CN111158370B - Automatic guided vehicle AGV deployment method and system and automatic guided vehicle AGV - Google Patents

Automatic guided vehicle AGV deployment method and system and automatic guided vehicle AGV Download PDF

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CN111158370B
CN111158370B CN201911425494.7A CN201911425494A CN111158370B CN 111158370 B CN111158370 B CN 111158370B CN 201911425494 A CN201911425494 A CN 201911425494A CN 111158370 B CN111158370 B CN 111158370B
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CN111158370A (en
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肖美华
李泽寰
欧阳日
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East China Jiaotong University
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
    • G05D1/0274—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means using mapping information stored in a memory device
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/10—Path keeping
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
    • B62D—MOTOR VEHICLES; TRAILERS
    • B62D63/00—Motor vehicles or trailers not otherwise provided for
    • B62D63/02—Motor vehicles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
    • B62D—MOTOR VEHICLES; TRAILERS
    • B62D63/00—Motor vehicles or trailers not otherwise provided for
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    • B62D63/04—Component parts or accessories

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Abstract

The invention discloses an AGV deployment method, which comprises the following steps: drawing and storing a topological map G according to the deployment site; acquiring the initial position of the AGV; determining a travel path according to the topological map G, the starting position and a preset target position; and driving the automatic guided vehicle AGV to reach the target position according to the travelling path. According to the invention, the topological map is automatically drawn, the travelling path is determined according to the initial position and the preset target position, so that the automatic guided vehicle finally reaches the target position, the site is not required to be additionally modified or hardware equipment is not required to be additionally arranged, the deployment can be performed in a self-adaptive manner according to the site, and the deployment efficiency is improved, the site adaptability is enhanced and the deployment cost is reduced by a mode of determining the travelling path in advance. The invention also discloses an automatic guided vehicle AGV deployment system and an automatic guided vehicle AGV.

Description

Automatic guided vehicle AGV deployment method and system and automatic guided vehicle AGV
Technical Field
The invention relates to the technical field of industrial automation, in particular to an automatic guided vehicle AGV deployment method and system and an automatic guided vehicle AGV.
Background
In the current factory environment, the deployment of a common automatic guided vehicle AGV has the following problems:
1. the flexibility is poor, if the factory needs to change the production environment, professional personnel are required to adjust the AGV, and the deployment time is slow;
2. electromagnetic guidance, tape guidance or optical guidance are adopted, additional site modification or additional equipment is usually required, and the cost is high.
Disclosure of Invention
Based on the problems, the invention provides an automatic guided vehicle AGV deployment method and system and an automatic guided vehicle AGV.
In view of this, the invention provides an automatic guided vehicle AGV deployment method, comprising the following steps:
drawing and storing a topological map G according to the deployment site;
acquiring the initial position of the AGV;
determining a travel path according to the topological map G, the starting position and a preset target position;
and driving the automatic guided vehicle AGV to reach the target position according to the travelling path.
The invention also discloses an AGV deployment system of the automatic guided vehicle, which comprises,
the map drawing module is used for drawing and storing a topological map G according to the deployment site;
the starting position acquisition module is used for acquiring the starting position of the AGV;
the travel path determining module is used for determining a travel path according to the topological map, the current position and a preset target position;
and the traveling module is used for driving the AGV to reach the target position according to the traveling path.
The invention also discloses an automatic guided vehicle AGV, which comprises the automatic guided vehicle AGV deployment system.
The beneficial effects of the invention are as follows: the automatic guided vehicle reaches the target position finally by automatically drawing the topological map and determining the travelling path according to the initial position and the preset target position, the site is not required to be additionally modified or hardware equipment is additionally arranged, the deployment can be performed in a self-adaptive mode according to the site, and the deployment efficiency is improved, the site adaptability is enhanced and the deployment cost is reduced by a mode of determining the travelling path in advance.
