WO2017114130A1

WO2017114130A1 - Method and device for obtaining state of robot

Info

Publication number: WO2017114130A1
Application number: PCT/CN2016/109111
Authority: WO
Inventors: 刘若鹏; 武晨
Original assignee: 深圳光启合众科技有限公司
Priority date: 2015-12-31
Filing date: 2016-12-09
Publication date: 2017-07-06
Also published as: CN106926236A; CN106926236B

Abstract

A method and device for obtaining a state of a robot, the method comprising: according to state output data of a robot at a previous moment and a state result at the previous moment, determining a state result of the robot at a current moment, the state result at the previous moment being determined via an initial state result of the robot at an initial moment and state output data at a plurality of moments before the previous moment (S102); obtaining state data received at the current moment (S104); according to the state data of the robot at the current moment, the state output data at the previous moment and the state result at the current moment, determining state output data of the robot at the current moment (S106). The method and corresponding device solve the technical problem in the prior art that when calculations are performed on a feeling system of a robot, the calculations only relate to a currently inputted feeling and the effect of a feeling at a previous moment on the current feeling, which causes operational results of the feeling system of the robot to be inaccurate. The method and corresponding device thereby enable calculated robot feeling systems to be more anthropomorphic.

Description

Method and apparatus for acquiring the state of a robot

Technical field

The present invention relates to the field of robots, and in particular to a method and apparatus for acquiring the state of a robot.

Background technique

With the development of related technologies of robots, research on the emotional changes of robots has become more and more in-depth. In the prior art, the corresponding emotions can be output according to the external stimulus received by the robot, or when the emotion of the current moment of the robot is output. Consider the emotional emotions of the robot at the last moment and the emotional feelings of the current moment, making the robot's feelings more anthropomorphic.

However, human emotions are not only related to the emotions of the previous moment and the current moment. Human emotions are formed by the long-term evolution of human beings to form individuality and the stimulation of external emotions received for a long time, so the emotions in the robot When the system is designed, only the emotions input by the outside world and the emotions of the previous moment are considered to affect the emotions of the current moment, which will make the emotional system of the robots inaccurate, and the emotional system cannot be anthropomorphized.

The calculation of the emotional system of the robot in the prior art only involves the emotion of the current input and the influence of the emotion of the previous moment on the current emotion, resulting in an inaccurate operation result of the emotional system of the robot, and no effective solution has been proposed yet. Program.

Summary of the invention

Embodiments of the present invention provide a method and apparatus for acquiring a state of a robot, so as to at least solve the prior art calculation of the emotion system of the robot, which only involves the emotion of the current input and the influence of the emotion of the previous moment on the current emotion. A technical problem that leads to inaccurate results of the robot's emotional system.

According to an aspect of an embodiment of the present invention, a method for acquiring a state of a robot includes: determining a state result of the robot at a current time according to a state output data of the robot at a previous moment and a state result at a previous moment, wherein The state result of the last moment is determined by the initial state result of the robot at the initial moment and the state output data of the plurality of moments before the last moment; acquiring the state data received at the current moment; according to the state data of the robot at the current moment, The state output data at the current moment and the state result at the current moment determine the state output data of the robot at the current moment; wherein the state data represents the externally input emotion information received by the robot, and the state output data represents the robot output to the outside. The emotional information, the status result represents the personalized information formed by the robot accumulating at least one emotional information during the running process.

According to another aspect of the embodiments of the present invention, an apparatus for acquiring a state of a robot includes: a first determining module, configured to determine, according to a state output data of the robot at a previous moment and a state result of a previous moment, a state result of the robot at the current time, wherein the state result of the previous moment is determined by the initial state result of the robot at the initial moment and the state output data of the plurality of moments before the previous moment; the first obtaining module is configured to acquire the current The current state data received at a time; the second determining module is configured to determine the state output data of the robot at the current time according to the state data of the current time of the robot, the state output data at the current time, and the state result at the current time; The state data represents the sentiment information of the external input received by the robot, the state output data represents the sentiment information output by the robot to the outside, and the state result represents the personality information formed by the robot accumulating at least one sentiment information during the running process.

