A pet barking-based mobile robot control method

Abstract

The application discloses a pet barking-based mobile robot control method, which comprises the following steps: controlling a mobile robot to acquire pet barking sounds in real time, and detecting whether the pet barking sounds meet preset abnormal conditions; when the mobile robot detects that the pet barking sounds meet the preset abnormal conditions, controlling the mobile robot to determine a position where a pet is located based on the pet barking sounds in real time; controlling the mobile robot to move towards the position where the pet is located, and performing environment abnormality detection; and controlling the mobile robot to perform corresponding environment abnormality feedback work based on the environment abnormality detection result. The pet barking sounds are taken as a trigger condition for the mobile robot to perform environment abnormality detection, the monitoring of the environment abnormality condition can be realized at low cost, the range of the environment abnormality detection required by the mobile robot is reduced based on the position where the pet is located, the utilization effectiveness of the computing resources of the mobile robot is improved, and the environment abnormality detection efficiency is high.

Description

Technical Field

[0001] This application relates to the field of environmental anomaly detection, specifically to a mobile robot control method based on pet barking. Background Technology

[0002] Currently, environmental anomaly detection, such as unauthorized user intrusion detection, typically requires setting up 24-hour cameras pointed at the entrance and exit of the home. However, fixed cameras have limited shooting range; for example, they can only capture unauthorized users entering through the door, but cannot capture burglars entering through windows or balconies. Setting up multiple cameras also presents problems such as compromised user privacy and high security costs. To improve the flexibility of environmental anomaly detection, cameras mounted on mobile robots have been introduced for home environmental anomaly detection. These mobile robots typically patrol the home at set times, consuming a lot of power and exhibiting relatively poor detection performance. Summary of the Invention

[0003] This application provides a mobile robot control method based on pet barking, the specific technical solution of which is as follows:

[0004] A mobile robot control method based on pet barking specifically includes: controlling the mobile robot to acquire pet barking sounds in real time and detecting whether the pet barking sounds meet preset abnormal conditions; when the mobile robot detects that the pet barking sounds meet the preset abnormal conditions, controlling the mobile robot to determine the pet's location in real time based on the pet barking sounds; controlling the mobile robot to move based on the pet's location and performing environmental anomaly detection; and controlling the mobile robot to perform corresponding environmental anomaly feedback work based on the environmental anomaly detection results.

[0005] Furthermore, the method for detecting whether a pet barking sound meets preset abnormal conditions specifically includes: determining whether the decibel level corresponding to the pet barking sound reaches a preset abnormal decibel level; if the decibel level corresponding to the pet barking sound reaches the preset abnormal decibel level, then the time when the pet barking sound reaches the preset abnormal decibel level is acquired is taken as the starting point of the abnormal detection time, and the time elapsed after a first time length from the time when the pet barking sound reaches the preset abnormal decibel level is taken as the ending point of the abnormal detection time; the audio of the pet barking sound between the starting point and the ending point of the abnormal detection time is matched and compared with the preset abnormal pet barking audio; if the matching degree meets the preset matching threshold, then the pet barking sound is determined to meet the preset abnormal conditions; if the matching degree does not meet the preset matching threshold, then the pet barking sound does not meet the preset abnormal conditions; if the decibel level corresponding to the pet barking sound does not reach the preset abnormal decibel level, then the pet barking sound does not meet the preset abnormal conditions.

[0006] Furthermore, the control of the mobile robot to move toward the pet's location and perform environmental anomaly detection specifically includes: determining the target movement position of the mobile robot based on the pet's location; controlling the mobile robot to move to the target movement position; controlling the mobile robot to rotate in place at the target movement position to obtain environmental parameters around the target movement position; performing environmental anomaly detection based on the environmental parameters around the target movement position, and outputting the environmental anomaly detection result.

[0007] Furthermore, as the mobile robot moves toward the pet's location, if the location of the pet, determined in real-time by the mobile robot based on the pet's barking, changes, then controlling the mobile robot to move toward the pet's location specifically includes: calculating the distance between the pet's location before and after the change; if the distance between the pet's location before and after the change is greater than a change distance threshold, then controlling the mobile robot to determine the target movement location based on the changed pet's location; if the distance between the pet's location before and after the change is less than or equal to the change distance threshold, then controlling the mobile robot to determine the target movement location based on both the pet's location before and after the change.

[0008] Furthermore, the method for calculating the change distance threshold specifically includes: calculating a first distance between the pet's position before the change and the target movement position of the mobile robot determined based on the pet's position before the change; and calculating the difference between the mobile robot's farthest environmental detection distance and the first distance as the change distance threshold.

