WO2022218306A1

WO2022218306A1 - Unmanned driving device

Info

Publication number: WO2022218306A1
Application number: PCT/CN2022/086368
Authority: WO
Inventors: 董峻峰; 何祎; 李秋成; 胡增科; 申浩; 夏华夏
Original assignee: 北京三快在线科技有限公司
Priority date: 2021-04-12
Filing date: 2022-04-12
Publication date: 2022-10-20
Also published as: CN112859131A; CN112859131B

Abstract

A positioning method and apparatus for an unmanned driving device. A positioning deviation function is obtained in advance through fitting on the basis of the proportion of regions that do not obstruct satellite signals among multiple regions in history and the positioning deviation in multiple regions. During the positioning of an unmanned driving device, the confidence of results of satellite positioning currently performed can be determined according to the proportion of the regions that do not obstruct satellite signals in a target region where the unmanned driving device is currently located and the pre-fitted positioning deviation function. Furthermore, according to the confidence of the results and the satellite positioning location determined by means of a satellite positioning method, fusion positioning is performed on the unmanned driving device.

Description

an unmanned vehicle

technical field

The present application relates to the field of unmanned driving technology, and in particular, to an unmanned driving device.

Background technique

At present, when positioning the unmanned equipment during the unmanned driving process, the location of the unmanned equipment is usually determined in real time based on a satellite positioning system such as the Global Positioning System (GPS). However, since the accuracy of satellite positioning is not accurate enough, other sensor devices, such as Inertial Measurement Unit (IMU), etc., need to be used to assist positioning.

Taking the unmanned device as an unmanned vehicle as an example, when the location of the unmanned vehicle is determined based on the satellite positioning system, the GPS sensor configured on the unmanned vehicle can receive the satellite signals of multiple positioning satellites, and according to the received The satellite signals of the multiple positioning satellites are determined, and the signal transmission duration of the multiple positioning satellites and the position information of the multiple positioning satellites are determined. Finally, the location of the unmanned vehicle is determined according to the location information of the multiple positioning satellites and the transmission duration of the signals transmitted to the unmanned vehicle.

SUMMARY OF THE INVENTION

Embodiments of the present disclosure provide a method and device for positioning an unmanned device.

The embodiment of the present disclosure adopts the following technical solutions:

A method for positioning an unmanned vehicle provided by the present disclosure includes:

Determine the target area where the unmanned equipment is currently located;

According to the proportion of the unobstructed satellite signal in the target area and the pre-fitted positioning deviation function, the confidence level of the current satellite positioning result of the unmanned device is determined, wherein the positioning deviation function is based on historical The proportion of unobstructed satellite signals in multiple areas and the positioning deviation in multiple areas are obtained by fitting;

Determine the current satellite positioning position of the unmanned device according to the received satellite signals of multiple satellites;

According to the current satellite positioning position of the unmanned device and the confidence level of the current satellite positioning result, the unmanned device is fused to locate the unmanned device, and the fused positioning position of the unmanned device is determined.

Optionally, determining the confidence level of the current satellite positioning result performed by the unmanned device specifically includes:

According to the first positioning deviation output by the positioning deviation function, and the second positioning deviation determined in the history of the target area, determine the positioning deviation of the satellite positioning performed by the unmanned device in the target area;

According to the positioning deviation of the satellite positioning performed by the unmanned device in the target area, the confidence level of the result of the current satellite positioning performed by the unmanned device is determined.

Optionally, according to the current satellite positioning position of the unmanned device and the confidence level of the current satellite positioning result, perform fusion positioning on the unmanned device, and determine the fusion positioning position of the unmanned device, Specifically include:

In response to the confidence of the result being greater than a preset threshold, perform fusion positioning according to the satellite positioning position and other positioning methods, and determine the fusion positioning position of the unmanned device, wherein the other positioning methods include IMU positioning, laser positioning One or more of radar positioning and visual positioning;

In response to the result confidence being less than or equal to a preset threshold, the fusion positioning position of the unmanned device is determined according to other positioning methods.

Optionally, the method further includes:

Determine the incremental deviation of satellite positioning in the target area according to the fusion positioning position of the unmanned device and the satellite positioning position of the unmanned device;

According to the incremental deviation of the satellite positioning in the target area, the second positioning deviation of the satellite positioning in the target area in the history is updated.

