JP2001157980A - Robot device, and control method thereof - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a robot device and a control method thereof capable of improving amusement performance. SOLUTION: In this robot device to generate an action based on an emotion model and/or an instinct model, an external sensor to detect a degree of a specified environmental condition, a recognition means to recognize the degree of the environmental condition based on result of detection by the external sensor, and a changing means to change the emotion model and/or the instinct model based on result of recognition by the recognition means are provided. In this control method for a robot device to generate an action model based on the emotion model and/or the instinct model, a first step to recognize a degree of a specified environmental condition, and a second step to change the emotion model and/or the instinct model based on result of recognition are provided.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a robot apparatus and a control method therefor, and is suitably applied to, for example, a pet robot.

[0002]

2. Description of the Related Art In recent years, a pet robot of a four-legged walking type has been proposed and developed by the present applicant. Such a pet robot has a shape similar to a dog or cat bred in an ordinary household, and acts autonomously in response to user's actions such as "slap" and "stroke" and the surrounding environment. is there.

[0003]

By the way, such a pet robot is provided with a function of changing emotions and instinct according to the surrounding environment such as "bright", "dark", "noisy" and "hot". If it can be mounted, it is thought that it is possible to improve the feeling of life, give the user a further sense of intimacy and satisfaction, and further improve the amusement as a pet robot.

The present invention has been made in consideration of the above points, and has as its object to propose a robot apparatus capable of improving amusement and a control method thereof.

[0005]

According to the present invention, there is provided a robot apparatus for generating an action based on an emotion model and / or an instinct model, wherein an external sensor for detecting a degree of a predetermined environmental condition is provided. And recognition means for recognizing the degree of the environmental condition based on the detection result of the external sensor, and changing means for changing the emotion model and / or the instinct model based on the recognition result of the recognition means. As a result, in this robot device, emotions and / or instinct change according to the environment.

According to the present invention, in a control method of a robot apparatus for generating an action based on an emotion model and / or an instinct model, a first step of recognizing a degree of a predetermined environmental condition, And a second step of changing the emotion model and / or the instinct model. As a result, according to the robot apparatus control method, the emotion and / or instinct of the robot apparatus can be changed according to the environment.

[0007]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below in detail with reference to the drawings.

(1) Configuration of a Pet Robot According to the Present Embodiment In FIG. 1, reference numeral 1 denotes a pet robot according to the present embodiment as a whole, and leg units 3A to 3D are connected to the front, rear, left and right of a body unit 2, respectively. The head unit 4 and the tail unit 5 are connected to the front end and the rear end of the body unit 2, respectively.

As shown in FIG. 2, a CPU (Central Processing Unit) 10 and a DRA
M (Dynamic Random Access Memory) 11, Flash ROM (Read Only Memory) 12, PC (Personal Com
puter) A control unit 16 formed by connecting a card interface circuit 13 and a signal processing circuit 14 to each other via an internal bus 15 and a battery 17 as a power source of the pet robot 1 are housed therein. . The body unit 2 has an angular velocity sensor 18 for detecting the direction and the acceleration of the movement of the pet robot 1.
And an acceleration sensor 19 are also stored.

The head unit 4 detects a CCD (Charge Coupled Device) camera 20 for capturing an image of an external situation and a pressure received by a physical action such as "stroke" or "hit" from the user. A touch sensor 21, a distance sensor 22 for measuring a distance to an object located ahead, a microphone 23 for collecting external sound, and a speaker 24 for outputting a sound such as a cry. , An LED (Light Emitting Diode) (not shown) corresponding to the “eyes” of the pet robot 1 and the like are arranged at predetermined positions.

Further, the joints of the leg units 3A to 3D, the leg units 3A to 3D and the trunk unit 2
Each coupling portion of the head unit 4 and body unit connecting portion 2, and the tail unit actuator 25 _1, respectively, etc. The consolidated portion of the tail 5A of freedom minutes 5
To 25 _n and potentiometers 26 _{1 to} 26 _n are provided.

