阅读说明：本技术 一种移动机器人定位监测方法、装置、设备和介质 (Mobile robot positioning monitoring method, device, equipment and medium ) 是由 马啸 于 2020-08-06 设计创作，主要内容包括：本发明涉及机器人技术领域,尤其是一种移动机器人定位监测方法,步骤1,获取并处理二维栅格地图数据及地图坐标信息,得到相关地图数据用于后续计算；步骤2,获取激光雷达发送的一帧激光数据；步骤3,获取并处理里程计数据,得到激光发射时刻对应的里程计数据；步骤4,修正激光数据；步骤5,计算定位准确度,定位准确度计算精度较高；本发明通过里程计数据修正激光雷达传感器数据,计算修正后的数据与栅格地图数据的匹配情况,进而判断机器人定位准确度,该方法可以广泛适用于移动机器人领域；本发明还提供了一种装置、设备和介质。(The invention relates to the technical field of robots, in particular to a mobile robot positioning monitoring method, which comprises the following steps of 1, acquiring and processing two-dimensional grid map data and map coordinate information to obtain related map data for subsequent calculation; step 2, acquiring a frame of laser data sent by a laser radar; step 3, acquiring and processing odometer data to obtain odometer data corresponding to the laser emission time; step 4, correcting laser data; step 5, calculating the positioning accuracy, wherein the calculation precision of the positioning accuracy is higher; according to the method, the data of the laser radar sensor is corrected through the mileage count data, the matching condition of the corrected data and the raster map data is calculated, and then the positioning accuracy of the robot is judged, so that the method can be widely applied to the field of mobile robots; the invention also provides a device, equipment and a medium.)

1. A mobile robot positioning monitoring method is characterized by comprising the following steps:

step 1, acquiring and processing two-dimensional grid map data and map coordinate information to obtain related map data for subsequent calculation;

step 2, acquiring a frame of laser data sent by a laser radar;

step 3, acquiring and processing odometer data to obtain odometer data corresponding to the laser emission time; step 4, correcting laser data;

and 5, calculating the positioning accuracy.

2. The method according to claim 1, wherein o, x, y are a map coordinate system (global coordinate system) established while loading a map; d _ o, d _ x and d _ y are odometer coordinate systems, and the transformation of the odometer coordinate systems relative to the global coordinate changes along with the change of odometer errors; b _ o, b _ x and b _ y are robot coordinate systems, and the transformation of the robot coordinate system relative to the global coordinate system changes along with the movement of the robot; l _ o, l _ x, l _ y are lidar coordinate systems.

3. The method according to claim 2, wherein the coordinate system of the grid map in step 1 is a global coordinate system, and the size of the grid cell is Sm/pix; the grid cell has a coordinate n in the x-direction_x×S(n_xA sequence of grid cells in the x-direction), the coordinate n of a grid cell in the y-direction_y×S(n_yAs a sequence of grid cells in the y-direction); nearest obstacle distance o of grid cell_iIf, ifThe grid cell is occupied by an obstacle o_iIs 0, otherwise o_iIs the distance between the grid cell and its nearest neighbor barrier grid cell.

4. The method according to claim 3, wherein the laser data acquired in step 2 comprises: the number N of beams of one frame of laser light; time t of first beam laser emission_sTime t of last laser emission_eThe time interval Δ t of adjacent laser beams; angle theta of each laser beam with respect to the lidar coordinate system_iDistance l between end point of each laser beam and origin of laser radar coordinate system_iAnd i represents a laser emission time.

