User behavior acquisition and processing method, system and robot for robots

Abstract

This application proposes a method, system and robot for obtaining and processing user behavior for robots, the method comprising: selecting a simulation object; screening work items and dividing them into terminal work items and non-terminal work items; obtaining a work map and dividing it into multiple sub-areas, assigning non-terminal trigger conditions to each sub-area; when it is sensed that the simulation object has arrived at a certain sub-area and the non-terminal trigger conditions are met, collecting the non-terminal data of the simulation object; obtaining the terminal data of the simulation object; processing and analyzing the terminal data and the non-terminal data, so that the robot executes the simulation work items according to the behavioral habits. This application divides the work items into terminal work items and non-terminal work items, and collects and processes these two types of data differently, so as to train the robot to more accurately and comprehensively imitate the user's work behavior.

Description

Technical Field

[0001] The present application relates to the field of role simulation, and more specifically, to a method, system and robot for obtaining and processing user behavior of a robot. Background Art

[0002] With the rapid development of artificial intelligence technology, robots are increasingly used in various industries, especially in simulating human work roles and performing specific work tasks. Traditionally, corporate organizations rely on manual labor to complete various complex and repetitive tasks, such as data analysis, customer service, production scheduling, etc. However, this method has problems such as low efficiency, high cost, and prone to errors. In addition, as business needs continue to change, the skill requirements for employees are also constantly increasing, resulting in long training cycles and poor adaptability.

[0003] In the existing technology, although there are some automation tools and robotic process automation solutions that attempt to solve the above problems, they are often limited to predefined rules and processes, lack flexibility and learning ability, and cannot effectively adapt to changes in work processes or differences in personal work habits. Furthermore, these systems often fail to fully utilize the experience and knowledge of existing employees when simulating specific work roles, which limits the effect and depth that can be achieved by automation. In addition, employees' work behavior data is complex and involves not only behavioral data when working with terminals, but also a lot of behavioral data when working with non-terminals. When dealing with some projects that use methods other than terminals to work, it is difficult to accurately collect data. Summary of the invention

[0004] Based on the problems existing in the prior art, this application provides a method, system and robot for obtaining and processing user behavior for robots. The specific solution is as follows:

[0005] The present application proposes a method for obtaining and processing user behavior for a robot, wherein the robot is used to simulate a specific person to perform work, and the method comprises:

[0006] Select a specific simulation object under a certain work role, wherein the simulation object has some work items that can only be completed with the help of a preset work terminal;

[0007] Filter out the work items of the simulation object that can be executed by the robot to obtain simulation work items, and divide the simulation work items into terminal work items and non-terminal work items according to whether they rely on the work terminal to be completed;

[0008] Obtaining a work map corresponding to the work environment in which the simulation object is located, dividing the work map into a plurality of sub-areas according to the functional type of the area, and assigning a non-terminal trigger condition to each sub-area according to the non-terminal work item;

[0009] When it is sensed that the simulated object has reached a certain sub-area and meets the non-terminal trigger condition of the sub-area, the working behavior of the simulated object in dealing with the non-terminal work item is collected by a preset data collection device to obtain non-terminal data; the working behavior of the simulated object in dealing with the terminal work item is obtained by a preset monitoring program to obtain terminal data;

[0010] The terminal data and the non-terminal data are processed to analyze the behavior habits of the simulated object when dealing with terminal work items and non-terminal work items and input them into the robot, so that the robot executes the simulated work items according to the behavior habits.

[0011] In some specific embodiments, at least sub-areas including a conference area, a terminal work area, and a non-terminal work area are divided in the work map;

[0012] The conference area is an area where the simulated object attends a meeting; the terminal work area is an area where the simulated object executes the terminal work item; and the non-terminal work area is an area where the simulated object executes the non-terminal work item.

[0013] In some specific embodiments, a living area is further divided in the work map, and the living area is an area for the simulated object to carry out life and entertainment;

[0014] When it is sensed that the simulated object has arrived at the living area, the data collection device automatically stops collecting data.

[0015] In some specific embodiments, in the work map, a movable area in which the simulated object and the robot can move is determined;

[0016] In the work map, the terminal work area, the meeting area and the living area are determined according to the location of the work terminal, the location of the meeting room, and the location of the living and entertainment venues including the toilet;

[0017] The area in the movable area other than the terminal working area, the meeting area and the living area is used as the non-terminal working area.

[0018] In some specific embodiments, when the sub-area is the conference area, the process of obtaining the non-terminal trigger condition includes:

[0019] Acquire the work schedule of the simulation object, and extract meeting items related to the meeting from the work schedule, wherein the meeting items include the meeting time and meeting location;

[0020] Determine whether the meeting location has been divided into a meeting area; if not, divide the area corresponding to the meeting location into a meeting area in the work map and mark it, and ensure that the simulated object can be sensed when it arrives at the meeting area;

[0021] The non-terminal trigger condition of the sub-area is set according to the meeting time and the meeting location, so that the simulation object reaches the sub-area before the end of the meeting to meet the non-terminal trigger condition of the sub-area.

[0022] In some specific embodiments, for the sub-area being the terminal working area, the non-terminal trigger condition is: the simulation object is located in the terminal working area, and the monitoring program detects that the working terminal has no operational response or no interactive interface change within a preset time period.

[0023] In some specific embodiments, the method further includes: filtering work items that require interaction with others from the non-terminal work items to obtain non-terminal interaction items, wherein the non-terminal interaction items include interaction personnel, interaction time, and interaction location;

[0024] A sub-area is determined according to the interaction location, and a non-terminal trigger condition of the sub-area is set according to the interaction time and the interaction person, so that the non-terminal trigger condition of the sub-area is satisfied when the simulation object senses that the interaction person arrives at the interaction location at the interaction time.