In the embodiment of the present invention, the state result of the robot at the current time is determined according to the state output data of the robot at the previous moment and the state result of the previous moment, and the current state data received at the current time is obtained. According to the state data of the robot at the current time, the state output data at the previous moment, and the state result at the current moment, the purpose of the robot to output the data at the current moment is determined, thereby realizing the basis of the evolution of the robot's personality. In addition, the technical effect of the accurate emotional output of the robot is obtained, thereby solving the prior art calculation of the emotional system of the robot, which only involves the emotion of the current input and the influence of the emotion of the last moment on the current emotion, resulting in the emotional system of the robot. The technical results of the inaccurate running results.

DRAWINGS

The drawings described herein are intended to provide a further understanding of the invention, and are intended to be a part of the invention. In the drawing:

1 is a flow chart of a method of acquiring a state of a robot according to an embodiment of the present invention;

2 is a flow chart of an alternative method of acquiring a state of a robot in accordance with an embodiment of the present invention;

3 is a schematic structural diagram of an apparatus for acquiring a state of a robot according to an embodiment of the present invention;

4 is a schematic structural diagram of an apparatus for acquiring a state of a robot according to an embodiment of the present invention;

FIG. 5 is a schematic structural diagram of an apparatus for acquiring a state of a robot according to an embodiment of the present invention; FIG.

6 is a schematic structural diagram of an apparatus for acquiring a state of a robot according to an embodiment of the present invention;

7 is a schematic structural diagram of an apparatus for acquiring a state of a robot according to an embodiment of the present invention;

FIG. 8 is a schematic structural diagram of an apparatus for acquiring a state of a robot according to an embodiment of the present invention.

detailed description

The technical solutions in the embodiments of the present invention are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present invention. It is an embodiment of the invention, but not all of the embodiments. Based on the embodiments in the present invention, the field All other embodiments obtained by a skilled person without creative efforts shall fall within the protection scope of the present invention.

It is to be understood that the terms "first", "second" and the like in the specification and claims of the present invention are used to distinguish similar objects, and are not necessarily used to describe a particular order or order. It is to be understood that the data so used may be interchanged where appropriate, so that the embodiments of the invention described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "comprises" and "comprises" and "the" and "the" are intended to cover a non-exclusive inclusion, for example, a process, method, system, product, or device that comprises a series of steps or units is not necessarily limited to Those steps or units may include other steps or units not explicitly listed or inherent to such processes, methods, products or devices.

Embodiment 1

In accordance with an embodiment of the present invention, an embodiment of a method of acquiring a state of a robot is provided, it being noted that the steps illustrated in the flowchart of the figures may be performed in a computer system such as a set of computer executable instructions, and Although the logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in a different order than the ones described herein.

1 is a flow chart of a method for acquiring a state of a robot according to an embodiment of the present invention. As shown in FIG. 1, the method includes the following steps:

Step S102, determining a state result of the robot at the current time according to the state output data of the robot at the previous moment and the state result of the previous moment, wherein the state result of the previous moment is the initial state result of the robot at the initial moment and The status output data is determined at a plurality of times before a moment.

Specifically, in the above step S102, the state output data of the last moment may be the emotion information that the robot has external input at the last moment; the state result accumulated before the last moment may be the personality information of the robot at the previous moment; the robot The status result of the current time may be the personality information of the robot at the current time. The time in the above embodiment may be the time when the robot inputs or outputs the emotion information.

It is worth noting that the personality information of the robot at the current moment is determined by the state output data of the robot at the previous moment and the state result of the previous moment. It can be considered that the personality information of the robot at the current moment is input by the external moment of the robot. The information and the personality information of the previous moment are determined, so the personality information of the robot may be accumulated by the robot after the stimulation of the external input emotion information at a plurality of moments, wherein the robot initially has an initial state result, the state The initial value can be regarded as the "character" of the robot in the initial state. When the external emotion information is input externally, the emotion information is superimposed on the initial value of the initial state result of the robot, forming a robotic emotional system more in line with the human character.

As an optional embodiment, in the example where the initial state of the robot is "sadness", when the emotion information of "happy" is input to the robot a plurality of times, the initial state of the above "sadness" and the plurality of "happy" mentioned above. Emotional letter The information constitutes the new personality information of the robot at the current moment. Since the robot inputs the "happy" emotional information multiple times, the personality information of the robot is more inclined to the cheerful state than the initial state.

In another alternative embodiment, in the example where the initial state of the robot is "sadness", after inputting a plurality of "sad" emotional information to the robot, the initial state of the "sadness" and the plurality of the above The "sad" emotional information constitutes the new personality information of the robot at the current moment. Since the robot has input "anger" emotional information many times, the robot's personality information is more introverted or pessimistic than the initial state. status.

