CN110070712A - A kind of low speed sweeper Global localization system and method - Google Patents

Abstract

The invention relates to a global positioning system and method for a low-speed sweeper. The system includes a signal source subsystem, a map subsystem and a fusion subsystem. A vision module in the signal source subsystem provides the heading of the vehicle relative to the lane line and the distance information from the lane line. , the single-axis angular velocity meter provides vehicle yaw rate information, the vehicle information module provides wheel speed information, and the low-precision GNSS module provides global initial position information and global heading information; the map subsystem provides local map information of lane lines; initialization in the fusion subsystem The module determines the initial area according to the initial position of the vehicle, and the vehicle area determination module determines the driving area of the vehicle according to the initialized information; the heading fusion module fuses the heading information to obtain the optimal heading value, and the position fusion module fuses to obtain the optimal position. Compared with the prior art, the present invention does not need expensive GNSS positioning equipment and laser radar equipment, has low cost, and can realize positioning in a fixed area.

Description

A low-speed sweeper global positioning system and method

technical field

The invention relates to a local positioning method for a low-speed sweeper, in particular to a global positioning system and method for a low-speed sweeper.

Background technique

The unmanned sweeper can independently complete the cleaning operation according to the fixed route and fixed area in the closed park, and the positioning module provides the location information for the normal operation of the sweeper. The general positioning system uses GNSS positioning equipment to achieve accurate positioning of the vehicle, while the sweeper often encounters shading conditions such as tree shades during the operation process, which leads to the weakening or failure of the GNSS signal, and cannot achieve accurate positioning. Therefore, how to achieve accurate positioning on the unmanned sweeper has become a difficult point of research.

At present, the commonly used positioning methods on vehicles mainly include: 1. GNSS and inertial navigation fusion for positioning, the positioning effect is better when the GNSS signal is good in an open environment, but when the GNSS signal fails, the positioning effect is poor; 2. Lidar Mapping positioning is not affected by GNSS signals, but requires expensive lidar equipment, and needs to use a GNSS receiver with the function of receiving differential signals for RTK positioning. The board usually does not have differential positioning function, but the accuracy is low.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a global positioning system and method for a low-speed sweeper in order to overcome the above-mentioned defects of the prior art.

The object of the present invention can be realized through the following technical solutions:

A low-speed sweeper global positioning system is used for local positioning of the low-speed sweeper. The system includes a signal source subsystem, a map subsystem and a fusion subsystem. in:

The signal source subsystem includes:

The vision module is used to obtain information on the heading of the lane line and the distance from the lane line;

Single-axis angular velocity meter, used to obtain the yaw angular velocity information of the sweeper;

The vehicle information module is used to obtain the wheel speed information of the sweeper;

The low-precision GNSS module is used to obtain the global initial position information and global heading information of the sweeper;

The map subsystem includes:

The local lane line coordinate collection module is used to collect the global coordinates of the lane line;

The local coordinate and global coordinate conversion module is used to select the origin of the appropriate local plane rectangular coordinate system according to the global coordinate point, and obtain the coordinates of each point of the collected lane line in this coordinate system;

The local lane line map building module is used to build a local lane line map and divide the driving area according to the coordinates of each point of the lane line;

The fusion subsystem includes:

The initialization module is used to determine the initial area of the vehicle according to the information of the initial position and rough heading of the given vehicle and the lane line information provided by the map subsystem, and obtain the initial local heading value of the vehicle;

The vehicle area judgment module is used to detect the area where the vehicle travels and obtain the measured value of the local heading according to the local heading information and initial area information provided by the initialization module, combined with the lane line map and the driving area division information provided by the map subsystem. , and take the lane lines that can be detected by the vision module in this area as the feedback lane lines;

The heading fusion module is used to correct the heading of the sweeper according to the measured value of the local heading provided by the vehicle area judgment module;

The position fusion module is used to obtain the optimal global position information and heading information of the vehicle according to the heading value corrected by the heading fusion module and the speed of the vehicle;

Local coordinate and global coordinate conversion module: used to convert the local map of lane lines into global position and heading information.

