CN113418522B - AGV path planning method, following method, device, equipment and storage medium - Google Patents
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Abstract
The invention discloses an AGV path planning method, a following device, equipment and a storage medium, wherein the planning method comprises the following steps: acquiring an SLAM map, and setting an AGV following path and a navigation terminal point on the SLAM map according to operation requirements; extracting a following path, setting the road width, expanding the following path by the road width to form an initial virtual road, and acquiring a virtual road map corresponding to the SLAM map specification based on the initial virtual road; superposing the SLAM map and the virtual road map, reducing the barrier area in the SLAM map by the initial virtual road of the virtual road map, and acquiring the final virtual road; the planning method obtains an initial virtual road in a virtual road map based on following path expansion, superposes the SLAM map and the virtual road map to obtain a final virtual road for the AGV to travel, and limits the travel area of the AGV by using the final virtual road so that the AGV can carry out obstacle avoidance navigation following movement in a limited area, thereby improving the reliability and the safety of the AGV obstacle avoidance navigation.
Description
Technical Field
The application relates to the technical field of robot navigation, in particular to an AGV path planning method, a following method, a device, equipment and a storage medium.
Background
An agv (automated Guided vehicle) is a transportation device equipped with an electromagnetic or other sensing sensor, which can travel along a specified path after being programmed and set, and can realize the functions of stopping at a specific position, transporting materials or moving a mechanical arm, and is widely used in industry.
The traditional AGV adopts magnetic stripe navigation and color bar navigation, the running path of the navigation method is fixed and reliable, but the navigation method lacks flexibility, the magnetic stripe and the color bar need to be changed when the transportation path is changed, and the navigation method does not have the function of bypassing dynamic obstacles.
Therefore, the AGV also adopts the laser navigation to perform obstacle avoidance navigation, and in the current common laser navigation method, the optimization path is often not fixed, if not limited, when an uncertain dynamic obstacle is encountered, the obstacle avoidance path of the AGV cannot be estimated, so that the AGV travels to a dangerous area, and the control of a factory is not facilitated.
In view of the above problems, no effective technical solution exists at present.
Disclosure of Invention
An object of the embodiments of the present application is to provide an AGV path planning method, a following method, an apparatus, a device, and a storage medium, which avoid that an AGV obstacle avoidance path cannot be estimated and thus the AGV obstacle avoidance path travels to a dangerous area, thereby improving reliability and safety of AGV obstacle avoidance navigation.
In a first aspect, an embodiment of the present application provides an AGV path planning method, configured to plan a following path of an AGV, where the method includes the following steps:
a1, acquiring an SLAM map, and setting an AGV following path and a navigation terminal point on the SLAM map according to operation requirements;
a2, extracting a following path, setting the road width, expanding the following path by the road width to form an initial virtual road, and acquiring a virtual road map corresponding to the SLAM map specification based on the initial virtual road;
and A3, overlapping the SLAM map and the virtual road map, reducing the obstacle area in the SLAM map on the initial virtual road of the virtual road map, and acquiring the final virtual road.
According to the AGV path planning method, after the appropriate following path is obtained on the SLAM map, the initial virtual road in the virtual road map is obtained based on expansion of the following path, the SLAM map and the virtual road map are overlaid to obtain the final virtual road capable of being driven by the AGV, the driving area of the AGV is limited by the final virtual road, so that the AGV can carry out obstacle avoidance navigation following movement in the limited area, the AGV is prevented from driving to a dangerous area due to the fact that the obstacle avoidance path cannot be estimated, and therefore reliability and safety of AGV obstacle avoidance navigation are improved.
In the AGV path planning method, in step a2, the road width is set based on the site security level.
The AGV path planning method comprises the following substeps in step A2:
a21, acquiring the specification size of the SLAM map, and generating a grid map with the same specification size as the SLAM map;
a22, extracting a following path from the SLAM map, and generating a virtual path corresponding to the position in the raster map based on the following path;
a23, setting the road width, expanding the virtual path to two sides based on the road width to form an initial virtual road, and forming the grid map into a virtual road map with the initial virtual road.