Step S104: Acquire status data received at the current time.

Specifically, in the above step S104, the current state data may be emotion information that is externally input to the robot at the current time.

In step S106, based on the state data of the robot at the current time, the state output data at the previous time, and the state result at the current time, the state output data of the robot at the current time is determined.

Specifically, in the above step S106, the state output data of the robot at the current time may be emotion information that the robot outputs to the outside at the current time.

In an optional embodiment, the state data represents the sentiment information of the external input received by the robot, the state output data represents the sentiment information output by the robot to the outside, and the state result indicates that the robot accumulates at least one sentiment information during the operation to form Personality information.

In another optional embodiment, as shown in FIG. 2, the personality information of the robot and the emotional output information of the robot at the previous moment can be input to the state result calculation formula to obtain new personality information of the robot, and then the robot is The new personality information and the robot input the state calculation formula with the time output information to obtain the new emotion output information of the robot.

As can be seen from the above, the above embodiment of the present application determines the state result of the robot at the current time according to the state output data of the robot at the previous moment and the state result of the previous moment, and acquires the current state data received at the current moment, according to the robot. The state data of the current time, the state output data at the current time, and the state result at the current time determine the state output data of the robot at the current time. In the above solution, when determining the state output data of the robot at the current time, the state data of the current time of the robot, the state output data of the previous time, and the state result of the current time are used, wherein the state result is the initial state of the robot at the initial time. The result and the state data at a plurality of times before the last moment are determined. By adopting the above scheme, the output state data of the robot is more anthropomorphic and more accurate, thereby solving the prior art emotional system for the robot. The calculation involves only the emotions of the current input and the influence of the emotions of the previous moment on the current emotions, resulting in inaccurate technical problems in the operation results of the robot's emotional system.

Optionally, in the foregoing step S102, the data is output according to the state of the robot at the last moment and the previous moment. The status result, the steps of determining the state result of the robot at the current time include:

In step S1021, the state output data of the robot at the last moment and the state result of the previous moment are acquired.

Specifically, in the above step S1021, the state output data of the robot at the last moment may be the emotion information input by the robot from the outside at the last moment, and the emotional result of the last moment may be the emotion of the robot at multiple moments before the last moment. After the input, the evolution of the emotional information is obtained from the robot's personality information at the previous moment.

Step S1023: The state output data of the previous moment and the state result of the previous moment are input to a preset state result model, and the state result of the current moment is determined, wherein the state result model includes the current state determined by the state result of the previous moment. The weight function of the moment.

Specifically, in the above step S1023, the preset state result model may be a function related to the time information. As an alternative embodiment, in the example where the state result of the current time is c(t)=f(w(t), c(t-1), e _o (t-1)), f(w (t), c(t-1), e _o (t-1))=c(t-1)*e _o (t-1)*w(t), in the above functional formula, c(t) Is the state result of the robot at the current moment, w(t) is a weight function, which can be represented by a transition matrix, which is used to characterize the robot in the process of transitioning from the state result of the previous moment to the state result of the current moment, each emotion The probability of conversion to any one or more emotions, the degree of importance is related to the moment information of the robot, c(t-1) is the state result of the robot at the last moment, and e _o (t-1) is the robot The status output data at the previous moment.

It should be noted that the weight function represented by w(t) may be the importance of the state result of the previous moment relative to the state result of the robot at the current moment. It can be considered that the shorter the time between the current moment and the previous moment is, the shorter the time is. The value of the above weighting function can be larger, indicating that the state result of the robot at the previous moment is more important for the state result of the robot at the current moment than the input value of the previous moment.

As can be seen from the above, the foregoing embodiment of the present application uses the state output data of the acquiring robot at the previous moment and the state result of the previous moment, and inputs the state output data of the previous moment and the state result of the previous moment to the preset state result. The model, the method of determining the state result of the current moment, realizes the technical purpose of determining the state result of the robot at the current moment by the state output data of the robot at the previous moment and the state result of the previous moment.

Optionally, before the step S102, that is, before the state output result of the current time is determined according to the state output data of the robot at the previous moment and the state result of the previous moment, the method further includes the following steps. :

In step S1025, the state output data of the previous moment at the previous moment and the state result of the previous moment of the previous moment are input to the state result model, and the state result of the last moment of the robot is obtained.

