JP2005202578A - Communication device and communication method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a communication device for quantitatively analyzing surrounding circumstances by using the potential energy of objective equipment or human beings to correspond to various circumstances. <P>SOLUTION: This communication device is constituted of: a distributed sensor information DB111 which stores sensor information from a plurality of sensors by correlating them to sensor classifications or attributes; a distributed environment action processing part 102 for performing recognition processing on the basis of the sensor information stored in the distributed sensor information DB; a potential energy calculating part 104 for calculating the potential energy on the basis of the recognition result of the distributed environment action processing part 102; and a communication control part 105 for performing communication control on the basis of the potential energy calculated by the potential energy calculating part 104. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

The present invention relates to a communication apparatus that integrates sensor information acquired by various distributed sensors and the like with a potential energy function to realize various communications.

  The GUI (Graphical User Interface), which operates by pointing icons and menus on the screen using a keyboard and mouse, has greatly contributed to improving production efficiency in the office. On the other hand, there is a demand for natural dialogue for humans using gestures and natural language without using a keyboard or mouse at home.

  In order to respond to this request, a system that performs a question response using a natural language, a dialogue system with a robot using a gesture, and the like have been developed (for example, see Non-Patent Document 1).

  However, in these dialogue systems, it is already decided what to speak, and it is difficult to communicate according to the situation. Further, although also techniques such as provide information services have been developed by connecting a network, such as information appliances, they are also determined whether to provide advance what services, new services by combining function There is no mechanism to create

A constructive approach to intelligent robots (Information Processing Society of Japan Vo.44, No.11, PP1118-1122)

  As described above, in a system for interactive control such as question response, there is a problem in that the content to be spoken is determined in advance and only a response with no change can be made. In addition, a fixed or is to perform also in advance what services information providing service or the like, there was no mechanism that creates the service according to the situation other than that determined like.

  The present invention solves the above problem, and an object of the present invention is to provide a communication device that can cope with various situations by quantitatively analyzing the surrounding situation using the potential energy of the target.

  In order to achieve the above object, a communication device according to the present invention includes a distributed sensor storage unit that stores sensor information from a plurality of sensors in association with sensor types and attributes, and a sensor stored in the distributed sensor storage unit. A distributed environment behavior processing unit that performs recognition processing based on information; a potential energy calculation unit that calculates potential energy based on a recognition result of the distributed environment behavior processing unit; and a potential energy that is calculated by the potential energy calculation unit. And a communication control unit for performing communication control.

  In the communication method according to the present invention, the sensor information from a plurality of sensors is stored in correspondence with the sensor type and attribute by the distributed sensor storage unit, and the sensor stored in the distributed sensor storage unit by the distributed environment action processing unit is stored. A recognition process is performed based on information, a potential energy is calculated based on a recognition result of the distributed environment behavior processing unit by a potential energy calculation unit, and communication control is performed based on the potential energy by a communication control unit. To do.

  According to the present invention, it is possible to deal with various situations by quantitatively analyzing the surrounding situation using the target device and human potential energy, and further adapts sequentially to the introduction of new sensors and devices. be able to.

Embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing a schematic configuration of a communication apparatus according to an embodiment.
The communication apparatus according to the present embodiment includes a sensor input unit 101 including a plurality of distributed sensors such as an RF (Radio Frequency) tag, an optical sensor, a microphone (hereinafter referred to as a microphone), and a camera, and a sensor input unit 101. Distributed environment action DB (DataBase) 110 that stores sensor information input from the sensor and its recognition result, and various processes such as voice recognition, image recognition, or position identification based on wireless strength for information from the sensor input unit 101 Communicates with the distributed energy behavior processing unit 102, the potential energy calculation unit 104 that calculates the potential energy based on the sensor information from the sensor input unit 101 or the information stored in the distributed environment behavior DB 110, and the communication effect time. Community to evaluate Based on the information stored in the communication evaluation unit 103, the information stored in the distributed environment behavior DB 110 and the potential energy calculated by the potential energy calculation unit 104, the communication control unit 105 that performs communication control, and the control of the communication control unit 105 A communication generation unit 106 that generates a communication to be presented to the user, an expression media conversion unit 107 that converts a generation result of the communication generation unit 106 into media that can be presented by the robot, and a conversion result of the expression media conversion unit 107 are presented. The communication presentation part 108 is comprised.