The angular velocity sensor 18, acceleration sensor 19, touch sensor 21, distance sensor 22, microphone 23, speaker 24, and each potentiometer 26
Various sensors such as _{1 to} 26 _n , LEDs and actuators 25 _{1 to} 25 _n are respectively connected to the corresponding hubs 27.
_The CCD camera 20 and the battery 17 are connected to the signal processing circuit 14 of the control unit 16 through _{1 to} 27 _N.
Are directly connected to the signal processing circuit 14, respectively.

At this time, the signal processing circuit 14 sequentially takes in the sensor data, image data, and audio data supplied from each of the above-described sensors, and receives these sequentially into the internal bus 15.
, And sequentially stored in a predetermined position in the DRAM 11. In addition, the signal processing circuit 14 sequentially takes in remaining battery power data indicating the remaining battery power supplied from the battery 17 and stores the data at a predetermined position in the DRAM 11.

The sensor data, image data, audio data and remaining battery data stored in the DRAM 11 in this manner are used when the CPU 10 controls the operation of the pet robot 1 thereafter.

In practice, when the power of the pet robot 1 is turned on, the CPU 10 executes the control program stored in the memory card 28 or the flash ROM 12 inserted in the PC card slot (not shown) of the body unit 2 into the PC card interface. The data is read out via the circuit 13 or directly and stored in the DRAM 11.

Further, the CPU 10 thereafter, based on the sensor data, image data, audio data, and remaining battery power data sequentially stored in the DRAM 11 from the signal processing circuit 14 as described above, as well as from the user and the surroundings. Judge whether or not there is an instruction for and action.

Further, the CPU 10 determines the result of this determination and D
And it determines a subsequent action based on the control program stored in the RAM 11, by driving the actuator 25 ₁ to 25 _n required based on the determination result,
The head unit 4 can be swung up and down, left and right, the tail 5A of the tail unit 5 can be moved, and each of the leg units 3A to 3A.
D is driven to perform an action such as walking.

At this time, the CPU 10 generates audio data as required, and supplies the generated audio data to the speaker 24 as an audio signal via the signal processing circuit 14, thereby outputting an audio based on the audio signal to the outside, LED above
Is turned on, off or blinking.

As described above, the pet robot 1 is capable of acting autonomously according to its own and surrounding conditions, instructions and actions from the user.

(2) Software Configuration of Control Program The software configuration of the above-described control program in the pet robot 1 is shown in FIG. In FIG.
The device driver layer 30 is located at the lowest layer of the control program, and includes a device driver set 31 including a plurality of device drivers. In this case, each device driver is a CCD camera 2
0 (FIG. 2), an object such as a timer, which is allowed to directly access hardware used in a normal computer, and performs processing in response to an interrupt from the corresponding hardware.

The robotic server object 32 is located above the device driver layer 30 and includes, for example, the various sensors and actuators 25 ₁ described above.
A virtual robot 33 comprising a software group that provides an interface for accessing the hardware, such as to 25 _n, the power manager 34 made of a software suite for managing the power supply switching, the other various device drivers Device driver manager 35, which is a group of software to be managed, and pet robot 1
And a designed robot 36 which is a software group for managing the mechanism.

The manager object 37 includes an object manager 38 and a service manager 39.
It is composed of In this case, the object manager 38 has the robotic server object 32,
Middleware layer 40 and application
The service manager 39 is a software group that manages activation and termination of each software group included in the layer 41. The service manager 39 stores connection information between objects described in a connection file stored in the memory card 28 (FIG. 2). Is a group of software that manages the connection of each object based on.

The middleware layer 40 is located on the upper layer of the robotic server object 32 and is composed of a group of software for providing basic functions of the pet robot 1 such as image processing and sound processing. I have.
Further, the application layer 41 is located in a layer above the middleware layer 40, and
It is composed of a software group for determining the behavior of the pet robot 1 based on the processing result processed by each software group constituting the layer 40.

