Elevator control method and device based on man-machine integration and elevator system

Abstract

The invention aims at providing an elevator control method and device based on man-machine integration and an elevator system. The elevator control method comprises the steps that an elevator is continuously photographed to obtain an elevator taking image set; sampling each image in the elevator taking image group to obtain position information of passengers and objects in each image; generating an elevator space according to the elevator taking image group; passenger influence factors are calculated according to the elevator space and the position information of each passenger of the two adjacent images; calculating an elevator operation influence factor according to the elevator space, the elevator operation parameters, the position information of each passenger and each object in the last image of the elevator taking image group, and a standard anchor point parameter; according to the passenger influence factor, the elevator operation influence factor and state information of a robot, a man-machine co-fusion evaluation index is calculated; and when the man-machine co-fusion evaluation index is larger than a preset threshold value, an elevator stopping instruction and a robot elevator taking instruction are generated. According to the method, the information of the elevator running state, the passenger state and the robot state in the elevator control scene can be organically integrated, and whether the current condition can cooperatively meet the quantitative result of the requirements of passengers and robots for elevator use or not is judged.

Description

Technical Field

[0001] The present invention relates to the field of elevator control, and in particular to the technical field of an elevator control method, a control device and an elevator system based on human-machine integration. Background Art

[0002] Human-machine collaboration is a technology that aims to achieve natural and harmonious interaction between humans and machines. Its core goal is to enable machines to understand and adapt to human behavior and needs through intelligent algorithms, sensor technology, and human-machine interface design, thereby maximizing human-machine collaboration.

[0003] In a human-machine collaborative system, machines can dynamically adjust their behavior to match human activities by sensing human actions, emotions, and intentions. This technology is widely used in robotics, smart homes, medical assistance equipment, and other fields.

[0004] Although human-machine integration technology has made significant progress in many fields, its application in elevator control is still relatively lagging. The current elevator system mainly relies on traditional weight sensors and simple logic control, lacking intelligent and humanized interactive capabilities. This limitation is particularly prominent in the modern society where robots and smart devices are becoming increasingly popular.

[0005] With the popularization of smart buildings and automated equipment, robots are playing an increasingly important role in public places. As an important means of transportation in buildings, elevators urgently need to be upgraded to adapt to this trend. Summary of the invention

[0006] Based on this, the object of the present invention is to provide an elevator control method, a control device and an elevator system based on human-machine integration, which include:

[0007] Take a group of elevator images by taking continuous photos inside the elevator;

[0008] Generate an elevator space according to the elevator image group; and sample each image in the elevator image group to obtain position information of each passenger and position information of each object in each image;

[0009] Calculate a passenger impact factor S according to the elevator space and the position information of each passenger in at least two adjacent images in the elevator image group;

[0010] Calculate the elevator operation influencing factor F according to the elevator space, the position information of each passenger and each object in the last image of the elevator image group, the elevator operation parameters and a standard anchor point parameter; wherein the elevator operation parameters include the rated load capacity of the elevator and the current load capacity of the elevator;

[0011] Calculate the human-machine integration evaluation index L according to the passenger impact factor S, the elevator operation impact factor F, and the operation status R of the robot to be boarded;

[0012] When the human-machine integration evaluation index L is greater than a preset threshold, an elevator stop instruction and a robot elevator boarding instruction are generated, otherwise a robot waiting instruction is generated.

[0013] The control method can organically integrate the information of the elevator operation status, passenger status and robot status in the elevator control scene, and determine whether the current situation can collaboratively meet the quantitative results of the needs of passengers and robots for elevator use. The method can also realize the pre-determination of the elevator stop, avoiding the process of the robot repeatedly trying to enter the elevator to determine whether it can take the elevator, improving the human-machine integrated elevator scheduling, and helping to improve the intelligence and efficiency of elevator control. At the same time, when there are already passengers in the elevator, the control method of the present invention is conducive to ensuring the safety of the passengers in the elevator, and is also conducive to improving the work efficiency of the robot.