5. The method as claimed in claim 4, wherein the frequency of the odometer data distribution in step 3 is obtainedPose data of the odometer at the moment (pose of the robot in the odometer coordinate system), where t_f≤t_s，t_l≥t_e，Δt₁The time interval of the odometer data can be obtained by fitting and interpolating the time interval to obtain the emitting time { t ] of the laser beam_s,t_s+Δt,…,t_eMilemeter pose data under { pd }_s,pd_s+Δt,…,pd_e}。

6. The method as claimed in claim 5, wherein the step 4 of modifying the laser data is to unify the laser data into the coordinate system of the odometer, and the coordinate of the laser beam end point in the coordinate system of the lidar at each time is (I)_i×cosθ_i,l_i×sinθ_i) The coordinate (dx) of the laser beam end point in the coordinate system of the odometer can be obtained through coordinate transformation_i,dy_i)。

7. The mobile robot positioning and monitoring method according to claim 6, wherein the robot pose data in step 5 are pose coordinates (px, py, p θ) in a global coordinate system, px being coordinates of the robot in the x direction in meters; px is the coordinate of the robot in the y direction, and the unit is meter; and p theta is an included angle between the robot orientation and the x direction, and the unit is radian. The pose data is t_eAnd (5) the pose data of the robot at all times.

8. The method according to claim 7, wherein the step 5 further comprises the steps of: step 5.1, acquiring positioning information to obtain the coordinates of the laser beam endpoint under the global coordinates; step 5.2, calculating the grid map position corresponding to the end point of each laser beam in the laser data; step 5.3, calculating the matching condition of each laser beam and the grid map; and 5.4, integrating each laser beam and calculating the positioning accuracy.

9. A mobile robot positioning and monitoring method as claimed in claim 8, characterized in that the positioning information p in step 5.1_eThe data is the data to be judged; the positioning information is t_eThe pose data of the robot under a map coordinate system at any moment; by p_eAnd pd in step 3_eCan be obtained at t_eCoordinate transformation of the coordinate system of the time odometer relative to the global coordinate system; can assume at t_s～t_eCoordinate transformation of the odometer coordinate system relative to the global coordinate system at the moment is fixed, so that the coordinates of the laser beam end point in the step 4 in the odometer coordinate system are converted into coordinates (x) in the global coordinate system_i,y_i)。

10. The method as claimed in claim 9, wherein in step 5.2, the grid position (nx) corresponding to the end point can be obtained according to the coordinates of the end point of the laser beam_i,ny_i) In which nx_i＝[x_i÷S]，ny_i＝[y_i÷S]. The nearest barrier distance o corresponding to the end point can be obtained by looking up a table_i。

Technical Field

The invention relates to the technical field of robots, in particular to a mobile robot positioning monitoring method, a device, equipment and a medium.

Background

With the progress of technology, mobile robots are widely used in various aspects of society. The positioning technology is the basic technology of the mobile robot, and whether the positioning is accurate or not directly influences the performance of the mobile robot. In the moving process of the mobile robot, the positioning accuracy of the mobile robot may be reduced by the influence of environmental changes, slipping of wheels of a chassis of the robot, human touch and the like. It is necessary to monitor the positioning accuracy of the mobile robot in real time.

Disclosure of Invention

The technical problem to be solved by the invention is as follows: in order to solve the problem that the positioning accuracy calculation precision is low due to the fact that the problem of motion distortion of laser radar data is not considered in the prior art, the invention provides a method for judging the positioning accuracy of a mobile robot, and the method comprises the following steps of 1, obtaining and processing two-dimensional grid map data and map coordinate information to obtain related map data for subsequent calculation; step 2, acquiring a frame of laser data sent by a laser radar; step 3, acquiring and processing odometer data to obtain odometer data corresponding to the laser emission time; step 4, correcting laser data; and 5, calculating the positioning accuracy, and effectively solving the existing problems.

In a first aspect, the present invention provides a mobile robot positioning and monitoring method,

a mobile robot positioning monitoring method comprises the following steps:

step 1, acquiring and processing two-dimensional grid map data and map coordinate information to obtain related map data for subsequent calculation;

step 2, acquiring a frame of laser data sent by a laser radar;

step 3, acquiring and processing the odometer data to obtain the mileage corresponding to the laser emission time

Counting data; step 4, correcting laser data;

and 5, calculating the positioning accuracy.

Further, o, x, y are map coordinate systems, i.e. global coordinate systems, which are established while loading the map; d _ o, d _ x and d _ y are odometer coordinate systems, and the transformation of the odometer coordinate systems relative to the global coordinate changes along with the change of odometer errors; b _ o, b _ x and b _ y are robot coordinate systems, and the transformation of the robot coordinate system relative to the global coordinate system changes along with the movement of the robot; l _ o, l _ x, l _ y are lidar coordinate systems.

