Visual simulation method and device for multi-agent planning path and electronic equipment

Abstract

The invention relates to a visual simulation method and device for a multi-agent planning path and electronic equipment, relates to the field of computers, and solves the problems of low flexibility and low efficiency when visual simulation is carried out on multi-agent scheduling in the prior art. The visual simulation method for the multi-agent planning path comprises the following steps: step S100: performing assignment on the state of a grid in a spreadsheet to construct an environment scene; s200, generating a starting point and an ending point of each agent in the environment scene by setting coordinate types of grids in the spreadsheet; step S300, importing a path planning algorithm of each agent; step S400, calculating a planned path of each agent in the environment scene according to the path planning algorithm of each agent and the starting point and the ending point of each agent; and step S500, moving the intelligent agent according to the planning path of each intelligent agent, and displaying the grid to which the intelligent agent arrives every time in a pattern determined by the intelligent agent.

Description

Technical Field

[0001] The present invention relates to the field of computers, and in particular to a visual simulation method, device and electronic equipment for planning paths of multiple intelligent agents. Background Art

[0002] Path planning refers to the process of finding the best path from the starting point to the end point in a given environment. It has a wide range of applications in real life, including unmanned driving, logistics distribution, robot navigation and other fields. With the development of artificial intelligence and computer technology, path planning technology is also constantly being improved and applied. Path planning algorithm visualization is a technology that displays the calculation results of the path planning algorithm in a graphical way, which helps users intuitively understand the path planning process and results.

[0003] Traditional path planning algorithm visualization methods are based on existing commercial software and customized development. They are not flexible enough when developing certain functions and must rely on other components of commercial software for overall implementation. In addition, traditional path planning algorithm visualization methods often focus on single agents and do not provide sufficient support for multi-agents. Summary of the invention

[0004] In view of the above analysis, an embodiment of the present invention aims to provide a method, device and electronic device for visual simulation of the planning path of multiple agents, so as to solve the problem of low flexibility and low efficiency in the prior art when performing visual simulation on the scheduling of multiple agents.

[0005] In a first aspect, an embodiment of the present invention provides a method for visual simulation of a planning path of a multi-agent, comprising the following steps:

[0006] Step S100: constructing an environment scene by assigning values ​​to the states of the grids in the electronic form;

[0007] Step S200: generating the starting point and the end point of each agent in the environment scene by setting the coordinate type of the grid in the electronic table;

[0008] Step S300: importing the path planning algorithm of each agent;

[0009] Step S400: Calculate the planned path of each agent in the environment scene according to the path planning algorithm of each agent and its starting point and end point; and

[0010] Step S500: Move each agent according to the planned path and display the grid where the agent moves forward each step in a style determined by the agent.

[0011] Based on the further improvement of the above visual simulation method, before executing step S500, the visual simulation method further includes:

[0012] The planned path of each agent in the environment scene is pre-displayed in a style determined by the agent.

[0013] Based on further improvement of the above visual simulation method, the state of the grid includes an occupied state and a non-occupied state, the state value of the occupied state is 1, and the state value of the non-occupied state is 0.

[0014] Based on the further improvement of the above visual simulation method, the assigning of the state of the grid in the electronic form includes:

[0015] A table file in a first format is imported, wherein the value edited in each cell in the table file in the first format corresponds to the state value of the grid in the electronic spreadsheet.

[0016] Based on the further improvement of the above visual simulation method, the setting of the coordinate type of the grid in the electronic form includes:

[0017] Import a table file in the second format, wherein the table file in the second format includes cells in two columns and multiple rows, the cells in the first column represent the starting point, the cells in the second column represent the end point, the cells in each row represent an agent, and the value edited in each cell is the coordinate of the grid in the electronic spreadsheet.

[0018] Based on the further improvement of the above visual simulation method, the path planning algorithm imported into each agent includes:

[0019] Import a path planning class for each agent written in Python, where the path planning class is a path planning algorithm.

