CN113008250A - Unmanned vehicle navigation method and device - Google Patents
Unmanned vehicle navigation method and device Download PDFInfo
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- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
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Abstract
The application discloses a method and a device for navigating an unmanned vehicle, and relates to the technical field of navigation. One embodiment of the method comprises: acquiring a map marked with road condition information, wherein the map marked with the road condition information is obtained by manually marking the map based on the monitored road condition information; and replanning the navigation path of the unmanned vehicle based on the map in response to detecting that the road condition information on the navigation path of the unmanned vehicle is changed. The embodiment effectively improves the effectiveness and accuracy of navigation.
Description
Technical Field
The application relates to the technical field of unmanned driving, in particular to the technical field of navigation, and particularly relates to an unmanned vehicle navigation method and device.
Background
The unmanned delivery vehicle needs to run on a non-motor vehicle lane as far as possible, and in an actual road, the non-motor vehicle lane can be subjected to road repair, road condition damage, obstruction of a plurality of motor vehicles parked for a long time and the like, so that the unmanned delivery vehicle can avoid the routes in a navigation stage.
In the prior art, for the navigation route closing of an unmanned delivery vehicle, a method of designating a closed road in a navigation configuration is adopted, and the road is not considered as a path search during navigation, so that the road is not selected by navigation.
Disclosure of Invention
The embodiment of the application provides an unmanned vehicle navigation method, device, equipment and storage medium.
According to a first aspect, an embodiment of the present application provides an unmanned vehicle navigation method, including: acquiring a map marked with road condition information, wherein the map marked with the road condition information is obtained by manually marking the map based on the monitored road condition information; and replanning the navigation path of the unmanned vehicle based on the map in response to detecting that the road condition information on the navigation path of the unmanned vehicle is changed.
In some embodiments, re-planning the navigation path of the unmanned vehicle based on a map comprises: updating the road topological graph based on the map to obtain an updated road topological graph; and replanning the navigation path of the unmanned vehicle according to the updated road topological graph.
In some embodiments, updating the road topology map based on the map includes: and in response to determining that the changed road condition information comprises information indicating the occurrence of the road-closing obstacle, performing a pruning operation on the road topology map to realize the updating of the road topology map.
In some embodiments, updating the road topology map based on the map comprises: and in response to determining that the changed road condition information comprises information indicating that the road blocking obstacle is eliminated, performing an adding operation on the road topological graph to update the road topological graph.
In some embodiments, obtaining the road condition information on the unmanned vehicle navigation path includes: and acquiring a map marked with road condition information in response to the fact that the residence time of the unmanned vehicle is greater than or equal to the preset time.
According to a second aspect, an embodiment of the present application provides an unmanned vehicle navigation apparatus, including: the acquisition module is configured to acquire a map marked with road condition information, and the map marked with the road condition information is obtained by manually marking the map based on the monitored road condition information; a change module configured to re-plan a navigation path of the unmanned vehicle based on a map in response to detecting a change in road condition information on the unmanned vehicle navigation path.
In some embodiments, the planning module further comprises: the updating unit is configured to update the road topological graph based on the map to obtain an updated road topological graph; and the planning unit is configured to re-plan the navigation path of the unmanned vehicle according to the updated road topological graph.
In some embodiments, the planning unit is further configured to: and in response to determining that the changed road condition information comprises information indicating the occurrence of the road-closing obstacle, performing a pruning operation on the road topology map to realize the updating of the road topology map.
In some embodiments, the planning unit is further configured to: and in response to determining that the changed road condition information comprises information indicating that the road blocking obstacle is eliminated, performing an adding operation on the road topological graph to update the road topological graph.
In some embodiments, the acquisition module is further configured to: and acquiring a map marked with road condition information in response to the fact that the residence time of the unmanned vehicle is greater than or equal to the preset time.
According to a third aspect, embodiments of the present application provide an electronic device, which includes one or more processors; a storage device having one or more programs stored thereon that, when executed by the one or more processors, cause the one or more processors to implement the unmanned vehicle navigation method as any one embodiment of the first aspect.
According to a fourth aspect, embodiments of the present application provide a computer-readable medium, on which a computer program is stored, which when executed by a processor, implements the unmanned vehicle navigation method as in any of the embodiments of the first aspect.
