Interaction control method and system based on mobile robot control

Abstract

The invention discloses an interaction control method, system and device based on mobile robot control, computer equipment and a storage medium, and relates to the technical field of data encryption, and the method comprises the steps: obtaining first feature information of an environment position identifier and second feature information of a user face; generating a delivery request message in combination with the first feature information and the second feature information; determining an optimal path based on the delivery request message, and optimizing path planning by using a reinforcement learning algorithm; based on a camera of the robot, shooting a face picture of the user, and performing face contour recognition processing to obtain third feature information; and the third feature information is compared with the second feature information, identity verification is carried out, and the robot executes article unloading operation. The face recognition technology is used for recognizing the face information to serve as the second feature information, a foundation is laid for subsequent accurate positioning and identity verification, the information collection efficiency is improved, and the accuracy and reliability of the information are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of mobile robot control, and in particular to an interactive control method and system based on mobile robot control. Background Art

[0002] Mobile robots have been widely used in logistics distribution, service robots and other fields. With their autonomous navigation capabilities and intelligence level, mobile robots have greatly improved work efficiency and service quality. Traditional mobile robots mainly rely on preset maps and path planning algorithms to complete tasks. However, this method often seems inadequate when facing dynamically changing environments. In recent years, with the advancement of deep learning and reinforcement learning technologies, more and more research has been devoted to the development of intelligent mobile robots that can adapt to complex environments and have self-learning capabilities. These technologies enable robots to autonomously learn and optimize path planning in unknown environments, greatly enhancing their adaptability and practicality.

[0003] Despite this, the existing mobile robot control systems still have some shortcomings. First, most systems rely solely on environmental features for navigation and lack a mechanism to verify user identity, which is an obvious shortcoming in application scenarios with high security requirements. Second, traditional path planning methods are often unable to flexibly respond to emergencies, such as temporary obstacles or path changes, which cause the robot to frequently pause or replan its path, reducing delivery efficiency. In addition, the existing technology's response mechanism in emergencies is not perfect and lacks an effective emergency stop function, which may cause safety hazards. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides an interactive control method and system, device, computer equipment and storage medium based on mobile robot control to solve the problems of lack of combination of environment and user characteristics, efficient path planning and emergency safety mechanism in existing mobile robot control systems.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, an embodiment of the present invention provides an interactive control method and system based on mobile robot control, which includes: Acquire first feature information of the environment location identifier and second feature information of the user's face; Combining the first characteristic information and the second characteristic information, generating a delivery request message; Determine the optimal route based on the delivery request message and optimize the route planning using reinforcement learning algorithm; Based on the camera built into the robot, the user's face is photographed and the face contour is recognized to obtain the third feature information; The third characteristic information is compared with the second characteristic information to perform identity authentication, and the robot performs the item unloading operation; Set the emergency stop signal. When the mobile robot deviates, it will send an emergency stop signal.

[0007] As a preferred solution of the interactive control method and system based on mobile robot control of the present invention, wherein: the first feature information of the environmental location identifier and the second feature information of the user's face are obtained, including: Start the program, and the user points the camera at the area containing the environmental location mark and his / her face, and takes a picture; The photos taken are uploaded to the server for analysis and processing; Using image recognition technology to identify environmental location markers in the photo as first feature information; The facial information in the photo is identified using face recognition technology as the second feature information.

[0008] As a preferred solution of the interactive control method and system based on mobile robot control of the present invention, wherein: the combination of the first characteristic information and the second characteristic information to generate a delivery request message includes: The position coordinates are determined based on the first feature information, the facial feature points are determined based on the second feature information, the user manually inputs the weight information of the item, and the function is defined Generate a delivery request message , , whose expression is: in: is the longitude coordinate; is the latitude coordinate; is the weight of the item; is the facial feature vector, whose length Represents the modulus of the facial feature vector; is the natural logarithm of the facial feature vector; is the exponential function of the ratio of the object weight to the modulus of the facial feature vector; is the cosine value of the item weight; is the square root of the modulus of the facial feature vector.

