A control method for unmanned intelligent robot

Abstract

The present invention discloses a control method for an unmanned intelligent robot, which relates to the field of intelligent robots and includes the following steps: S1, obtaining current environmental data through an ultrasonic sensor; S2, determining whether the data is valid by a control mechanism; if so, proceeding to step S3; if not, proceeding to step S5; S3, generating a control signal and outputting it to a foot power mechanism, which executes the received action command; S5, turning on a visual sensor, analyzing the current environment of the intelligent robot, determining the movement direction and distance of the intelligent robot based on the current environment, and returning to step S1; S6, dynamically adjusting the robot's path of action. The advantages of the present invention are: effectively realizing the effective reuse of existing data, realizing pre-emptive comprehensive travel control, ensuring the control accuracy of the intelligent robot, and realizing efficient and stable control of the unmanned intelligent robot.

Description

Technical Field

[0001] The present invention relates to the field of intelligent robots, and in particular to a control method for an unmanned intelligent robot. Background Art

[0002] During operation, the intelligent robot uses sensors such as lasers to survey its surroundings, detect obstacles, and determine whether it can safely navigate. Based on this determination, it takes appropriate action to ensure safe passage. To avoid obstacles, the intelligent robot plans its route based on current conditions, typically selecting a route using polynomial calculations to design the robot's route.

[0003] Existing control methods for unmanned intelligent robots usually use real-time calculations, which require a large number of complex operations. In order to cope with random changes, repetitive calculations increase, occupying a large amount of computer computing performance. In actual application, this affects the control accuracy of the intelligent robot and makes it difficult to effectively reuse existing experience. In complex and repetitive application scenarios, it is difficult to achieve efficient and stable control of unmanned intelligent robots. Summary of the Invention

[0004] In order to solve the above technical problems, a method for controlling an unmanned intelligent robot is provided. This technical solution solves the problem that the existing technology proposed in the above background technology affects the control accuracy of the intelligent robot in the actual application process, makes it difficult to effectively reuse existing experience, and is difficult to achieve efficient and stable control of the unmanned intelligent robot in complex and repetitive application scenarios.

[0005] In order to achieve the above objects, the technical solution adopted by the present invention is:

[0006] A method for controlling an unmanned intelligent robot, comprising:

[0007] S1, obtain current environment data through ultrasonic sensor;

[0008] S2, the data obtained by the ultrasonic sensor is transmitted to the control mechanism, and the control mechanism determines whether the data is valid data. If so, step S3 is performed; if not, step S5 is performed;

[0009] S3. The control mechanism analyzes the valid data, obtains data analysis results, and generates a control signal based on the data analysis results and outputs it to the foot power mechanism, which executes the received action instructions;

[0010] S4. If the data obtained by the ultrasonic sensor is invalid data, the visual sensor is turned on. After the control mechanism receives the data sent by the visual sensor, it analyzes the current environment of the intelligent robot, determines the moving direction and moving distance of the intelligent robot based on the current environment of the intelligent robot, and returns to step S1;

[0011] S5, visual sensors and ultrasonic sensors monitor the surrounding environment in real time, and dynamically adjust the machine's movement path based on the real-time monitoring results of the surrounding environment.

[0012] Preferably, the transmitting of the data obtained by the ultrasonic sensor to the control mechanism, and the control mechanism determining whether the data is valid data specifically includes:

[0013] Based on the data transmitted by the ultrasonic sensor to the control mechanism, the data is cleaned and preprocessed. If missing values, abnormal values, or duplicate values ​​are found in the data, the byte of the missing value is recorded as a, the byte of the abnormal value is recorded as b, and the byte of the duplicate value is recorded as c;

[0014] Based on the instruction sent from the control mechanism to the foot power mechanism, the number of bytes of the instruction is recorded as d;

[0015] Determine whether e=max{a, b, c} is less than 2^20 and whether d is greater than 4^20. If so, record the data as valid data; otherwise, record the data as invalid data.

[0016] Preferably, the control mechanism analyzes the valid data, obtains the data analysis results, and generates a control signal based on the data analysis results and outputs it to the foot power mechanism. The foot power mechanism executes the received action instructions specifically including:

[0017] The control mechanism analyzes the valid data and determines whether the data parsing result is global map data;

[0018] If so, an exhaustive method is used to calculate the time required for the intelligent robot to pass through all paths, and the shortest path is converted into an action command and transmitted to the foot power mechanism, which executes the received action command;

[0019] If not, the data analysis result is determined to be partial map data. The control mechanism calculates the shortest time required for the intelligent robot to reach the edge of the map of the partial map data and converts it into an action command and transmits it to the foot power mechanism. The foot power mechanism executes the received action command and returns to step S1.

