positioning precision under the condition of not limiting the scene.
In the relative positioning method based on point cloud registration provided by the embodiment of the application, first point cloud data of a quay bridge are obtained; registering the first point cloud data of the shore bridge with a pre-acquired point cloud map of the shore bridge to obtain second point cloud data corresponding to the registered first point cloud data; acquiring a first current position of a vehicle, and determining a first coordinate position of the vehicle in a quay crane coordinate system according to the first current position and second point cloud data, wherein a quay crane point cloud map comprises coordinate positions of the quay crane in the quay crane coordinate system; and converting the first coordinate position according to the pre-acquired coordinate position of the quay bridge in the wharf coordinate system to obtain a second coordinate position of the vehicle in the wharf coordinate system. By means of the method, the first point cloud data of the shore bridge and the point cloud map of the shore bridge are registered to obtain an actual shore bridge map (namely, second point cloud data), and therefore the first coordinate position of the vehicle under the coordinate system of the shore bridge can be determined according to the actual point cloud map of the shore bridge and the current position of the vehicle, and accordingly the relative position of the vehicle and the shore bridge can be determined according to the first coordinate position and the coordinate position of the shore bridge in the coordinate system of the shore bridge, and accordingly the second coordinate position of the vehicle under the coordinate system of the dock can be determined according to the obtained coordinate position of the shore bridge under the coordinate system of the dock, and therefore the accuracy of vehicle positioning can be improved even if the coordinate position of the shore bridge changes in an actual scene.
In an embodiment, the step 101 may specifically include the following steps:
s1011, acquiring a second current position of the vehicle;
s1012, acquiring first point cloud data of the shore bridge under the condition that the second current position information is located in a preset range of the shore bridge.
Alternatively, in one possible implementation manner of the present application, the first current position of the vehicle may be obtained by acquiring sensor data of the vehicle, for example, a laser radar or a camera, and by processing the sensor data, point cloud data of the vehicle at a current time point may be obtained. And filtering, registering and the like are carried out on the point cloud data of the vehicle so as to acquire the current position of the vehicle. Of course, the current position of the vehicle can also be obtained directly by GPS or other positioning tools. And then judging whether the vehicle is in the preset range of the quay by comparing the second current position of the vehicle with the pre-acquired quay position. If the vehicle is within the preset range, the vehicle can be considered to have reached the target position (namely, the range of the quay), the vehicle can be stopped, and the first point cloud data of the quay can be acquired. And if the vehicle is not in the preset range, waiting for receiving a driving instruction until the vehicle reaches a target position, stopping the vehicle, and collecting first point cloud data of the quay bridge.
In these optional embodiments, by comparing the vehicle position with the quay position, it is determined whether to enter the quay range, so that only when the vehicle runs in the quay range, the collection of the point cloud data is performed, thereby saving the resource cost, and only collecting the first point cloud data of the quay within the quay range, and improving the accuracy of the collected quay point cloud data; on the other hand, all point cloud data on the code head do not need to be acquired, and the calculation amount for registration and positioning in the follow-up process is saved.
In one embodiment, the step 1012 may specifically include the following steps:
s10121, acquiring Euclidean distance between the second current position and the coordinate position of the quay bridge in the quay bridge coordinate system;
s10122, acquiring first point cloud data of the quay bridge under the condition that the Euclidean distance is located in a preset threshold value interval.
Optionally, in the embodiment of the present application, the euclidean distance between the second current position of the vehicle and the coordinate position of the quay bridge in the quay bridge coordinate system may be calculated by using a euclidean distance calculation formula, where the specific calculation formula of the euclidean distance may refer to the prior art, and the present application is not described herein.
Optionally, in the embodiment of the present application, if the euclidean distance is within the threshold range, the vehicle may be considered to be already approaching the target position, and at this time, the vehicle may be stopped, and the collection of the shore bridge point cloud data may be performed. It is easy to understand that if the euclidean distance is smaller than the lower limit of the preset threshold interval, the vehicle can be stopped to collect the shore bridge point cloud data when the vehicle reaches the target position; if the Euclidean distance is greater than the upper limit of the threshold interval, the vehicle is far away from the shore bridge, and the vehicle needs to continue to advance; if the distance is within the threshold range, the vehicle may be considered to have approached the target location.
