Unmanned intelligent robot control method

Abstract

The invention discloses an unmanned intelligent robot control method, and relates to the field of intelligent robots, and the method comprises the steps: S1, obtaining the current environment data through an ultrasonic sensor; s2, judging whether the data is valid data or not by a control mechanism, if so, performing a step S3, and if not, performing a step S5; s3, a control signal is generated and output to a foot power mechanism, and the foot power mechanism executes the transmitted action instruction; s5, opening a visual sensor, analyzing the current environment of the intelligent robot, determining the moving direction and the moving distance of the intelligent robot based on the current environment of the intelligent robot, and returning to the step S1; and S6, dynamically adjusting the action path of the robot. The method has the advantages that effective multiplexing of existing data is effectively achieved, comprehensive advancing control in advance is achieved, the control precision of the intelligent robot is guaranteed, and efficient and stable control over the unmanned intelligent robot is achieved.

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 detect the surroundings, detect actual obstacles, and determine whether it can pass safely. According to the results of the judgment, appropriate operation methods are taken to drive safely. In order to avoid obstacles, the intelligent robot plans to run the road according to the current situation. Generally, it is necessary to select the road through polynomial calculations and design the operation road of the intelligent robot.

[0003] Existing control methods for unmanned intelligent robots usually adopt real-time calculation methods, which require a large number of complex operations. In order to cope with random changes, repetitive calculations increase, which takes up a large amount of computer computing performance. In actual application processes, it 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-mentioned 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-mentioned background technology affects the control accuracy of the intelligent robot in the actual application process, makes it difficult to effectively reuse the existing experience, and makes it 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 purpose, the technical solution adopted by the present invention is:

[0006] A control method for 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, and if not, step S5 is performed;

[0009] S3, the control mechanism analyzes the effective 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, and the foot power mechanism executes the received action instructions;

[0010] S4. If the data acquired 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 action 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 from the ultrasonic sensor to the control mechanism, the data is cleaned and preprocessed. If missing values, abnormal values, and repeated 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 repeated 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; if not, record the data as invalid data.

[0016] Preferably, the control mechanism analyzes the effective 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 analysis 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, and the foot power mechanism executes the transmitted 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] Get the standard global path map of the area where the intelligent robot is currently located;

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

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

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

[0028] Based on the data transmitted by the visual sensor, the unmanned intelligent robot searches in 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 action path of the machine specifically including:

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

[0032] According to the direction of the obstacle, according to the order of front, back, left and right, select the next forward movement in the direction of the obstacle, and return to step S1.

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

[0034] Based on the data transmitted by the visual 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] The various situations are classified into danger levels 1-9, with the larger the number, the higher the danger level. 1 means that the intelligent robot body is slightly scratched, 2-3 means that the non-core parts of the intelligent robot are slightly to moderately damaged, 4-5 means that the core parts of the intelligent robot are slightly to moderately damaged, 6 means that the non-core parts of the intelligent robot are seriously damaged, 7 means that the core parts of the intelligent robot are seriously damaged, 8 means that both the core and non-core parts of the intelligent robot are damaged, and 9 means that the intelligent robot suffers irreversible damage or the intelligent robot cannot pass the road ahead.

[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 comprises:

[0039] A receiving storage mechanism is used to receive data transmitted by the visual sensor and the ultrasonic sensor, and store 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 is based on the action instructions generated by the processing compilation unit, the instructions are pre-run, and after judging that the running results are correct, the action instructions are transmitted 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 scheme 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, which effectively realizes the effective reuse of existing data and realizes pre-comprehensive travel control. In addition, a multimodal approach is adopted. When effective map data and global map data are not identified, a dynamic loop algorithm is adopted 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 A schematic diagram of a control method for an unmanned intelligent robot proposed by the present invention;

[0048] Figure 2 A schematic diagram of a flow chart of transmitting data obtained by an ultrasonic sensor to a control mechanism, and determining whether the data is valid data by the control mechanism;

[0049] Figure 3 A schematic diagram of a process in which the control mechanism of the present invention analyzes effective 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 A schematic diagram of a process for determining whether a data analysis result is global map data according to the present invention;

[0051] Figure 5 A schematic diagram of a process of 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 according to the present invention;

[0052] Figure 6 A schematic diagram of a process of using a visual sensor and an ultrasonic sensor of the present invention to monitor the surrounding environment in real time and dynamically adjusting the action path of the machine based on the real-time monitoring results of the surrounding environment;

[0053] Figure 7 It 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 used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think 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, proceed to step S3, if not, proceed to step S4;

[0059] S3, the control mechanism analyzes the effective 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, and the foot power mechanism executes the received action instructions;

[0060] S4. If the data acquired 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 action 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 identified as global map data. At this time, the global map data can be used for comprehensive travel control, which effectively realizes the effective reuse of existing data and realizes 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 adopted 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 including:

[0064] Based on the data transmitted from the ultrasonic sensor to the control mechanism, the data is cleaned and preprocessed. If missing values, abnormal values, and repeated 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 repeated 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; if not, 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 realizing efficient control of the unmanned intelligent robot.