The AGV path planning method comprises the following substeps in step A3:
a31, defining the area outside the initial virtual road in the virtual road map as a virtual obstacle area;
a32, overlapping and fusing the SLAM map and the virtual road map to form an obstacle map;
and A33, acquiring an area belonging to a non-obstacle area in the initial virtual road as a final virtual road.
In a second aspect, an embodiment of the present application further provides an AGV path following method, for controlling AGV to follow displacement, including the following steps:
b1, acquiring a final virtual road in the AGV obstacle avoidance path planning method;
and B2, controlling the AGV to follow along the final virtual road to the navigation terminal.
According to the AGV path following method, the final virtual road in the AGV obstacle avoiding path planning method is obtained, AGV is controlled and limited to follow and run towards a navigation end point on the final virtual road, the AGV can be always kept near the following path in the running process of the AGV, even if obstacles occur, the obstacle can still be avoided within the range of the final virtual road, compared with the common AGV, the method guarantees the path controllability of the AGV running at every time, the AGV is prevented from moving to a dangerous area due to obstacle avoiding requirements, the moving stroke of the AGV can be limited, and the consistency of the transportation beats at every time is achieved.
In the AGV path following method, in step B2, when no obstacle exists in the final virtual road, the AGV is controlled to follow along the center of the final virtual road toward the navigation end point; when a barrier exists in the final virtual road and the barrier does not completely block the final virtual road, planning an obstacle avoiding path bypassing the barrier in the final virtual road, and controlling the AGV to follow along the obstacle avoiding path in the final virtual road towards a navigation terminal; and when the obstacle exists in the final virtual road and completely blocks the final virtual road, controlling the AGV to stop moving and enter a state of waiting for clearing the obstacle.
According to the AGV path following method, the SLAM map is an ROS standard map generated based on single line laser radar scanning, and step B2 is used for calculating a potential field based on a dijkstra algorithm of ROS to obtain an AGV displacement path so as to control the AGV to follow and run.
In a third aspect, an embodiment of the present application further provides an AGV path planning apparatus, configured to plan a following path of an AGV, including:
the obtaining module is used for setting an AGV following path and a navigation terminal point on an SLAM map according to operation requirements;
the setting module is used for setting the width of a road;
the virtual map module is used for expanding the width of the road along the following path to form an initial virtual road and acquiring a virtual road map corresponding to the SLAM map specification according to the initial virtual road;
and the superposition module is used for superposing the SLAM map and the virtual road map, so that the initial virtual road of the virtual road map reduces the obstacle area in the SLAM map, and the final virtual road is obtained.
The utility model provides a AGV path planning device, acquire SLAM map and navigation information in it based on acquisition module, utilize virtual map module to make the road width of following route inflation setting module setting for in order to acquire the initial virtual road in the virtual road map, then obtain the final virtual road that can supply AGV to travel through the stack module with SLAM map and virtual road map stack, utilize final virtual road to inject AGV's the region of traveling so that AGV keeps away barrier navigation in limited area and follows the removal, avoid AGV because of keeping away barrier route unable estimate and lead to its traveling to danger area, thereby improve AGV and keep away barrier navigation's reliability, security.
In a fourth aspect, embodiments of the present application further provide an apparatus, including a processor and a memory, where the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the apparatus performs the steps in the method as provided in the first aspect.
In a fifth aspect, embodiments of the present application further provide a storage medium, on which a computer program is stored, where the computer program runs the steps in the method provided in the above first aspect when executed by a processor.