[0020] Based on the further improvement of the above visual simulation method, the style determined by the agent includes:

[0021] Each of the agents fills a grid in the spreadsheet with a corresponding color value.

[0022] Based on the further improvement of the above visual simulation method, the path planning algorithm is any one of the following:

[0023] A* path planning algorithm, bidirectional A* path planning algorithm, Dijkstra algorithm.

[0024] In a second aspect, an embodiment of the present invention provides a visual simulation device for planning paths of multiple agents, comprising:

[0025] A scene building module is configured to build an environment scene by assigning values ​​to states of grids in a spreadsheet;

[0026] A setting module, which is configured to generate a starting point and an end point of each intelligent agent in the environment scene by setting a coordinate type of a grid in the electronic table;

[0027] An import module configured to import the path planning algorithm of each agent;

[0028] A calculation module, configured to calculate a planned path of each agent in the environment scene according to the path planning algorithm of each agent and its starting point and end point;

[0029] The display module is configured to move each agent according to the planned path and display a grid where the agent moves each step forward in a style determined by the agent.

[0030] In a second aspect, an embodiment of the present invention provides an electronic device, including:

[0031] at least one processor; and

[0032] A memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the visual simulation method described in any one of the first aspects of the present invention.

[0033] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0034] 1. The embodiment of the present invention uses a highly compatible electronic spreadsheet to perform visual simulation of environmental scenarios and multi-agent path planning algorithms, thereby realizing an efficient and flexible multi-agent scheduling visualization method that can accelerate the development and deployment of multi-intelligent applications.

[0035] 2. The interaction between the embodiment of the present invention and the user is relatively friendly, especially in terms of support for third-party software such as Excel.

[0036] 3. In the embodiment of the present invention, the environment scene and the path planning algorithm of the intelligent agent are loosely coupled, so that different personnel can work together.

[0037] In the present invention, the above-mentioned technical solutions can also be combined with each other to achieve more preferred combination solutions. Other features and advantages of the present invention will be described in the subsequent description, and some advantages can become obvious from the description, or can be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained through the contents particularly pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings are only used for the purpose of illustrating specific embodiments and are not to be considered as limiting the present invention. In the entire drawings, the same reference symbols represent the same components;

[0039] Figure 1 A schematic flow chart of a method for visual simulation of multi-agent path planning according to an embodiment of the present invention is shown.

[0040] Figure 2 An example of an electronic form according to an embodiment of the present invention is shown.

[0041] Figure 3 An example of setting the state of a grid in an electronic table according to a table file in a first format in an embodiment of the present invention is shown.

[0042] Figure 4 An example of rendering the status value of a grid in a spreadsheet according to an embodiment of the present invention is shown.

[0043] Figure 5 An example of setting the coordinate type of a grid in a spreadsheet according to a table file in the second format in an embodiment of the present invention is shown.

[0044] Figure 6 An example of rendering a grid according to the coordinate type of the grid in a spreadsheet in an embodiment of the present invention is shown.

[0045] Figure 7 and Figure 8 The following are simulation diagrams of two stages of moving an intelligent agent according to a planned path in an embodiment of the present invention.

[0046] Fig. 9 An exemplary block diagram of a visual simulation device for planning paths of multiple agents according to an embodiment of the present invention is shown.

[0047] Fig.10 A schematic block diagram of an example electronic device 1000 is shown that can be used to implement embodiments of the present disclosure. DETAILED DESCRIPTION

[0048] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0049] Figure 1 FIG. 2 is a flow chart showing a method for visualizing and simulating a multi-agent planning path according to an embodiment of the present invention. Figure 1 As shown, the visual simulation method of the multi-agent planning path includes the following steps:

[0050] Step S100: constructing an environment scene by assigning values ​​to the states of the grids in the electronic form.

[0051] The environmental scenario refers to the simulated space environment in which the agent is located, in which the path planning algorithm of the agent can be simulated.