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FIG. 1 illustrates a flow chart of an automated guided vehicle AGV deployment method provided in accordance with an embodiment of the present invention;
FIG. 2 illustrates a block diagram of an automated guided vehicle hardware platform provided in accordance with an embodiment of the present invention;
FIG. 3 illustrates an example of an automated guided vehicle AGV deployment method topology map provided in accordance with an embodiment of the present invention;
FIG. 4 illustrates an automatic guided vehicle AGV deployment method obstacle intensity distribution histogram provided in accordance with an embodiment of the present invention;
FIG. 5 illustrates a schematic diagram of an automatic guided vehicle AGV deflection preset angle according to an automatic guided vehicle AGV deployment method provided by an embodiment of the present invention;
FIG. 6 shows a schematic diagram of an automated guided vehicle AGV affected by length and width;
FIG. 7 illustrates a schematic diagram of an AGV overcoming the length and width effects according to one embodiment of the present invention;
FIG. 8 illustrates a laser radar coordinate system schematic diagram of an automated guided vehicle AGV deployment method provided in accordance with an embodiment of the present invention;
FIG. 9 is a schematic diagram of an Inertial Measurement Unit (IMU) coordinate system of an AGV deployment method according to an embodiment of the present invention
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, without conflict, the embodiments of the present invention, i.e., the features in the embodiments, may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
FIG. 1 illustrates a flowchart of an automatic guided vehicle AGV deployment method provided in accordance with an embodiment of the present invention.
As shown in fig. 1, in this embodiment, an automatic guided vehicle AGV deployment method includes the following steps:
drawing and storing a topological map G according to the deployment site;
acquiring the initial position of the AGV;
the initial position of the AGV can be obtained by adding a code wheel and an inertial measurement unit IMU (Inertial Measurement Unit) to the AGV AGV (Automated Guided Vehicle).
Determining a travel path according to the topological map G, the starting position and a preset target position;
the determination of the travel path can be performed in a mode of manual specification according to a topological map or in a mode of automatic planning according to a certain rule, and the preset target position, namely the position where the trolley is expected to be deployed, can be specified manually or according to a certain rule.
And driving the automatic guided vehicle AGV to reach the target position according to the travelling path.
And the automatic guided vehicle AGV is driven to move according to the travelling path, and can be controlled by adopting a separately arranged lower computer. The lower computer comprises a singlechip, an Inertial Measurement Unit (IMU) and a code disc, and is mainly used for controlling the Automatic Guided Vehicle (AGV) to move according to the travelling path and obtaining the current gesture and position of the Automatic Guided Vehicle (AGV).
It can be understood that the path planning and the topology map drawing need more operation resources, and the topology map drawing can be realized by adopting a structure combining an upper computer and a lower computer. The hardware platform framework is shown in fig. 2.
As shown in fig. 2, the system comprises an upper computer and a lower computer. The lower computer consists of a singlechip (STM 32F 103), an IMU (MPU 6050) and a code disc and is used for controlling the movement of the AGV, wherein the IMU and the singlechip use IIC for communication; the upper computer consists of a laser radar and an embedded development board (Jetson Tk 1) and is used for planning the running direction of the AGV. The upper computer is developed based on the ROS, and is communicated with the lower computer and the laser radar through serial ports.
In the above embodiment, the topology map is automatically drawn, and the travel path is determined according to the current position and the preset target position, so that the automatic guided vehicle finally reaches the target position, and the site is not required to be additionally modified or hardware equipment is additionally installed, and the deployment can be performed adaptively according to the site, and the deployment efficiency is improved, the site adaptability is enhanced, and the deployment cost is reduced by determining the travel path in advance.