Alternatively, in the embodiment of the present application, the specific value of the preset threshold interval is already stored in the vehicle computer or the server, and may be obtained by reading a file or a network request.
In these optional embodiments, the euclidean distance between the vehicle position and the quay position is calculated, and compared with a set threshold value to determine whether the vehicle enters the quay range, so that only when the vehicle runs in the quay range, the acquisition of the point cloud data can be performed, thereby saving the resource cost, only acquiring the first point cloud data of the quay in the quay range, and improving the accuracy of the acquired quay point cloud data; on the other hand, all point cloud data on the code head do not need to be acquired, and the calculation amount for registration and positioning in the follow-up process is saved.
In an embodiment, the step 101 may specifically include the following steps:
s201, transmitting a first reflection signal to the surrounding environment of the vehicle through a transmitter of the vehicle;
s202, receiving target reflection information through a receiver of the vehicle, wherein the target reflection signal is a signal reflected by the first reflection signal.
Alternatively, in one possible implementation of the present application, the first reflected signal may be sent to the surrounding environment of the vehicle by a transmitter of the vehicle, where the transmitter may be a sensor device such as a lidar or millimeter wave radar. These devices can emit high-frequency electromagnetic waves to the surrounding environment, and obtain information such as the position, shape, distance, etc. of obstacles in the surrounding environment by measuring the reflected signals of the electromagnetic waves. When the radar device is used, proper transmitting parameters and receiving parameters are required to be selected according to the working principle and characteristics of the device so as to obtain more accurate reflected signals.
S203, determining first point cloud data of the shore bridge according to the target reflection signal.
When receiving the target reflection information, the target reflection signal may be received by a receiver of the vehicle. The receiver can identify the target reflected signal according to the parameters of the radar transmitter and the characteristics of the reflected signal, and convert the signal into a digital signal for processing. The design and parameter setting of the receiver need to consider factors such as environmental noise, signal interference and the like so as to ensure that the received reflected signal quality is good and accurate target information can be provided. And then, information such as the position, the shape, the distance and the like of the obstacle in the surrounding environment measured by the laser radar, the millimeter wave radar and other equipment is converted into point cloud data. The three-dimensional coordinates, shape, size, color and other attributes of the obstacle can be represented by the point cloud data, and the three-dimensional coordinates, shape, size, color and other attributes can be used for building a shore bridge point cloud map or performing real-time positioning and sensing.
In these alternative embodiments, by receiving the target reflection signal, accurate target information can be provided, so that the quality of the acquired first point cloud data of the quay bridge is better, accurate target information can be provided, accurate data support is provided for subsequent registration and positioning, and the positioning accuracy is further improved.
In an embodiment, the steps described above may be specifically performed according to 203 as follows:
s2031, determining initial point cloud data from the target reflection signal.
Alternatively, in one possible implementation of the present application, the emitter of the vehicle emits a laser beam to scan the surrounding environment, and measures the distance and the reflection intensity of the object surface, so as to generate an initial point cloud data.
S2032, analyzing the initial point cloud data to obtain analyzed point cloud data;
s2033, calibrating the analyzed point cloud data according to preset installation parameters to obtain first point cloud data of the shore bridge, wherein the preset installation parameters comprise the installation position of the emitter on the vehicle and the signal emission angle of the emitter.
After the initial point cloud data is obtained, the initial point cloud data needs to be analyzed to obtain the position and other attribute information of each point, such as reflection intensity, color and the like. The point cloud data is calibrated according to preset installation parameters, and the analyzed point cloud data is generally required to be rotated and translated so as to be overlapped with an actual quay crane coordinate system. The calibration process may be accomplished by calibrating or manually adjusting the parameters. The installation position of the transmitter on the vehicle and the signal transmission angle of the transmitter are one of important parameters in the calibration process, so that stable and accurate data support is provided for obtaining accurate and stable first point cloud data of the shore bridge, and further data support is provided for subsequent registration and positioning.