The vision module is a camera used to detect pedestrians and obstacles on the cleaning vehicle, the single-axis angular velocity meter is a vehicle yaw rate sensor, and the low-precision GNSS module adopts a low-precision GNSS without differential positioning function. The vehicle information obtained by the vehicle information module is obtained from the vehicle CAN bus.

A global positioning method for a low-speed sweeper, comprising the following steps:

(1) The map subsystem collects the coordinates of the lane lines, establishes a local map and divides the local map, which specifically includes the following steps:

11) The absolute coordinate collection module of the local lane line collects the coordinates of the lane line, and obtains the global coordinates of the lane line;

12) The global coordinate and local coordinate conversion module selects the origin of a suitable local plane rectangular coordinate system according to the collected global coordinate points, and obtains the coordinates of each point of the collected lane line in this coordinate system;

13) Using the method of least squares fitting, model the different lane lines in the driving area of the sweeper respectively, and obtain the equation of the lane lines in the local coordinate system;

14) The local lane line map establishment module establishes a lane line map according to the coordinates of each point of the lane line, and divides the local map according to the driving area of the sweeper.

(2) The map subsystem sends the local map information of the lane lines to the fusion subsystem.

(3) The low-precision GNSS module sends the global position information with lower precision to the fusion subsystem, the vision module sends the acquired information of the heading of the lane line and the distance from the lane line to the fusion subsystem, and the single-axis angular velocity meter sends the vehicle to the fusion subsystem. The yaw rate information is sent to the fusion subsystem, and the vehicle information module sends the acquired wheel speed information to the fusion subsystem.

(4) The fusion subsystem performs fusion according to the obtained information to obtain the optimal global position and heading information. Specifically include the following steps:

41) When the vehicle runs normally, the initialization module obtains the vehicle's global position information and global heading information according to the low-precision GNSS module to obtain the vehicle's initial local heading φ _L,ini and the vehicle's initial local position x _L,ini ,y _L,ini , and Complete the determination of the initial area of the vehicle, wherein the initial local position of the vehicle x _L,ini , y _L,ini is obtained by averaging the global position information obtained by the low-precision GNSS module at rest;

42) The vehicle area judgment module is based on the initial local heading φ _L,ini and the initial local position x _L,ini ,y _L,ini of the vehicle provided by the initialization module, combined with the lane line map and the driving area division information provided by the map subsystem, Detect the area where the vehicle is traveling, and select the lane line that the vision module can detect in this area as the feedback lane line;

43) The vehicle area judgment module sends the measured value φ _{L, Mea} of the local heading to the heading fusion module, and sends the measured lane line L _active at the current moment and the measured distance d _r from the lane line L _active to the position Fusion module.

The expression for the measured distance d _r from the lane line L _active is:

φ _{L, Mea} = φ _{L, Line} + φ _r

In the formula, φ _L,Line is the heading value of the lane line L _active in the local map coordinate system, and Φ _r is the heading value relative to the lane line measured by the vision module.

The heading fusion module uses the local heading measurement value φ _{L, Mea} as the measurement value to correct the heading of the sweeper. When there is no heading measurement value φ _{L, Mea} , the heading is obtained by integrating the yaw rate ω _z of the vehicle. Value φ _L,Fus :

φ _{L, Fus} = φ _{L, INS} +k _φ ·Δφ,

Δφ＝φ _L,Mea -φ _L,INS ,

In the formula, Δφ is the difference between the heading measurement value φ _{L, Mea} and the INS integral heading value Φ _{L, INS} , k _φ is the feedback gain of the heading error, and the value ranges from 0 to 1.

When there is no GNSS signal, the position fusion module obtains the position x _{L, k} and y _{L, k} of the vehicle in the local coordinate system at time k through integration according to the heading value φ _{L, Fus} and the vehicle speed V of the heading fusion module, respectively:

x _L,k =x _L,k-1 +V _x ·ΔT,

y _L,k =y _L,k-1 +V _y ·ΔT,

In the formula, ΔT is the sampling time of the discrete system, V _x and V _y are the velocities of the vehicle along the x and y directions in the local coordinate system, respectively. The calculation formula is as follows:

V _x =V·cos(φ _L ),

V _y =V·sin(φ _L ).

