Route planning method and system for robot dog battlefield rescue

Abstract

The invention discloses a route planning method and system for robot dog battlefield rescue. The method comprises the following steps: acquiring basic route point information for robot dog actions; the basic route point information comprises first route point information and second route point information; the first route point information comprises a plurality of pieces of first sub-route point information; the basic point information comprises first basic point information, and / or second basic point information, and / or a plurality of pieces of third basic point information; the second route point information comprises a plurality of pieces of reconnaissance point information; analyzing and processing the basic route point information to obtain first planning route information; the first planning path information comprises a plurality of pieces of first path area information; and performing planning processing on the first planning path information and the basic route point information to obtain target planning path information.

Description

Technical Field

[0001] The present invention relates to the technical field of route planning, and in particular to a route planning method and system for the battlefield rescue of a robotic dog. Background Art

[0002] With the continuous development of technology, the robotic dog, as an advanced unmanned rescue platform, has gradually been applied to various rescue scenarios, such as battlefield rescue. However, there are still some problems and deficiencies in the route planning of robotic dogs in rescue scenarios. First of all, the complexity of the rescue scenario environment poses a huge challenge to the route planning of robotic dogs. Traditional route planning methods often struggle to adapt to such complex rescue scenario environments and cannot provide safe and efficient rescue paths for robotic dogs. Secondly, existing robotic dog route planning methods also have deficiencies in environmental perception and path optimization. In rescue scenarios, robotic dogs need to continuously perceive changes in the surrounding environment and accurately identify information such as obstacles, dangerous areas, and the locations of injured personnel. However, the current perception technology still needs to be improved in terms of accuracy and real-time performance, which may lead to deviations or omissions of important information when robotic dogs plan routes. In addition, traditional path planning algorithms are difficult to quickly adjust the planned path when facing the dynamically changing battlefield environment and cannot meet the real-time requirements of rescue scenarios. Therefore, a route planning method and system for the battlefield rescue of robotic dogs are provided to improve the accuracy and efficiency of the rescue path planning of robotic dogs, and thus improve the rescue ability and efficiency of robotic dogs in complex rescue environments. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a route planning method and system for the battlefield rescue of robotic dogs, which is beneficial to improving the accuracy and efficiency of the rescue path planning of robotic dogs, and thus improving the rescue ability and efficiency of robotic dogs in complex rescue environments.

[0004] To solve the above technical problem, in the first aspect of the embodiments of the present invention, a route planning method is disclosed, and the method includes: Obtaining basic route point information for the movement of the robotic dog; the basic route point information includes first route point information and second route point information; the first route point information includes a plurality of first sub-route point information; the basic point information includes first basic point information, and / or, second basic point information, and / or, a plurality of third basic point information; the second route point information includes a plurality of reconnaissance point information; Analyzing and processing the basic route point information to obtain first planned path information; the first planned path information includes a plurality of first path area information; Performing planning processing on the first planned path information and the basic route point information to obtain target planned path information.

[0005] In the second aspect of the embodiments of the present invention, a route planning system is disclosed, and the system includes: An acquisition module, configured to acquire basic route point information for the operation of a robotic dog; the basic route point information includes first route point information and second route point information; the first route point information includes a plurality of first sub-route point information; the basic point information includes first basic point information, and / or, second basic point information, and / or, a plurality of third basic point information; the second route point information includes a plurality of reconnaissance point information; A first processing module, configured to analyze and process the basic route point information to obtain first planned path information; the first planned path information includes a plurality of first path area information; A second processing module, configured to perform planning processing on the first planned path information and the basic route point information to obtain target planned path information.

[0006] In the third aspect of the present invention, another route planning system is disclosed, and the system includes: A memory storing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory and executes some or all of the steps in the route planning method disclosed in the first aspect of the embodiments of the present invention.

[0007] In the fourth aspect of the present invention, a computer-readable storage medium is disclosed. The computer-readable storage medium stores computer instructions, and when the computer instructions are called, they are used to execute some or all of the steps in the route planning method disclosed in the first aspect of the embodiments of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0009] Figure 1 is a schematic diagram of the scenario of the route planning system provided by the embodiments of the present invention; Figure 2 is a schematic flowchart of a route planning method disclosed in the embodiments of the present invention; Figure 3 is a schematic structural diagram of a route planning system disclosed in the embodiments of the present invention; Figure 4 is a schematic structural diagram of another route planning system disclosed in the embodiments of the present invention; Figure 5It is a schematic diagram of generating path route points disclosed in an embodiment of the present invention. Detailed implementation manners

[0010] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0011] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0012] Reference to "embodiment" herein means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present invention. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0013] In this application, the word "exemplary" is used to mean "serving as an example, illustration, or description". Any embodiment described as "exemplary" in this application is not necessarily to be construed as more preferred or more advantageous than other embodiments. In order for any person skilled in the art to implement and use this application, the following description is given. In the following description, details are set forth for the purpose of explanation. It should be understood that those of ordinary skill in the art can recognize that this application can be implemented without these specific details. In other instances, well-known structures and processes are not elaborated in detail to avoid unnecessary details from obscuring the description of this application. Therefore, this application is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed in this application.