Alternatively, in one possible implementation of the present application, the transmitter may be a laser radar, where the laser radar receives a signal reflected by a target by transmitting a signal to the surrounding, determines a distance of the target by testing a running time of the reflected signal, so as to collect point cloud data of the surrounding in real time, and then sends the point cloud data in a user datagram protocol (User Datagram Protocol, UDP) through an ethernet. And after receiving the corresponding point cloud data, the controller running the algorithm analyzes the point cloud data and aligns and calibrates the point cloud data according to the installation parameters. The calibration formula is:
wherein x, y, z and phi, theta and phi are the installation position and the installation angle of the laser radar on the vehicle respectively, and P calibrated P is calibrated point cloud data raw Is the initial point cloud data.
In these optional embodiments, by calibrating and analyzing the point cloud data, the quality of the acquired first point cloud data of the shore bridge can be ensured to be better, accurate target information can be provided, accurate data support is provided for subsequent registration and positioning, and the positioning accuracy is further improved.
In an embodiment, the step 103 may specifically be performed as follows:
S1031, receiving message information, wherein the message information comprises the real-time position of the vehicle.
Optionally, in an embodiment of the present application, a network protocol may be used for communication to obtain the message information, such as a transmission control protocol/internet protocol (Transmission Control Protocol/Internet Protocol, TCP/IP) or UDP protocol. At the vehicle end, the message information may be received using a corresponding network interface or socket.
S1032, analyzing the message information through the database file to obtain the first current position of the vehicle.
Alternatively, in the embodiment of the present application, the database or the parsing library may be used to parse the message information. In general, the format of the message information is agreed by a standard or a protocol, so that the message information can be parsed by a corresponding parsing rule. The commonly used parsing library comprises a JS object numbered musical notation (JavaScript Object Notation, JSON) and a Database file (Database CAN, DBC) of CAN. And then, acquiring real-time position information of the vehicle according to the analyzed message information. According to the specific database file format and structure, the first current location information of the vehicle may be obtained through a corresponding query statement or application program interface (Application Program Interface, API interface).
Optionally, in one possible aspect of the present application, the vehicle location is sent in the form of a controller area network (Controller Area Network, CAN) message, and the present application needs to receive CAN message information including the vehicle location, and parse the CAN message information by aligning DBC files to obtain the vehicle location.
In the alternative embodiments, the real-time current position of the vehicle is obtained through the message information, so that the obtained vehicle position is more reliable and accurate, and accurate data support is provided for subsequent registration and positioning.
In an embodiment, before the step 104, the method may further specifically perform the following steps:
s301, acquiring stored real-time wharf map information;
s302, determining real-time information of the quay according to the real-time wharf map information, wherein the real-time information comprises the state of the quay and the position of the quay.
Alternatively, a quay refers to an area for docking a ship for cargo handling and stacking.
Alternatively, in one possible implementation of the application, real-time dock map information may be obtained from a dock map database. In the dock map database, the real-time dock map information should be updated in real time, including information such as the state and position of the quay bridge. The status information may be whether the quay is moving, whether the quay is unloading or lifting the container.
Optionally, in the embodiment of the present application, specific location and status information of the quay bridge may be obtained through an intelligent management system (Terminal Operation System, TOS) of the port, and sent to the vehicle through the background.
Optionally, in the embodiment of the present application, real-time information of the quay bridge, including the status and the position of the quay bridge, may be determined according to the real-time quay map information. The state information and the position information can comprise parameters such as the type, the height, the lifting state, the telescopic state, the rotating state and the like of the quay, and the coordinate position of the quay in a quay coordinate system.
S303, determining the coordinate position of the quay bridge in a wharf coordinate system in real time according to the real-time information of the quay bridge.
According to the real-time information of the quay, the coordinate position of the quay in a quay coordinate system can be determined in real time. Specifically, the real-time position of the quay can be converted into the coordinate position of the quay in the quay coordinate system, and then the coordinate position of the quay in the quay coordinate system is calculated through the coordinate position of the quay in the quay coordinate system and the transformation relationship between the quay coordinate system and the quay coordinate system.
In these alternative embodiments, the accuracy of the positioning is further improved by acquiring real-time map information of the quay, thereby enabling the determination of the real-time position of the quay, providing an accurate reference for the positioning of the vehicle.
In one embodiment, the positioning may be performed by:
and acquiring point cloud data from the laser radar and calibrating. The laser radar receives signals reflected by a target by transmitting signals to the surrounding, determines the distance of the target by testing the running time of the reflected light, collects point cloud data of the surrounding environment in real time, and then transmits the point cloud data through the Ethernet and the UDP protocol. And after receiving the corresponding point cloud data, the controller running the algorithm analyzes the point cloud data and aligns and calibrates the point cloud data according to the installation parameters.