In the formula, φ _L is the real heading value of the vehicle in the local coordinate system, and the optimal estimated value φ _{L, Fus} is used as the real value in the actual calculation;

When there is a GNSS signal, the position fusion module obtains the position information of the vehicle according to the heading value of the heading fusion module and the vehicle speed V integral, and fuses it with the low-precision filtered local position information. At this time, the local coordinates of the vehicle at time k are obtained. The positions x _L,k and y _L,k under the system are:

x _L,k =(1-k _G )·(x _L,k-1 +V _x ·ΔT)+k _G ·x _L,GNSS ,

y _L,k =(1-k _G )·(y _L,k-1 +V _y ·ΔT)+k _G ·y _L,GNSS ,

Among them, x _{L, GNSS} , y _{L, GNSS} is the conversion of low-precision global position to local position, and k _G is the weight coefficient of GNSS position feedback;

Calculate the distance d _INS from the current vehicle position to the lane line L _active used for measurement, assuming that the equation of the lane line L _active in the local coordinate system is y _Line -k _Line x _Line -b _Line =0, then the expression of d _INS for:

In the formula, x _L and y _L are the real positions of the vehicle, respectively, and the optimal estimated values x _{L, Fus} and y _{L, Fus} are used instead in the actual calculation, and the lateral distance measured by the vision module is used as the measured value of d _r , Correct the lateral distance of the vehicle to obtain the lateral distance d _Fus between the vehicle and the lane line after fusion:

d _Fus =d _INS +k _d ·Δd,

Δd=d _r -d _INS ,

In the formula, Δd is the difference between the lateral distance measurement value and the lateral distance calculated from the INS integral position, and k _d is the feedback gain of the lateral distance error.

Set the fused lateral distance error Δd _Fus =d _Fus -d _r , and use the fused lateral distance error Δd _Fus to correct the position to obtain the optimal fusion position:

x _L,Fus =x _L,k +Δd _Fus ·sin(φ _L,Fus ),

y _L,Fus =y _L,k +Δd _Fus ·cos(φ _L,Fus ).

In the formula, Φ _{K, Fus} is the local heading value after fusion.

Compared with the prior art, the present invention has the following advantages:

1. The present invention locates the vehicle by integrating the signals of low-precision GNSS, vision, wheel speed and inertial navigation, without the need for expensive GNSS high-precision positioning equipment with RTK positioning function, the cost is low, and it can realize no GNSS signal or GNSS Local and global positioning of vehicles in weak signal conditions;

2. The present invention fuses information on the basis of the existing sensor scheme of the unmanned sweeper. The low-precision GNSS module adopts the existing low-precision GNSS board without differential positioning function, which is cheap and can provide position information. The vision module is the camera used to detect pedestrians and obstacles on the intelligent cleaning vehicle, the single-axis angular velocity meter is the vehicle yaw rate sensor, and the vehicle information can be obtained directly from the vehicle CAN bus. Obtain high-reliability positioning information, which can be widely used in vehicles with the above-mentioned sensor equipment;

3. The fusion subsystem of the present invention is provided with a local coordinate and global coordinate conversion module, which can convert the local map of the lane line into the global map information, and obtain the position and output consistent with the standard of the prior art as the module output. The heading information can ensure the accuracy of the obtained position and heading information in the case of saving costs, and is convenient for users to use.

Description of drawings

Fig. 1 is the principle block diagram of the global positioning method of the low-speed sweeper of the present invention;

The numbers in the figure show:

1. Map subsystem, 2. Signal source subsystem, 3. Fusion subsystem.

Detailed ways

The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are some, but not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

The invention relates to a global positioning system for a low-speed sweeper, which comprises three parts: a signal source subsystem, a map subsystem and a fusion subsystem.

The signal source subsystem includes a vision module, a single-axis angular velocity meter, a vehicle information module, and a low-precision GNSS module. The vision module is used to obtain information on the heading of the lane line and the distance from the lane line. The vision module is a camera on the cleaning vehicle used to detect pedestrians and obstacles. The single-axis angular velocity meter provides vehicle yaw angular velocity information, and the single-axis angular velocity meter is the vehicle yaw angular velocity sensor. The vehicle information module is used to obtain the wheel speed information of the sweeper, and the vehicle information is obtained from the vehicle CAN bus. A low-precision GNSS module is used to obtain the initial global position information of the sweeper.