[0025] In some specific embodiments, the data collection device includes Bluetooth glasses, watches or recorders with audio and video recording functions;

[0026] And / or, the number of the data acquisition devices is one or more;

[0027] And / or, the data collection device is arranged on a sub-area or a mobile device.

[0028] In the second part, the present application proposes a user behavior acquisition and processing system for a robot, wherein the robot is used to simulate a specific person to perform work, and the system includes:

[0029] An object selection unit, used to select a specific simulation object under a certain work role, wherein the simulation object has at most some work items that can only be completed with the help of a work terminal;

[0030] An item screening unit is used to screen out the work items of the simulation object that can be executed by the robot to obtain simulation work items, and divide the simulation work items into terminal work items and non-terminal work items according to whether they are completed by relying on the work terminal;

[0031] An area division unit, used for obtaining a work map corresponding to the work environment where the simulation object is located, dividing the work map into a plurality of sub-areas according to the functional type of the area, and assigning a non-terminal trigger condition to each sub-area according to the non-terminal work item;

[0032] The data acquisition unit, when sensing that the simulated object has arrived at a certain sub-area and meets the non-terminal trigger condition of the sub-area, collects the work behavior of the simulated object when dealing with the non-terminal work item through a preset data acquisition device to obtain non-terminal data;

[0033] Acquire the working behavior of the simulation object when dealing with the terminal work item through a preset monitoring program to obtain terminal data;

[0034] A data analysis unit is used to process the terminal data and the non-terminal data, analyze the behavioral habits of the simulated object when dealing with terminal work items and non-terminal work items, and input the analyzed behavior habits into the robot, so that the robot executes the simulated work items according to the behavioral habits.

[0035] In the third part, the present application proposes a robot for implementing any of the user behavior acquisition and processing methods for a robot described in the first part above.

[0036] Beneficial effects: The present application proposes a method, system and robot for obtaining and processing user behaviors of robots, which divides work items into terminal work items and non-terminal work items, and collects and processes these two types of data differently, so as to train robots to imitate work behaviors more accurately and comprehensively, thereby providing services that are more in line with personal styles and improving user experience and satisfaction. By simulating the work behaviors of specific people, robots can perform work tasks more accurately, thereby improving work efficiency and consistency. By dividing the working environment into multiple sub-areas and setting different trigger conditions for each sub-area, robots can flexibly respond to different tasks in complex environments. Through the preset data acquisition device and monitoring program, automatic monitoring and recording of work behaviors are realized, reducing the need for manual intervention. According to different simulation objects and working environments, the work map, sub-areas and trigger conditions can be customized to improve the applicability and scalability of the system.

[0037] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 It is a flowchart of the work role simulation method of this application;

[0040] Figure 2 It is a schematic diagram of the work map of this application;

[0041] Figure 3 It is a schematic diagram of the work role simulation system module of this application.

[0042] Figure numerals: 1 - object selection unit; 2 - item screening unit; 3 - area division unit; 4 - data acquisition unit; 5 - data analysis unit. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0044] This application proposes a method for obtaining and processing user behavior for a robot, which divides work items into terminal work items and non-terminal work items, and collects and processes these two types of data differently, so as to train the robot to imitate work behavior more accurately and comprehensively, thereby providing services that are more in line with personal style and improving user experience and satisfaction. The flowchart of the method for obtaining and processing user behavior for a robot is shown in the attached figure. Figure 1 The specific plan is as follows:

[0045] A method for acquiring and processing user behavior for a robot, wherein the robot is used to simulate a specific person to perform work, the method comprising:

[0046] 101. Select a specific simulation object under a certain work role. Some of the simulation objects have work items that can only be completed with the help of a preset work terminal.

[0047] 102. Filter out the work items of the simulation object that can be executed by the robot to obtain simulation work items, and divide the simulation work items into terminal work items and non-terminal work items according to whether they rely on work terminals to be completed;

[0048] 103. Obtain a work map corresponding to the work environment where the simulation object is located, divide the work map into multiple sub-areas according to the functional type of the area, and assign a non-terminal trigger condition to each sub-area according to the non-terminal work item;

[0049] 104. When it is sensed that the simulated object has reached a certain sub-area and meets the non-terminal triggering condition of the sub-area, the working behavior of the simulated object in responding to the non-terminal work item is collected through a preset data collection device to obtain non-terminal data; the working behavior of the simulated object in responding to the terminal work item is obtained through a preset monitoring program to obtain terminal data;

[0050] 105. Process the terminal data and non-terminal data, analyze the behavior habits of the simulation object when dealing with terminal work items and non-terminal work items, and input them into the robot, so that the robot executes the simulation work items according to the behavior habits.

[0051] Among them, the robot of this application is a working robot, which is based on an artificial robot and is built in combination with various schedulable functional models. The selection of the functional model is based on the skill information and job responsibilities of the selected simulation object, such as data analysis model, text editing model, prediction model, etc. Based on advanced artificial robots, deep learning and other functional models are integrated to achieve highly accurate simulation of specific work roles. The robot adopts a multi-layer neural network structure, especially convolutional neural network (CNN), recurrent neural network (RNN), long short-term memory network (LSTM) or variants under the deep learning framework, such as Transformer model, to process complex nonlinear relationships and time series data. The robot should have the ability of self-learning and evolution, and continuously learn from new data through online learning or incremental learning mechanisms to adapt to changes in work processes and updates to personal work habits.