[0014] It should be noted that since the method of the embodiment of the present application is executed in a computer device, the processing objects of each computer device exist in the form of data or information. For example, time, which is actually time information. It can be understood that in subsequent embodiments, if dimensions, quantities, positions, etc. are mentioned, they are all corresponding data existences for the computer device to process. Details are not elaborated here.

[0015] It should be noted that a brief introduction to the artificial intelligence related technologies that may be involved in the present application is given. Artificial Intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technology in computer science. It attempts to understand the essence of intelligence and produce a new intelligent machine that can react in a way similar to human intelligence. Artificial intelligence is also the study of the design principles and implementation methods of various intelligent machines, enabling the machines to have the functions of perception, reasoning and decision-making.

[0016] Artificial intelligence technology is an interdisciplinary subject, involving a wide range of fields, including both hardware-level technologies and software-level technologies. The basic technologies of artificial intelligence generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, and mechatronics. The software technologies of artificial intelligence mainly include several major directions such as computer vision technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0017] Computer Vision Technology (CV) Computer vision is a science that studies how to enable machines to "see". Further, it refers to using cameras and computers to replace human eyes to identify and measure targets, etc., which is machine vision, and further perform graphic processing to make the computer process the images into a form more suitable for human eyes to observe or transmit to instruments for detection. As a scientific discipline, computer vision studies related theories and technologies, and attempts to establish an artificial intelligence system that can obtain information from images or multi-dimensional data. Computer vision technology usually includes technologies such as image processing, image recognition, image semantic understanding, image retrieval, OCR, video processing, video semantic understanding, video content / behavior recognition, three-dimensional object reconstruction, 3D technology, virtual reality, augmented reality, simultaneous localization and mapping, etc., and also includes common biometric recognition technologies such as face recognition and fingerprint recognition.

[0018] Single-modal information is data of only one type, such as one of the data information of text, image, audio, video, electromagnetic signal, etc. Multi-modal information is data information that includes at least two types of single-modal information. Further, multi-modal information is applicable to complex tasks that require integrating multiple information sources, such as sentiment analysis, robot interaction, autonomous driving, etc. By integrating information of multiple modalities, higher performance and accuracy can usually be achieved in tasks.

[0019] A large model refers to an artificial neural network model with a very large number of parameters. In the field of artificial intelligence, a large model usually refers to a model with hundreds of millions to trillions of parameters. The model usually needs to be trained on a large-scale dataset and requires a large amount of computing resources for optimization and adjustment. Large models are usually used to solve complex natural language processing, computer vision, speech recognition and other tasks. Generative AI is a type of AI that can create new content and ideas, including conversations, stories, images, videos and music. In the embodiments of the present application, the large model can be large-scale pre-trained models such as ChatGPT series, BERT, XLNet, Zhipu model, Claude, Moonshot AI model, ChatGLM model, Tongwen Qianyi model, MiniMax model, Spark model, Llama model, 360GPT model, Qwen model, Baichuan model, Lark model, vivoLM model, deepseek, Tencent Yuanbao and Wenxin Yiyan, etc., and the embodiments of the present application do not make limitations.

[0020] The embodiments of the present application provide a route planning method, system, computer device and computer-readable storage medium, which will be described in detail below respectively.

[0021] Please refer to Figure 1 , Figure 1 which is a schematic diagram of the scenario of the route planning system provided by the embodiments of the present application. The route planning system may include a computer device 100, and the route planning system is integrated in the computer device 100, such as Figure 1 the computer device in

[0022] In the embodiments of the present application, the computer device 100 is mainly used to obtain basic route point information for the operation of the robot dog; the basic route point information includes first route point information and second route point information; the first route point information includes a number of first sub-route point information; the basic point information includes first basic point information, and / or, second basic point information, and / or, a number of third basic point information; the second route point information includes a number of reconnaissance point information; Analyze and process the basic route point information to obtain first planning path information; the first planning path information includes a number of first path area information; Perform planning processing on the first planned path information and the basic route point information to obtain target planned path information.

