CN114488237A - Positioning method and device, electronic equipment and intelligent driving method - Google Patents
Positioning method and device, electronic equipment and intelligent driving method Download PDFInfo
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- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
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Abstract
The disclosure provides a positioning method, a positioning device, electronic equipment and an intelligent driving method, relates to the technical field of positioning and automatic driving, and can be particularly used in a positioning scene. The specific scheme is as follows: acquiring a predicted position coordinate of a vehicle to be positioned at a target moment; acquiring a collection position coordinate of a vehicle to be positioned collected at a target moment; and fusing the collected position coordinates and the predicted position coordinates to obtain the positioning coordinates of the vehicle to be positioned at the target moment. In the process of determining the positioning coordinate of the vehicle to be positioned at the target moment, the predicted position coordinate of the vehicle to be positioned at the target moment is considered, the acquired position coordinate of the vehicle to be positioned acquired at the target moment is also considered, the acquired position coordinate and the predicted position coordinate are fused to obtain the positioning coordinate of the vehicle to be positioned at the target moment, and therefore the accuracy of positioning the vehicle to be positioned can be improved.
Description
Technical Field
The disclosure relates to the technical field of positioning and automatic driving, in particular to a positioning method, a positioning device, electronic equipment and an intelligent driving method, which can be used in a positioning scene.
Background
With the increasing of road mileage and the increasing of total facilities in a road, the demand of road maintenance is in a rapidly increasing trend, for example, road inspection by a road inspection vehicle is an important part of daily road management and it is necessary to locate the vehicle.
Currently, in the process of Positioning a vehicle, Positioning is generally performed by a Global Positioning System (GPS).
Disclosure of Invention
The disclosure provides a positioning method, a positioning device, electronic equipment and an intelligent driving method.
In a first aspect, an embodiment of the present disclosure provides a positioning method, including:
acquiring a predicted position coordinate of a vehicle to be positioned at a target moment;
acquiring the coordinates of the acquisition position of the vehicle to be positioned acquired at the target moment;
and fusing the collected position coordinates and the predicted position coordinates to obtain the positioning coordinates of the vehicle to be positioned at the target moment.
In the positioning method of the embodiment of the disclosure, in the process of determining the positioning coordinate of the vehicle to be positioned at the target time, not only the predicted position coordinate of the vehicle to be positioned at the target time is considered, but also the acquired position coordinate of the vehicle to be positioned acquired at the target time is considered, and the acquired position coordinate and the predicted position coordinate are fused to obtain the positioning coordinate of the vehicle to be positioned at the target time, so that the accuracy of positioning the vehicle to be positioned can be improved.
In a second aspect, an embodiment of the present disclosure provides a positioning apparatus, including:
the first acquisition module is used for acquiring the predicted position coordinates of the vehicle to be positioned at the target moment;
the second acquisition module is used for acquiring the acquisition position coordinates of the vehicle to be positioned acquired at the target moment;
and the fusion module is used for fusing the acquisition position coordinates and the prediction position coordinates to obtain the positioning coordinates of the vehicle to be positioned at the target moment.
In a third aspect, an embodiment of the present disclosure further provides an electronic device, including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the positioning method of the present disclosure as provided in the first aspect.
In a fourth aspect, an embodiment of the present disclosure further provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the positioning method provided by the first aspect of the present disclosure.
In a fifth aspect, an embodiment of the present disclosure provides a computer program product comprising a computer program, which when executed by a processor, implements the positioning method of the present disclosure as provided in the first aspect.