Optionally, according to the incremental deviation of satellite positioning in the target area, updating the historical second positioning deviation of satellite positioning in the target area, including:

According to the average value of the incremental deviations of the satellite positioning performed in the target area several times in the history, the second positioning deviation of the satellite positioning performed in the target area in the history is updated.

Optionally, fit a positioning deviation function, including:

Obtain the historical positioning deviation generated by satellite positioning in multiple pre-divided areas;

For each area of the pre-divided multiple areas, according to the obstacle information of one or more obstacles corresponding to the area, determine the proportion of areas in the area that receive satellite signals that are not blocked by obstacles;

The positioning deviation function is obtained by fitting according to the proportion of the unobstructed satellite signals in the multiple regions and the positioning deviation generated in the multiple regions.

Optionally, according to the obstacle information of one or more obstacles corresponding to the area, determine the proportion of areas in the area that receive satellite signals that are not blocked by obstacles, including:

According to the obstacle information of one or more obstacles corresponding to the area, determine the angular range in which the satellite signal is received at the center point of the area without being blocked by obstacles;

According to the angular range of the received satellite signal at the center of the area that is not blocked by obstacles, determine

The proportion of the area that receives satellite signals and is not blocked by obstacles in this area.

The present disclosure provides a positioning device for unmanned equipment, including:

The area determination module determines the target area where the unmanned equipment is currently located;

The confidence level determination module determines the confidence level of the current satellite positioning result performed by the unmanned device according to the proportion of the unobstructed satellite signal in the target area and the pre-fitted positioning deviation function, wherein the positioning The deviation function is fitted according to the proportion of unobstructed satellite signals in multiple regions in history and the positioning deviation in multiple regions;

a satellite positioning module, for determining the current satellite positioning position of the unmanned device according to the received satellite signals of multiple satellites;

The fusion positioning module performs fusion positioning on the unmanned equipment according to the current satellite positioning position of the unmanned equipment and the confidence level of the current satellite positioning result, and determines the fusion positioning position of the unmanned equipment.

The present disclosure provides a computer-readable storage medium, where a computer program is stored in the storage medium, and when the computer program is executed by a processor, the above-mentioned positioning method for an unmanned vehicle is implemented.

An unmanned device provided by the present disclosure includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the above-mentioned positioning method for the unmanned device when the program is executed. .

The above-mentioned at least one technical solution adopted in the embodiments of the present disclosure can achieve the following beneficial effects:

In the embodiment of the present disclosure, the positioning deviation function is obtained in advance based on the proportion of the regions in which the satellite signals are not blocked in the history and the positioning deviation in the multiple regions. When positioning the unmanned device, the confidence of the current satellite positioning result can be determined according to the proportion of the unobstructed satellite signal in the target area where the unmanned device is currently located, and the pre-fitted positioning deviation function. Spend. And according to the confidence of the result and the satellite positioning position determined by the satellite positioning method, the unmanned equipment is fused and positioned. By determining the confidence of the current satellite positioning result of the unmanned equipment, and positioning based on the confidence of the result, the accuracy of the positioning of the unmanned equipment is improved.

Description of drawings

The drawings described herein are used to provide further understanding of the present application and constitute a part of the present application. The schematic embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation of the present application. In the attached image:

1 is a schematic flowchart of a method for locating an unmanned device according to an embodiment of the present disclosure;

2A-2B are schematic diagrams of determining the proportion of unobstructed satellite signal areas in a target area according to an embodiment of the present disclosure;

3 is a schematic diagram of updating result confidence based on incremental deviation according to an embodiment of the present disclosure;

FIG. 4 is a schematic structural diagram of a positioning device for an unmanned device according to an embodiment of the present disclosure;

FIG. 5 is a schematic diagram of an unmanned device for implementing a method for positioning an unmanned device according to an embodiment of the present disclosure.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present disclosure clearer, the technical solutions of the present application will be described clearly and completely below with reference to the specific embodiments of the present disclosure and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the description, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

The present disclosure provides a positioning method for an unmanned device, as shown in FIG. 1 .

1 is a schematic flowchart of a method for locating an unmanned device according to an embodiment of the present disclosure, which may specifically include the following steps:

S100: Determine the target area where the unmanned device is currently located.

In one or more embodiments of the present disclosure, the unmanned device may be a device such as an unmanned vehicle, a drone, and a robot. With the positioning method provided by the present disclosure, the position of the unmanned device during the driving process can be determined in real time.

