CN115973178B - Vehicle movement control method, apparatus, electronic device, and computer-readable medium - Google Patents
Vehicle movement control method, apparatus, electronic device, and computer-readable medium Download PDFInfo
- Publication number
- CN115973178B CN115973178B CN202310262448.XA CN202310262448A CN115973178B CN 115973178 B CN115973178 B CN 115973178B CN 202310262448 A CN202310262448 A CN 202310262448A CN 115973178 B CN115973178 B CN 115973178B
- Authority
- CN
- China
- Prior art keywords
- sensor
- timestamp
- sequence
- time stamp
- target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Traffic Control Systems (AREA)
- Arrangements For Transmission Of Measured Signals (AREA)
Abstract
Embodiments of the present disclosure disclose a vehicle movement control method, apparatus, electronic device, and computer-readable medium. One embodiment of the method comprises the following steps: acquiring a sensor data set, a sensor time stamp sequence set, a sensor time stamp differential value sequence set and a sensor time stamp differential mean value set; performing alignment processing on each sensor time stamp sequence in the sensor time stamp sequence set to obtain a reference sensor time stamp sequence set; updating the reference sensor time stamp sequence set to obtain a target sensor time stamp sequence set; determining sensor data corresponding to each target sensor timestamp in each target sensor timestamp sequence in the set of sensor data sets as a target sensor data sequence, and obtaining a target sensor data sequence set; the target sensor data sequence set is transmitted to the control terminal to control movement of the target vehicle. This embodiment can control the movement of the vehicle in time.
Description
Technical Field
Embodiments of the present disclosure relate to the field of computer technology, and in particular, to a vehicle movement control method, apparatus, electronic device, and computer readable medium.
Background
Because the frequencies of the data acquired by each vehicle-mounted sensor in the vehicle-mounted sensor assembly are different, in the vehicle movement control process, the time stamps of the sensor data acquired by each vehicle-mounted sensor are required to be aligned uniformly so as to facilitate the control terminal to control the vehicle to move. Currently, in controlling the movement of a vehicle, the following methods are generally adopted: and taking the time stamps of all sensor data of one sensor in the sensor assembly as a time stamp reference sequence or presetting a generated time stamp reference sequence, then determining an error interval of each time stamp reference in the time stamp reference sequence, traversing the time stamp sequences corresponding to all sensors in sequence, taking out the time stamps in the error interval as alignment time stamps, and finally controlling the movement of the vehicle according to the aligned sensor data.
However, the inventors found that when the movement of the vehicle is controlled in the above manner, there are often the following technical problems:
firstly, when a time stamp sequence is longer, comparing each time stamp can cause the comparison processing time to be increased, so that the sensor data cannot be aligned in time, and further, the movement of a vehicle cannot be controlled in time;
Second, only the time stamps within the error interval are of interest, and the missing time stamps and the number of missing time stamps are not of interest, resulting in a reduced accuracy of the aligned sensor data sequences and thus a reduced accuracy of the vehicle movement control.
The above information disclosed in this background section is only for enhancement of understanding of the background of the inventive concept and, therefore, may contain information that does not form the prior art that is already known to those of ordinary skill in the art in this country.
Disclosure of Invention
The disclosure is in part intended to introduce concepts in a simplified form that are further described below in the detailed description. The disclosure is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Some embodiments of the present disclosure propose a vehicle movement control method, apparatus, electronic device, and computer-readable medium to solve one or more of the technical problems mentioned in the background section above.
In a first aspect, some embodiments of the present disclosure provide a vehicle movement control method, the method comprising: acquiring a sensor data set, a sensor time stamp sequence set, a sensor time stamp differential value sequence set and a sensor time stamp differential mean value set; based on the sensor time stamp differential mean value set, performing alignment processing on each sensor time stamp sequence in the sensor time stamp sequence set to obtain a reference sensor time stamp sequence set; updating each reference sensor time stamp sequence in the reference sensor time stamp sequence set based on the sensor time stamp differential mean value set and the sensor time stamp differential value sequence set to generate a target sensor time stamp sequence, so as to obtain a target sensor time stamp sequence set; determining sensor data corresponding to each target sensor timestamp in each target sensor timestamp sequence in the sensor data set as a target sensor data sequence, and obtaining a target sensor data sequence set; and transmitting the target sensor data sequence set to a control terminal to control the driving of the target vehicle.
In a second aspect, some embodiments of the present disclosure provide a vehicle movement control apparatus, the apparatus comprising: an acquisition unit configured to acquire a sensor data set, a sensor time stamp sequence set, a sensor time stamp differential value sequence set, and a sensor time stamp differential mean set; an alignment unit configured to perform alignment processing on each sensor timestamp sequence in the sensor timestamp sequence set based on the sensor timestamp differential mean set, to obtain a reference sensor timestamp sequence set; an updating unit configured to update each reference sensor timestamp sequence in the reference sensor timestamp sequence set based on the sensor timestamp differential mean set and the sensor timestamp differential value sequence set to generate a target sensor timestamp sequence, and obtain a target sensor timestamp sequence set; a determining unit configured to determine, as a target sensor data sequence, sensor data in the set of sensor data sets corresponding to respective target sensor timestamps in the set of target sensor timestamp sequences, to obtain a set of target sensor data sequences; and a transmitting unit configured to transmit the target sensor data series set to the control terminal to control the target vehicle driving.