In a sixth aspect, an embodiment of the present disclosure provides an intelligent driving method, including:
acquiring a positioning coordinate of a vehicle at a target moment, wherein the positioning coordinate is a position coordinate obtained by fusing an acquisition position coordinate and a predicted position coordinate, the acquisition position coordinate is the position coordinate of the vehicle acquired at the target moment, and the predicted position coordinate is the predicted position coordinate of the vehicle at the target moment;
intelligent driving control based on the positioning coordinates
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 is a schematic flow chart diagram of a positioning method according to an embodiment provided in the present disclosure;
FIG. 2 is a schematic diagram of determining predicted position coordinates in a positioning method according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a positioning method according to an embodiment provided by the present disclosure;
FIG. 4 is one of the block diagrams of a positioning device of one embodiment provided by the present disclosure;
FIG. 5 is a second block diagram of a positioning device according to an embodiment of the present disclosure;
FIG. 6 is a third block diagram of a positioning device according to an embodiment of the present disclosure;
FIG. 7 is a fourth illustration of the configuration of the positioning device in accordance with one embodiment of the present disclosure;
fig. 8 is a block diagram of an electronic device for implementing a positioning method of an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
As shown in fig. 1, according to an embodiment of the present disclosure, the present disclosure provides a positioning method applicable to an electronic device, the method including:
step S101: and acquiring the predicted position coordinates of the vehicle to be positioned at the target moment.
The target time may be a positioning sampling time, and it should be noted that, at the 1 st positioning sampling time, the predicted position coordinate at the 1 st positioning sampling time may be a preset position coordinate, that is, a default preset position coordinate at the 1 st positioning sampling time is preset. The predicted position coordinates of a certain positioning sampling moment acquired subsequently can be predicted by a coordinate position prediction mode along with the time, for example, the certain positioning sampling moment is the (i +1) th positioning sampling moment, the predicted position of the positioning sampling moment is predicted, the predicted position coordinate of the vehicle to be positioned at the (i +1) th positioning sampling moment is obtained by predicting the position coordinate of the ith positioning sampling moment, the driving distance between the ith positioning sampling moment and the (i +1) th positioning sampling moment of the vehicle to be positioned and the driving direction of the vehicle to be positioned at the (i +1) th positioning sampling moment, the position coordinate of the ith positioning sampling moment can be the acquisition position coordinate of the ith positioning sampling moment, or the corrected position coordinate obtained by fusing the collection position coordinate of the ith positioning sampling time and the predicted position coordinate of the ith positioning sampling time, and the like. For example, the predicted position information of the vehicle to be positioned at the (i +1) th positioning sampling time can be obtained by predicting the vehicle to be positioned at the ith positioning sampling time by using the trained position prediction model through the track information of the vehicle to be positioned at the ith positioning sampling time and the like.
Step S102: and acquiring the coordinates of the acquisition position of the vehicle to be positioned acquired at the target moment.
In addition to the predicted position coordinates at the target time, the position coordinates of the vehicle to be positioned can also be acquired, that is, the acquired position coordinates of the vehicle to be positioned acquired at the target time are acquired. The mode of obtaining the position coordinates of the acquisition is various, and the mode of obtaining the position coordinates of the acquisition is not particularly limited in the disclosure, for example, the vehicle to be positioned can be positioned through the GPS to obtain the position coordinates of the acquisition of the vehicle to be positioned, and for example, the vehicle to be positioned can be positioned through the Beidou to obtain the position coordinates of the acquisition of the vehicle to be positioned.
Step S103: and fusing the acquired position coordinates and the predicted position coordinates to obtain the position coordinates of the vehicle to be positioned at the target moment.
In the embodiment of the disclosure, the position coordinates of the vehicle to be positioned at the target moment are obtained by fusing the acquired position coordinates and the predicted position coordinates, so as to improve the positioning accuracy of the obtained vehicle to be positioned at the target moment.
In the positioning method of the embodiment of the disclosure, in the process of determining the positioning coordinate of the vehicle to be positioned at the target time, not only the predicted position coordinate of the vehicle to be positioned at the target time is considered, but also the acquired position coordinate of the vehicle to be positioned acquired at the target time is considered, and the acquired position coordinate and the predicted position coordinate are fused to obtain the positioning coordinate of the vehicle to be positioned at the target time, so that the accuracy of positioning the vehicle to be positioned at the target time can be improved.
In one embodiment, the acquisition location coordinates are acquisition longitude and latitude coordinates;
before fusing the collection position coordinates and the prediction position coordinates, the method further comprises the following steps:
the acquisition position coordinates are converted to cartesian coordinates to update the acquisition position coordinates.