Specifically, when positioning the unmanned device, the current position of the unmanned device may be roughly determined first. After that, according to the current position of the unmanned device and the corresponding position ranges of the pre-divided areas, determine the target area where the unmanned device currently falls, that is, the target area where the unmanned device is currently located. . Among them, the pre-divided areas can be divided according to the unit range, for example, the ground area is divided into several squares with a side length of 5 meters.

It should be noted that the above rough determination of the current position of the unmanned device is not very accurate. The current position of the unmanned device can be roughly determined according to the latest positioning result of the unmanned device in the history. Of course, any existing positioning method can also be used to roughly determine the position of the unmanned device, such as base station positioning, satellite positioning, and lidar positioning, etc., which are not limited in this disclosure, and can be set as required. .

S102: Determine the confidence level of the current satellite positioning result performed by the unmanned device according to the proportion of the area in the target area that does not block satellite signals and the pre-fitted positioning deviation function.

In one or more embodiments of the present disclosure, after roughly determining the target area where the unmanned device is located, it can be determined whether the satellite positioning of the unmanned device is accurate according to the occlusion of the satellite signal by the target area. .

Specifically, after the target area where the unmanned device is located is determined, the area proportion of the unobstructed satellite signals in the target area can be determined from the pre-stored area proportions of the unobstructed satellite signals corresponding to the multiple areas. Compare. After that, the proportion of the area in the target area that does not block the satellite signal is input into the pre-fitted positioning deviation function to obtain the positioning deviation generated by the satellite positioning of the unmanned vehicle in the target area. Finally, according to the positioning deviation generated by the satellite positioning performed by the unmanned equipment in the target area, the confidence level of the current satellite positioning result of the unmanned equipment is determined.

Among them, the pre-divided multiple areas refer to multiple grids divided according to the unit range, and the area that does not block the satellite signal refers to the area where the unmanned device can directly receive the satellite signal, that is, the satellite signal It is directly received by the unmanned device without being blocked by any obstacle. In addition, the positioning deviation is negatively correlated with the confidence of the result. The larger the positioning deviation, the smaller the confidence of the result, indicating that the positioning result of the current satellite positioning is inaccurate.

In some embodiments, when determining the confidence of the current satellite positioning result performed by the unmanned device, the positioning deviation output based on the pre-fitted positioning deviation function may be used as the first positioning deviation. Combined with the second positioning deviation determined by satellite positioning in the target area in the history, and the first positioning deviation, determine the positioning deviation of the satellite positioning of the unmanned equipment in the target area, for example, the unmanned equipment is in The positioning deviation of the satellite positioning of the target area may be an average value of the first positioning deviation and the second positioning deviation. According to the positioning deviation of the satellite positioning performed by the unmanned device in the target area, the confidence level of the current satellite positioning result of the unmanned device is determined. For example, the positioning deviation of the satellite positioning performed by the unmanned device in the target area is the same as The confidence of the results is negatively correlated, and the greater the positioning deviation, the lower the confidence of the results.

S104: Determine the current satellite positioning position of the unmanned device according to the received satellite signals of multiple satellites.

S106: According to the current satellite positioning position of the unmanned device and the confidence level of the current satellite positioning result, perform fusion positioning on the unmanned device, and determine the fusion positioning position of the unmanned device.

The positioning method provided by the present disclosure can determine the precise position of the unmanned device based on the confidence of the current satellite positioning result of the unmanned device.

Specifically, the unmanned device can receive satellite signals of multiple satellites through the GPS sensor configured by itself, and determine the current status of the unmanned device by means of satellite positioning based on the received satellite signals of multiple satellites. Satellite positioning location.

Afterwards, it can be determined whether the confidence level of the result of the current satellite positioning performed by the unmanned device is greater than a preset threshold. When it is determined that the confidence level of the result is greater than the preset threshold, it indicates that the result of the current satellite positioning is credible, and it can be determined that the current satellite positioning position of the unmanned device is accurate. Therefore, the fusion positioning can be performed according to the satellite positioning position determined by the satellite positioning method and other positioning methods, and the fusion positioning position of the unmanned device can be determined. Among them, the fusion positioning position is the more accurate position of the unmanned device.

When it is determined that the confidence level of the result is less than the preset threshold, it indicates that the current satellite positioning result is unreliable, and it can be determined that the current satellite positioning position of the unmanned device is inaccurate. Therefore, other positioning methods can be used to locate the unmanned device to determine the fusion positioning position of the unmanned device. Wherein, the preset threshold can be set as required, for example, set to 0.5. The other positioning manner may be one or more of IMU positioning, lidar positioning, and visual positioning, which is not limited in the present disclosure.