[0014] Furthermore, the passenger impact factor is obtained through the following steps:

[0015] Determine the three-dimensional spatial position coordinates of each passenger in each image of the elevator space according to the position information of each passenger in at least two adjacent images;

[0016] According to the three-dimensional spatial position coordinates of each passenger in each image, the passenger influence factor S is calculated according to the following formula:

[0017]

[0018] In the formula, m represents the total number of passengers in the current elevator, i represents the serial number of the passenger in the current elevator, j represents the serial number of the sampling point on a certain passenger in the current elevator, n represents the total number of sampling points on a certain passenger in the current elevator, t1 represents the starting time of the preset sampling time, t2 represents the ending time of the preset sampling time, is the coordinate of the horizontal axis of the jth sampling point on the i-th passenger in the current elevator corresponding to time t1, is the coordinate of the vertical axis of the jth sampling point on the i-th passenger in the current elevator corresponding to time t2, is the coordinate of the depth axis corresponding to the jth sampling point on the i-th passenger in the current elevator corresponding to time t2.

[0019] Furthermore, the elevator operation influencing factor F is obtained through the following steps:

[0020] Calculating the center of gravity coordinate information of each passenger and object in the elevator according to the elevator space and the position information of each passenger and object;

[0021] Calculating diagonal coordinate information of each passenger and object in the elevator according to the elevator space and the position information of each passenger and object;

[0022] According to the rated load of the elevator, the current load of the elevator, the center of gravity coordinate information of each passenger and object in the elevator, the diagonal coordinate information of each passenger and object, and the standard anchor point parameters, the elevator operation impact factor F is calculated according to the following formula:

[0023]

[0024] Where G is the current load of the elevator, G max is the rated load of the elevator, b is the total number of sampling points for the center of gravity of objects and / or human bodies in the elevator, a is the sequence number of the sampling points for the center of gravity of objects and / or human bodies in the elevator, and x a ,y a 、z a x represents the coordinates of the horizontal axis, the vertical axis and the depth axis of the a-th sampling point of the object and / or human body in the elevator respectively; c ,y c and z c represents the coordinates of the horizontal axis, the vertical axis and the depth axis corresponding to the predetermined anchor point c in the elevator; h represents the total number of diagonal samples of objects and / or human bodies in the elevator, g represents the sample number of the diagonal samples of objects and / or human bodies in the elevator, x represents the sample number of the diagonal samples of objects and / or human bodies in the elevator, g1 ,y g1 and z g1 represents the coordinates of the horizontal axis, the vertical axis, and the depth axis of one of the endpoints on the diagonal of the object and / or human body in the elevator corresponding to the g-th sample, i.e., point g1. g2 ,y g2 and z g2 The coordinates of the horizontal axis, the vertical axis, and the depth axis of the other endpoint g2 on the diagonal line of the object and / or human body in the elevator corresponding to the g-th sample, x f1 ,y f1 and z f1 represents the coordinates of the horizontal axis, the vertical axis, and the depth axis corresponding to one of the endpoints of the predetermined diagonal line f1f2 in the elevator, namely, point f1. f2 ,y f2 and z f2 The coordinates corresponding to the horizontal axis, the vertical axis, and the depth axis represent the coordinates of the point f2, which is one of the endpoints on the predetermined diagonal line f1f2 in the elevator.

[0025] Furthermore, the human-machine integration evaluation index L is obtained by the following formula:

[0026]

[0027] Where M represents the mapping value of the Boolean value of whether the elevator is faulty to the digital quantity, F is the elevator operation influencing factor, B is the mapping value of the Boolean value of the passenger age binary classification to the digital quantity, S is the passenger influencing factor, and R represents the mapping value of the Boolean value of the robot's operating status to the digital quantity.

[0028] Furthermore, the robot operation state R is specifically:

[0029] R=r1·r2·r3

[0030] Among them, r1 represents the mapping value of the Boolean value of whether the robot is in an unloaded state to the digital quantity, r2 represents the mapping value of the Boolean value of whether the robot's current task is an emergency state to the digital quantity, and r3 represents whether the robot needs to perform a disinfection task.

[0031] Furthermore, the threshold range of the human-machine integration evaluation index is [0, 1].