The specific software configurations of the middleware layer 40 and the application layer 41 are shown in FIGS. 4 and 5, respectively.

In the middleware layer 40,
As is clear from FIG. 4, for scale recognition, for distance detection,
Recognition system 5 including signal processing modules 50 to 55 for posture detection, touch sensor, motion detection, and color recognition, input semantics converter module 56, and the like.
7 and the output semantics converter module 57 and for attitude management, tracking, motion playback,
An output system 65 includes signal processing modules 58 to 64 for walking, falling back, turning on LEDs, and reproducing sounds.

In this case, the signal processing modules 50 to 55 of the recognition system 57 are connected to the DRAM 11 by the virtual robot 33 of the robotic server object 32.
The corresponding data among the sensor data, image data, and audio data read out from FIG. 2 (FIG. 2) is fetched, predetermined processing is performed based on the data, and the processing result is provided to the input semantics converter module 56.

The input semantics converter module 56, based on the processing results given from each of the signal processing modules 50 to 55, “detects a ball”,
"Detected fall,""stroke,""beaten,"
"I heard the domeso scale,""Detected a moving object."
Alternatively, it recognizes the situation of itself and surroundings, such as "detected an obstacle", and commands and actions from the user, and outputs the recognition result to the application layer 41 (FIG. 2).

As shown in FIG. 5, the application layer 41 is composed of five modules: a behavior model library 70, a behavior switching module 71, a learning module 72, an emotion model 73, and an instinct model 74.

In this case, the behavior model library 70 includes
As shown in FIG. 6, "when the battery level is low", "when the vehicle returns to the fall", "when avoiding obstacles", "when expressing emotion", "when the ball is detected", and the like. Respectively correspond to several pre-selected condition items, and independent behavior models 70 _{1 to} 7 respectively.
0 _n is provided.

The behavior models 70 ₁ to 70 _1
n is stored in the emotion model 73 as described later as necessary when a recognition result is given from the input semantics converter module 56 or when a certain time has elapsed since the last recognition result was given. The next action is determined with reference to the corresponding emotion parameter value and the corresponding desire parameter value held in the instinct model 74, and the determination result is output to the action switching module 71.

In the case of this embodiment, each of the behavior models 70 ₁ to 70 _n uses one node (state) NODE _{0 to} NO as shown in FIG.
The arc ARC ₁ transition probabilities are set respectively ~ARC _{n 1} P ₁ ~P _n for connecting the respective nodes NODE ₀ ~NODE _n or transitions from DE _n to any other node NODE ₀ ~NODE _n An algorithm called a probabilistic automaton, which determines stochastically based on this, is used.

More specifically, each of the behavior models 70 ₁ to 70
_n corresponds to each of the nodes NODE _{0 to} NODE _n forming their own behavior models 70 ₁ to 70 _n , respectively, and FIG. 8 for each of these nodes NODE _{0 to} NODE _n
Has a state transition table 80 as shown in FIG.

In this state transition table 80, the node NO
Input events (recognition results) as transition conditions in DE _{0 to} NODE _n are listed in order of priority in the row of “input event name”, and further conditions for the transition conditions are described in the rows of “data name” and “data range”. It is described in the corresponding column.

Therefore, in the node NODE ₁₀₀ represented by the state transition table 80 in FIG. 8, "ball detected (BALL)"
When the recognition result is given, the "size (SIZE)" of the ball given together with the recognition result is in the range of "0 to 1000", or the recognition of "obstacle detected (OBSTACE)" is given. When the result is given, the condition for transition to another node is that the "distance" to the obstacle given together with the recognition result is in the range of "0 to 100". .

In the node NODE ₁₀₀ , even when the recognition result is not input, the behavior models 70 _{1 to} 7
0 _n of the parameter values of the emotions and desires stored in the emotion model 73 and the instinct model 74 that are periodically referred to, respectively.
When the parameter value of any of "Y)", "Surprise", or "Sadness" is in the range of "50 to 100", it is possible to make a transition to another node.