Due to the dense distribution of buildings in cities, multi-path effects are prone to occur when transmitting satellite signals, resulting in inaccurate satellite positioning, which in turn makes unmanned vehicle positioning errors larger. Based on the positioning method of the unmanned vehicle shown in FIG. 1 , the embodiment of the present disclosure obtains the positioning deviation function in advance based on the proportion of the regions in which the satellite signals are not blocked in the history and the positioning deviation in the multiple regions. When positioning the unmanned device, the confidence of the current satellite positioning result can be determined according to the proportion of the unobstructed satellite signal in the target area where the unmanned device is currently located, and the pre-fitted positioning deviation function. Spend. And according to the confidence of the result and the satellite positioning position determined by the satellite positioning method, the unmanned equipment is fused and positioned. By determining the confidence of the current satellite positioning result of the unmanned device, and performing positioning based on the confidence of the result, the accuracy of the positioning of the unmanned device is improved.

In step S102 of the present disclosure, when determining the area ratio of the unobstructed signals in the multiple areas, specifically, for each area in the pre-divided multiple areas, one or more obstacles corresponding to the area may be determined first. , that is, one or more obstacles around the area or inside the area. Then, according to the obstacle information of one or more obstacles corresponding to the area, such as position information and altitude information, etc., determine the angular range in which the satellite signal is received at the center point of the area without being blocked by the obstacle. Finally, according to the angular range of the received satellite signal at the center point of the area that is not blocked by obstacles, the proportion of the area in which the received satellite signal is not blocked by obstacles is determined.

2A-2B are schematic diagrams of determining the proportion of unobstructed satellite signal areas in a target area according to an embodiment of the present disclosure. In FIG. 2A , for the target area where the unmanned device is currently located, there are buildings with different heights on both sides of the target area, and the buildings are obstacles that block satellite signals in the target area.

Generally, the ideal signal receiving area is that there are no obstacles blocking the satellite signal within a range of 180 degrees in the front, rear, left and right. However, in actual roads, there are usually no obstacles that block satellite signals in the direction of road extension, so satellite signals received in the range of -90° to 90° in the direction of road extension are not blocked by obstacles. However, due to the existence of obstacles on both sides of the road, some angles in the direction perpendicular to the road are blocked. As shown in Figure 2A, within the range of -90°～-α° and β°～90° of the target area, due to Obstacles block and cannot receive satellite signals. Therefore, according to the obstacle information such as the position and height of the obstacle corresponding to the target area, it can be determined that the angle range of the satellite signal received by the target area not blocked by the obstacle in the vertical road direction is -α°～β°.

In FIG. 2B , a two-dimensional polar coordinate system is established with the angular ranges of receiving satellite signals in two different directions, "road extension direction" and "vertical road direction" as coordinate axes. After that, according to the target area, the angular range -90°～90° when the satellite signal is not blocked by obstacles in the direction of road extension, and the angular range -α°～90° when the satellite signal is received in the vertical direction of the road and not blocked by obstacles β°, to determine the area that does not block the satellite signal and the proportion of the area in the target area. Among them, the blank area represents the area where the satellite signal is not blocked, and the gray filled area represents the area where the obstacle blocks the satellite signal.

In addition, the pre-fitted positioning deviation function in the present disclosure can be obtained by fitting based on the proportion of the regions in which the satellite signals are not blocked in the history and the positioning deviation in the multiple regions. When fitting the positioning deviation function, historical positioning deviations generated by satellite positioning in a plurality of pre-divided regions can be obtained first. Afterwards, for each of the pre-divided areas, the proportion of the area in which the satellite signal is received and not blocked by the obstacle may be determined according to the obstacle information of one or more obstacles corresponding to the area. Finally, according to the proportion of unobstructed satellite signals in multiple regions, and the positioning deviation generated in multiple regions, the positioning deviation function is obtained by fitting. The specific manner of determining the proportion of the areas in which the received satellite signals are not blocked by obstacles has been described in detail above, and will not be repeated in the present disclosure.