[0032] In a second aspect, the present invention provides an elevator control device based on human-machine integration, which includes:

[0033] Image acquisition device: used to continuously take photos of the interior of the elevator to obtain a group of elevator images;

[0034] An elevator space information acquisition unit is used to generate an elevator space according to the elevator image group; and to sample each image in the elevator image group to obtain the position information of each passenger and each object in each image;

[0035] A passenger impact factor calculation unit: used to calculate a passenger impact factor S according to the elevator space and the position information of each passenger in at least two adjacent images;

[0036] An elevator operation impact factor calculation unit: calculates an elevator operation impact factor F according to the elevator space, elevator operation parameters, position information of each passenger and position information of each object in the last image of the elevator image group, and a standard anchor point parameter;

[0037] A human-machine integration evaluation index calculation unit: used to calculate a human-machine integration evaluation index L according to the passenger impact factor S, the elevator operation impact factor F and a robot state information R;

[0038] Control unit: used to generate an elevator stop instruction and a robot elevator boarding instruction when the human-machine integration evaluation index is greater than a preset threshold; otherwise, generate a robot waiting instruction.

[0039] Furthermore, the passenger influence factor calculation unit includes:

[0040] The spatial position matching subunit determines the three-dimensional spatial position coordinates of each passenger in each image of the elevator space according to the position information of each passenger in at least two adjacent images;

[0041] Passenger influence factor calculation subunit: used to calculate the passenger influence factor S according to the three-dimensional spatial position coordinate information of each passenger according to the following formula:

[0042]

[0043] In the formula, m represents the total number of passengers in the current elevator, i represents the serial number of the passenger in the current elevator, j represents the serial number of the sampling point on a certain passenger in the current elevator, n represents the total number of sampling points on a certain passenger in the current elevator, t1 represents the starting time of the preset sampling time, t2 represents the ending time of the preset sampling time, is the coordinate of the horizontal axis of the jth sampling point on the i-th passenger in the current elevator corresponding to time t1, is the coordinate of the vertical axis of the jth sampling point on the i-th passenger in the current elevator corresponding to time t2, is the coordinate of the depth axis corresponding to the jth sampling point on the i-th passenger in the current elevator corresponding to time t2.

[0044] In a third aspect, the present invention also provides an elevator system based on human-machine integration, which includes

[0045] A robot, an elevator control device based on human-machine collaboration as described in any one of the above, and an elevator;

[0046] The elevator control device based on human-machine integration is used to generate a human-machine integration evaluation index according to the acquired elevator image group in the elevator and the robot's status information after receiving the robot's elevator demand instruction; and control the robot movement and elevator stop according to the human-machine integration evaluation index.

[0047] In a fourth aspect, the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of the human-machine collaborative elevator control method described in any one of the above are implemented.

[0048] For better understanding and implementation, the present invention is described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a structural block diagram of the elevator system based on human-machine integration of the present invention;

[0050] Figure 2 It is a structural block diagram of an elevator control device based on human-machine integration of the present invention;

[0051] Figure 3 for Figure 2 A flow chart of a control method of an elevator control device shown;

[0052] Figure 4 It is a structural block diagram of the subunits of the passenger influence factor calculation unit of the present invention;

[0053] Figure 5 for Figure 4 The execution flow chart of the sub-units of the passenger influence factor calculation unit is shown.

[0054] The technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiments of the present application. DETAILED DESCRIPTION

[0055] In existing elevator systems, the integration of human-machine collaboration technology is relatively superficial. Usually, the robot sends out elevator stop information, and the control unit or control center controls the elevator to stop based on the elevator stop information. Then the robot enters the elevator and scans or photographs the space inside the elevator based on its own sensors and image acquisition equipment, and then calculates to determine whether the robot's elevator riding needs can be met; or a robot stop space is preset in the elevator, and when a person or object is scanned in the robot stop space, a warning message is issued to remind passengers to move or remove the object. Although this control method can realize the intelligent control of elevators and robots to a certain extent, the robot's scanning process and adjustment process greatly affect the elevator's operating efficiency and the passengers' elevator experience.

[0056] Based on the above problems, the present invention provides an elevator control method based on human-machine integration, a control device is used to control the existing robot-elevator system, and a Figure 1 The human-machine collaborative elevator system shown in the figure integrates the elevator operation status, passenger status and robot status in the elevator scene during the elevator operation, and outputs a quantitative result to indicate whether the status (including elevator, passenger and robot) can collaboratively meet the passenger and robot's needs for elevator use. It ultimately achieves pre-determination of the elevator stop, avoids the robot's repeated attempts to enter the elevator to determine whether it can take the elevator, improves human-machine collaborative elevator scheduling, and is conducive to improving the intelligence and efficiency of elevator control. Figure 2The elevator control device based on human-machine integration of the present invention comprises: an image acquisition device 10, an image sampling unit 20, an elevator space generation unit 22, a passenger influence factor calculation unit 31, an elevator operation influence factor calculation unit 32, a human-machine integration evaluation index calculation unit 40 and a control unit 50. The elevator control process based on human-machine integration is completed by the above components, please refer to Figure 3 , Figure 3 for Figure 2 The flowchart of the control method of the elevator control device is shown in FIG. 1 , and the execution flow of each component of the elevator control device is as follows:

[0057] Obtain a set of elevator images obtained by continuously photographing the interior of the elevator;

[0058] Generate an elevator space according to the elevator image group; and sample each image in the elevator image group to obtain position information of each passenger and position information of each object in each image;

[0059] Calculate a passenger impact factor S according to the elevator space and the position information of each passenger in at least two adjacent images in the elevator image group;

[0060] Calculate the elevator operation influencing factor F according to the elevator space, the position information of each passenger and each object in the last image of the elevator image group, the elevator operation parameters and a standard anchor point parameter; wherein the elevator operation parameters include the rated load capacity of the elevator and the current load capacity of the elevator;

[0061] Calculate the human-machine integration evaluation index L according to the passenger impact factor S, the elevator operation impact factor F, and the operation status R of the robot to be boarded;

[0062] When the human-machine integration evaluation index L is greater than a preset threshold, an elevator stop instruction and a robot elevator boarding instruction are generated; otherwise, a robot waiting instruction is generated.

[0063] The image acquisition device 10 is used to execute step S10: acquiring a group of elevator images obtained by continuously photographing the interior of the elevator;

[0064] In an embodiment of the present invention, the image acquisition device is a camera installed in the elevator. When the robot sends a request to take the elevator, the camera of the elevator control device starts to take pictures to obtain real-time images in the elevator, and obtains a passenger image group consisting of a group of continuous images.

[0065] The image sampling unit 20 is used to execute step S20: generate an elevator space according to the elevator image group; and sample each image in the elevator image group to obtain the position information of each passenger and each object in each image;

[0066] The image acquisition unit performs image analysis on each image of the passenger image group and performs key point sampling on different passengers and objects to obtain the position information of each passenger and each object in each image for subsequent analysis and processing.

[0067] Different elevators have inconsistent internal structure sizes. In order to achieve automatic matching of different elevator scenes, the present invention realizes the reorganization of the elevator space through an elevator space generation unit. According to the images of the elevator image group, a vertex in the elevator is used as the coordinate origin of the elevator space to establish a three-dimensional elevator space coordinate system, thereby generating the elevator space.

[0068] The passenger impact factor calculation unit 31 is used to execute step S31: calculate the passenger impact factor S according to the elevator space and the position information of each passenger in at least two adjacent images in the elevator image group; Figure 4 and Figure 5 Specifically, the passenger influence factor calculation unit 31 includes:

[0069] The spatial position matching subunit 311 is used to perform step S311: determine the three-dimensional spatial position coordinates of each passenger in each image of the elevator space according to the position information of each passenger in at least two adjacent images;

[0070] After establishing a three-dimensional space coordinate system with the boundary point in the elevator as the coordinate origin, the spatial coordinates (x, y, z) of each point in the elevator are all positive numbers. The position information of each passenger is converted into the three-dimensional space with the elevator space as the reference, and the three-dimensional space position coordinate information of each passenger in the elevator space is obtained.

[0071] The passenger influence factor calculation subunit 312 is used to execute step S312: according to the three-dimensional spatial position coordinate information of each passenger, the passenger influence factor S is calculated according to the following formula:

[0072]

[0073] In the formula, m represents the total number of passengers in the current elevator, i represents the serial number of the passenger in the current elevator, j represents the serial number of the sampling point on a certain passenger in the current elevator, n represents the total number of sampling points on a certain passenger in the current elevator, t1 represents the starting time of the preset sampling time, t2 represents the ending time of the preset sampling time, is the coordinate of the horizontal axis of the jth sampling point on the i-th passenger in the current elevator corresponding to time t1, is the coordinate of the vertical axis of the jth sampling point on the i-th passenger in the current elevator corresponding to time t2, is the coordinate of the depth axis corresponding to the jth sampling point on the i-th passenger in the current elevator corresponding to time t2.