[0023] It can improve the accuracy and efficiency of the rescue path planning of the robotic dog, and thus improve the rescue ability and efficiency of the robotic dog in a complex rescue environment.

[0024] In the embodiment of the present application, the computer device 100 can be an independent server, or a server network or server cluster composed of servers. For example, the computer device 100 described in the embodiment of the present application includes, but is not limited to, a computer, a network host, a single network server, a set of multiple network servers, or a cloud server composed of multiple servers. Among them, the cloud server is composed of a large number of computers or network servers based on cloud computing.

[0025] It can be understood that the computer device 100 used in the embodiment of the present application can be a device that includes both receiving and transmitting hardware, that is, a device that has the receiving and transmitting hardware capable of performing two-way communication on a two-way communication link. Such devices can include: cellular or other communication devices, which have a single-line display or a multi-line display or a cellular or other communication device without a multi-line display. Specifically, the computer device 100 can specifically be a desktop terminal or a mobile terminal, and the computer device 100 can specifically also be one of a mobile phone, a tablet computer, a laptop computer, etc.

[0026] Those skilled in the art can understand that Figure 1 the application environment shown in Figure 1 is only one application scenario of the solution of the present application, and does not constitute a limitation on the application scenario of the solution of the present application. Other application environments can also include more or fewer computer devices than those shown in Figure 1 For example, only 1 computer device is shown in

[0027] It can be understood that the route planning system can also include one or more other services, which are not specifically limited here. Figure 1 In addition, as shown in

[0028] It should be noted that Figure 1 the scene schematic diagram of the route planning system shown is only an example. The route planning system and the scene described in the embodiment of the present application are for more clearly explaining the technical solution of the embodiment of the present application, and do not constitute a limitation on the technical solution provided by the embodiment of the present application. Those skilled in the art know that with the evolution of the route planning system and the emergence of new business scenarios, the technical solution provided by the embodiment of the present application is equally applicable to similar technical problems.

[0029] The present invention discloses a route planning method and system for a robotic dog's battlefield rescue, which is beneficial to improving the accuracy and efficiency of the robotic dog's rescue path planning, and further enhancing the rescue ability and efficiency of the robotic dog in a complex rescue environment. The following will be described in detail respectively.

[0030] Embodiment 1 Please refer to Figure 2 , Figure 2 which is a schematic flowchart of a route planning method disclosed in an embodiment of the present invention. Among them, Figure 2 the described route planning method is applied in a management system, such as a local server or a cloud server for management, etc., and the embodiments of the present invention do not make limitations. As Figure 2 shown, the route planning method may include the following operations: 101. Obtain the basic route point information for the robotic dog's movement.

[0031] In an embodiment of the present invention, the basic route point information includes first route point information and second route point information; the first route point information includes several first sub-route point information; the basic point information includes first basic point information, and / or, second basic point information, and / or, several third basic point information; the second route point information includes several reconnaissance point information.

[0032] 102. Analyze and process the basic route point information to obtain the first planned path information.

[0033] In an embodiment of the present invention, the first planned path information includes several first path area information.

[0034] 103. Plan and process the first planned path information and the basic route point information to obtain the target planned path information.

[0035] It should be noted that the above-mentioned first basic point information represents the starting point of the robotic dog's movement, and the embodiments of the present invention do not make limitations.

[0036] It should be noted that the above-mentioned second basic point information represents the ending point of the robotic dog's movement, and the embodiments of the present invention do not make limitations.

[0037] It should be noted that the above-mentioned third basic point information represents the points that the robotic dog needs to pass through during the movement process, and the embodiments of the present invention do not make limitations.

[0038] It should be noted that the above-mentioned reconnaissance point information represents the coordinate points that may be used for the robotic dog's movement detected by platforms such as drones, and the embodiments of the present invention do not make limitations.

[0039] It should be noted that the coordinates in this application are constructed based on the UTM coordinate system, and the embodiments of the present invention do not make limitations.

[0040] It should be noted that the above-mentioned target planning path information represents a path for guiding the robot dog to perform a rescue operation, and the embodiment of the present invention does not limit this.

[0041] It can be seen that implementing the route planning method described in the embodiment of the present invention is conducive to improving the accuracy and efficiency of the rescue path planning of the robot dog, thereby improving the rescue capability and efficiency of the robot dog in a complex rescue environment.