Optionally, the topological map is represented by g= (V, E), wherein V represents a set of nodes, E represents a set of edges connecting nodes, the edges in the set of edges including a start node, a stop node, and a travel direction;
the four nodes are a, b, c, d, the topological map diagram is shown in fig. 3, the nodes contain the position information of the point, the automatic guided vehicle AGV searches the stored nodes when working normally, and the automatic guided vehicle AGV can acquire the parameters required to move to the next point according to the node information. The topological map is symbolized as g= (V, E), where the set of nodes is represented as: v= { a, b, c, d }, the set of edges connecting the nodes is expressed as:
E＝{(a,b),(b,a),(b,c),(c,b),(c,d),(d,c)}，
the edges contain position information of the start node and the end node, as well as direction information.
The method for drawing and storing the topological map G according to the deployment site comprises the following steps of
Acquiring deployment site radar scanning data;
the method comprises the steps of acquiring the scanning data of the radar of the deployment site, and acquiring the scanning data through an optical radar arranged on an AGV.
Acquiring the current position of the AGV; the current position information can be obtained through a code disc on an automatic guided vehicle AGV and an inertial measurement unit IMU.
According to the radar sweepTracing data to obtain obstacle intensity value H of each direction within 360 DEG i ；
According to the obstacle intensity value H of each direction i Determining the candidate direction set A;
calculating a cost value g (c) of each candidate direction in the candidate direction set A;
selecting the candidate direction corresponding to the minimum cost value g (c) from the candidate direction set A as a downward walking direction;
when the angle difference between the downward walking direction and the current direction is larger than a preset threshold value, judging whether the current position is already stored in the node set V, and when the current position is not stored in the node set V, taking the current position as the termination node, taking the previous node as the starting node, taking the current direction as the travelling direction, and storing edges formed by the starting node, the termination node and the travelling direction into the edge set E;
the preset threshold may be 5 °, and the formula of the joining node is expressed as follows:
φ＝vfh_aimR-vfh_aim_N
Figure BDA0002346522600000051
Figure BDA0002346522600000052
vfh _aimr is the current direction, vfh _aimn is the next driving direction, phi is the offset, Q is the preset threshold, which may be 5 °, point is the current node, points is the topology node set, mapping indicates that the newly obtained node is matched in the node set, mapping= =1 indicates that the matching is successful, the node is the old node, mapping= =0 indicates that the matching is failed, the node is the new node, and the node with failed matching is added into the new node.
The AGV moves according to the downward walking direction;
and from the step of acquiring the deployment site radar scanning data, repeatedly executing the steps until the automatic guided vehicle AGV stops moving according to the downward walking direction until new nodes and edges cannot be added.
It can be appreciated that the AGV automatically adds nodes at the deployment site, eventually, all nodes are found, and thus new nodes cannot be found, at which time the topology map is drawn.
In the above embodiment, by judging whether the running direction changes beyond the preset threshold value, the inflection point of the direction change is stored in the topological map, so that the data volume of map storage processing is greatly reduced, and the automatic guided vehicle AGV can conveniently and rapidly conduct path planning when actually moving in a mode of pre-storing the topological map.
Optionally, the obstacle intensity value H of each direction in the 360 ° range is obtained according to the radar scan data i Comprises
Figure BDA0002346522600000061
Wherein i represents the scanning direction of the laser radar acquisition data, the value of the scanning direction i corresponds to the scanning range of the 360-degree laser radar, and the value of the scanning direction i is {0,1,2,3 … 359}, d i For the distance of the laser radar measured in the scanning direction i, cv, a and b are constants, and a and b satisfy
Figure BDA0002346522600000062
d max For a maximum value of distances measured by the lidar in the 360 ° direction, the radar scan data includes a distance d measured by the lidar in the scan direction i i ；
Wherein, the values of cv, a and b can be 10, 22.5 and 2.5, and the obstacle intensity value H i Larger indicates harder to travel in the i direction, H i The vector histogram of the distribution is shown in fig. 4.
Said determining said set of candidate directions a based on said obstacle intensity values Hi for each direction, comprising,
the candidate direction set a is determined to be {0,1,2,3 … 359}.