  FIG. 2 shows a state in which a plurality of sensor input units 101 are installed in the home. There are various sensors such as smoke sensors, temperature sensors, strain sensors, pressure sensors, etc. installed in homes. Here, only position sensors, cameras, and microphones using RF tags and optical sensors used for explanation are used. It is written.

  For example, in the bathroom on the first floor, there is a watching robot A (201), in the living room on the second floor, there is a robot B (202) as a talking partner, and on the outside there is a robot C (203) serving as a watchdog. These robots A to C (201 to 203) are provided with various sensors such as an ultrasonic sensor and an infrared sensor for detecting an obstacle necessary for movement. Only such sensors are shown.

  Each robot has a camera (video camera) 2012 for identifying the situation such as whether it is a human face, personal authentication with a recognized face, detection of face orientation, or whether there is a moving object. 2022 and 2032 are attached. The cameras 2012, 2022, and 2032 need not all be the same standard. For example, since the robot C201 is intended for monitoring, the camera 2032 is an infrared camera that can be used at night, or a high-speed shooting camera that can shoot at 60 frames / second or more for distinguishing moving objects moving at high speed. It is also possible to use it (a normal camera has about 30 frames / second). In addition, since robot A (201) and robot B (203) are for the purpose of interacting with humans, a stereotype camera (two eyes) is used to distinguish distances, and by using two eyes, the corresponding humans can see. Because it is a dialogue between the two eyes, there are times when it can be relieved. Alternatively, when a lullaby is a role like the robot A201, it corresponds to a child, so a water-resistant camera or the like may be used. One robot has a plurality of cameras. For example, since it has high illuminance during the daytime, it can be used as an ordinary camera, and at night, it can be used as an infrared camera. Further, the resolution of the camera can be properly used for each robot, such as a high resolution camera or a low resolution camera. In order to save power, a surveillance camera or the like that captures an image only when there is movement may be used in combination with an infrared sensor or the like. Such proper use is the same for the camera 1011 -B and the camera 1013 -B installed in the home room.

  For example, the result captured by the camera 1013 -A installed in the living room is stored as sensor information from the sensor input unit 101 in the distributed sensor information DB 111 of the distributed environment behavior DB 110 that is stored together with the accuracy of the sensor. The information format stored in the distributed sensor information DB 111 is as shown in FIG.

  For all cameras, microphones, and other sensors, this is necessary when referring to a unique sensor ID (such as a machine (MAC) address), sensor name, sensor performance, or function. , The location where the sensor is installed, the type of data acquired by the sensor, the dimension of the data, the accuracy of the data, the sampling rate for sensor data acquisition, the recording start date and time, the unit of the acquired data, and the label of the acquired data are described at the beginning Has been. The accuracy of data and the unit of data are described according to the dimension of the data.

  Next, the data body is described in the part between <body> and </ body>. In this case, the data captured by the camera is, for example, image data of 30 frames / second. In the case of a normal video camera, the image is two-dimensional data of 640 pixels × 480 pixels. However, since one frame is a single unit, the data dimension is one dimension and the sampling rate is 1/30. Each data is a file compressed by MPEG2 (Motion Picture Expert Group) as described in <body>, for example, and the file name and the time stamp at the end of each file are described. ing.

  Here, for example, it is stored as an MPEG2 file, but it is not necessarily limited to this. For example, there are various moving image compatible formats such as Motion JPEG, JPEG2000, avi, MPEG1, MPEG4, and DV, and any format can be applied.

  By the way, since the accuracy is one-dimensional, only <accurate-x> is described, and is 1.0 here. That is, it shows that the image is being taken in the state when the camera is set. This accuracy is less than 1.0 when the camera cannot capture images with the performance of the catalog value, such as when the illumination is insufficient but the flash cannot be used, direct sunlight falls directly into the backlight, or charging is insufficient. It becomes.

  In addition, the robots A to C (201 to 203) are provided with microphones 2013, 2023, and 2033 for personal identification with a human voice or for identifying the situation such as the presence of a moving object. As with the camera, there is no need to use the same standard microphone.

For example, only a certain range of sounds may be collected by using a microphone array with enhanced directivity by using two microphones. Alternatively, in order to save power, it is also possible to use a sound collection microphone that collects sound only when there is movement in combination with an infrared sensor or the like. Such proper use is the same for the microphone 1011 -C and the microphone 1013 -C installed in the home room.