Further, the coordinate system of the grid map in the step 1 is a global coordinate system, and the size Sm/pix of the grid unit; the grid cell has a coordinate n in the x-direction_x×S(n_xA sequence of grid cells in the x-direction), the coordinate n of a grid cell in the y-direction_y×S(n_yAs a sequence of grid cells in the y-direction); nearest obstacle distance o of grid cell_iIf the grid cell is occupied by an obstacle o_iIs 0, otherwise o_iIs the distance between the grid cell and its nearest neighbor barrier grid cell.

Further, the laser data acquired in step 2 includes: the number N of beams of one frame of laser light; time t of first beam laser emission_sTime t of last laser emission_eThe time interval Δ t of adjacent laser beams; angle theta of each laser beam with respect to the lidar coordinate system_iDistance l between end point of each laser beam and origin of laser radar coordinate system_iAnd i represents a laser emission time.

Further, the frequency of issuing the odometer data in the step 3 can be obtained

Pose data of the odometer at the moment (pose of the robot in the odometer coordinate system), where t_f≤t_s，t_l≥t_e，Δt₁The time interval of the odometer data can be obtained by fitting and interpolating the time interval to obtain the emitting time { t ] of the laser beam_s,t_s+Δt,…,t_eMilemeter pose data under { pd }_s,pd_s+Δt,…,pd_e}。

Furthermore, the purpose of correcting the laser data in the step 4 is to unify the laser data under a coordinate system of the odometer, and the coordinate of the laser beam endpoint under the coordinate system of the laser radar at each moment is (l)_i×cosθ_i,l_i×sinθ_i) Through coordinate transformationThe coordinates (dx) of the laser beam end point in the coordinate system of the odometer can be obtained_i,dy_i)。

Further, the pose data of the robot in the step 5 are pose coordinates (px, py, p θ) in a global coordinate system, where px is a coordinate of the robot in the x direction and is expressed in meters; px is the coordinate of the robot in the y direction, and the unit is meter; and p theta is an included angle between the robot orientation and the x direction, and the unit is radian. The pose data is t_eAnd (5) the pose data of the robot at all times.

Further, the step 5 further comprises the following steps: step 5.1, acquiring positioning information to obtain the coordinates of the laser beam endpoint under the global coordinates; step 5.2, calculating the grid map position corresponding to the end point of each laser beam in the laser data; step 5.3, calculating the matching condition of each laser beam and the grid map; and 5.4, integrating each laser beam and calculating the positioning accuracy.

Further, the positioning information p in step 5.1_eThe data is the data to be judged; the positioning information is t_eThe pose data of the robot under a map coordinate system at any moment; by p_eAnd pd in step 3_eCan be obtained at t_eCoordinate transformation of the coordinate system of the time odometer relative to the global coordinate system; can assume at t_s～t_eCoordinate transformation of the odometer coordinate system relative to the global coordinate system at the moment is fixed, so that the coordinates of the laser beam end point in the step 4 in the odometer coordinate system are converted into coordinates (x) in the global coordinate system_i,y_i)。

Further, in the step 5.2, according to the coordinates of the end point of the laser beam, the grid position (nx) corresponding to the end point can be obtained_i,ny_i) In which nx_i＝[x_i÷S]，ny_i＝[y_i÷S]. The nearest barrier distance o corresponding to the end point can be obtained by looking up a table_i。

Further, in the step 5.3, the matching degree of each laser beam is calculated

Wherein α is a Gaussian distributionThe coefficient, for example, α is 0.4 and β is a gaussian distribution variance, for example, β is 0.05. o_iSmaller means that the laser beam matches the grid map more closely.

Further, the positioning accuracy in the step 5.4I.e. the average value of all laser beam matching degrees.