Optionally, the obstacle intensity value H according to each direction i Determining the set of candidate directions a, including,
determining an obstacle intensity threshold M;
determining the candidate direction set A as the H i And when the intensity of the obstacle is smaller than the threshold M, the corresponding scanning direction i is set.
It will be appreciated that the obstacle intensity value H is derived directly from the radar scan data i And the passable degree is inversely changed. To simplify the processing, an obstacle intensity threshold M may be set, when the obstacle intensity value H is derived directly from the radar scan data i If the intensity value is greater than or equal to the obstacle intensity threshold value M, the obstacle cannot pass through, and the obstacle intensity value H is directly obtained from radar scanning data i And if the intensity is smaller than the obstacle intensity threshold M, the vehicle can pass through. When the value of M is smaller, more directions can pass, so that the AGV needs more time to find out all nodes. When the value of M is larger, the passing direction is smaller, so that the AGV cannot find all nodes.
The obstacle intensity threshold M can be determined by combining a deployment site, and is selected on the narrowest passing path, so that when the passable angle of the AGV is 60 DEG, the corresponding obstacle intensity value H i As the obstacle intensity threshold M.
In the above embodiment, the operation speed is improved by determining the obstacle intensity threshold M, and using the intensity threshold as the limit for dividing the passable boundary, and determining the range of the candidate direction set.
Optionally, the calculating a cost value g (c) for each candidate direction in the set of candidate directions a includes,
g(c)＝μ 1 Δ(c,k t )+μ 2 Δ(c,k r )+μ 3 Δ(c,k b_pre )，
c is a candidate direction, the value of c is taken from the candidate direction set A, and delta (c, k) t ) For the angle between the candidate direction and the preset direction, delta (c, k r ) For the angle between the candidate direction and the current direction, delta (c, k b_pre ) Is the included angle between the candidate direction and the motion direction at the previous moment, wherein mu 1, mu 2 and mu 3 are constants, and mu 1>μ2+μ3。
The preset direction is a direction in which the automatic guided vehicle AGV is preferentially assigned in advance, and values of μ1, μ2, and μ3 may be 10, 4, and 2. The cost value g (c) reflects the influence of the preset direction, the current direction and the motion direction at the previous moment on the candidate direction, and the higher the cost value is, the harder the user can pass.
In the above embodiment, by introducing the cost value g (c), the direction preference is made more convenient.
Alternatively, as shown in FIG. 6, the obstacle intensity value H in each direction is calculated based on the above-described i Before calculating the cost value g (c) of each candidate direction in the candidate direction set A, the method further comprises the following steps;
respectively shifting the candidate direction c leftwards and rightwards by a preset angle theta to obtain a leftwards offset sector and a rightwards offset sector;
counting the obstacle intensity values H of each direction corresponding to the left-offset sector and the right-offset sector i A number less than the obstacle intensity threshold M;
if the left-offset sector and the right-offset sector are obstacle intensity values H i The number of the obstacle intensity thresholds M is smaller than the preset number, the obstacle intensity value corresponding to the scanning direction c+theta is smaller than the obstacle intensity threshold M, the obstacle intensity value corresponding to the scanning direction c-theta is smaller than the obstacle intensity threshold M, the candidate direction c is reserved in the candidate direction set A, and otherwise, the candidate direction c is deleted from the candidate direction set A.
Wherein, the preset angle θ may be 5 °, the preset number may be 0.6θ, and the data formula expression process is as follows:
Figure BDA0002346522600000081
Figure BDA0002346522600000082
when the result is not Valid, the candidate direction c needs to be deleted from the candidate direction set a.
It should be noted that, as shown in fig. 5, in the traveling process of the AGV, a conclusion that the AGV can pass is obtained without considering the volume, but the AGV cannot pass due to the obstruction of the length and width of the AGV, so that misjudgment and ineffective direction may be caused. The preferred embodiment described above is to solve this problem.