Therefore, the AGV path planning method, the following method, the device, the equipment and the storage medium are provided, wherein the planning method obtains an initial virtual road in a virtual road map based on following path expansion, superposes the SLAM map and the virtual road map to obtain a final virtual road for the AGV to travel, and limits a travel area of the AGV by using the final virtual road to enable the AGV to carry out obstacle avoidance navigation following movement in a limited area, so that the condition that the AGV travels to a dangerous area due to the fact that the obstacle avoidance path can not be estimated is avoided, and reliability and safety of the AGV obstacle avoidance navigation are improved.
Drawings
Fig. 1 is a flowchart of an AGV path planning method according to an embodiment of the present disclosure.
Fig. 2 is a schematic structural view of a SLAM map and an obstacle map.
Fig. 3 is a flowchart of an AGV path following method according to an embodiment of the present disclosure.
Fig. 4 is a schematic structural diagram of an AGV path planning apparatus according to an embodiment of the present application.
Fig. 5 is a schematic structural diagram of an apparatus provided in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
In a first aspect, please refer to fig. 1-2, where fig. 1-2 are a method for planning an AGV path according to some embodiments of the present application, the method includes the following steps:
a1, acquiring an SLAM map, and setting an AGV following path and a navigation terminal point on the SLAM map according to operation requirements;
specifically, an Automated Guided Vehicle (AGV), also commonly referred to as an AGV cart, is a transport Vehicle equipped with an electromagnetic or optical automatic navigation device, capable of traveling along a predetermined navigation path, and having safety protection and various transfer functions.
Specifically, the SLAM map is a standard map generated by scanning the working environment with the laser radar, and reflects an obstacle area where an obstacle exists in the working environment and a safe area through which the AGV can travel.
More specifically, the current position of the AGV is obtained on a SLAM map, an AGV traveling destination is arranged on the SLAM map, the destination is marked as a navigation end point, a shortest route connected with the front position of the AGV and the navigation end point is planned in a safety area, and the shortest route is marked as a following route.
More specifically, the following path is an AGV navigation travel path and is a line in the SLAM map, and the setting process of the following path is set by considering the obstacle avoidance area of the overall volume structure of the AGV.
A2, extracting a following path, setting the road width, expanding the following path by the road width to form an initial virtual road, and acquiring a virtual road map corresponding to the SLAM map specification based on the initial virtual road;
specifically, the following path is acquired from the SLAM map, and since the following path is a line, a virtual area can be formed by expanding the following path according to the road width, and the virtual area is defined as an initial virtual road.
More specifically, a virtual road map in which only the initial virtual road is present and the position thereof corresponds to the following route in the SLAM map is generated based on the SLAM map with the specifications thereof being in agreement.
Specifically, the road width is a set distance value, and the width of the generated initial virtual road may be the same as the road width or twice the road width.
And A3, overlapping the SLAM map and the virtual road map, reducing the obstacle area in the SLAM map on the initial virtual road of the virtual road map, and acquiring the final virtual road.
Specifically, the SLAM map and the virtual road map are superimposed and fused in position, so that the fused map includes the obstacle area of the SLAM map and the initial virtual road of the virtual road map, and then the obstacle area is reduced from the area of the initial virtual road, even if the initial virtual road performs a non-operation on the obstacle area, the area where the initial virtual road is not in the obstacle area is obtained, and the area is defined as the final virtual road.
More specifically, the final virtual road is used for limiting the travel range of the AGVs, the AGVs do not touch obstacles existing in the operation scene when traveling in the final virtual road, and when additional obstacles appear in the final virtual road, the AGVs can be controlled to move within the range of the final virtual road to avoid the obstacles, that is, the range of the travel path for avoiding the obstacles by the AGVs is limited.
According to the AGV path planning method, after the appropriate following path is obtained on the SLAM map, the initial virtual road in the virtual road map is obtained based on expansion of the following path, the SLAM map and the virtual road map are overlaid to obtain the final virtual road capable of being driven by the AGV, the driving area of the AGV is limited by the final virtual road, so that the AGV can carry out obstacle avoidance navigation following movement in the limited area, the AGV is prevented from driving to a dangerous area due to the fact that the obstacle avoidance path cannot be estimated, and therefore reliability and safety of AGV obstacle avoidance navigation are improved.