In the state transition table 80, in the column of "transition destination node" in the column of "transition probability to another node", the names of nodes that can transition from the nodes NODE _{0 to} NODE _n are listed, and Other nodes NODE _{0 to} N that can transition when all the conditions described in the rows of “event name”, “data value”, and “data range” are met
The transition probability to ODE _n is described in a corresponding part in the column of “transition probability to another node”, and the node N
The action to be output when transitioning from ODE _{0 to} NODE _n is “output action” in the column of “transition probability to another node”.
Is described in the line. Note that the sum of the probabilities of the respective rows in the column of “transition probability to another node” is 100 [%].

Therefore, in the node NODE ₁₀₀ represented by the state transition table 80 in FIG.
L) "and the" SIZE "of the ball is" 0 ".
Is given in the range of “node NODE” with a probability of “30 [%]”.
₁₂₀ (node 120) ”, and then“ ACTIO ”
The action of "N1" will be output.

Each of the behavior models 70 ₁ to 70 _n is configured such that a number of nodes NODE _{0 to} NODE _n described as such a state transition table 80 are connected, and the input semantics converter module 56 For example, when a recognition result is given, the next action is stochastically determined using the state transition table 80 of the corresponding nodes NODE ₀ to NODE _n , and the determination result is output to the action switching module 71. ing.

The action switching module 71 includes an action model
Each behavior model 70 of the library 70 ₁~ 70_nFrom it
Of the actions that are output respectively,
High behavior model 70₁~ 70_nSelect the action output from
Command to execute the action (hereinafter referred to as
Is called an action command).
To the output semantics converter 57. Note that
In this embodiment, the lower part of FIG.
Behavior model 70₁~ 70_nSet higher priority
Have been.

Further, based on the action completion information provided from the output semantics converter 57 after the action is completed, the action switching module 71 notifies the learning module 72, the emotion model 73, and the instinct model 7 that the action has been completed.
Notify 4.

On the other hand, the learning module 72 inputs the recognition result of the teaching received from the user, such as “hit” or “stroke”, among the recognition results given from the input semantics converter 56.

Based on the recognition result and the notification from the action switching module 71, the learning module 72 lowers the probability of occurrence of the action when "beaten (scolded)" and "strokes (praise)". was) "sometimes to increase the expression probability of that action, behavior model 70 _1-7 corresponding in behavioral model library 70
Change the corresponding transition probability of 0 _n .

On the other hand, the emotion model 73 indicates "joy (joy)
) "," Sadness "," anger "
) "," Surprise "," disgust "
For a total of six emotions of “fear” and “fear”, a parameter indicating the strength of the emotion is stored for each emotion. Then, the emotion model 73 converts the parameter values of each of these emotions from the specific recognition results such as “hit” and “stroke” given from the input semantics converter module 56 and the elapsed time and action switching module 71, respectively. Is periodically updated based on the notification of.

Specifically, the emotion model 73 is based on the recognition result given from the input semantics converter module 56, the behavior of the pet robot 1 at that time, the elapsed time since the last update, and the like. Is the amount of change of the emotion at that time calculated by ΔE
[T], the current parameter value of the emotion E [t], the coefficient representing the sensitivity of the emotion as k _e, the following equation

[0045]

(Equation 1)

Thus, the parameter value E [t + 1] of the emotion in the next cycle is calculated, and the parameter value of the emotion is updated by replacing the parameter value E [t] with the current parameter value E [t] of the emotion. The emotion model 73 is
Similarly, the parameter values of all emotions are updated.

Each recognition result and action switching module 7
1 is the variation ΔE of the parameter value of each emotion
The degree of influence on [t] is determined in advance. For example, a recognition result such as “hit” has a large effect on the variation ΔE [t] of the parameter value of the emotion of “anger”. The recognition result such as “stroke” has a great influence on the variation ΔE [t] of the parameter value of the emotion of “joy”.