[0020] Preferably, the determining whether the data analysis result is global map data specifically includes:

[0021] Obtain the standard global path map of the area where the intelligent robot is currently located;

[0022] Perform similarity matching calculation on the data analysis results and the standard global path map to obtain the matching degree between the data analysis results and the standard global path map;

[0023] Determine whether the matching degree is greater than a similarity threshold; if so, determine that the data parsing result is global map data; if not, determine that the data parsing result is not global map data;

[0024] The similarity threshold value ranges from 90% to 99%.

[0025] Preferably, analyzing the current environment of the intelligent robot and determining the moving direction and moving distance of the intelligent robot based on the current environment of the intelligent robot specifically includes:

[0026] Acquire at least one simulation experiment data to obtain a simulation learning database;

[0027] Input the simulation learning database into the unmanned intelligent robot;

[0028] Based on the data transmitted by the visual sensor, the unmanned intelligent robot searches the simulation learning database, matches similar images, and makes corresponding judgments based on the information in the simulation learning database;

[0029] If the unmanned intelligent robot fails to match the relevant picture, it will choose the next step forward in the direction of the obstacle according to the direction of the obstacle and the order of front, back, left and right. During the forward process, it will observe the surrounding environment in real time and upload it to the control mechanism. If the unmanned intelligent robot matches the relevant picture, it will make corresponding judgments based on the data in the simulation learning database.

[0030] Preferably, the visual sensor and the ultrasonic sensor monitor the surrounding environment in real time, and based on the real-time monitoring results of the surrounding environment, dynamically adjust the movement path of the machine specifically including:

[0031] Based on the real-time monitoring results of the surrounding environment, locations that the intelligent robot cannot pass through or where the damage to the intelligent robot body is greater than a preset ratio are recorded as obstacles;

[0032] According to the direction of the obstacle, in the order of front, back, left and right, the next forward movement in the direction of the obstacle is selected, and the process returns to step S1.

[0033] Preferably, the step of marking a position where the intelligent robot cannot pass through or where the damage to the intelligent robot body is greater than a preset ratio as an obstacle specifically includes:

[0034] Based on the data transmitted by the vision sensor to the control mechanism, various situations that may occur when the intelligent robot passes through the position are simulated in the control mechanism;

[0035] Various situations are classified into a danger level of 1-9, with higher numbers representing higher danger levels. 1 represents a slight scratch on the intelligent robot's body, 2-3 represents light to moderate damage to non-core parts of the intelligent robot, 4-5 represents light to moderate damage to the core parts of the intelligent robot, 6 represents severe damage to non-core parts of the intelligent robot, 7 represents severe damage to the core parts of the intelligent robot, 8 represents damage to both the core and non-core parts of the intelligent robot, and 9 represents irreversible damage to the intelligent robot or the road ahead is impassable to the intelligent robot.

[0036] The core parts include: visual sensor, ultrasonic sensor, foot power mechanism;

[0037] Determine the danger level of the position ahead. If it is greater than 4, it is recorded as an obstacle.

[0038] Preferably, the control mechanism includes:

[0039] A receiving and storing mechanism for receiving data transmitted by the visual sensor and the ultrasonic sensor, and storing the data after analyzing and judging it as valid data;

[0040] The processing and compilation mechanism is equipped with an artificial intelligence system to analyze and process the data stored in the receiving storage unit and generate corresponding action instructions;

[0041] The modified transmission mechanism pre-runs the action instructions generated by the processing compilation unit, and after judging that the running results are correct, transmits the action instructions to the foot power mechanism;

[0042] The foot power mechanism includes:

[0043] The direction control mechanism is equipped with a steering wheel and a signal receiving system. After receiving the command from the control mechanism, the steering wheel moves forward, backward, left and right.