[0042] In an optional embodiment, the above-mentioned analysis and processing of the basic route point information to obtain the first planned path information includes: Performing path area closing processing on the second route point information in the basic route point information to obtain first path area information; the first path area information includes a plurality of first sub-path area information; The first path area information is optimized to obtain first planned path information.

[0043] It can be seen that implementing the route planning method described in the embodiment of the present invention is conducive to improving the accuracy and efficiency of the rescue path planning of the robot dog, thereby improving the rescue capability and efficiency of the robot dog in a complex rescue environment.

[0044] In another optional embodiment, performing path area closing processing on the second route point information in the basic route point information to obtain the first path area information includes: Performing area closing processing on the reconnaissance point information in the second route point information to obtain second path area information; the second path area information includes a plurality of reconnaissance path area information; the number of the reconnaissance path area information is greater than or equal to the number of the first sub-path area information; The reconnaissance path area information in the second path area information is subjected to ablation processing of the overlapping area to obtain the first path area information.

[0045] It should be noted that the above-mentioned area closing processing of the reconnaissance point information in the second route point information to obtain the second path area information is to connect the reconnaissance point information to the smallest closed area, that is, starting from one reconnaissance point information, the nearby reconnaissance point information that can enclose the smallest area is connected in sequence counterclockwise to obtain a reconnaissance path area information, which is not limited in the embodiment of the present invention.

[0046] It should be noted that the above-mentioned ablation processing of the overlapping area of ​​the reconnaissance path area information in the second path area information is to remove the overlapping reconnaissance point information of the two overlapping reconnaissance path area information, and then merge them into a new closed area, which is not limited in the embodiment of the present invention.

[0047] It can be seen that implementing the route planning method described in the embodiments of the present invention is beneficial to improving the accuracy and efficiency of the rescue path planning of the robot dog, and further improving the rescue ability and efficiency of the robot dog in a complex rescue environment.

[0048] In another optional embodiment, optimizing the first path region information to obtain the first planned path information includes: Screening the first sub-path region information in the first path region information to obtain the third path region information; the third path region information includes several third sub-path region information; Optimizing the third path region information to obtain the first planned path information.

[0049] It should be noted that the above screening process for the first sub-path region information in the first path region information is to remove the mutually coupled reconnaissance point information in the same sub-path region information, so as to obtain the corresponding third sub-path region information. The embodiments of the present invention do not make limitations. Further, the above mutual coupling means that the distance between two adjacent reconnaissance point information is less than 2 distance units. The embodiments of the present invention do not make limitations. Further, the above distance unit can be 1 meter, 5 meters or 10 meters. The embodiments of the present invention do not make limitations. Further, by removing the mutually coupled reconnaissance point information, the number of analyzed reconnaissance points can be reduced, and the route planning efficiency can be improved without affecting the planning accuracy. The embodiments of the present invention do not make limitations.

[0050] It can be seen that implementing the route planning method described in the embodiments of the present invention is beneficial to improving the accuracy and efficiency of the rescue path planning of the robot dog, and further improving the rescue ability and efficiency of the robot dog in a complex rescue environment.

[0051] In another optional embodiment, optimizing the third path region information to obtain the first planned path information includes: For any third sub-path region information in the third path region information, for any side point in the third sub-path region information, judge whether the side point is located in the region enclosed by the remaining side points of the third sub-path region information, and obtain the first judgment result; When the first judgment result is yes, delete the side point from the third sub-path region information, and update the closed region of the third sub-path region information; When the first judgment result is no, end the analysis and judgment of the side point; Use the updated third sub-path region information as the first path region information corresponding to the third sub-path region information.

[0052] It should be noted that the above-mentioned boundary points represent the endpoints of the line segments. Further, the determination of whether the boundary point is located within the region enclosed by the remaining boundary points of the third sub-path region information is to enclose the other boundary points except this boundary point into a closed region again. If this boundary point is located within this new closed region, it is considered that this boundary point is an abnormal point and does not need to be analyzed and processed in the route planning, so it can be excluded to improve the efficiency and accuracy of the route planning. The embodiments of the present invention do not make any limitations. Further, the boundary points correspond to the reconnaissance point information, and the embodiments of the present invention do not make any limitations.

[0053] It should be noted that the above-mentioned use of the updated third sub-path region information as the first path region information corresponding to the third sub-path region information is the third sub-path region information after analyzing all the boundary points. The embodiments of the present invention do not make any limitations.