In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors causes the one or more processors to implement the method described in any of the implementations of the first aspect above.
In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.
The above embodiments of the present disclosure have the following advantageous effects: by the vehicle movement control method of some embodiments of the present disclosure, vehicle movement can be controlled in time. Specifically, the reason why the movement of the vehicle cannot be controlled in time is that: when the time stamp sequence is long, comparing each time stamp results in an increase in comparison processing time, thereby resulting in failure to perform alignment processing on the sensor data in time. Based on this, the vehicle movement control method of some embodiments of the present disclosure first acquires a sensor data set, a sensor time stamp sequence set, a sensor time stamp differential value sequence set, and a sensor time stamp differential mean set. And secondly, based on the sensor timestamp differential mean value set, performing alignment processing on each sensor timestamp sequence in the sensor timestamp sequence set to obtain a reference sensor timestamp sequence set. Thus, the time intervals from the first sensor timestamp to the last sensor timestamp in each sequence of sensor timestamps may be made equal for subsequent updating of each sequence of sensor timestamps. And updating each reference sensor time stamp sequence in the reference sensor time stamp sequence set based on the sensor time stamp differential average value set and the sensor time stamp differential value sequence set to generate a target sensor time stamp sequence, so as to obtain a target sensor time stamp sequence set. Thus, the number of sensor timestamps in each sensor timestamp sequence may be unified such that each sensor timestamp in each sensor timestamp sequence is aligned, respectively, for subsequent alignment of sensor data. Then, the sensor data corresponding to each target sensor timestamp in each target sensor timestamp sequence in the set of sensor data sets is determined as a target sensor data sequence, and a target sensor data sequence set is obtained. Therefore, the sensor data sequences corresponding to the sensor time stamp sequences can be updated according to the aligned sensor time stamp sequences, so that the sensor data sequences are aligned for subsequent control of vehicle movement. And finally, the target sensor data sequence set is sent to a control terminal to control the driving of the target vehicle. Therefore, according to some vehicle movement control methods disclosed by the disclosure, when the time stamp sequences are longer, the starting position and the ending position of each time stamp sequence can be aligned first, then the time stamps with the abnormality in each time stamp sequence are aligned, each time stamp in each time stamp sequence can be not required to be compared, the time of alignment can be reduced, so that the alignment of sensor data can be performed in time, and further, the movement of the vehicle can be controlled in time.
Drawings
The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. The same or similar reference numbers will be used throughout the drawings to refer to the same or like elements. It should be understood that the figures are schematic and that elements and components are not necessarily drawn to scale.
FIG. 1 is a flow chart of some embodiments of a vehicle movement control method according to the present disclosure;
FIG. 2 is a schematic structural view of some embodiments of a vehicle movement control device according to the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.
It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings. Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict.
It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.
It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.
The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.
The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 illustrates a flow 100 of some embodiments of a vehicle movement control method according to the present disclosure. The vehicle movement control method includes the steps of:
In some embodiments, the execution subject of the vehicle movement control method may acquire the sensor data set, the sensor time stamp series set, the sensor time stamp differential value series set, and the sensor time stamp differential mean set by way of a wired connection or a wireless connection. The target vehicle may be a moving vehicle.
It should be noted that the wireless connection may include, but is not limited to, 3G/4G connections, wiFi connections, bluetooth connections, wiMAX connections, zigbee connections, UWB (ultra wideband) connections, and other now known or later developed wireless connection means.
In some optional implementations of some embodiments, the executing entity acquiring the set of sensor data sets, the set of sensor time stamp sequences, the set of sensor time stamp differential value sequences, and the set of sensor time stamp differential mean values may include the steps of:
first, a sensor time stamp set and the sensor data set are obtained. Wherein the sensor time stamps in the sensor time stamp group are in one-to-one correspondence with the sensor data in the sensor data group. The set of sensor time stamp sets and the set of sensor data sets may be obtained from a sensor assembly of the target vehicle. Here, the sensors in the sensor assembly are in one-to-one correspondence with the sensor data sets in the sensor data set. The sensor timestamps in the set of sensor timestamp sets may characterize a time at which the sensor data in the set of sensor data sets was acquired.
As an example, the sensor in the sensor assembly described above may be, but is not limited to, at least one of: a wheel speed sensor, an acceleration sensor, an on-vehicle camera sensor, or a lidar sensor. When the sensor is a wheel speed sensor, the sensor data in the sensor data set may be indicative of a wheel speed of the target vehicle. When the sensor is a wheel speed sensor, the sensor data in the sensor data set may characterize acceleration of the target vehicle while traveling. When the sensor is an in-vehicle camera sensor, the sensor data in the sensor data set may characterize the environmental image information around the target vehicle. When the sensor is a lidar sensor, the sensor data in the sensor data set may characterize radar point cloud map information around the target vehicle.
And step two, sequencing each sensor time stamp group in the sensor time stamp group to generate a sensor time stamp sequence, so as to obtain the sensor time stamp sequence set. Wherein, the sensor timestamps in each sensor timestamp group in the sensor timestamp group set can be ordered in the order of the sensor timestamps from small to large.
