Driving control method, device and equipment of automatic guided vehicle and storage medium

Abstract

The invention relates to the technical field of path planning, and discloses a driving control method, device and equipment for an automatic guided vehicle and a storage medium, and the method comprises the steps: firstly, planning a path node set of the automatic guided vehicle from an initial node to a target node, and then combining the initial orientation of the automatic guided vehicle and the path attribute of a topological map, and analyzing a target action which needs to be executed when the automatic guided vehicle arrives at each path node so as to adjust the orientation of the vehicle head and further drive to the next path node. Therefore, the dynamic path planning of the magnetic navigation automatic guided vehicle can be realized, the driving path and the execution action do not need to be set in advance, the application scene is wider, and the working efficiency and the use flexibility of the automatic guided vehicle can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of path planning, and in particular to a driving control method, device, equipment and storage medium for an automatic guided vehicle. Background Art

[0002] An automated guided vehicle (AGV) is a type of transport equipment that can automatically travel along a specified path and can be guided by a variety of methods such as electromagnetic induction and laser navigation.

[0003] Traditional AGV path planning algorithms such as the Dijkstra algorithm and the A* algorithm treat the AGV as a particle during calculation, without considering the driving mode of the AGV, that is, the walking action that the AGV can actually perform. This path planning method is applicable to AGVs such as laser navigation, QR code navigation and inertial navigation, because these navigation types of AGVs can detect their own position and heading during operation, and then judge whether to move forward, backward or turn according to the path points given by the path planning algorithm.

[0004] However, when the magnetic navigation AGV is running, it only knows whether it is on the magnetic stripe and whether it has scanned the ground path node such as the Radio-Frequency Identification (RFID) card. It cannot know its specific coordinate position and heading. Therefore, it is impossible to determine the action to be performed only through the path points given by the path planning algorithm, and it is impossible to realize dynamic path planning and AGV navigation. Installing position or heading sensors on the AGV will increase the structural complexity of the control system, and the operation and maintenance costs are high. Therefore, it is generally necessary to set and save the path and path node actions of the magnetic navigation AGV in advance, and call them out when needed. After completing the task, the magnetic navigation AGV needs to return to the designated parking point to wait for new tasks, which greatly reduces the flexibility and work efficiency of the magnetic navigation AGV. Summary of the invention

[0005] In view of this, the present invention provides a driving control method, device, equipment and storage medium for an automated guided vehicle to solve the problem that the existing magnetic navigation AGV path planning requires the driving path and path node actions to be set in advance, which reduces the flexibility and work efficiency of the magnetic navigation AGV.

[0006] In a first aspect, the present invention provides a driving control method for an automatic guided vehicle, the method comprising:

[0007] Obtain the topological map and the initial node of the automated guided vehicle, the initial orientation of the vehicle head, and the target node;

[0008] Determine a set of path nodes for the automated guided vehicle to travel from an initial node to a target node in a topological map;

[0009] According to the initial orientation and the path attributes of the topological map, the target action that the automated guided vehicle needs to perform at each path node is determined. The target action is used to adjust the head orientation of the automated guided vehicle.

[0010] According to the set of path nodes and the target action corresponding to each path node, the automatic guided vehicle is controlled to travel to the target node.

[0011] Beneficial effect: The present invention first plans the set of path nodes that the automatic guided vehicle passes through from the initial node to the target node, and then combines the initial orientation of the automatic guided vehicle and the path attributes of the topological map to analyze the target action that the automatic guided vehicle needs to perform when reaching each path node, so as to adjust the orientation of the vehicle head and then drive to the next path node. In this way, dynamic path planning of magnetic navigation automatic guided vehicles can be realized, without setting the driving path and executing actions in advance, with a wider range of application scenarios, which is conducive to improving the working efficiency and flexibility of automatic guided vehicles.

[0012] In some optional implementations, determining the target action to be performed by the automated guided vehicle at each path node according to the initial orientation and the path attributes of the topological map includes:

[0013] For each path node in the path node collection, do the following:

[0014] Determine the vehicle head direction at the current path node; wherein, if the current path node is an initial node, the vehicle head direction at the current path node is the initial direction;

[0015] According to the path attributes of the topological map, determine the path type and path direction of the path segment between the current path node and the next path node; wherein the path type is a straight line path or an arc path;

[0016] According to the vehicle head orientation and the path direction, and in accordance with the target calculation method corresponding to the path type, the preliminary vehicle head orientation and the target action that the automatic guided vehicle needs to perform at the current path node are determined; wherein the preliminary vehicle head orientation is the vehicle head orientation at the next path node.

[0017] Beneficial effects: The present invention determines, for each path node, what kind of target action the automated guided vehicle needs to perform in combination with the current vehicle head orientation, the path type and path direction of the path segment to be traveled, so as to adjust the vehicle head orientation to an angle consistent with the path direction, thereby being able to travel along the corresponding path segment to the next path node, thereby realizing dynamic path planning and improving the working efficiency of the automated guided vehicle.