The application needs to receive CAN message information containing the vehicle position, and analyze the CAN message information through DBC files to obtain the vehicle position.
The application needs to receive the information of the shore bridge to judge whether the information enters the range of registration positioning of the shore bridge or not.
And then calculating the position of the vehicle relative to the quay, after the vehicle position and the quay position are obtained, if the vehicle position enters the quay range, starting to enter the relative registration positioning, and if not, waiting. The method and the device determine whether the vehicle enters the range of the quay bridge by calculating the Euclidean distance between the position of the vehicle and the position of the quay bridge and comparing the Euclidean distance with a set threshold value.
And registering the plurality of point clouds under the same coordinate system through point cloud registration, and if the coordinate system of one of the point clouds is known, obtaining the position information of other point clouds under the coordinate system. In the application, the shore bridge point cloud data acquired by the laser radar in real time is registered with a pre-prepared shore bridge point cloud map, so that the position, namely the relative position, of the laser radar under the coordinates of the shore bridge point cloud is obtained. Among them, registration algorithms include, but are not limited to (normal distribution transformation algorithm (Normal Distributions Transform, NDT), nearest point iterative algorithm (iterative closest point, ICP), etc.).
And then converting the relative positioning result into an absolute positioning result according to the position of the quay crane, obtaining the position of the laser radar under the quay crane point cloud coordinate, namely the relative position, and obtaining the coordinate of the quay crane, namely the position of the quay crane in the whole code head face coordinate system, wherein the position of the vehicle in the code head face coordinate system can be obtained through the formula (1). Meanwhile, the formulas 2, 3 and 4 also illustrate that the relative positioning method based on the point cloud registration can perform registration positioning according to the shore bridge moving in real time.
Fig. 4 is a schematic structural view of a positioning device according to another embodiment of the present application, and for convenience of explanation, only a portion related to the embodiment of the present application is shown.
Referring to fig. 4, the positioning device may include:
an obtaining module 401, configured to obtain first point cloud data of a shore bridge;
the registration module 402 is configured to register the first point cloud data of the shore bridge with a pre-acquired point cloud map of the shore bridge, and obtain second point cloud data corresponding to the registered first point cloud data;
a determining module 403, configured to obtain a first current position of the vehicle, and determine a first coordinate position of the vehicle in a quay coordinate system according to the first current position and the second point cloud data, where the quay point cloud map includes coordinate positions of the quay in the quay coordinate system;
the conversion module 404 is configured to convert the first coordinate position according to the pre-acquired coordinate position of the quay bridge in the quay coordinate system, so as to obtain a second coordinate position of the vehicle in the quay coordinate system.
In one embodiment, the acquisition module 401 includes:
the first acquisition sub-module is used for acquiring a second current position of the vehicle;
the second obtaining sub-module is used for obtaining the first point cloud data of the shore bridge under the condition that the second current position information is located in the preset range of the shore bridge.
In one embodiment, the second acquisition submodule includes:
the first acquisition unit is used for acquiring Euclidean distance between the second current position and the coordinate position of the quay bridge in the quay bridge coordinate system;
The second acquisition unit is used for acquiring the first point cloud data of the quay bridge under the condition that the Euclidean distance is located in a preset threshold value interval.
In one embodiment, the acquisition module 401 includes:
a transmitting sub-module for transmitting a first reflected signal to the surrounding environment of the vehicle through a transmitter of the vehicle;
the first receiving sub-module is used for receiving target reflection information through a receiver of the vehicle, and the target reflection signal is a signal reflected back by the first reflection signal;
and the first determining submodule is used for determining first point cloud data of the quay bridge according to the target reflection signal.
In an embodiment, the first determination submodule includes:
a first determining unit for determining initial point cloud data according to the target reflection signal;
the analyzing unit is used for analyzing the initial point cloud data to obtain analyzed point cloud data;
and the calibration unit is used for calibrating the analysis point cloud data according to preset installation parameters to obtain first point cloud data of the shore bridge, wherein the preset installation parameters comprise the installation position of the emitter on the vehicle and the signal emission angle of the emitter.