And thirdly, determining a sensor time stamp differential value sequence corresponding to each sensor time stamp sequence in the sensor time stamp sequence set to obtain the sensor time stamp differential value sequence set. The difference between each sensor timestamp in the sensor timestamp sequence and the last sensor timestamp may be determined as a sensor timestamp difference value corresponding to the sensor timestamp, so as to obtain the sensor timestamp difference value sequence. Here, the preset time stamp differential value may be determined as the first sensor time stamp differential value in the above-described sensor time stamp differential value series.
As an example, the preset timestamp differential value may be 0.
And thirdly, determining the average value of each sensor timestamp differential value in each sensor timestamp differential value sequence in the sensor timestamp differential value sequence set as the sensor timestamp differential average value, and obtaining the sensor timestamp differential average value set.
And 102, based on the sensor timestamp differential mean value set, performing alignment processing on each sensor timestamp sequence in the sensor timestamp sequence set to obtain a reference sensor timestamp sequence set.
In some embodiments, the executing body may perform alignment processing on each sensor timestamp sequence in the sensor timestamp sequence set based on the sensor timestamp differential mean set, to obtain a reference sensor timestamp sequence set.
In some optional implementations of some embodiments, the executing body performs alignment processing on each sensor timestamp sequence in the sensor timestamp sequence set based on the sensor timestamp differential average set to obtain a reference sensor timestamp sequence set, and may include the following steps:
first, a target sensor time stamp sequence set is generated based on the sensor time stamp differential mean set and the sensor time stamp sequence set.
And a second step of generating the reference sensor time stamp sequence set based on the sensor time stamp differential mean set and the target sensor time stamp sequence set.
In some optional implementations of some embodiments, the executing entity may generate the target sensor timestamp sequence set based on the sensor timestamp differential mean set and the sensor timestamp sequence set, and may include the steps of:
The first step is to determine a first sensor timestamp in each sensor timestamp sequence in the sensor timestamp sequence set as a starting point timestamp, and obtain a starting point timestamp set. Wherein a first sensor timestamp in each of the set of sensor timestamp sequences may characterize a start time at which a sensor of the sensor assembly corresponding to the sensor timestamp sequence acquired sensor data.
And secondly, determining the largest starting point timestamp in the starting point timestamp set as a target starting point timestamp. Thus, the last starting sensor time stamp sequence in the set of sensor time stamp sequences can be determined, and the starting time of each sensor time stamp sequence in the set of sensor time stamp sequences can be unified with the target starting time stamp as a reference.
And thirdly, determining the difference value between each sensor time stamp differential mean value in the sensor time stamp differential mean value set and the target starting point time stamp as a reference starting point time stamp to obtain a reference starting point time stamp set.
Fourth, for each of the set of sensor time stamp sequences, performing the following first deletion sub-step to generate a target sensor time stamp sequence of the set of target sensor time stamp sequences:
A first sub-step of determining, as a target reference origin time stamp, a reference origin time stamp corresponding to the sensor time stamp sequence in the reference origin time stamp set.
And a second sub-step of deleting each sensor timestamp smaller than the target reference starting point timestamp in the sensor timestamp sequence from the sensor timestamp sequence to obtain the target sensor timestamp sequence.
In some optional implementations of some embodiments, the executing entity generating the reference sensor timestamp sequence set based on the sensor timestamp differential mean set and the target sensor timestamp sequence set may include the steps of:
and determining the last target sensor timestamp in each target sensor timestamp sequence in the target sensor timestamp sequence set as an end point timestamp to obtain an end point timestamp set. Wherein the last sensor timestamp in each of the set of sensor timestamp sequences may characterize an end time at which a sensor of the sensor assembly corresponding to the sensor timestamp sequence acquired sensor data.
And secondly, determining the smallest end point timestamp in the end point timestamp sets as a target end point timestamp. Thus, the first end sensor time stamp sequence in the target sensor time stamp sequence set can be determined, and the end time of each target sensor time stamp sequence in the target sensor time stamp sequence set can be unified based on the target end time stamp.
And thirdly, determining the sum of each sensor time stamp differential mean value in the sensor time stamp differential mean value set and the target end point time stamp as a reference end point time stamp to obtain a reference end point time stamp set.
Fourth, for each target sensor time stamp sequence in the set of target sensor time stamp sequences, performing the following second deletion sub-step to generate a reference sensor time stamp sequence in the set of reference sensor time stamp sequences:
a first sub-step of determining, as a target reference end point timestamp, a reference end point timestamp corresponding to the target sensor timestamp sequence in the reference end point timestamp set.
And a second sub-step of deleting each target sensor timestamp less than the target reference end point timestamp in the target sensor timestamp sequence from the target sensor timestamp sequence to obtain the reference sensor timestamp sequence.
And step 103, updating each reference sensor time stamp sequence in the reference sensor time stamp sequence set based on the sensor time stamp differential mean value set and the sensor time stamp differential value sequence set to generate a target sensor time stamp sequence, so as to obtain a target sensor time stamp sequence set.
In some embodiments, the executing entity may update each reference sensor timestamp sequence in the reference sensor timestamp sequence set based on the sensor timestamp differential mean set and the sensor timestamp differential value sequence set to generate a target sensor timestamp sequence, to obtain a target sensor timestamp sequence set.