[0018] In some optional implementations, when the path type of the path segment is a straight path, the preliminary vehicle head orientation and the target action to be performed by the automated guided vehicle at the current path node are determined according to the vehicle head orientation and the path direction and in accordance with the target calculation method corresponding to the path type, including:

[0019] The vehicle head direction and the path direction are numerically converted to obtain a vehicle head direction value and a path direction value, and the difference between the direction values ​​of the vehicle head direction value and the path direction value is calculated;

[0020] According to the preset first mapping relationship, a target action corresponding to the difference in the direction value is obtained; wherein the target action is one of the following items: forward, backward, left rotation, right rotation, and no action is performed;

[0021] The preparation vehicle head direction is determined according to the type of target action, vehicle head direction and path direction.

[0022] Beneficial effect: For each path node, the present invention calculates the difference in direction value between the current head orientation of the automatic guided vehicle and the path direction, and combines the first mapping relationship to determine the target action corresponding to the difference in direction value, so that the automatic guided vehicle executes the target action to adjust the head orientation to an angle consistent with the path direction, and then can travel along the corresponding path segment to the next path node, thereby realizing dynamic path planning.

[0023] In some optional implementations, determining the preliminary vehicle head direction according to the type of the target action, the vehicle head direction and the path direction includes:

[0024] If the target action is detected to be a left turn or a right turn, the path direction is used as the preparatory vehicle head direction;

[0025] If the target action is not detected as a left turn or a right turn, the vehicle head orientation is used as a preliminary vehicle head orientation.

[0026] Beneficial effect: When the present invention detects that the automatic guided vehicle needs to perform a rotation action to adjust the current vehicle head orientation, the path direction of the corresponding path segment is used as the preliminary vehicle head orientation, that is, the vehicle head orientation when the automatic guided vehicle travels to the next path node; otherwise, the current vehicle head orientation is used as the preliminary vehicle head orientation to facilitate entering the next recursive process, thereby determining the target action to be performed at the next path node.

[0027] In some optional implementations, when the path type of the path segment is an arc path, the preliminary vehicle head orientation and the target action to be performed by the automated guided vehicle at the current path node are determined according to the vehicle head orientation and the path direction and in accordance with the target calculation method corresponding to the path type, including:

[0028] Determine that the target action to be performed by the automated guided vehicle at the current path node is a non-execution action;

[0029] The vehicle head direction and the path direction are numerically converted to obtain a vehicle head direction value and a path direction value, and the sum of the direction values ​​between the vehicle head direction value and the path direction value is calculated;

[0030] According to the preset second mapping relationship, the preliminary vehicle head orientation corresponding to the sum of the direction values ​​is obtained.

[0031] Beneficial effect: When the automatic guided vehicle of the present invention is about to travel along an arc path, no action needs to be performed. In addition, according to the sum of the current vehicle head orientation value and the path direction value of the corresponding arc path segment, the vehicle head orientation after the automatic guided vehicle travels along the corresponding path segment, i.e., the preliminary vehicle head orientation, is determined according to the second mapping relationship, so as to facilitate entering the next recursive process, thereby determining the target action to be performed at the next path node.

[0032] In some optional implementations, determining a set of path nodes for an automated guided vehicle to travel from an initial node to a target node in a topological map includes:

[0033] Path planning is performed based on the topological map, initial nodes, and target nodes to obtain multiple driving paths;

[0034] Calculate the weight of each driving path according to the path attributes of the topological map, and select a target driving path from multiple driving paths based on the weight;

[0035] According to the path nodes of the target driving path, a set of path nodes arranged in order is obtained.

[0036] Beneficial effect: The present invention determines the target driving path of the automatic guided vehicle from the initial node to the target node through path planning and path screening, which is beneficial to saving transportation time and improving work efficiency. Then, the order in which the automatic guided vehicle needs to pass through the path nodes is analyzed, and a set of path nodes arranged in sequence is obtained, so that the automatic guided vehicle can adjust the direction of the front of the vehicle at the corresponding path node, thereby changing the driving direction.

[0037] In some optional implementations, according to the set of path nodes and the target action corresponding to each path node, controlling the automatic guided vehicle to travel to the target node includes:

[0038] The path node set and the target action corresponding to each path node are sent to the automatic guided vehicle, so that the automatic guided vehicle drives to each path node in sequence according to the path node set, and performs the corresponding target action after driving to each path node.

[0039] Beneficial effects: The present invention combines the target action with the path node and sends it to the automatic guided vehicle. After the automatic guided vehicle reaches a path node according to the planned path, it executes the corresponding target action to adjust its own front direction, and then drives to the next path node, thereby realizing dynamic path planning of the automatic guided vehicle.