In one embodiment, the determining module 403 includes:
the second receiving sub-module is used for receiving message information, wherein the message information comprises the real-time position of the vehicle;
The first analysis sub-module is used for analyzing the message information through the database file to obtain a first current position of the vehicle.
In an embodiment, the positioning device may further include:
the second acquisition module is used for acquiring stored real-time wharf map information;
the second determining module is used for determining real-time information of the quay according to the real-time wharf map information, wherein the real-time information comprises the state of the quay and the position of the quay;
and the third determining module is used for determining the coordinate position of the quay bridge in the wharf coordinate system in real time according to the real-time information of the quay bridge.
It should be noted that, based on the same concept as the method embodiment of the present application, the information interaction and the execution process between the devices/units are devices corresponding to the battery thermal runaway warning method, and all implementation manners in the method embodiment are applicable to the device embodiment, and specific functions and technical effects thereof may be referred to the method embodiment section, and are not repeated herein.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
Fig. 5 shows a schematic hardware structure of an electronic device according to an embodiment of the present application.
The device may include a processor 501 and a memory 502 in which program instructions are stored.
The steps of any of the various method embodiments described above are implemented when the processor 501 executes a program.
By way of example, a program may be partitioned into one or more modules/units that are stored in the memory 502 and executed by the processor 501 to accomplish the present application. One or more of the modules/units may be a series of program instruction segments capable of performing specific functions to describe the execution of the program in the device.
In particular, the processor 501 may include a Central Processing Unit (CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured as one or more integrated circuits that implement embodiments of the present application.
Memory 502 may include mass storage for data or instructions. By way of example, and not limitation, memory 502 may comprise a Hard Disk Drive (HDD), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, magnetic tape, or universal serial bus (Universal Serial Bus, USB) Drive, or a combination of two or more of the foregoing. Memory 502 may include removable or non-removable (or fixed) media, where appropriate. Memory 502 may be internal or external to the integrated gateway disaster recovery device, where appropriate. In a particular embodiment, the memory 502 is a non-volatile solid state memory.
The memory may include Read Only Memory (ROM), random Access Memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical, or other physical/tangible memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) readable storage media (e.g., memory devices) encoded with software comprising computer-executable instructions and when the software is executed (e.g., by one or more processors) it is operable to perform the operations described with reference to methods in accordance with aspects of the present disclosure.
The processor 501 implements any one of the methods of the above embodiments by reading and executing program instructions stored in the memory 502.
In one example, the electronic device may also include a communication interface 503 and a bus 510. The processor 501, the memory 502, and the communication interface 503 are connected to each other via a bus 510 and perform communication with each other.
The communication interface 503 is mainly used to implement communication between each module, apparatus, unit and/or device in the embodiments of the present application.
Bus 510 includes hardware, software, or both that couple the components of the online data flow billing device to each other. By way of example, and not limitation, the buses may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an infiniband interconnect, a Low Pin Count (LPC) bus, a memory bus, a micro channel architecture (MCa) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus, or a combination of two or more of the above. Bus 510 may include one or more buses, where appropriate. Although embodiments of the application have been described and illustrated with respect to a particular bus, the application contemplates any suitable bus or interconnect.
In addition, in combination with the method in the above embodiment, the embodiment of the present application may be implemented by providing a storage medium. The storage medium has program instructions stored thereon; the program instructions, when executed by a processor, implement any of the methods of the embodiments described above.
The embodiment of the application further provides a chip, the chip comprises a processor and a communication interface, the communication interface is coupled with the processor, the processor is used for running programs or instructions, the processes of the embodiment of the method can be realized, the same technical effects can be achieved, and the repetition is avoided, and the description is omitted here.
It should be understood that the chips referred to in the embodiments of the present application may also be referred to as system-on-chip chips, chip systems, or system-on-chip chips, etc.
Embodiments of the present application provide a computer program product stored in a storage medium, where the program product is executed by at least one processor to implement the respective processes of the above method embodiments, and achieve the same technical effects, and for avoiding repetition, a detailed description is omitted herein.
It should be understood that the application is not limited to the particular arrangements and instrumentality described above and shown in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between steps, after appreciating the spirit of the present application.
The functional blocks shown in the above block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and the like. The code segments may be downloaded via computer grids such as the internet, intranets, etc.
