Anti-following method, robot and storage medium

Abstract

The embodiment of the invention relates to the field of robots, in particular to an anti-following method, a robot and a computer readable storage medium, and the method comprises the steps: obtaining a task instruction, executing a task according to the task instruction, obtaining environment information around the robot, determining whether there is a pedestrian according to the environment information, and if there is a pedestrian in the environment information, executing the task according to the task instruction; if yes, the identity of the pedestrian is determined through the biological characteristics and activity behaviors of the pedestrian, whether a suspicious behavior exists or not is determined according to the identity of the pedestrian, and if it is detected that the suspicious behavior exists, response operation is executed according to the suspicious behavior. When the robot executes the task, the environment around the robot can be detected, whether suspicious behaviors exist around or not is determined, and the corresponding operation is executed when the suspicious behaviors exist, so that the following behaviors can be effectively reduced, the situation that the robot enters an unauthorized area is reduced, the safety can be improved, and the privacy of guests can be protected; and the satisfaction and credibility of the guests are improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of robots, and in particular to an anti-tailgating method, a robot, and a computer-readable storage medium. Background Art

[0002] With the development of intelligent technology, service robots are increasingly used in the hotel industry. These robots usually have functions such as leading and delivering items, providing convenient services for hotel guests. However, the openness of these functions also brings potential safety risks, especially in places such as hotels that have high requirements for privacy and security.

[0003] Currently, most hotel service robots focus on functionality and efficiency, such as guiding guests, delivering meals, and providing information. These robots usually do not require identity verification or password verification to perform tasks. They may be used by criminals to enter unauthorized areas. However, existing systems have difficulty in effectively identifying and preventing suspicious people from following robots. Summary of the invention

[0004] The embodiment of the present invention provides an anti-tailgating method, which can prevent suspicious persons from tailing when the robot is working, thereby improving safety and protecting the privacy of guests.

[0005] In a first aspect, an embodiment of the present invention provides an anti-tailgating method for a robot, the method comprising:

[0006] Obtaining a task instruction, and executing the task according to the task instruction;

[0007] Acquire environmental information around the robot, and determine whether there are pedestrians based on the environmental information;

[0008] If there is a pedestrian in the environmental information, the identity of the pedestrian is determined through the biological characteristics and activity behavior of the pedestrian, wherein the identity of the pedestrian includes employees, guests and unknown persons;

[0009] Determining whether there is suspicious behavior based on the identity of the pedestrian;

[0010] If suspicious behavior is detected, a response operation is performed based on the suspicious behavior.

[0011] In some embodiments, determining whether suspicious behavior exists according to the identity of the pedestrian includes:

[0012] If the pedestrian is a guest, the check-in information of the guest is obtained to determine whether the guest is a guest of a target room, where the target room is the room corresponding to the goods delivered by the robot;

[0013] If the guest is not a guest of the target room, determining the travel path between the guest's room and the public area;

[0014] If the location of the guest does not belong to the driving route, it is determined that suspicious behavior exists.

[0015] In some embodiments, determining whether there is suspicious behavior based on the identity of the pedestrian further includes:

[0016] If the identity of the pedestrian is an unknown person, and the distance between the pedestrian and the robot is less than a first distance for more than a first time period, it is determined that suspicious behavior exists.

[0017] In some embodiments, determining whether there is suspicious behavior based on the identity of the pedestrian further includes:

[0018] If the identity of the pedestrian is an employee or a guest of the target room, it is determined that there is no suspicious behavior.

[0019] In some embodiments, if suspicious behavior is detected, executing a response operation according to the suspicious behavior includes:

[0020] If the robot has not reached the target room when suspicious behavior is detected, the robot moves forward at a first speed, which is lower than the working speed of the robot;

[0021] If no suspicious behavior is detected after the second period of time, the task will continue;

[0022] If suspicious behavior is still detected after the second period of time, the task will be suspended and a warning reminder will be issued.

[0023] In some embodiments, after the robot arrives at the target room, if the suspicious behavior is not detected, a pickup notification is sent to the guest of the target room.