[0052] Figure 2 An example of an electronic form according to an embodiment of the present invention is shown. Figure 2 As shown, the length of the electronic form is 49 and the width is 23. The content in each grid is empty, and the electronic form is a blank electronic form. In this embodiment, a blank electronic form can be formed by constructing an empty blank matrix with a length of X and a width of Y. In this embodiment, each grid in the electronic form represents a simulation space that can be occupied by a single agent, and the state of each grid can take a value of 0 or 1. The state of the grid is 0, which means that the grid is not occupied, and the state of the grid is 1, which means that the grid is occupied. In this embodiment, the default state of the grid can be unoccupied. Occupied means that the agent cannot pass through or reach; unoccupied means that the agent can pass through or reach.

[0053] In some embodiments, the state of a grid can be added or modified manually on the grid of the spreadsheet. When the state of a grid is set to 1, it means that the agent cannot reach this grid; when the state of a grid is not set or is set to 0, it means that the agent can pass through or reach this grid, or the agent can be initialized in this grid. The agent in this embodiment can be a drone or a smart car, etc.

[0054] In some embodiments, the state of each grid in the electronic table can be set by importing a table file in the first format. In the table file in the first format, 1 can be set on some cells according to the size of length X and width Y, and other cells that are not set are defaulted to 0. Setting it to 1 means that the grid agent corresponding to this cell is unreachable, and not setting it or setting it to 0 means that the grid agent corresponding to this cell can be initialized, passed through, and reached. Figure 3FIG. 2 shows an example of setting the state of a grid in an electronic table according to a table file in a first format in an embodiment of the present invention. Figure 3 As shown, the state of the corresponding grid of the electronic table can be set by filling 1 in each cell of the Excel file of the first format. Figure 3 In the example, the length and width of the cell array in the Excel file of the first format may correspond to the length and width of the electronic table, respectively. For example, the value in the cell of the Mth row and the Nth column in the Excel file of the first format is the state value of the grid of the Mth row and the Nth column in the electronic table.

[0055] In this embodiment, after the states of the grids in the electronic form are assigned values, each grid may be rendered according to the result of the assignment of the state of each grid. Figure 4 FIG. 2 shows an example of rendering the state value of a grid in a spreadsheet according to an embodiment of the present invention. Figure 4 As shown, a grid filled with pure black squares means that the state value of the grid is 1, and a grid without any content means that the state value of the grid is 0. In this embodiment, the construction of the environment scene is completed after each grid is rendered according to the state value of each grid. Figure 4 That is, an example of an environmental scene according to an embodiment of the present invention is shown.

[0056] Step S200: Generate the starting point and end point of each agent in the environment scene by setting the coordinate type of the grid in the electronic table.

[0057] In this embodiment, the coordinate type of the grid can be the starting point or end point of one or more agents. For example, there are four agents, namely agent 1, agent 2, agent 3 and agent 4, then the coordinate type of the grid can include the starting point and end point of agent 1, the starting point and end point of agent 2, the starting point and end point of agent 3 and the starting point and end point of agent 4.

[0058] In some embodiments, the coordinate type of the grid can be added or modified manually on the grid of the spreadsheet. The coordinate type of the grid is represented by a two-dimensional array, the first dimension represents the serial number of the agent, and the second dimension represents the starting point or the end point. The second dimension can use A to represent the starting point and B to represent the end point. For example, when the coordinate type of a grid is set to [1, A], it means that the grid is set as the starting point of agent 1; when the coordinate type of the grid is set to [1, B], it means that the grid is set as the end point of agent 1; when the coordinate type of the grid is set to [3, A], it means that the grid is set as the starting point of agent 3, and so on. In the above example, the coordinate type of the grid is represented by a two-dimensional array, the first dimension data specifies which specific agent it is, and the second dimension data specifies whether it is the starting point or the end point.