In addition, due to the high requirements for real-time positioning of unmanned devices, and the proportion of areas that do not block satellite signals in multiple areas, one or more obstacles corresponding to each area in the multiple areas in the high-precision map need to be determined. The amount of calculation is large. Therefore, in the present disclosure, the proportion of the areas that do not block satellite signals in the multiple areas to be driven by the unmanned device can be pre-determined offline, and the positioning deviation function can be pre-fitted. When positioning is required, the proportion of the unobstructed satellite signal area in the target area where the unmanned vehicle is currently located can be directly determined from the pre-stored area proportions of the unobstructed satellite signals corresponding to the multiple areas, and based on the The proportion of the unobstructed satellite signal area in the target area, and the pre-fitted positioning deviation function, determine the positioning deviation of satellite positioning in the target area. The calculation amount required for positioning is reduced, and the real-time performance of positioning is improved.

In step S106 of the present disclosure, after the position of the unmanned device is accurately determined by the fusion positioning method, the satellite positioning position obtained by the satellite positioning method can be corrected according to the precise fusion positioning position. Specifically, the incremental deviation of satellite positioning in the target area can be determined according to the fusion positioning position of the unmanned device, the satellite positioning position, and the positioning deviation of satellite positioning in the target area. Then, according to the incremental deviation of satellite positioning in the target area, update the second positioning deviation of satellite positioning in the target area in the history, so as to correct the satellite positioning in the target area according to the second positioning deviation The resulting positioning error.

To sum up, as shown in Figure 3, the unmanned device can determine its own satellite positioning position based on the received satellite signals, and based on the current satellite positioning position and the confidence of the satellite positioning result, The human-driving device performs fusion positioning to determine the fusion positioning position. The confidence of the satellite positioning result may be determined based on the first positioning deviation output by the fitted positioning deviation function and the second positioning deviation determined in the target area in the history. After that, the incremental deviation generated by satellite positioning in the target area can be determined according to its own fusion positioning position and satellite positioning position, so as to update the second positioning deviation according to the incremental deviation, and then update the second positioning deviation in the target area. Confidence in the result of satellite positioning. Through continuous iterative update, the result confidence of the target area is made more accurate.

In some embodiments, in order to more accurately correct the deviation of satellite positioning, incremental deviations generated by satellite positioning in the target area for several times in the history may also be obtained, and according to the difference of the incremental deviations generated several times Average, update the second positioning deviation of satellite positioning in the target area in history.

In some embodiments, based on the target area where the unmanned device is currently located, the horizontal position deviation (also referred to as positioning deviation) (unit meters) of the satellite positioning in the area may be estimated. This estimated bias can be used in the calculation of the final fused localization algorithm. The following embodiments specifically illustrate the positioning method for an unmanned vehicle provided by the embodiments of the present disclosure, including steps 1 to 3:

Step 1: Obtain a fitting function S that is estimated to represent the satellite positioning position error according to the occlusion of the sky.

In the above embodiment, the fitting function S is a positioning deviation function. When obtaining the fitting function S, collect multiple sample data, each sample data contains satellite positioning position (x, y), real position (x', y'), and the proportion of unobstructed satellite signal area p. The true location may be a fused location location. For each sample data, the sample data is further processed to obtain a sample point whose abscissa is p and the ordinate is the satellite horizontal positioning deviation value d. Specifically, the value range of p may be [0.0, 1.0], and the calculation formula of the satellite positioning horizontal position deviation d may be d=sqrt((x-x')^2+(y-y')^2). Curve fitting is performed on multiple sample points to obtain a curve function d=S(p). Enter the proportion p of the unobstructed satellite signal area, and the corresponding estimated horizontal position deviation d can be obtained through this function.

Step 2: When drawing a map for the first time, record the horizontal position deviation d of satellite positioning.

The map is rasterized in the horizontal direction to obtain multiple grids. For each grid Ci (i is the grid number), calculate the proportion pi of the unobstructed satellite signal area at this grid position. The satellite position error estimate (positioning deviation) di=S(pi) for the grid is obtained by function S. Record the estimated satellite position error di in the map grid Ci.

Step 3: Constantly correct the estimated satellite position error in the map during the actual operation of the map.

Through the actual operation data, when the unmanned equipment is in the grid Ci, the observed satellite positioning results (xi,yi) and the vehicle fusion positioning position (xi",yi") at that time, and calculate the horizontal position of the satellite positioning Incremental deviation di'. Specifically, the calculation method of di' may be di'=sqrt((xi-xi")^2+(yi-yi")^2). Since the unmanned device may travel to the grid Ci multiple times, the average value of the horizontal incremental deviation of the satellite positioning can be calculated based on multiple di'.