[0024] In some embodiments, obtaining a task instruction and executing a task according to the task instruction includes:

[0025] Obtaining a task instruction, obtaining operator information, determining the identity of the operator according to the operator information, and if the operator is an employee or a guest of the target room, executing the task according to the task instruction;

[0026] Otherwise, the task will not be executed and a warning will be given.

[0027] In a second aspect, an embodiment of the present invention provides a robot, comprising:

[0028] at least one processor, and

[0029] A memory, the memory is communicatively connected to the at least one processor, the memory stores instructions executable by the at least one processor, the instructions are executed by the at least one processor so that the at least one processor can execute the anti-tailgating method as described in the first aspect above.

[0030] In a third aspect, an embodiment of the present invention provides a non-volatile computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are executed by at least one processor, the at least one processor executes the anti-tailgating method described in the first aspect above.

[0031] Beneficial effects of the embodiments of the present invention: Different from the prior art, the anti-tailgating method provided by the embodiments of the present invention obtains task instructions, executes tasks according to the task instructions, obtains environmental information around the robot, and determines whether there are pedestrians according to the environmental information. If there are pedestrians in the environmental information, the identity of the pedestrian is determined by the biological characteristics and activity behavior of the pedestrian, wherein the identity of the pedestrian includes employees, guests and unknown persons, and whether there is suspicious behavior is determined according to the identity of the pedestrian. If suspicious behavior is detected, a response operation is performed according to the suspicious behavior. When the robot is performing a task, the environment around the robot can be detected to confirm whether there is suspicious behavior around, and a response operation is performed when there is suspicious behavior, which can effectively reduce tailgating behavior, prevent the use of the robot to enter unauthorized areas, improve security, protect guest privacy, and improve guest satisfaction and trust. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0033] Figure 1 A schematic diagram of an application environment of an anti-tailgating method provided by an embodiment of the present invention;

[0034] Figure 2 A structural block diagram of a robot provided by an embodiment of the present invention;

[0035] Figure 3 A structural block diagram of a robot provided by an embodiment of the present invention;

[0036] Figure 4 A schematic diagram of a process flow of an anti-tailgating method provided by an embodiment of the present invention;

[0037] Figure 5A schematic flow chart of an anti-tailgating method provided in another embodiment of the present invention;

[0038] Figure 6 A schematic flow chart of an anti-tailgating method provided in another embodiment of the present invention. DETAILED DESCRIPTION

[0039] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several variations and improvements may be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0040] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0041] It should be noted that, if there is no conflict, the various features in the embodiments of the present invention can be combined with each other, all within the scope of protection of the present application. In addition, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a different order than the module division in the device or the flow chart. In addition, the words "first", "second", "third", etc. used herein do not limit the data and execution order, but only distinguish the same items or similar items with basically the same functions and effects.

[0042] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in this specification and in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used in this specification includes any and all combinations of one or more of the related listed items.

[0043] In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0044] Figure 1 is a schematic diagram of the application environment of the anti-tailgating method provided by an embodiment of the present invention. Figure 1 , the application environment includes a robot 10 and a pedestrian 20 ( Figure 1 A pedestrian is used as an example in the figure).

[0045] The robot 10 is a robot used to perform tasks according to task instructions, such as delivery tasks, guidance tasks, information provision tasks, etc. The robot 10 can be used in various scenarios. In some embodiments, the robot 10 is used in a hotel to provide guests with guidance services, meal delivery services, etc.

[0046] The pedestrian 20 refers to a pedestrian in the surrounding environment of the robot 10 . It should be understood that there may be no pedestrians around the robot 10 , or there may be multiple pedestrians.

[0047] In some embodiments, pedestrians 20 include three identities, guests, employees, and unknown identities. Among them, guests and employees are people who have registered their identities in the system, and unknown identities are people who are not registered in the system. For example, all employees are registered in the system and authorize the robot to identify the authority; for example, the guest registers his identity when checking in and agrees to the authorization, so that the robot can identify the guest's identity; for example, the guest registers his identity when checking in but does not agree to the authorization, then the robot cannot identify him and he is identified as an unknown identity; for example, people who have not registered are also identified as unknown identities.

[0048] In some embodiments, see Figure 2 The robot 10 includes a camera device 110 , a recognition module 120 and a communication module 130 .