[0009] Furthermore, the environmental anomaly detection refers to the detection of unauthorized user intrusion in the environment. The environmental anomaly detection based on environmental parameters around the target movement position and the output of the environmental anomaly detection result specifically includes: controlling the mobile robot to rotate at the target movement position by a first angle, and during the rotation, acquiring first environmental image information using a camera mounted on the mobile robot; performing human body recognition based on the first environmental image information; when the first environmental image information contains a human body, controlling the mobile robot to stop rotating, and controlling the mobile robot to follow the human body's location to acquire second environmental image information; acquiring human body parameter information in the environment based on the second environmental image information, comparing the human body parameter information in the environment with preset human body parameter information to determine whether the human body parameter information belongs to an unauthorized user; if the human body parameter information in the environment belongs to an unauthorized user, the output environmental anomaly detection result is that an unauthorized user intrusion exists; if the human body parameter information in the environment matches the preset human body parameter information, the output environmental anomaly detection result is that no unauthorized user intrusion exists.

[0010] Furthermore, when the environmental anomaly detection result indicates the presence of unauthorized user intrusion, the controlled mobile robot performs corresponding environmental anomaly feedback based on the detection result. Specifically, this includes: controlling the mobile robot to follow the unauthorized user and, during the following process, using a camera mounted on the mobile robot to capture video images of the unauthorized user; controlling the mobile robot to report the environmental anomaly detection result of unauthorized user intrusion to the user terminal and transmitting the unauthorized user video images to the user terminal in real time; controlling the mobile robot to request an unauthorized user intrusion unlocking command from the user terminal. If the user terminal refuses to grant the unauthorized user intrusion unlocking command, or if the user terminal does not grant the unauthorized user intrusion unlocking command to the mobile robot within a second time, the controlled mobile robot transmits the preset alarm home information, the environmental anomaly detection result, and the unauthorized user video images to the network alarm platform.

[0011] Furthermore, the environmental anomaly detection refers to the detection of user health anomalies in the environment. The environmental anomaly detection based on environmental parameters around the target movement position and the output of the environmental anomaly detection result specifically includes: controlling the mobile robot to rotate at the target movement position by a first angle, and during the rotation, acquiring first environmental image information using a camera mounted on the mobile robot; performing user identification based on the first environmental image information; when a user is identified in the first environmental image information, controlling the mobile robot to stop rotating and controlling the mobile robot to follow the user's location to acquire second environmental image information; determining the user's corresponding identity information in the first environmental image based on preset user identity information; identifying the user's posture based on the second environmental image information and determining whether the user's posture conforms to a preset fall state; controlling the mobile robot to acquire user vital signs and determining whether the user's vital signs conform to preset abnormal vital signs; when the user's posture conforms to the preset fall state or the user's vital signs conform to the preset abnormal vital signs, the output environmental anomaly detection result is that there is a user health anomaly; if the user's posture does not conform to the preset fall state and the user's vital signs do not conform to the preset abnormal vital signs, the output environmental anomaly detection result is that there is no user health anomaly.

[0012] Furthermore, when the environmental anomaly detection result indicates a user health anomaly, the controlled mobile robot performs corresponding environmental anomaly feedback based on the environmental anomaly detection result. Specifically, this includes: the controlled mobile robot using its onboard camera to acquire user video image information and transmitting it to a user terminal other than the user's corresponding identity information in the first environmental image from the preset user identity information; the controlled mobile robot requesting a user health anomaly unlocking command from the user terminal receiving the user video image information; if the user terminal refuses to grant the user health anomaly unlocking command, or if the user terminal does not grant the user health anomaly unlocking command to the mobile robot within a second time, the controlled mobile robot transmits preset emergency information, the environmental anomaly detection result, and the user video image to the network emergency rescue platform.

[0013] Furthermore, the environmental anomaly detection refers to detecting the safety of gases in the environment. The environmental anomaly detection based on environmental parameters around the target's moving position and the output of the environmental anomaly detection result specifically includes: controlling a mobile robot to rotate around the target's moving position to acquire ambient gases; analyzing the composition and concentration of the ambient gases using a gas analysis device mounted on the mobile robot; if harmful gases are present in the ambient gases, and the concentration of these harmful gases reaches a corresponding preset harmful gas concentration, the environmental anomaly detection result output by the mobile robot is that the ambient gas safety is abnormal; conversely, if there are no harmful gases in the environment, or the concentration of harmful gases present does not reach the corresponding preset harmful gas concentration, the environmental anomaly detection result output by the mobile robot is that the ambient gas safety is not abnormal.

[0014] Furthermore, when the environmental anomaly detection result indicates an environmental gas safety anomaly, the controlled mobile robot performs corresponding environmental anomaly feedback based on the detection result. Specifically, this includes: controlling the mobile robot to play a voice alarm corresponding to the environmental gas safety anomaly and transmitting the environmental anomaly detection result back to the user terminal; controlling the mobile robot to request an environmental gas safety anomaly unlocking command from the user terminal; if the user terminal does not grant the unlocking command within a second time, the controlled mobile robot searches and identifies the user by traversing each room based on the environmental map, and continues playing the voice alarm corresponding to the environmental gas safety anomaly during the search process; when the mobile robot identifies the user, it acquires the user's vital signs and checks whether the user's vital signs match preset abnormal vital signs; if the user's vital signs match the preset abnormal vital signs, the controlled mobile robot uses a camera mounted on its body to capture video images of the user and transmits the environmental anomaly detection result, preset emergency information, and the user's video images to the network emergency rescue platform.