[0040] In a second aspect, the present invention provides a travel control device for an automatic guided vehicle, the device comprising:

[0041] The acquisition module is used to obtain the topological map and the initial node of the automatic guided vehicle, the initial orientation of the vehicle head, and the target node;

[0042] The first processing module is used to determine a set of path nodes for the automatic guided vehicle to travel from an initial node to a target node in a topological map;

[0043] The second processing module is used to determine the target action that the automatic guided vehicle needs to perform at each path node according to the initial orientation and the path attribute of the topological map, and the target action is used to adjust the head orientation of the automatic guided vehicle;

[0044] The third processing module is used to control the automatic guided vehicle to travel to the target node according to the path node set and the target action corresponding to each path node.

[0045] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the driving control method of an automatic guided vehicle according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0046] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the driving control method for an automatic guided vehicle according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0048] Figure 1 is a flow chart of a driving control method of an automatic guided vehicle according to an embodiment of the present invention;

[0049] Figure 2is a flow chart of another driving control method of an automatic guided vehicle according to an embodiment of the present invention;

[0050] Figure 3 is a schematic diagram of attributes of a path segment according to an embodiment of the present invention;

[0051] Figure 4 is a flow chart of another driving control method of an automatic guided vehicle according to an embodiment of the present invention;

[0052] Figure 5 is a schematic diagram of a topological map according to an embodiment of the present invention;

[0053] Figure 6 is a structural block diagram of a travel control device for an automatic guided vehicle according to an embodiment of the present invention;

[0054] Figure 7 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0056] Traditional path planning algorithms such as Dijkstra algorithm and A* algorithm are applicable to AGVs such as laser navigation, QR code navigation and inertial navigation, because these types of navigation AGVs can detect their own position and heading during operation. However, magnetic navigation AGVs only know whether they are on the magnetic stripe and whether they scan the ground path nodes such as RFID cards during operation, so they cannot turn, move forward, or move backward only through the path points given by the path planning algorithm.

[0057] At present, it is generally necessary to set and save the path and path node actions of the magnetic navigation AGV in advance, and call them out for use when needed. In addition, the magnetic navigation AGV needs to return to the designated parking point after completing the task and wait for new tasks. This greatly reduces the flexibility and work efficiency of the magnetic navigation AGV.

[0058] Therefore, an embodiment of the present invention provides a driving control method for an automated guided vehicle, which first plans a set of path nodes that the AGV passes through from the initial node to the target node, and then analyzes the target action that the AGV needs to perform when it reaches each path node in combination with the initial orientation of the AGV and the path attributes of the topological map, such as path type and path direction, so as to adjust the orientation of the vehicle head and then drive to the next path node. In this way, the dynamic planning of the magnetic navigation AGV path can be realized, without presetting the driving path and execution action of the AGV in advance, which is conducive to improving the working efficiency and flexibility of the magnetic navigation AGV.

[0059] According to an embodiment of the present invention, an embodiment of a driving control method for an automated guided vehicle is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0060] In this embodiment, a driving control method for an automated guided vehicle is provided, which can be used for computer devices such as mobile phones, computers, etc. for magnetic navigation AGV planning. Figure 1 is a flow chart of a driving control method for an automatic guided vehicle according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0061] Step S101, obtaining a topological map and an initial node of the automatic guided vehicle, an initial orientation of the vehicle head, and a target node.

[0062] Specifically, the topological map is extracted based on the park environment where the AGV car works. The embodiment of the present invention performs path planning based on the topological map. There are several path nodes in the topological map, and these path nodes are connected by path segments to form a topological map. In the present invention, in addition to the basic attributes (including starting and ending points, weights) of the path segment of the topological map, a direction attribute is added to characterize the path direction of the path segment. In other words, the topological map in this embodiment is a directed graph in which each edge has only one direction. For example, there is an edge from node A to node B, which means that it is possible to reach B from A. If there is an actual path segment that directly reaches A from B, it is necessary to reset an edge from B to A.

[0063] In some optional embodiments, when determining the starting point required for path planning, the initial node where the magnetic navigation AGV is located can be determined by obtaining the RFID card read by the AGV. The RFID card is a smart card that uses radio frequency identification technology to store and transmit data. When the RFID card enters the magnetic field range of the AGV, the antenna on the card will receive the radio frequency signal emitted by the AGV. Through the principle of electromagnetic induction, the RFID card uses the energy of the radio frequency signal to activate itself and send the identification data stored in its own path node to the AGV, which then uploads it to the device for path planning. In addition, the target node that the AGV needs to reach can be determined based on the execution task of the AGV.

[0064] Step S102, determining a set of path nodes for the automated guided vehicle to travel from an initial node to a target node in a topological map.

[0065] Specifically, after obtaining the initial node, target node and topological map of the AGV, the path node set from the initial node to the target node of the AGV is calculated through conventional path planning algorithms such as the A* algorithm and the Dijkstra algorithm. This path planning process does not need to consider the direction of the AGV, that is, the action that the AGV needs to perform, but only treats the AGV as a particle for path planning.

[0066] Step S103, determining the target action that the automated guided vehicle needs to perform at each path node according to the initial orientation and the path attributes of the topological map, where the target action is used to adjust the head orientation of the automated guided vehicle.