[0059] In some embodiments, the coordinate type of each grid in the electronic table can be set by importing a table file in the second format. In the table file in the second format, the coordinates of some grids in the electronic table can be edited on each cell according to the size of R rows and 2 columns. In the table file in the second format, the first column represents the starting point, which can be represented by the letter "A", and the second column represents the end point, which can be represented by the letter "B"; the first row to the Rth row represent agent 1 to agent R respectively. Figure 5 An example of setting the coordinate type of a grid in an electronic table according to a table file in the second format in an embodiment of the present invention is shown. Figure 5 As shown, the coordinates of a grid in the spreadsheet can be filled in each cell in the Excel file of the second format. For example, the cell in the first row and column A is filled with "2,23", which means that the grid in the second row and column 23 in the spreadsheet is set as the starting point of agent 1; the cell in the seventh row and column A is filled with "22,23", which means that the grid in the 22nd row and column 23 in the spreadsheet is set as the starting point of agent 7, and so on.

[0060] In this embodiment, after the coordinate type of the grid in the electronic form is set, each grid can be rendered according to the coordinate type. In this embodiment, the grid can be rendered by filling different identifiers into the grid, and the filled identifier type can be determined by the coordinate type of each grid. Exemplarily, the grid as the starting point can be filled with an identifier of a first shape, and the grid as the end point can be filled with an identifier of a second shape, and different agents use different color identifiers.

[0061] Figure 6 FIG. 2 shows an example of rendering a grid according to the coordinate type of the grid in the electronic table in an embodiment of the present invention. Figure 6As shown, the grid as the starting point can be filled with a circular mark, and the grid as the end point can be filled with a square mark. Different agents are marked with different colors, for example, the starting point and end point of agent 1 are represented by dark green, and the starting point and end point of agent 5 are represented by red.

[0062] Step S300: Import the path planning algorithm of each agent.

[0063] In this embodiment, the path planning algorithm and the visualization method of the planned path (i.e. Figure 1 The method shown in the figure can be decoupled, so the path planning algorithm of a third party can be integrated into the visualization method of planning the path. In some embodiments, importing the path planning algorithm of each agent can be importing a path planning class for each agent written in Python. In Python, a class is the basis of object-oriented programming (OOP), and a class is a data type that allows attributes and methods to be defined as an object. The method of the path planning class can be defined as a path planning algorithm, and the import of the path planning algorithm can be achieved by calling the method of the path planning class. In some embodiments, the path planning algorithm can be any one of the following: an A* path planning algorithm, a bidirectional A* path planning algorithm, and a Dijkstra algorithm.

[0064] Step S400: Calculate the planned path of each agent in the environment scene according to the path planning algorithm of each agent and its starting point and end point.

[0065] In this embodiment, a path from the starting point to the end point can be formed according to the environment scene and the path planning algorithm. Taking the A* path planning algorithm as an example, when searching for a path in the environment scene, the starting point can be first placed in the open set, and then the sum of the cost and the heuristic value of the adjacent nodes is traversed and calculated and added to the open set; in each iteration, the node with the minimum cost in the open set is selected, and a child node is generated for it and the parent node is added to the closed set. If the generated child node collides with an obstacle in the environment scene (for example, the state value of the grid is 1) or is already in the closed set, the child node is skipped; if the generated child node is already in the open set, whether to update the sum of its cost and heuristic value is selected according to whether the current generation method is more preferred; if the generated child node is the end point, it is added to the closed set, the algorithm ends, and the shortest planning path can be generated by tracing back to the starting point along the parent node pointer.

[0066] Step S500: Move each agent according to the planned path and display the grid where the agent moves forward each step in a style determined by the agent.

[0067] Figure 7 and Figure 8 Schematic diagrams of simulation of two stages of moving an intelligent agent according to a planned path in an embodiment of the present invention are shown respectively. Figure 7 and Figure 8 As shown in the figure, the planned path of each agent is represented by a corresponding light color. For example, the planned path of agent 5 is represented by light red (red is the color of agent 5), the planned path of agent 1 is represented by light green (green is the color of agent 1), and so on. In the simulation stage, it can be determined whether all agents are at their terminal positions. If any agent is not at the terminal position, the path planning algorithm of each agent continues to iterate until the simulation process ends. For example, in Figure 7 In the current stage, agent 5 has not yet reached the end point (i.e., the grid filled with red squares), so in the next stage, each agent can move forward one step according to its planned path. Figure 8 In the simulation, all agents have reached their final positions, so the simulation ends.