[0015] The mobile robot control method based on pet barking described in this application leverages the fact that pets are more sensitive to abnormal situations in the environment and that they usually bark when abnormal situations occur. The method uses the pet's barking as a trigger condition for the mobile robot to perform environmental anomaly detection. It fully utilizes the security features of pets in the home, eliminating the need for the mobile robot to continuously patrol the house and for cameras to continuously record footage. This enables low-cost and efficient monitoring of abnormal environmental situations in the home. Furthermore, it utilizes the mobility, networking capabilities, and video information acquisition capabilities of the mobile robot to improve the logical rationality of the environmental anomaly feedback process. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a mobile robot control method based on pet barking, as described in one embodiment of this application. Implementation

[0017] The embodiments of this application will now be described in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described below are for illustrative purposes only and are not intended to limit the scope of this application.

[0018] Currently, environmental anomaly detection, such as unauthorized intrusion detection, typically requires 24-hour cameras pointed at home entrances and exits. However, fixed cameras have limited shooting range; for example, they can only capture unauthorized users entering through the door, but not intruders entering through windows or balconies. Installing multiple cameras also presents problems such as compromised user privacy and high security costs. To improve the flexibility of environmental anomaly detection, cameras mounted on mobile robots have been introduced for home environmental anomaly detection. These mobile robots typically patrol the home at set times, consuming a lot of power and exhibiting poor detection performance. To address the issues of high power consumption and poor detection performance of current home security mobile robots, this application provides a mobile robot control method based on pet barking. Leveraging the typical caregiving characteristics of pets, this method uses pet barking as a trigger condition for environmental anomaly detection, reducing the cost of mobile robot-based home security and achieving more efficient detection of environmental anomalies.

[0019] Specifically, such as Figure 1 As shown, the mobile robot control method based on pet barking specifically includes:

[0020] The system controls a mobile robot to acquire pet barking sounds in real time and detect whether the barking sounds meet preset abnormal conditions. The acquisition of pet barking sounds by the mobile robot can be, but is not limited to, using a microphone array. The detection of whether the pet barking sounds meet the preset abnormal conditions is used to detect whether the pet barking sounds differ from normal daily whimpers, thereby more accurately triggering the mobile robot to perform environmental anomaly detection. The preset abnormal conditions can be, but are not limited to, conditions set by the user in advance based on factors such as the type of pet and its barking habits to distinguish whether the pet barking sounds are abnormal.

[0021] When the mobile robot detects that a pet's barking sound matches a preset abnormal condition, it determines the pet's location in real time based on the barking sound. Based on the pet's location, the robot moves and performs environmental anomaly detection, then executes corresponding environmental anomaly feedback based on the detection results. Since pets typically linger and bark near abnormal locations, this implementation uses the pet's barking sound as the trigger for the mobile robot to perform environmental anomaly detection. This fully utilizes the security features of pets in the home, eliminating the need for continuous patrols by the mobile robot and long-term camera recording. This allows for low-cost and efficient monitoring of abnormal environmental conditions in the home. By controlling the mobile robot to move towards the pet's location while simultaneously performing environmental anomaly detection, the scope of environmental anomaly detection is narrowed, improving the utilization of the mobile robot's computing resources and resulting in high efficiency in environmental anomaly detection.

[0022] As one implementation method, the method for detecting whether a pet barking sound meets preset abnormal conditions specifically includes: determining whether the decibel level corresponding to the pet barking sound reaches a preset abnormal decibel level; if the decibel level corresponding to the pet barking sound does not reach the preset abnormal decibel level, then the pet barking sound is determined to not meet the preset abnormal conditions; conversely, if the decibel level corresponding to the pet barking sound reaches the preset abnormal decibel level, then the time when the pet barking sound reaches the preset abnormal decibel level is acquired is taken as the starting point of the abnormal detection time, and the time elapsed after a first time length is taken as the ending point of the abnormal detection time; the pet barking sound audio between the starting point and the ending point of the abnormal detection time is matched and compared with preset abnormal pet barking sound audio; if the matching degree meets a preset matching threshold, then the pet barking sound is determined to meet the preset abnormal conditions; if the matching degree does not meet the preset matching threshold, then the pet barking sound is determined to not meet the preset abnormal conditions. Specifically, the first time length is a preset time length used to improve the accuracy of pet barking sound abnormality recognition, which may be, but is not limited to, 3s, 5s, etc. The preset abnormal pet barking audio includes one or more pre-set audio segments of abnormal pet barking. By analyzing the matching degree between the pet barking sound reaching the preset abnormal decibel level and the preset abnormal pet barking audio, it is possible to effectively analyze whether the pet barking sound is abnormal. In this technical solution, the decibel level of the pet barking sound at a certain point in time is first compared with the preset abnormal decibel level to achieve preliminary anomaly screening of the pet barking sound. Then, the pet barking audio segment is matched and compared with the preset abnormal pet barking audio to achieve further anomaly screening of the pet barking sound. Compared with the existing technical solutions that only screen for anomalies from a single angle, this method can more accurately determine the abnormality of the pet barking sound.