[0049] The camera device 110 is provided on the robot 10 to capture the environmental information around the robot 10 and determine whether there are pedestrians around the robot according to the environmental information. For example, the camera device 110 may be a high-definition camera, which may be installed on the front, back and top of the robot 10, to shoot and record the environmental images near the robot 10 and determine whether there are pedestrians in the environmental images.

[0050] Among them, the recognition module 120 is set in the robot 10, and is used to obtain the environmental information around the robot obtained by the camera device 110, and recognize the identity of the pedestrian through the biological characteristics and activity behavior. For example, the recognition module 120 may include a radar, and the radar is used to track the target and record the direction and distance. For example, the recognition module 120 may include a facial recognition module, and the identity of the pedestrian is verified by recognizing the facial picture in the environmental information. It should be understood that since the distance between the pedestrian and the robot will affect the clarity of the facial picture, when the distance is slightly far and the facial picture is not clear enough, the person is tracked first, and the facial recognition is performed to confirm the identity when the facial picture is clear enough. For example, the recognition module 120 may include an iris recognition module, a fingerprint recognition module, a palm print recognition module or other biometric recognition modules, and the identity of the pedestrian is confirmed by recognizing the pedestrian's iris, fingerprint, palm print or other biometric features.

[0051] The communication module 130 is provided in the robot 10 for communicating with external devices. For example, when an abnormal situation occurs, the robot 10 can notify the staff or report to the management system through the communication module 130. For example, when the robot 10 performs a delivery task, after arriving at the target room, it can send a pick-up notification to the guest in the target room through the communication module.

[0052] In this embodiment, the cooperation of the camera device and the radar can also achieve an effective monitoring angle of nearly 360° and an effective monitoring radius of 5m or even larger. For example, the camera device can be installed on the front, back and top of the robot, and the radar can be installed on the front and back of the robot to achieve a better detection range.

[0053] One embodiment of the present invention provides an anti-tailing method for a robot, which can prevent suspicious persons from following the robot when it is working, thereby improving safety and protecting the privacy of guests.

[0054] Before introducing the anti-tailgating method in detail, the hardware structure of a robot provided in another embodiment of the present invention is described.

[0055] In the above Figure 1-2 Based on the above, another embodiment of the present invention provides a robot, such as Figure 3 As shown, the robot includes at least one processor 11 and a memory 12 ( Figure 3 A bus connection and a processor are used as an example). A person skilled in the art can understand that Figure 3 The structure shown is for illustration only and does not limit the structure of the electronic device. Figure 3 More or fewer components as shown, or with Figure 3 Different configurations shown.

[0056] The processor 11 is used to provide computing and control capabilities to control the robot 10 to perform corresponding tasks, for example, to control the robot 10 to perform any one of the anti-tailgating methods provided in the following embodiments of the invention.

[0057] It can be understood that the processor 11 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0058] The memory 12, as a non-transient computer-readable storage medium, can be used to store non-transient software programs, non-transient computer executable programs and modules, such as program instructions / modules corresponding to the anti-tailgating method in the embodiment of the present invention. The processor 11 can implement the anti-tailgating method in any of the following method embodiments by running the non-transient software programs, instructions and modules stored in the memory 12. The memory 12 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory 12 may also include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network and a combination thereof.

[0059] The following is a detailed description of the anti-tailgating method provided by the embodiment of the present invention. Figure 4 The anti-tailgating method includes but is not limited to the following steps S101-S105:

[0060] S101: Obtain task instructions and execute tasks according to the task instructions.

[0061] Among them, the task instruction is an instruction for instructing the robot to perform a task. For example, the task instruction may include a delivery task instruction, a guidance task instruction, an information provision task instruction, etc. In some embodiments, it should be understood that the task instruction may be issued by an employee or by a guest who has registered in the system, but the task authority of the employee and the guest is different. The employee can issue the task instruction of any room to the robot, but the guest can only issue the task instruction of the room he / she is staying in to the robot.

[0062] In some embodiments, see Figure 5 , step S101, obtaining a task instruction, and executing the task according to the task instruction includes steps S201-S204:

[0063] S201: Obtain task instructions.

[0064] In this embodiment, a task instruction is obtained and information in the task instruction is obtained, such as a target room; for example, the task instruction is a delivery task, and the target room is the destination of the goods delivery; for example, the task instruction is a guidance task, and the target room is the guidance destination.