The map subsystem includes a local lane line absolute coordinate acquisition module, a local coordinate and global coordinate conversion module, and a local lane line map building module. The absolute coordinate acquisition module of the local lane line is used to collect the global coordinates of the lane line; the local coordinate and global coordinate conversion module is used to select the origin of the appropriate local plane rectangular coordinate system according to the global coordinate point, and obtain the collected lane line in this coordinate system. The coordinates of each point; the local lane line map building module is used to build a lane line map and divide the driving area according to the coordinates of each point of the lane line.

The fusion subsystem includes an initialization module, a vehicle area judgment module, a heading fusion module, a position fusion module, and a local coordinate and global coordinate conversion module.

The initialization module is used to determine the initial area of the vehicle according to the information of the initial position and rough heading of the given vehicle and the lane line information provided by the local map subsystem, and obtain the initial local heading value of the vehicle;

The vehicle area judgment module is used to detect the area where the vehicle travels and obtain the measured value of the local heading according to the local heading information and initial area information provided by the initialization module, combined with the lane line map and the driving area division information provided by the local map subsystem. , and take the lane lines that can be detected by the vision module in this area as the feedback lane lines;

The heading fusion module is used to correct the heading of the sweeper according to the measured value of the local heading provided by the vehicle area judgment module;

The position fusion module is used to obtain the optimal fusion position information of the vehicle according to the heading value corrected by the heading fusion module and the vehicle speed.

The present invention also relates to a local positioning method of a sweeper that integrates vision, wheel speed and inertial navigation, the method comprising the following steps:

Step 1: The map subsystem provides local map information of lane lines to the fusion subsystem.

The map subsystem first needs to collect the coordinates of the lane lines. At this time, the global coordinates of the lane lines are collected. Then, according to the collected coordinate points, through the global coordinate and local coordinate conversion module, the origin of the appropriate local plane rectangular coordinate system is selected. , and obtain the coordinates of each point of the collected lane line in this coordinate system, and then use the least squares fitting method to model the different lane lines in the driving area of the sweeper respectively, and obtain the lane line in the local coordinate system. The following equation is used, and the local map is divided according to the driving area of the sweeper.

Step 2. The low-precision GNSS module sends the low-precision global position information to the fusion subsystem. The vision module provides the fusion subsystem with information about the heading relative to the lane line and the distance from the lane line. The single-axis angular velocity meter provides the vehicle yaw rate. information, the vehicle information module provides wheel speed information to the fusion module.

Step 3: The fusion subsystem synthesizes and fuses the above information to obtain the optimal global position and heading information. Specific content includes:

Before the whole fusion subsystem starts to work, it needs the information of the initial position and rough heading of the vehicle given by the outside world. At this time, the initialization module determines the initial area of the vehicle according to the above information and the lane line information provided by the map subsystem, and obtains the vehicle. Initial local heading values φ _L,ini and position values x _L,ini ,y _L,ini .

After the vehicle is initialized for the first time, the vehicle area judgment module combines the lane line map and the driving area division information provided by the map subsystem according to the local heading information φ _L,ini and the initial position information x _L,ini ,y _L,ini provided by the initialization module. , detect the area where the vehicle is traveling, and select the lane line that can be detected by the vision module in this area as the feedback lane line; and when the vehicle is running normally, according to the optimal heading value φ obtained by the fusion subsystem at the last moment fusion _L,Fus and position x _L,Fus ,y _L,Fus , combined with the lane line map and driving area division information provided by the map subsystem, detect the area where the vehicle is at the current moment, and select the area where the vision module can The detected lane lines are used as feedback lane lines. Finally, the vehicle area judgment module provides the measured value φ _L,Mea of the local heading to the heading fusion module, the lane line L _active used for measurement at the current moment of the position fusion module, and the measured distance d _r from the lane line L _active :

φ _{L, Mea} = φ _{L, Line} + φ _r

Among them, φ _L,Line is the heading value of the lane line L _active in the local map coordinate system, and Φ _r is the heading value of the relative lane line measured by the vision module.