On the other hand, the instinct model 74 includes “exercise (exersise)”, “affection (afection)”, and “appetite (ap
For each of the four independent desires "petite" and "curiocity", a parameter indicating the strength of the desire is held for each of the desires. Then, the instinct model 74 converts the parameter values of the desire into the recognition result given from the input semantics converter module 56, the elapsed time and the action switching module 71, respectively.
Update periodically based on notification from

More specifically, the instinct model 74 is “exercise desire”
Regarding “affection desire” and “curiosity”, the amount of change in the desire at that time calculated by a predetermined arithmetic expression based on the recognition result, the elapsed time, and the notification from the action switching module 71 is ΔI [k] , The current parameter value of the desire is I [k], and the coefficient representing the sensitivity of the desire is k _i ,

[0050]

(Equation 2)

Is used to calculate the parameter value I [k + 1] of the desire in the next cycle, and replaces the result of this operation with the current parameter value I [k] of the desire to update the parameter value of the desire. I do. Similarly, the instinct model 74 updates the parameter values of each desire except for “appetite”.

The recognition result and action switching module 7
1 is the variation ΔI of the parameter value of each desire
The degree of influence on [k] is predetermined. For example, the notification from the action switching module 71 has a large effect on the variation ΔI [k] of the parameter value of “motivation”. I have.

In the instinct model 74, the “appetite” is calculated based on the remaining battery level data provided through the input semantics converter module 56 as B _L and the following equation at a predetermined cycle.

[0054]

(Equation 3)

By calculating the parameter value I [k] of “appetite”, the result of this calculation is used as the parameter value I of the current appetite.
The parameter value of the “appetite” is updated by replacing with [k].

In the present embodiment, the parameter values of each emotion and each desire are regulated so as to fluctuate in the range of 0 to 100, and the coefficients k _e and k _i
Is also set individually for each emotion and each desire.

On the other hand, as shown in FIG. 4, the output semantics converter module 57 of the middleware layer 40 is provided with "forward" and "pleased" given from the action switching module 71 of the application layer 41 as described above. , "Sound" or "tracking (follow the ball)" to the corresponding signal processing modules 58 to 64 of the output system 65.

The signal processing modules 58 to 6
4, given the behavior command based on the action command, and servo command value to be applied to the actuator 25 ₁ to 25 _n (Fig. 2) corresponding to perform that action, the output from the speaker 24 (FIG. 2) Generating sound data of the sound to be played and / or driving data to be given to the LED of the “eye”,
These data are transferred to the virtual robot 33 of the robotic server object 32 and the signal processing circuit 14.
The corresponding actuators 25 ₁ to 25 ₁ through (FIG. 2)
25 _n , sequentially to the speaker 24 or the LED.

In this manner, the pet robot 1 can perform an autonomous action in accordance with its own and surrounding conditions, instructions and actions from the user, based on the control program. .

(3) Changes in emotions and instinct according to the environment In addition to the above configuration, in the case of the pet robot 1, for example, when the surroundings are “bright”, the pet becomes cheerful, whereas when the surroundings are “dark”, it is quiet. For example, emotions and instinct are changed in accordance with the degree of three conditions of the surrounding environment such as "noise", "temperature" and "illuminance" (hereinafter referred to as environmental conditions). .

That is, the pet robot 1 has the above-described C as an external sensor for detecting the surrounding situation.
In addition to the CD camera 20, the distance sensor 22, the touch sensor 21, the microphone 23, and the like, a temperature sensor (not shown) for detecting an ambient temperature is provided at a predetermined position.

The middleware layer 4 shown in FIG.
In addition to the above-described signal processing modules 50 to 55 for scale recognition, distance detection, attitude detection, touch sensor, motion detection, and color recognition, the recognition system 57 of FIG. As shown in FIG. 5, signal processing modules 90 to 91 for noise detection, temperature detection, and brightness detection are provided.