In the embodiment, the passing condition within the range of the preset angle theta is judged by the AGV, so that the influence of the length and width of the AGV is avoided, the failure of drawing the topological map is caused, and the stability of the method is further improved. After the method is adopted, the traveling diagram of the AGV is shown in FIG. 7.
Alternatively, the process may be carried out in a single-stage,
the determining a travel path according to the topological map G, the starting position and a preset target position includes,
determining a path with the shortest sum of the distances between the starting position and the preset target position as a traveling path according to the topological map G,
or determining a travel path according to the topological map G, the starting position and a preset target position according to a preset direction sequence.
The preset direction sequence may be a longitudinal approach to the preset target position and then a transverse approach to the target position, or a transverse approach to the preset target position and then a longitudinal approach to the target position.
The path of travel may be represented by an adjacency matrix. The rows and columns of the adjacency matrix are determined by the points of the topological map. The traveling direction and the blocking direction are distinguished by giving different weights to the sides, wherein the weight of the traveling direction is set to 2, the weight of the blocking direction is set to 1, and the weights of the other directions are set to 0. When an automated guided vehicle AGV needs to move from one node to another in the topology map, only the parameters in the adjacency matrix need be changed. Such as the travel path shown in fig. 3. As represented by the following adjacency matrix.
Figure BDA0002346522600000091
The above-described adjacency matrix represents one process by which an automated guided vehicle AGV moves from node a to node d: the AGV starts moving from a, moves from b to c, then moves from c to d, and stops moving at d. The combination of the topology map and the adjacency matrix allows the complex motion control abstraction of the automated guided vehicle AG to be a simple parameter modification. Therefore, after the automatic guided vehicle AGV builds the completion map, the traveling path of the automatic guided vehicle AGV can be rapidly defined.
Optionally, the automated guided vehicle AGV is driven to the target position according to the travel path, including,
and repeatedly acquiring the traveling direction from the traveling path, controlling the AGV to turn to the traveling direction, and traveling in the traveling direction until the target position is reached.
The step of the AGV in the travel direction is to control the AGV to turn in the travel direction and then travel in this travel direction.
The control formula is as follows:
Figure BDA0002346522600000101
Figure BDA0002346522600000102
BiasL＝EncoderL-left
BiasR＝EncoderR-right
left_pwm+＝P×(BiasL-Last_biasL)+I×BiasL
right_pwm+＝P×(BiasR-Last_biasR)+I×BiasR
this manner of controlling the travel of the automated guided vehicle AGV is also known as proportional and integral PI (proportional integral controller) control.
In the above formula, left and right are target rotational speeds of the left wheel and the right wheel, angle is the interval between the current course angle and the target angle, encoderL and EncoderR are rotational speeds of the current left wheel and the right wheel, biasL and BiasR are difference values between the current motor rotational speed and the target rotational speed, left_pwm and right_pwm are pulse modulation width pwm (Pulse Width Modulation) values of the left wheel and the right wheel, and the related constants of '1.2', '20', and the like can be adjusted and determined according to the actual conditions of the AGV. The motor is controlled to achieve the purpose of controlling the AGV by controlling the pulse modulation width pwm of the left wheel and the right wheel.
In the embodiment, the PI control mode is adopted, so that the interaction of data is reduced, and the communication cost and the control complexity are reduced.
In addition, in the actual deployment process of the automatic guided vehicle AGV deployment method, since the data of the laser radar on the automatic guided vehicle AGV is an angle output in a local angle, the heading angle measured by the IMU needs to be utilized to convert the angle of the laser radar into a global polar coordinate angle. The coordinate system of the lidar is shown in fig. 8. The coordinate system of the IMU is shown in fig. 9. The formula of the conversion is as follows:
Figure BDA0002346522600000103
Global＝yaw+Lida
Figure BDA0002346522600000104
lida is the angle of the laser radar, yaw is the heading angle measured by the IMU, and Global is the angle after laser radar conversion. The angular transformation of the lidar is calculated as a global polar angle.