[0052] It should be noted that a job role is a position, and the simulation object is a specific person with specific working habits. The robot needs to imitate the simulation object, perform certain work tasks according to the working habits of the simulation object, and to a certain extent replace the simulation object to perform certain work tasks in order to reduce its workload.

[0053] This application divides work into terminal work items and non-terminal work items, and handles complex non-terminal work items in a targeted manner. Resource allocation can be optimized by clearly distinguishing which tasks require specific equipment support (terminal work items) and which can be performed directly by robots (non-terminal work items). For example, robots can focus on tasks that do not require special tools, freeing up human employees to handle more complex or higher-value work. For non-terminal work items, since such work usually involves more human interaction or more flexible operating methods, treating such tasks separately will help develop robot solutions that are more adaptable to changing environments, thereby better simulating human behavior patterns and even being able to respond reasonably when faced with unforeseen situations.

[0054] Step 101 is the starting point of the entire robot user behavior acquisition and processing method. Its main task is to select a specific work role and determine the simulation object under this role. The significance of this step is to clarify the object of research and simulation, and to ensure that subsequent data collection, analysis, and robot training are based on accurate and relevant goals. Among them, a work role refers to a collection of duties or tasks performed in a specific industry. For example, in the hotel industry, it can be a front desk receptionist; in the manufacturing industry, it can be an assembly line worker. The simulation object refers to the real person who actually performs these work tasks. Each simulation object has different working habits. The robot can analyze the working habits of the simulation object from the data and customize it to replace the simulation object to complete part of the work.

[0055] In this application, there are some work items in the simulation object that can only be completed with the help of preset work terminals. That is to say, the selected simulation roles include not only tasks that can be completed directly through physical actions, but also tasks that require the use of some form of technical equipment (such as computer systems, special tools, etc.) to complete, so as to comprehensively cover all aspects of the work.

[0056] Before selecting job roles and simulation objects, you need to conduct a comprehensive needs analysis of the target industry or department to understand which job roles are most in need of automation support. Select employees who meet the requirements as potential simulation objects. Ideally, this person should have rich experience and be able to represent the best practices of the role. You can consider multiple people as alternatives to compare different styles and efficiency.

[0057] In this application, a work terminal refers to various technical devices or systems that are relied upon when performing tasks in a specific work environment. These terminals can be hardware devices, software applications, or a combination of the two. Depending on the industry and job role, the specific form of the work terminal will vary. For example, the work terminal can be: an ordinary desktop or laptop computer, special software applications such as accounting and financial management software and human resource management systems, special-purpose handheld devices such as inventory management scanners, medical diagnostic equipment, etc., measuring tools and test equipment used by engineers, and various machines on automated production lines. Each work terminal has its own specific functions and operating methods, so when obtaining behavioral data, it is necessary to adopt corresponding data collection methods for different types of terminals. For example, for software applications on computers, screen recording and keyboard and mouse motion capture may be required; while for industrial control systems, it may be necessary to capture instruction streams through network protocols. Understanding the characteristics of these terminals helps to more accurately define the working environment of the simulated object and provide accurate information for subsequent data analysis and robot behavior modeling.

[0058] The purpose of step 102 is to select work items that can be performed by robots from all the work of the selected simulation object, and further divide them into terminal work items and non-terminal work items according to the characteristics of these items. Perform a comprehensive task analysis on the selected simulation object and record all the tasks of their daily work. Evaluate each task to determine whether it can be automated by a robot. This includes considering factors such as technical feasibility, cost-effectiveness, and safety. Some tasks may be too complex or involve a high degree of human intuition and judgment and are not suitable for automation. Select those items that can be performed by robots from all tasks. These items should have clear operating steps and do not require human-specific perception or decision-making processes. For example, tasks such as data entry, file sorting, and simple assembly are usually easier to automate. Design corresponding data collection methods for different types of work items. For terminal work items, it may be necessary to install screen recording software, keyboard and mouse activity monitors, etc. For non-terminal work items, it may be necessary to set up cameras, microphones, and other sensors to capture motion and environmental information.

[0059] In this application, terminal work items and non-terminal work items are classified according to whether the task requires specific technical equipment or systems to complete. This classification helps to capture and analyze the behavior of simulated objects more accurately and train robots accordingly. Terminal work items refer to tasks that must be completed with the help of preset work terminals (such as computers, software applications, special equipment, etc.), usually involving complex interactions, data processing or operations of specific functions. Exemplary: Customer service representative: Use the customer relationship management (CRM) system to record customer information, query historical orders, and update the status of service requests. Doctor: Use the electronic health record (EHR) system to enter patient medical records, view test results, and issue electronic prescriptions. Accountant: Use financial software to record accounts, generate reports, and handle tax affairs. Factory operator: Operate the programmable logic controller (PLC) to adjust production line parameters and monitor production data in the SCADA system. Logistics manager: Use the inventory management system (WMS) to update inventory records, print shipping labels, and arrange transportation plans. Non-terminal work items refer to tasks that can be completed directly without relying on specific technical equipment, usually involving physical actions, interpersonal interactions, or simple manual operations. Exemplary: Accountant: manually fill out simple forms, organize paper documents, and attend department meetings. Factory Operator: manually assemble products, conduct quality checks, and clean up work areas. Logistics Administrator: on-site supervision of cargo loading, communication with drivers, and on-site inspection of warehouse conditions.