According to the method, the map marked with the road condition information is obtained, and the map marked with the road condition information is obtained by manually marking the map based on the monitored road condition information; the navigation path of the unmanned vehicle is re-planned based on the map in response to the detection that the road condition information on the navigation path of the unmanned vehicle is changed, so that the unmanned vehicle can acquire the road condition information on the navigation path in advance, the path can be re-planned in advance, the problems of low navigation efficiency and the like caused by the fact that the road condition of multiple ends cannot be changed are solved, and the navigation effectiveness and accuracy are effectively improved.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
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FIG. 1 is an exemplary system architecture diagram in which the present application may be applied;
FIG. 2 is a flow diagram of one embodiment of an unmanned vehicle navigation method according to the present application;
FIG. 3 is a schematic diagram of an application scenario of the unmanned vehicle navigation method according to the present application;
FIG. 4 is a flow diagram of another embodiment of an unmanned vehicle navigation method according to the present application;
FIG. 5 is a schematic view of one embodiment of an unmanned vehicle navigation device according to the present application;
FIG. 6 is a schematic block diagram of a computer system suitable for use in implementing a server according to embodiments of the present application.
Detailed Description
The following description of the exemplary embodiments of the present application, taken in conjunction with the accompanying drawings, includes various details of the embodiments of the application for the understanding of the same, which are to be considered exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
FIG. 1 illustrates an exemplary system architecture 100 to which embodiments of the unmanned vehicle navigation methods of the present application may be applied.
As shown in fig. 1, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The terminal devices 101, 102, 103 interact with a server 105 via a network 104 to receive or send messages or the like. Various communication client applications, such as navigation applications, communication applications, etc., may be installed on the terminal devices 101, 102, 103.
The terminal apparatuses 101, 102, and 103 may be hardware or software. When the terminal devices 101, 102, 103 are hardware, they may be various electronic devices having a display screen, including but not limited to a mobile phone and a notebook computer. When the terminal apparatuses 101, 102, 103 are software, they can be installed in the electronic apparatuses listed above. It may be implemented as multiple pieces of software or software modules (e.g., to provide unmanned vehicle navigation services) or as a single piece of software or software module. And is not particularly limited herein.
The server 105 may be a server that provides various services, for example, a map marked with traffic information is obtained, and the map marked with traffic information is obtained by manually marking the map based on the monitored traffic information; and replanning the navigation path of the unmanned vehicle based on the map in response to detecting that the road condition information on the navigation path of the unmanned vehicle is changed.
The server 105 may be hardware or software. When the server 105 is hardware, it may be implemented as a distributed server cluster composed of a plurality of servers, or may be implemented as a single server. When the server is software, it may be implemented as a plurality of software or software modules (for example, for providing an unmanned vehicle navigation service), or as a single software or software module. And is not particularly limited herein.
It should be noted that the unmanned vehicle navigation method provided by the embodiment of the present disclosure may be executed by the server 105, or may be executed by the terminal devices 101, 102, and 103, or may be executed by the server 105 and the terminal devices 101, 102, and 103 in cooperation with each other. Accordingly, each part (for example, each unit, sub-unit, module, sub-module) included in the unmanned vehicle navigation apparatus may be provided entirely in the server 105, may be provided entirely in the terminal devices 101, 102, 103, or may be provided in the server 105 and the terminal devices 101, 102, 103, respectively.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Fig. 2 shows a flow diagram 200 of an embodiment of an unmanned vehicle navigation method that may be applied to the present application. In this embodiment, the unmanned vehicle navigation method includes the following steps:
In this embodiment, the execution main body (for example, the server 105 or the terminal devices 101, 102, and 103 shown in fig. 1) may obtain the map marked with the traffic information in real time, obtain the map marked with the traffic information at preset time intervals, or obtain the map marked with the traffic information in response to detecting that the residence time of the unmanned vehicle is greater than or equal to a preset time period, which is not limited in this application.
The road condition information is used for indicating the congestion condition of the road, whether a road-sealing barrier exists or not, and the road-sealing barrier can be a barrier which can not be passed by the unmanned vehicle caused by stone piles, illegal vehicles parked for a long time and the like.
It should be noted that the map marked with the traffic information may be obtained by manually marking the map based on the traffic information monitored by the monitoring device. The monitoring device may be one or more of a monitoring device in the prior art or a monitoring device in a future development, for example, a video monitoring device, a positioning monitoring device, and the like.
Specifically, the operator can monitor the road condition information on each path in real time through the video monitoring device, and if congestion, a road-closing obstacle or elimination of the original road-closing obstacle and the like occur on the path, the operator marks the corresponding path on the map to obtain the map marked with the road condition information.