[0067] Specifically, the AGV travels in the direction consistent with the vehicle head direction. If the path direction of the path segment that the AGV is about to travel is inconsistent with the vehicle head direction at this time, since the AGV itself does not have the heading perception function, it is difficult to adjust the vehicle head direction by itself. Therefore, it is necessary to set a series of walking actions that the AGV can perform according to the characteristics of the AGV's own driving mode. These actions are mainly used to combine with the path nodes so that the AGV can adjust its own vehicle head direction to facilitate driving to the next path node.

[0068] Step S104, controlling the automatic guided vehicle to travel to the target node according to the path node set and the target action corresponding to each path node.

[0069] Specifically, the path node set and the target action corresponding to each path node are sent to the automatic guided vehicle, so that the automatic guided vehicle drives to each path node in sequence according to the path node set, and performs the corresponding target action after driving to each path node.

[0070] The present invention combines the target action with the path node and sends it to the AGV car, so that after the AGV car reaches a path node according to the planned path, it executes the corresponding target action to adjust its own head direction, and then drives to the next path node, realizing the dynamic path planning of the AGV.

[0071] The driving control method of the automatic guided vehicle provided in this embodiment first plans a set of path nodes that the automatic guided vehicle passes through from the initial node to the target node, and then analyzes the target action that the automatic guided vehicle needs to perform when reaching each path node in combination with the initial orientation of the automatic guided vehicle and the path attributes of the topological map, so as to adjust the orientation of the vehicle head and then drive to the next path node. In this way, dynamic path planning of the magnetic navigation automatic guided vehicle can be realized, without setting the driving path and executing actions in advance, and the application scenarios are more extensive, which is conducive to improving the working efficiency and flexibility of the automatic guided vehicle.

[0072] In this embodiment, a driving control method for an automated guided vehicle is provided, which can be used for computer devices such as mobile phones, computers, etc. for magnetic navigation AGV planning. Figure 2 is a flow chart of a driving control method for an automatic guided vehicle according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0073] Step S201, obtain the topological map and the initial node of the automatic guided vehicle, the initial orientation of the vehicle head and the target node. Figure 1 Step S101 of the illustrated embodiment will not be described in detail here.

[0074] Step S202, determining a set of path nodes for the automated guided vehicle to travel from an initial node to a target node in a topological map.

[0075] Specifically, the above step S202 includes:

[0076] Step S2021, performing path planning according to the topological map, the initial node and the target node to obtain multiple driving paths.

[0077] Specifically, the A* algorithm and the Dijkstra algorithm can be used for path planning to obtain multiple driving paths. The detailed calculation process can be found in the specific description of the relevant technology, which will not be repeated here.

[0078] Step S2022, calculating the weight of each driving path according to the path attributes of the topological map, and filtering out a target driving path from multiple driving paths based on the weight.

[0079] Specifically, each path segment in the topological map has a weight attribute, which can be set based on comprehensive considerations such as the length of the path segment and the path type. The weighted sum of each path segment in the driving path is performed to obtain the score of each driving path, and the driving path with the largest score is taken as the target driving path.

[0080] Step S2023, obtaining a set of path nodes arranged in order according to the path nodes of the target driving path.

[0081] Specifically, according to the path direction of the path segment of the target driving path, the order in which the AGV needs to pass through the path nodes is determined to obtain a set of path nodes arranged in order.

[0082] The present invention determines the target driving path of the AGV from the initial node to the target node through path planning and path screening, which is conducive to saving transportation time and improving work efficiency. Then the order in which the AGV needs to pass through the path nodes is analyzed, and then a set of path nodes arranged in sequence is obtained, so that the AGV can adjust the direction of the head at the corresponding path node, thereby changing the driving direction.

[0083] Step S203, determining the target action that the automated guided vehicle needs to perform at each path node according to the initial orientation and the path attributes of the topological map, where the target action is used to adjust the head orientation of the automated guided vehicle.

[0084] Specifically, for each path node in the path node set, the above step S203 includes:

[0085] Step S2031, determining the vehicle head orientation at the current path node; wherein, if the current path node is an initial node, the vehicle head orientation at the current path node is the initial orientation.

[0086] Specifically, due to the limitation of specifications and design efficiency, the track map of the AGV working environment is relatively regular. The track map is usually composed of arc paths and straight paths. When drawing the topological map, the corresponding path direction is added to each edge according to the actual situation. Figure 3 As shown, for a straight path, there are four types of path directions, namely east, south, west, and north, and the corresponding values ​​(in degrees) are 0 / 360, 90, 180, 270 / -90 respectively; and for an arc path (quarter circle), there are two types of path directions: left and right, and the corresponding values ​​are -90 and 90 respectively.