[0044] The speed drive mechanism, equipped with tires, adjusts the speed at which the intelligent robot moves based on the instructions received.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] This solution proposes a control method for an unmanned intelligent robot. The method matches and calculates the environmental data collected by the intelligent robot in real time with the known standard global path map of the area where the intelligent robot is currently located. When the matching degree between the environmental data and the standard global path map of the area where the intelligent robot is currently located reaches a threshold, the environmental data collected by the intelligent robot in real time is determined to be global map data. At this time, the global map data can be used for comprehensive travel control, effectively realizing the effective reuse of existing data and realizing pre-emptive comprehensive travel control. In addition, a multimodal approach is adopted. When valid map data and global map data are not identified, a dynamic loop algorithm is used until comprehensive map data is identified and collected, thereby ensuring the control accuracy of the intelligent robot and realizing efficient and stable control of the unmanned intelligent robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flow chart of a control method for an unmanned intelligent robot proposed in the present invention;

[0048] Figure 2 This is a flow chart of the present invention, in which data obtained by an ultrasonic sensor is transmitted to a control mechanism, and the control mechanism determines whether the data is valid data;

[0049] Figure 3 A schematic diagram of the process by which the control mechanism of the present invention analyzes valid data, obtains data analysis results, generates control signals based on the data analysis results and outputs them to the foot power mechanism, and the foot power mechanism executes the received motion instructions;

[0050] Figure 4 This is a schematic diagram of the process of determining whether the data analysis result is global map data according to the present invention;

[0051] Figure 5 A schematic diagram of a process for analyzing the current environment of an intelligent robot and determining the moving direction and distance of the intelligent robot based on the current environment of the intelligent robot according to the present invention;

[0052] Figure 6 This is a flow chart of the present invention's use of a visual sensor and an ultrasonic sensor to monitor the surrounding environment in real time, and dynamically adjusting the machine's path of movement based on the real-time monitoring results of the surrounding environment;

[0053] Figure 7 This is a schematic diagram of the structure of the electronic device of the present invention;

[0054] Figure 8 It is a schematic diagram of the computer-readable storage medium structure of the present invention. DETAILED DESCRIPTION

[0055] The following description is intended to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are merely examples, and those skilled in the art may conceive of other obvious variations.

[0056] Reference Figure 1 As shown, a control method for an unmanned intelligent robot includes:

[0057] S1, obtain current environment data through ultrasonic sensor;

[0058] S2, the data obtained by the ultrasonic sensor is transmitted to the control mechanism, and the control mechanism determines whether the data is valid data. If so, step S3 is performed; if not, step S4 is performed;

[0059] S3. The control mechanism analyzes the valid data, obtains data analysis results, and generates a control signal based on the data analysis results and outputs it to the foot power mechanism, which executes the received action instructions;

[0060] S4. If the data obtained by the ultrasonic sensor is invalid data, the visual sensor is turned on. After the control mechanism receives the data sent by the visual sensor, it analyzes the current environment of the intelligent robot, determines the moving direction and moving distance of the intelligent robot based on the current environment of the intelligent robot, and returns to step S1;

[0061] S5, visual sensors and ultrasonic sensors monitor the surrounding environment in real time, and dynamically adjust the machine's movement path based on the real-time monitoring results of the surrounding environment.

[0062] This solution calculates and matches the environmental data collected by the intelligent robot in real time with the known standard global path map of the area where the intelligent robot is currently located. When the matching degree between the environmental data and the standard global path map of the area where the intelligent robot is currently located reaches a threshold, the environmental data collected by the intelligent robot in real time is determined to be global map data. At this time, the global map data can be used for comprehensive travel control, effectively realizing the effective reuse of existing data and realizing pre-emptive comprehensive travel control. In addition, a multimodal approach is adopted. When no valid map data or global map data is identified, a dynamic loop algorithm is used until comprehensive map data is identified and collected.

[0063] Reference Figure 2 As shown, the data obtained by the ultrasonic sensor is transmitted to the control mechanism, and the control mechanism determines whether the data is valid data. Specifically, the following steps are performed:

[0064] Based on the data transmitted by the ultrasonic sensor to the control mechanism, the data is cleaned and preprocessed. If missing values, abnormal values, or duplicate values ​​are found in the data, the byte of the missing value is recorded as a, the byte of the abnormal value is recorded as b, and the byte of the duplicate value is recorded as c;

[0065] Based on the instruction sent from the control mechanism to the foot power mechanism, the number of bytes of the instruction is recorded as d;

[0066] Determine whether e=max{a, b, c} is less than 2^20 and whether d is greater than 4^20. If so, record the data as valid data; otherwise, record the data as invalid data.

[0067] This solution uses a data anomaly mechanism to initially identify the data collected by the ultrasonic sensor, identify the valid data, and perform subsequent map matching analysis based on the valid data, effectively achieving efficient control of the unmanned intelligent robot.