The embodiment of the invention discloses an AGV deployment system of an automatic guided vehicle, which comprises,
the map drawing module is used for drawing and storing a topological map G according to the deployment site;
the starting position acquisition module is used for acquiring the starting position of the AGV;
the advancing path determining module is used for determining an advancing path according to the topological map, the starting position and the preset target position;
and the traveling module is used for driving the AGV to reach the target position according to the traveling path. The embodiment of the invention also discloses an automatic guided vehicle AGV, which comprises the automatic guided vehicle AGV deployment system according to claim 9.
In the embodiment, the automatic guided vehicle reaches the target position by automatically drawing the topological map and determining the travelling path according to the current position and the preset target position, so that the automatic guided vehicle does not need to additionally improve the field or add hardware equipment, can be deployed in a self-adaptive manner according to the field, improves the deployment efficiency by determining the travelling path in advance, enhances the field adaptability and reduces the deployment cost.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (9)

1. An automatic guided vehicle AGV deployment method is characterized by comprising the following steps:
drawing and storing a topological map G according to the deployment site;
acquiring the initial position of the AGV;
determining a travel path according to the topological map G, the starting position and a preset target position;
driving the AGV to reach the target position according to the travelling path;
wherein the topological map is represented by g= (V, E), wherein V represents a set of nodes, E represents a set of edges connecting the nodes, the edges in the set of edges comprising a start node, a stop node, and a direction of travel;
the method for drawing and storing the topological map G according to the deployment site comprises the following steps of
Acquiring radar scanning data of a deployment site;
acquiring the current position of the AGV;
according to the radar scanning data, obtaining an obstacle intensity value H of each direction within a 360-degree range i ；
According to the obstacle intensity value H of each direction i Determining a candidate direction set A;
calculating a cost value g (c) of each candidate direction in the candidate direction set A;
selecting the candidate direction corresponding to the minimum cost value g (c) from the candidate direction set A as a downward walking direction;
when the angle difference between the downward walking direction and the current direction is larger than a preset threshold value, judging whether the current position is already stored in the node set V, and when the current position is not stored in the node set V, taking the current position as the termination node, taking the previous node as the starting node, taking the current direction as the travelling direction, and storing edges formed by the starting node, the termination node and the travelling direction into the edge set E;
the AGV moves according to the downward walking direction;
and from the step of acquiring the deployment site radar scanning data, the automatic guided vehicle AGV repeatedly executes the steps from the step of acquiring the deployment site radar scanning data to the step of stopping the automatic guided vehicle AGV according to the walking direction until new nodes and edges cannot be added.
2. An automated guided vehicle AGV deployment method according to claim 1 wherein,
the obstacle intensity value H of each direction within the 360-degree range is obtained according to the radar scanning data i Comprises
Figure QLYQS_1
Wherein i represents the scanning direction of the laser radar acquisition data, the value of the scanning direction i corresponds to the scanning range of the 360-degree laser radar, and the value of the scanning direction i is {0,1,2,3 … 359}, d i For the distance of the laser radar measured in the scanning direction i, cv, a and b are constants, and a and b satisfy
Figure QLYQS_2
d max For a maximum value of distances measured by the lidar in the 360 ° direction, the radar scan data includes a distance d measured by the lidar in the scan direction i i。
3. An automated guided vehicle AGV deployment method according to claim 2 wherein,
the obstacle intensity value H according to each direction i Determining the set of candidate directions a, including,
determining an obstacle intensity threshold M;
determining the candidate direction set A as the H i And when the intensity of the obstacle is smaller than the threshold M, the corresponding scanning direction i is set.
