Method for AGV chassis to automatically obtain map labels

Abstract

The method of automatically acquiring map labels for the AGV chassis proposed in this application, and the solution of automatically acquiring map labels and updating map routing information, are intended to improve the efficiency of AGV positioning and navigation and achieve strong compatibility under the premise of ensuring no errors. The implementation steps include the following: step 1), receiving instructions; step 2), initialization; step 3), traversing routing points and planning running trajectories; step 4), chassis posture calculation and updating positioning information; step 5), updating the map; step 6), judging whether the routing point information is updated.

Description

Technical Field

[0001] The invention relates to a method for an AGV chassis to automatically obtain map labels, and belongs to the field of unmanned intelligent driving and logistics warehousing. Background Art

[0002] AGVs used in logistics warehousing and express sorting industries operate on standard flat maps in their operating environments. Maps are the basic components of AGV chassis positioning and navigation, and usually have different dimensions, as shown in the attached figure. Figure 1 As shown. A routing point is set at the exact center of each unit that constitutes the map. Each routing point contains multiple information, such as routing point number information, label value, coordinate value, point characteristics, access rights, etc. Among them, the label value corresponds to the routing point one by one; the routing point number, coordinate value point characteristics and access rights are automatically generated when the map is created in the cloud.

[0003] There are various forms of existing maps. Label pasting and label value statistics are generally done manually. In the process of map creation, due to the large number of map route points, manual input is very time-consuming and prone to errors. The main manifestations are: 1. Randomly affix labels and then manually enter them; this makes construction more difficult when the map size is large, and manual entry is prone to errors; 2. Route numbers are bound to label values ​​in advance, and labels are pasted to corresponding route points during construction; this makes pasting errors more likely and pasting corresponding numbers is more time-consuming and labor-intensive.

[0004] In view of this, this patent application is proposed. Summary of the invention

[0005] The method for automatically acquiring map labels for the AGV chassis described in the present invention aims to solve the problems existing in the above-mentioned prior art and propose a solution for automatically acquiring map labels and updating map routing information, so as to improve the AGV positioning and navigation efficiency and achieve stronger compatibility performance while ensuring error-free operation.

[0006] To achieve the above design objectives, the method for the AGV chassis to automatically obtain map labels includes the following implementation steps:

[0007] Step 1), receiving instructions;

[0008] Receive cloud instructions and determine whether to start automatic identification; if so, proceed to step 2); if not, continue waiting;

[0009] Step 2), initialization;

[0010] Initialize the AGV chassis posture, obtain the original map and save the map routing points;

[0011] After loading the map, the route points in the map are stored in the form of key-value pairs {(x, y), RouteNode}, where the key is the (x, y) coordinate information and RouteNode is the route point corresponding to the coordinate;

[0012] Put the starting location routing point into set Q, and put other routing points into set P;

[0013] Step 3), traverse the routing points and plan the running trajectory;

[0014] Traverse all routing points in order and plan the running trajectory; if set P is empty, copy the routing points in set N to set P, clear set N at the same time, and use the traversal algorithm to plan the traversal order of routing points in set P; if set P is not empty, directly use the traversal algorithm to plan the traversal order of routing points in set P; plan the motion trajectory according to the traversal order of routing points;

[0015] Step 4), chassis posture calculation and update positioning information;

[0016] Obtain data from the vehicle-mounted sensors and obtain the current routing point of the AGV through coordinate matching;

[0017] If a tag is recognized, the current routing point information is updated with the recognized tag value and the positioning information is published; the routing point matching the tag information is put into set Q, and the point is deleted from set P, and the offset calculated by the magnetic permeability sensor is used to correct the position information of the AGV chassis;

[0018] If the routing label is not identified, the routing point that does not match the label information is placed in set N, and the point is deleted from set P, and the label value in the published positioning information is recorded as 0;

[0019] Step 5), update the map;

[0020] The cloud receives AGV location information and updates the map;

[0021] If the received location information tag value is not 0, the corresponding routing point information in the map is updated with the tag value;

[0022] If the received location information tag value is 0, the staff will be prompted to check the reason and skip the point to continue updating the next routing point information;

[0023] Step 6) Determine whether the routing point information is updated;

[0024] Determine whether all routing points have been traversed, that is, whether set P and set N are both empty; if so, stop updating; if not, jump to step 3) to continue execution.