The above steps provide a method for obtaining the state result of the robot. It can be concluded from the above method that the state result of the robot at any moment is related to the state result of the robot at a plurality of previous moments, thereby realizing the process of the personality evolution of the robot.

It is worth noting that when the robot's emotional system is first run and does not have the status results of multiple previous moments, the robot has a preset initial state result.

As can be seen from the above, the above method of the present application obtains the state result of the last time of the robot by inputting the state output data of the previous time at the previous time and the state result of the previous time of the previous time to the state result model. The above method provides a method for acquiring the state result of the robot, and realizes the technical effect of taking the state result of the robot at the current time and the plurality of times before the current time when calculating the state data of the robot by using the method of acquiring the state result. Therefore, the technical purpose of the robot has an anthropomorphic personality evolution process, thereby further solving the prior art calculation of the robot's emotional system, which only involves the current input emotion and the influence of the emotion at the last moment on the current emotion, resulting in The technical results of the robot's emotional system are inaccurate.

Optionally, in step S106, according to the state data of the current time of the robot, the state output data at the previous time, and the state result at the current time, the step of determining the state output data of the robot at the current time includes:

Step S1061, acquiring state data of the robot at the current time.

In step S1063, the state output data of the robot at the current time, the state data at the current time, and the state result at the current time are input to a preset state calculation formula, and the state output data of the robot at the current time is determined.

As can be seen from the above, the above steps of the present application input the state data of the robot at the current time, the state data at the current time, and the state result at the current time to the preset state by acquiring the state data of the robot at the current time. The calculation formula determines the state output data of the robot at the current time, and achieves the purpose of outputting the state output data obtained by the robot output.

Optionally, in the above step S1063, the state output data of the robot at the current time, the state data at the current time, and the state result at the current time are input to a preset state calculation formula to determine the state of the robot at the current time. The steps to output data include:

In step S1065, the state output data of the robot at the current time is calculated by the following formula:

e _o (t)=c(t)*a*e _i (t)+c(t)*(1-a)*e _o (t-1),

Where e _o (t) is the state output data of the robot at the current time, c(t) is the state result of the robot at the current time, a is the proportional coefficient, and e _i (t) is the state data of the robot at the current time, e _o (t-1) is the output data of the robot at the last moment.

Specifically, in the above formula, a may be any value greater than 0 and less than 1, for determining the state data of the robot at the current time and the state result of the current time and the robot at the previous moment when calculating the state output data of the robot. The ratio of the state output data to the state result at the previous moment.

As an alternative embodiment, e _i (t) and e _o (t) may be a matrix of one row and multiple columns, in the example of the emotional system including "happy, sad, angry, surprised, disgusted, fearful and calm". , you can get the basic matrix {happy, sad, angry, surprised, disgusted, fear, calm}, when the emotional information output from the outside to the robot is "happy", e _i (t) = {1, 0, 0, 0, 0,0,0}; When the sentiment information outputted to the robot by the outside world is "happy" and "surprised", e _i (t) = {1, 0, 0, 1, 0, 0, 0}.

As can be seen from the above, the above steps of the present application provide a scheme for calculating the state output data of the robot at the current time by using the state output data of the robot at the current time, the state data at the current time, and the state result at the current time. The above solution acquires the state data of the robot at the current time by the calculation formula of the state output data of the robot at the current time.

Optionally, in the above steps of the present application, the proportional coefficient a is any value between 0 and 1.

It can be seen from the above that the method provided by the above embodiment of the present application determines the value range of the proportional coefficient a, and realizes the effect of calculating the state output data of the robot at the current time according to the formula for calculating the state output data of the robot at the current time.

Optionally, in the foregoing step S1021 of the present application, the step of outputting the state output data of the previous moment and the state result of the previous moment to the preset state result model, and determining the state result of the current moment includes: calculating by using the following formula The status of the robot:

c(t)=c(t-1)*e _o (t-1)*w(t),

Where c(t) is the state result of the robot at the current time, c(t-1) is the state result of the robot at the previous moment, and e _o (t-1) is the state output data of the robot at the previous moment, w (t) is a weight function.

Specifically, in the above steps, w(t) is used as a weight function for characterizing the robot in the process of transitioning from the state result of the previous moment to the state result of the current moment, and each emotion is converted into any one or more The probability of emotion, in the example of the emotional system including "happy, sad, angry, surprised, disgusted, fearful and calm", w(t) can be an n*n transition matrix, where n=7.