[0087] Accordingly, the setting of the AGV's head direction should be consistent with the path segment setting, so that when the difference of the direction values ​​and the sum of the direction values ​​are calculated later, the subsequent calculation results can be guaranteed to be consistent with the actual meaning. Figure 3Corresponding to the path direction shown, the setting of the AGV head direction is shown in Table 1 below:

[0088] Table 1 AGV head orientation and its numerical correspondence

[0089]

[0090]

[0091] In this embodiment, the path nodes on the topological map have attributes such as "AGV head direction", "AGV preparatory head direction", and "target action performed by the node", and the values ​​of these attributes are not fixed, but dynamically assigned according to the planning method of the present invention. When determining the target action and preparatory head direction of each path node, the initial node needs to be recursive. The head direction of the initial node is also the initial direction, which can be pre-set and adjusted or use the previously recorded and stored head direction.

[0092] Step S2032: Determine the path type and path direction of the path segment between the current path node and the next path node according to the path attributes of the topology map.

[0093] In some optional embodiments, see again Figure 3 The path types of path segments mainly include straight path and arc path. The straight path has four types of path directions, namely east, south, west, and north, and the corresponding values ​​are 0 / 360, 90, 180, and 270 / -90 respectively; the arc path has two types of path directions, left and right, and the corresponding values ​​are -90 and 90 respectively.

[0094] Step S2033, according to the vehicle head orientation and the path direction, and in accordance with the target calculation method corresponding to the path type, determine the preliminary vehicle head orientation and the target action that the automatic guided vehicle needs to perform at the current path node; wherein the preliminary vehicle head orientation is the vehicle head orientation at the next path node.

[0095] In some optional implementations, when the path type of the path segment is a straight path, the above step S2033 includes:

[0096] Step a1, converting the vehicle head direction and the path direction into numerical values ​​to obtain the vehicle head direction value and the path direction value, and calculating the difference between the direction values ​​of the vehicle head direction value and the path direction value.

[0097] For example, according to the corresponding relationship shown in Table 1, the value corresponding to the vehicle head orientation is determined to obtain the vehicle head orientation value; according to Figure 3 The corresponding relationship shown is used to obtain the path direction value corresponding to the path direction, and then the difference in direction value between the vehicle head direction value and the path direction value is calculated.

[0098] Step a2: obtaining a target action corresponding to the difference in direction values ​​according to a preset first mapping relationship.

[0099] In some optional embodiments, see again Figure 3 According to the driving characteristics of the AGV itself and the map characteristics, a series of walking actions that the AGV can execute are set, which are mainly used to combine with the path nodes and are sent to the AGV for execution. This embodiment takes the dual-steering wheel drive AGV as an example. According to the characteristics of the dual-steering wheel drive, the walking actions that the AGV can execute are set as shown in Table 2:

[0100] Table 2 List of walking actions that AGV can perform

[0101] serial number action 0 none 1 go ahead 2 Back 3 Rotate Left 4 Rotate Right

[0102] From Table 2 above, it can be seen that the target action of the AGV is one of the following: forward, backward, left rotation, right rotation, and no action. Further, according to the first mapping relationship, the target action corresponding to the difference in direction value is obtained, and the first mapping relationship is shown in Table 3 below:

[0103] Table 3 Correspondence between the difference in direction values ​​and the actions performed by AGV

[0104] Difference action 0 go ahead 90 Rotate Right -90 Rotate Left 180 Back -180 Back

[0105] Step a3, determining the preliminary vehicle head direction according to the type of the target action, the vehicle head direction and the path direction. Figure 3 If the target action is detected as a left rotation or a right rotation, the path direction is used as the preliminary vehicle head orientation; if the target action is not detected as a left rotation or a right rotation, the vehicle head orientation is used as the preliminary vehicle head orientation.

[0106] When the present invention detects that the AGV needs to perform a rotation action to adjust the current vehicle head orientation, the path direction of the corresponding path segment is used as the preliminary vehicle head orientation, that is, the vehicle head orientation when the AGV travels to the next path node; otherwise, the current vehicle head orientation is used as the preliminary vehicle head orientation to facilitate entering the next recursive process, thereby determining the target action to be performed at the next path node.

[0107] In an embodiment of the present invention, for each path node, the difference in direction value between the current head orientation of the AGV and the path direction is calculated, and combined with the first mapping relationship, the target action corresponding to the difference in direction value is determined, so that the AGV executes the target action to adjust the head orientation to an angle consistent with the path direction, and then can travel along the corresponding path segment to the next path node, thereby realizing dynamic path planning.

[0108] In some optional implementations, when the path type of the path segment is an arc path, the above step S2033 includes:

[0109] Step b1, determining that the target action to be performed by the automated guided vehicle at the current path node is a non-execution action.

[0110] For example, see again Figure 3 ,When AGV travels on an arc path, due to the influence of the curvature of the path, the AGV can travel along the corresponding path segment without performing an action. That is, if the path type of the path segment is an arc path, the action of the current path node is "none".