The heading fusion module uses the measured value φ _{L, Mea} of the local heading as the measured value to correct the heading of the sweeper, and when the measured value φ _{L, Mea} of the re-course does not exist due to the absence of lane lines or other reasons, Then, the heading value φ _L,Fus is obtained by integrating the vehicle yaw rate ω _z .

φ _{L, Fus} = φ _{L, INS} +k _φ ·Δφ,

Δφ＝φ _L,Mea -φ _L,INS ,

Among them, Δφ is the difference between the heading measurement value φ _{L, Mea} and the INS integrated heading value Φ _{L, INS} , which is called the heading error; k _φ is the feedback gain of the heading error, and the value ranges from 0 to 1.

When there is no GNSS signal, the position fusion module integrates the position information of the vehicle according to the heading value φ _{L, Fus} of the heading fusion module, and the vehicle speed V:

x _L,k =x _L,k-1 +V _x ·ΔT,

y _L,k =y _L,k-1 +V _y ·ΔT,

Among them, x _{L, k} and y _{L, k} are the positions of the vehicle in the local coordinate system at time k, respectively, and x _{L, k-1} and y _{L, k-1} are the positions of the vehicle in the local coordinate system at time k-1, respectively. position, ΔT is the sampling time of the discrete system, V _x and V _y are the velocities of the vehicle in the local coordinate system along the x and y directions, respectively, and the calculation formula is as follows:

V _x =V·cos(φ _L ),

V _y =V·sin(φ _L ).

Among them, φ _L is the real heading value of the vehicle in the local coordinate system, and the optimal estimated value φ _{L, Fus} is used as the real value in the actual calculation.

When there is a GNSS signal, the position fusion module obtains the position information of the vehicle according to the heading value of the heading fusion module and the vehicle speed V integral, and fuses it with the low-precision filtered local position information. At this time, the local coordinates of the vehicle at time k are obtained. The positions x _L,k and y _L,k under the system are:

x _L,k =(1-k _G )·(x _L,k-1 +V _x ·ΔT)+k _G ·x _L,GNSS ,

y _L,k =(1-k _G )·(y _L,k-1 +V _y ·ΔT)+k _G ·y _L,GNSS ,

Among them, x _{L, GNSS} , y _{L, GNSS} is the conversion of low-precision global position to local position, and k _G is the weight coefficient of GNSS position feedback;

Calculate the distance d _INS from the current vehicle position to the lane line L _active used for measurement, assuming that the equation of the lane line L _active in the local coordinate system is y _Line -k _Line x _Line -b _Line =0, then the expression of d _INS for:

Among them, x _L and y _L are the real positions of the vehicle, respectively, and are replaced by the optimal estimated values x _L,Fus and y _L,Fus in the actual calculation. Taking the lateral distance measured by the vision module as the measured value of d _r , the lateral distance of the vehicle is corrected to obtain the lateral distance d _Fus between the vehicle and the lane line after fusion:

d _Fus =d _INS +k _d ·Δd,

Δd=d _r -d _INS ,

Among them, Δd is the difference between the lateral distance measurement value and the lateral distance calculated by the INS integral position, which is called the lateral distance error; k _d is the feedback gain of the lateral distance error, and the value range is 0～ 1. Finally, the fused lateral distance error Δd _Fus =d _Fus -d _r is obtained, and the fused lateral distance error Δd _Fus is used to correct the position to obtain the optimal fusion position:

x _L,Fus =x _L,k +Δd _Fus ·sin(φ _L,Fus ),

y _L,Fus =y _L,k +Δd _Fus ·cos(φ _L,Fus ).

In the formula, Φ _{L, Fus} is the local heading value after fusion.

The present invention locates the vehicle by fusing low-precision GNSS, vision, wheel speed and inertial navigation signals, does not require expensive GNSS high-precision positioning equipment with RTK positioning function, has low cost, and can realize no GNSS signal or GNSS signal comparison. Local and global localization of vehicles in weak cases.