  For example, the result of sound collection by the microphone 1013 -C installed in the living room is stored as sensor information from the sensor input unit 101 in the distributed sensor information DB 111 in the distributed environment action DB 110 that is stored together with the accuracy of the sensor. The information format stored in the distributed sensor information DB 111 is as shown in FIG.

  The information format of FIG. 4 is the same as the information format of FIG. The difference is that in the case of the above-described camera, although it was an MPEG file or the like, here it is in the wav format which is the format of the sound data. As an example, the wav format is used, but it is not necessarily limited to this. For example, any format such as MPEG format (MP3) may be used as in the case of moving images.

  Since the accuracy is one-dimensional, only <accurate-x> is described, and is 1.0 here. In other words, it indicates that sound is being collected when the microphone is set. This accuracy is a value smaller than 1.0 when the microphone cannot capture images with the performance as in the catalog value, such as insufficient charging.

  As sensors, position sensors 1011 -A, 1012 -A, and 1013 -A are installed in FIG. 2 in addition to the camera and the microphone. There are various types of position sensors. Here, for example, the robots A to C (201 to 203) or the humans A to D have radio tags such as RFID, and the position sensor 1011- A, 1012-A, and 1013-A detect. There are an active method for emitting radio waves to the wireless tag and a passive method for generating radio waves by electromagnetic induction when the radio tag approaches the gate of the position sensor without emitting radio waves by itself. Here, it is assumed that each of the robots A to C (201 to 203) or the humans A to D wears an active wireless tag. In the case of a human being, for example, if a wireless tag is attached to indoor wear, the person is not conscious of wearing it and does not feel burdened. However, since indoor footwear may not necessarily be worn, in that case, the human position certainty is a value lower than 1.0.

  The result detected by the position sensor 1013 -A in the living room is accumulated as sensor information from the sensor input unit 101 in the distributed sensor information DB 111 of the distributed environment behavior DB 110 that is accumulated together with the accuracy of the sensor. The information format stored in the distributed sensor information DB 111 is as shown in FIG.

  The information format of FIG. 5 is almost the same as the information format of FIG. 3 or FIG. The difference is that the data is two-dimensional, and that the data is not as large as a sound or an image, so it is described directly in <body>.

  There are two types of data: the number of the wireless tag that detected the radio wave and the radio wave intensity at that time. In order to make the wireless tag number easy to understand, the wireless tag number assigned by human A is described as “XXX human A”, and the wireless tag number provided by robot B (202) is described as “XXX robot B”. doing. One radio wave intensity is a value obtained by normalizing the radio wave intensity acquired by the position sensor in 256 levels from 0 to 255. However, the radio wave intensity representing 255 is the strongest and exists in the nearest place, and the lower the value, the farther away. Since the radio wave intensity is inversely proportional to the square of the distance, the 256 levels are not linear, and the range is narrower as the value is larger, and the wider range is included as the value is smaller.

  As shown in FIG. 2, when there are humans A to C, the robot B (202), and a plurality of wireless tags in the living room, the position sensor 1013-A does not detect all the wireless tags at the same time, but sequentially detects them. ing. Therefore, as shown in FIG. 5, the detected results are described in time series. In this case, since the human B and the human C are located far from the position sensor 1013-A, the radio waves do not necessarily reach because the radio waves are weak. Therefore, it may not be detected, and as shown in FIG. 5, the number of times human A or robot B (202) is detected is larger. In some cases, the robot C (203) outside may be detected as shown in FIG. Therefore, the accuracy with respect to the detected wireless tag ID is 1.0 or less. Here, the accuracy of this sensor is 0.8.

  For example, when the wireless tag has a communication distance of 10 m in the catalog, it can be detected at least 10 m. The minimum 10 m means that radio waves reach 10 m or more, and there are cases where detection is practically possible up to 40 m. Furthermore, in practice, there are individual differences in the distance that radio waves reach such as the direction of antenna attachment. Therefore, the range of the y-axis (second data of the two-dimensional data) is, for example, 8 to 40 m. The minimum of 8 m indicates that even if 10 m is the minimum, the minimum is 8 m in the data measured when the living room was actually installed.