Corrections are made to the satellite position error estimates recorded in raster Ci. The estimated value of the original satellite horizontal position error recorded in Ci is di(old). When the average satellite positioning horizontal position error average is obtained, di(old) can be corrected according to a fixed correction coefficient α, and the correction amount is α *(average-di(old)). The coefficient α controls the speed of correction, and its value is 0.0 to 1.0 (the recommended value is 0.1 according to engineering experience, which can make the correction amount gradually approach the average, and prevent the di' value from fluctuating violently due to accidental factors). The revised estimate of the horizontal position error of the new satellite is di(new)=di(old)+α*(average−di(old)). Record the new value di(new) into the map grid Ci, replacing the original value di(old).

Combining steps 1 to 3, the unmanned equipment can not only obtain the position deviation estimated by the satellite positioning receiver when driving, but also obtain the satellite positioning deviation for the fusion algorithm by directly checking the position of the unmanned equipment.

The positioning method shown in this disclosure can be specifically used in the process of unmanned distribution. When the positioning method is applied to perform an unmanned distribution task, the unmanned device can determine its own position in real time through the positioning method in this disclosure, so as to determine its own position according to its own The distribution path is planned according to the location, and the distribution task is executed according to the planned path.

Based on the positioning method for an unmanned device shown in FIG. 1 , an embodiment of the present disclosure also provides a schematic structural diagram of a positioning device for an unmanned device, as shown in FIG. 4 .

FIG. 4 is a schematic structural diagram of a positioning device for an unmanned device provided by an embodiment of the present disclosure, including:

The area determination module 200 determines the target area where the unmanned device is currently located;

The confidence level determination module 202 determines the confidence level of the current satellite positioning result performed by the unmanned device according to the proportion of the unobstructed satellite signal in the target area and the pre-fitted positioning deviation function, wherein the The positioning deviation function is fitted according to the proportion of unobstructed satellite signals in multiple regions in history and the positioning deviation in multiple regions;

The satellite positioning module 204 determines the current satellite positioning position of the unmanned device according to the received satellite signals of multiple satellites;

The fusion positioning module 206, according to the current satellite positioning position of the unmanned equipment and the confidence of the current satellite positioning result, perform fusion positioning on the unmanned equipment, and determine the fusion positioning position of the unmanned equipment .

Optionally, the confidence level determination module 202 is specifically configured to determine the unmanned vehicle according to the first positioning deviation output by the positioning deviation function and the second positioning deviation historically determined in the target area. The positioning deviation of the satellite positioning performed in the target area is determined according to the positioning deviation of the satellite positioning performed by the unmanned device in the target area to determine the confidence level of the current satellite positioning result performed by the unmanned device.

Optionally, the fusion positioning module 206 is specifically configured to determine whether the confidence of the result is greater than a preset threshold, and if so, perform fusion positioning according to the satellite positioning position and other positioning methods to determine the unmanned vehicle. If not, determine the fusion positioning position of the unmanned vehicle according to other positioning methods.

Optionally, the fusion positioning module 206 is further configured to, according to the fusion positioning position of the unmanned equipment and the satellite positioning position of the unmanned equipment, determine the increment of satellite positioning in the target area. The deviation, according to the incremental deviation of the satellite positioning in the target area, update the second positioning deviation of the satellite positioning in the target area in the history.

Optionally, the fusion positioning module 206 is further configured to, according to the average value of the incremental deviations of satellite positioning performed in the target area several times in the history, update the number of satellite positioning performed in the history in the target area. Two positioning deviation.

Optionally, the positioning device of the unmanned equipment further includes an offline fitting module 208, and the offline fitting module 208 is specifically configured to acquire the positioning deviations generated by satellite positioning in the pre-divided regions in the history. , for each area of the pre-divided multiple areas, according to the obstacle information of one or more obstacles corresponding to the area, determine the proportion of the area receiving satellite signals that are not blocked by obstacles in the area. The proportion of unobstructed satellite signals in the region and the positioning deviation generated in multiple regions are fitted to obtain the positioning deviation function.

Optionally, the offline fitting module 208 is specifically configured to, according to the obstacle information of one or more obstacles corresponding to the area, determine the angular range in which the satellite signal is received at the center point of the area without being blocked by the obstacle, According to the angular range of receiving satellite signals at the center point of the area that is not blocked by obstacles, determine the proportion of the area where satellite signals are received and not blocked by obstacles in the area.