[0065] S202: Acquire operator information, and determine the identity of the operator according to the operator information.

[0066] In this embodiment, after receiving the task instruction and before executing the task according to the task instruction, the identity of the person who issued the task instruction is verified. To obtain the operator information, for example, the operator's facial information, fingerprint information, iris information and other biometric features can be obtained, or the operator's employee card information, room card information and the like can be obtained. The identity of the operator is determined based on the obtained operator information. For example, the operator's identity is determined by comparing the operator's biometric features with the information in the system. If it matches the employee's information in the system, the operator's identity is determined to be an employee. If it matches the guest's information in the system, the operator's identity is determined to be a guest, and the room where the guest is staying is determined. If there is no corresponding information in the system, the operator is an unknown identity. For example, the operator is determined to be an employee by obtaining the employee card information, and the operator is determined to be a guest by obtaining the room card information, and the room where the guest is staying is determined; if the operator does not cooperate and the operator information cannot be obtained, the operator is also identified as an unknown identity.

[0067] S203: If the operator is an employee or a guest of the target room, the task is performed according to the task instruction.

[0068] In this embodiment, if the operator is an employee, the verification is passed and the task is performed according to the task instruction. If the operator is a guest, the guest's room is compared with the target room. If the guest is a guest of the target room, the verification is passed and the task is performed according to the task instruction.

[0069] S204: Otherwise, the task is not executed and a warning reminder is given.

[0070] In this embodiment, if the operator is not an employee or a guest of the target room, the verification fails, the operator has insufficient authority, the robot does not perform the task according to the task instruction, and a warning reminder is issued.

[0071] For example, if the operator is an unknown person, the task will not be executed and a warning reminder will be issued. For example, if the operator is a guest, but the guest is not a guest of the target room, the task will not be executed and a warning reminder will be issued.

[0072] The warning reminder may include a voice reminder, such as "illegal request, please re-issue the instruction or verify the identity"; the warning reminder may also include a text reminder, such as displaying "illegal request, please re-issue the instruction or verify the identity" on the robot display unit; to remind the operator to try again to prevent misjudgment, and to serve as a reminder to surrounding staff. The warning reminder may also include remote reminders, such as SMS reminders, email reminders, reports to the management system, etc., to remotely remind staff to pay attention.

[0073] In this embodiment, by performing identity authentication before executing the task according to the task instruction, the legitimacy of the task instruction can be determined, and the lawless elements can be prevented from following the robot to the restricted area by issuing task instructions to the robot, which can improve security and protect the privacy of guests.

[0074] S102: Obtain environmental information around the robot, and determine whether there are pedestrians based on the environmental information.

[0075] In this embodiment, whether there are pedestrians around the robot is detected by obtaining environmental information around the robot and determining whether there are pedestrians based on the environmental information. For example, the robot can be provided with a camera device, which takes pictures of the robot's surroundings, analyzes the pictures, and determines whether there are pedestrians. For example, the robot can be provided with a radar device, which scans the robot's surroundings to determine whether there are pedestrians.

[0076] S103: If there is a pedestrian in the environmental information, the identity of the pedestrian is determined based on the pedestrian's biological characteristics and activity behavior.

[0077] Among them, pedestrians include three identities: guests, employees, and unknown identities. Guests and employees are people who have registered their identities in the system, while unknown identities are people who are not registered in the system. For example, all employees are registered in the system and the robot is authorized to identify them; for example, guests register their identities when they check in and agree to the authorization, so that the robot can identify the guests; for example, if guests register their identities when they check in but do not agree to the authorization, the robot cannot identify them and they are identified as unknown identities; for example, people who have not registered are also identified as unknown identities.

[0078] In this embodiment, if it is confirmed that there are pedestrians around the robot, the pedestrians are detected and their identities are determined by obtaining the pedestrians' biometric features and activities. For example, the pedestrians' facial images are obtained and facial recognition is performed to confirm their identities; or the pedestrians' iris information, fingerprint information, etc. are obtained to confirm their identities. For example, when the pedestrians are a little far away from the robot and the biometric features that can be used to identify the pedestrians cannot be obtained, the pedestrians are first tracked based on their activities. If the pedestrians get closer to the robot, the pedestrians' biometric features are tried again to be obtained and their identities are determined based on the biometric features.