The signal processing module 9 for noise detection
0 detects the ambient noise level based on audio data from the microphone 23 (FIG. 2) given via the virtual robot 33 of the robotic server object 32, and sends the detection result to the input semantics converter module 56. The output has been made.

A signal processing module 91 for temperature detection
Detects the ambient temperature based on the sensor data from the temperature sensor provided via the virtual robot 33, and outputs the detection result to the input semantics converter module 56.

Further, a signal processing module 92 for detecting brightness detects surrounding illuminance based on image data from the CCD camera 20 (FIG. 2) given through the virtual robot 33, and inputs the detection result to input semantics. Output to the converter module 56.

The input semantics converter module 56 performs, in addition to the recognition processing described above with reference to FIG. 4, the surrounding “noise”, “temperature”, and “illuminance” based on the outputs of these signal processing modules 90 to 92. And outputs the recognition result to the emotion model 73 and the instinct model 74 of the application module 41 (FIG. 5) as described above.

Specifically, the input semantics converter module 56 is a signal processing module 9 for noise detection.
Recognizing the degree of surrounding “noise” based on the output of 0,
The recognition result such as "noisy" or "quiet" is output to the emotion model 73, the instinct model 74, and the like.

The input semantics converter module 56 recognizes the degree of “temperature” of the surroundings based on the output of the signal processing module 91 for temperature detection, and recognizes the recognition result of “hot” or “cold” as the emotion model 73 and Output to the instinct model 74 and the like.

Further, the input semantics converter module 56 includes a signal processing module 91 for detecting brightness.
Recognizes the degree of "illuminance" in the surrounding area based on the output of
The recognition result such as “bright” or “dark” is output to the emotion model 73, the instinct model 74, and the like.

As described above, the emotion model 73 periodically changes the parameter value of each emotion according to the expression (1) based on the various recognition results provided from the input semantics converter module 56.

The emotion model 73 includes “noise” given from the input semantics converter module 56,
Based on the recognition results for "temperature" and "illuminance",
Increase or decrease the value of the coefficient k _e of equation (1) for a predetermined corresponding emotion.

Specifically, when the recognition result such as “noisy” is given, for example,
Emotional predetermined number increases the value of the coefficient k _e for the, if the recognition result such as "quiet" is given to this reduces a predetermined number of values of the coefficient k _e for the emotion "angry".

[0073] The emotion model 73, "hot" if such a recognition result is given reduces a predetermined number of values of the coefficient k _e for emotion "joy", "cold" contrast
Increasing the predetermined number of values of the coefficient k _e for emotion "sadness" when the recognition result such is given.

[0074] Further emotion model 73, emotional value of the coefficient k _e is increased by a predetermined number with respect to the "joy" when the recognition result such as "bright" is given, the recognition result such as "dark" with respect to this when given increases a predetermined number of values of the coefficient k _e for the emotion "fear".

Similarly, as described above, the instinct model 74 periodically changes the parameter values of each desire in accordance with equations (2) and (3) based on various recognition results and the like given from the input semantics converter module 56. Change.

The instinct model 74 includes “noise” given from the input semantics converter module 56,
Based on the recognition result of the degree of “temperature” and “illuminance”, the value of the coefficient k _i of the predetermined corresponding desire (2) is increased or decreased.

Specifically, in the instinct model, when a recognition result such as “noisy” or “bright” is given, for example, the value of the coefficient k _i for “motivation” is increased by a predetermined number,
This "quiet" and when the recognition result such as "dark" is given reduces a predetermined number of values of the coefficient k _i for "exercise desire" to. In addition, the instinct model indicates that when a recognition result such as “hot” or “cold” is given,
Predetermined number to reduce the value of the coefficient k _i for.