[0009] As a preferred solution of the interactive control method and system based on mobile robot control of the present invention, wherein: the optimal path is determined based on the delivery request message, and the path planning is optimized by using a reinforcement learning algorithm, including: Robot receives delivery request message , define the initial position of the robot , based on the reinforcement learning algorithm to optimize the path, the expression is: in: For the status Take action The expected return value of It is a combination of the robot’s current position and the item’s weight information; is the change value of moving direction and speed; is the learning rate; is the discount factor; Request message for delivery; Define the reward function: in: Status arrive The Euclidean distance of To take action After arrival status time; To take action After the energy consumption; , and is the adjustment coefficient; After multiple rounds of iterations, the optimal path is obtained; the obstacle detection algorithm is defined to identify obstacles, and the expression is: in: For the The distance to the obstacle; For the The height of the obstacle.

[0010] The obstacle prediction model is used to predict the future position of the robot based on the current position, size and time of the obstacle. The expression is: in: For the The distance to the obstacle; For the The height of the obstacle; To predict the time; is the coefficient related to the obstacle height; is the coefficient related to time; is the time-dependent rate of change of altitude; The obstacle avoidance algorithm is used to adjust the path of the mobile robot, and the expression is: in: For the The distance to the obstacle; For the The height of the obstacle; To predict the time; is the optimal path.

[0011] As a preferred solution of the interactive control method and system based on mobile robot control of the present invention, wherein: the camera based on the robot itself takes pictures of the user's face and performs facial contour recognition processing, including: The robot determines its current position through the built-in positioning system, and when it approaches the predetermined position, it triggers the camera to take pictures; The face detection algorithm is used to detect the photographed face area. The expression is: in: To shoot images; is the coordinates of the face area; and is the coordinate of the upper left corner; is the width; is the height; The facial contour features are extracted from the detected face area, and the third feature information is defined, which is expressed as .

[0012] As a preferred solution of the interactive control method and system based on mobile robot control of the present invention, wherein: the third characteristic information is obtained, including: The second feature information is compared with the third feature information, and the similarity between the two is calculated using a facial feature comparison algorithm, and the expression is: in: It is the facial contour feature currently captured; for similarity; is the second feature information, i.e., the reference feature information of the user's face; is the preset threshold; is the number of key points of the face; is the standard deviation; is the adjustment coefficient, If the similarity Greater than or equal to the preset threshold , it is determined that the user identity authentication is successful, and the mobile robot performs the item unloading operation.

[0013] As a preferred solution of the interactive control method and system based on mobile robot control of the present invention, wherein: the setting of the emergency stop signal, when the mobile robot sends a deviation, sends an emergency stop signal, including: The central server collects the real-time location and status information of the mobile robot through wireless communication protocols; When the robot deviates from the predetermined route, an emergency stop signal is sent to the central server. The central server receives the emergency stop signal and sends it to the robot through a wireless communication protocol. After receiving the emergency stop signal, the robot immediately stops.

[0014] In a second aspect, the present invention provides an interactive control system based on mobile robot control, comprising: Environmental perception module: obtains the first characteristic information of the environmental position identifier to identify the robot's location and environment; User face recognition module: Use the robot's built-in camera to take a picture of the user's face and perform facial contour recognition to obtain the user's third feature information; Feature fusion module: combining the first feature information and the second feature information to generate a delivery request message including location and user information; Path planning and optimization module: Determine the optimal path based on the delivery request message and use reinforcement learning algorithm to further optimize the path planning; Identity verification module: compares the third feature information with the second feature information to perform identity verification. After ensuring that they are correct, the robot performs the item unloading operation; Safety control module: Set up an emergency stop signal mechanism to send an emergency stop signal when the robot exhibits abnormal behavior or deviates from the preset path to ensure the safety of human-machine interaction.

[0015] In a third aspect, an embodiment of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the interactive control method and system based on mobile robot control as described in the first aspect of the present invention is implemented.

[0016] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the interactive control method and system based on mobile robot control as described in the first aspect of the present invention.