Radio wave intensity I is

k is a distance with a coefficient r. In this case, the radio wave intensity I has 256 levels.
Further, the position sensor is assumed to have a distance accuracy of 0.6 here in consideration of fluctuations in the way radio waves reach depending on the temperature and the number of people in the room.
Here, although not particularly mentioned, other sensor information is also stored in the distributed sensor information DB 111 as in FIGS.
The distributed environment behavior processing unit 102 sequentially reads information stored in the distributed sensor information DB 111, divides the information into human and thing information, performs appropriate recognition processing, and based on the accuracy of the sensor information, the potential energy calculation unit In addition to the calculated potential energy of 104, the position and posture related to the object, the state of the object (moving, etc.) in the distributed environment information DB 112, the basic movement information such as the position and posture related to humans, walking and rest Write to the distributed state information DB 113.

  Further, the information of the distributed sensor information DB 111, the distributed state information DB 112, and the distributed state information DB 113 is read out, and appropriate recognition processing is performed. Based on the read sensor accuracy and potential energy, the potential energy calculated by the potential energy calculation unit 104 and In addition, actions such as sleeping, eating, watching TV, bathing, cooking, etc. are written in the distributed action information DB 114.

  Further, the information of the distributed sensor information DB 111, the distributed state information DB 112, the distributed state information DB 113, and the distributed behavior information DB 114 is read out, and appropriate recognition processing is performed. Based on the read sensor accuracy and potential energy, the potential energy calculation unit 104 In combination with the calculated potential energy, for example, when a human is watching TV, the fact that the human is using the TV service is stored in the interaction DB 115 of the human and the service. The relationship between things is written in the interaction DB 116 between people and things, and the relationship between people such as a family talking is written in the interaction DB 117.

  Hereinafter, how to edit the distributed environment behavior DB 110 while calculating the potential energy based on the distributed sensor information illustrated in FIGS. 3, 4, and 5 will be described. As shown in FIG. 6, the distributed environment behavior processing unit 102 recognizes whether or not a person is an resident, a personal authentication unit 1021, a motion recognition unit 1024 for recognizing the motion, and a behavior recognition. Action recognition unit 1045, a situation recognition unit 1046 for recognizing a situation, an environment recognition unit 1047 for recognizing an environment such as an object or a service, and an image recognition unit for performing recognition processing based on these 1022 and a voice recognition unit 1023.

From FIG. 5, it can be seen that human A, human B, and robot B (202) are detected by the position sensor.
"XXX Human A 200"
"XXX Human B
Ten"
"XXX Robo B 100"
Based on this information, the potential energy calculation unit 104 calculates potential energy.
The potential energy is

It is expressed.
F is a potential energy function, an appropriate function is selected, x, y, z are coordinate values in a three-dimensional space, θ, φ, γ are angles (yaw, row, pitch) indicating postures, and t is a time , Prn are N parameters representing the user's preferences and hobbies (the number is N for convenience of formulation, but is not limited thereto).

There are several forms of potential energy function.
For example, whether or not it exists at a certain point can be regarded as a binomial distribution. The occurrence probability p existing at a certain point is extremely small, but if there are n points at a certain point in terms of the lifetime of a human being, it becomes sufficiently large and np becomes finite.

np = λ
The binomial distribution is a Poisson distribution as a probability function.

  here,

  and

  Therefore, when expressed as a Poisson distribution function centered on the position detected by the position sensor, the potential energy converted into the coordinate value in the room is calculated based on the position of the sensor as shown in FIG. Can do. The Poisson distribution function shown in FIG. 7 has a three-dimensional shape.

  Alternatively, as shown in FIG.

It is also possible to express.
In order to improve comprehension in both FIG. 7 and FIG. 8, only the coordinate values of x and y are used and displayed in a three-dimensional space (coordinate value 2 degrees of freedom). As shown in the above, the function is an N + 8-dimensional space (coordinate value 3 degrees of freedom, posture 3 degrees of freedom, time 1 degree of freedom, profile N degrees of freedom).

  Similarly to humans and robots, devices such as TVs and washing machines have potential energy. For example, although the TV speaker 2032 presents a sound, the sound spreads in all directions without directivity, so that its potential energy is a sphere indicated by a dotted line as shown in FIG.

  Here, since the TV has two speakers, the potential energy is represented by two spheres. On the other hand, the TV screen 2031 presents video and has a viewing angle, so it is not omnidirectional. Here, it is treated as an electromagnetic field radiation pattern having directivity (the chain line in FIG. 9).

FIG. 10 shows the potential energy calculated for the human or the robot and the potential energy calculated for the device.
The communication control unit 105, calculates the potential energy F _p for human and robot, overlap between the potential energy F _a related equipment (inner product).