In an alternative embodiment, the weighting function can be determined using an expert system, and the expert system determining the weighting function can include the process in which the robot transitions from one state result to another in different situations. Each emotion is converted into a probability factor table of one or more emotions, and the probability factor table can be composed of empirical values obtained by simulating human emotion changes.

In another optional embodiment, the factor analysis weight method may be used to obtain the weight function of the state result at the previous moment, and in the case of using the factor analysis weight method to obtain the state result of the previous moment, In the state result of the previous moment, each emotion calculates the contribution rate of conversion to other emotions. For example, the contribution rate of “happy” to “calm” can be 25%, and “happy” is converted to “fear”. The contribution rate may be 3%, and when the above contribution rate is larger, it can be considered that the value indicating the above contribution ratio is larger in the state matrix for expressing the weight function.

The method of determining the weight function of the state result of the robot at the last moment may be any one of the methods provided in the above embodiments, but is not limited thereto.

As can be seen from the above, in the above embodiment of the present application, a calculation formula that can be used to calculate the state result of the robot and a method for determining the weight function are proposed, and the technical effect that the state result of the robot can be calculated according to the above calculation formula is realized.

Optionally, in the above steps of the present application, the status data and the status output data comprise a combination of any one or more of the following emotional information: happy, sad, angry, surprised, disgusted, fearful, and calm.

As an optional embodiment, in an example in which the emotional information of the robot includes any one or more of a combination of happiness, sadness, anger, surprise, disgust, fear, and calm, Table 1 is in the embodiment of the present invention. The initial state result of the robot is converted to the weight value, and the emotion conversion matrix is an example of the emotion in 7 as shown in Table 1. When the initial state result of the robot is happy, when the robot is in the state result of the next moment, when the next When the time state data is happy, the weight of the initial conversion result of the robot is 0.6, and when the state data of the next time is fear, the weight of the initial conversion result of the robot is 0.25.

Table 1

	开心Happy	难过Sad	生气pissed off	惊讶Surprised	厌恶disgust	恐惧fear	平静calm
开心Happy	0.60.6	0.030.03	0.030.03	0.030.03	0.030.03	0.030.03	0.250.25
难过Sad	0.030.03	0.60.6	0.030.03	0.030.03	0.030.03	0.030.03	0.250.25
生气pissed off	0.030.03	0.030.03	0.60.6	0.030.03	0.030.03	0.030.03	0.250.25
惊讶Surprised	0.030.03	0.030.03	0.030.03	0.60.6	0.030.03	0.030.03	0.250.25
厌恶disgust	0.030.03	0.030.03	0.030.03	0.030.03	0.60.6	0.030.03	0.250.25
恐惧fear	0.030.03	0.030.03	0.030.03	0.030.03	0.030.03	0.60.6	0.250.25
平静calm	1/71/7	1/71/7	1/71/7	1/71/7	1/71/7	1/71/7	1/71/7

As can be seen from the above, the foregoing embodiment of the present application provides optional state information of the robot and optional emotion information of the state output data, so that the state data and the state output data of the robot can be one emotional information or multiple emotional information combinations. The technical effect further makes the robot's emotional system more anthropomorphic.

Embodiment 2

3 is a schematic structural diagram of an apparatus for acquiring a state of a robot according to an embodiment of the present invention. For the purposes of description, the depicted architecture is only one example of a suitable environment and is not intended to limit the scope of the application. Nor should the device that acquires the state of the robot be considered to have any dependency or need for any of the components or combinations shown in FIG.

As shown in FIG. 3, the device for acquiring the state of the robot may include: a first determining module 30, a first obtaining module 32, and a second determining module 34, wherein:

The first determining module 30 is configured to determine a state result of the robot at the current moment according to the state output data of the robot at the previous moment and the state result of the previous moment, wherein the state result of the previous moment is initiated by the robot at the initial moment The status result and the status output data at a plurality of times before the previous time are determined.

Specifically, in the foregoing device, the status output data of the last moment may be the emotion information that the robot has external input at the last moment; the state structure accumulated before the last moment may be the personality information of the robot at the previous moment; The state result of the moment may be the personality information of the person at the current moment. The moment in the above embodiment may be the time when the robot inputs or outputs the emotion information.