[0017] The beneficial effects of the present invention are: 1. The user points the camera at the area containing the environmental location identifier and his own face and takes a picture, uses image recognition technology to identify the environmental location identifier as the first feature information, and uses face recognition technology to identify facial information as the second feature information, thereby achieving simultaneous acquisition of user and environmental information, laying the foundation for subsequent precise positioning and identity authentication, which not only improves the efficiency of information collection, but also ensures the accuracy and reliability of the information.

[0018] 2. By defining complex function expressions, it is possible to integrate environmental location and user identity information to generate detailed delivery request messages, providing precise data support for subsequent path planning, improving the accuracy and completeness of delivery request messages, and thus enhancing the reliability of the entire system and user experience.

[0019] 3. After receiving the delivery request message, the robot optimizes the path planning based on the reinforcement learning algorithm to cope with the ever-changing environmental conditions. In particular, through the obstacle detection algorithm and prediction model, it can avoid obstacles in advance, optimize the path, and improve delivery efficiency. This not only improves the intelligence level of path planning, but also enhances the adaptability and flexibility of the system, enabling the robot to operate efficiently in complex and changing environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0021] Figure 1 This is a flow chart of the interactive control method and system based on mobile robot control in Example 1. DETAILED DESCRIPTION

[0022] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0023] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0024] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments. Example

[0025] Reference Figure 1 , which is the first embodiment of the present invention, provides an interactive control method and system based on mobile robot control, comprising the following steps: Acquire first feature information of the environment location identifier and second feature information of the user's face; Start the program, and the user points the camera at the area containing the environmental location mark and his / her face, and takes a picture; The photos taken are uploaded to the server for analysis and processing; Using image recognition technology to identify environmental location markers in the photo as first feature information; The facial recognition technology is used to identify the facial information in the photo as the second feature information.

[0026] Combining the first characteristic information and the second characteristic information, generating a delivery request message; The step of combining the first characteristic information and the second characteristic information to generate a delivery request message includes: Determine the position coordinates based on the first feature information, determine the facial feature points based on the second feature information, and the user manually inputs the weight information of the item to define the function Generate a delivery request message , , whose expression is: in: is the longitude coordinate; is the latitude coordinate; is the weight of the item; is the facial feature vector, whose length Represents the modulus of the facial feature vector; is the natural logarithm of the facial feature vector; is the exponential function of the ratio of the object weight to the modulus of the facial feature vector; is the cosine value of the item weight; is the square root of the modulus of the facial feature vector.

[0027] Determine the optimal route based on the delivery request message and optimize the route planning using reinforcement learning algorithm; Robot receives delivery request message , define the initial position of the robot , based on the reinforcement learning algorithm to optimize the path, the expression is: in: For the status Take action The expected return value of It is a combination of the robot’s current position and the item’s weight information; is the change value of moving direction and speed; is the learning rate; is the discount factor; Request message for delivery; Define the reward function: in: Status arrive The Euclidean distance of To take action After arrival status time; To take action After the energy consumption; , and is the adjustment coefficient; After multiple rounds of iterations, the optimal path is obtained; Define the obstacle detection algorithm to identify obstacles. The expression is: in: For the The distance to the obstacle; For the The height of the obstacle; The obstacle prediction model is used to predict the future position of the robot based on the current position, size and time of the obstacle. The expression is: in: For the The distance to the obstacle; For the The height of the obstacle; To predict the time; is the coefficient related to the obstacle height; is the coefficient related to time; is the rate of change of altitude with respect to time; The obstacle avoidance algorithm is used to adjust the path of the mobile robot, and the expression is: in: For the The distance to the obstacle; For the The height of the obstacle; To predict the time; is the optimal path.

[0028] Based on the camera built into the robot, the user's face is photographed and the face contour is recognized to obtain the third feature information; The robot determines its current position through the built-in positioning system, and when it approaches the predetermined position, it triggers the camera to take pictures; The face detection algorithm is used to detect the photographed face area. The expression is: in: To shoot images; is the coordinates of the face area; and is the coordinate of the upper left corner; is the width; is the height; The facial contour features are extracted from the detected face area, and the third feature information is defined, which is expressed as .