[0025] Furthermore, in the AGV chassis initialization in step 2), the coordinates of the origin of the map coordinate system or any routing point are used as the starting point.

[0026] Furthermore, the traversal algorithm flow of step 3) is as follows:

[0027] 3.1) Get the coordinates of the routing point where the AGV is currently located and get the routing point set;

[0028] 3.2) Calculate the cost from the current routing point to each routing point in the set;

[0029] The calculation formula is as follows,

[0030] F(n)=C(n)+R(n)

[0031] C(n)=|x n -x i |+|y n -y i |

[0032] R(n)=r n -r i

[0033] In the above formula, n represents the routing point numbered n, i represents the current routing point; F(n) is the cost value of routing point n, C(n) is the Manhattan distance from routing point n to the current routing point (in millimeters); R(n) is the difference between the routing point number n and the current routing point; the point with the smallest cost value is selected as the next target point.

[0034] Furthermore, in the step 4), the positioning information includes the current routing point number, the routing point label value and the AGV chassis posture information.

[0035] Furthermore, in step 4), the calculation formula for matching the current routing point by coordinates is as follows:

[0036]

[0037] Among them, (x t ,y t ) is the coordinate of the current routing point, (x g ,y g ) is the coordinate value of the AGV chassis fusion positioning, and w is the distance between routing points;

[0038] Match the obtained routing point coordinates with the routing point set key value. From step 2), it is known that the routing point storage method is {(x, y), RouteNode}. Find (x t ,y t ), find the key value x=xt ,y=y t The corresponding routing point RouteNode completes the coordinate matching.

[0039] Furthermore, the calculation process of performing posture correction in step 4) is as follows:

[0040] 4.1) Determine the position offset of the magnetic stripe based on the sensor data, and obtain the coordinates of the four points P0 to P3 in the chassis coordinate system: d0, d1, d2, and d3 are offsets, which are positive or negative. The offset in the positive direction of the coordinate axis is positive, and the offset in the negative direction is negative;

[0041]

[0042] 4.2) Obtain the angle α between the two coordinate systems based on the coordinates of points P0 and P1;

[0043] Counterclockwise is positive;

[0044] 4.3) Determine two straight lines based on P0P1 and P2P3, and obtain the following straight line equations:

[0045] The P0P1 equation is,

[0046]

[0047] The P2P3 equation is,

[0048]

[0049] 4.4) Obtain the coordinates of the origin of the geomagnetic coordinate system in the chassis coordinate system (x m ,y m );

[0050]

[0051] b1=y0-m1x0

[0052] b2=y2-m2x2

[0053]

[0054] y m =m1x m +b1

[0055] 4.5) By α and (x m ,y m ) Inversely deduce the position and posture of the chassis coordinate system in the geomagnetic coordinate system;

[0056] The declination angle Δa and deviations Δx and Δy of the chassis coordinate system in the geomagnetic coordinate system, where the angle is positive if it is counterclockwise and negative if it is clockwise;

[0057] The deflection angle of the chassis coordinate system is,

[0058] The transformation matrix from the magnetic stripe coordinate system to the chassis coordinate system is:

[0059]

[0060] The transformation matrix from chassis coordinate system to magnetic stripe coordinate system is:

[0061]

[0062] Then, the coordinate deviation of the chassis coordinate system is:

[0063]

[0064] The calculated offset is:

[0065]

[0066] The AGV chassis posture is corrected to:

[0067]

[0068] In the above formula, (x, y, a) is the corrected pose information at the current moment, (x t ,y t ,a t ) is the pose calculated by the odometer at the current moment.

[0069] Furthermore, the map tag is an RFID or a QR code.

[0070] In summary, the method for automatically obtaining map labels by the AGV chassis has the following advantages:

[0071] 1. This application enables AGV to autonomously obtain map tag values ​​and feed them back to the cloud, so as to collaborate with the cloud to complete the task of improving map information, which can significantly reduce the workload of manual participation and improve navigation efficiency and the accuracy of positioning information;

[0072] 2. This application has high compatibility and is compatible with a variety of map labeling solutions including RFID, QR code, etc., and has extremely low hardware performance requirements;