[0060] For terminal work items, detailed interaction data, such as keyboard input, mouse clicks, screen content, etc., can be obtained through the built-in monitoring program. After identifying which tasks belong to terminal work items, the corresponding software interfaces or hardware adapters can be developed in a targeted manner so that the robot can smoothly perform these tasks. For non-terminal work items, external data acquisition devices such as cameras, microphones, wearable sensors, etc. are required to record physical actions and interpersonal communication. For non-terminal work items, more flexible mechanical structures and sensor layouts can be designed to adapt to different human-computer interaction scenarios. The two types of work items reflect different behavioral patterns. Terminal work items are more about the proficient use of technical tools, while non-terminal work items focus on practical operation capabilities and interpersonal skills. Dividing work tasks into terminal work items and non-terminal work items helps to accurately obtain and analyze behavioral data, and then fully understand the overall work performance of the simulated object, providing a multi-dimensional reference for robot design.

[0061] Step 103 involves obtaining a work map of the simulated object's work environment and dividing the work environment into regions based on non-terminal work items. This step is critical to ensure that the robot can accurately mimic the behavior of human workers in different regions. Obtain a detailed work environment map to understand the workspace layout of the simulated object. Divide different functional sub-regions on the map based on the requirements of non-terminal work items. Set non-terminal trigger conditions for each sub-region to guide the subsequent data collection process. A schematic diagram of the work map is shown in Figure 2 shown.

[0062] Regarding work maps, a detailed work environment map can be created through on-site measurements, using building plans, or with the help of professional surveying and mapping tools. Computer-aided design (CAD) software or other 3D modeling tools can also be used to create digital work maps, combining on-site measurement data with existing drawings to generate more intuitive and detailed models. The map should include all important physical structures and facilities, such as desks, machinery and equipment, passages, doors, etc. In addition, the map can also include three-dimensional information, such as floor heights, internal layout of rooms, etc., to provide a more comprehensive perception of space. Work maps can be in the form of two-dimensional floor plans, three-dimensional models, vector graphics, raster images, etc.

[0063] According to the workflow and task requirements of the simulated object, the work map is divided into multiple sub-areas with specific functions. For example, in an office environment, it can be divided into reception area, conference room, personal workstation, rest area, etc.; in a factory environment, it can be divided into production line, quality control area, storage area, etc. Each sub-area should have its main purpose clearly defined, and these uses are associated with non-terminal work items. For each sub-area, based on the characteristics of non-terminal work items, define the corresponding trigger conditions. The trigger condition refers to the standard for starting to record the behavior data of the simulated object when it enters the area and meets certain preset conditions. For example, in the reception area, the trigger condition may be "the simulated object stands at the front desk"; in the conference room, the trigger condition may be "the simulated object sits at the conference table and starts speaking."

[0064] In some embodiments, appropriate data collection devices, such as cameras, microphones, sensors, etc., are installed in each sub-area to ensure that the positions and angles of these devices can cover the entire sub-area and clearly capture the movements and behaviors of the simulated object. They can also be worn on the simulated object. When configuring the device, privacy protection should be considered to avoid infringing on the privacy of others.

[0065] The sub-areas are divided into more detailed and functional areas to ensure the effectiveness and pertinence of data collection. In some specific embodiments, at least sub-areas including a meeting area, a terminal work area, and a non-terminal work area are divided in the work map. Among them, the meeting area is the area where the simulated object attends the meeting, and the behavior of the simulated object in the meeting, such as speaking, discussing, etc., is recorded by a data acquisition device. The video screen can be captured by a camera, the audio can be recorded by a microphone, and the presence and actions of people can be detected by sensors. The terminal work area is the area involved in the execution of terminal work items by the simulated object, and the behavior of the simulated object interacting with technical tools such as computers and special equipment can be recorded by a monitoring program. Exemplarily, the user's operations on the computer screen are recorded by screen recording software, the user's input behavior is recorded by a keyboard and mouse activity monitor, and network activity and data transmission are monitored by a network traffic analysis tool.

[0066] The non-terminal work area is the area where the simulated object performs non-terminal work items, and the physical actions or simple interpersonal interactions of the simulated object can be recorded by a data acquisition device. For example, the video screen is captured by a camera, and the movements and position changes of the personnel are detected by sensors such as infrared sensors and motion sensors; and the body movements and physiological data are recorded by wearable devices such as smart bracelets.

[0067] In some specific embodiments, a living area is also divided in the work map, and the living area is the area where the simulated object conducts life and entertainment; when it is sensed that the simulated object has arrived in the living area, the data collection device automatically stops collecting data. The living area is separated from other work areas to ensure that the employee will not be monitored during life and entertainment, thereby protecting the personal privacy of the employee. When it is sensed that the simulated object has entered the living area, the data collection device automatically stops collecting data, thereby avoiding unnecessary data leakage and protecting the privacy of the employee.

[0068] Divide the meeting area, terminal work area, non-terminal work area and living area, and configure corresponding data collection equipment according to the characteristics of different areas to avoid waste of resources. Meeting area: Focus on recording key information such as discussions and decision-making processes in meetings, which helps to understand team collaboration and communication patterns. Terminal work area: Centrally record operational behaviors related to technical equipment, such as computer use, software applications, etc., which can capture the technical skills and workflow of the simulated object in detail. Non-terminal work area: Record physical movements and simple interpersonal interactions, which helps to understand the actual operational capabilities and interpersonal skills of the simulated object. Living area: Protect personal privacy by stopping data collection and ensure that only work-related behavioral data is collected. Through clear regional division, it is easier to identify which tasks are suitable for automation, thereby improving overall work efficiency. Data from different areas can be processed and analyzed separately, making data analysis more efficient and targeted. High-quality data helps to more accurately analyze the behavioral patterns of simulated objects and provide a reliable basis for robot training. Clearly explaining to employees which areas will be monitored and which will not increase the transparency of work and reduce employees' doubts and resistance. Considering the living needs of employees and providing them with an environment that is both efficient and comfortable will help improve employee job satisfaction and loyalty. In actual applications, different area divisions can adapt to a variety of work scenarios and industry needs. Whether it is an office, factory or service place, it can be adjusted according to actual conditions.