[0079] S104: Determine whether there is any suspicious behavior based on the identity of the pedestrian.

[0080] In this embodiment, since different identities have different permissions, it is necessary to determine whether the pedestrian has suspicious behavior based on the identity of the pedestrian. For example, it is assumed that employees have the permission to go to any room in any area. If there are employees around the robot, it is not considered suspicious behavior and there is no need to continuously monitor the behavior of the employees. For example, it is assumed that guests have the permission to go to the room they are staying in and the public area. If the guest follows the robot to the room they are staying in, it will not be considered suspicious behavior. For example, it should be understood that the permissions of the activity areas of each identity can be adjusted, different active areas can be set for employees, and the permissions of the public areas or other active areas that guests can go to can be adjusted. For example, the active areas of different guests can be adjusted according to the floor where the guest is staying or the additional services selected by the guest.

[0081] In some embodiments, see Figure 6 Step S104, determining whether there is suspicious behavior according to the identity of the pedestrian includes steps S301-S303:

[0082] S301: If the pedestrian is a guest, obtain the guest's check-in information to determine whether the guest is a guest of the target room.

[0083] Among them, the target room is the room corresponding to the goods delivered by the robot.

[0084] In this embodiment, if the identity of the pedestrians around the robot is a guest, then the check-in information of the guest is obtained, the room where the guest is staying is obtained, and compared with the target room to confirm whether the guest is the guest of the target room.

[0085] S302: If the guest is not a guest of the target room, determine the travel path between the guest's room and the public area.

[0086] In this embodiment, if the guest is not the guest of the target room, then the driving path of the guest's staying room and the public area is determined, that is, the driving path of the guest to the staying room and the driving path from the staying room to the public areas are determined, that is, the guest's movable area is determined.

[0087] S303: If the location of the guest does not belong to the driving route, it is determined that suspicious behavior exists.

[0088] In this embodiment, if the current location of the guest does not belong to the driving path, that is, the location of the guest does not belong to the guest's movable area, then it is determined that the guest has suspicious behavior.

[0089] For example, the guest checked into room 210, and the robot identified the guest in room 201 while performing a task on the second floor. There is no public area on the second floor, which is not an area where guests can move around. In this case, the guest is considered to have suspicious behavior. For example, the guest checked into room 210, and the robot identified the guest in room 201 while performing a task. The route from public areas such as fire escapes, elevators, and halls to room 210 does not pass through room 201, so the guest is considered to have suspicious behavior.

[0090] In this embodiment, by identifying the guest's identity and combining it with the guest's check-in information, the guest's behavior can be judged to determine whether the guest has any suspicious behavior. Combined with the judgment of the guest's identity, it can effectively reduce the misjudgment of guests who are just passing by the robot in normal activities, thereby improving the guest experience.

[0091] In some embodiments, step S104, determining whether there is suspicious behavior based on the identity of the pedestrian, further includes step S304:

[0092] S304: If the identity of the pedestrian is an unknown person, and the distance between the pedestrian and the robot is less than the first distance for more than a first time period, it is determined that suspicious behavior exists.

[0093] The first distance and the first duration are both set in advance, and can be set by an administrator or automatically set according to big data. For example, the first distance can be 1 meter, and the first duration can be two minutes.

[0094] In this embodiment, if the pedestrian is determined to be an unknown person, and the distance between the pedestrian and the robot is less than the first distance for more than the first time period, and the pedestrian continues to follow the robot, it is determined that there is suspicious behavior. For example, after determining that the pedestrian is an unknown person, the unknown person is tracked, the distance between the unknown person and the robot is obtained, and timing is performed. If the distance between the unknown person and the robot is less than the first distance and continues for more than the first time period, for example, the first distance is set to 1 meter, the first time period is two minutes, and if the unknown person follows the robot within one meter for more than two minutes, it is considered that there is suspicious behavior.