It should be noted that the predicted position coordinate may be a cartesian coordinate, and in the embodiment of the present disclosure, the collected position coordinate is a longitude and latitude coordinate, for example, the collected position coordinate may be a longitude and latitude coordinate collected by a GPS, so that the collected position coordinate needs to be converted into the cartesian coordinate, and the updated collected position coordinate and the predicted position coordinate are the same type of position coordinate.
In one embodiment, the fusing the collected position coordinates and the predicted position coordinates to obtain the positioning coordinates of the vehicle to be positioned at the target moment includes:
fusing the collected position coordinates and the predicted position coordinates through a Kalman fusion algorithm to obtain corrected position coordinates at a target moment;
and converting the corrected position coordinates into longitude and latitude coordinates to obtain the positioning coordinates of the vehicle to be positioned at the target moment.
The kalman filtering algorithm may also be referred to as a kalman filtering algorithm, which is a better data fusion method and is not described in detail in the embodiments of the present disclosure. In this embodiment, a kalman fusion algorithm is first adopted to fuse the two coordinates to obtain a corrected position coordinate at a target time, so as to improve the accuracy of the obtained corrected position coordinate, convert the corrected position coordinate into a longitude and latitude coordinate, and obtain a positioning coordinate of a vehicle to be positioned at the target time, thereby improving the positioning accuracy of the vehicle.
In one embodiment, the target time is the ith positioning sampling time;
fusing the collected position coordinates and the predicted position coordinates through a Kalman fusion algorithm to obtain corrected position coordinates at a target moment, and further comprising:
under the condition that the ith +1 positioning sampling moment is reached, determining a predicted position coordinate at the (i +1) th positioning sampling moment based on a corrected position coordinate, a driving distance and an included angle of the ith positioning sampling moment, wherein the predicted position coordinate at the 1 st positioning sampling moment is a preset position coordinate, the driving distance is a driving distance of a vehicle to be positioned in a time difference between the ith positioning sampling moment and the (i +1) th positioning sampling moment, and the included angle is an included angle between a driving direction and a first axial direction, which are acquired by a compass in the vehicle to be positioned in the time difference;
and adding one to the i, returning to the step of acquiring the acquired position coordinates of the vehicle to be positioned acquired at the target moment, and determining the position coordinates of the vehicle to be positioned at the target moment again until the positioning sampling is finished.
In the positioning process, namely the positioning sampling process, once positioning sampling is carried out at preset time intervals (preset positioning sampling intervals), namely the positioning coordinate at the positioning sampling moment is obtained, and once positioning can be carried out as long as the positioning sampling interval is met along with the time lapse as long as the positioning sampling is not finished, so that one positioning coordinate is obtained. The target time is the ith positioning sampling time, after the corrected position coordinate of the ith positioning sampling time is obtained, under the condition of reaching the (i +1) th positioning sampling time, the corrected position coordinate of the ith positioning sampling time, the running distance and the included angle in the time difference can be used firstly, the predicted position coordinate of the (i +1) th positioning sampling time is determined, then i is added by one, the target time is the ith time due to the fact that i is subjected to addition processing, the ith time can be the original i +1 time, the predicted position coordinate of the moment is predicted to be obtained through the corrected position coordinate of the original ith positioning sampling time, the running distance and the included angle in the time difference, the step of obtaining the collecting position coordinate of the vehicle to be positioned collected at the target time can be returned, and the collecting coordinate positions of the (i) th (after the addition processing) positioning sampling time are obtained again, and fusing the acquired coordinate position of the ith positioning sampling moment and the predicted position coordinate of the ith (i after plus one processing) positioning sampling moment to obtain the positioning coordinate of the vehicle to be positioned at the ith (i after plus one processing) positioning sampling moment, realizing once positioning sampling again, then adding one to i, and carrying out next positioning sampling again, and repeating the steps until the positioning sampling is finished, namely, not carrying out next positioning again to obtain the positioning coordinates of a plurality of positioning sampling moments. It should be noted that the first axial direction may be a magnetic north direction of the compass.