[0073] 3. The present application can reduce the investment in positioning and navigation equipment accordingly. Taking the "magnetic guidance + RFID" solution as an example, the offset of the magnetic stripe obtained by the magnetic guidance sensor is used to calculate the offset to correct the posture deviation, which can ensure the reliability of the acquired label value. At the same time, the "local + cloud" map label acquisition method can also make full use of the original vehicle-mounted positioning, regulation and control, and communication modules to reduce the additional performance expenses of equipment such as vehicle-mounted controllers. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] The following specifically describes the implementation scheme in conjunction with the accompanying drawings;

[0075] Figure 1 This is a schematic diagram of the currently used AGV navigation map;

[0076] Figure 2 It is a flow chart of the method for the AGV chassis to automatically obtain and update map labels described in this application;

[0077] Figure 3 It is a schematic diagram of AGV chassis posture correction;

[0078] Figure 4 It is the traversal algorithm flowchart; DETAILED DESCRIPTION

[0079] Embodiment 1, as Figures 2 to 4 As shown, the present application proposes a method for an AGV chassis to automatically obtain map labels, which is used to automatically obtain map labels and update map routing information, and includes the following implementation steps:

[0080] Step 1), receiving instructions;

[0081] Receive cloud instructions and determine whether to start automatic identification; if so, proceed to step 2); if not, continue waiting;

[0082] Step 2), initialization;

[0083] Initialize the AGV chassis posture, obtain the original map and save the map routing points;

[0084] Since the original map is generated by a cloud tool, which lacks corresponding label values, the initial position coordinates of the AGV chassis need to be given; taking the coordinate point (0, 0) as an example, the initial angle is set to 0;

[0085] After loading the map, the route points in the map are stored in the form of key-value pairs {(x, y), RouteNode}, where the key is the (x, y) coordinate information and RouteNode is the route point corresponding to the coordinate;

[0086] Put the starting location routing point into set Q, and put other routing points into set P;

[0087] Step 3), traverse the routing points and plan the running trajectory;

[0088] Traverse all routing points in order and plan the running trajectory; if set P is empty, copy the routing points in set N to set P, clear set N at the same time, and use the traversal algorithm to plan the traversal order of routing points in set P; if set P is not empty, directly use the traversal algorithm to plan the traversal order of routing points in set P; plan the motion trajectory according to the traversal order of routing points;

[0089] like Figure 4 As shown, the process of the traversal algorithm is as follows:

[0090] 3.1) Get the coordinates of the routing point where the AGV is currently located and get the routing point set;

[0091] 3.2) Calculate the cost from the current routing point to each routing point in the set; the calculation formula is as follows:

[0092] F(n)=C(n)+R(n)

[0093] C(n)=|x n -x i |+|y n -y i |

[0094] R(n)=r n -r i

[0095] Wherein, n in the above formula represents the routing point numbered n, i represents the current routing point; F(n) is the cost value of routing point numbered n, C(n) is the Manhattan distance from routing point numbered n to the current routing point (in millimeters); R(n) is the difference between the routing point numbered n and the current routing point;

[0096] The point with the smallest cost is selected as the next target point. Since the Manhattan distance is much larger than the deviation value of the routing point number, this ensures that the target point is selected nearby. At the same time, R(n) has positive and negative values, which ensures that the target point selects the nearest routing point with a smaller number.

[0097] As from Figure 1 It can be seen that the routing point numbers are continuous in rows or columns. The above traversal algorithm ensures that the traversal order of the AGV chassis is continuous in rows / columns, which reduces the number of turns and shortens the working time;

[0098] Step 4), chassis posture calculation and update positioning information;

[0099] Acquire the data of the vehicle-mounted sensor. This embodiment takes the "magnetic guide + RFID" solution as an example;

[0100] Get the current routing point of the AGV through coordinate matching;

[0101] If a tag is identified, the current routing point information is updated with the identified tag value and the positioning information is published, including but not limited to the current routing point number, routing point tag value and AGV chassis posture information; the routing point matching the tag information is put into set Q, and the point is deleted from set P, and the offset calculated by the magnetic permeability sensor is used to correct the AGV chassis posture information;

[0102] If the routing label is not identified, the routing point that does not match the label information is placed in set N, and the point is deleted from set P, and the label value in the published positioning information is recorded as 0;

[0103] The calculation formula for matching the current routing point through coordinates is as follows:

[0104]

[0105] Among them, (x t ,y t ) is the coordinate of the current routing point, (x g ,y g ) is the coordinate value of the AGV chassis fusion positioning, and w is the distance between routing points;

[0106] Match the obtained routing point coordinates with the routing point set key value. From step 2), it is known that the routing point storage method is {(x, y), RouteNode}. Find (x t ,y t ), find the key value x=x t ,y=y t The corresponding routing point RouteNode completes the coordinate matching.