[0023] In one implementation, controlling the mobile robot to move towards the pet's location and perform environmental anomaly detection specifically includes: determining the target movement position of the mobile robot based on the pet's location; controlling the mobile robot to move to the target movement position; controlling the mobile robot to rotate in place at the target movement position to acquire environmental parameters around the target movement position; performing environmental anomaly detection based on the environmental parameters around the target movement position; and outputting the environmental anomaly detection result. Specifically, since pets usually linger near abnormal locations when there are abnormal conditions, determining the target movement position of the mobile robot based on the pet's location enables the mobile robot to achieve environmental anomaly detection by acquiring environmental parameters within a small area after moving to the target movement position, thereby improving the efficiency and accuracy of environmental anomaly detection and reducing the power consumption required for environmental anomaly detection by the mobile robot.

[0024] Preferably, determining the target movement position of the mobile robot based on the location of the pet can be, but is not limited to, using the location of the pet as the center, a second distance as the radius of a first circle, and a third distance as the radius of a second circle, configuring the target movement position as any coordinate point between the first and second circles. The second distance is used to limit the shortest distance between the mobile robot and the location of the pet, and the third distance is used to limit the longest distance between the mobile robot and the location of the pet, so that the mobile robot can fully perform environmental anomaly detection around the pet at the target movement position.

[0025] In one implementation, as the mobile robot moves towards the pet's location, if the pet's location, determined in real-time by the mobile robot based on the pet's barking, changes, then controlling the mobile robot to move towards the pet's location specifically includes: calculating the distance between the pet's location before and after the change; if the distance between the pet's location before and after the change is greater than a change distance threshold, then controlling the mobile robot to determine the target movement location based on the changed pet's location; if the distance between the pet's location before and after the change is less than or equal to the change distance threshold, then controlling the mobile robot to determine the target movement location based on both the pet's location before and after the change. Specifically, the change distance threshold is a distance used to determine whether the pet's location has changed significantly, and can be, but is not limited to, the difference between the furthest environmental anomaly detection distance that the mobile robot can perform and the distance between the target movement location and the pet's location.

[0026] Because the location of a pet may change depending on the location of the abnormal situation when there is a significant change in the environment, for example, when an unauthorized user intrudes, the pet will move with the unauthorized user, so the location from which the pet's barking sounds may change significantly. Therefore, this implementation method determines whether there has been a significant change in the environmental anomaly by judging the distance between the pet's location before and after the change. When the distance between the pet's location before and after the change is greater than the change distance threshold, that is, when there has been a significant change in the environmental anomaly, the mobile robot is controlled to directly change to move towards the changed location of the pet, so that the mobile robot can track the pet in time and perform the latest environmental anomaly detection. Conversely, when the distance between the pet's location before and after the change is less than the change distance threshold, that is, when there has been no significant change in the environmental anomaly, the mobile robot is controlled to determine the target movement location based on the pet's location before and after the change.

[0027] Specifically, the control of the mobile robot determines the target movement position based on the pet's position before and after the change. This can be, but is not limited to, using the midpoint of the line connecting the pet's position before and after the change as the center of a circle, a second distance as the radius of a first circle, and a third distance as the radius of a second circle. The target movement position is configured as any coordinate point between the first and second circles. The second distance is used to limit the shortest distance between the mobile robot and the center of the circle, and the third distance is used to limit the longest distance between the mobile robot and the center of the circle, so that the mobile robot can fully perform environmental anomaly detection around the pet's position before and after the change at the target movement position.

[0028] In one implementation, the environmental anomaly detection refers to the detection of unauthorized user intrusion in the environment. The environmental anomaly detection based on environmental parameters around the target movement location, and the output of the environmental anomaly detection result, specifically includes: controlling a mobile robot to rotate at the target movement location by a first angle, and during the rotation, acquiring first environmental image information using a camera mounted on the mobile robot; this step, by controlling the mobile robot to rotate and acquire the first environmental image information, ensures that the range of the first environmental image information is not limited by the camera's field of view, thus enabling a more comprehensive detection of the environment. Human body recognition is performed based on the first environmental image information. When the first environmental image information contains a human body, the mobile robot stops rotating and follows the human body's location to acquire second environmental image information; human body parameter information in the environment is acquired based on the second environmental image information, and compared with preset human body parameter information to determine whether the human body parameter information belongs to an unauthorized user. If the human body parameter information in the environment belongs to an unauthorized user, the output environmental anomaly detection result is "unauthorized user intrusion exists"; if the human body parameter information in the environment matches the preset human body parameter information, the output environmental anomaly detection result is "no unauthorized user intrusion exists". Specifically, the human body recognition based on the first environmental image information can be, but is not limited to, recognizing human body presence by identifying human body contours, body temperature, and other vital signs in the first environmental image information. The difference between the second environmental image information and the first environmental image information is that the second environmental image information contains more human body feature information to facilitate the acquisition of human body parameter information. The human body parameter information can be, but is not limited to, human gait information, human height information, human facial information, and other information capable of human identification. This embodiment enables the mobile robot to collect and compare human body information in the environment through environmental images, allowing the mobile robot to detect unauthorized users triggered by pet barking sounds, eliminating the need for the mobile robot to perform unauthorized user intrusion detection for extended periods, and improving the detection efficiency and accuracy of environmental anomaly detection such as unauthorized user intrusion.