In addition, the AGV is limited to act in the final virtual road, so that the displacement path of the AGV at each time is close, the AGV approaches the displacement path of the AGV at each time of reciprocating displacement, the regularity of certain operation time is met, and the timeliness of production operation is met.
In some preferred embodiments, in step a2, the road width is set based on the site safety level.
Specifically, the working environment is divided into different working areas, corresponding safety levels can be manually set on the SLAM map corresponding to each area, the higher the safety level is, the danger is shown on the area, the smaller the correspondingly set road width is, the more cautious the AGV runs, namely, the width of the initial virtual road section generated corresponding to the safety level area is smaller, and therefore the obstacle avoidance running range of the AGV is narrowed and limited.
More specifically, since the AGV travels to the navigation end point possibly through the work areas of different safety levels, the road width setting value has different setting values at the work areas of different safety levels based on the following path, so that the initial virtual road has different road widths at the work areas of different safety levels.
More specifically, the edge of the initial virtual road at the transition between the working areas of different levels is in curve smooth transition, so that the edge of the final virtual road for AGV navigation is smoother and smoother, and the AGV obstacle avoidance driving is facilitated.
In some preferred embodiments, step a2 includes the following sub-steps:
a21, acquiring the specification size of the SLAM map, and generating a grid map with the same specification size as the SLAM map;
specifically, the SLAM map, which may be a regular or irregular figure in which a safety area and an obstacle area are distinguished, generates a map projected on a plane based on laser radar scanning, and the generated grid map conforms to the SLAM map figure size specification.
More specifically, the grid values of the grid map are all initially set to 255, i.e., expressed as an obstacle fully occupied state.
A22, extracting a following path from the SLAM map, and generating a virtual path corresponding to the position in the raster map based on the following path;
specifically, the following path generated in step S1 is extracted and placed in the corresponding position in the raster map to form a virtual path, and the raster value of the virtual path is set to 0, indicating an unoccupied free area.
A23, setting the road width, expanding the virtual path to two sides based on the road width to form an initial virtual road, and forming the grid map into a virtual road map with the initial virtual road.
Specifically, the virtual path forms an initial virtual road for equal inflation to both sides.
Specifically, the grid value of the initial virtual road in the grid map is 0, which indicates that the initial virtual road is an unoccupied free area, and the grid map with the initial virtual road is defined as the virtual road map.
Specifically, in the present embodiment, an initial virtual road may be obtained by performing a dilation processing operation on a grid of a virtual path using OpenCV.
More specifically, a map model with an obstacle occupied area and an idle area can be quickly defined and generated in a grid value setting mode, and the virtual road map adopts a map specification with the same size specification of SLAM map graphics, so that the establishment of an initial virtual road is facilitated and the subsequent map fusion operation is facilitated.
In some preferred embodiments, step a3 includes the following sub-steps:
a31, defining the area outside the initial virtual road in the virtual road map as a virtual obstacle area;
specifically, an area having a grid value of 255 in the virtual road map is defined as a virtual obstacle area, and thus the grid value of the initial virtual road is 0, that is, all areas other than the initial virtual road are virtual obstacle areas.
A32, overlapping and fusing the SLAM map and the virtual road map to form an obstacle map;
specifically, the size specifications of the SLAM map and the virtual road map are consistent, and the SLAM map and the virtual road map can be directly superposed after alignment, so that an obstacle map is obtained, wherein the obstacle map comprises an obstacle area of the SLAM map, a virtual obstacle area in the virtual road map and an initial virtual road.
Specifically, the obstacle area and the virtual obstacle area in the obstacle map are superimposed to form a total obstacle area.
And A33, acquiring an area belonging to a non-obstacle area in the initial virtual road as a final virtual road.