In some optional implementations of some embodiments, the executing entity updates each reference sensor timestamp sequence in the reference sensor timestamp sequence set based on the sensor timestamp differential mean set and the sensor timestamp differential value sequence set to generate a target sensor timestamp sequence may include the steps of:
and determining each sensor time stamp difference value which is larger than a target threshold corresponding to the sensor time stamp difference value sequence in each sensor time stamp difference value sequence in the sensor time stamp difference value sequence set as a sensor data loss time stamp sequence to obtain a sensor data loss time stamp sequence set. Wherein the target threshold may be determined by the following formula:
Wherein, the liquid crystal display device comprises a liquid crystal display device,
representing the target threshold. />
Representing a preset scoring value. />
And representing the sensor time stamp differential average value corresponding to the sensor time stamp differential value sequence in the sensor time stamp differential average value set. />
Representing the above-mentioned sensorStandard deviation values of the time stamp differential values of the individual sensors in the sequence of time stamp differential values.
As an example, the preset score value may be 2.58.
And a second step of determining the sensor data loss amount corresponding to each sensor data loss time stamp in the sensor data loss time stamp sequence set based on the sensor time stamp differential average value set, and obtaining a sensor data loss amount sequence set. The sensor data loss amount may be obtained by rounding the sensor data loss time stamp with the sensor time stamp differential average value set corresponding to the sensor data loss time stamp.
And thirdly, updating the reference sensor time stamp sequence based on the sensor time stamp differential mean value set, the data loss time stamp sequence set and the data loss quantity sequence set to obtain the target sensor time stamp sequence.
In some optional implementations of some embodiments, the executing body updates the reference sensor timestamp sequence based on the sensor timestamp differential mean set, the data loss timestamp sequence set, and the data loss quantity sequence set to obtain the target sensor timestamp sequence, and may include the following steps:
the first step, based on the sensor time stamp differential mean value set, a data loss interval corresponding to each data loss time stamp in the data loss time stamp sequence set is generated, and a data loss interval set is obtained. The sensor timestamp differential mean value corresponding to the data loss timestamp in the sensor timestamp differential mean value set may be determined as a target timestamp mean value, then a difference value between the data loss timestamp and the target timestamp mean value may be determined as a lower limit of the data loss interval, and a sum value of the data loss timestamp and the target timestamp mean value may be determined as an upper limit of the data loss interval.
And secondly, determining the sensor time stamp in each data loss interval in the data loss interval set in the sensor time stamp sequence as a data disconnection time stamp, and obtaining a data disconnection time stamp sequence.
And thirdly, determining the maximum data loss in each data loss corresponding to each data disconnection time stamp in the data disconnection time stamp set in the data loss sequence set as the maximum data loss, and obtaining the maximum data loss sequence.
Fourth, based on the maximum data loss sequence and the reference sensor timestamp sequence, for each of the data-off timestamp sequences, performing the following third deletion sub-step to generate the target sensor timestamp sequence:
and a first sub-step of determining the maximum data loss corresponding to the data disconnection time stamp in the maximum data loss sequence as a target data loss.
And a second sub-step of deleting a reference sensor time stamp corresponding to the target data loss amount after the data disconnection point in the reference sensor time stamp sequence from the reference sensor time stamp sequence to obtain an initial sensor time stamp sequence.
And a third sub-step of determining the initial sensor time stamp sequence as the target sensor time stamp sequence in response to determining that the data disconnection point satisfies a preset condition. The preset condition may be that the data disconnection point is a last data disconnection point in the data disconnection point sequence.
Optionally, the executing body may further determine the initial sensor time stamp sequence as a reference sensor time stamp sequence in response to determining that the data disconnection time stamp does not satisfy the preset condition, so as to execute the third deletion sub-step again.
The related matter of step 103 is taken as an invention point of the embodiment of the present disclosure, and solves the second technical problem mentioned in the background art, namely "the accuracy of the vehicle movement control is reduced". Among them, factors that cause a decrease in accuracy of vehicle movement control tend to be as follows: only the time stamps within the error interval are of interest, and the missing time stamps and the number of missing time stamps are not of interest, resulting in a reduced accuracy of the aligned sensor data sequence. If the above factors are solved, the effect of improving the accuracy of the vehicle movement control can be achieved. To achieve this effect, the present disclosure may determine, according to a differential sequence of sensor timestamps, a time node at which data loss occurs and the amount of lost sensor data in the sequence of sensor timestamps, and then may synchronize different sensor data loss timestamps and corresponding sensor data loss amounts in each sequence of sensor timestamps to each sequence of sensor timestamps, and further, may make the number of sensor timestamps in the different sequences of sensor timestamps identical and one-to-one, so that the number of sensor data corresponding to the sensor timestamps in the different sequences of sensor timestamps may be identical and one-to-one. Thus, the accuracy of the aligned sensor data sequence can be improved, and the accuracy of the vehicle movement control can be improved.
And 104, determining sensor data corresponding to each target sensor time stamp in each target sensor time stamp sequence in the sensor data set as a target sensor data sequence, and obtaining a target sensor data sequence set.