[0029] As one implementation method, when the environmental anomaly detection result indicates the presence of unauthorized user intrusion, the controlled mobile robot performs corresponding environmental anomaly feedback based on the environmental anomaly detection result, specifically including:

[0030] The system controls a mobile robot to follow unauthorized users and collects video images of them using a camera mounted on the robot. This step leverages the robot's mobility to enable it to follow unauthorized users, allowing the collected video images to help users or police more accurately identify them and submit them as evidence to the police station, effectively increasing the arrest rate of unauthorized users.

[0031] The mobile robot is controlled to report the environmental anomaly detection results of unauthorized user intrusion to the user terminal and transmit the unauthorized user video image to the user terminal in real time. The mobile robot requests the unauthorized user intrusion unlocking command from the user terminal. If the user terminal refuses to grant the unauthorized user intrusion unlocking command, or if the user terminal does not grant the unauthorized user intrusion unlocking command to the mobile robot in the next time, the mobile robot will transmit the preset alarm home information, environmental anomaly detection results, and unauthorized user video image to the network alarm platform. This implementation transmits unauthorized user video images to the user terminal, allowing the user to determine whether the unauthorized user is a relative or friend. A mobile robot is then controlled to request an unauthorized user intrusion unlock command from the user terminal. Compared to existing technologies that directly trigger an alarm upon obtaining unauthorized user video images, this approach, combined with user testimony, double-guarantees the illegitimacy of the intrusion. If the user refuses to grant the unauthorized user intrusion unlock command, the illegitimacy of the unauthorized user is effectively confirmed, and the mobile robot is then controlled to send an unauthorized user intrusion alarm to the network alarm platform. Furthermore, if the user does not grant the unauthorized user intrusion unlock command for an extended period, the user may be harmed by the unauthorized user, or the user may be busy with other matters. To ensure timely capture of the unauthorized user, a second period is set where, if the user does not grant the unauthorized user intrusion unlock command, the mobile robot is controlled to send an unauthorized user intrusion alarm to the network alarm platform.

[0032] As one implementation method, the environmental anomaly detection refers to the detection of user health anomalies in the environment. The environmental anomaly detection based on environmental parameters surrounding the target's movement location, and the output of the environmental anomaly detection result, specifically includes:

[0033] The mobile robot is controlled to rotate at a first angle at the target moving position, and during the rotation, a camera mounted on the mobile robot body is used to acquire first environmental image information. This step acquires first environmental image information by controlling the rotation of the mobile robot, so that the range of the first environmental image information is not limited by the camera's field of view, and the environment is detected more comprehensively.

[0034] User identification is performed based on first environmental image information. When a user is identified in the first environmental image information, the mobile robot stops rotating and follows the user's location to acquire second environmental image information. The user's identity information in the first environmental image is determined based on preset user identity information. The user's posture is identified based on the second environmental image information to determine whether the posture conforms to a preset fall state. Specifically, user identification based on the first environmental image information can be, but is not limited to, identifying human facial features, human contours, gait information, height information, etc., in the first environmental image information. The difference between the second and first environmental image information is that the second environmental image information contains more human posture information, including but not limited to human position, human posture movements, and human body area, which can distinguish whether a person is standing or lying down, or whether a person has fallen. The preset fall state consists of multiple pre-set postures used to identify whether a user has fallen. The user posture identified based on the second environmental information can be matched and compared with these multiple postures in the preset fall state to determine whether the user's posture conforms to the preset fall state.

[0035] The mobile robot is controlled to acquire user vital signs and determine whether these signs match preset abnormal signs. If the user's posture matches a preset fall state or the user's vital signs match preset abnormal signs, the output environmental anomaly detection result indicates that there is a user health abnormality. If the user's posture does not match the preset fall state and the user's vital signs do not match the preset abnormal signs, the output environmental anomaly detection result indicates that there is no user health abnormality. Specifically, the mobile robot acquires user vital signs by interacting with a wearable device worn by the user to obtain the user's heart rate, body temperature, facial expressions, or a combination of one or more of the above. When the user's vital sign is heart rate, the preset abnormal signs include at least a preset abnormal heart rate range. The user's vital signs are determined by comparing whether the user's heart rate matches the preset abnormal heart rate range. Similarly, when the user's vital sign is body temperature, the preset abnormal signs include at least a preset abnormal body temperature range. The user's vital signs are determined by comparing whether the user's body temperature matches the preset abnormal body temperature range. This implementation method uses the barking of a pet to trigger the control of a mobile robot to detect abnormal situations such as user falls in the environment. It effectively solves the problem that it is difficult for outsiders to know if a user has an accident while living alone. It does not require 24-hour tracking of the user's vital signs. It only uses the barking of a pet as a trigger condition, which reduces the power consumption of the mobile robot for abnormal detection and improves the efficiency of environmental abnormal detection.