In this embodiment, the positioning coordinates of different positioning sampling moments are obtained through continuous circulation, that is, positioning of the vehicle to be positioned at different moments is realized, wherein the predicted position coordinate of the (i +1) th positioning sampling moment is determined by using the corrected position coordinate, the traveling distance and the included angle of the (i) th positioning sampling moment when the (i +1) th positioning sampling moment is reached, that is, the corrected coordinate position of the previous positioning sampling moment is considered, the traveling distance in the time difference from the (i) th positioning sampling moment to the (i +1) th positioning sampling moment and the included angle between the traveling direction and the first axis direction in the time difference acquired by the compass in the vehicle to be positioned are also considered, so that the accuracy of the obtained predicted position coordinate of the (i +1) th positioning sampling moment can be improved, and the positioning of the vehicle to be positioned is subsequently performed based on the predicted position coordinate of the (i +1) th positioning sampling moment and the acquired position coordinate of the (i +1) th positioning sampling moment Fusion, the (i +1) th positioning is realized, and the positioning accuracy is improved.
In one embodiment, the predicted position coordinates of the (i +1) th positioning sampling time comprise a first coordinate component in a first axis direction and a second coordinate component in a second axis direction, the first axis direction is perpendicular to the second axis direction, and the corrected position coordinates of the (i) th positioning sampling time comprise a first corrected coordinate component in the first axis direction and a second corrected coordinate component in the second axis direction;
the first coordinate component is the sum of the first correction coordinate component and the first distance component, the first distance component is the product of the travelling distance and the cosine of the included angle, the second coordinate component is the sum of the second correction coordinate component and the second distance component, and the second distance component is the product of the travelling distance and the sine of the included angle.
It will be appreciated that the predicted position coordinates for the (i +1) th location sample time can be obtained by the following equation:
wherein x (i +1) is a first coordinate component in the predicted position coordinate of the (i +1) th positioning sampling time, y (i +1) is a second coordinate component in the predicted position coordinate of the (i +1) th positioning sampling time, x (i) is a first corrected coordinate component in the corrected position coordinate of the (i) th positioning sampling time, y (i) is a second corrected coordinate component in the corrected position coordinate of the (i) th positioning sampling time, theta is an included angle between the driving direction and the first axis direction in the time difference from the (i) th positioning sampling time to the (i +1) th positioning sampling time, and diFor the driving distance traveled in the time difference between the ith positioning sampling time and the (i +1) th positioning sampling time, the first distance component is cos (theta)i)*diThe second distance component is sin (θ)i)*diAnd denotes a multiplication number. If the first axial direction is the magnetic north direction of the compass, i.e. the X-axis direction, the second axial direction is the Y-axis direction.
In this embodiment, the predicted position coordinate of the (i +1) th positioning sampling time is obtained through the above process, where a first coordinate component of the predicted position coordinate of the (i +1) th positioning sampling time is a sum of a first corrected coordinate component and a first distance component, the first distance component is a product of the traveling distance and a cosine of the included angle, a second coordinate component of the predicted position coordinate of the (i +1) th positioning sampling time is a sum of a second corrected coordinate component and a second distance component, and the second distance component is a product of the traveling distance and a sine of the included angle, so that the accuracy of the calculated predicted position coordinate of the (i +1) th positioning sampling time can be improved.
In one embodiment, the distance traveled within the time difference is determined by the radius of the wheel of the vehicle to be positioned and the wheel rotation angle sensed by the encoder.
It should be noted that, the wheel of the vehicle to be positioned rotates by an angle of 2 pi (radian, that is, corresponding to 360 degrees), the distance traveled is the circumferential length L of the wheel, the circumferential length L can be calculated according to a circumferential formula in which L is 2 pi r, r is the radius of the wheel, and the arc length can be calculated by multiplying the radius by the radian, so that the driving distance in the time difference can be obtained by multiplying the rotation angle (radian) of the wheel of the vehicle to be positioned and the radius of the wheel in the time difference, and thus the accuracy of the obtained driving distance can be improved.