In a second aspect, the present invention provides an apparatus for performing positioning accuracy monitoring,

a device for realizing positioning accuracy monitoring adopts the monitoring method, and comprises the following steps: the map module is used for loading a specified grid map; the laser radar module is used for generating laser scanning information; the odometer module is used for generating odometer pose data; the laser data correction module is combined with the odometer module to generate data to correct the data generated by the laser radar module; and the accuracy calculation module is used for calculating the matching condition of the pose data, the grid map data and the corrected laser data to generate positioning accuracy. The module comprises a pose interface for receiving pose data input from the outside; and the accuracy display module is used for displaying the calculation result of the positioning accuracy.

In a third aspect, the present invention provides a computer device,

a computer device adopting the monitoring method comprises a memory and an actuator, wherein the memory stores a computer program, and the actuator realizes the positioning accuracy monitoring method when executing the computer program.

In a fourth aspect, the present invention provides a mobile robot positioning and monitoring method,

a storage medium, which employs the above-described monitoring method, has stored thereon a computer program that, when executed by an actuator, implements the above-described positioning accuracy monitoring method.

The invention has the beneficial effects that: the invention provides a method for judging the positioning accuracy of a mobile robot, which comprises the following steps of 1, acquiring and processing two-dimensional grid map data and map coordinate information to obtain related map data for subsequent calculation; step 2, acquiring a frame of laser data sent by a laser radar; step 3, acquiring and processing odometer data to obtain odometer data corresponding to the laser emission time; step 4, correcting laser data; step 5, calculating the positioning accuracy, wherein the calculation precision of the positioning accuracy is higher; according to the invention, the data of the laser radar sensor is corrected through the mileage count data, and the matching condition of the corrected data and the raster map data is calculated, so that the positioning accuracy of the robot is judged. The method can be widely applied to the field of mobile robots.

Drawings

The invention is further illustrated with reference to the following figures and examples.

FIG. 1 is a schematic diagram of a robot positioning accuracy monitoring method of the present invention;

FIG. 2 is a schematic diagram of a coordinate system in a robot positioning accuracy monitoring method according to the present invention;

FIG. 3 is a schematic diagram of a grid map in a robot positioning accuracy monitoring method according to the present invention;

fig. 4 is a schematic structural diagram of the positioning accuracy monitoring apparatus of the present invention.

Detailed Description

The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic views illustrating only the basic structure of the present invention in a schematic manner, and thus show only the constitution related to the present invention.

As shown in the figures 1-4 of the drawings,

in a first aspect, the present invention provides a mobile robot positioning and monitoring method,

a mobile robot positioning monitoring method comprises the following steps:

step 1, acquiring and processing two-dimensional grid map data and map coordinate information to obtain related map data for subsequent calculation;

step 2, acquiring a frame of laser data sent by a laser radar;

step 3, acquiring and processing the odometer data to obtain the mileage corresponding to the laser emission time

Counting data; step 4, correcting laser data;

and 5, calculating the positioning accuracy.

o, x, y are map coordinate systems, i.e. global coordinate systems, which are established while loading the map; d _ o, d _ x and d _ y are odometer coordinate systems, and the transformation of the odometer coordinate systems relative to the global coordinate changes along with the change of odometer errors; b _ o, b _ x and b _ y are robot coordinate systems, and the transformation of the robot coordinate system relative to the global coordinate system changes along with the movement of the robot; l _ o, l _ x, l _ y are lidar coordinate systems.

The coordinate system of the grid map in the step 1 is a global coordinate system, and the size Sm/pix of a grid unit is obtained; the grid cell has a coordinate n in the x-direction_x×S(n_xA sequence of grid cells in the x-direction), the coordinate n of a grid cell in the y-direction_y×S(n_yAs a sequence of grid cells in the y-direction); nearest obstacle distance o of grid cell_iIf the grid cell is occupied by an obstacle o_iIs 0, otherwise o_iIs the distance between the grid cell and its nearest neighbor barrier grid cell.

The laser data acquired in step 2 includes: the number N of beams of one frame of laser light; time t of first beam laser emission_sTime t of last laser emission_eThe time interval Δ t of adjacent laser beams; angle theta of each laser beam with respect to the lidar coordinate system_iDistance l between end point of each laser beam and origin of laser radar coordinate system_iAnd i represents a laser emission time.