[0107] like Figure 3 As shown in the figure, the calculation process of posture correction for the "magnetic guide + RFID" solution is:

[0108] 4.1) Determine the position offset of the magnetic stripe based on the sensor data, and obtain the coordinates of the four points P0 to P3 in the chassis coordinate system: d0, d1, d2, and d3 are offsets, which are positive or negative. The offset in the positive direction of the coordinate axis is positive, and the offset in the negative direction is negative;

[0109]

[0110] 4.2) Obtain the angle α between the two coordinate systems based on the coordinates of points P0 and P1;

[0111] Counterclockwise is positive;

[0112] 4.3) Determine two straight lines based on P0P1 and P2P3, and obtain the following straight line equations:

[0113] The P0P1 equation is,

[0114]

[0115] The P2P3 equation is,

[0116]

[0117] 4.4) Obtain the coordinates of the origin of the geomagnetic coordinate system in the chassis coordinate system (x m ,y m );

[0118]

[0119] b1=y0-m1x0

[0120] b2=y2-m2x2

[0121]

[0122] y m =m1x m +b1

[0123] 4.5) By α and (x m ,y m ) Inversely deduce the position and posture of the chassis coordinate system in the geomagnetic coordinate system;

[0124] The declination angle Δa and deviations Δx and Δy of the chassis coordinate system in the geomagnetic coordinate system, where the angle is positive if it is counterclockwise and negative if it is clockwise;

[0125] The deflection angle of the chassis coordinate system is,

[0126] The transformation matrix from the magnetic stripe coordinate system to the chassis coordinate system is:

[0127]

[0128] The transformation matrix from chassis coordinate system to magnetic stripe coordinate system is:

[0129]

[0130] Then, the coordinate deviation of the chassis coordinate system is:

[0131]

[0132] The calculated offset is:

[0133]

[0134] The AGV chassis posture is corrected to:

[0135]

[0136] In the above formula, (x, y, a) is the corrected pose information at the current moment, (x t ,y t ,a t ) is the pose calculated by the odometer at the current moment.

[0137] Step 5), update the map;

[0138] The cloud receives AGV location information and updates the map;

[0139] If the received location information tag value is not 0, the corresponding routing point information in the map is updated with the tag value;

[0140] If the received location information tag value is 0, the staff will be prompted to check the reason and skip the point to continue updating the next routing point information;

[0141] Step 6) Determine whether the routing point information is updated;

[0142] Determine whether all routing points have been traversed, that is, whether set P and set N are both empty; if so, stop updating; if not, jump to step 3) to continue execution.

[0143] The above contents and the embodiments given in the accompanying drawings are only preferred solutions for achieving the purpose of the present invention. Those skilled in the art can be inspired by this and directly deduce other alternative structures that conform to the design concept of the present invention. Other structural features obtained thereby should also belong to the scope of the solution described in the present invention.