The process of the above method is specifically described below with specific examples.
x (i) and y (i) are the collected position coordinates of the current positioning sampling moment (i.e. the ith positioning sampling moment), and x (i +1) and y (i +1) are the predicted next position coordinates, i.e. the predicted position coordinates of the ith positioning sampling moment, wherein:
x(i+1)＝x(i)+d_x；
y(i+1)＝y(i)+d_y；
θ is the counterclockwise angle between the vehicle-moving direction and the x-axis direction, d is the vehicle-moving distance in the time difference between the two positioning sampling times, as shown in fig. 2, d _ x is the first distance component, d _ y is the second distance component, where:
d_x＝d*cos(θ)；
d_y＝d*sin(θ)；
the final motion model equation of the system is:
the input of the positioning system for implementing the positioning method of the embodiment comprises the following three parts:
the x-axis direction is responsible for acquiring the theta angle defined in fig. 2;
the encoder can sense the rotation angle of the wheel, and can acquire the driving distance, namely the value d, based on a circumference formula;
the GPS is responsible for collecting the collection position coordinates of the vehicle to be positioned, namely the current longitude and latitude coordinates of the vehicle to be positioned.
As shown in fig. 3, the positioning method of the present embodiment is as follows:
reading a GPS module, and acquiring longitude and latitude coordinates of a vehicle to be positioned at the current ith positioning sampling moment;
reading the electronic compass, and obtaining the included angle from the ith positioning sampling time to the (i +1) th positioning sampling time, which can be expressed as thetai；
Reading the encoder, and obtaining the distance from the ith positioning sampling time to the (i +1) th positioning sampling time, which can be expressed as di；
Converting the longitude and latitude coordinates into Cartesian coordinates, and acquiring Cartesian coordinates (x _ m, y _ m) of the ith positioning sampling moment, namely (x (i), y (i));
based on a Kalman fusion algorithm, fusing Cartesian coordinates (x _ m, y _ m) of the ith positioning sampling moment and a predicted coordinate position of the ith positioning sampling moment, namely, correcting the position coordinates, acquiring corrected position coordinates (x _ c, y _ c) of the ith positioning sampling moment, converting the corrected position coordinates (x _ c, y _ c) of the ith positioning sampling moment into longitude and latitude coordinates, namely, obtaining the positioning coordinates of the ith positioning sampling moment, and realizing the positioning of a vehicle to be positioned;
synthesizing the corrected coordinate of the ith positioning sampling time and thetaiAnd diPredicting the position coordinates by combining the motion model equation, namely acquiring the predicted position coordinates (x _ p, y _ p) at the (i +1) th positioning sampling moment, namely (x (i +1), y (i + 1));
and (5) after the step i is added, repeating the steps, thereby obtaining the positioning coordinates at different positioning sampling moments and realizing the positioning of the vehicle to be positioned at different positioning sampling moments.
Through the positioning method of the embodiment of the disclosure, Inertial Measurement Unit (IMU) hardware is not needed, the position prediction is carried out by relying on an encoder and a compass, the encoder measurement precision can reach millimeter level, the angular measurement of the compass is matched, the whole position prediction precision can reach centimeter level, the positioning precision is higher than that of a single GPS, and the GPS measurement precision of 1-3 meters can be improved to sub-meter level, so that the positioning accuracy is improved.
The embodiment of the present disclosure further provides an intelligent driving method, including:
acquiring a positioning coordinate of the vehicle at a target moment, wherein the positioning coordinate is a position coordinate obtained by fusing an acquisition position coordinate and a predicted position coordinate, the acquisition position coordinate is a position coordinate of the vehicle acquired at the target moment, and the predicted position coordinate is a predicted position coordinate of the vehicle at the target moment;
and carrying out intelligent driving control based on the positioning coordinates.
It should be noted that the vehicle may be an autonomous vehicle, and the intelligent driving control may include, but is not limited to, steering control, speed control, and the like. The position coordinates of the vehicle at the target moment can be obtained by positioning the vehicle by the positioning method in the embodiment, so that the positioning of the vehicle is realized.