It is worth noting that the personality information of the robot at the current moment is determined by the state output data of the robot at the previous moment and the state result of the previous moment. It can be considered that the personality information of the robot at the current moment is determined by the robot at a moment. The emotion information input from the outside is determined by the personality information of the previous moment, so the personality information of the robot may be accumulated by the robot after the stimulation of the input emotion information outside the plurality of moments, wherein the robot initially has one The initial state result, the initial value of the state result can be considered as the "character" of the robot in the initial state. When the external emotion information is input externally, the emotion information is superimposed on the initial value of the initial state result of the robot, forming a more conforming to humanity. Character robotic emotional system.

The first obtaining module 32 is configured to acquire state data received at the current time.

a second determining module 34, configured to determine, according to the state data of the current time of the robot, the state output data at the current time, and the state result at the current time, the state output data of the robot at the current time;

The state data represents the sentiment information of the external input received by the robot, the state output data represents the sentiment information output by the robot to the outside, and the state result represents the personality information formed by the robot accumulating at least one sentiment information during the running process.

As can be seen from the above, the first embodiment of the present application determines the state result of the robot at the current time according to the state output data of the robot at the previous moment and the state result of the previous moment, and acquires the current state data received at the current time. The state output data of the robot at the current time is determined by the second determining module according to the state data of the robot at the current time, the state output data at the current time, and the state result at the current time. In the above solution, when determining the state output data of the robot at the current time, the state data of the current time of the robot, the state output data of the previous time, and the state result of the current time are used, wherein the state result is the initial state of the robot at the initial time. The result and the state output data at a plurality of times before the last moment are determined. By adopting the above scheme, the state output data of the robot is more anthropomorphic and more accurate, thereby solving the emotion of the robot in the prior art. When the system performs calculations, it only involves the emotions of the current input and the influence of the emotions of the previous moment on the current emotions, resulting in inaccurate technical problems of the operation results of the robot's emotional system.

Optionally, in conjunction with FIG. 4, according to the apparatus provided by the foregoing embodiment of the present application, the first determining module 30 includes:

The first obtaining sub-module 301 is configured to acquire state output data of the robot at a previous moment and a state result of the last moment.

Specifically, in the above device, the state output data of the robot at the last moment may be the emotion information input by the robot from the outside at the last moment, and the emotional result of the last moment may be the emotion input of the robot at multiple moments before the last moment. After the evolution of emotional information, the robot’s personality information at the last moment

The first determining sub-module 302 is configured to input the state output data of the last moment and the state result of the last moment to a preset state result model, and determine a state result of the current moment, where the state result model includes the previous moment The state result determines the weight function of the current moment.

Specifically, in the foregoing solution, the preset state result model may be a function related to time information, for example, c(t)=f(w(t), c(t-1), e _o (t-1) In the above function formula, c(t) is the state result of the robot at the current time, w(t) is the weight function related to the time information, and c(t-1) is the state result of the robot at the previous moment. e _o (t-1) is the state output data of the robot at the previous moment.

It is worth noting that the weight function represented by w(t) can be the importance of the state result of the previous moment relative to the state result of the robot at the current moment. It can be considered that the shorter the time between the current moment and the previous moment is considered. The value of the above weighting function can be larger, indicating that the state result of the robot at the previous moment is more important for the state result of the robot at the current moment than the input value of the previous moment.

As can be seen from the above, the foregoing embodiment of the present application uses the second acquiring module to acquire the state output data of the robot at the previous moment and the state result of the previous moment, and input the state output data of the previous moment and the state result of the previous moment to the pre-previous The state result model is set, and the method for determining the state result of the current time by the third determining module realizes the technical purpose of determining the state result of the robot at the current time by the state output data of the robot at the previous moment and the state result of the previous moment. .

Optionally, as shown in FIG. 5, the device provided by the foregoing embodiment of the present application further includes:

The second obtaining module 50 is configured to input the state output data of the previous moment at the previous moment and the state result of the previous moment of the previous moment to the state result model, and acquire the state result of the last moment of the robot.

As can be seen from the above, the device of the present application inputs the state output data of the previous moment at the previous moment and the state result of the previous moment of the previous moment to the state result model through the third acquisition module to obtain the state of the robot at the previous moment. result. The above method provides a method for acquiring the state result of the robot, and implements a technique in which the state result of the robot is calculated by taking the state result and calculating the state output data of the robot at a plurality of times before the current time and the current time. The effect, so as to achieve the technical purpose of the robot with the anthropomorphic personality evolution process, thereby further solving the prior art calculation of the robot's emotional system only involves the current input emotion and the influence of the last moment's emotion on the current emotion, A technical problem that leads to inaccurate results of the robot's emotional system.