[0069] In some specific embodiments, in the work map, a movable area for the simulated object and the robot to move is determined; in the work map, the terminal work area, the meeting area, and the living area are determined according to the location of the work terminal, the location of the conference room, and the location of the living and entertainment venues including the toilet; the area other than the terminal work area, the meeting area, and the living area in the movable area is used as a non-terminal work area. Through clear regional division, data collection equipment is deployed in a targeted manner to avoid resource waste, improve efficiency, and improve data quality and availability.

[0070] The division of the work map includes not only the meeting area, terminal work area and living area, but also a movable area. This movable area refers to the area where the simulated objects and robots can move freely. In this way, the work environment can be defined more comprehensively and the accuracy and effectiveness of data collection and behavior analysis can be ensured. The movable area is the area where the simulated objects and robots can move freely, usually including corridors, passages, open spaces, etc. Mark all movable paths and areas on the work map to ensure that these areas connect the various sub-areas. Determine the terminal work area according to the location of computers and other terminal devices in the actual work environment. Mark the specific location of each terminal device on the work map and define a reasonable operating range around these devices. Start data collection when the simulated object logs in to the terminal device or starts the relevant software. Determine the meeting area according to the location of the meeting room in the actual work environment. Clearly mark the four boundaries of the meeting room on the work map, including the entrance, seating area, podium, etc. Start data collection when the simulated object enters the meeting room and sits down. Determine the living area according to the location of the living and entertainment places including the toilet in the actual work environment. Mark the boundaries of these areas on the work map to ensure that all lounges, toilets, restaurants, etc. are covered. When the simulated object is sensed to enter the living area, the data collection device automatically stops collecting data. The areas in the movable area other than the terminal work area, meeting area and living area are regarded as non-terminal work areas. Clearly mark the boundaries of these areas on the work map to ensure that all work areas that do not rely on specific technical equipment are covered. Start data collection when the simulated object is sensed to enter the area and start to perform tasks, such as picking up a folder, talking to a colleague, etc.

[0071] In some specific embodiments, for a sub-area as a meeting area, the process of obtaining its non-terminal trigger conditions includes: obtaining the work itinerary of the simulated object, extracting meeting items related to the meeting from the work itinerary, and the meeting items include the meeting time and meeting place; judging whether the meeting place has been divided into a meeting area; if not, dividing the area corresponding to the meeting place into a meeting area in the work map and marking it, while ensuring that the simulated object can be sensed when it arrives at the meeting area; setting the non-terminal trigger conditions of the sub-area according to the meeting time and meeting place, so that the simulated object reaches the sub-area before the end of the meeting to meet the non-terminal trigger conditions of the sub-area. The meeting place is divided into meeting areas, and reasonable non-terminal trigger conditions are set to ensure the accuracy and efficiency of data collection. This detailed division and configuration helps to fully understand the behavior patterns of the simulated objects in the meeting, and provides a reliable foundation for subsequent data analysis and robot training.

[0072] Specifically, obtain the work schedule by accessing the calendar system of the simulation object (such as Outlook, Google Calendar, etc.). If the simulation object uses a paper schedule or other method to record the schedule, it can be collected through interviews or manual input. For example, use natural language processing (NLP) technology or calendar API to parse the meeting letter in the schedule, or manually extract information such as meeting time, location, and participants from the schedule. Find the corresponding physical location on the work map. Use GIS software or manual drawing methods to mark the boundaries of the meeting area on the map. Add labels or annotations to indicate that the area is a meeting area, and record the specific time and location of the meeting.

[0073] For example, according to the time and location of the meeting, the following trigger conditions are set:

[0074] Entry time: When the simulated object enters the meeting area within a certain period of time before the meeting starts (for example, 10 minutes in advance), data collection is triggered.

[0075] Stay time: If the simulated subject continues to stay in the meeting area during the meeting, continue data collection.

[0076] Departure time: Stop data collection when the simulated subject leaves the meeting area after the meeting.

[0077] Ensure that data collection devices (such as cameras, microphones, etc.) are activated during the meeting and automatically shut down or enter standby mode after the meeting.

[0078] In some specific embodiments, for the sub-area being a terminal work area, its non-terminal trigger condition is: the simulated object is located in the terminal work area, and the monitoring program detects that the work terminal has no operation response or no interactive interface change within a preset period of time. Setting non-terminal trigger conditions in the terminal work area ensures the efficiency and accuracy of data collection, helps to fully understand the behavior pattern of the simulated object in the terminal work area, and provides a solid foundation for subsequent data analysis and robot training. Detect whether the simulated object enters the terminal work area through sensors (such as infrared sensors, RFID readers, etc.). No operation response within a preset period of time: Detect whether the terminal device has keyboard input, mouse clicks or other forms of operation response within a preset period of time through a monitoring program. No interactive interface change: Detect whether the screen content of the terminal device has changed within a preset period of time through screen recording software or interface capture tools. Install monitoring programs such as screen recording software, keyboard and mouse activity monitors on the terminal device. Set a preset time period (for example, 5 minutes). If no keyboard or mouse activity is detected during this period of time, it is considered that there is no operation response; if the screen content does not change during this period of time, it is considered that there is no interactive interface change.