[0054] It can be seen that implementing the route planning method described in the embodiments of the present invention is beneficial to improving the accuracy and efficiency of the rescue path planning of the robot dog, and further improving the rescue ability and efficiency of the robot dog in a complex rescue environment.

[0055] In an alternative embodiment, the first planned path information and the basic route point information are processed for planning to obtain the target planned path information, including: Performing an optimization process on the first path region information in the first planned path information to obtain the second planned path information; the second planned path information includes a plurality of second path region information; the second path region corresponding to the second path region information intersects with the line segment connecting the first basic point corresponding to the first basic point information and the second basic point corresponding to the second basic point information; Performing a path point optimization process on the second planned path information and the basic route point information to obtain the target planned path information.

[0056] It should be noted that the intersection of the second path region corresponding to the second path region information with the line segment connecting the first basic point corresponding to the first basic point information and the second basic point corresponding to the second basic point information represents the region between the second path region corresponding to the second path region information and the line segment connecting the first basic point and the second basic point corresponding to the second basic point information. The embodiments of the present invention do not make any limitations.

[0057] It should be noted that the above-mentioned optimization process on the first path region information in the first planned path information is to exclude the regions that the robot dog will not go to, so as to reduce the calculation amount and interference factors of the route planning, thereby improving the efficiency and accuracy of the route planning. The embodiments of the present invention do not make any limitations.

[0058] It can be seen that implementing the route planning method described in the embodiments of the present invention is beneficial to improving the accuracy and efficiency of the rescue path planning of the robotic dog, and further improving the rescue ability and efficiency of the robotic dog in a complex rescue environment.

[0059] In another optional embodiment, path point optimization processing is performed on the second planned path information and the basic route point information to obtain target planned path information, including: Based on the basic route point information, path line information is determined; the path line includes several path lines; the path line represents the connection line of the basic points corresponding to two adjacent first sub-route point information; For any second path area information in the second planned path information, the path lines that intersect with the second path area corresponding to the second path area information are screened out from the path lines as target path lines; Path point generation processing is performed on the target path line and the second path area information to obtain path route point information corresponding to the second path area information; The basic route point information is optimized and updated by using the path route point information; The optimized and updated basic route point information is used as the target planned path information.

[0060] It should be noted that the above path line represents a vector pointing from the basic point corresponding to the previous first sub-route point information to the basic point corresponding to the next first sub-route point information, and the embodiments of the present invention do not make any limitations.

[0061] It should be noted that the above path route point information includes a first path route point and a second path route point, and the embodiments of the present invention do not make any limitations.

[0062] It should be noted that the path distance from the above first path route point to the basic point corresponding to the first basic point information is not greater than the path distance from the second path route point to the basic point corresponding to the first basic point information, and the embodiments of the present invention do not make any limitations.

[0063] It should be noted that the above-mentioned use of the optimized and updated basic route point information as the target planned path information is to use the basic route point information finally optimized and updated by the path route point information as the target planned path information only after analyzing and processing all the second path area information, and the embodiments of the present invention do not make any limitations.

[0064] It should be noted that the above target path line includes a first target path point and a second target path point, and the embodiments of the present invention do not make any limitations.