[0036] In one implementation, when the environmental anomaly detection result indicates a user health anomaly, the controlled mobile robot performs corresponding environmental anomaly feedback based on the detection result. Specifically, this includes: the controlled mobile robot using its onboard camera to acquire user video image information and transmitting it to a user terminal (excluding the user's corresponding identity information in the first environmental image) from a preset user identity information set; the controlled mobile robot requesting a user health anomaly unlock command from the user terminal receiving the video image information; if the user terminal refuses to grant the unlock command, or fails to grant the unlock command within a second time, the controlled mobile robot transmits preset emergency information, the environmental anomaly detection result, and the user video image to a network emergency rescue platform. Specifically, the preset user identity information refers to the pre-stored identity information of each user in the family, or the identity information of the user and other emergency contacts. This allows the mobile robot to inform the other users of the user's health condition based on the preset user identity information when a user experiences an abnormal health condition. This enables the other users to conduct a secondary confirmation of the user's health condition and provides them with the right to unlock the user's health condition. This optimizes the emergency rescue process and improves the effectiveness of emergency rescue. At the same time, by limiting the execution time of unlocking the user's health condition, it avoids affecting the user's emergency rescue time limit due to the other users not granting the user the health condition unlock command for a long time.

[0037] In one implementation, the environmental anomaly detection refers to detecting the safety of gases in the environment. This detection, based on environmental parameters around the target's moving position, outputs a result. Specifically, this includes: controlling a mobile robot to rotate around the target's moving position to acquire ambient gases; analyzing the composition and concentration of the ambient gases using a gas analysis device mounted on the mobile robot; if harmful gases are present in the ambient gases, and the concentration of these harmful gases reaches a preset concentration, the mobile robot outputs an environmental anomaly detection result indicating an environmental gas safety anomaly; conversely, if there are no harmful gases in the environment, or the concentration of harmful gases is below the preset concentration, the mobile robot outputs an environmental anomaly detection result indicating no environmental gas safety anomaly. Since pets have a more sensitive sense of smell than humans, they often bark when there is an environmental gas safety anomaly. Therefore, this implementation configures the environmental anomaly detection to detect the safety of gases in the environment, solving the problem of excessive levels of harmful gases such as carbon monoxide affecting user safety in the home. The environmental gas safety detection mainly assesses safety by assessing the types of harmful gases present in the environment and the concentrations of each type. Since the human body has different resistance to different types of harmful gases, the preset concentrations of harmful gases corresponding to different types of harmful gases are different.

[0038] As one implementation method, when the environmental anomaly detection result indicates an environmental gas safety anomaly, the controlled mobile robot performs corresponding environmental anomaly feedback work based on the environmental anomaly detection result, specifically including:

[0039] The mobile robot is controlled to play a voice alarm corresponding to an abnormality in environmental gas safety, and the environmental anomaly detection results are transmitted and fed back to the user terminal. This step uses the voice alarm to alert the user to an abnormality in environmental gas safety, prompting the user to ventilate or check for the source of harmful gases, so as to avoid harm to the user's health due to excessively high concentrations of harmful gases.

[0040] The mobile robot is controlled to request an unlock command for environmental gas safety anomalies from the user terminal. This step controls the mobile robot to request an unlock command for environmental gas safety anomalies from the user terminal to confirm whether the user has effectively received the environmental gas safety anomaly notification, thereby improving the effectiveness of environmental anomaly feedback.

[0041] If the user terminal does not grant the mobile robot an unlock command for environmental gas safety anomalies within the second time, the mobile robot will be controlled to traverse each room based on the environmental map to search for and identify the user. During the traversal and search process, the mobile robot will continue to play the voice alarm corresponding to the environmental gas safety anomaly. Specifically, if the user terminal does not grant the mobile robot an unlock command for environmental gas safety anomalies within the second time, the user may have been affected by harmful gases and become unconscious or even comatose. Therefore, this step controls the mobile robot to move to each room to traverse and search for and identify the user in order to confirm whether the user has been affected by harmful gases.