[0079] In some specific embodiments, the user behavior acquisition and processing method also includes: filtering out work items that require interaction with others from non-terminal work items to obtain non-terminal interaction items, and non-terminal interaction items include interaction personnel, interaction time, and interaction location; determining a sub-area according to the interaction location, and setting a non-terminal trigger condition for the sub-area according to the interaction time and interaction personnel, so that the simulation object satisfies the non-terminal trigger condition of the sub-area when it senses that the interaction personnel arrive at the interaction location at the interaction time. This application can not only handle tasks that are completed independently, but also handle work items that require interaction with others, so that the robot can also perform well in collaborative scenarios.

[0080] Exemplarily, a comprehensive task analysis is conducted on the daily work of the simulation object, and all tasks involving interpersonal interaction are recorded to obtain non-terminal interaction items. Regarding the interaction personnel: clarify the specific personnel involved in the interaction, such as colleagues, customers, suppliers, etc. Regarding the interaction time: record the planned interaction time period, such as 10 am to 11 am every day. Regarding the interaction location: determine the specific interaction location, such as the reception area, conference room, desk, etc. The trigger conditions include: the current time is within the preset interaction time period, and the designated interaction personnel arrive at the interaction location when it is sensed. Data collection is triggered only when the above two conditions are met at the same time. The system continuously monitors the current time to determine whether it is within the preset interaction time period. Detect whether the designated interaction personnel arrive at the interaction location through RFID readers, Bluetooth beacons or face recognition technology. For example, give each employee a work badge with an RFID tag, or use Bluetooth beacons to locate mobile phones or other mobile devices. Once the trigger conditions are met, start the camera, microphone and other data acquisition devices for recording.

[0081] In some specific embodiments, when a certain area has multiple functional types at the same time, the area is defined as a composite functional area, and the most frequently used functional type is used as the main functional type; the composite functional area is divided into sub-areas according to the main functional type; and the non-terminal trigger conditions of the sub-areas corresponding to each functional type are set respectively for each functional type of the composite functional area with reference to the non-terminal trigger conditions of the sub-areas corresponding to each functional type. Identify those areas that have multiple functional types at the same time, effectively manage the composite functional areas, and set corresponding non-terminal trigger conditions according to different functional types. For example, a conference room may be used as a training room in certain time periods and as a team discussion area in other time periods. According to the actual usage, the frequency of use of each functional type is counted, and the most frequently used functional type is selected as the main functional type. According to the main functional type, the composite functional area is divided into corresponding sub-areas. For example, if the main purpose of the conference room is meeting, it is divided into a meeting area. These sub-areas are clearly marked on the work map, and their main functional types are indicated. Referring to the non-terminal trigger conditions of the sub-areas corresponding to each functional type, non-terminal trigger conditions are set respectively for each functional type of the composite functional area. Assume that there is a conference room (composite functional area), which is sometimes used for meetings and sometimes for training (non-terminal work area). Through statistics, it is found that the frequency of use of conferences is the highest, so the main function type of the conference room is defined as the conference area. Two trigger conditions are configured for the conference room, namely the non-terminal trigger condition of the conference area and the non-terminal trigger condition of the non-terminal work area.

[0082] After obtaining the terminal data and non-terminal data, the data needs to be processed and analyzed. For example: First, the collected terminal data and non-terminal data need to be cleaned. This includes removing irrelevant information, correcting erroneous data, processing missing values, etc. to ensure the quality of the data. Since terminal data and non-terminal data may come from different sources (for example, sensors, video surveillance, log files, etc.), these different forms of data need to be integrated into a unified data set for subsequent analysis. Use machine learning algorithms or other data analysis techniques to identify the specific behavior patterns of the simulated object when performing different types of work items. This may involve a variety of technical means such as time series analysis, action recognition, and natural language processing, with the goal of understanding how the simulated object completes the task. Based on the above-mentioned behavior recognition, a mathematical model or a set of rules is constructed to describe the behavior habits of the simulated object. For example, if it is found that the simulated object always processes certain documents in a specific order, this rule can be added to the model as a guiding principle. The obtained behavior habit model is converted into specific control logic or instructions and loaded onto the robot. This may involve operations such as writing new software code, configuring parameter settings, or updating existing algorithms. The implemented robot should undergo a series of tests to verify whether its performance meets expectations. Further adjust and improve the model based on test feedback until it reaches a satisfactory level.

[0083] Apply robots to specific simulation objects under specific work roles to achieve simulation and enhancement of specific roles. By imitating the habits and preferences of employees, robots can replace specific simulation objects to perform related work items, provide more personalized services or products, and enhance user experience. It can not only reduce manual errors, improve work accuracy, accelerate decision-making processes, and significantly improve efficiency, but also reduce long-term labor costs. Reducing dependence on manpower through automation can help avoid costly mistakes. In addition, it can promote the innovation and competitiveness of enterprises while creating a more positive and productive working environment for employees.