The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited to this. Any person familiar with the technical field can easily think of various equivalents within the technical scope disclosed by the present invention. Modifications or substitutions should be included within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims (10)

1. a kind of low speed sweeper Global localization system, to carry out local positioning to low speed sweeper, which is characterized in that packet It includes:

Signal source subsystem:

Vision module, for obtaining the course of lane line and the information away from lane line distance；

Uniaxial angular speed meter, for obtaining the yaw velocity information of sweeper；

Information of vehicles module, for obtaining the wheel speed information of sweeper；

Low precision GNSS module, for obtaining the global initial position message and global course information of sweeper；

Ground dsp subsystem:

Local lane line coordinates acquisition module, for acquiring lane line world coordinates；

Local coordinate and global coordinate transform module, for choosing suitable local plane rectangular coordinate system according to world coordinates point Origin, and obtain the coordinate of each point of acquired lane line in this coordinate system；

Local lane line map establishes module, for establishing lane line local map according to the coordinate of each point of lane line and dividing Running region；

Merge subsystem:

Initialization module, for according to give vehicle initial position and rough course information, dsp subsystem provide vehicle Diatom information carries out prime area judgement to vehicle, and obtains the initial local course value of vehicle；

Vehicle region judgment module, local course information and prime area information for being provided according to initialization module, in conjunction with The information that the lane line map and running region that ground dsp subsystem provides divide, detects the region of vehicle driving, obtains The measured value in local course, and the lane line that vision module in the region is able to detect that is as feedback lane line；

Course Fusion Module, the course of the measured value in the local course for being provided according to vehicle region judgment module to sweeper It is modified；

Co-factor propagation module, for obtaining the optimal overall situation of vehicle according to the revised course value of course Fusion Module and speed Location information and course information.

2. a kind of low speed sweeper Global localization system according to claim 1, which is characterized in that the fusion subsystem System further includes the local coordinate and global coordinate transform lane line local map to be converted into global position and course information Module.

3. a kind of low speed sweeper Global localization system according to claim 1, which is characterized in that the vision module To clean for detecting the camera of pedestrian and barrier on vehicle, the uniaxial angular speed is calculated as yaw rate biography Sensor, the low precision GNSS module is using the low precision GNSS board for not having Differential positioning function, the vehicle letter The information of vehicles of module acquisition is ceased by obtaining on vehicle CAN bus.

4. a kind of a kind of application low speed sweeper global localization method as described in any one of claims 1-3, which is characterized in that This method includes the following steps:

1) dsp subsystem is acquired lane line coordinates, establishes local map and divides to local map；

2) the local map information of lane line is sent to fusion subsystem by dsp subsystem；

3) the lower global position information of precision is sent to fusion subsystem by low precision GNSS module, what vision module will acquire The course of lane line and information away from lane line distance are sent to fusion subsystem, and uniaxial angular speed meter is by Vehicular yaw angle speed Degree information is sent to fusion subsystem, and the wheel speed information that information of vehicles module will acquire is sent to fusion subsystem；

4) fusion subsystem is merged according to the every terms of information of acquisition, obtains optimal global position and course information.

5. a kind of low speed sweeper global localization method according to claim 4, which is characterized in that step 1) specifically includes Following steps:

11) local lane line absolute coordinate acquisition module is acquired the coordinate of lane line, obtains the world coordinates of lane line；

12) world coordinates and local coordinate transferring are chosen suitable local plane rectangular according to the world coordinates point of acquisition and are sat The origin of system is marked, and obtains the coordinate of each point of acquired lane line in this coordinate system；

13) method for using least square fitting, models the different lane lines in sweeper running region respectively, obtains Equation of the pick-up diatom under local coordinate system；

14) local lane line map establishes module and establishes lane line map according to the coordinate of each point of lane line, and according to cleaning The running region of vehicle carries out region division to local map.

6. a kind of low speed sweeper global localization method according to claim 5, which is characterized in that step 4) specifically includes Following steps:

41) after normal vehicle operation, initialization module according to low precision GNSS module obtain vehicle global position information and Global course information obtains vehicle initial local course φ_L,iniWith vehicle initial local position x_L,ini,y_L,ini, and complete vehicle The judgement of prime area, wherein vehicle initial local position x_L,ini,y_L,iniBy it is static when low precision GNSS module obtain it is complete Office's location information is averaged to obtain；

42) the vehicle initial local course φ that vehicle region judgment module is provided according to initialization module_L,iniWith the initial office of vehicle Portion position x_L,ini,y_L,ini, the information that the lane line map and running region that dsp subsystem provides in combination divide, to vehicle row The region sailed is detected, and selects vision module is able to detect that in the area lane line as feedback lane line；

43) vehicle region judgment module is by the measured value φ in local course_L,MeaIt is sent to course Fusion Module, and by current time Lane line L as measurement_activeAnd measure away from lane line L_activeDistance d_rIt is sent to Co-factor propagation module.