[0068] Reference Figure 3 As shown, the control mechanism analyzes the effective 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 analysis 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, and the foot power mechanism executes the transmitted 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, judging whether the data parsing result is global map data specifically includes:

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

[0074] Perform similarity matching calculation on the data analysis result and the standard global path map to obtain the matching degree between the data analysis result 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 with the known standard global path map of the current area where the intelligent robot is located is calculated. When the matching degree of the environmental data with the standard global path map of the current area where the intelligent robot is located reaches a threshold, the environmental data collected by the intelligent robot in real time is deemed to be the global map data. At this time, the global map data can be used for comprehensive travel control, realizing effective reuse of known data, reducing the real-time travel computing power requirements of the intelligent robot during travel 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 include:

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

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

[0081] Based on the data transmitted by the visual sensor, the unmanned intelligent robot searches in 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 adopting a large amount of simulation training with known data, the control training of the unmanned driving intelligent robot in various environments is realized, ensuring the unmanned driving intelligent robot's 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 based on the real-time monitoring results of the surrounding environment, dynamically adjust the action path of the machine, including:

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

[0086] According to the direction of the obstacle, according to the order of front, back, left and right, select the next forward movement in the direction of the obstacle, and return 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 instantly identified and obstacle avoidance control can be performed, thus ensuring the control accuracy of the unmanned intelligent robot.

[0088] Positions where the intelligent robot cannot pass or where the degree of damage to the intelligent robot body is greater than a preset ratio are recorded as obstacles, including:

[0089] Based on the data transmitted by the visual 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] The various situations are classified into danger levels 1-9, with the larger the number, the higher the danger level. 1 means that the intelligent robot body is slightly scratched, 2-3 means that the non-core parts of the intelligent robot are slightly to moderately damaged, 4-5 means that the core parts of the intelligent robot are slightly to moderately damaged, 6 means that the non-core parts of the intelligent robot are seriously damaged, 7 means that the core parts of the intelligent robot are seriously damaged, 8 means that both the core and non-core parts of the intelligent robot are damaged, and 9 means that the intelligent robot suffers irreversible damage or the intelligent robot cannot pass the road ahead.

[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 storage mechanism is used to receive data transmitted by the visual sensor and the ultrasonic sensor, and store 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 is based on the action instructions generated by the processing compilation unit, the instructions are pre-run, and after judging that the running results are correct, the action instructions are transmitted to the foot power mechanism;

[0097] The dynamics of the foot 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 performed by 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 a control method for an unmanned intelligent robot provided in 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 Schematic diagram of a 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 an 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, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory (cache), etc. 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-comprehensive travel control, guarantee of 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 only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached 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, and if not, step S5 is performed; S3, the control mechanism analyzes the effective 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, and the foot power mechanism executes the received action instructions; S4. If the data acquired 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 action path based on the real-time monitoring results of the surrounding environment.

2. The unmanned intelligent robot control method according to claim 1, characterized in that: 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 from the ultrasonic sensor to the control mechanism, the data is cleaned and preprocessed. If missing values, abnormal values, and repeated 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 repeated 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.

3. The unmanned intelligent robot control method according to claim 2, characterized in that: The control mechanism analyzes the effective 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 analysis 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, and the foot power mechanism executes the transmitted 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.

4. The unmanned intelligent robot control method according to claim 3, characterized in that: The determining whether the data analysis result is global map data specifically includes: Get the standard global path map of the area where the intelligent robot is currently located; Perform similarity matching calculation on the data analysis result and the standard global path map to obtain the matching degree between the data analysis result 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%.

5. The control method of an unmanned intelligent robot according to claim 4, 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; Enter the simulation learning database into the unmanned intelligent robot; Based on the data transmitted by the visual sensor, the unmanned intelligent robot searches in 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.

6. The unmanned intelligent robot control method according to claim 5, characterized in that: 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 action path of the machine, specifically including: Based on the real-time monitoring results of the surrounding environment, the positions where the intelligent robot cannot pass or where the degree of damage to the body of the intelligent robot is greater than a preset ratio when passing through are recorded as obstacles; According to the direction of the obstacle, according to the order of front, back, left and right, select the next forward movement in the direction of the obstacle, and return to step S1.

7. The unmanned intelligent robot control method according to claim 6, characterized in that: The positions where the intelligent robot cannot pass or where the degree of damage to the body of the intelligent robot is greater than a preset ratio are recorded as obstacles specifically include: Based on the data transmitted by the visual sensor to the control mechanism, various situations that may occur when the intelligent robot passes through the position are simulated in the control mechanism; The various situations are classified into danger levels 1-9, with the larger the number, the higher the danger level. 1 means that the intelligent robot body is slightly scratched, 2-3 means that the non-core parts of the intelligent robot are slightly to moderately damaged, 4-5 means that the core parts of the intelligent robot are slightly to moderately damaged, 6 means that the non-core parts of the intelligent robot are seriously damaged, 7 means that the core parts of the intelligent robot are seriously damaged, 8 means that both the core and non-core parts of the intelligent robot are damaged, and 9 means that the intelligent robot suffers irreversible damage or the intelligent robot cannot pass the road ahead. 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.

8. The unmanned intelligent robot control method according to claim 7, characterized in that: The control mechanisms include: A receiving storage mechanism is used to receive data transmitted by the visual sensor and the ultrasonic sensor, and store 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 is based on the action instructions generated by the processing compilation unit, the instructions are pre-run, and after judging that the running results are correct, the action instructions are transmitted 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.

9. 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 1-8.

10. 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 driving intelligent robot control method described in any one of claims 1-8 is implemented.

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