In some embodiments, the executing entity may determine, as the target sensor data sequence, sensor data in the set of sensor data sets corresponding to the respective target sensor timestamps in the set of target sensor timestamp sequences, to obtain the set of target sensor data sequences.
In some embodiments, the executing entity may send the target sensor data sequence set to a control terminal to control movement of the target vehicle.
As an example, when the target sensor data sequence in the target sensor data sequence set is a wheel speed sensor data sequence or an acceleration sensor data sequence, the control terminal may control the target vehicle to accelerate or decelerate according to the wheel speed sensor data sequence and the acceleration sensor data sequence. When the target sensor data sequence in the target sensor data sequence set is a vehicle-mounted camera sensor data sequence or a laser radar sensor data sequence, the control terminal can control the target vehicle to avoid the obstacle according to the vehicle-mounted camera sensor data sequence and the laser radar sensor data sequence.
The above embodiments of the present disclosure have the following advantageous effects: by the vehicle movement control method of some embodiments of the present disclosure, vehicle movement can be controlled in time. Specifically, the reason why the movement of the vehicle cannot be controlled in time is that: when the time stamp sequence is long, comparing each time stamp results in an increase in comparison processing time, thereby resulting in failure to perform alignment processing on the sensor data in time. Based on this, the vehicle movement control method of some embodiments of the present disclosure first acquires a sensor data set, a sensor time stamp sequence set, a sensor time stamp differential value sequence set, and a sensor time stamp differential mean set. And secondly, based on the sensor timestamp differential mean value set, performing alignment processing on each sensor timestamp sequence in the sensor timestamp sequence set to obtain a reference sensor timestamp sequence set. Thus, the time intervals from the first sensor timestamp to the last sensor timestamp in each sequence of sensor timestamps may be made equal for subsequent updating of each sequence of sensor timestamps. And updating each reference sensor time stamp sequence in the reference sensor time stamp sequence set based on the sensor time stamp differential average value set and the sensor time stamp differential value sequence set to generate a target sensor time stamp sequence, so as to obtain a target sensor time stamp sequence set. Thus, the number of sensor timestamps in each sensor timestamp sequence may be unified such that each sensor timestamp in each sensor timestamp sequence is aligned, respectively, for subsequent alignment of sensor data. Then, the sensor data corresponding to each target sensor timestamp in each target sensor timestamp sequence in the set of sensor data sets is determined as a target sensor data sequence, and a target sensor data sequence set is obtained. Therefore, the sensor data sequences corresponding to the sensor time stamp sequences can be updated according to the aligned sensor time stamp sequences, so that the sensor data sequences are aligned for subsequent control of vehicle movement. And finally, the target sensor data sequence set is sent to a control terminal to control the driving of the target vehicle. Therefore, according to some vehicle movement control methods disclosed by the disclosure, when the time stamp sequences are longer, the starting position and the ending position of each time stamp sequence can be aligned first, then the time stamps with the abnormality in each time stamp sequence are aligned, each time stamp in each time stamp sequence can be not required to be compared, the time of alignment can be reduced, so that the alignment of sensor data can be performed in time, and further, the movement of the vehicle can be controlled in time.
With further reference to fig. 2, as an implementation of the method shown in the above figures, the present disclosure provides some embodiments of a vehicle movement control apparatus, which correspond to those method embodiments shown in fig. 1, and which are particularly applicable to various electronic devices.
As shown in fig. 2, the vehicle movement control apparatus 200 of some embodiments includes: an acquisition unit 201, an alignment unit 202, an update unit 203, a determination unit 204, and a transmission unit 205. Wherein the obtaining unit 201 is configured to obtain a sensor data set, a sensor timestamp sequence set, a sensor timestamp differential value sequence set and a sensor timestamp differential mean set; an alignment unit 202 configured to perform alignment processing on each sensor timestamp sequence in the sensor timestamp sequence set based on the sensor timestamp differential mean set, to obtain a reference sensor timestamp sequence set; an updating unit 203 configured to update each reference sensor timestamp sequence in the reference sensor timestamp sequence set based on the sensor timestamp differential mean set and the sensor timestamp differential value sequence set to generate a target sensor timestamp sequence, resulting in a target sensor timestamp sequence set; a determining unit 204 configured to determine, as a target sensor data sequence, sensor data in the set of sensor data sets corresponding to respective target sensor timestamps in the set of target sensor timestamp sequences, to obtain a set of target sensor data sequences; the transmitting unit 205 is configured to transmit the above-described target sensor data series set to the control terminal to control the target vehicle driving.
It is understood that the units described in the vehicle movement control apparatus 200 correspond to the respective steps in the vehicle movement control method described with reference to fig. 1. Thus, the operations, features, and advantages described above for the vehicle movement control method are equally applicable to the vehicle movement control device 200 and the units contained therein, and are not described here again.
Referring now to fig. 3, a schematic diagram of an electronic device 300 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic devices in some embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), car terminals (e.g., car navigation terminals), and the like, as well as stationary terminals such as digital TVs, desktop computers, and the like. The terminal device shown in fig. 3 is only one example and should not impose any limitation on the functionality and scope of use of the embodiments of the present disclosure.