In addition, the operator can also monitor the road condition information on at least one unmanned vehicle navigation path in real time through the positioning monitoring equipment, and if the length of time that the unmanned vehicle stays is greater than or equal to the preset length of time, the operator marks the corresponding route on the map (if a road blocking obstacle appears), so that the map marked with the road condition information is obtained.
In some optional manners, in response to detecting that the residence time of the unmanned vehicle is greater than or equal to a preset time, a map marked with road condition information is acquired.
In this implementation manner, the execution main body may detect whether the residence time of the unmanned vehicle is greater than or equal to a preset time length in real time, and if the residence time is greater than or equal to the preset time length, obtain the map marked with the road condition information.
The preset time period may be set according to actual needs, experience, and specific application scenarios, for example, 5 minutes, 10 minutes, and the like, which is not limited in the present application.
According to the implementation mode, the map marked with the road condition information is obtained by responding to the fact that the residence time of the unmanned vehicle is greater than or equal to the preset duration, so that frequent change of a navigation path can be effectively avoided, and the navigation effectiveness of the unmanned vehicle is improved.
In this embodiment, after obtaining the map marked with the road condition information, the execution main body detects whether the road condition information on the navigation path of the unmanned vehicle is changed according to the map, and if the road condition information is changed, the navigation path is re-planned according to the map marked with the road condition information and the navigation algorithm.
Specifically, the navigation path of the unmanned vehicle is: the method comprises the steps that a road K, a road M and a road N are obtained, an execution main body obtains a map marked with road condition information in real time, whether the road condition information on a navigation path of the unmanned vehicle is changed or not is detected according to the map, and if the execution main body detects that the road condition information on the road N is changed, for example, a road N is blocked, the navigation path is planned again according to the map and a navigation algorithm.
With continued reference to fig. 3, fig. 3 is a schematic diagram of an application scenario of the unmanned vehicle navigation method according to the present embodiment.
In the application scenario of fig. 3, the execution main body 301 obtains the map marked with the traffic information in real time, wherein the map marked with the traffic information is obtained by monitoring the change of the traffic information manually through the monitoring device and marking the changed traffic information on the map. The execution subject 301 further acquires a navigation path 303 of an unmanned vehicle 302, for example, an unmanned delivery vehicle: road E-road F-road H, with the unmanned vehicle 302 currently on road E. The executing body 302 matches the road condition information on the navigation path 303 of the unmanned vehicle 302 with the road condition information labeled on the map, and in response to detecting that the road condition information on the navigation path 303 of the unmanned vehicle 302 is changed, for example, a road blocking obstacle 304 appears on the road F, the navigation path of the unmanned vehicle is re-planned based on the map, for example, the navigation path 305: road E-road K-road H.
According to the unmanned vehicle navigation method, the map marked with the road condition information is obtained, and the map marked with the road condition information is obtained by manually marking the map based on the road condition information monitored by the monitoring equipment; and in response to the detection that the road condition information on the unmanned vehicle navigation path is changed, the navigation path of the unmanned vehicle is re-planned based on the map, so that the navigation effectiveness and accuracy are effectively improved.
With further reference to fig. 4, a flow 400 of yet another embodiment of an unmanned vehicle navigation method is shown. The flow 400 of the unmanned vehicle navigation method of the embodiment may include the following steps:
In this embodiment, details of implementation and technical effects of step 401 may refer to the description of step 201, and are not described herein again.
And 402, updating the road topological graph based on the map to obtain the updated road topological graph.
In this embodiment, after acquiring the map marked with the road condition information, the executing entity may update the changed road condition information in the map to the corresponding road topology map to obtain the updated road topology map.
Here, the road topology may be set according to the application scenario. For example, for a goods delivery scene, an unmanned delivery vehicle usually runs in a non-motor vehicle lane, and the road topological graph can be a topological graph constructed based on the non-motor vehicle lane in a specified area; for an automatic driving scenario, the unmanned vehicle usually runs in a vehicle lane, and the road topology map may be a topology map constructed based on the vehicle lane of a specified area.
The changed road condition information may include the occurrence of a road closure obstacle, the elimination of a road closure obstacle, and the like.
Specifically, the road condition information marked on the road a in the map is that a road-closing barrier appears, the road condition information marked on the road B is that the road-closing barrier is eliminated, the execution main body acquires the road identifier corresponding to the changed road condition information, namely the road a and the road B, after detecting the changed road condition information, and updates the road condition information of the road a and the road B into the road topological graph to obtain the updated road topological graph.