Specifically, the final virtual road may be obtained by removing the obstacle area from the initial virtual road in the obstacle map, or the final virtual road may be obtained by directly removing the total obstacle area in the obstacle map; since the obstacle map can be used for simultaneously planning and using a plurality of AGVs, the embodiment of the present application preferably obtains the final virtual road by removing the obstacle area from the initial virtual road in the obstacle map.
More specifically, as shown in fig. 3, the left side is a SLAM map, and the right side is an obstacle map, where a rectangular area in the obstacle map is an initial virtual road formed by expanding a straight line following a path correspondingly, the initial virtual road forms a final virtual road after removing a plurality of circular obstacle area portions overlapping with the initial virtual road, and AGV movement is defined in the final virtual road.
According to the AGV path planning method, the initial virtual road in the virtual road map is obtained based on following path expansion, the SLAM map and the virtual road map are overlapped to obtain the final virtual road capable of being driven by the AGV, the driving area of the AGV is limited by the final virtual road, so that the AGV can carry out obstacle avoidance navigation following movement in the limited area, the AGV is prevented from driving to a dangerous area due to the fact that the obstacle avoidance path cannot be estimated, and reliability and safety of the AGV obstacle avoidance navigation are improved.
In a second aspect, please refer to fig. 3, fig. 3 is an AGV path following method for controlling AGV to follow a displacement according to some embodiments of the present application, including the following steps:
b1, acquiring a final virtual road in the AGV obstacle avoidance path planning method;
and B2, controlling the AGV to follow the driving along the final virtual road towards the navigation end point.
According to the AGV path following method, the final virtual road in the AGV obstacle avoiding path planning method is obtained, AGV is controlled and limited to follow and run towards a navigation end point on the final virtual road, the AGV can be always kept near the following path in the running process of the AGV, even if obstacles occur, the obstacle can still be avoided within the range of the final virtual road, compared with the common AGV, the method guarantees the path controllability of the AGV running at every time, the AGV is prevented from moving to a dangerous area due to obstacle avoiding requirements, the moving stroke of the AGV can be limited, and the consistency of the transportation beats at every time is achieved.
Specifically, in an actual production link, environmental factors often change, and finally, a barrier may appear in the virtual road, and accordingly, in the process of controlling the AGV to travel in step B2, the travel is controlled according to the road condition; therefore, in some preferred embodiments, in step B2, when there is no obstacle in the final virtual road, the AGV is controlled to follow along the center of the final virtual road toward the navigation end; when the obstacle exists in the final virtual road and the obstacle does not completely block the final virtual road, planning an obstacle avoiding path bypassing the obstacle in the final virtual road, and controlling an AGV to follow and run towards a navigation terminal along the obstacle avoiding path in the final virtual road; and when the obstacle exists in the final virtual road and completely blocks the final virtual road, controlling the AGV to stop moving and enter a state of waiting for clearing the obstacle.
More specifically, when the AGV enters a state of waiting for obstacle clearing, an alarm is sent to the upper computer to inform workers of clearing the obstacles, and the AGV drives towards the navigation target again along the center of the final virtual road until the obstacles are cleared.
More specifically, the center of the final virtual road is a center line in the final virtual road, which is equidistant from both side edges thereof.
In some preferred embodiments, the SLAM map is an ROS standard map generated based on a single line laser radar scan, and step B2 calculates a potential field based on a dijkstra algorithm of the ROS to obtain an AGV displacement path so as to control the AGV to follow the travel.
Specifically, step B2 is based on potential field calculation to perform AGV navigation and avoid the barrier, that is, the barrier is set to repulsion by manually establishing a potential field, and the navigation end point is set to attraction, so that the AGV avoids the barrier based on the attraction of the potential field, and the AGV is prevented from excessively approaching the barrier.