[0111] Step b2, converting the vehicle head orientation and the path direction into numerical values ​​to obtain the vehicle head orientation value and the path direction value, and calculating the sum of the direction values ​​between the vehicle head orientation value and the path direction value.

[0112] For example, see again Figure 3 As well as Table 1, the query obtains the vehicle head orientation value and the path direction value, and calculates the sum of the direction values.

[0113] Step b3: obtaining a preliminary vehicle head orientation corresponding to the sum of the direction values ​​according to a preset second mapping relationship.

[0114] Exemplarily, the second mapping relationship is the reverse mapping of the vehicle head orientation and numerical correspondence shown in Table 1, and the sum of the direction values ​​represents the vehicle head orientation after the AGV travels along the corresponding path segment. That is to say, by reversely searching the vehicle head orientation corresponding to the sum of the direction values ​​in Table 2, the preliminary vehicle head orientation can be obtained.

[0115] When the AGV of the present invention is about to travel along an arc path, there is no need to perform an action to adjust the vehicle head orientation. In addition, according to the sum of the current vehicle head orientation value and the path direction value of the corresponding arc path segment, the vehicle head orientation after the AGV travels along the corresponding path segment, i.e., the preliminary vehicle head orientation, is determined according to the second mapping relationship, so as to enter the next recursive process, thereby determining the target action to be performed at the next path node.

[0116] It should be noted that the mapping relationship between the target action, the difference in direction value and the target action, etc., exemplified in this embodiment is only an example. It is easy to imagine that in other embodiments, the topological map can be more complex, for example, it can also include oblique path segments such as northeast, southeast, northwest, and southwest. Then the head direction of the AGV can also add northeast, southeast, northwest, southwest and other directions on the original basis, as long as it corresponds to the path direction of the path segment. Furthermore, the corresponding target action can be set according to the path direction and the head direction, for example, a 45-degree left turn, a 45-degree right turn, etc. can be added, as long as it can cover all possible turns, and the embodiments of the present invention are not limited to this.

[0117] In an embodiment of the present invention, for each path node, the current vehicle head orientation, the path type and path direction of the path segment to be traveled are combined to determine which target action the AGV needs to perform, so as to adjust the vehicle head orientation to an angle consistent with the path direction, and ensure that the AGV can travel along the corresponding path segment to the next path node, thereby realizing dynamic path planning and improving the working efficiency of the AGV.

[0118] Step S204: According to the path node set and the target action corresponding to each path node, the automatic guided vehicle is controlled to travel to the target node. Figure 1 Step S104 of the illustrated embodiment will not be described in detail here.

[0119] The driving control method of the automatic guided vehicle provided in this embodiment describes the dynamic path planning process of the magnetic navigation AGV, which can solve the problem that the traditional path planning algorithm cannot be directly applied to the magnetic navigation AGV, realizes the dynamic planning of the magnetic navigation AGV path, and is conducive to improving the working efficiency and flexibility of the magnetic navigation AGV.

[0120] Below Figure 3 The path setting and the magnetic navigation AGV shown are taken as a dual-steering wheel driven AGV as an example, and the driving control method of the automatic guided vehicle of the present invention is described in detail in combination with a specific application example.

[0121] like Figure 4 As shown in the figure, we first need to know the initial direction and initial node of the AGV, and then use conventional path planning algorithms such as A*, Dijkstra, etc. to calculate the path node set from the AGV initial node to the target node. This process does not need to consider the AGV direction and execution action, and only treats the AGV as a particle. Then traverse the path node set in order, the steps are as follows:

[0122] Step 1: If the current path node is the AGV initial node, the initial orientation of the AGV is used as the AGV head orientation of this node;

[0123] Step 2: If the current path node is neither the AGV initial node nor the target node, the AGV preparatory head direction of the previous path node is used as the AGV head direction of the current path node.

[0124] Step 3, find the corresponding path segment in the map through the next path node of the current path node, and determine the path type of the path segment. If the path type is an arc path, jump to step 4, otherwise jump to step 5;

[0125] Step 4: If the path segment is an arc path, set the AGV target action of the current path node to "do not perform action" and calculate the AGV preparatory head direction value of the current path node:

[0126] AGV preparation head direction value = AGV head direction value + arc path segment direction value

[0127] After obtaining the AGV preparatory vehicle head orientation value, search for the corresponding vehicle head orientation according to Table 1, and set the AGV preparatory vehicle head orientation of the current path node to the corresponding vehicle head orientation;

[0128] Step 5: If the path segment is a straight path, calculate the difference between the AGV head orientation of the current path node and the path segment direction value, find the corresponding AGV target action (Table 3) according to the direction value difference, and assign the target action to the current path node. Next, determine whether the target action of the current path node is "rotate left" or "rotate right". If so, set the AGV preparatory head orientation of the current path node to the direction of the path segment. If not, set the AGV preparatory head orientation of the current path node to be consistent with the AGV head orientation of the current path node.

[0129] Repeat the above steps until the target node is traversed. When the AGV actually walks to the target node according to the planned path, the AGV orientation at this time can be used as a reference for the next path planning calculation.