[0042] When the mobile robot detects a user, it acquires the user's vital signs and checks if these signs match preset abnormal signs. If they do, the robot uses its mounted camera to capture video images of the user and transmits the environmental anomaly detection results, preset emergency information, and the video images to a network emergency rescue platform. Specifically, the preset abnormal signs refer to pre-set vital sign information used to determine if a user is affected by harmful gases. This information can be, but is not limited to, vital sign settings corresponding to historical cases of harmful gas exposure obtained from a medical system database. The preset emergency information includes at least home address and other information that facilitates the network emergency rescue platform in determining the location of emergency services. This implementation method, when determining that a user's vital signs are abnormal due to the influence of harmful gases in the environment, controls the mobile robot to request help from the network emergency rescue platform. This effectively solves the problem of users in homes being unable to effectively seek help due to the influence of harmful gases in the environment. The robot is unaffected by harmful gases, thus improving the success rate of emergency rescue when there are abnormal gas safety conditions in the environment.

[0043] Obviously, the above embodiments are only some embodiments of the present invention, and not all embodiments. The technical solutions of various embodiments can be combined with each other. If terms such as "first," "second," and "third" appear in the embodiments, they are for the purpose of distinguishing related features and should not be construed as indicating or implying their relative importance, order, or number of technical features.

[0044] Those skilled in the art will understand that all or part of the steps in the methods described above can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0045] It should be noted that any process or method description in the flowchart or otherwise described herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order described or discussed, including substantially simultaneously or in reverse order according to the functions involved, as should be understood by those skilled in the art to which the embodiments of the invention pertain.

[0046] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A mobile robot control method based on pet barking, characterized in that, The mobile robot control method based on pet barking specifically includes: Control the mobile robot to acquire pet barking sounds in real time and detect whether the pet barking sounds meet preset abnormal conditions; When the mobile robot detects that the pet's barking sound meets the preset abnormal conditions, it controls the mobile robot to determine the pet's location in real time based on the barking sound, controls the mobile robot to move based on the pet's location, performs environmental anomaly detection, and controls the mobile robot to perform corresponding environmental anomaly feedback work based on the environmental anomaly detection results. Specifically, when the mobile robot moves towards the pet's location, and the location of the pet, determined in real-time based on the pet's barking, changes, the control of the mobile robot to move towards the pet's location includes: Calculate the distance between the pet's location before and after the change; If the distance between the pet's position before and after the change is greater than the change distance threshold, the mobile robot is controlled to determine the target movement position based on the pet's position after the change. If the distance between the pet's position before and after the change is less than or equal to the change distance threshold, the mobile robot is controlled to determine the target movement position based on the pet's position before and after the change. The method of controlling the movement of the mobile robot based on the location of the pet and detecting environmental anomalies specifically includes: The target movement position of the mobile robot is determined based on the location of the pet; Control the mobile robot to move to the target location; Control the mobile robot to rotate in place at the target movement position to obtain environmental parameters around the target movement position; Environmental anomaly detection is performed based on environmental parameters around the target's movement location, and the environmental anomaly detection results are output. The environmental anomaly detection refers to the detection of unauthorized user intrusion in the environment, or the detection of abnormal user health in the environment, or the detection of gas safety in the environment.

2. The mobile robot control method based on pet barking according to claim 1, characterized in that, The method for detecting whether a pet's barking meets preset abnormal conditions specifically includes: Determine whether the decibel level corresponding to the pet's barking sound reaches the preset abnormal decibel level; If the decibel level corresponding to the pet barking reaches the preset abnormal decibel level, the time when the pet barking reaches the preset abnormal decibel level is acquired is taken as the start time of the abnormal detection time, and the time after the first time length of the time when the pet barking reaches the preset abnormal decibel level is acquired is taken as the end time of the abnormal detection time. The pet barking audio between the start time and the end time of the abnormal detection time is matched and compared with the preset abnormal pet barking audio. If the matching degree meets the preset matching threshold, the pet barking is determined to meet the preset abnormal condition. If the matching degree does not meet the preset matching threshold, the pet barking is determined to not meet the preset abnormal condition. If the decibel level corresponding to the pet's barking does not reach the preset abnormal decibel level, then the pet's barking is determined to not meet the preset abnormal conditions.

3. The mobile robot control method based on pet barking according to claim 2, characterized in that, The method for calculating the change distance threshold specifically includes: calculating a first distance between the pet's position before the change and the target movement position of the mobile robot determined based on the pet's position before the change; and calculating the difference between the mobile robot's farthest environmental detection distance and the first distance as the change distance threshold.

4. The mobile robot control method based on pet barking according to claim 3, characterized in that, When the environmental anomaly detection refers to the detection of unauthorized user intrusion in the environment, the environmental anomaly detection based on environmental parameters around the target's movement location, and the output of the environmental anomaly detection result, specifically includes: Control the mobile robot to rotate a first angle at the target moving position, and during the rotation, use the camera mounted on the mobile robot to acquire the first environmental image information; Human body recognition is performed based on the first environmental image information. When the first environmental image information contains a human body, the mobile robot is controlled to stop rotating and then follow the location of the human body to obtain the second environmental image information. Human parameter information in the environment is obtained based on the second environmental image information. The human parameter information in the environment is compared with the preset human parameter information to determine whether the human parameter information belongs to an unauthorized user. If the human parameter information in the environment belongs to an unauthorized user, the output environmental anomaly detection result is that an unauthorized user has intruded. If the human parameter information in the environment matches the preset human parameter information, the output environmental anomaly detection result is that no unauthorized user has intruded.