[0065] In this alternative embodiment, as an alternative implementation, the above processing of generating path points for the target path line and the second path region information to obtain the path route point information corresponding to the second path region information includes: For any one of the boundary lines that make up the region corresponding to the second path region information, a vector construction is performed between the boundary line and the target path line to obtain boundary vector information; the boundary line is a line segment composed of a first boundary endpoint and a second boundary endpoint; the boundary vector information includes a first boundary vector pointing from the first target path point to the first boundary endpoint, a second boundary vector pointing from the first target path point to the second boundary endpoint, a third boundary vector pointing from the second target path point to the first boundary endpoint, and a fourth boundary vector pointing from the second target path point to the second boundary endpoint; Using a first vector calculation model to perform calculation processing on the boundary vector information to obtain vector angle information; the vector angle information includes a first vector angle and a second vector angle; Wherein, the first vector calculation model is: ; In the formula, and respectively represent the first vector angle and the second vector angle; , , and respectively represent the first boundary vector, the second boundary vector, the third boundary vector, and the fourth boundary vector; Using a second vector calculation model to perform calculation processing on the boundary vector information and the target path line to obtain vector distance information; the vector distance information includes a first vector distance and a second vector distance; Wherein, the second vector calculation model is: ; In the formula, and respectively represent the first vector distance and the second vector distance; represents the target path line; When the product of the first vector angle and the second vector angle in the vector angle information is less than 0, and the first vector distance and the second vector distance in the vector distance information are not greater than 0, the boundary line is taken as a first intersecting boundary line; Obtain the maximum distance from the endpoints in the region corresponding to the second path region information to the target path line; If the product of the maximum distance and the second vector distance is not less than 0, use the first path point model to perform calculation processing on the first intersecting boundary line to obtain the path route point information corresponding to the first intersecting boundary line; the path route point information includes a first path route point and a second path route point; Wherein, the first path point model is: ; In the formula, and respectively represent the coordinates corresponding to the first path route point and the second path route point; and represent the coordinates of the second end point of the boundary line and the coordinates of the second end point of another boundary line that intersects simultaneously in the area corresponding to the second path area information when the target path line intersects with the boundary line; and respectively represent the vector from the first end point to the second end point of the boundary line and the vector from the first end point to the second end point of another boundary line that intersects simultaneously in the area corresponding to the second path area information when the target path line intersects with the boundary line; represents the minimum turning radius of the robotic dog; If the product of the maximum distance and the second vector distance is less than 0, the first intersection boundary line is calculated and processed using the second path point model to obtain the path route point information corresponding to the first intersection boundary line; the path route point information includes the first path route point and the second path route point; Among them, the second path point model is: ; In the formula, and represent the coordinates of the first end point of the boundary line and the coordinates of the first end point of another boundary line that intersects simultaneously in the area corresponding to the second path area information when the target path line intersects with the boundary line; and respectively represent the vector from the second end point to the first end point of the boundary line and the vector from the second end point to the first end point of another boundary line that intersects simultaneously in the area corresponding to the second path area information when the target path line intersects with the boundary line; Otherwise, end the analysis and judgment of the boundary line; All the path route point information is supplemented to the first route point information in coordinate order to obtain the target planned path information.

[0066] It should be noted that the above and are the end points on the same side of the target path line, that is, both are the second end points, and those on the other side are the first end points. The embodiments of the present invention do not make any limitations.

[0067] For example, such as Figure 5As shown, when the boundary line is D1D2, the first target path point and the second target path point in the target path line are Y2 and Y1 (the vector from Y2 to Y1) respectively. The first boundary vector is the vector from Y2 to D1, and the second boundary vector is the vector from Y2 to D2; the third boundary vector is the vector from Y1 to D1, and the fourth boundary vector is the vector from Y1 to D2. The embodiments of the present invention do not make any limitations. Further, the maximum distance from the end point in the area corresponding to the second path area information to the target path line is Figure 5 JL0 in Figure 5 . Further, JL1 or JL2 can be less than 0, which is a value calculated by the second vector calculation model. The embodiments of the present invention do not make any limitations.

[0068] It can be seen that implementing the route planning method described in the embodiments of the present invention is beneficial to improving the accuracy and efficiency of the rescue path planning of the robotic dog, and further improving the rescue ability and efficiency of the robotic dog in a complex rescue environment.

[0069] Embodiment 2 Please refer to Figure 3 , Figure 3 which is a schematic structural diagram of a route planning system disclosed in the embodiments of the present invention. Among them, Figure 3 the described system can be applied to a management system, such as a local server or a cloud server for management, etc. The embodiments of the present invention do not make any limitations. As Figure 3 shown, the system may include: An acquisition module 201, configured to acquire basic route point information for the movement of the robotic dog; the basic route point information includes first route point information and second route point information; the first route point information includes several first sub-route point information; the basic point information includes first basic point information, and / or, second basic point information, and / or, several third basic point information; the second route point information includes several reconnaissance point information; A first processing module 202, configured to analyze and process the basic route point information to obtain first planning path information; the first planning path information includes several first path area information; A second processing module 203, configured to perform planning processing on the first planning path information and the basic route point information to obtain target planning path information.

[0070] It can be seen that implementing Figure 3 the described route planning system is beneficial to improving the accuracy and efficiency of the rescue path planning of the robotic dog, and further improving the rescue ability and efficiency of the robotic dog in a complex rescue environment.

[0071] In another alternative embodiment, as Figure 3 shown, analyzing and processing the basic route point information to obtain the first planning path information includes: Perform path area closing processing on the second route point information in the basic route point information to obtain the first path area information; the first path area information includes several first sub-path area information; Perform optimization processing on the first path area information to obtain the first planned path information.

[0072] It can be seen that implementing Figure 3 the described route planning system is beneficial to improving the accuracy and efficiency of the rescue path planning of the robot dog, and further improving the rescue ability and efficiency of the robot dog in a complex rescue environment.