As a result, in the pet robot 1, for example, when the surroundings are "loud", the parameter values of "anger" and "greed for exercise" are both likely to increase, so that the behavior becomes "irritated" as a whole. In contrast, when the surroundings are "quiet", the parameter values of "anger" and "exercise desire" tend to decrease,
The behavior as a whole is a “calm” behavior.

When the surroundings are "hot", the parameter values of "joy" and "exercise desire" both tend to decrease, so that the behavior as a whole is "slack".
On the other hand, when it is "cold", the parameter value of "sadness" tends to increase and the parameter value of "exercise desire" tends to decrease, so that the behavior as a whole is "cold".

Further, when the surroundings are "bright", the parameter values of "joy" and "greed for exercise" both tend to increase, so that the behavior becomes "cheerful" as a whole, whereas the surroundings are "dark". At that time, the parameter value of “joy” tends to increase and the parameter value of “exercise greed” tends to decrease, so that the behavior becomes a “quiet” behavior as a whole.

As described above, in the pet robot 1, the emotion and the instinct are changed according to the environment, and the behavior is changed according to the change.

(4) Operation and Effect of this Embodiment In the above configuration, the pet robot 1
Based on the outputs of the D camera 20, the temperature sensor and the microphone 23, the degree of “noise”, “temperature” and “illuminance” of the surroundings are recognized, and based on the recognition result, the corresponding emotion of the emotion model is expressed by equation (1). the value of the coefficient k _e of, so as to increase or decrease the value of the coefficient k _i of the expression (2) for the corresponding desire instinct model, varying these emotions and desires.

Therefore, in the pet robot 1, the behavior according to the environment is easily exhibited, and the feeling of living things can be further improved, and the user can be given a closer feeling and a more satisfying feeling.

In the pet robot 1, the sensitivity of the corresponding emotion and desire is changed as a means for changing the emotion and desire according to the environment. Can take action according to

According to the above configuration, by changing the corresponding emotions and desires according to the environment, it is possible to improve the biological feeling and to give the user a further sense of closeness and satisfaction. Thus, a pet robot that can improve amusement properties can be realized.

(5) Other Embodiments In the above-described embodiment, a case has been described in which the present invention is applied to the four-legged walking type pet robot 1. However, the present invention is not limited to this. The present invention can be widely applied to other various types of robot devices.

[0087] Further in the above embodiment, as an update rule for updating the parameters of emotions and desires a corresponding depending on the degree of environmental conditions, and the coefficient k _e in the corresponding emotional expression (1), the corresponding The case where the value of the coefficient k _i in equation (2) of the desire to do is changed has been described. However, the present invention is not limited to this. For example, the amount of change in equation (1) or equation (2) according to the environment ΔE [t], ΔI
The value of [k] may be changed, and other various update rules may be widely applied.

Further, in the above-described embodiment, a case has been described in which “noise”, “temperature”, and “illuminance” are applied as environmental conditions that change emotions and desires. However, the present invention is not limited to this. For example, “humidity”, “color”, and / or “room size” can be applied.

Further, in the above embodiment, the recognition means for recognizing the degree of “noise”, “temperature” and “illuminance” based on the detection result of the external sensor, and the emotion based on the recognition result of the recognition means. Although a case has been described in which the model and the changing means for changing the instinct model are configured by the same module of the emotion model 73 and the instinct model 74, the present invention is not limited to this, and these are formed separately. May be.

[0090]

As described above, according to the present invention, a robot device capable of improving amusement and a control method thereof are proposed.

[0091]

According to the present invention, there is provided a robot apparatus for generating an action based on an emotion model and / or an instinct model, wherein an external sensor for detecting a degree of a predetermined environmental condition is provided. And a recognizing means for recognizing the degree of the environmental condition based on the detection result of the external sensor, and a changing means for changing an emotion model and / or an instinct model based on the recognition result of the recognizing means. , The emotion and / or instinct can be changed according to the above, and a robot device that can improve amusement can be realized.