The frequency of the data distribution of the odometer in the step 3 can be obtainedPose data of the odometer at the moment (pose of the robot in the odometer coordinate system), where t_f≤t_s，t_l≥t_e，Δt₁The time interval of the odometer data can be obtained by fitting and interpolating the time interval to obtain the emitting time { t ] of the laser beam_s,t_s+Δt,…,t_eMilemeter pose data under { pd }_s,pd_s+Δt,…,pd_e}。

The purpose of correcting the laser data in the step 4 is to unify the laser data under a coordinate system of the odometer, and the coordinate of the laser beam endpoint under the coordinate of the laser radar at each moment is (l)_i×cosθ_i,l_i×sinθ_i) The coordinate (dx) of the laser beam end point in the coordinate system of the odometer can be obtained through coordinate transformation_i,dy_i)。

The pose data of the robot in the step 5 are pose coordinates (px, py, p theta) in a global coordinate system, and px is the coordinate of the robot in the x direction and the unit is meter; px is the coordinate of the robot in the y direction, and the unit is meter; and p theta is an included angle between the robot orientation and the x direction, and the unit is radian. The pose data is t_eAnd (5) the pose data of the robot at all times.

Step 5 also includes the following steps: step 5.1, acquiring positioning information to obtain the coordinates of the laser beam endpoint under the global coordinates; step 5.2, calculating the grid map position corresponding to the end point of each laser beam in the laser data; step 5.3, calculating the matching condition of each laser beam and the grid map; and 5.4, integrating each laser beam and calculating the positioning accuracy.

Location information p in step 5.1_eThe data is the data to be judged; the positioning information is t_eThe pose data of the robot under a map coordinate system at any moment; by p_eAnd pd in step 3_eCan be obtained at t_eCoordinate transformation of the coordinate system of the time odometer relative to the global coordinate system; can assume at t_s～t_eCoordinate transformation of the odometer coordinate system relative to the global coordinate system at the moment is fixed, so that the coordinates of the laser beam end point in the step 4 in the odometer coordinate system are converted into coordinates (x) in the global coordinate system_i,y_i)。

In step 5.2, according to the coordinates of the end points of the laser beams, the grid positions (nx) corresponding to the end points can be obtained_i,ny_i) In which nx_i＝[x_i÷S]，ny_i＝[y_i÷S]. The nearest barrier distance o corresponding to the end point can be obtained by looking up a table_i。

In step 5.3, the matching degree of each laser beam is calculated

Where α is a gaussian distribution coefficient, e.g., α is 0.4, and β is a gaussian distribution variance, e.g., β is 0.05. o_iSmaller means that the laser beam matches the grid map more closely.

Positioning accuracy in step 5.4

I.e. the average value of all laser beam matching degrees.

In a second aspect, the present invention provides an apparatus for performing positioning accuracy monitoring,

a device for realizing positioning accuracy monitoring adopts the monitoring method, and comprises the following steps: the map module is used for loading a specified grid map; the laser radar module is used for generating laser scanning information; the odometer module is used for generating odometer pose data; the laser data correction module is combined with the odometer module to generate data to correct the data generated by the laser radar module; and the accuracy calculation module is used for calculating the matching condition of the pose data, the grid map data and the corrected laser data to generate positioning accuracy. The module comprises a pose interface for receiving pose data input from the outside; and the accuracy display module is used for displaying the calculation result of the positioning accuracy.

In a third aspect, the present invention provides a computer device,

a computer device adopting the monitoring method comprises a memory and an actuator, wherein the memory stores a computer program, and the actuator realizes the positioning accuracy monitoring method when executing the computer program.

In a fourth aspect, the present invention provides a mobile robot positioning and monitoring method,

a storage medium, which employs the above-described monitoring method, has stored thereon a computer program that, when executed by an actuator, implements the above-described positioning accuracy monitoring method.

In light of the foregoing description of the preferred embodiment of the present invention, many modifications and variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.