[0068] Reference Figure 3 As shown, the control mechanism analyzes the valid data, obtains the data analysis results, and generates a control signal based on the data analysis results and outputs it to the foot power mechanism. The foot power mechanism executes the received action instructions specifically including:

[0069] The control mechanism analyzes the valid data and determines whether the data parsing result is global map data;

[0070] If so, an exhaustive method is used to calculate the time required for the intelligent robot to pass through all paths, and the shortest path is converted into an action command and transmitted to the foot power mechanism, which executes the received action command;

[0071] If not, the data analysis result is determined to be partial map data. The control mechanism calculates the shortest time required for the intelligent robot to reach the edge of the map of the partial map data and converts it into an action command and transmits it to the foot power mechanism. The foot power mechanism executes the received action command and returns to step S1.

[0072] Reference Figure 4 As shown, determining whether the data parsing result is global map data specifically includes:

[0073] Obtain the standard global path map of the area where the intelligent robot is currently located;

[0074] Perform similarity matching calculation on the data analysis results and the standard global path map to obtain the matching degree between the data analysis results and the standard global path map;

[0075] Determine whether the matching degree is greater than a similarity threshold; if so, determine that the data parsing result is global map data; if not, determine that the data parsing result is not global map data;

[0076] The similarity threshold value ranges from 90% to 99%.

[0077] In this solution, the matching degree of the collected data of the known standard global path map of the current area of ​​the intelligent robot is calculated. When the matching degree of the environmental data and the standard global path map of the current area of ​​the intelligent robot reaches the threshold, the environmental data collected by the intelligent robot in real time is determined to be the global map data. At this time, the global map data can be used for comprehensive movement control, realizing the effective reuse of known data, reducing the real-time movement computing power requirements of the intelligent robot during movement control, ensuring the control accuracy of the intelligent robot, and realizing efficient and stable control of the unmanned intelligent robot.

[0078] Reference Figure 5 As shown, analyzing the current environment of the intelligent robot and determining the moving direction and moving distance of the intelligent robot based on the current environment of the intelligent robot specifically includes:

[0079] Acquire at least one simulation experiment data to obtain a simulation learning database;

[0080] Input the simulation learning database into the unmanned intelligent robot;

[0081] Based on the data transmitted by the visual sensor, the unmanned intelligent robot searches the simulation learning database, matches similar images, and makes corresponding judgments based on the information in the simulation learning database;

[0082] If the unmanned intelligent robot fails to match the relevant picture, it will choose the next step forward in the direction of the obstacle according to the direction of the obstacle and the order of front, back, left and right. During the forward process, it will observe the surrounding environment in real time and upload it to the control mechanism. If the unmanned intelligent robot matches the relevant picture, it will make corresponding judgments based on the data in the simulation learning database.

[0083] By using a large amount of simulation training with known data, the control training of unmanned intelligent robots in various environments is achieved, ensuring the unmanned intelligent robots' ability to respond to sudden obstacles.

[0084] Reference Figure 6 As shown in the figure, the visual sensor and ultrasonic sensor monitor the surrounding environment in real time and dynamically adjust the machine's action path based on the real-time monitoring results of the surrounding environment. Specifically, the following are

[0085] Based on the real-time monitoring results of the surrounding environment, locations that the intelligent robot cannot pass through or where the damage to the intelligent robot body is greater than a preset ratio are recorded as obstacles;

[0086] According to the direction of the obstacle, in the order of front, back, left and right, the next forward movement in the direction of the obstacle is selected, and the process returns to step S1.

[0087] By real-time monitoring of environmental conditions and on the basis of global control, sudden obstacles on the road can be immediately identified and obstacle avoidance control can be implemented, thus ensuring the control accuracy of the unmanned intelligent robot.

[0088] Locations where the intelligent robot cannot pass through or where the damage to the intelligent robot body is greater than a preset ratio are recorded as obstacles. Specifically, they include:

[0089] Based on the data transmitted by the vision sensor to the control mechanism, various situations that may occur when the intelligent robot passes through the position are simulated in the control mechanism;

[0090] Various situations are classified into a danger level of 1-9, with higher numbers representing higher danger levels. 1 represents a slight scratch on the intelligent robot's body, 2-3 represents light to moderate damage to non-core parts of the intelligent robot, 4-5 represents light to moderate damage to the core parts of the intelligent robot, 6 represents severe damage to non-core parts of the intelligent robot, 7 represents severe damage to the core parts of the intelligent robot, 8 represents damage to both the core and non-core parts of the intelligent robot, and 9 represents irreversible damage to the intelligent robot or the road ahead is impassable to the intelligent robot.