In some optional modes, the updating the road topological graph based on the map comprises the following steps: and in response to determining that the changed road condition information comprises information indicating the occurrence of the road-closing obstacle, performing a pruning operation on the road topology map to realize the updating of the road topology map.
In this implementation manner, the execution main body analyzes the change of the road condition information after acquiring the map marked with the road condition information, acquires the identifier of the road occupied by the road blocking obstacle if the changed road condition information includes the information indicating that the road blocking obstacle appears, and executes the deletion operation on the road topology map based on the identifier of the road to update the road topology map.
Specifically, the execution main body obtains the identifier of the road corresponding to the changed road condition information (i.e., the road a) after detecting the changed road condition information (e.g., the road condition information marked on the road a in the map includes the indication of the occurrence of the road-closing obstacle), and deletes the road corresponding to the road a in the road topological graph to obtain the updated road topological graph.
In the method, in response to the fact that the determined road condition information comprises the information indicating that the road blocking obstacle appears, the road topological graph is subjected to deletion operation to update the road topological graph, the updated road topological graph is obtained, and path planning is carried out based on the updated road topological graph, so that paths needing to be considered during navigation planning are effectively reduced, and the navigation efficiency is improved.
In some optional modes, the updating the road topological graph based on the map comprises the following steps: and in response to determining that the changed road condition information comprises information indicating that the road blocking obstacle is eliminated, performing an adding operation on the road topological graph to update the road topological graph.
In this implementation manner, the execution main body analyzes the change of the road condition information after acquiring the map marked with the road condition information, acquires the identifier of the road occupied by the eliminated road-sealing barrier if the changed road condition information includes the information indicating the elimination of the road-sealing barrier, and executes an adding operation on the road topological graph based on the identifier of the road to update the road topological graph.
Specifically, the execution main body obtains the identifier of the road corresponding to the changed road condition information (i.e., the B road) after detecting the changed road condition information (e.g., the road condition information marked on the B road in the map includes information indicating that the road-closing obstacle is eliminated), and adds the road corresponding to the B road to the road topological graph to obtain the updated road topological graph.
In the method, in response to the fact that the changed road condition information comprises the information indicating the elimination of the road-closing barrier, the road topological graph is added to update the road topological graph, the updated road topological graph is obtained, and the path planning is carried out based on the updated road topological graph, so that the road with the road-closing barrier eliminated is updated to the road topological graph in real time to serve as a candidate path for path planning, and the navigation effectiveness and accuracy are effectively improved.
And 403, replanning the navigation path according to the updated road topological graph.
In this embodiment, after obtaining the updated road topology map, the executive body may re-plan the navigation path of the unmanned vehicle according to the updated road topology map to obtain a re-planned navigation path, and control the unmanned vehicle to continue to travel according to the re-planned navigation path.
Compared with the embodiment corresponding to fig. 2, the flow 400 of the unmanned vehicle navigation method in the embodiment represents that the road topological graph is updated based on the map to obtain an updated road topological graph; and the navigation path of the unmanned vehicle is re-planned according to the updated road topological graph, so that the candidate route graph for re-planning the path of the unmanned vehicle is effectively simplified, and the pertinence and the efficiency of navigation are improved.
With further reference to fig. 5, as an implementation of the methods shown in the above-mentioned figures, the present application provides an embodiment of an unmanned vehicle navigation apparatus, which corresponds to the embodiment of the method shown in fig. 1, and which is particularly applicable to various electronic devices.
As shown in fig. 5, the unmanned vehicle navigation apparatus 500 of the present embodiment includes: an acquisition module 501 and a change module 502.
The obtaining module 501 may be configured to obtain a map marked with traffic information, where the map marked with traffic information is obtained by manually marking the map based on the monitored traffic information.
A change module 502, which may be configured to re-plan the navigation path of the unmanned vehicle based on the map in response to detecting a change in road condition information on the navigation path of the unmanned vehicle.
In some optional aspects of this embodiment, the planning module further includes: the updating unit is configured to update the road topological graph based on the map to obtain an updated road topological graph; a planning unit configured to re-plan a navigation path of the unmanned vehicle according to the updated road topology map.
In some alternatives of this embodiment, the planning unit is further configured to: and in response to determining that the changed road condition information comprises information indicating the occurrence of the road-closing obstacle, performing a pruning operation on the road topology map to realize the updating of the road topology map.
In some alternatives of this embodiment, the planning unit is further configured to: and in response to determining that the changed road condition information comprises information indicating that the road blocking obstacle is eliminated, performing an adding operation on the road topological graph to update the road topological graph.