As shown in fig. 3, the electronic device 300 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 301 that may perform various suitable actions and processes in accordance with a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage means 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic apparatus 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
In general, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 307 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 308 including, for example, magnetic tape, hard disk, etc.; and communication means 309. The communication means 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. While fig. 3 shows an electronic device 300 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead. Each block shown in fig. 3 may represent one device or a plurality of devices as needed.
In particular, according to some embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via communications device 309, or from storage device 308, or from ROM 302. The above-described functions defined in the methods of some embodiments of the present disclosure are performed when the computer program is executed by the processing means 301.
It should be noted that, the computer readable medium described in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having 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. In some embodiments of the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, the computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.
In some implementations, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.
The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring a sensor data set, a sensor time stamp sequence set, a sensor time stamp differential value sequence set and a sensor time stamp differential mean value set; based on the sensor time stamp differential mean value set, performing alignment processing on each sensor time stamp sequence in the sensor time stamp sequence set to obtain a reference sensor time stamp sequence set; updating each reference sensor time stamp sequence in the reference sensor time stamp sequence set based on the sensor time stamp differential mean value set and the sensor time stamp differential value sequence set to generate a target sensor time stamp sequence, so as to obtain a target sensor time stamp sequence set; determining sensor data corresponding to each target sensor timestamp in each target sensor timestamp sequence in the sensor data set as a target sensor data sequence, and obtaining a target sensor data sequence set; and transmitting the target sensor data sequence set to a control terminal to control the driving of the target vehicle.
Computer program code for carrying out operations for some embodiments of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted 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-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in some embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. The described units may also be provided in a processor, for example, described as: a processor includes an acquisition unit, an alignment unit, an update unit, a determination unit, and a transmission unit. The names of these units do not in any way limit the unit itself, and the acquisition unit may also be described as "a unit that acquires a set of sensor data sets, a set of sensor time stamps, a set of sensor time stamp differential values, and a set of sensor time stamp differential means", for example.
The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.
The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above technical features, but encompasses other technical features formed by any combination of the above technical features or their equivalents without departing from the spirit of the invention. Such as the above-described features, are mutually substituted with (but not limited to) the features having similar functions disclosed in the embodiments of the present disclosure.
Claims (10)
1. A vehicle movement control method, comprising:
acquiring a sensor data set, a sensor time stamp sequence set, a sensor time stamp differential value sequence set and a sensor time stamp differential mean value set;
based on the sensor timestamp differential mean value set, performing alignment processing on each sensor timestamp sequence in the sensor timestamp sequence set to obtain a reference sensor timestamp sequence set;
updating each reference sensor time stamp sequence in the reference sensor time stamp sequence set based on the sensor time stamp differential mean value set and the sensor time stamp differential value sequence set to generate a target sensor time stamp sequence, so as to obtain a target sensor time stamp sequence set;
determining sensor data corresponding to each target sensor timestamp in each target sensor timestamp sequence in the sensor data set and the target sensor timestamp sequence set as a target sensor data sequence, and obtaining a target sensor data sequence set;
the target sensor data sequence set is sent to a control terminal to control the movement of the target vehicle.
2. The method of claim 1, wherein the acquiring a set of sensor data sets, a set of sensor time stamp sequences, a set of sensor time stamp differential value sequences, and a set of sensor time stamp differential mean values comprises:
Acquiring a sensor timestamp group set and the sensor data group set, wherein the sensor timestamps in the sensor timestamp group set correspond to the sensor data in the sensor data group one by one;
sorting each sensor timestamp group in the sensor timestamp group sets to generate a sensor timestamp sequence, so as to obtain the sensor timestamp sequence set;
determining a sensor timestamp differential value sequence corresponding to each sensor timestamp sequence in the sensor timestamp sequence set to obtain the sensor timestamp differential value sequence set;
and determining the average value of each sensor timestamp differential value in each sensor timestamp differential value sequence in the sensor timestamp differential value sequence set as the sensor timestamp differential average value, and obtaining the sensor timestamp differential average value set.
3. The method of claim 1, wherein the aligning each sensor timestamp sequence in the set of sensor timestamp sequences based on the set of sensor timestamp differential averages to obtain a set of reference sensor timestamp sequences, comprises:
generating a target sensor timestamp sequence set based on the sensor timestamp differential mean set and the sensor timestamp sequence set;
The reference sensor timestamp sequence set is generated based on the sensor timestamp differential mean set and the target sensor timestamp sequence set.
4. The method of claim 3, wherein the generating a target sensor timestamp sequence set based on the sensor timestamp differential mean set and the sensor timestamp sequence set comprises:
determining a first sensor timestamp in each sensor timestamp sequence in the sensor timestamp sequence set as a starting point timestamp to obtain a starting point timestamp set;
determining the largest starting point timestamp in the starting point timestamp set as a target starting point timestamp;
determining the difference value between each sensor time stamp differential mean value in the sensor time stamp differential mean value sets and the target starting point time stamp as a reference starting point time stamp to obtain a reference starting point time stamp set;
for each sensor timestamp sequence in the set of sensor timestamp sequences, performing the following first deletion step to generate a target sensor timestamp sequence in the set of target sensor timestamp sequences:
determining a reference origin time stamp corresponding to the sensor time stamp sequence in the reference origin time stamp set as a target reference origin time stamp;
And deleting each sensor time stamp smaller than the target reference starting point time stamp in the sensor time stamp sequence from the sensor time stamp sequence to obtain the target sensor time stamp sequence.