Embodiments of the present disclosure further provide a computer-readable storage medium, where a computer program is stored in the storage medium, and the computer program can be used to execute the method for positioning an unmanned vehicle provided in FIG. 1 .

Based on the positioning method of the unmanned device shown in FIG. 1 , an embodiment of the present disclosure also proposes a schematic structural diagram of the unmanned device shown in FIG. 5 . As shown in Figure 5, at the hardware level, the driverless device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and of course, it may also include hardware required by other services. The processor reads the corresponding computer program from the non-volatile memory into the memory and runs it, so as to realize the positioning method of the unmanned vehicle shown in FIG. 1 above.

Of course, in addition to software implementation, the present disclosure does not exclude other implementations, such as logic devices or a combination of software and hardware, etc., that is to say, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic device.

In the 1990s, improvements in a technology could be clearly differentiated between improvements in hardware (eg, improvements to circuit structures such as diodes, transistors, switches, etc.) or improvements in software (improvements in method flow). However, with the development of technology, the improvement of many methods and processes today can be regarded as a direct improvement of the hardware circuit structure. Designers almost get the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be realized by hardware entity modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is an integrated circuit whose logic function is determined by user programming of the device. It is programmed by the designer to "integrate" a digital system on a PLD, without the need for a chip manufacturer to design and generate a dedicated integrated circuit chip. Moreover, instead of manually generating integrated circuit chips, this kind of programming is now mostly implemented using "logic compiler" software, which is similar to the software compiler used in program development and writing, and needs to be compiled before compiling. The original code also has to be written in a specific programming language, which is called Hardware Description Language (HDL), and there is not only one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language) , AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc., currently the most commonly used The ones are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. It should also be clear to those skilled in the art that a hardware circuit for implementing the logic method process can be easily obtained by simply programming the method process in the above-mentioned several hardware description languages and programming it into the integrated circuit.

The controller may be implemented in any suitable manner, for example, the controller may take the form of eg a microprocessor or processor and a computer readable medium storing computer readable program code (eg software or firmware) executable by the (micro)processor , logic gates, switches, application specific integrated circuits (ASICs), programmable logic controllers and embedded microcontrollers, examples of controllers include but are not limited to the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20 and Silicon Labs C8051F320, the memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that, in addition to implementing the controller in the form of pure computer-readable program code, the controller can be implemented as logic gates, switches, application-specific integrated circuits, programmable logic controllers and embedded devices by logically programming the method steps. The same function can be realized in the form of a microcontroller, etc. Therefore, such a controller can be regarded as a hardware component, and the devices included therein for realizing various functions can also be regarded as a structure within the hardware component. Or even, the means for implementing various functions can be regarded as both a software module implementing a method and a structure within a hardware component.

The systems, devices, modules or units described in the above embodiments may be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or A combination of any of these devices.

For the convenience of description, when describing the above device, the functions are divided into various units and described respectively. Of course, when implementing the present disclosure, the functions of each unit may be implemented in one or more software and/or hardware.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block in the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for implementing the functions specified in a flow or flow of a flowchart and/or a block or blocks of a block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions The apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

Memory may include forms of non-persistent memory, random access memory (RAM) and/or non-volatile memory in computer readable media, such as read only memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media includes both persistent and non-permanent, removable and non-removable media, and storage of information may be implemented by any method or technology. Information may be computer readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), Flash Memory or other memory technology, Compact Disc Read Only Memory (CD-ROM), Digital Versatile Disc (DVD) or other optical storage, Magnetic tape cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.

It should also be noted that the terms "comprising", "comprising" or any other variation thereof are intended to encompass a non-exclusive inclusion such that a process, method, article or device comprising a series of elements includes not only those elements, but also Other elements not expressly listed or inherent to such a process, method, article of manufacture or apparatus are also included. Without further limitation, an element qualified by the phrase "comprising a..." does not preclude the presence of additional identical elements in a process, method, article of manufacture or apparatus that includes the element.

As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present disclosure may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The disclosure may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including storage devices.

The various embodiments in the present disclosure are described in a progressive manner, and the same and similar parts between the various embodiments may be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, as for the system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and for related parts, please refer to the partial descriptions of the method embodiments.

The above descriptions are merely embodiments of the present disclosure, and are not intended to limit the present disclosure. Various modifications and variations of the present disclosure will occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure shall be included within the scope of the claims of the present disclosure.