[0084] Considering that the actual application environment may be different from the training scenario, it is also necessary to consider giving the robot a certain degree of flexibility and adaptability. This means not only copying known behavioral habits, but also being able to make appropriate adjustments according to environmental changes. In some embodiments, after the robot starts to execute the work project, its execution needs to be monitored to ensure that it can accurately imitate the habits of the simulated object and optimize according to the actual situation. Collect data on the robot during the execution process, including execution time, error rate, resource consumption, etc. Based on the monitoring data, analyze the execution efficiency and accuracy of the robot, identify any deviations or deficiencies, and make necessary adjustments and optimizations to the habit logic chain. In some embodiments, it also includes: collecting feedback from actual users or stakeholders to understand whether the robot's performance meets expectations and whether there is room for improvement. Then, based on the feedback, iteratively improve the robot and continuously optimize the habit logic chain to make it more in line with the habits and workflow of the simulated object.

[0085] In some specific embodiments, the data acquisition device includes Bluetooth glasses, watches or recorders with audio and video recording functions; and / or, the number of data acquisition devices is one or more; and / or, the data acquisition device is set on a sub-area or mobile device. According to actual needs, one or more data acquisition devices can be configured. If the work task covers a wide range or involves multiple different sub-areas, more equipment may be required to ensure comprehensive coverage. The data acquisition device can be fixedly installed in each sub-area or designed to be mobile and move with the simulated object. For example, in some cases, the camera is installed in the corner of the room; in other cases, it may be more appropriate for the simulated object to wear a movable device (such as Bluetooth glasses) so as to follow its activity trajectory and record it at any time.

[0086] This application proposes a user behavior acquisition and processing system for a robot, which systematizes the above-mentioned user behavior acquisition and processing method for a robot to make it more practical. A module schematic diagram of a user behavior acquisition and processing system for a robot is shown in the attached figure. Figure 3 The specific plan is as follows:

[0087] A user behavior acquisition and processing system for a robot, wherein the robot is used to simulate a specific person to perform work, the system comprising:

[0088] The object selection unit 1 is used to select a specific simulation object under a certain work role, and the simulation object has at most some work items that can only be completed with the help of a work terminal;

[0089] The project screening unit 2 is used to screen out the work items of the simulation object that can be executed by the robot to obtain simulation work items, and divide the simulation work items into terminal work items and non-terminal work items according to whether they rely on the work terminal to be completed;

[0090] The area division unit 3 is used to obtain a work map corresponding to the work environment where the simulation object is located, divide the work map into multiple sub-areas according to the functional type of the area, and assign a non-terminal trigger condition to each sub-area according to the non-terminal work item;

[0091] The data acquisition unit 4, when sensing that the simulated object has reached a certain sub-area and meets the non-terminal trigger condition of the sub-area, collects the work behavior of the simulated object when dealing with the non-terminal work item through a preset data acquisition device to obtain non-terminal data;

[0092] The working behavior of the simulation object in dealing with the terminal work item is obtained through a preset monitoring program to obtain the terminal data;

[0093] The data analysis unit 5 is used to process the terminal data and the non-terminal data, analyze the behavior habits of the simulation object when dealing with the terminal work items and the non-terminal work items, and input them into the robot, so that the robot executes the simulation work items according to the behavior habits.

[0094] The present application proposes a robot for implementing any of the above-mentioned methods for obtaining and processing user behavior for a robot.

[0095] The present application provides a computer program product, which includes computer instructions, which are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes a method for obtaining and processing user behavior for a robot. A method for obtaining and processing user behavior for a robot is applied to a computer program product for easy execution.

[0096] The present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a method for acquiring and processing user behavior for a robot as described above.

[0097] The computer storage medium of the present application may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device. The present application applies a method for obtaining and processing user behavior for a robot to a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the clothing simulation method provided by the present application are implemented, which is simple, fast, easy to store, and not easy to lose.

[0098] The present application proposes a method, system and robot for obtaining and processing user behaviors of robots, which divides work items into terminal work items and non-terminal work items, and collects and processes these two types of data differently, so as to train robots to imitate work behaviors more accurately and comprehensively, thereby providing services that are more in line with personal styles and improving user experience and satisfaction. By simulating the work behaviors of specific people, robots can perform work tasks more accurately, thereby improving work efficiency and consistency. By dividing the working environment into multiple sub-areas and setting different trigger conditions for each sub-area, robots can flexibly respond to different tasks in complex environments. Through the preset data acquisition device and monitoring program, automatic monitoring and recording of work behaviors are achieved, reducing the need for manual intervention. According to different simulation objects and working environments, work maps, sub-areas and trigger conditions can be customized to improve the applicability and scalability of the system.

[0099] Those skilled in the art should understand that the modules of the present application described above can be implemented by a general-purpose computing system, they can be concentrated on a single computing system, or distributed on a network composed of multiple computing systems, and optionally, they can be implemented by program codes executable by a computer system, so that they can be stored in a storage system and executed by the computing system, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present application is not limited to any specific combination of hardware and software.

[0100] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the appended claims.

[0101] The above disclosure only discloses several specific implementation scenarios of the present application. However, the present application is not limited thereto, and any changes that can be conceived by technicians in this field should fall within the scope of protection of the present application.