5. The method of claim 3, wherein the generating the reference sensor timestamp sequence set based on the sensor timestamp differential mean set and the target sensor timestamp sequence set comprises:
determining the last target sensor timestamp in each target sensor timestamp sequence in the target sensor timestamp sequence set as an end point timestamp to obtain an end point timestamp set;
determining the smallest end point timestamp in the end point timestamp set as a target end point timestamp;
determining the sum of each sensor time stamp differential mean value in the sensor time stamp differential mean value set and the target end point time stamp as a reference end point time stamp to obtain a reference end point time stamp set;
for each target sensor timestamp sequence in the set of target sensor timestamp sequences, performing the following second deleting step to generate a reference sensor timestamp sequence in the set of reference sensor timestamp sequences:
Determining a reference end point timestamp corresponding to the target sensor timestamp sequence in the reference end point timestamp set as a target reference end point timestamp;
and deleting each target sensor time stamp smaller than the target reference end point time stamp in the target sensor time stamp sequence from the target sensor time stamp sequence to obtain the reference sensor time stamp sequence.
6. The method of claim 1, wherein the updating each reference sensor timestamp sequence of the reference sensor timestamp sequence set based on the sensor timestamp differential mean set and the sensor timestamp differential value sequence set to generate a target sensor timestamp sequence comprises:
determining each sensor timestamp difference value which is larger than a target threshold corresponding to the sensor timestamp difference value sequence in each sensor timestamp difference value sequence in the sensor timestamp difference value sequence set as a sensor data loss timestamp sequence, and obtaining a sensor data loss timestamp sequence set;
determining a sensor data loss amount corresponding to each sensor data loss timestamp in the sensor data loss timestamp sequence set based on the sensor timestamp differential mean value set, and obtaining a sensor data loss amount sequence set;
And updating the reference sensor time stamp sequence based on the sensor time stamp differential mean value set, the data loss time stamp sequence set and the data loss quantity sequence set to obtain the target sensor time stamp sequence.
7. The method of claim 6, wherein the updating the reference sensor timestamp sequence based on the sensor timestamp differential mean set, the data loss timestamp sequence set, and the data loss quantity sequence set to obtain the target sensor timestamp sequence comprises:
generating a data loss interval corresponding to each data loss time stamp in the data loss time stamp sequence set based on the sensor time stamp differential mean value set to obtain a data loss interval set;
determining a sensor timestamp in each data loss interval in the data loss interval set in the sensor timestamp sequence as a data disconnection timestamp, and obtaining a data disconnection timestamp sequence;
determining the maximum data loss in each data loss corresponding to each data disconnection time stamp in the data disconnection time stamp set in the data loss sequence set as the maximum data loss, and obtaining the maximum data loss sequence;
Based on the maximum data loss amount sequence and the reference sensor timestamp sequence, for each data-off timestamp in the data-off timestamp sequence, performing the following third deletion step to generate the target sensor timestamp sequence:
determining the maximum data loss amount corresponding to the data disconnection time stamp in the maximum data loss amount sequence as a target data loss amount;
deleting a reference sensor time stamp corresponding to the target data loss amount after the data disconnection point in the reference sensor time stamp sequence from the reference sensor time stamp sequence to obtain an initial sensor time stamp sequence;
in response to determining that the data disconnection point satisfies a preset condition, the initial sensor timestamp sequence is determined as the target sensor timestamp sequence.
8. A vehicle movement control device comprising:
an acquisition unit configured to acquire a sensor data set, a sensor time stamp sequence set, a sensor time stamp differential value sequence set, and a sensor time stamp differential mean set;
the alignment unit is configured to perform alignment processing on each sensor time stamp sequence in the sensor time stamp sequence set based on the sensor time stamp differential mean value set to obtain a reference sensor time stamp sequence set;
An updating unit configured to update each reference sensor timestamp sequence in the reference sensor timestamp sequence set based on the sensor timestamp differential mean set and the sensor timestamp differential value sequence set to generate a target sensor timestamp sequence, and obtain a target sensor timestamp sequence set;
a determining unit configured to determine sensor data in the sensor data set corresponding to each target sensor timestamp in each target sensor timestamp sequence in the target sensor timestamp sequence set as a target sensor data sequence, and obtain a target sensor data sequence set;
and a transmitting unit configured to transmit the target sensor data series set to a control terminal to control a target vehicle driving.
9. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon;
when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-7.