Optionally, in conjunction with FIG. 6, according to the apparatus provided by the foregoing embodiment of the present application, the second determining module 34 includes:

The second obtaining submodule 341 is configured to acquire state data of the robot at the current time.

The second determining sub-module 343 is configured to input the state output data of the robot at the current moment, the state data at the current moment, and the state result at the current moment to a preset state calculation formula, and determine the state output of the robot at the current moment. data.

As can be seen from the above, the above step of the present application acquires state data of the state of the robot at the current time through the third obtaining module, and outputs the state of the robot at the current time, the state data at the current time, and the state result at the current time. The input to the preset state calculation formula determines the state output data of the robot at the current time through the fourth determining module, and achieves the purpose of outputting the state output data obtained by the robot output.

Optionally, in conjunction with FIG. 7, according to the apparatus provided by the foregoing embodiment of the present application, the second determining submodule 343 includes:

The first calculating unit 3431 is configured to calculate the state output data of the robot at the current moment by the following formula:

e _o (t)=c(t)*a*e _i (t)+c(t)*(1-a)*e _o (t-1),

As can be seen from the above, the above steps of the present application provide a calculation module that uses the state output data of the robot at the current time, the state data at the current time, and the state result at the current time to calculate the state output data of the robot at the current time. The state data of the robot at the current time is acquired by the calculation formula of the output data by the state of the robot at the current time.

Optionally, according to the apparatus provided by the above embodiment of the present application, the proportional coefficient a is an arbitrary value between 0 and 1.

Optionally, as shown in FIG. 8 , the device according to the foregoing embodiment of the present application is characterized in that: The determining sub-module 302 includes:

The second calculating unit 3021 is configured to calculate a state result of the robot by using the following formula:

c(t)=c(t-1)*e _o (t-1)*w(t),

It can be seen from the above that in the above embodiment of the present application, a calculation formula for calculating the state result of the robot by the second calculation module is proposed, and the technical effect that the state result of the robot can be calculated according to the above calculation formula is realized.

Optionally, according to the apparatus provided by the above embodiment of the present application, the status data and the status output data comprise a combination of any one or more of the following emotion information: happy, sad, angry, surprised, disgusted, fearful and calm.

The serial numbers of the embodiments of the present invention are merely for the description, and do not represent the advantages and disadvantages of the embodiments.

In the above-mentioned embodiments of the present invention, the descriptions of the various embodiments are different, and the parts that are not detailed in a certain embodiment can be referred to the related descriptions of other embodiments.

In the several embodiments provided by the present application, it should be understood that the disclosed technical contents may be implemented in other manners. The device embodiments described above are only schematic. For example, the division of the unit may be a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be combined or may be Integrate into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, unit or module, and may be electrical or otherwise.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated order The element can be implemented in the form of hardware or in the form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention, which is essential or contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product stored in a storage medium. A number of instructions are included to cause a computer device (which may be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: a U disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk, and the like. .

The above description is only a preferred embodiment of the present invention, and it should be noted that those skilled in the art can also make several improvements and retouchings without departing from the principles of the present invention. It should be considered as the scope of protection of the present invention.

Claims

A method for acquiring a state of a robot, comprising:

Determining a state result of the robot at a current time according to a state output data of the robot at a previous moment and a state result of a previous moment, wherein the state result of the last moment is an initial state result of the robot at an initial moment And determining the status output data at a plurality of times before the last moment;

Obtaining state data received at the current time;

And determining, according to the state data of the robot at the current time, the state output data at the previous time, and the state result at the current time, the state output data of the robot at the current time.
The method according to claim 1, wherein the state result of the robot at the current time is determined according to the state output data of the robot at the last moment and the state result of the previous moment, including:

Obtaining state output data of the robot at the last moment and a state result of the last moment;

Inputting the state output data of the last moment and the state result of the previous moment to a preset state result model, and determining a state result of the current moment, wherein the state result model includes the previous one The weight function of the current moment determined by the state result of the moment.
The method according to claim 1, wherein the method further comprises: before determining the state result of the robot at the current time based on the state output data of the robot at the last moment and the state result of the last moment, the method further comprising:

The state output data of the previous time at the previous time and the state result of the previous time of the previous time are input to the state result model, and the state result of the last time of the robot is acquired.
The method according to any one of claims 1 to 3, characterized in that, according to the state data of the robot at the current time, the state output data at the last moment, and the state at the current time As a result, determining the state output data of the robot at the current moment includes:

Obtaining state data of the robot at the current time;

Determining, by the robot, the state output data at the last moment, the state data at the current moment, and the state result at the current moment to a preset state calculation formula, determining that the robot is at the current moment Status output data.
The method according to claim 4, wherein the state output data of the robot at the last moment, the state data at the current moment, and the state result at the current moment are input to a preset a state calculation formula determining the state output data of the robot at the current moment, including:

The state output data of the robot at the current moment is calculated by the following formula:

e o (t)=c(t)*a*e i (t)+c(t)*(1-a)*e o (t-1),

Wherein the e o (t) is the state output data of the robot at the current time, the c(t) is a state result of the robot at the current time, and the a is a proportional coefficient, The e i (t) is the state data of the robot at the current time, and the e o (t-1) is the state output data of the robot at the last moment.
The method according to claim 5, wherein said proportional coefficient a is an arbitrary value between 0 and 1.
The method according to claim 2, wherein the state output data of the last moment and the state result of the last moment are input to a preset state result model, and the state result of the current moment is determined. include:

The state result of the robot is calculated by the following formula:

c(t)=c(t-1)*e o (t-1)*w(t),

Wherein the c(t) is a state result of the robot at the current moment, and the c(t-1) is a state result of the robot at the last moment, the e o (t- 1) outputting data for the state of the robot at the last moment, the w(t) being the weight function.
The method of claim 1 wherein said status data and said status output data comprise a combination of any one or more of the following: emotional, sad, angry, surprised, disgusted, fearful, and calm.
A device for acquiring a state of a robot, comprising:

a first determining module, configured to determine a state result of the robot at a current time according to a state output data of the robot at a previous moment and a state result of a previous moment, wherein the state result of the last moment is determined by the robot The initial state result at the initial time and the state output data at a plurality of times before the last time are determined;

a first acquiring module, configured to acquire state data received at the current time;

a second determining module, configured to determine, according to the state data of the robot at the current moment, the state output data at the last moment, and the state result at the current moment, the robot at the current moment Status output data.
The apparatus according to claim 9, wherein the first determining module comprises:

a first acquiring submodule, configured to acquire state output data of the robot at the last moment and a state result of the last moment;

a first determining submodule, configured to input the state output data of the last moment and the state result of the last moment to a preset state result model, and determine a state result of the current moment, where the state The resulting model includes a weighting function of the current time determined by the state result of the last moment.
The device according to claim 9, wherein the device further comprises:

a second acquiring module, configured to input the state output data of the previous moment of the last moment and the state result of the previous moment of the last moment to the state result model, and acquire the previous moment of the robot The status of the result.
The apparatus according to any one of claims 9 to 11, wherein the second determining module comprises:

a second obtaining submodule, configured to acquire state data of the robot at the current moment;

a second determining submodule, configured to input the state output data of the robot at the last moment, the state data at the current moment, and the state result at the current moment to a preset state calculation formula, The robot outputs data in a state of the current time.
The apparatus according to claim 12, wherein the second determining submodule comprises:

a first calculating unit, configured to calculate, by using the following formula, the state output data of the robot at the current moment:

e o (t)=c(t)*a*e i (t)+c(t)*(1-a)*e o (t-1),

Wherein the e o (t) is the state output data of the robot at the current time, the c(t) is a state result of the robot at the current time, and the a is a proportional coefficient, The e i (t) is the state data of the robot at the current time, and the e o (t-1) is the state output data of the robot at the last moment.
The device according to claim 13, characterized in that said proportional coefficient a is an arbitrary value between 0 and 1.
The apparatus according to claim 10, wherein the first determining submodule comprises:

a second calculating unit, configured to calculate the state result of the robot by the following formula:

c(t)=c(t-1)*e o (t-1)*w(t),

Wherein the c(t) is a state result of the robot at the current moment, and the c(t-1) is a state result of the robot at the last moment, the e o (t- 1) outputting data for the state of the robot at the last moment, the w(t) being the weight function.
The apparatus of claim 9, wherein the status data and the status output data comprise a combination of any one or more of the following emotional information: happy, sad, angry, surprised, disgusted, fearful, and calm.