Claims

A positioning method for an unmanned device, comprising:

Determine the target area where the unmanned equipment is currently located;

According to the proportion of the unobstructed satellite signal in the target area and the pre-fitted positioning deviation function, the confidence level of the current satellite positioning result of the unmanned device is determined, wherein the positioning deviation function is based on historical The proportion of unobstructed satellite signals in multiple areas and the positioning deviation in multiple areas are obtained by fitting;

Determine the current satellite positioning position of the unmanned device according to the received satellite signals of multiple satellites;

According to the current satellite positioning position of the unmanned device and the confidence level of the current satellite positioning result, the unmanned device is fused to locate the unmanned device, and the fused positioning position of the unmanned device is determined.
The method of claim 1, wherein determining the confidence level of the satellite positioning result currently performed by the unmanned device comprises:

According to the first positioning deviation output by the positioning deviation function, and the second positioning deviation determined in the history of the target area, determine the positioning deviation of the satellite positioning performed by the unmanned device in the target area;

According to the positioning deviation of the satellite positioning performed by the unmanned device in the target area, the confidence level of the result of the current satellite positioning performed by the unmanned device is determined.
The method according to claim 1 or 2, wherein, according to the current satellite positioning position of the unmanned device and the confidence of the result of the current satellite positioning, the unmanned device is fused and positioned to determine the said unmanned device. The fusion positioning position of unmanned equipment, including:

In response to the confidence of the result being greater than a preset threshold, perform fusion positioning according to the satellite positioning position and other positioning methods, and determine the fusion positioning position of the unmanned device, wherein the other positioning methods include IMU positioning, laser positioning One or more of radar positioning and visual positioning;

In response to the result confidence being less than or equal to a preset threshold, the fusion positioning position of the unmanned device is determined according to other positioning methods.
The method of claim 2, wherein the method further comprises:

Determine the incremental deviation of satellite positioning in the target area according to the fusion positioning position of the unmanned device and the satellite positioning position of the unmanned device;

According to the incremental deviation of the satellite positioning in the target area, the second positioning deviation of the satellite positioning in the target area in the history is updated.
The method of claim 4, wherein, according to the incremental deviation of satellite positioning in the target area, updating the historical second positioning deviation of satellite positioning in the target area, comprising:

The second positioning deviation of the historical satellite positioning in the target area is updated according to the average value of the incremental deviations of the satellite positioning in the target area for several times in the history.
The method of claim 1, wherein fitting the positioning deviation function comprises:

Obtain the historical positioning deviation generated by satellite positioning in multiple pre-divided areas;

For each area of the pre-divided multiple areas, according to the obstacle information of one or more obstacles corresponding to the area, determine the proportion of areas in the area that receive satellite signals that are not blocked by obstacles;

The positioning deviation function is obtained by fitting according to the proportion of the unobstructed satellite signals in the multiple regions and the positioning deviation generated in the multiple regions.
The method according to claim 6, wherein, according to the obstacle information of one or more obstacles corresponding to the area, determining the proportion of the area receiving satellite signals in the area that is not blocked by obstacles, comprising:

According to the obstacle information of one or more obstacles corresponding to the area, determine the angular range in which the satellite signal is received at the center point of the area without being blocked by obstacles;

According to the angular range of receiving satellite signals at the center point of the area that is not blocked by obstacles, determine the proportion of the area where satellite signals are received and not blocked by obstacles in the area.
A positioning device for unmanned equipment, comprising:

The area determination module determines the target area where the unmanned equipment is currently located;

The confidence level determination module determines the confidence level of the current satellite positioning result performed by the unmanned device according to the proportion of the unobstructed satellite signal in the target area and the pre-fitted positioning deviation function, wherein the positioning The deviation function is fitted according to the proportion of unobstructed satellite signals in multiple regions in history and the positioning deviation in multiple regions;

a satellite positioning module, for determining the current satellite positioning position of the unmanned device according to the received satellite signals of multiple satellites;

The fusion positioning module performs fusion positioning on the unmanned equipment according to the current satellite positioning position of the unmanned equipment and the confidence level of the current satellite positioning result, and determines the fusion positioning position of the unmanned equipment.
A computer-readable storage medium storing a computer program, when the computer program is executed by a processor, implements the method according to any one of the preceding claims 1-7.
An unmanned vehicle, comprising a memory, a processor and a computer program stored in the memory and running on the processor, the processor implementing the method according to any one of claims 1-7 when the processor executes the program .