[0074] The above-mentioned coordinates can be coordinates in a three-dimensional space corresponding to the real space constructed based on the images taken by the camera installed in the elevator. The passenger influence factor obtained through the above calculation can dynamically characterize the current passenger movement status of the elevator, which can not only reflect the current passenger position status, but also reflect the tendency of passenger position change, which is conducive to further analysis of subsequent passenger status.

[0075] The elevator operation impact factor calculation unit 32 is used to execute step S32: calculate the elevator operation impact factor F according to the elevator space, the elevator operation parameters, the position information of each passenger and the position information of each object in the last image of the elevator image group, and a standard anchor point parameter, wherein the elevator operation parameters include the rated load capacity of the elevator and the current load capacity of the elevator; wherein step S32 includes:

[0076] S321: Calculating the center of gravity coordinate information of each passenger and object in the elevator according to the elevator space and the position information of each passenger and object;

[0077] Although weight has a certain impact on elevator riding, in a human-machine integrated environment, the robot's footprint and its weight ratio are relative to the human body, and the robot's center of gravity position has a much greater impact on the center of gravity position of the entire elevator than the passenger's. The offset of the center of gravity position will directly affect the loss of the elevator's traction rope. Therefore, the present invention calculates the center of gravity based on the passenger's position information. If the passengers and objects are regarded as having uniformly distributed mass, then their geometric center of gravity is the location of the center of gravity, and finally the center of gravity coordinate information of each passenger and object is obtained.

[0078] S322: Calculating diagonal coordinate information of each passenger and object in the elevator according to the elevator space and the position information of each passenger and object;

[0079] Combining the diagonal coordinate information is to further refine the space occupied by the object, and use the diagonal to represent the position of the object in the elevator space. Combined with the sampled three-dimensional space coordinates, even with a small number of sampling points as the data source, it is possible to accurately express the position and space of passengers or objects.

[0080] S323: Calculate the elevator operation impact factor F according to the rated load of the elevator, the current load of the elevator, the center of gravity coordinate information of each passenger and object in the elevator, the diagonal coordinate information of each passenger and object, and the standard anchor point parameters according to the following formula:

[0081]

[0082] Where G is the current load of the elevator, G max is the rated load of the elevator, b is the total number of sampling points for the center of gravity of objects and / or human bodies in the elevator, a is the sequence number of the sampling points for the center of gravity of objects and / or human bodies in the elevator, and x a ,y a 、z a x represents the coordinates of the horizontal axis, the vertical axis and the depth axis of the a-th sampling point of the object and / or human body in the elevator respectively; c ,y c and z c represents the coordinates of the horizontal axis, the vertical axis and the depth axis corresponding to the predetermined anchor point c in the elevator; h represents the total number of diagonal samples of objects and / or human bodies in the elevator, g represents the sample number of the diagonal samples of objects and / or human bodies in the elevator, x represents the sample number of the diagonal samples of objects and / or human bodies in the elevator, g1 ,y g1 and z g1 represents the coordinates of the horizontal axis, the vertical axis, and the depth axis of one of the endpoints on the diagonal of the object and / or human body in the elevator corresponding to the g-th sample, i.e., point g1. g2 ,y g2 and z g2 The coordinates of the horizontal axis, the vertical axis, and the depth axis of the other endpoint g2 on the diagonal line of the object and / or human body in the elevator corresponding to the g-th sample, x f1 ,y f1 and z f1 represents the coordinates of the horizontal axis, the vertical axis, and the depth axis corresponding to one of the endpoints of the predetermined diagonal line f1f2 in the elevator, namely, point f1. f2 ,y f2 and z f2 The coordinates corresponding to the horizontal axis, the vertical axis, and the depth axis represent the coordinates of the point f2, which is one of the endpoints on the predetermined diagonal line f1f2 in the elevator.

[0083] Through the above calculations, the influence of the load and center of gravity distribution in the elevator on the operating state of the elevator is determined.

[0084] The human-machine integration evaluation index calculation unit 40 is used to execute step S40: calculate a human-machine integration evaluation index L according to the passenger impact factor S, the elevator operation impact factor F and the state information R of a robot;

[0085] Among them, the human-machine integration evaluation index L is obtained by the following formula:

[0086]

[0087] Where M represents the mapping value of the Boolean value of whether the elevator is faulty to the digital quantity, F is the elevator operation influencing factor, B is the mapping value of the Boolean value of the passenger age binary classification to the digital quantity, S is the passenger influencing factor, and R represents the mapping value of the Boolean value of the robot's operating status to the digital quantity.