[0091] The core parts include: visual sensor, ultrasonic sensor, foot power mechanism;

[0092] Determine the danger level of the position ahead. If it is greater than 4, it is recorded as an obstacle.

[0093] Control mechanisms include:

[0094] A receiving and storing mechanism for receiving data transmitted by the visual sensor and the ultrasonic sensor, and storing the data after analyzing and judging it as valid data;

[0095] The processing and compilation mechanism is equipped with an artificial intelligence system to analyze and process the data stored in the receiving storage unit and generate corresponding action instructions;

[0096] The modified transmission mechanism pre-runs the action instructions generated by the processing compilation unit, and after judging that the running results are correct, transmits the action instructions to the foot power mechanism;

[0097] Foot dynamics include:

[0098] The direction control mechanism is equipped with a steering wheel and a signal receiving system. After receiving the command from the control mechanism, the steering wheel moves forward, backward, left and right.

[0099] The speed drive mechanism, equipped with tires, adjusts the speed at which the intelligent robot moves based on the instructions received.

[0100] Furthermore, the method according to the embodiment of the present application can also be used with the aid of Figure 7 The electronic device architecture shown in FIG. Figure 7 As shown, the electronic device 500 may include a bus 501, one or more CPUs 502, a read-only memory (ROM) 503, a random access memory (RAM) 504, a communication port 505 connected to a network, an input / output component 506, a hard disk 507, etc. The storage device in the electronic device 500, such as the ROM 503 or the hard disk 507, may store an unmanned intelligent robot control method provided by the present application. The electronic device 500 may also include a user interface 508. Of course, Figure 7 The architecture shown is only exemplary and can be omitted according to actual needs when implementing different devices. Figure 7 One or more components of an electronic device are shown.

[0101] Figure 8 This is a schematic diagram of the computer-readable storage medium structure provided by an embodiment of the present application. Figure 8 As shown, a computer-readable storage medium 600 according to one embodiment of the present application is shown. Computer-readable instructions are stored on the computer-readable storage medium 600. When the computer-readable instructions are executed by the processor, the unmanned intelligent robot control method according to the embodiment of the present application described with reference to the above figures can be executed. The storage medium 600 includes, but is not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0102] In summary, the advantages of the present invention are: effective reuse of existing data, realization of pre-emptive comprehensive travel control, guaranteed control accuracy of the intelligent robot, and realization of efficient and stable control of the unmanned intelligent robot.

[0103] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions merely illustrate the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A control method for an unmanned intelligent robot, characterized in that: include: S1, obtain current environment data through ultrasonic sensor; S2, the data obtained by the ultrasonic sensor is transmitted to the control mechanism, and the control mechanism determines whether the data is valid data. If so, step S3 is performed; if not, step S5 is performed; S3. The control mechanism analyzes the valid data, obtains data analysis results, and generates a control signal based on the data analysis results and outputs it to the foot power mechanism, which executes the received action instructions; S4. If the data obtained by the ultrasonic sensor is invalid data, the visual sensor is turned on. After the control mechanism receives the data sent by the visual sensor, it analyzes the current environment of the intelligent robot, determines the moving direction and moving distance of the intelligent robot based on the current environment of the intelligent robot, and returns to step S1; S5, visual sensors and ultrasonic sensors monitor the surrounding environment in real time, and dynamically adjust the machine's movement path based on the real-time monitoring results of the surrounding environment; The control mechanism analyzes the valid data, obtains the data analysis results, and generates a control signal based on the data analysis results and outputs it to the foot power mechanism. The foot power mechanism executes the received action instructions specifically including: The control mechanism analyzes the valid data and determines whether the data parsing result is global map data; If so, an exhaustive method is used to calculate the time required for the intelligent robot to pass through all paths, and the shortest path is converted into an action command and transmitted to the foot power mechanism, which executes the received action command; If not, the data analysis result is determined to be partial map data. The control mechanism calculates the shortest time required for the intelligent robot to reach the edge of the map of the partial map data and converts it into an action command and transmits it to the foot power mechanism. The foot power mechanism executes the received action command and returns to step S1. The determination of whether the data analysis result is global map data specifically includes: Obtain the standard global path map of the area where the intelligent robot is currently located; Perform similarity matching calculation on the data analysis results and the standard global path map to obtain the matching degree between the data analysis results and the standard global path map; Determine whether the matching degree is greater than a similarity threshold; if so, determine that the data parsing result is global map data; if not, determine that the data parsing result is not global map data; The similarity threshold value ranges from 90% to 99%. The transmitting of the data obtained by the ultrasonic sensor to the control mechanism, and the control mechanism determining whether the data is valid data specifically includes: Based on the data transmitted by the ultrasonic sensor to the control mechanism, the data is cleaned and preprocessed. If missing values, abnormal values, or duplicate values ​​are found in the data, the byte of the missing value is recorded as a, the byte of the abnormal value is recorded as b, and the byte of the duplicate value is recorded as c; Based on the instruction sent from the control mechanism to the foot power mechanism, the number of bytes of the instruction is recorded as d; Determine whether e=max{a, b, c} is less than 2^20 and whether d is greater than 4^20. If so, record the data as valid data; if not, record the data as invalid data.