7. a kind of low speed sweeper global localization method according to claim 6, which is characterized in that measure away from lane line L_activeDistance d_rExpression formula are as follows:

φ_L,Mea=φ_L,Line+φ_r

In formula, φ_L,LineFor lane line L_activeCourse value under local map coordinate system, Φ_rIt is measured for vision module opposite The course value of lane line.

8. a kind of low speed sweeper global localization method according to claim 7, which is characterized in that course Fusion Module with The measured value φ in local course_L,MeaAs measuring value, the course of sweeper is modified, when there is no heading measure values φ_L,MeaWhen, then according to the yaw velocity ω of vehicle_zIntegral obtains course value φ_L,Fus:

φ_L,Fus=φ_L,INS+k_φ·Δφ,

Δ φ=φ_L,Mea-φ_L,INS,

In formula, Δ φ is heading measure value φ_L,MeaCourse value Φ is integrated with INS_L,INSDifference, k_φIncrease for the feedback of course error Benefit, value range are 0~1.

9. a kind of low speed sweeper global localization method according to claim 8, which is characterized in that in no GNSS signal When, Co-factor propagation module is according to the course value φ of course Fusion Module_L,FusAnd vehicle velocity V, k moment vehicle is obtained by integral and is existed Position x under local coordinate system_L,kAnd y_L,kIt is respectively as follows:

x_L,k=x_L,k-1+V_x·ΔT,

y_L,k=y_L,k-1+V_y·ΔT,

In formula, Δ T is the sampling time of discrete system, V_xAnd V_yRespectively vehicle under local coordinate system along the direction x and y Speed, calculation formula are as follows:

V_x=Vcos (φ_L),

V_y=Vsin (φ_L).

In formula, φ_LFor vehicle under local coordinate system true course value, it is practical when calculating with optimal estimation value φ_L,FusAs True value；

When there are GNSS signal, Co-factor propagation module integrates according to the course value and vehicle velocity V of course Fusion Module and obtains vehicle Location information, while being merged with the filtered local location information of low precision, obtain k moment vehicle at this time in office Position x under portion's coordinate system_L,kAnd y_L,kIt is respectively as follows:

x_L,k=(1-k_G)·(x_L,k-1+V_x·ΔT)+k_G·x_L,GNSS,

y_L,k=(1-k_G)·(y_L,k-1+V_y·ΔT)+k_G·y_L,GNSS,

Wherein, x_L,GNSS,y_L,GNSSLocal location, k are converted to for low precision global position_GFor the weight coefficient of GNSS location feedback；

Current vehicle location is calculated to the lane line L for being used as measurement_activeDistance d_INS, it is assumed that lane line L_activeIn local seat Equation under mark system is y_Line-k_Linex_Line-b_Line=0, then d_INSExpression formula are as follows:

In formula, x_LAnd y_LThe respectively actual position of vehicle uses optimal estimation value x when reality calculates_L,FusAnd y_L,FusSubstitution, with The lateral distance that vision module measures is as d_rMeasuring value is modified the lateral distance of vehicle, obtains fused vehicle Lateral distance d away from lane line_Fus:

d_Fus=d_INS+k_d·Δd,

Δ d=d_r-d_INS,

In formula, Δ d integrates the difference between the lateral distance that position is calculated, k for lateral distance measured value and INS_dIt is lateral The feedback oscillator of range error.

10. a kind of low speed sweeper global localization method according to claim 9, which is characterized in that by fused side To range error Δ d_Fus=d_Fus-d_r, using fused lateral distance error delta d_FusPosition is modified to obtain optimal Merge position:

x_L,Fus=x_L,k+Δd_Fus·sin(φ_L,Fus),

y_L,Fus=y_L,k+Δd_Fus·cos(φ_L,Fus)。

In formula, Φ_L,FusFor fused local course value.