10. A computer readable medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the method of any of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310262448.XA CN115973178B (en) | 2023-03-17 | 2023-03-17 | Vehicle movement control method, apparatus, electronic device, and computer-readable medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310262448.XA CN115973178B (en) | 2023-03-17 | 2023-03-17 | Vehicle movement control method, apparatus, electronic device, and computer-readable medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115973178A CN115973178A (en) | 2023-04-18 |
| CN115973178B true CN115973178B (en) | 2023-05-23 |
Family
ID=85970862
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310262448.XA Active CN115973178B (en) | 2023-03-17 | 2023-03-17 | Vehicle movement control method, apparatus, electronic device, and computer-readable medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115973178B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109450582A (en) * | 2018-11-01 | 2019-03-08 | 百度在线网络技术（北京）有限公司 | Sensor time stabs synchronous detecting method, device, equipment, medium and vehicle |
| CN112445879A (en) * | 2019-09-04 | 2021-03-05 | 阿里巴巴集团控股有限公司 | Track data processing method and device, medium, terminal and server |
| CN113848696A (en) * | 2021-09-15 | 2021-12-28 | 北京易航远智科技有限公司 | Multi-sensor time synchronization method based on position information |
| CN115529096A (en) * | 2021-06-24 | 2022-12-27 | 高德软件有限公司 | Timestamp synchronization method, data acquisition platform and chip |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9075545B2 (en) * | 2012-08-01 | 2015-07-07 | Hewlett-Packard Development Company, L.P. | Synchronizing sensor data using timestamps and signal interpolation |
| US10647328B2 (en) * | 2018-06-11 | 2020-05-12 | Augmented Radar Imaging, Inc. | Dual-measurement data structure for autonomous vehicles |
| US10831631B2 (en) * | 2018-06-28 | 2020-11-10 | International Business Machines Corporation | Continuous time alignment of a collection of independent sensors |
| US11004224B2 (en) * | 2019-01-22 | 2021-05-11 | Velodyne Lidar Usa, Inc. | Generation of structured map data from vehicle sensors and camera arrays |
-
2023
- 2023-03-17 CN CN202310262448.XA patent/CN115973178B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109450582A (en) * | 2018-11-01 | 2019-03-08 | 百度在线网络技术（北京）有限公司 | Sensor time stabs synchronous detecting method, device, equipment, medium and vehicle |
| CN112445879A (en) * | 2019-09-04 | 2021-03-05 | 阿里巴巴集团控股有限公司 | Track data processing method and device, medium, terminal and server |
| CN115529096A (en) * | 2021-06-24 | 2022-12-27 | 高德软件有限公司 | Timestamp synchronization method, data acquisition platform and chip |
| CN113848696A (en) * | 2021-09-15 | 2021-12-28 | 北京易航远智科技有限公司 | Multi-sensor time synchronization method based on position information |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115973178A (en) | 2023-04-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110909521B (en) | Online document information synchronous processing method and device and electronic equipment | |
| CN115257727B (en) | Obstacle information fusion method and device, electronic equipment and computer readable medium | |
| CN113327598B (en) | Model training method, voice recognition method, device, medium and equipment | |
| CN112015816A (en) | Data synchronization method, device, medium and electronic equipment | |
| CN111596992B (en) | Navigation bar display method and device and electronic equipment | |
| CN115973178B (en) | Vehicle movement control method, apparatus, electronic device, and computer-readable medium | |
| CN116740382A (en) | Obstacle information generation method, obstacle information generation device, electronic device, and computer-readable medium | |
| CN113420400B (en) | Routing relation establishment method, request processing method, device and equipment | |
| CN112373471B (en) | Method, device, electronic equipment and readable medium for controlling vehicle running | |
| CN115817163B (en) | Method, apparatus, electronic device and computer readable medium for adjusting wheel speed of vehicle | |
| CN115908143B (en) | Vehicle cross-layer parking method, device, electronic equipment and computer readable medium | |
| CN112311842A (en) | Method and device for information interaction | |
| CN115991235B (en) | Vehicle steering control method, apparatus, electronic device, and computer-readable medium | |
| CN111628913A (en) | Online time length determining method and device, readable medium and electronic equipment | |
| CN116051657B (en) | Radar external parameter calibration method, radar external parameter calibration device, electronic equipment and computer readable medium | |
| CN116022159B (en) | Vehicle movement control method, apparatus, electronic device, and computer-readable medium | |
| CN114359673B (en) | Small sample smoke detection method, device and equipment based on metric learning | |
| CN112307320A (en) | Information pushing method and device, mobile terminal and storage medium | |
| CN111404824B (en) | Method, apparatus, electronic device, and computer-readable medium for forwarding request | |
| CN116566819B (en) | Simulation test communication method, simulation test communication device, electronic equipment and computer readable medium | |
| CN116580583B (en) | Vehicle scheduling information generation method, device, equipment and computer readable medium | |
| CN115937046B (en) | Road ground information generation method, device, equipment and computer readable medium | |
| CN115535080B (en) | Steering wheel zero deflection angle determination method and device, electronic equipment and readable medium | |
| CN112590811B (en) | Method, apparatus, electronic device, and medium for controlling longitudinal travel of vehicle | |
| CN118170779A (en) | Data processing method, medium, electronic device and program product of electronic form |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP03 | Change of name, title or address |
Address after: 201, 202, 301, No. 56-4 Fenghuang South Road, Huadu District, Guangzhou City, Guangdong Province, 510806 Patentee after: Heduo Technology (Guangzhou) Co.,Ltd. Address before: 100099 101-15, 3rd floor, building 9, yard 55, zique Road, Haidian District, Beijing Patentee before: HOLOMATIC TECHNOLOGY (BEIJING) Co.,Ltd. |
|
| CP03 | Change of name, title or address |