[0029] The third characteristic information is compared with the second characteristic information to perform identity authentication, and the robot performs the item unloading operation; The second feature information is compared with the third feature information, and the similarity between the two is calculated using a facial feature comparison algorithm, and the expression is: in: It is the facial contour feature currently captured; for similarity; is the second feature information, i.e., the reference feature information of the user's face; is the preset threshold; is the number of key points of the face; is the standard deviation; is the adjustment coefficient, If the similarity Greater than or equal to the preset threshold , it is determined that the user identity authentication is successful, and the mobile robot performs the item unloading operation.

[0030] Set the emergency stop signal. When the mobile robot deviates, it will send an emergency stop signal.

[0031] The central server collects the real-time location and status information of the mobile robot through wireless communication protocols; When the robot deviates from the predetermined route, an emergency stop signal is sent to the central server. The central server receives the emergency stop signal and sends it to the robot through a wireless communication protocol. After receiving the emergency stop signal, the robot immediately stops.

[0032] This embodiment also provides an interactive control system based on mobile robot control, including: Environmental perception module: obtains the first characteristic information of the environmental position identifier to identify the robot's location and environment; User face recognition module: Use the robot's built-in camera to take a picture of the user's face and perform facial contour recognition to obtain the user's third feature information; Feature fusion module: combining the first feature information and the second feature information to generate a delivery request message including location and user information; Path planning and optimization module: Determine the optimal path based on the delivery request message and use reinforcement learning algorithm to further optimize the path planning; Identity verification module: compares the third feature information with the second feature information to conduct identity verification. After ensuring that they are correct, the robot performs the item unloading operation; Safety control module: Set up an emergency stop signal mechanism to send an emergency stop signal when the robot exhibits abnormal behavior or deviates from the preset path to ensure the safety of human-machine interaction This embodiment also provides a computer device, which is suitable for the interactive control method and system based on mobile robot control, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the interactive control method and system based on mobile robot control as proposed in the above embodiments.

[0033] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0034] The present embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the interactive control method and system based on mobile robot control as proposed in the above embodiment are implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, disk or optical disk.

[0035] In summary, the present invention realizes the monitoring and understanding of user behavior through the analysis of user file operation behavior, can accurately capture the user's operation habits and behavior patterns, provide basic data for the subsequent generation of encryption strategies, and also help the system to detect and prevent abnormal behaviors; predict the user's future operations according to the user's behavior habits, so as to formulate encryption strategies more intelligently; more accurately protect user privacy, reduce the risk of data leakage, and improve the data security and confidentiality of the system; the present invention better adapts to the user's operation habits and needs, improves the intelligence level of the encryption algorithm and user experience, and enhances the flexibility and adaptability of the system.

[0036] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An interactive control method based on mobile robot control, characterized in that: include: Acquire first feature information of the environment location identifier and second feature information of the user's face; Combining the first characteristic information and the second characteristic information, generating a delivery request message; Determine the optimal route based on the delivery request message and optimize the route planning using reinforcement learning algorithm; Based on the camera built into the robot, the user's face is photographed and the face contour is recognized to obtain the third feature information; The third characteristic information is compared with the second characteristic information to perform identity authentication, and the robot performs the item unloading operation; Set the emergency stop signal. When the mobile robot deviates, it will send an emergency stop signal.

2. The interactive control method based on mobile robot control according to claim 1, characterized in that: The first feature information of the environment location identifier and the second feature information of the user's face are obtained, include, Start the program, and the user points the camera at the area containing the environmental location mark and his / her face, and takes a picture; The photos taken are uploaded to the server for analysis and processing; Using image recognition technology to identify environmental location markers in the photo as first feature information; The facial recognition technology is used to identify the facial information in the photo as the second feature information.

3. The interactive control method based on mobile robot control as claimed in claim 2, characterized in that: The step of combining the first characteristic information and the second characteristic information to generate a delivery request message includes: Determine the position coordinates based on the first feature information, determine the facial feature points based on the second feature information, and the user manually inputs the weight information of the item to define the function Generate a delivery request message , , whose expression is: in: is the longitude coordinate; is the latitude coordinate; is the weight of the item; is the facial feature vector, its length Represents the modulus of the facial feature vector; is the natural logarithm of the facial feature vector; is the exponential function of the ratio of the object weight to the modulus of the facial feature vector; is the cosine value of the item weight; is the square root of the modulus of the facial feature vector.