Claims

1. A method for acquiring and processing user behavior for a robot, characterized in that: The robot is used to simulate a specific person to perform work, and the method includes: A specific simulation object under a certain work role is selected, wherein the simulation object has some work items that can only be completed with the help of a preset work terminal; Filter out the work items of the simulation object that can be executed by the robot to obtain simulation work items, and divide the simulation work items into terminal work items and non-terminal work items according to whether they rely on the work terminal to be completed; Obtaining a work map corresponding to the work environment in which the simulation object is located, dividing the work map into a plurality of sub-areas according to the functional type of the area, and assigning a non-terminal trigger condition to each sub-area according to the non-terminal work item; When it is sensed that the simulated object has reached a certain sub-area and meets the non-terminal trigger condition of the sub-area, the working behavior of the simulated object in dealing with the non-terminal work item is collected by a preset data collection device to obtain non-terminal data; the working behavior of the simulated object in dealing with the terminal work item is obtained by a preset monitoring program to obtain terminal data; Processing the terminal data and the non-terminal data, analyzing the behavior habits of the simulated object when dealing with terminal work items and non-terminal work items, and inputting the behavior habits into the robot, so that the robot executes the simulated work items according to the behavior habits; At least a sub-area including a meeting area is divided in the work map; wherein the meeting area is the area where the simulated object attends the meeting; for the sub-area being the meeting area, the process of obtaining the non-terminal trigger condition includes: obtaining the work itinerary of the simulated object, extracting meeting items related to the meeting from the work itinerary, the meeting items including the meeting time and the meeting place; determining whether the meeting place has been divided into a meeting area; if not, dividing the area corresponding to the meeting place into a meeting area and marking it in the work map, while ensuring that the simulated object can be sensed when arriving at the meeting area; setting the non-terminal trigger condition of the sub-area according to the meeting time and the meeting place, so that the simulated object reaches the sub-area before the end of the meeting, thus satisfying the non-terminal trigger condition of the sub-area.

2. The method for acquiring and processing user behavior according to claim 1, characterized in that: At least sub-areas including the meeting area, the terminal work area and the non-terminal work area are divided in the work map; The terminal work area is an area involved in the execution of the terminal work item by the simulation object; and the non-terminal work area is an area involved in the execution of the non-terminal work item by the simulation object.

3. The method for acquiring and processing user behavior according to claim 2, characterized in that: The working map is also divided into a living area, which is an area for the simulated object to carry out life and entertainment; When it is sensed that the simulated object has arrived at the living area, the data collection device automatically stops collecting data.

4. The method for acquiring and processing user behavior according to claim 3, characterized in that: In the working map, determining a movable area in which the simulation object and the robot can move; In the work map, the terminal work area, the meeting area and the living area are determined according to the location of the work terminal, the location of the meeting room, and the location of the living and entertainment venues including the toilet; The area in the movable area other than the terminal working area, the meeting area and the living area is used as the non-terminal working area.

5. The method for acquiring and processing user behavior according to claim 2, characterized in that: For the sub-area being the terminal working area, the non-terminal triggering condition is: the simulation object is located in the terminal working area, and the monitoring program detects that the working terminal has no operation response or no interactive interface change within a preset period of time.

6. The method for acquiring and processing user behavior according to claim 1, characterized in that: Also includes: Filtering work items that require interaction with others from the non-terminal work items to obtain non-terminal interaction items, wherein the non-terminal interaction items include interaction personnel, interaction time, and interaction location; A sub-area is determined according to the interaction location, and a non-terminal trigger condition of the sub-area is set according to the interaction time and the interaction person, so that the non-terminal trigger condition of the sub-area is satisfied when the simulation object senses that the interaction person arrives at the interaction location at the interaction time.

7. The method for acquiring and processing user behavior according to claim 1, characterized in that: The data collection device includes Bluetooth glasses, watches or recorders with audio and video recording functions; And / or, the number of the data acquisition devices is one or more; And / or, the data collection device is arranged on a sub-area or a mobile device.

8. A user behavior acquisition and processing system for a robot, characterized in that: The robot is used to simulate a specific person to perform work, and the system includes: An object selection unit, used to select a specific simulation object under a certain work role, wherein the simulation object has at most some work items that can only be completed with the help of a work terminal; An item screening unit is used to screen out the work items of the simulation object that can be executed by the robot to obtain simulation work items, and divide the simulation work items into terminal work items and non-terminal work items according to whether they are completed by relying on the work terminal; An area division unit, used for obtaining a work map corresponding to the work environment where the simulation object is located, dividing the work map into a plurality of sub-areas according to the functional type of the area, and assigning a non-terminal trigger condition to each sub-area according to the non-terminal work item; The data acquisition unit, when sensing that the simulated object has arrived at a certain sub-area and meets the non-terminal trigger condition of the sub-area, collects the work behavior of the simulated object when dealing with the non-terminal work item through a preset data acquisition device to obtain non-terminal data; Acquire the working behavior of the simulation object when dealing with the terminal work item through a preset monitoring program to obtain terminal data; a data analysis unit, configured to perform data processing on the terminal data and the non-terminal data, analyze the behavior habits of the simulated object when dealing with terminal work items and non-terminal work items, and input the behavior habits into the robot, so that the robot executes the simulated work items according to the behavior habits; At least a sub-area including a meeting area is divided in the work map; wherein the meeting area is the area where the simulated object attends the meeting; for the sub-area being the meeting area, the process of obtaining the non-terminal trigger condition includes: obtaining the work itinerary of the simulated object, extracting meeting items related to the meeting from the work itinerary, the meeting items including the meeting time and the meeting place; determining whether the meeting place has been divided into a meeting area; if not, dividing the area corresponding to the meeting place into a meeting area and marking it in the work map, while ensuring that the simulated object can be sensed when arriving at the meeting area; setting the non-terminal trigger condition of the sub-area according to the meeting time and the meeting place, so that the simulated object reaches the sub-area before the end of the meeting, thus satisfying the non-terminal trigger condition of the sub-area.

9. A robot, characterized in that: Used to implement a user behavior acquisition and processing method for a robot as described in any one of claims 1-7.

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