[0095] In this embodiment, when the specific identity of the pedestrian cannot be determined, that is, the pedestrian is an unknown person, determining whether there is suspicious behavior through the activities of the unknown person can more accurately identify suspicious behavior, and misjudgment can be reduced by judging the conditions of suspicious behavior. Because there may be some guests who are unwilling to authorize their biometrics to the robot in order to protect their privacy, it is directly judged as suspicious behavior if it cannot be detected as an unknown person. Through the embodiment of the present application, it is possible to make a more accurate judgment on whether the unknown person has suspicious behavior, reduce misjudgment, improve the guest experience, and protect the guest privacy.

[0096] In some embodiments, step S104, determining whether there is suspicious behavior based on the identity of the pedestrian, further includes step S305:

[0097] S305: If the pedestrian is an employee or a guest of the target room, it is determined that there is no suspicious behavior.

[0098] In this embodiment, if the identity of the pedestrian is determined to be an employee or a guest of the target room, it is determined that there is no suspicious behavior, and the employee and the guest of the target room can be stopped from being monitored and identified. It should be understood that for work needs, employees can go to each room by default, so if an employee follows the robot, it will not be considered a suspicious behavior. The robot goes to the target room to perform the delivery task. If it is a guest of the target room, it may come to pick up the goods or go to the target room with the robot, and it cannot be identified as a suspicious behavior. Therefore, if it is an employee or a guest of the target room, it is determined that there is no suspicious behavior.

[0099] It should be understood that in some embodiments, the employee's permissions regarding the movable area can be modified, so the determination of suspicious behavior must also be modified accordingly. Only when it is identified that the employee has the relevant permissions can it be determined that there is no suspicious behavior. If it is identified that the employee does not have the relevant permissions, it is determined that there is suspicious behavior.

[0100] In this embodiment, the absence of suspicious behavior is determined based on the identities of the employees and the guests in the target room, and normal people appearing around the robot can be quickly excluded, thereby reducing misjudgment behavior, improving guest satisfaction, and improving the robot's work efficiency.

[0101] S105: If suspicious behavior is detected, a response operation is performed according to the suspicious behavior.

[0102] In this embodiment, if suspicious behavior is detected, a response operation is performed. For example, the response operation may include pausing the task, issuing a voice warning, sending a warning reminder, notifying the management system, terminating the task and returning to the starting point, etc.

[0103] In summary, the anti-tailgating method provided by the embodiment of the present invention obtains task instructions, executes tasks according to the task instructions, obtains environmental information around the robot, and determines whether there are pedestrians according to the environmental information. If there are pedestrians in the environmental information, the identity of the pedestrian is determined by the biological characteristics and activity behavior of the pedestrian, wherein the identity of the pedestrian includes employees, guests and unknown persons, and whether there is suspicious behavior is determined according to the identity of the pedestrian. If suspicious behavior is detected, a response operation is performed according to the suspicious behavior. When the robot is performing a task, the environment around the robot can be detected to confirm whether there is suspicious behavior around, and a response operation is performed when suspicious behavior exists, which can effectively reduce tailgating behavior, prevent the use of the robot to enter unauthorized areas, improve safety, protect guest privacy, and improve guest satisfaction and trust.

[0104] In some embodiments, in step S105, if suspicious behavior is detected, executing a response operation according to the suspicious behavior includes step S401:

[0105] S401: If suspicious behavior is detected and the robot has reached the target room, the task will be suspended and a warning reminder will be issued.

[0106] In this embodiment, if suspicious behavior is detected and the robot has arrived at the target room, the task will be suspended immediately, and no arrival notification will be sent to the guest in the target room. Instead, the robot will stop at the spot and issue a warning reminder. For example, the warning reminder may include issuing a voice reminder, such as "The robot is performing a task. Please respect the privacy of other guests and avoid it." The warning reminder may also include a text reminder, such as displaying "The robot is performing a task. Please respect the privacy of other guests and avoid it" on the robot display unit to remind the suspicious person to leave and to remind the surrounding staff. The warning reminder may also include a remote reminder, such as a text reminder, an email reminder, a report to the management system, and a reminder to the staff to check the relevant monitoring through the network, etc., which is used to remotely remind the staff to pay attention to suspicious behavior and suspicious persons.

[0107] In some embodiments, after pausing the execution of a task and issuing a warning reminder, the task will not be continued and the guest in the target room will not be notified until a new authorization instruction is obtained.