[0068] In some embodiments, before executing step S500, Figure 1 The method further comprises the following steps: pre-displaying the planned path of each agent in the environment scene in a style determined by the agent. In this embodiment, the style determined by the agent can be that each agent fills a grid in the electronic table with a corresponding color value. Figure 8 Also shown is an example diagram of a pre-display of the planned path of each agent according to an embodiment of the present invention. Figure 8 As shown, the planned path of each agent is filled with the corresponding light-colored square. For example, the planned path of agent 5 is filled with light red squares (red is the color of agent 5), the planned path of agent 1 is filled with light green squares (green is the color of agent 1), and so on.

[0069] Compared with the prior art, the embodiments of the present invention can achieve at least one of the following beneficial effects:

[0070] 1. The embodiment of the present invention uses a highly compatible electronic spreadsheet to perform visual simulation of environmental scenarios and multi-agent path planning algorithms, thereby realizing an efficient and flexible multi-agent scheduling visualization method that can accelerate the development and deployment of multi-intelligent applications.

[0071] 2. The interaction between the embodiment of the present invention and the user is relatively friendly, especially in terms of support for third-party software such as Excel.

[0072] 3. In the embodiment of the present invention, the environment scene and the path planning algorithm of the intelligent agent are loosely coupled, so that different personnel can work together.

[0073] Fig. 9 FIG. 2 shows an exemplary block diagram of a visual simulation device for planning paths of multiple agents according to an embodiment of the present invention. Fig. 9 As shown, the visualization simulation device 900 for planning paths of multiple agents comprises: a scene construction module 901, which is configured to construct an environment scene by assigning values ​​to the states of grids in a spreadsheet; a setting module 902, which is configured to generate the starting point and the end point of each agent in the environment scene by setting the coordinate type of the grids in the spreadsheet; an import module 903, which is configured to import the path planning algorithm of each agent; a calculation module 904, which is configured to calculate the planned path of each agent in the environment scene according to the path planning algorithm of each agent and its starting point and end point; and a display module 905, which is configured to move the agent according to the planned path of each agent and display the grid reached by the agent at each step forward in a style determined by the agent.

[0074] It should be understood that Fig. 9 The various modules of the apparatus 900 shown in FIG. Figure 1 The steps in the described method correspond to each other. Therefore, the operations, features and advantages described above for the method are also applicable to the device 900 and the modules included therein. For the sake of brevity, some operations, features and advantages are not repeated here.

[0075] Fig.10 1 shows a schematic block diagram of an example electronic device 1000 that can be used to implement an embodiment of the present disclosure. Fig.10 , a structural block diagram of an electronic device 1000 that can serve as a server or client of the present disclosure will now be described, which is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device can 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 merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein. Fig.10As shown, the electronic device 1000 includes a computing unit 1001, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1002 or a computer program loaded from a storage unit 1008 into a random access memory (RAM) 1003. In RAM 1003, various programs and data required for the operation of the device 1000 can also be stored. The computing unit 1001, ROM 1002, and RAM 1003 are connected to each other via a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004. Multiple components in the device 1000 are connected to the I / O interface 1005, including: an input unit 1006, such as a keyboard, a mouse, etc.; an output unit 1007, such as various types of displays, speakers, etc.; a storage unit 1008, such as a disk, an optical disk, etc.; and a communication unit 1009, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 1009 allows the device 1000 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0076] The computing unit 1001 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 1001 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 1001 performs the various methods and processes described above, such as a visual simulation method for planning paths of multiple agents. For example, in some embodiments, the visual simulation method for planning paths of multiple agents may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 1008. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 1000 via ROM 1002 and / or the communication unit 1009. When the computer program is loaded into RAM 1003 and executed by the computing unit 1001, one or more steps of the gift package recommendation method described above may be executed. Alternatively, in other embodiments, the computing unit 1001 may be configured in any other appropriate manner (eg, by means of firmware) to execute a visual simulation method for planning paths of multiple agents.