[0073] In another alternative embodiment, as Figure 3 shown, performing path area closing processing on the second route point information in the basic route point information to obtain the first path area information includes: Perform area closing processing on the reconnaissance point information in the second route point information to obtain the second path area information; the second path area information includes several reconnaissance path area information; the number of reconnaissance path area information is greater than or equal to the number of first sub-path area information; Perform ablation processing on the overlapping areas of the reconnaissance path area information in the second path area information to obtain the first path area information.

[0074] It can be seen that implementing Figure 3 the described route planning system is beneficial to improving the accuracy and efficiency of the rescue path planning of the robot dog, and further improving the rescue ability and efficiency of the robot dog in a complex rescue environment.

[0075] In another alternative embodiment, as Figure 3 shown, performing optimization processing on the first path area information to obtain the first planned path information includes: Perform screening processing on the first sub-path area information in the first path area information to obtain the third path area information; the third path area information includes several third sub-path area information; Perform optimization processing on the third path area information to obtain the first planned path information.

[0076] It can be seen that implementing Figure 3 the described route planning system is beneficial to improving the accuracy and efficiency of the rescue path planning of the robot dog, and further improving the rescue ability and efficiency of the robot dog in a complex rescue environment.

[0077] In another alternative embodiment, as Figure 3 shown, performing optimization processing on the third path area information to obtain the first planned path information includes: For any third sub-path region information in the third path region information, for any edge point in the third sub-path region information, determine whether the edge point is located within the region enclosed by the remaining edge points of the third sub-path region information to obtain a first judgment result; When the first judgment result is yes, delete the edge point from the third sub-path region information, and perform an update process on the closed region of the third sub-path region information; When the first judgment result is no, end the analysis and judgment of the edge point; Use the updated third sub-path region information as the first path region information corresponding to the third sub-path region information.

[0078] It can be seen that implementing Figure 3 the described route planning system is beneficial to improving the accuracy and efficiency of the rescue path planning of the robotic dog, and thus improving the rescue ability and efficiency of the robotic dog in a complex rescue environment.

[0079] In another alternative embodiment, as Figure 3 shown, perform a planning process on the first planned path information and the basic route point information to obtain the target planned path information, including: Perform an optimization process on the first path region information in the first planned path information to obtain the second planned path information; the second planned path information includes several second path region information; the second path region corresponding to the second path region information intersects with the line segment connecting the first basic point corresponding to the first basic point information and the second basic point corresponding to the second basic point information; Perform a path point optimization process on the second planned path information and the basic route point information to obtain the target planned path information.

[0080] It can be seen that implementing Figure 3 the described route planning system is beneficial to improving the accuracy and efficiency of the rescue path planning of the robotic dog, and thus improving the rescue ability and efficiency of the robotic dog in a complex rescue environment.

[0081] In another alternative embodiment, as Figure 3 shown, perform a path point optimization process on the second planned path information and the basic route point information to obtain the target planned path information, including: Based on the basic route point information, determine the path line information; the path line includes several path lines; the path line represents the connection line of the basic points corresponding to two adjacent first sub-route point information; For any second path region information in the second planned path information, screen out the path lines that intersect with the second path region corresponding to the second path region information as the target path lines; Perform path point generation processing on the target path line and the second path region information to obtain the path route point information corresponding to the second path region information; Perform optimization and update processing on the basic route point information using the path route point information; Use the optimized and updated basic route point information as the target planning path information.

[0082] It can be seen that implementing Figure 3 the described route planning system is beneficial to improving the accuracy and efficiency of the rescue path planning of the robotic dog, and thus improving the rescue ability and efficiency of the robotic dog in a complex rescue environment.

[0083] Embodiment III Please refer to Figure 4 , Figure 4 which is a schematic structural diagram of another route planning system disclosed in the embodiments of the present invention. Among them, Figure 4 the described system can be applied to a management system, such as a local server or a cloud server for management, etc., which is not limited in the embodiments of the present invention. As Figure 4 shown, the system may include: A memory 301 storing executable program code; A processor 302 coupled to the memory 301; The processor 302 calls the executable program code stored in the memory 301 to execute the steps in the route planning method described in Embodiment I.

[0084] Embodiment IV The embodiments of the present invention disclose a computer-readable storage medium that stores a computer program for electronic data exchange, wherein the computer program causes a computer to execute the steps in the route planning method described in Embodiment I.

[0085] Embodiment V The embodiments of the present invention disclose a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps in the route planning method described in Embodiment I.