  The inner product between the human and the device is

  The inner product between humans is

It is represented by
Hereinafter, how the communication control unit 105 and the communication evaluation unit 103 operate based on the inner product will be described. The flow of processing will be described with reference to FIG.

  Step S101 calculates the potential energy described above. Next, the calculated number of potential energies is determined and set to human Np and device Na, respectively (step S102).

  Next, the inner product of potential energies is calculated for all the calculated humans and devices, and processing is performed on human i, device j, and another human k other than human i so that control and evaluation can be performed. Each parameter is initialized in step S103. Since i and j are 1 and k is other than i, i + 1 is set.

The inner product ijC _tl between the potential energy of the human i and the device j is calculated (step S104). The calculation of the inner product is as described above. If the calculated inner product ijC _{tl of} the human i and the device j is positive, communication occurs between the human i and the device j, so a determination is first made in step S105.

If the result is positive in S105, the inner product value ijC _tl (the inner product at the time of tl of the human i and the device j) at that time tl is stored for later communication evaluation (step S106). If it is positive, communication occurs between the human i and the device j. For this purpose, the device j service needs to be turned on. Whether or not it is ON is determined in step S107.

Stores ijT _on = tl when the service is turned _on when the device j service is turned _on , in order to send the communication evaluation between the human i and the device j service when and in what state the communication started. (Step S108).

In order to calculate the inner product for all the device j services, increment until j becomes Na (steps S109 and S110).
If the person has already lost interest in the service or moved to another location, the inner product becomes zero or the inner product becomes smaller. When moving to another location and the inner product becomes 0, it is necessary to terminate the service in order to prevent the TV from staying on when there is no user.

That is, if the device j service is ON (step S107), it is calculated in step S115 whether the inner product has changed from the previous time.
In other words, the difference between the current and the inner product value _{ijC tl} and the last of the inner product value _{ijC tl-1} at the time of _{tl ijE tl = ijC tl -ijC tl} -1
Take.
The difference ijE _tl is first stored as an effect on the human i of the device j service in step S116. In step S117, it is checked whether ijE _tl <0. If ijE _tl is 0 or less, it means that the user has moved to another place or lost interest, so the device j service is turned off (step S118). Further, the time when the service is turned _off is stored as ijT _off = tl when the service is turned _off .

Next, the service effect time ijT _off -ijT _on of the device j service is calculated and stored as one index for calculating how much the device j service is effective for the user i (step S119).

With the above method, the service can be turned off when the user disappears.
Alternatively, instead of determining whether the inner product difference ijE _tl is equal to or smaller than 0, the service level may be changed when the difference is equal to or smaller than a preset threshold value. In that case, before step S117, as shown in FIG. 12, it is determined whether ijE _tl <α in step S127.

As a result, when the threshold value falls below a preset threshold value, the level of the device j service is reduced to one paragraph (step S128), for example, the sound of the TV can be reduced.

As described above, we have explained what is based on the inner product of potential energy between humans and machines. Similarly, we calculate the inner product of potential energy for humans and store the changes to record the communication history. can do.

In step S111, an inner product ikC _tl between potential energies of human i and human k is calculated. It is determined whether or not the inner product ikC _tl of the human i and the human k is positive (step S112), and if it is positive, it means that there is communication, so that the inner product value ikC _tl at the time of the current tl Is stored (step S120).

If the previous inner product ikC _tl-1 is 0 (step S121), it can be determined that communication has started at tl, so ikT _on at the start of communication is stored as tl (step S122).

Like the communication between humans and machines, taking the current differential _{ikE tl = ikC tl -ikC tl-} 1 with the inner product value _{IKC tl} and the last inner product value _{IKC tl-1} at the time tl (step S123).

ikE _tl is stored as an effect on the human i of the device j service (step S124).
If the difference ikE _tl becomes 0, it can be considered that the communication has ended (step S125), so the communication effect time tl-ikT _on between the human i and k is calculated and stored (step S126). The above is repeated for all humans.