In the present invention, in a control method of a robot apparatus for generating an action based on an emotion model and / or an instinct model, a first step of recognizing a degree of a predetermined environmental condition, And the second step of changing the emotion model and / or the instinct model is provided, so that the emotion and / or instinct of the robot device can be changed according to the environment,
Thus, it is possible to realize a control method of a robot device that can improve amusement.

[Brief description of the drawings]

FIG. 1 is a perspective view showing a configuration of a pet robot according to the present embodiment.

FIG. 2 is a block diagram illustrating a circuit configuration of the pet robot.

FIG. 3 is a conceptual diagram showing a software configuration of a control program.

FIG. 4 is a conceptual diagram showing a software configuration of a middleware layer.

FIG. 5 is a conceptual diagram showing a software configuration of application ware.

FIG. 6 is a conceptual diagram serving to explain an action model library.

FIG. 7 is a conceptual diagram illustrating a stochastic automaton.

FIG. 8 is a chart showing a state transition table.

FIG. 9 is a conceptual diagram showing a software configuration of a middleware layer recognition system.

[Explanation of symbols]

1 ... pet robot, 10 ... CPU, 40 ... middleware layer, 41 ... application layer, 50-55, 90-92 ... signal processing module,
56 Input semantics converter module, 5
7... Recognition system, 73... Emotion model, 74... Instinct model, k _e , k _i .

──────────────────────────────────────────────────続 き Continued on the front page (51) Int.Cl. ⁷ Identification symbol FI Theme coat ゛ (Reference) 9A001 F term (Reference) 2C150 CA02 DA05 DA24 DA26 DA27 DA28 DF02 DF04 ED10 ED11 ED42 ED52 EF16 EF23 EF28 EF29 EF33 EF46 3F059 AA00 BA00 BB06 DA05 DB04 DC00 FC00 3F060 AA00 BA10 CA14 5B049 BB61 CC22 DD00 DD03 DD04 EE03 EE05 EE07 EE11 FF01 FF06 5H004 GA15 GA26 GB16 HA07 HB01 HB07 HB15 JA03 JB05 JB06 JB07 JB08 KD52 KD55 KD52 KD55 KD52 KD55

Claims (8)

[Claims] 1. A robot apparatus having an emotion model and / or an instinct model and generating an action based on the emotion model and / or the instinct model, wherein: an external sensor for detecting a degree of a predetermined environmental condition; A recognition unit that recognizes the degree of the environmental condition based on a detection result of the sensor; and a changing unit that changes the emotion model and / or the instinct model based on the recognition result of the recognition unit. Robot device. 2. The robot apparatus according to claim 1, wherein the environmental conditions are noise, temperature, illuminance, color, and / or humidity. 3. The emotion model and / or the instinct model hold parameter values respectively corresponding to a plurality of emotions or parameter values respectively corresponding to a plurality of desires, and the changing means is based on a recognition result of the recognition means. hand,
The robot apparatus according to claim 1, wherein an update rule of the parameter value of the emotion and / or the desire is changed. 4. The robot apparatus according to claim 1, wherein said changing means changes the sensitivity of the corresponding emotion and / or desire as the update rule. 5. A control method for a robot device having an emotion model and / or an instinct model and generating an action based on the emotion model and / or the instinct model, wherein a first environmental condition is recognized for a predetermined environmental condition. And a second step of changing said emotion model and / or said instinct model based on said recognition result. 6. The method according to claim 5, wherein the environmental conditions are noise, temperature, illuminance, color, and / or humidity. 7. The emotion model and / or the instinct model holds parameter values respectively corresponding to a plurality of emotions or parameter values respectively corresponding to a plurality of desires, and in the second step, based on the recognition result. 6. The method according to claim 5, wherein an updating rule of the parameter value of the emotion and / or the desire is changed. 8. The control method according to claim 5, wherein in the second step, the sensitivity of the corresponding emotion and / or desire is changed as the update rule.