2. The control method of an unmanned intelligent robot according to claim 1, characterized in that: The analyzing the current environment of the intelligent robot and determining the moving direction and moving distance of the intelligent robot based on the current environment of the intelligent robot specifically includes: Acquire at least one simulation experiment data to obtain a simulation learning database; Input the simulation learning database into the unmanned intelligent robot; Based on the data transmitted by the visual sensor, the unmanned intelligent robot searches the simulation learning database, matches similar images, and makes corresponding judgments based on the information in the simulation learning database; If the unmanned intelligent robot fails to match the relevant picture, it will choose the next step forward in the direction of the obstacle according to the direction of the obstacle and the order of front, back, left and right. During the forward process, it will observe the surrounding environment in real time and upload it to the control mechanism. If the unmanned intelligent robot matches the relevant picture, it will make corresponding judgments based on the data in the simulation learning database.

3. The control method of an unmanned intelligent robot according to claim 2, characterized in that: The visual sensor and ultrasonic sensor monitor the surrounding environment in real time, and based on the real-time monitoring results of the surrounding environment, dynamically adjust the movement path of the machine, specifically including: Based on the real-time monitoring results of the surrounding environment, locations that the intelligent robot cannot pass through or where the damage to the intelligent robot body is greater than a preset ratio are recorded as obstacles; According to the direction of the obstacle, in the order of front, back, left and right, the next forward movement in the direction of the obstacle is selected, and the process returns to step S1.

4. The control method of an unmanned intelligent robot according to claim 3, characterized in that: The locations where the intelligent robot cannot pass through or where the damage to the intelligent robot body is greater than a preset ratio are marked as obstacles specifically include: Based on the data transmitted by the vision sensor to the control mechanism, various situations that may occur when the intelligent robot passes through the position are simulated in the control mechanism; Various situations are classified into a danger level of 1-9, with higher numbers representing higher danger levels. 1 represents a slight scratch on the intelligent robot's body, 2-3 represents light to moderate damage to non-core parts of the intelligent robot, 4-5 represents light to moderate damage to the core parts of the intelligent robot, 6 represents severe damage to non-core parts of the intelligent robot, 7 represents severe damage to the core parts of the intelligent robot, 8 represents damage to both the core and non-core parts of the intelligent robot, and 9 represents irreversible damage to the intelligent robot or the road ahead is impassable to the intelligent robot. The core parts include: visual sensor, ultrasonic sensor, foot power mechanism; Determine the danger level of the position ahead. If it is greater than 4, it is recorded as an obstacle.

5. The control method of an unmanned intelligent robot according to claim 4, characterized in that: The control mechanisms include: A receiving and storing mechanism for receiving data transmitted by the visual sensor and the ultrasonic sensor, and storing the data after analyzing and judging it as valid data; The processing and compilation mechanism is equipped with an artificial intelligence system to analyze and process the data stored in the receiving storage unit and generate corresponding action instructions; The modified transmission mechanism pre-runs the action instructions generated by the processing compilation unit, and after judging that the running results are correct, transmits the action instructions to the foot power mechanism; The foot power mechanism includes: The direction control mechanism is equipped with a steering wheel and a signal receiving system. After receiving the command from the control mechanism, the steering wheel moves forward, backward, left and right. The speed drive mechanism, equipped with tires, adjusts the speed at which the intelligent robot moves based on the instructions received.

6. An electronic device, characterized in that: include: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed 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 unmanned intelligent robot control method as described in any one of claims 1-5.

7. A computer-readable storage medium having a computer-readable program stored thereon, characterized in that: When the computer-readable program is executed by a processor, the unmanned intelligent robot control method according to any one of claims 1 to 5 is implemented.

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