Based on the above communication effect time, the communication evaluation unit 103 performs evaluation.
In the case of FIG. 1, there is one person in front of the TV. In this case, the TV service effect time stored in the communication evaluation unit 103 is, for example,
Te = ijT _off -ijT _on
And
On the other hand, for example, as shown in FIG. 13, when there are two people in front of the TV, the TV service effect time stored in the communication evaluation unit 103 is apparent,

Te = (ijT _off −ijT _on ) + (kjT _off −kjT _on )

It will be almost twice as effective.
In addition, communication effect time between humans Ce = tl-ikT _on
So, the total effect time is Total = Te + Ce
It becomes.
Based on this result, for example, the communication control unit will be described performing control for increasing the effect time. When the communication evaluation unit 103 determines that the service effect time or the communication effect time is short, another family recognized by the distributed environment behavior processing unit 102 in order to increase the effect time in the communication control unit 105 (For example, human A) is controlled to call. For example, the communication generation unit 106 generates voice information that calls the family, performs speech synthesis that can be output by a robot (for example, robot B) by the conversion unit 107 using expression media, and calls the family using a speaker provided in the robot. Can do.

  Therefore, by analyzing the surrounding situation quantitatively using the potential energy of the target device or human being from the above configuration, it is possible to cope with various situations and further adapt sequentially to the introduction of new sensors and devices. Can do.

The block diagram which shows schematic structure of the communication apparatus of embodiment of this invention. The implementation outline figure of embodiment of this invention. The figure which shows the example of a description of the distributed sensor information DB of a camera. The figure which shows the example of description of the dispersion | distribution sensor information DB of a microphone. The figure which shows the example of description of the distributed sensor information DB of a position sensor. The block diagram which shows the detailed structure of a distributed environment action process part. The figure which shows the example of the calculated potential energy. The figure which shows the example of the calculated potential energy. The figure which shows the example of the calculated potential energy. The figure which shows the example of the calculated potential energy. The processing flow figure of a communication evaluation part. The processing flow figure of a communication evaluation part. The other implementation outline figure of embodiment of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 101 ... Sensor input part 102 ... Distributed environment action processing part 103 ... Communication evaluation part 104 ... Position energy calculation part 105 ... Communication control part 106 ... Communication generation part 107 ... Expression Media conversion unit 108 ... communication presentation unit 110 ... distributed environment action DB
111 ... distributed sensor information DB
112 ... Distributed state information DB (thing)
113 ... Distributed state information DB (human)
114 ... distributed action information DB
115 ... Interaction DB of people and services
116 ... Interaction DB of people and things
117 ... Human-human interaction DB
1011-A, 1012-A, 1013-A ... Position sensors 1011-B, 1013-B ... Cameras 1011-C, 1013-C ... Microphone 1021 ... Personal authentication unit 1022 ... Image Recognition unit 1023 ... Voice recognition unit 1024 ... Motion recognition unit 1025 ... Action recognition unit 1026 ... Situation recognition unit 1027 ... Environment recognition units 201, 202, 203 ... Robots 2011, 2021, 2031 ... Speakers 2012, 2022, 2032 ... Cameras 2013, 2023, 2033 ... Microphone 204 ... TV
2041 ... TV screen 2042 ... TV speaker

Claims (6)

  A distributed sensor storage unit that stores sensor information from a plurality of sensors in association with sensor types and attributes, a distributed environment behavior processing unit that performs recognition processing based on sensor information stored in the distributed sensor storage unit, and the distributed A potential energy calculation unit that calculates potential energy based on a recognition result of an environmental action processing unit, and a communication control unit that performs communication control based on the potential energy calculated by the potential energy calculation unit, Communication device.   The communication device according to claim 1, wherein the potential energy calculation unit calculates the potential energy of a target detected as a recognition result of the distributed environment action processing unit.   The communication control unit performs communication control based on an inner product value of the potential energy of the first target detected as the recognition result of the distributed environment action processing unit and the potential energy of the second target detected as the recognition result. The communication device according to claim 1, wherein:   The communication according to claim 3, further comprising a communication evaluation unit that evaluates a control effect of the communication control unit based on a time difference between inner potential values of potential energy of the first object and the second object. apparatus.   The communication apparatus according to claim 4, wherein the communication control is performed based on an evaluation result of the communication evaluation unit.   Sensor information from a plurality of sensors is stored in correspondence with sensor types and attributes by the distributed sensor storage unit, and recognition processing is performed based on the sensor information stored in the distributed sensor storage unit by the distributed environment behavior processing unit. A communication method, wherein a calculation unit calculates potential energy based on a recognition result of the distributed environment action processing unit, and a communication control unit performs communication control based on the position energy.

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