[0088] The evaluation is completed by combining the passenger impact factor, the elevator operation impact factor F and the status information R of a robot.

[0089] In the present invention, M represents the mapping value of the Boolean value of whether the elevator has a fault on the digital quantity. For example, when the elevator has a fault, the corresponding Boolean value is 0, and when the elevator has no fault (normal operation), the corresponding Boolean value is 1; further, when the elevator has a fault, the corresponding Boolean value mapping value on the digital quantity is 0, and when the elevator has no fault, the corresponding Boolean value mapping value on the digital quantity is 1.

[0090] B represents the mapping value of the Boolean value of the passenger's age binary classification to the digital quantity. For example, when the age of the passenger in the elevator is between 14 and 50 years old, the corresponding Boolean value is 0, and when the age of the passenger in the elevator is outside the range of 14 to 50 years old, the corresponding Boolean value is 1; further, when the age of the passenger in the elevator is between 14 and 50 years old, the corresponding Boolean value mapping value to the digital quantity is 0, and when the age of the passenger in the elevator is outside the range of 14 to 50 years old, the corresponding Boolean value mapping value to the digital quantity is 1.

[0091] R represents the mapping value of the Boolean value of the robot's operating state to the digital quantity. The operating state of the robot may include two types of operating states: whether it is unloaded, whether the current task is an emergency state, and / or whether the robot needs to perform a disinfection task. Optionally, R = r1·r2·r3, wherein r1 represents the mapping value of the Boolean value of whether the robot is in an unloaded state to the digital quantity, r2 represents the mapping value of the Boolean value of whether the robot's current task is an emergency state to the digital quantity, and r3 represents the mapping value of the Boolean value of whether the robot needs to perform a disinfection task (such as a task that requires disinfection in the elevator) to the digital quantity. When the robot is in a no-load state, the mapping value of the corresponding Boolean value about the digital quantity is 1, and when the robot is in a non-no-load state, the mapping value of the corresponding Boolean value about the digital quantity is 0; when the robot's current task is an emergency state, the mapping value of the corresponding Boolean value about the digital quantity is 1, and when the robot's current task is a non-emergency state, the mapping value of the corresponding Boolean value about the digital quantity is 0; when the robot needs to perform a disinfection task, the mapping value of the corresponding Boolean value about the digital quantity is 0, and when the robot does not need to perform a disinfection task, the mapping value of the corresponding Boolean value about the digital quantity is 1.

[0092] The control unit 50 is used to execute step S50: when the human-machine integration evaluation index is greater than a preset threshold, an elevator stop instruction and a robot elevator boarding instruction are generated; otherwise, a robot waiting instruction is generated.

[0093] The control unit determines the human-machine integration evaluation index based on the current operation status information of the elevator, the status information of the passengers in the elevator, and the status information of the robot, and determines whether the human-machine integration evaluation index is greater than or equal to a predetermined threshold value. If so, it determines to generate a stop instruction based on the need of the robot to take the elevator. The threshold range of the predetermined human-machine integration evaluation index can be [0,1]. Or the condition of the elevator is not sufficient to meet the robot's riding, and the elevator control device sends a waiting instruction to the robot. Among them, the stop instruction indicates that the elevator needs to stop at a specific floor. Optionally, the priority of the stop instruction can be consistent with the stop instruction triggered by the passenger; it can also be adjusted according to the actual application scenario to improve the efficiency of elevator use. For example, in the office building scenario, during the work / off-get off work period, the stop instruction sent by the robot has a lower priority than the stop instruction triggered by the user through the elevator door button, and it can even be considered to block the stop instruction sent by the robot; for example, in the office building scenario, after the end of the evening rush hour until the beginning of the next morning rush hour, the stop instruction sent by the robot and the stop instruction triggered by the user through the elevator door button have the same priority.

[0094] The present invention proposes an elevator control method based on human-machine integration. First, the elevator operation status, passenger status and robot status in the elevator scene are organically integrated, and the quantitative results used to indicate whether the status (including elevator, passenger and robot) can collaboratively meet the passenger and robot's needs for elevator use are output, and finally the pre-determination of the elevator stop is realized, avoiding the process of the robot repeatedly trying to enter the elevator to determine whether it can take the elevator, improving the elevator scheduling based on human-machine integration, and being conducive to improving the intelligence and efficiency of elevator control and ensuring the safety of passengers in the elevator when there are passengers in the elevator. In the judgment process, the influence of the center of gravity factor on the robot taking the elevator is integrated, avoiding the loss of the elevator traction rope caused by the displacement of the center of gravity of the fully loaded robot to the overall center of gravity of the elevator, and improving the harmony of human-machine integration.