5. The mobile robot control method based on pet barking according to claim 4, characterized in that, When the environmental anomaly detection result indicates the presence of unauthorized user intrusion, the controlled mobile robot performs corresponding environmental anomaly feedback based on the environmental anomaly detection result, specifically including: Control the mobile robot to follow unauthorized users, and use the camera mounted on the mobile robot to collect video images of the unauthorized users during the following process; The system controls the mobile robot to report the environmental anomaly detection results of unauthorized user intrusion to the user terminal, and transmits the video images of the unauthorized user to the user terminal in real time. The mobile robot requests an unauthorized user intrusion unlocking command from the user terminal. If the user terminal refuses to grant the unauthorized user intrusion unlocking command, or if the user terminal fails to grant the unauthorized user intrusion unlocking command to the mobile robot within a second time, the mobile robot will transmit the preset alarm home information, environmental anomaly detection results, and unauthorized user video images to the network alarm platform.

6. The mobile robot control method based on pet barking according to claim 3, characterized in that, When the environmental anomaly detection refers to the detection of user health anomalies in the environment, the environmental anomaly detection based on environmental parameters around the target movement location, and the output of the environmental anomaly detection result, specifically includes: Control the mobile robot to rotate a first angle at the target moving position, and during the rotation, use the camera mounted on the mobile robot to acquire the first environmental image information; User identification is performed based on the first environmental image information. When a user is identified in the first environmental image information, the mobile robot is controlled to stop rotating and to follow the user's location to obtain the second environmental image information. Determine the user's corresponding identity information in the first environment image based on preset user identity information; Based on the second environmental image information, the user's posture is identified to determine whether the user's posture matches the preset falling state; Control the mobile robot to acquire the user's vital signs and determine whether the user's vital signs match the preset abnormal vital signs; If the user's posture matches the preset fall state or the user's vital signs match the preset abnormal vital signs, the output environmental anomaly detection result is that there is a user health abnormality; if the user's posture does not match the preset fall state and the user's vital signs do not match the preset abnormal vital signs, the output environmental anomaly detection result is that there is no user health abnormality.

7. The mobile robot control method based on pet barking according to claim 6, characterized in that, When the environmental anomaly detection result indicates a user health abnormality, the controlled mobile robot performs corresponding environmental anomaly feedback based on the environmental anomaly detection result, specifically including: The mobile robot is controlled to use the camera mounted on its body to acquire user video image information and transmit the user video image information to the user terminal other than the user's identity information in the first environmental image, which is a preset user identity information. The mobile robot requests a user health abnormality unlock command from the user terminal that receives the user's video image information. If the user terminal refuses to grant the user health abnormality unlock command, or if the user terminal does not grant the user health abnormality unlock command to the mobile robot within a second time, the mobile robot will transmit the preset emergency information, environmental abnormality detection results, and user video image to the network emergency rescue platform.

8. The mobile robot control method based on pet barking according to claim 3, characterized in that, When the environmental anomaly detection refers to the detection of gas safety in the environment, the environmental anomaly detection based on environmental parameters around the target's moving location, and the output of the environmental anomaly detection result, specifically includes: Control the mobile robot to rotate around the target movement position to collect ambient gas; The composition and concentration of ambient gases are analyzed using a gas analysis device mounted on the mobile robot. When harmful gases are present in the ambient air and the concentration of these harmful gases reaches the corresponding preset concentration, the mobile robot outputs an environmental anomaly detection result indicating an environmental gas safety anomaly. Conversely, when there are no harmful gases in the environment, or when the concentration of harmful gases present does not reach the corresponding preset concentration, the mobile robot outputs an environmental anomaly detection result indicating no environmental gas safety anomaly.

9. The mobile robot control method based on pet barking according to claim 8, characterized in that, When the environmental anomaly detection result indicates an environmental gas safety anomaly, the controlled mobile robot performs corresponding environmental anomaly feedback based on the environmental anomaly detection result, specifically including: Control the mobile robot to play voice alarms corresponding to abnormal environmental gas safety, and transmit and feed back the environmental anomaly detection results to the user terminal; Control the mobile robot to request an environmental gas safety anomaly unlock command from the user terminal; If the user terminal does not grant the mobile robot the unlock command for environmental gas safety anomaly within the second time, the mobile robot is controlled to traverse each room based on the environmental map to search for and identify the user, and the mobile robot continues to play the voice alarm corresponding to the environmental gas safety anomaly during the traversal and search process. When the mobile robot searches and identifies a user, it controls the mobile robot to obtain the user's vital signs and detect whether the user's vital signs match the preset abnormal vital signs. If the user's vital signs match the preset abnormal signs, the mobile robot will use the camera mounted on its body to collect video images of the user and transmit the environmental anomaly detection results, preset emergency information, and user video images to the network emergency rescue platform.

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