4. The interactive control method based on mobile robot control as claimed in claim 3, characterized in that: The method of determining the optimal path based on the delivery request message and optimizing the path planning using a reinforcement learning algorithm includes: Robot receives delivery request message , define the initial position of the robot , based on the reinforcement learning algorithm to optimize the path, the expression is: in: For the status Take action The expected return value of It is a combination of the robot’s current position and the item’s weight information; is the change value of moving direction and speed; is the learning rate; is the discount factor; Request message for delivery; Define the reward function: in: Status arrive The Euclidean distance of To take action After arrival status time; To take action After the energy consumption; , and is the adjustment coefficient; After multiple rounds of iterations, the optimal path is obtained; Define the obstacle detection algorithm to identify obstacles. The expression is: in: For the The distance to the obstacle; For the The height of the obstacle; The obstacle prediction model is used to predict the future position of the robot based on the current position, size and time of the obstacle. The expression is: in: For the The distance to the obstacle; For the The height of the obstacle; To predict the time; is the coefficient related to the obstacle height; is the coefficient related to time; is the time-dependent rate of change of altitude; The obstacle avoidance algorithm is used to adjust the path of the mobile robot, and the expression is: in: For the The distance to the obstacle; For the The height of the obstacle; To predict the time; is the optimal path.

5. The interactive control method based on mobile robot control according to claim 4, characterized in that: The robot's built-in camera captures the user's face and performs facial contour recognition, including: The robot determines its current position through the built-in positioning system, and when it approaches the predetermined position, it triggers the camera to take pictures; The face detection algorithm is used to detect the photographed face area. The expression is: ;in: To shoot images; is the coordinates of the face area; and is the coordinate of the upper left corner; is the width; is the height; The facial contour features are extracted from the detected face area, and the third feature information is defined, which is expressed as .

6. The interactive control method based on mobile robot control according to claim 5, characterized in that: The obtaining of the third characteristic information includes: The second feature information is compared with the third feature information, and the similarity between the two is calculated using a facial feature comparison algorithm, and the expression is: in: It is the facial contour feature currently captured; for similarity; is the second feature information, i.e., the reference feature information of the user's face; is the preset threshold; is the number of key points of the face; is the standard deviation; is the adjustment coefficient, If the similarity Greater than or equal to the preset threshold , it is determined that the user identity authentication is successful, and the mobile robot performs the item unloading operation.

7. The interactive control method based on mobile robot control according to claim 6, characterized in that: The emergency stop signal is set, when the mobile robot deviates, the emergency stop signal is sent, including: The central server collects the real-time location and status information of the mobile robot through wireless communication protocols; When the robot deviates from the predetermined route, an emergency stop signal is sent to the central server. The central server receives the emergency stop signal and sends it to the robot through a wireless communication protocol. After receiving the emergency stop signal, the robot immediately stops.

8. An interactive control system based on mobile robot control, based on the interactive control method and system based on mobile robot control according to any one of claims 1 to 7, characterized in that: include: Environmental perception module: obtains the first characteristic information of the environmental position identifier to identify the robot's location and environment; User face recognition module: Use the robot's built-in camera to take a picture of the user's face and perform facial contour recognition to obtain the user's third feature information; Feature fusion module: combining the first feature information and the second feature information to generate a delivery request message including location and user information; Path planning and optimization module: Determine the optimal path based on the delivery request message and use reinforcement learning algorithm to further optimize the path planning; Identity verification module: compares the third feature information with the second feature information to perform identity verification. After ensuring that they are correct, the robot performs the item unloading operation; Safety control module: Set up an emergency stop signal mechanism to send an emergency stop signal when the robot exhibits abnormal behavior or deviates from the preset path to ensure the safety of human-machine interaction.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the interactive control method and system based on mobile robot control described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the interactive control method and system based on mobile robot control described in any one of claims 1 to 7 are implemented.

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