In a third aspect, referring to fig. 4, fig. 4 is a diagram illustrating an AGV path planning apparatus for planning a following path of an AGV according to some embodiments of the present application, including:
the obtaining module is used for setting an AGV following path and a navigation terminal point on an SLAM map according to operation requirements;
the setting module is used for setting the width of a road;
the virtual map module is used for expanding the width of the road along the following path to form an initial virtual road and acquiring a virtual road map corresponding to the SLAM map specification according to the initial virtual road;
and the superposition module is used for superposing the SLAM map and the virtual road map, so that the initial virtual road of the virtual road map reduces the obstacle area in the SLAM map, and the final virtual road is obtained.
The utility model provides a AGV path planning device, acquire SLAM map and navigation information in it based on acquisition module, utilize virtual map module to make the road width of following route inflation setting module setting for in order to acquire the initial virtual road in the virtual road map, then obtain the final virtual road that can supply AGV to travel through the stack module with SLAM map and virtual road map stack, utilize final virtual road to inject AGV's the region of traveling so that AGV keeps away barrier navigation in limited area and follows the removal, avoid AGV because of keeping away barrier route unable estimate and lead to its traveling to danger area, thereby improve AGV and keep away barrier navigation's reliability, security.
In a fourth aspect, please refer to fig. 5, fig. 5 is a schematic structural diagram of an apparatus provided in an embodiment of the present application, and the present application provides an apparatus 3, including: the processor 301 and the memory 302, the processor 301 and the memory 302 being interconnected and communicating with each other via a communication bus 303 and/or other form of connection mechanism (not shown), the memory 302 storing a computer program executable by the processor 301, the processor 301 executing the computer program when the computing device is running to perform the method of any of the alternative implementations of the embodiments described above.
In a fifth aspect, the present application provides a storage medium, and when being executed by a processor, the computer program performs the method in any optional implementation manner of the foregoing embodiments. The storage medium may be implemented by any type of volatile or nonvolatile storage device or combination thereof, such as a Static Random Access Memory (SRAM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), an Erasable Programmable Read-Only Memory (EPROM), a Programmable Read-Only Memory (PROM), a Read-Only Memory (ROM), a magnetic Memory, a flash Memory, a magnetic disk, or an optical disk.
In summary, the embodiment of the application provides an AGV path planning method, a following device, an apparatus and a storage medium, wherein the planning method obtains an initial virtual road in a virtual road map based on following path expansion, superimposes a SLAM map and the virtual road map to obtain a final virtual road for the AGV to travel, and limits a travel area of the AGV by using the final virtual road to enable the AGV to carry out obstacle avoidance navigation following movement in a limited area, so that the situation that the AGV travels to a dangerous area due to the fact that an obstacle avoidance path cannot be estimated is avoided, and reliability and safety of the AGV obstacle avoidance navigation are improved.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
In addition, units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
Furthermore, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (9)
1. An AGV path planning method is used for planning a following path of an AGV and is characterized by comprising the following steps:
a1, acquiring an SLAM map, and setting an AGV following path and a navigation terminal point on the SLAM map according to operation requirements;
a2, extracting a following path, setting the road width, expanding the following path by the road width to form an initial virtual road, and acquiring a virtual road map corresponding to the SLAM map specification based on the initial virtual road;
a3, overlapping the SLAM map and the virtual road map, reducing the obstacle area in the SLAM map by the initial virtual road of the virtual road map, and acquiring the final virtual road;
in step a2, the road width is set based on the site safety level, so that the initial virtual road has different road widths in the working areas with different safety levels;
planning a shortest route connected with a front position and a navigation terminal of the AGV in a safety area, and marking the shortest route as a following route, wherein the following route is an AGV navigation driving route;
the edge of the initial virtual road at the transition between the working areas with different safety levels is in curve smooth transition.