It should also be noted that the exemplary embodiments mentioned in this disclosure describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, or may be performed in a different order from the order in the embodiments, or several steps may be performed simultaneously.
Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to being, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware which performs the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In the foregoing, only the specific embodiments of the present application are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that the scope of the present application is not limited thereto, and any equivalent modifications or substitutions can be easily made by those skilled in the art within the technical scope of the present application, and they should be included in the scope of the present application.
Claims (10)
1. A method of relative positioning based on point cloud registration, the method comprising:
acquiring first point cloud data of a shore bridge;
registering the first point cloud data of the shore bridge with a pre-acquired point cloud map of the shore bridge to obtain second point cloud data corresponding to the registered first point cloud data;
acquiring a first current position of a vehicle, and determining a first coordinate position of the vehicle in a quay coordinate system according to the first current position and the second point cloud data, wherein the quay point cloud map comprises coordinate positions of the quay in the quay coordinate system;
and converting the first coordinate position according to the pre-acquired coordinate position of the quay bridge in a wharf coordinate system to obtain a second coordinate position of the vehicle in the wharf coordinate system.
2. The method of claim 1, wherein the acquiring the first point cloud data of the quay comprises:
acquiring a second current position of the vehicle;
and acquiring first point cloud data of the shore bridge under the condition that the second current position information is located in a preset range of the shore bridge.
3. The method according to claim 2, wherein the obtaining the first point cloud data of the quay bridge if the second current position is within a preset range of the quay bridge comprises:
Acquiring Euclidean distance between the second current position and the coordinate position of the quay bridge in the quay bridge coordinate system;
and under the condition that the Euclidean distance is located in a preset threshold value interval, acquiring first point cloud data of the shore bridge.
4. The method of claim 1, wherein the acquiring the first point cloud data of the quay comprises:
transmitting a first reflected signal to the vehicle surroundings by a transmitter of the vehicle;
receiving target reflection information through a receiver of the vehicle, wherein the target reflection signal is a signal reflected back by the first reflection signal;
and determining first point cloud data of the shore bridge according to the target reflected signal.
5. The method of claim 4, wherein determining the first point cloud data of the quay bridge from the target reflected signal comprises:
determining initial point cloud data according to the target reflected signal;
analyzing the initial point cloud data to obtain analyzed point cloud data;
and calibrating the analysis point cloud data according to preset installation parameters to obtain first point cloud data of the quay bridge, wherein the preset installation parameters comprise the installation position of the transmitter on the vehicle and the signal emission angle of the transmitter.
6. The method of claim 1, wherein the obtaining the first current location of the vehicle comprises:
receiving message information, wherein the message information comprises the real-time position of the vehicle;
and analyzing the message information through a database file to obtain the first current position of the vehicle.
7. The method of claim 1, wherein prior to converting the first coordinate location based on the pre-acquired coordinate location of the quay bridge in a quay coordinate system, the method further comprises:
acquiring stored real-time dock map information;
determining real-time information of the quay according to the real-time wharf map information, wherein the real-time information comprises the state of the quay and the position of the quay;
and determining the coordinate position of the quay bridge in a wharf coordinate system in real time according to the real-time information of the quay bridge.
8. A positioning device, the device comprising:
the acquisition module is used for acquiring first point cloud data of the shore bridge;
the registration module is used for registering the first point cloud data of the shore bridge with a pre-acquired shore bridge point cloud map to obtain second point cloud data corresponding to the registered first point cloud data;
The determining module is used for obtaining a first current position of the vehicle, determining a first coordinate position of the vehicle in a quay coordinate system according to the first current position and the second point cloud data, and the quay point cloud map comprises coordinate positions of the quay in the quay coordinate system;
the conversion module is used for converting the first coordinate position according to the pre-acquired coordinate position of the quay bridge in a wharf coordinate system to obtain a second coordinate position of the vehicle in the wharf coordinate system.
9. An electronic device, the device comprising: a processor and a memory storing computer program instructions;
the processor, when executing the computer program instructions, implements a relative positioning method based on point cloud registration as claimed in any of claims 1-7.
10. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon computer program instructions, which when executed by a processor, implement the relative positioning method based on point cloud registration as claimed in any of claims 1-7.
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