[0108] In this embodiment, when suspicious behavior is detected and the robot has reached the target room, it stops executing the task and issues a warning to prevent the trailing personnel from entering the unauthorized room, and notifies them in time, which can improve safety and facilitate further processing by the staff.

[0109] In some embodiments, in step S105, if suspicious behavior is detected, executing a response operation according to the suspicious behavior also includes steps S402-S404:

[0110] S402: If suspicious behavior is detected and the robot has not reached the target room, it moves forward at the first speed.

[0111] S403: If no suspicious behavior is detected after the second period of time, the task continues to be executed.

[0112] S404: If suspicious behavior is still detected after the second period of time, the task is suspended and a warning reminder is issued.

[0113] Among them, the first speed is lower than the working speed of the robot, and the first speed and the second duration are set in advance, and can be set by an administrator or automatically set according to big data.

[0114] In this embodiment, if the robot has not reached the target room when suspicious behavior is detected, it will decelerate, move forward at the first speed, and continue to track the pedestrian who may have suspicious behavior. If there is no suspicious behavior after the second time period, for example, the pedestrian has left, the task can be continued. If there is still suspicious behavior after the second time period, the task will be suspended and a warning will be issued. That is, if the robot has not reached the target room when suspicious behavior is detected, it will be further verified by deceleration whether there is suspicious behavior. If the suspicious person also decelerates and continues to move closely around the robot, it is further determined that there is suspicious behavior, and the task will be suspended and a warning will be issued.

[0115] In this embodiment, suspicious behavior can be further verified by changing the travel speed, thereby improving the accuracy of identifying tailing behavior, reducing misjudgments, and improving robot efficiency.

[0116] In some embodiments, it should be understood that since the activities of the robot are affected by many factors, for example, when the robot passes through narrow roads, curves, slopes, thresholds, elevators and other areas, it usually slows down to ensure safety and stability, but normal people do not need to deliberately slow down in these areas. Therefore, if there are pedestrians around the robot, and the pedestrians also slow down when the robot encounters a special area and slows down, and keep a relatively stable distance from the robot, it is considered that there is abnormal behavior. The robot can perform a secondary verification by further deceleration. If the pedestrian also slows down after deceleration again and still keeps a relatively stable distance from the robot, the task is suspended and a warning is issued. The robot can also perform a secondary verification by stopping. If the pedestrian still stays near the robot after the robot stops, the task is suspended and a warning is issued. The robot can also perform a secondary verification by decelerating and stopping in sequence.

[0117] In some embodiments, the anti-tailgating method further includes step S501:

[0118] S501: After the robot arrives at the target room, if no suspicious behavior is detected, a pickup notification is sent to the guest of the target room.

[0119] In this embodiment, after the robot arrives at the target room according to the task instructions, if there is no suspicious behavior, a pickup notification is sent to the guest of the target room. For example, the pickup notification may include the situation at the door of the target room, such as a prompt such as "There are no pedestrians at the door of the target room, please feel free to pick up the goods", or a prompt such as "There is a staff member and a guest at the door of the target room, please pay attention", etc.

[0120] In this embodiment, the guest is reminded to pick up the goods only when there is no suspicious behavior, which can ensure the safety of the guest, reduce the occurrence of adverse events, improve the guest's sense of security, and protect the guest's privacy.

[0121] In some embodiments, after the robot arrives at the target room according to the task instruction and sends a pickup notification to the guest in the target room, the guest in the target room can view the environmental information around the robot through the user device to understand the external situation, such as viewing the real-time image of the robot's camera device through an app or applet on a mobile phone or computer. For example, the guest in the target room can also send a control instruction to the robot to control the robot to issue a reminder, such as playing a specified voice content through the robot. For example, the guest in the target room can also ask for help remotely from the management system or security personnel with one click.

[0122] In some embodiments, the robot records the entire execution process and any abnormal situations that occur during task execution, stores them locally, and synchronizes them with the management system for subsequent analysis and system optimization.