4. An automated guided vehicle AGV deployment method according to claim 3 wherein,
the calculating of the cost value g (c) for each candidate direction in the set of candidate directions a includes,
g(c)＝μ 1 Δ(c,k t )+μ 2 Δ(c,k r )+μ 3 Δ(c,k b_pre )，
c is a candidate direction, the value of c is taken from the candidate direction set A, and delta (c, k) t ) For the angle between the candidate direction and the preset direction, delta (c, k r ) For the angle between the candidate direction and the current direction, delta (c, k b_pre ) Is the included angle between the candidate direction and the previous movement direction, and the mu 1, the mu 2 and the mu 3 areConstant, and mu 1>μ2+μ3。
5. The automatic guided vehicle AGV deployment method of claim 4 wherein
At said obstacle intensity value H according to said each direction i Before calculating the cost value g (c) of each candidate direction in the candidate direction set A, the method further comprises the following steps;
respectively shifting the candidate direction c leftwards and rightwards by a preset angle theta to obtain a leftwards offset sector and a rightwards offset sector;
counting the obstacle intensity values H of each direction corresponding to the left-offset sector and the right-offset sector i A number less than the obstacle intensity threshold M;
if the left-offset sector and the right-offset sector are obstacle intensity values H i The number of the obstacle intensity thresholds M is smaller than the preset number, the obstacle intensity value corresponding to the scanning direction c+theta is smaller than the obstacle intensity threshold M, the obstacle intensity value corresponding to the scanning direction c-theta is smaller than the obstacle intensity threshold M, the candidate direction c is reserved in the candidate direction set A, and otherwise, the candidate direction c is deleted from the candidate direction set A.
6. The automatic guided vehicle AGV deployment method according to claim 1, wherein the determining a travel path according to the topology map G, the start position, and a preset target position comprises,
determining a path with the shortest sum of the distances between the starting position and the preset target position as a traveling path according to the topological map G,
or determining a travel path according to the topological map G, the starting position and a preset target position according to a preset direction sequence.
7. An automated guided vehicle AGV deployment method as set forth in claim 1 wherein said driving the automated guided vehicle AGV to the target location based on the travel path comprises,
and repeatedly acquiring the traveling direction from the traveling path, controlling the AGV to turn to the traveling direction, and traveling in the traveling direction until the target position is reached.
8. An automated guided vehicle AGV deployment system comprising,
the map drawing module is used for drawing and storing a topological map G according to the deployment site;
the starting position acquisition module is used for acquiring the starting position of the AGV;
the advancing path determining module is used for determining an advancing path according to the topological map, the starting position and the preset target position;
the traveling module is used for driving the AGV to reach the target position according to the traveling path;
wherein the topological map is represented by g= (V, E), wherein V represents a set of nodes, E represents a set of edges connecting the nodes, the edges in the set of edges comprising a start node, a stop node, and a direction of travel;
the method for drawing and storing the topological map G according to the deployment site comprises the following steps of
Acquiring radar scanning data of a deployment site;
acquiring the current position of the AGV;
according to the radar scanning data, obtaining an obstacle intensity value H of each direction within a 360-degree range i ；
According to the obstacle intensity value H of each direction i Determining a candidate direction set A;
calculating a cost value g (c) of each candidate direction in the candidate direction set A;
selecting the candidate direction corresponding to the minimum cost value g (c) from the candidate direction set A as a downward walking direction;
when the angle difference between the downward walking direction and the current direction is larger than a preset threshold value, judging whether the current position is already stored in the node set V, and when the current position is not stored in the node set V, taking the current position as the termination node, taking the previous node as the starting node, taking the current direction as the travelling direction, and storing edges formed by the starting node, the termination node and the travelling direction into the edge set E;
the AGV moves according to the downward walking direction;
and from the step of acquiring the deployment site radar scanning data, the automatic guided vehicle AGV repeatedly executes the steps from the step of acquiring the deployment site radar scanning data to the step of stopping the automatic guided vehicle AGV according to the walking direction until new nodes and edges cannot be added.
9. An automated guided vehicle AGV comprising the automated guided vehicle AGV deployment system of claim 8.
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