[0077] Compared with the prior art, the embodiments of the present invention can achieve at least one of the following beneficial effects:

[0078] 1. The embodiment of the present invention uses a highly compatible electronic spreadsheet to perform visual simulation of environmental scenarios and multi-agent path planning algorithms, thereby realizing an efficient and flexible multi-agent scheduling visualization method that can accelerate the development and deployment of multi-intelligent applications.

[0079] 2. The interaction between the embodiment of the present invention and the user is relatively friendly, especially in terms of support for third-party software such as Excel.

[0080] 3. In the embodiment of the present invention, the environment scene and the path planning algorithm of the intelligent agent are loosely coupled, so that different personnel can work together.

[0081] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A visual simulation method for planning paths of multiple agents, characterized in that: The steps include: Step S100: constructing an environment scene by assigning values ​​to the states of the grids in the electronic form; Step S200: generating the starting point and the end point of each agent in the environment scene by setting the coordinate type of the grid in the electronic table; Step S300: importing the path planning algorithm of each agent; Step S4 00: Calculate the planned path of each agent in the environment scene according to the path planning algorithm of each agent and its starting point and end point; as well as Step S500: Move each agent according to the planned path and display the grid where the agent moves forward each step in a style determined by the agent.

2. The visual simulation method according to claim 1, characterized in that: Before executing step S500, the visual simulation method further includes: The planned path of each agent in the environment scene is pre-displayed in a style determined by the agent.

3. The visual simulation method according to claim 1, characterized in that: The state of the grid includes an occupied state and a non-occupied state, the state value of the occupied state is 1, and the state value of the non-occupied state is 0.

4. The visual simulation method according to claim 1, characterized in that: The assigning of the state of the grid in the electronic form comprises: A table file in a first format is imported, wherein the value edited in each cell in the table file in the first format corresponds to the state value of the grid in the electronic spreadsheet.

5. The visual simulation method according to claim 1, characterized in that: The setting of the coordinate type of the grid in the electronic table includes: Import a table file in the second format, wherein the table file in the second format includes cells in two columns and multiple rows, the cells in the first column represent the starting point, the cells in the second column represent the end point, the cells in each row represent an agent, and the value edited in each cell is the coordinate of the grid in the electronic spreadsheet.

6. The visual simulation method according to claim 1, characterized in that: The path planning algorithm introduced into each agent includes: Import a path planning class for each agent written in Python, where the path planning class is a path planning algorithm.

7. The visual simulation method according to claim 1 or 2, characterized in that: The style determined by the agent includes: Each of the agents fills a grid in the spreadsheet with a corresponding color value.

8. The visual simulation method according to claim 1, characterized in that: The path planning algorithm is any one of the following: A* path planning algorithm, bidirectional A* path planning algorithm, Dijkstra algorithm.

9. A visual simulation device for multi-agent path planning, characterized in that: include: A scene building module is configured to build an environment scene by assigning values ​​to states of grids in a spreadsheet; A setting module, which is configured to generate a starting point and an end point of each intelligent agent in the environment scene by setting a coordinate type of a grid in the electronic table; An import module configured to import the path planning algorithm of each agent; A calculation module, configured to calculate a planned path of each agent in the environment scene according to the path planning algorithm of each agent and its starting point and end point; The display module is configured to move each agent according to the planned path and display a grid where the agent moves each step forward in a style determined by the agent.

10. An electronic device comprising: at least one processor; as well as A memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor so that the at least one processor can execute the visual simulation method described in any one of claims 1-8.

Images