2. The AGV path planning method according to claim 1, wherein step a2 includes the following substeps:
a21, acquiring the specification size of the SLAM map, and generating a grid map with the same specification size as the SLAM map;
a22, extracting a following path from the SLAM map, and generating a virtual path corresponding to the position in the raster map based on the following path;
a23, setting the road width, expanding the virtual path to two sides based on the road width to form an initial virtual road, and forming the grid map into a virtual road map with the initial virtual road.
3. The AGV path planning method according to claim 1, wherein step a3 includes the following substeps:
a31, defining the area outside the initial virtual road in the virtual road map as a virtual obstacle area;
a32, overlapping and fusing the SLAM map and the virtual road map to form an obstacle map;
and A33, acquiring an area belonging to a non-obstacle area in the initial virtual road as a final virtual road.
4. An AGV path following method, comprising the steps of:
b1, obtaining a final virtual road in the AGV path planning method according to any one of claims 1 to 3;
and B2, controlling the AGV to follow along the final virtual road to the navigation terminal.
5. The AGV path following method according to claim 4, wherein in step B2, when no obstacle exists in the final virtual road, the AGV is controlled to follow along the center of the final virtual road toward the navigation end point; when a barrier exists in the final virtual road and the barrier does not completely block the final virtual road, planning an obstacle avoiding path bypassing the barrier in the final virtual road, and controlling the AGV to follow along the obstacle avoiding path in the final virtual road towards a navigation terminal; and when the obstacle exists in the final virtual road and completely blocks the final virtual road, controlling the AGV to stop moving and enter a state of waiting for clearing the obstacle.
6. The AGV path following method according to claim 4, wherein the SLAM map is an ROS standard map generated based on single line laser radar scanning, and step B2 is implemented by calculating a potential field based on a dijkstra algorithm of ROS to obtain the AGV path to control the AGV to follow and travel.
7. An AGV path planning apparatus for planning a following path of an AGV, comprising:
the obtaining module is used for setting an AGV following path and a navigation terminal point on an SLAM map according to operation requirements;
the setting module is used for setting the width of a road;
the virtual map module is used for expanding the width of the road along the following path to form an initial virtual road and acquiring a virtual road map corresponding to the SLAM map specification according to the initial virtual road;
the superposition module is used for superposing the SLAM map and the virtual road map, so that the initial virtual road of the virtual road map reduces the obstacle area in the SLAM map, and the final virtual road is obtained; the road width is set based on the site safety level, so that the initial virtual road has different road widths in working areas with different safety levels.
8. An apparatus comprising a processor and a memory, said memory storing computer readable instructions which, when executed by said processor, perform the steps of the method of any one of claims 1 to 4.
9. A storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, performs the steps of the method according to any one of claims 1-3.
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| CN114019988B (en) * | 2022-01-05 | 2022-04-01 | 季华实验室 | AGV control method and device based on CPG, electronic equipment and storage medium |
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Family Cites Families (30)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8818711B2 (en) * | 2009-12-18 | 2014-08-26 | Empire Technology Development Llc | 3D path analysis for environmental modeling |