[0095] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the human-machine collaborative elevator control method described in any one of the above embodiments are implemented.

[0096] The present invention may take the form of a computer program product implemented on one or more storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing program code. Computer-readable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be achieved by any method or technology. The information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include but are not limited to: phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0097] The above-mentioned embodiments only express several implementation methods of the present invention, and the description is relatively specific and detailed, but it cannot be understood as limiting the scope of the invention patent. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. An elevator control method based on human-machine collaboration, characterized in that: include: Obtain a set of elevator images obtained by continuously photographing the interior of the elevator; Generate an elevator space according to the elevator riding image group; and, sampling each image in the elevator image group to obtain position information of each passenger and position information of each object in each image; Calculate a passenger impact factor S according to the elevator space and the position information of each passenger in at least two adjacent images in the elevator image group; Calculate the elevator operation influencing factor F according to the elevator space, the position information of each passenger and each object in the last image of the elevator image group, the elevator operation parameters and a standard anchor point parameter; wherein the elevator operation parameters include the rated load capacity of the elevator and the current load capacity of the elevator; Calculate the human-machine integration evaluation index L according to the passenger impact factor S, the elevator operation impact factor F, and the operation status R of the robot to be boarded; When the human-machine integration evaluation index L is greater than a preset threshold, an elevator stop instruction and a robot elevator boarding instruction are generated, otherwise a robot waiting instruction is generated.

2. The human-machine collaborative elevator control method according to claim 1, characterized in that: The passenger impact factor S is obtained by the following steps: Determine the three-dimensional spatial position coordinates of each passenger in each image of the elevator space according to the position information of each passenger in at least two adjacent images; According to the three-dimensional spatial position coordinates of each passenger in each image, the passenger influence factor S is calculated according to the following formula: In the formula, m represents the total number of passengers in the current elevator, i represents the serial number of the passenger in the current elevator, j represents the serial number of the sampling point on a certain passenger in the current elevator, n represents the total number of sampling points on a certain passenger in the current elevator, t1 represents the starting time of the preset sampling time, t2 represents the ending time of the preset sampling time, is the coordinate of the horizontal axis of the jth sampling point on the i-th passenger in the current elevator corresponding to time t1, is the coordinate of the vertical axis of the jth sampling point on the i-th passenger in the current elevator corresponding to time t2, is the coordinate of the depth axis corresponding to the jth sampling point on the i-th passenger in the current elevator corresponding to time t2.

3. The human-machine collaborative elevator control method according to claim 2, characterized in that: The elevator operation influencing factor F is obtained by the following steps: Calculate the center of gravity coordinate information of each passenger and the center of gravity coordinate information of each object in the elevator according to the elevator space and the position information of each passenger and the position information of each object; Calculate the diagonal coordinate information of each passenger and the diagonal coordinate information of each object in the elevator according to the elevator space and the position information of each passenger and the position information of each object; According to the rated load of the elevator, the current load of the elevator, the center of gravity coordinate information of each passenger and each object in the elevator, the diagonal coordinate information of each passenger and each object, and the standard anchor point parameters, the elevator operation impact factor F is calculated according to the following formula: Where G is the current load of the elevator, G max is the rated load of the elevator, b is the total number of sampling points for the center of gravity of objects and / or human bodies in the elevator, a is the sequence number of the sampling points for the center of gravity of objects and / or human bodies in the elevator, and x a ,y a 、z a x represents the coordinates of the horizontal axis, the vertical axis and the depth axis of the a-th sampling point of the object and / or human body in the elevator respectively; c ,y c and z c represents the coordinates of the horizontal axis, the vertical axis and the depth axis corresponding to the predetermined anchor point c in the elevator; h represents the total number of diagonal samples of objects and / or human bodies in the elevator, g represents the sample number of the diagonal samples of objects and / or human bodies in the elevator, x represents the sample number of the diagonal samples of objects and / or human bodies in the elevator, g1 ,y g1 and z g1 represents the coordinates of the horizontal axis, the vertical axis, and the depth axis of one of the endpoints on the diagonal of the object and / or human body in the elevator corresponding to the g-th sample, i.e., point g1. g2 ,y g2 and z g2 The coordinates of the horizontal axis, the vertical axis, and the depth axis of the other endpoint g2 on the diagonal line of the object and / or human body in the elevator corresponding to the g-th sample, x f1 ,y f1 and z f1 represents the coordinates of the horizontal axis, the vertical axis, and the depth axis corresponding to one of the endpoints of the predetermined diagonal line f1f2 in the elevator, namely, point f1. f2 ,y f2 and z f2 The coordinates corresponding to the horizontal axis, the vertical axis, and the depth axis represent the coordinates of the point f2, which is one of the endpoints on the predetermined diagonal line f1f2 in the elevator.