In this embodiment, first, a positioning coordinate at a target time is obtained, where the positioning coordinate is a position coordinate obtained by fusing an acquired position coordinate and a predicted position coordinate, that is, the positioning coordinate takes into account both an acquired position coordinate of a vehicle acquired at the target time and a predicted position coordinate of the vehicle at the target time, and the two coordinates are fused to obtain the positioning coordinate, so that accuracy of the positioning coordinate can be improved, and the positioning coordinate is used for performing intelligent driving control, thereby improving accuracy of the intelligent driving control.
As shown in fig. 4, the present disclosure also provides a positioning apparatus 400 according to an embodiment of the present disclosure, the apparatus 400 including:
the first acquisition module 401 is configured to acquire a predicted position coordinate of a vehicle to be positioned at a target time;
a second obtaining module 402, configured to obtain a collection position coordinate of the vehicle to be positioned collected at the target time;
and the fusion module 403 is configured to fuse the acquired position coordinates and the predicted position coordinates to obtain positioning coordinates of the vehicle to be positioned at the target time.
In one embodiment, the acquisition location coordinates are acquisition longitude and latitude coordinates;
as shown in fig. 5, the apparatus 400 further comprises:
a first conversion module 404, configured to convert the acquisition position coordinates into cartesian coordinates before the fusion module 403 performs fusion on the acquisition position coordinates and the predicted position coordinates, so as to update the acquisition position coordinates.
As shown in fig. 6, in one embodiment, the fusion module 403 includes:
the coordinate fusion sub-module 4031 is used for fusing the collected position coordinates and the predicted position coordinates through a Kalman fusion algorithm to obtain corrected position coordinates at a target moment;
and the second conversion module 4032 is used for converting the corrected position coordinates into longitude and latitude coordinates to obtain the positioning coordinates of the vehicle to be positioned at the target moment.
In one embodiment, the target time is the ith positioning sampling time;
as shown in fig. 7, the apparatus 400 further comprises:
the predicted position determining module 405 is configured to determine, when the ith +1 th positioning sampling time is reached, a predicted position coordinate at the (i +1) th positioning sampling time based on a corrected position coordinate, a traveling distance, and an included angle at the ith positioning sampling time, where the predicted position coordinate at the 1 st positioning sampling time is a preset position coordinate, the traveling distance is a traveling distance of the vehicle to be positioned within a time difference between the ith positioning sampling time and the (i +1) th positioning sampling time, and the included angle is an included angle between a traveling direction acquired by a compass in the vehicle to be positioned within the time difference and the first axis direction;
and the processing module 406 is configured to add one to i, return to the second obtaining module 402, execute obtaining of the collected position coordinates of the vehicle to be positioned collected at the target time, and determine the position coordinates of the vehicle to be positioned at the target time again until the positioning sampling is finished.
In one embodiment, the predicted position coordinates of the (i +1) th positioning sampling time comprise a first coordinate component in a first axis direction and a second coordinate component in a second axis direction, the first axis direction is perpendicular to the second axis direction, and the corrected position coordinates of the (i) th positioning sampling time comprise a first corrected coordinate component in the first axis direction and a second corrected coordinate component in the second axis direction;
the first coordinate component is the sum of the first correction coordinate component and the first distance component, the first distance component is the product of the travelling distance and the cosine of the included angle, the second coordinate component is the sum of the second correction coordinate component and the second distance component, and the second distance component is the product of the travelling distance and the sine of the included angle.
In one embodiment, the distance traveled within the time difference is determined by the radius of the wheel of the vehicle to be positioned and the wheel rotation angle sensed by the encoder.
The positioning device of each embodiment is a device for implementing the positioning method of each embodiment, and has corresponding technical features and technical effects, which are not described herein again.
The present disclosure also provides an electronic device, a readable storage medium, a computer program product, and an autonomous vehicle according to embodiments of the present disclosure.
A non-transitory computer readable storage medium of an embodiment of the present disclosure stores computer instructions for causing a computer to perform a positioning method provided by the present disclosure.
The computer program product of the embodiments of the present disclosure includes a computer program for causing a computer to execute the positioning method provided by the embodiments of the present disclosure.