[0123] In summary, the anti-tailgating method provided by the embodiment of the present invention obtains task instructions, executes tasks according to the task instructions, obtains environmental information around the robot, and determines whether there are pedestrians according to the environmental information. If there are pedestrians in the environmental information, the identity of the pedestrian is determined by the biological characteristics and activity behavior of the pedestrian, wherein the identity of the pedestrian includes employees, guests and unknown persons, and whether there is suspicious behavior is determined according to the identity of the pedestrian. If suspicious behavior is detected, a response operation is performed according to the suspicious behavior. When the robot is performing a task, the environment around the robot can be detected to confirm whether there is suspicious behavior around, and a response operation is performed when suspicious behavior exists, which can effectively reduce tailgating behavior, prevent the use of the robot to enter unauthorized areas, improve safety, protect guest privacy, and improve guest satisfaction and trust.

[0124] Another embodiment of the present invention further provides a non-volatile computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are executed by at least one processor, the at least one processor executes the anti-tailgating method as described in any one of the above embodiments.

[0125] It should be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0126] Through the description of the above implementation methods, ordinary technicians in this field can clearly understand that each implementation method can be implemented by means of software plus a general hardware platform, and of course, it can also be implemented by hardware. Ordinary technicians in this field can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Under the concept of the present invention, the technical features in the above embodiments or different embodiments may also be combined, the steps may be implemented in any order, and there are many other changes in different aspects of the present invention as described above, which are not provided in detail for the sake of simplicity. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they may still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for preventing tailgating, for a robot, characterized in that: The method comprises: Obtaining a task instruction, and executing the task according to the task instruction; Acquire environmental information around the robot, and determine whether there are pedestrians based on the environmental information; If there is a pedestrian in the environmental information, the identity of the pedestrian is determined through the biological characteristics and activity behavior of the pedestrian, wherein the identity of the pedestrian includes employees, guests and unknown persons; Determining whether there is suspicious behavior based on the identity of the pedestrian; If suspicious behavior is detected, a response operation is performed based on the suspicious behavior.

2. The method according to claim 1, characterized in that The determining whether there is suspicious behavior according to the identity of the pedestrian includes: If the pedestrian is a guest, the check-in information of the guest is obtained to determine whether the guest is a guest of a target room, where the target room is the room corresponding to the goods delivered by the robot; If the guest is not a guest of the target room, determining the travel path between the guest's room and the public area; If the location of the guest does not belong to the driving route, it is determined that suspicious behavior exists.

3. The method according to claim 2, characterized in that The determining whether there is suspicious behavior according to the identity of the pedestrian also includes: If the identity of the pedestrian is an unknown person, and the distance between the pedestrian and the robot is less than a first distance for more than a first time period, it is determined that suspicious behavior exists.

4. The method according to claim 3, characterized in that The determining whether there is suspicious behavior according to the identity of the pedestrian also includes: If the identity of the pedestrian is an employee or a guest of the target room, it is determined that there is no suspicious behavior.

5. The method according to any one of claims 2-3, characterized in that: If a suspicious behavior is detected, a response operation is performed according to the suspicious behavior, including: If suspicious behavior is detected and the robot has arrived at the target room, the task will be suspended and a warning will be issued.

6. The method according to any one of claims 2-3, characterized in that: If a suspicious behavior is detected, a response operation is performed according to the suspicious behavior, including: If the robot has not reached the target room when suspicious behavior is detected, the robot moves forward at a first speed, which is lower than the working speed of the robot; If no suspicious behavior is detected after the second period of time, the task will continue; If suspicious behavior is still detected after the second period of time, the task will be suspended and a warning reminder will be issued.

7. The method according to claim 6, characterized in that The method further comprises: After the robot arrives at the target room, if the robot does not detect the suspicious behavior, it sends a pickup notification to the guest of the target room.

8. The method according to claim 1, characterized in that The obtaining of the task instruction and executing the task according to the task instruction comprises: Obtaining a task instruction, obtaining operator information, determining the identity of the operator according to the operator information, and if the operator is an employee or a guest of the target room, executing the task according to the task instruction; Otherwise, the task will not be executed and a warning will be given.

9. A robot, characterized in that: include: at least one processor, and A memory, wherein the memory is communicatively connected to the at least one processor, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described in any one of claims 1 to 8.

10. A non-volatile computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by at least one processor, the at least one processor is caused to execute the method according to any one of claims 1 to 8.

Images