[0086] The system embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place, or may be distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0087] Through the specific descriptions of the above embodiments, those skilled in the art can clearly understand that each implementation can be realized by means of software plus a necessary general hardware platform, and of course, it can also be realized by hardware. Based on such an understanding, the above technical solution, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memories, magnetic disc memories, tape memories, or any other computer-readable medium capable of carrying or storing data.

[0088] Finally, it should be noted that: what is disclosed in an embodiment of the present invention for a route planning method and system for a robotic dog battlefield rescue is only the preferred embodiment of the present invention, and is only used to illustrate the technical solution of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A route planning method, characterized in that: The method comprises: Obtaining basic route point information for the robot dog's action; the basic route point information includes first route point information and second route point information; the first route point information includes a plurality of first sub-route point information; the basic point information includes first basic point information, and / or second basic point information, and / or a plurality of third basic point information; the second route point information includes a plurality of scout point information; Analyze and process the basic route point information to obtain first planned path information; the first planned path information includes a plurality of first path area information; The first planned path information and the basic route point information are planned and processed to obtain target planned path information.

2. The route planning method according to claim 1, characterized in that: The analyzing and processing the basic route point information to obtain the first planned path information includes: Performing path area closing processing on the second route point information in the basic route point information to obtain first path area information; the first path area information includes a plurality of first sub-path area information; The first path area information is optimized to obtain first planned path information.

3. The route planning method according to claim 2, characterized in that: The performing path area closing processing on the second route point information in the basic route point information to obtain first path area information includes: Performing area closing processing on the reconnaissance point information in the second route point information to obtain second path area information; the second path area information includes a plurality of reconnaissance path area information; the number of the reconnaissance path area information is greater than or equal to the number of the first sub-path area information; The overlapping area of ​​the reconnaissance path area information in the second path area information is subjected to ablation processing to obtain the first path area information.

4. The route planning method according to claim 2, characterized in that: The optimizing the first path area information to obtain the first planned path information includes: The first sub-path area information in the first path area information is filtered to obtain third path area information; the third path area information includes a plurality of third sub-path area information; The third path area information is optimized to obtain the first planned path information.

5. The route planning method according to claim 4, characterized in that: The optimizing the third path area information to obtain the first planned path information includes: For any of the third sub-path area information in the third path area information, for any edge point in the third sub-path area information, determine whether the edge point is located in the area surrounded by the remaining edge points of the third sub-path area information to obtain a first determination result; When the first judgment result is yes, the edge point is deleted from the third sub-path area information, and the closed area of ​​the third sub-path area information is updated; When the first judgment result is no, the analysis and judgment of the edge point is terminated; The updated third sub-path area information is used as the first path area information corresponding to the third sub-path area information.

6. The route planning method according to claim 1, characterized in that: The planning and processing of the first planned path information and the basic route point information to obtain target planned path information includes: The first path area information in the first planned path information is preferentially processed to obtain second planned path information; the second planned path information includes a plurality of second path area information; the second path area corresponding to the second path area information intersects with a line segment connecting a first basic point corresponding to the first basic point information and a second basic point corresponding to the second basic point information; The second planned path information and the basic route point information are subjected to path point optimization processing to obtain target planned path information.

7. The route planning method according to claim 6, characterized in that: The performing path point optimization processing on the second planned path information and the basic route point information to obtain target planned path information includes: Based on the basic route point information, path line information is determined; the path line includes a plurality of path lines; the path line represents a line connecting two adjacent basic points corresponding to the first sub-route point information; For any of the second path area information in the second planned path information, screening out from the path lines the path line that intersects with the second path area corresponding to the second path area information as a target path line; Performing path point generation processing on the target path line and the second path area information to obtain path route point information corresponding to the second path area information; Utilizing the path route point information to optimize and update the basic route point information; The optimized and updated basic route point information is used as the target planning path information.

8. A route planning system, characterized in that: The system comprises: An acquisition module, used for acquiring basic route point information for the robot dog's action; the basic route point information includes first route point information and second route point information; the first route point information includes a plurality of first sub-route point information; the basic point information includes first basic point information, and / or second basic point information, and / or a plurality of third basic point information; the second route point information includes a plurality of scout point information; A first processing module, configured to analyze and process the basic route point information to obtain first planned path information; the first planned path information includes a plurality of first path area information; The second processing module is used to perform planning processing on the first planned path information and the basic route point information to obtain target planned path information.

9. A route planning system, characterized in that: The system comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the route planning method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the route planning method according to any one of claims 1 to 7.

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