FIG. 8 illustrates a schematic block diagram of an example electronic device 800 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 8, the electronic device 800 includes a computing unit 801 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)802 or a computer program loaded from a storage unit 808 into a Random Access Memory (RAM) 803. In the RAM803, various programs and data necessary for the operation of the device 800 can also be stored. The calculation unit 801, the ROM 802, and the RAM803 are connected to each other by a bus 804. An input/output (I/O) interface 8085 is also connected to bus 804.
A number of components in the electronic device 800 are connected to the I/O interface 805, including: an input unit 806, such as a keyboard, a mouse, or the like; an output unit 807 such as various types of displays, speakers, and the like; a storage unit 808, such as a magnetic disk, optical disk, or the like; and a communication unit 804 such as a network card, modem, wireless communication transceiver, etc. The communication unit 804 allows the electronic device 800 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), the internet, and blockchain networks.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The Server can be a cloud Server, also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system, or a server incorporating a blockchain.
The autonomous vehicle of the disclosed embodiment may include an electronic device 500. For example, an autonomous vehicle may include an electronic device capable of performing the positioning method applied to various embodiments of the vehicle.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel or sequentially or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (16)
1. A method of positioning, comprising:
acquiring a predicted position coordinate of a vehicle to be positioned at a target moment;
acquiring the coordinates of the acquisition position of the vehicle to be positioned acquired at the target moment;
and fusing the collected position coordinates and the predicted position coordinates to obtain the positioning coordinates of the vehicle to be positioned at the target moment.
2. The method of claim 1, wherein the acquisition location coordinates are acquisition latitude and longitude coordinates;
before the fusing the collecting position coordinates and the predicting position coordinates, the method further comprises:
converting the acquisition position coordinates to Cartesian coordinates to update the acquisition position coordinates.
3. The method of claim 2, wherein the fusing the acquired position coordinates and the predicted position coordinates to obtain the positioning coordinates of the vehicle to be positioned at the target time comprises:
fusing the collection position coordinates and the prediction position coordinates through a Kalman fusion algorithm to obtain corrected position coordinates at the target moment;
and converting the corrected position coordinates into longitude and latitude coordinates to obtain the positioning coordinates of the vehicle to be positioned at the target moment.
4. The method of claim 3, wherein the target time instant is an ith positioning sample time instant;
the fusing the collection position coordinates and the prediction position coordinates through a kalman fusion algorithm to obtain corrected position coordinates at the target time, further comprising:
under the condition that the ith +1 th positioning sampling moment is reached, determining a predicted position coordinate at the (i +1) th positioning sampling moment based on a corrected position coordinate, a driving distance and an included angle of the ith positioning sampling moment, wherein the predicted position coordinate at the 1 st positioning sampling moment is a preset position coordinate, the driving distance is a driving distance of the vehicle to be positioned within a time difference between the ith positioning sampling moment and the (i +1) th positioning sampling moment, and the included angle is an included angle between a driving direction and a first axis direction, which are acquired by a compass in the vehicle to be positioned and are within the time difference;
and adding one to the i, returning to the step of acquiring the acquired position coordinates of the vehicle to be positioned acquired at the target moment, and determining the position coordinates of the vehicle to be positioned at the target moment again until the positioning sampling is finished.
5. The method of claim 4, wherein the predicted position coordinates for the i +1 th positioning sample time comprise a first coordinate component in the first axis direction and a second coordinate component in a second axis direction, the first axis direction being perpendicular to the second axis direction, the revised position coordinates for the i-th positioning sample time comprise a first revised coordinate component in the first axis direction and a second revised coordinate component in the second axis direction;
the first coordinate component is the sum of the first correction coordinate component and the first distance component, the first distance component is the product of the driving distance and the cosine of the included angle, the second coordinate component is the sum of the second correction coordinate component and the second distance component, and the second distance component is the product of the driving distance and the sine of the included angle.
6. The method according to claim 4, wherein the distance travelled within the time difference is determined by the radius of the wheel of the vehicle to be positioned and the wheel rotation angle sensed by the encoder.