In some optional aspects of this embodiment, the obtaining module is further configured to: and acquiring a map marked with road condition information in response to the fact that the residence time of the unmanned vehicle is greater than or equal to the preset time.
According to an embodiment of the present application, an electronic device and a readable storage medium are also provided.
As shown in fig. 6, the electronic device is a block diagram of an unmanned vehicle navigation method according to an embodiment of the present application.
600 is a block diagram of an electronic device for an unmanned vehicle navigation method according to an embodiment of the present application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.
As shown in fig. 6, the electronic apparatus includes: one or more processors 601, memory 602, and interfaces for connecting the various components, including a high-speed interface and a low-speed interface. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the electronic device, including instructions stored in or on the memory to display graphical information of a GUI on an external input/output apparatus (such as a display device coupled to the interface). In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, as desired. Also, multiple electronic devices may be connected, with each device providing portions of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). In fig. 6, one processor 601 is taken as an example.
The memory 602 is a non-transitory computer readable storage medium as provided herein. Wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the unmanned vehicle navigation method provided herein. The non-transitory computer-readable storage medium of the present application stores computer instructions for causing a computer to perform the unmanned vehicle navigation method provided by the present application.
The memory 602, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules (e.g., the obtaining module 501 and the changing module 502 shown in fig. 5) corresponding to the unmanned vehicle navigation method in the embodiments of the present application. The processor 601 executes various functional applications of the server and data processing by running non-transitory software programs, instructions and modules stored in the memory 602, that is, the unmanned vehicle navigation method in the above method embodiment is implemented.
The memory 602 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created by use of the electronic device for unmanned vehicle navigation, and the like. Further, the memory 602 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 602 may optionally include memory located remotely from the processor 601, which may be connected to the unmanned vehicle navigation electronics via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The electronic device of the unmanned vehicle navigation method may further include: an input device 603 and an output device 604. The processor 601, the memory 602, the input device 603 and the output device 604 may be connected by a bus or other means, and fig. 6 illustrates the connection by a bus as an example.
The input device 603 may receive input numeric or character information, such as an input device like a touch screen, keypad, mouse, track pad, touch pad, pointer, one or more mouse buttons, track ball, joystick, etc. The output devices 604 may include a display device, auxiliary lighting devices (e.g., LEDs), and tactile feedback devices (e.g., vibrating motors), among others. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device can be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
According to the technical scheme of the embodiment of the application, the accuracy and the effectiveness of unmanned vehicle navigation are greatly improved.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present application may be executed in parallel, sequentially, or in different orders, and the present invention is not limited thereto as long as the desired results of the technical solutions disclosed in the present application can be achieved.
The above-described embodiments should not be construed as limiting the scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (12)
1. A method of unmanned vehicle navigation, the method comprising:
acquiring a map marked with road condition information, wherein the map marked with the road condition information is obtained by manually marking the map based on the monitored road condition information;
and replanning the navigation path of the unmanned vehicle based on the map in response to detecting that the road condition information on the navigation path of the unmanned vehicle is changed.
2. The method of claim 1, wherein said re-planning the navigation path of the unmanned vehicle based on the map comprises:
updating the road topological graph based on the map to obtain an updated road topological graph;
and replanning the navigation path of the unmanned vehicle according to the updated road topological graph.
3. The method of claim 2, wherein the updating the road topology map based on the map comprises:
and in response to determining that the changed road condition information comprises information indicating the occurrence of the road-closing obstacle, performing a pruning operation on the road topology map to realize the updating of the road topology map.
4. The method of claim 2, wherein the updating the road topology map based on the map comprises:
and in response to determining that the changed road condition information comprises information indicating that the road blocking obstacle is eliminated, performing an adding operation on the road topological graph to update the road topological graph.
5. The method of claim 1, wherein the obtaining of the road condition information on the unmanned vehicle navigation path comprises:
and acquiring a map marked with road condition information in response to the fact that the residence time of the unmanned vehicle is greater than or equal to the preset time.
6. An unmanned vehicle navigation device, the device comprising:
the system comprises an acquisition module, a processing module and a display module, wherein the acquisition module is configured to acquire a map marked with road condition information, and the map marked with the road condition information is obtained by manually marking the map based on monitored road condition information;
a change module configured to re-plan a navigation path of the unmanned vehicle based on the map in response to detecting a change in road condition information on the unmanned vehicle navigation path.