| KR102029562B1 (en) * | 2015-01-05 | 2019-10-07 | 닛산 지도우샤 가부시키가이샤 | Target path generation device and travel control device |
| CN104615138B (en) * | 2015-01-14 | 2017-09-08 | 上海物景智能科技有限公司 | One kind divides mobile robot room area dynamic coverage method and its device |
| CN104777835A (en) * | 2015-03-11 | 2015-07-15 | 武汉汉迪机器人科技有限公司 | Omni-directional automatic forklift and 3D stereoscopic vision navigating and positioning method |
| CN104950883A (en) * | 2015-05-14 | 2015-09-30 | 西安电子科技大学 | Mobile robot route planning method based on distance grid map |
| CN107209854A (en) * | 2015-09-15 | 2017-09-26 | 深圳市大疆创新科技有限公司 | For the support system and method that smoothly target is followed |
| CN105698807A (en) * | 2016-02-01 | 2016-06-22 | 郑州金惠计算机系统工程有限公司 | Laser navigation system applicable to intelligent inspection robot of transformer substation |
| CN109891349B (en) * | 2016-10-25 | 2022-03-11 | 本田技研工业株式会社 | Vehicle control device |
| US10146224B2 (en) * | 2016-11-09 | 2018-12-04 | GM Global Technology Operations LLC | Processor-implemented systems and methods for automated driving |
| US10612932B2 (en) * | 2017-09-29 | 2020-04-07 | Wipro Limited | Method and system for correcting a pre-generated navigation path for an autonomous vehicle |
| CN108731693A (en) * | 2018-06-05 | 2018-11-02 | 北京智行者科技有限公司 | Block map acquisition method |
| WO2020018527A1 (en) * | 2018-07-16 | 2020-01-23 | Brain Corporation | Systems and methods for optimizing route planning for tight turns for robotic apparatuses |
| CN109696676B (en) * | 2019-01-24 | 2022-11-22 | 福瑞泰克智能系统有限公司 | Effective obstacle target determination method and device and vehicle |
| CN112396051B (en) * | 2019-08-15 | 2024-05-03 | 纳恩博（北京）科技有限公司 | Determination method and device for passable area, storage medium and electronic device |
| CN110726416A (en) * | 2019-10-23 | 2020-01-24 | 西安工程大学 | Reinforced learning path planning method based on obstacle area expansion strategy |
| CN110967028B (en) * | 2019-11-26 | 2022-04-12 | 深圳优地科技有限公司 | Navigation map construction method and device, robot and storage medium |
| CN111123949B (en) * | 2019-12-31 | 2023-07-07 | 达闼机器人股份有限公司 | Obstacle avoidance method and device for robot, robot and storage medium |
| CN111208839B (en) * | 2020-04-24 | 2020-08-04 | 清华大学 | Fusion method and system of real-time perception information and automatic driving map |
| CN111522898B (en) * | 2020-05-09 | 2023-07-04 | 江苏徐工工程机械研究院有限公司 | Map creation method, server and system |
| CN111486848B (en) * | 2020-05-25 | 2022-02-22 | 上海杰销自动化科技有限公司 | AGV visual navigation method, system, computer equipment and storage medium |
| CN111781925A (en) * | 2020-06-22 | 2020-10-16 | 北京海益同展信息科技有限公司 | Path planning method and device, robot and storage medium |
| CN112097784A (en) * | 2020-09-01 | 2020-12-18 | 武汉光庭信息技术股份有限公司 | Verification method and device for map matching result of map sensor |
| CN112162551B (en) * | 2020-09-10 | 2021-11-16 | 珠海格力电器股份有限公司 | Obstacle detection method, apparatus, device and computer readable medium |
| CN112214019B (en) * | 2020-09-21 | 2023-05-23 | 国网浙江省电力有限公司 | Unmanned inspection equipment non-blind area intelligent feedback control system, method and terminal |
| CN112269380A (en) * | 2020-10-15 | 2021-01-26 | 许继电源有限公司 | Obstacle meeting control method and system for substation inspection robot |
| CN112710318B (en) * | 2020-12-14 | 2024-05-17 | 深圳市商汤科技有限公司 | Map generation method, path planning method, electronic device, and storage medium |
| CN112650234B (en) * | 2020-12-16 | 2022-05-17 | 浙江大学 | Path planning method of biped robot |
| CN112987720A (en) * | 2021-01-29 | 2021-06-18 | 北京比得机器人科技有限公司 | Multi-scale map construction method and construction device for mobile robot |
| CN113008249B (en) * | 2021-02-09 | 2024-03-12 | 广州视睿电子科技有限公司 | Avoidance point detection method and avoidance method of mobile robot and mobile robot |
| CN113253686B (en) * | 2021-06-10 | 2021-10-15 | 浙江华睿科技股份有限公司 | AGV vehicle path planning method and device, electronic equipment and storage medium |
-
2021
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