[0130] for Figure 5 Taking the topological map shown in the figure as an example, assuming that the initial node of the AGV is 1 and the initial direction is east, the path planning method described in the above process can obtain the following results:

[0131] Table 4

[0132] node AGV direction AGV preparation direction Node Actions 1 East East go ahead 2 East South Rotate Right 3 South East Rotate Left 4 East north none 5 north north none 6 north —— none

[0133] The present invention performs path planning based on the topological map, adds directions such as "east, south, west, north, left, right" to each edge of the topological map, and only needs to set the initial orientation of the AGV head during initialization (east, south, west, north in the real environment), and then the path nodes and the actions that the AGV needs to perform at the nodes can be planned according to the map, so that the AGV can achieve navigation. At the same time, the present invention can calculate the direction of the head of the AGV at each path node. When the AGV reaches the path node, the current orientation of the AGV is recorded based on this, and this is used as the basis for the next path planning, without setting the initial orientation of the AGV multiple times.

[0134] In the present embodiment, a driving control device for an automated guided vehicle is also provided, and the device is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0135] This embodiment provides a driving control device for an automatic guided vehicle, such as Figure 6 As shown, including:

[0136] The acquisition module 601 is used to acquire the topological map and the initial node of the automatic guided vehicle, the initial orientation of the vehicle head, and the target node;

[0137] The first processing module 602 is used to determine a set of path nodes for the automated guided vehicle to travel from an initial node to a target node in a topological map;

[0138] The second processing module 603 is used to determine the target action that the automated guided vehicle needs to perform at each path node according to the initial orientation and the path attributes of the topological map, and the target action is used to adjust the head orientation of the automated guided vehicle;

[0139] The third processing module 604 is used to control the automatic guided vehicle to travel to the target node according to the path node set and the target action corresponding to each path node.

[0140] In some optional implementations, the first processing module 602 is further configured to:

[0141] Path planning is performed based on the topological map, initial nodes, and target nodes to obtain multiple driving paths;

[0142] Calculate the weight of each driving path according to the path attributes of the topological map, and select a target driving path from multiple driving paths based on the weight;

[0143] According to the path nodes of the target driving path, a set of path nodes arranged in order is obtained.

[0144] In some optional implementations, the second processing module 603 is further configured to:

[0145] For each path node in the path node collection, do the following:

[0146] Determine the vehicle head direction at the current path node; wherein, if the current path node is an initial node, the vehicle head direction at the current path node is the initial direction;

[0147] According to the path attributes of the topological map, determine the path type and path direction of the path segment between the current path node and the next path node; wherein the path type is a straight line path or an arc path;

[0148] According to the vehicle head orientation and the path direction, and in accordance with the target calculation method corresponding to the path type, the preliminary vehicle head orientation and the target action that the automatic guided vehicle needs to perform at the current path node are determined; wherein the preliminary vehicle head orientation is the vehicle head orientation at the next path node.

[0149] In some optional implementations, when the path type of the path segment is a straight path, the second processing module 603 is further configured to:

[0150] The vehicle head direction and the path direction are numerically converted to obtain a vehicle head direction value and a path direction value, and the difference between the direction values ​​of the vehicle head direction value and the path direction value is calculated;

[0151] According to the preset first mapping relationship, a target action corresponding to the difference in the direction value is obtained; wherein the target action is one of the following items: forward, backward, left rotation, right rotation, and no action is performed;

[0152] The preparation vehicle head direction is determined according to the type of target action, vehicle head direction and path direction.

[0153] In some optional implementations, the second processing module 603 is further configured to:

[0154] If the target action is detected to be a left turn or a right turn, the path direction is used as the preparatory vehicle head direction;

[0155] If the target action is not detected as a left turn or a right turn, the vehicle head orientation is used as a preliminary vehicle head orientation.

[0156] In some optional implementations, when the path type of the path segment is an arc path, the second processing module 603 is further configured to:

[0157] Determine that the target action to be performed by the automated guided vehicle at the current path node is a non-execution action;

[0158] The vehicle head direction and the path direction are numerically converted to obtain a vehicle head direction value and a path direction value, and the sum of the direction values ​​between the vehicle head direction value and the path direction value is calculated;

[0159] According to the preset second mapping relationship, the preliminary vehicle head orientation corresponding to the sum of the direction values ​​is obtained.

[0160] In some optional implementations, the third processing module 604 is further configured to:

[0161] The path node set and the target action corresponding to each path node are sent to the automatic guided vehicle, so that the automatic guided vehicle drives to each path node in sequence according to the path node set, and performs the corresponding target action after driving to each path node.

[0162] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0163] The driving control device of the automatic guided vehicle in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0164] The embodiment of the present invention also provides a computer device having the above Figure 6 A travel control device for an automated guided vehicle is shown.

[0165] See also Figure 7 , Figure 7 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 7 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 7 A processor 10 is taken as an example.