7. A positioning device, comprising:
the first acquisition module is used for acquiring the predicted position coordinates of the vehicle to be positioned at the target moment;
the second acquisition module is used for acquiring the acquisition position coordinates of the vehicle to be positioned acquired at the target moment;
and the fusion module is used for fusing the acquisition position coordinates and the prediction position coordinates to obtain the positioning coordinates of the vehicle to be positioned at the target moment.
8. The apparatus of claim 7, wherein the acquisition location coordinates are acquisition latitude and longitude coordinates;
the device further comprises:
a first conversion module, configured to convert the acquisition position coordinates into cartesian coordinates before the fusion module performs fusion on the acquisition position coordinates and the predicted position coordinates, so as to update the acquisition position coordinates.
9. The apparatus of claim 8, wherein the fusion module comprises:
the coordinate fusion submodule is used for fusing the acquisition position coordinate and the prediction position coordinate through a Kalman fusion algorithm to obtain a corrected position coordinate at the target moment;
and the second conversion module is used for converting the corrected position coordinates into longitude and latitude coordinates to obtain the positioning coordinates of the vehicle to be positioned at the target moment.
10. The apparatus of claim 9, wherein the target time instant is an ith positioning sample time instant;
the device further comprises:
the device comprises a predicted position determining module, a first axis direction determining module and a second axis direction determining module, wherein the predicted position determining module is used for determining the predicted position coordinate of the (i +1) th positioning sampling moment based on the corrected position coordinate, the traveling distance and the included angle of the (i +1) th positioning sampling moment when the (i +1) th positioning sampling moment is reached, the predicted position coordinate of the 1 st positioning sampling moment is a preset position coordinate, the traveling distance is the traveling distance of the vehicle to be positioned in the time difference between the (i) th positioning sampling moment and the (i +1) th positioning sampling moment, and the included angle is the included angle between the traveling direction and the first axis direction of the vehicle to be positioned, which are acquired by a compass in the vehicle to be positioned and are in the time difference;
and the processing module is used for adding one to the i, returning to the second acquisition module to execute acquisition of the acquired position coordinates of the vehicle to be positioned acquired at the target moment, and determining the position coordinates of the vehicle to be positioned at the target moment again until the positioning sampling is finished.
11. The apparatus according to claim 10, wherein the predicted position coordinates of the i +1 th positioning sampling time instant include a first coordinate component of the first axis direction and a second coordinate component of a second axis direction, the first axis direction being perpendicular to the second axis direction, and the corrected position coordinates of the i th positioning sampling time instant include a first corrected coordinate component of the first axis direction and a second corrected coordinate component of the second axis direction;
the first coordinate component is the sum of the first correction coordinate component and the first distance component, the first distance component is the product of the driving distance and the cosine of the included angle, the second coordinate component is the sum of the second correction coordinate component and the second distance component, and the second distance component is the product of the driving distance and the sine of the included angle.
12. The apparatus of claim 10, wherein the distance traveled within the time difference is determined by the radius of the wheel of the vehicle to be positioned and the wheel rotation angle sensed by the encoder.
13. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the positioning method of any of claims 1-6.
14. A non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the positioning method according to any one of claims 1 to 6.
15. A computer program product comprising a computer program which, when executed by a processor, implements a positioning method according to any one of claims 1-6.
16. An intelligent driving method, comprising:
acquiring a positioning coordinate of a vehicle at a target moment, wherein the positioning coordinate is a position coordinate obtained by fusing an acquisition position coordinate and a predicted position coordinate, the acquisition position coordinate is the position coordinate of the vehicle acquired at the target moment, and the predicted position coordinate is the predicted position coordinate of the vehicle at the target moment;
and carrying out intelligent driving control based on the positioning coordinates.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117053808A (en) * | 2023-07-06 | 2023-11-14 | 河北农业大学 | Automatic navigation method for agricultural machinery in field crop planting environment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117053808A (en) * | 2023-07-06 | 2023-11-14 | 河北农业大学 | Automatic navigation method for agricultural machinery in field crop planting environment |
| CN117053808B (en) * | 2023-07-06 | 2024-03-08 | 河北农业大学 | Automatic navigation method for agricultural machinery in field crop planting environment |
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