Claims

1. A method for automatically obtaining map labels for an AGV chassis, characterized in that: The implementation steps include: Step 1), receiving instructions; Receive cloud instructions and determine whether to start automatic identification; if so, proceed to step 2); if not, continue waiting; Step 2), initialization; Initialize the AGV chassis posture, obtain the original map and save the map routing points; After loading the map, the route points in the map are stored in the form of key-value pairs {(x, y), RouteNode}, where the key is the (x, y) coordinate information and RouteNode is the route point corresponding to the coordinate; Put the starting location routing point into set Q, and put other routing points into set P; Step 3), traverse the routing points and plan the running trajectory; Traverse all routing points in order and plan the running trajectory; If set P is empty, copy the routing points in set N to set P, clear set N at the same time, and use the traversal algorithm to plan the traversal order of the routing points in set P; If the set P is not empty, the traversal algorithm is directly used to plan the traversal order of the routing points in the set P; Plan the movement trajectory according to the traversal order of routing points; Step 4), chassis posture calculation and update positioning information; Obtain data from the vehicle-mounted sensors and obtain the current routing point of the AGV through coordinate matching; If a tag is recognized, the current routing point information is updated with the recognized tag value and the positioning information is published; the routing point matching the tag information is put into set Q, and the point is deleted from set P, and the offset calculated by the magnetic permeability sensor is used to correct the position information of the AGV chassis; If the routing label is not identified, the routing point that does not match the label information is placed in set N, and the point is deleted from set P, and the label value in the published positioning information is recorded as 0; Step 5), update the map; The cloud receives AGV location information and updates the map; If the received location information tag value is not 0, the corresponding routing point information in the map is updated with the tag value; If the received location information tag value is 0, the staff will be prompted to check the reason and skip the point to continue updating the next routing point information; Step 6) Determine whether the routing point information is updated; Determine whether all routing points have been traversed, that is, whether both set P and set N are empty; if so, stop updating; if not, jump to step 3) to continue execution; In step 4), the calculation formula for matching the current routing point by coordinates is as follows: Among them, (x t ,y t ) is the coordinate of the current routing point, (x g ,y g ) is the coordinate value of the AGV chassis fusion positioning, and w is the distance between routing points; Match the obtained routing point coordinates with the routing point set key value. From step 2), it is known that the routing point storage method is {(x, y), RouteNode}. Find (x t ,y t ), find the key value x=x t ,y=y t The corresponding route point RouteNode completes the coordinate matching; The calculation process of performing posture correction in step 4) is as follows: 4.1) Determine the position offset of the magnetic stripe based on the sensor data, and obtain the coordinates of the four points P0 to P3 in the chassis coordinate system: d0, d1, d2, and d3 are offsets, which are positive or negative. The offset in the positive direction of the coordinate axis is positive, and the offset in the negative direction is negative; P0 coordinates , P1 coordinates P2 coordinates , P3 coordinates 4.2) Obtain the angle α between the two coordinate systems based on the coordinates of points P0 and P1; Counterclockwise is positive; 4.3) Determine two straight lines based on P0P1 and P2P3, and obtain the following straight line equations: The P0P1 equation is, The P2P3 equation is, 4.4) Obtain the coordinates of the origin of the geomagnetic coordinate system in the chassis coordinate system (x m ,y m ); b1=y0-m1x0 b2=y2-m2x2 and m =m1x m +b1 4.5) By α and (x m ,y m ) Inversely deduce the position and posture of the chassis coordinate system in the geomagnetic coordinate system; The declination angle Δa and deviations Δx and Δy of the chassis coordinate system in the geomagnetic coordinate system, where the angle is positive if it is counterclockwise and negative if it is clockwise; The chassis coordinate system deflection angle is, The transformation matrix from the magnetic stripe coordinate system to the chassis coordinate system is: The transformation matrix from chassis coordinate system to magnetic stripe coordinate system is: Then, the coordinate deviation of the chassis coordinate system is: The calculated coordinate offset is: The AGV chassis posture is corrected to: In the above formula, (x, y, a) is the corrected pose information at the current moment, (x t ,y t ,a t ) is the pose calculated by the odometer at the current moment.

2. The method for automatically acquiring map labels for an AGV chassis according to claim 1, characterized in that: In the AGV chassis initialization of step 2), the coordinates of the origin of the map coordinate system or any routing point are used as the starting point.

3. The method for automatically acquiring map labels for an AGV chassis according to claim 1, characterized in that: The traversal algorithm flow of step 3) is as follows: 3.1) Get the coordinates of the routing point where the AGV is currently located and get the routing point set; 3.2) Calculate the cost from the current routing point to each routing point in the set; The calculation formula is as follows, F(n)=C(n)+R(n) C(n)=|x n -x i |+|y n -y i | R(n)=r n -r i In the above formula, n represents the routing point numbered n, i represents the current routing point; F(n) is the cost value of routing point n, C(n) is the Manhattan distance from routing point n to the current routing point, in millimeters; R(n) is the difference between routing point n and the current routing point number; the point with the smallest cost value is selected as the next target point.

4. The method for automatically acquiring map labels for an AGV chassis according to claim 1, characterized in that: In the step 4), the positioning information includes the current routing point number, routing point label value and AGV chassis posture information.

5. The method for automatically acquiring map labels for an AGV chassis according to claim 1, characterized in that: The map tag is an RFID or a QR code.

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