4. The human-machine collaborative elevator control method according to claim 3, characterized in that: The human-machine integration evaluation index L is obtained by the following formula: Where M represents the mapping value of the Boolean value of whether the elevator is faulty to the digital quantity, F is the elevator operation influencing factor, B is the mapping value of the Boolean value of the passenger age binary classification to the digital quantity, S is the passenger influencing factor, and R represents the mapping value of the Boolean value of the robot's operating status to the digital quantity.

5. The human-machine collaborative elevator control method according to claim 4, characterized in that: The robot running state R is specifically: R＝r1·r2·r3 Among them, r1 represents the mapping value of the Boolean value of whether the robot is in an unloaded state to the digital quantity, r2 represents the mapping value of the Boolean value of whether the robot's current task is an emergency state to the digital quantity, and r3 represents whether the robot needs to perform a disinfection task.

6. The human-machine collaborative elevator control method according to any one of claims 1 to 5, characterized in that: The threshold range of the human-machine integration evaluation index is [0, 1].

7. The elevator control device based on human-machine integration is characterized in that: include: Image acquisition device: used to continuously take photos of the interior of the elevator to obtain a group of elevator images; Image sampling unit: used for sampling each image in the elevator image group to obtain the position information of each passenger and each object in each image; An elevator space generating unit is used to generate an elevator space according to the elevator image group; A passenger impact factor calculation unit: used to calculate a passenger impact factor S according to the elevator space and the position information of each passenger in at least two adjacent images; An elevator operation impact factor calculation unit: calculates an elevator operation impact factor F according to the elevator space, elevator operation parameters, position information of each passenger and position information of each object in the last image of the elevator image group, and a standard anchor point parameter; A human-machine integration evaluation index calculation unit: used to calculate a human-machine integration evaluation index L according to the passenger impact factor S, the elevator operation impact factor F and a robot state information R; Control unit: used to generate an elevator stop instruction and a robot elevator boarding instruction when the human-machine integration evaluation index is greater than a preset threshold; otherwise, generate a robot waiting instruction.

8. The elevator control device based on human-machine integration according to claim 7, characterized in that: The passenger influence factor calculation unit comprises: The spatial position matching subunit determines the three-dimensional spatial position coordinates of each passenger in each image of the elevator space according to the position information of each passenger in at least two adjacent images; Passenger influence factor calculation subunit: used to calculate the passenger influence factor S according to the three-dimensional spatial position coordinate information of each passenger according to the following formula: In the formula, m represents the total number of passengers in the current elevator, i represents the serial number of the passenger in the current elevator, j represents the serial number of the sampling point on a certain passenger in the current elevator, n represents the total number of sampling points on a certain passenger in the current elevator, t1 represents the starting time of the preset sampling time, t2 represents the ending time of the preset sampling time, t k The coordinates of the horizontal axis of the jth sampling point on the i-th passenger in the current elevator corresponding to the time, t k The coordinates of the vertical axis of the jth sampling point on the i-th passenger in the current elevator corresponding to the time, t k The coordinates corresponding to the depth axis of the j-th sampling point on the i-th passenger in the current elevator corresponding to the time, k=1, 2.

9. The elevator system based on human-machine integration is characterized by: include: An elevator, an elevator control device based on human-machine collaboration and a robot as described in any one of claims 7 to 8; The elevator control device based on human-machine integration is used to generate a human-machine integration evaluation index according to the acquired elevator image group in the elevator and the robot's status information after receiving the robot's elevator demand instruction; and control the robot movement and elevator stop according to the human-machine integration evaluation index.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the human-machine collaborative elevator control method according to any one of claims 1 to 6 are implemented.

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