7. The apparatus of claim 6, wherein the planning module further comprises:
the updating unit is configured to update the road topological graph based on the map to obtain an updated road topological graph;
a planning unit configured to re-plan a navigation path of the unmanned vehicle according to the updated road topology map.
8. The apparatus of claim 7, wherein the planning unit is further configured to:
and in response to determining that the changed road condition information comprises information indicating the occurrence of the road-closing obstacle, performing a pruning operation on the road topology map to realize the updating of the road topology map.
9. The apparatus of claim 7, wherein the planning unit is further configured to:
and in response to determining that the changed road condition information comprises information indicating that the road blocking obstacle is eliminated, performing an adding operation on the road topological graph to update the road topological graph.
10. The apparatus of claim 6, wherein the acquisition module is further configured to:
and acquiring a map marked with road condition information in response to the fact that the residence time of the unmanned vehicle is greater than or equal to the preset time.
11. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory is stored with instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
12. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-5.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113865608A (en) * | 2021-09-26 | 2021-12-31 | 上海擎朗智能科技有限公司 | Navigation path planning method and device and storage medium |
| CN114241630A (en) * | 2021-11-15 | 2022-03-25 | 智马达汽车有限公司 | Vehicle unlocking control method and device, electronic equipment and storage medium |
| CN114489077A (en) * | 2022-01-26 | 2022-05-13 | 深圳优地科技有限公司 | Robot navigation method and device and robot |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103954294A (en) * | 2014-05-26 | 2014-07-30 | 龚永祥 | Method for avoiding jammed road and navigation device |
| CN105185145A (en) * | 2015-10-04 | 2015-12-23 | 陈燕 | Intelligent dynamic road condition map navigation system and method |
| CN108534787A (en) * | 2018-04-15 | 2018-09-14 | 肖恒念 | A kind of big data computational methods and device for real-time data analysis |
| CN108692725A (en) * | 2018-03-30 | 2018-10-23 | 东莞产权交易中心 | It is a kind of large size scenic spot in guide to visitors vehicle path planning system and paths planning method |
| CN109708656A (en) * | 2019-01-24 | 2019-05-03 | 爱驰汽车有限公司 | Route planning method, system, equipment and storage medium based on real-time road |
| CN110047306A (en) * | 2019-04-23 | 2019-07-23 | 杜泽臣 | A kind of intelligent traffic network |
| CN111862656A (en) * | 2020-07-21 | 2020-10-30 | 北京小马智行科技有限公司 | Map updating method and device for intelligent carrier, storage medium and processor |
| CN112099508A (en) * | 2020-09-22 | 2020-12-18 | 北京百度网讯科技有限公司 | Data management method and device for automatic driving vehicle |
-
2021
- 2021-02-20 CN CN202110192917.6A patent/CN113008250A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103954294A (en) * | 2014-05-26 | 2014-07-30 | 龚永祥 | Method for avoiding jammed road and navigation device |
| CN105185145A (en) * | 2015-10-04 | 2015-12-23 | 陈燕 | Intelligent dynamic road condition map navigation system and method |
| CN108692725A (en) * | 2018-03-30 | 2018-10-23 | 东莞产权交易中心 | It is a kind of large size scenic spot in guide to visitors vehicle path planning system and paths planning method |
| CN108534787A (en) * | 2018-04-15 | 2018-09-14 | 肖恒念 | A kind of big data computational methods and device for real-time data analysis |
| CN109708656A (en) * | 2019-01-24 | 2019-05-03 | 爱驰汽车有限公司 | Route planning method, system, equipment and storage medium based on real-time road |
| CN110047306A (en) * | 2019-04-23 | 2019-07-23 | 杜泽臣 | A kind of intelligent traffic network |
| CN111862656A (en) * | 2020-07-21 | 2020-10-30 | 北京小马智行科技有限公司 | Map updating method and device for intelligent carrier, storage medium and processor |
| CN112099508A (en) * | 2020-09-22 | 2020-12-18 | 北京百度网讯科技有限公司 | Data management method and device for automatic driving vehicle |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113865608A (en) * | 2021-09-26 | 2021-12-31 | 上海擎朗智能科技有限公司 | Navigation path planning method and device and storage medium |
| CN114241630A (en) * | 2021-11-15 | 2022-03-25 | 智马达汽车有限公司 | Vehicle unlocking control method and device, electronic equipment and storage medium |
| CN114489077A (en) * | 2022-01-26 | 2022-05-13 | 深圳优地科技有限公司 | Robot navigation method and device and robot |
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