[0166] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0167] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0168] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0169] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0170] The computer device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 7 The example of connecting through bus is taken in the following.

[0171] The input device 30 can receive input digital or character information, and generate key signal input related to the user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator bar, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0172] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0173] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0174] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A driving control method for an automatic guided vehicle, characterized in that: The method comprises: Obtain the topological map and the initial node of the automated guided vehicle, the initial orientation of the vehicle head, and the target node; Determine a set of path nodes for the automated guided vehicle to travel from an initial node to a target node in a topological map; According to the initial orientation and the path attributes of the topological map, the target action that the automated guided vehicle needs to perform at each path node is determined. The target action is used to adjust the head orientation of the automated guided vehicle. According to the set of path nodes and the target action corresponding to each path node, the automatic guided vehicle is controlled to travel to the target node.

2. The method according to claim 1, characterized in that The step of determining the target action to be performed by the automated guided vehicle at each path node according to the initial orientation and the path attributes of the topological map includes: For each path node in the path node collection, do the following: Determine the vehicle head direction at the current path node; wherein, if the current path node is an initial node, the vehicle head direction at the current path node is the initial direction; According to the path attributes of the topological map, determine the path type and path direction of the path segment between the current path node and the next path node; wherein the path type is a straight line path or an arc path; According to the vehicle head orientation and the path direction, and in accordance with the target calculation method corresponding to the path type, the preliminary vehicle head orientation and the target action to be performed by the automatic guided vehicle at the current path node are determined; wherein the preliminary vehicle head orientation is the vehicle head orientation at the next path node.

3. The method according to claim 2, characterized in that When the path type of the path segment is a straight path, the step of determining the preliminary vehicle head orientation and the target action to be performed by the automated guided vehicle at the current path node according to the vehicle head orientation and the path direction and in accordance with the target calculation method corresponding to the path type includes: The vehicle head direction and the path direction are numerically converted to obtain a vehicle head direction value and a path direction value, and the difference between the direction values ​​of the vehicle head direction value and the path direction value is calculated; According to the preset first mapping relationship, a target action corresponding to the difference in the direction value is obtained; wherein the target action is one of the following items: forward, backward, left rotation, right rotation, and no action is performed; The preparation vehicle head direction is determined according to the type of target action, the vehicle head direction and the path direction.

4. The method according to claim 3, characterized in that The step of determining the preliminary vehicle head direction according to the type of the target action, the vehicle head direction and the path direction includes: If the target action is detected as a left turn or a right turn, the path direction is used as the preparatory vehicle head direction; If the target action is not detected as a left turn or a right turn, the vehicle head orientation is used as a preliminary vehicle head orientation.

5. The method according to claim 2, characterized in that: When the path type of the path segment is an arc path, the step of determining the preliminary vehicle head orientation and the target action to be performed by the automated guided vehicle at the current path node according to the vehicle head orientation and the path direction and in accordance with the target calculation method corresponding to the path type includes: Determine that the target action to be performed by the automated guided vehicle at the current path node is a non-execution action; The vehicle head direction and the path direction are numerically converted to obtain a vehicle head direction value and a path direction value, and the sum of the direction values ​​between the vehicle head direction value and the path direction value is calculated; According to the preset second mapping relationship, the preliminary vehicle head orientation corresponding to the sum of the direction values ​​is obtained.

6. The method according to any one of claims 1 to 5, characterized in that The step of determining a set of path nodes for the automatic guided vehicle to travel from an initial node to a target node in a topological map includes: Path planning is performed based on the topological map, initial nodes, and target nodes to obtain multiple driving paths; Calculating the weight of each driving path according to the path attributes of the topological map, and filtering out a target driving path from multiple driving paths based on the weight; According to the path nodes of the target driving path, a set of path nodes arranged in order is obtained.

7. The method according to any one of claims 1 to 5, characterized in that The method of controlling the automatic guided vehicle to travel to the target node according to the set of path nodes and the target action corresponding to each path node includes: The path node set and the target action corresponding to each path node are sent to the automatic guided vehicle, so that the automatic guided vehicle drives to each path node in sequence according to the path node set, and performs the corresponding target action after driving to each path node.

8. A driving control device for an automatic guided vehicle, characterized in that: The device comprises: The acquisition module is used to obtain the topological map and the initial node of the automatic guided vehicle, the initial orientation of the vehicle head, and the target node; The first processing module is used to determine a set of path nodes for the automatic guided vehicle to travel from an initial node to a target node in a topological map; The second processing module is used to determine the target action that the automatic guided vehicle needs to perform at each path node according to the initial orientation and the path attribute of the topological map, and the target action is used to adjust the head orientation of the automatic guided vehicle; The third processing module is used to control the automatic guided vehicle to travel to the target node according to the path node set and the target action corresponding to each path node.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the driving control method of the automatic guided vehicle according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the driving control method of an automated guided vehicle according to any one of claims 1 to 7.

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