JP4793904B2 - Communication robot system and communication robot - Google Patents

Description

  The present invention relates to a communication robot system and a communication robot, and more particularly to a communication robot system and a communication robot in which a robot performs communication behavior with a human.

  An example of a conventional device related to the degree of congestion is disclosed in Patent Documents 1 and 2.

  In Patent Document 1, an object region is extracted from the three-dimensional information of the monitoring space and the three-dimensional information of the plane set in the monitoring space, and the congestion degree of the monitoring space is measured based on the object region.

Further, in Patent Document 2, the robot recognizes a moving object and moves from the direction of light flow caused by the movement of the robot.
JP 2001-34883 A JP 2003-317103 A

  As in the technology of Patent Document 1, there has been an apparatus that only measures the degree of congestion of a human or the like. In addition, as in the technique of Patent Document 2, there is a robot that moves around avoiding humans by recognizing the degree of congestion in the surrounding area.

  However, there has been no system in which surrounding information such as the detected congestion level is connected to the robot via a network, and the robot acts on humans according to the congestion level.

  Therefore, the main object of the present invention is to provide a novel communication robot.

  Another object of the present invention is to provide a communication robot system and a communication robot that can work on humans according to the degree of congestion around them.

The invention of claim 1 determines a communication behavior of a communication robot based on a detection result of a communication robot that executes a communication behavior with a human, a congestion degree identifying means for identifying a surrounding congestion degree, and a congestion degree identifying means. The communication action determining means is a communication robot system that determines an action for reducing congestion as a communication action when the congestion degree identifying means identifies “congestion” .
The invention according to claim 2 determines a communication behavior of a communication robot based on a detection result of a communication robot that executes communication behavior with a human, a congestion degree identifying unit that identifies the degree of congestion around, and a congestion degree identifying unit The communication behavior determination means is a communication robot system that determines an action of collecting humans as a communication action when the congestion degree identification means identifies “sparse”.

In the first and second aspects of the present invention, the communication robot system (10: reference numeral corresponding to the embodiment; the same applies hereinafter) includes the communication robot (12), the congestion degree identifying means (100, S9), and the communication action determination. Means (52, S23, S27).

  The congestion degree identifying means (100, S9) identifies the degree of congestion around the communication robot (12), and the communication robot (12) communicates based on the degree of congestion detected by the communication action determining means (52, S23, S27). The behavior is determined, and the communication robot (12) executes the communication behavior with the human based on the behavior.

As in the first aspect of the invention, when the congestion degree identifying means determines that there are many people around the communication robot and the degree of congestion is high, the communication action determining means is dangerous because people are pressed against each other. Determine communication behaviors that guide people to move to places . Conversely, if it is determined that there is less congestion have vacant around the communication robot, as the invention of claim 2, communication behavior determining means, communication behavior so as to induce human to gather around To decide.

The invention according to claim 3, congestion identifying means includes a noise detecting means for detecting an ambient noise level, identifying congestion degree based on the noise level detected by the noise detecting means, according to claim 1 or 2, wherein It is a communication robot system.

According to the third aspect of the present invention, the ambient noise level is captured by the noise detection means (100, S7), and the ambient noise level of the communication robot (12) is acquired based on the captured noise level. Then, the congestion degree identifying means (100, S9) identifies the congestion degree around the communication robot (12) based on the congestion degree identifying means (100, S9).

  Thus, since a certain degree of congestion can be grasped from the noise level, the degree of congestion around the communication robot can be easily identified.

The invention of claim 4 further includes a plurality of sound level meters each outputting a noise level at the installation location and distributed in the environment, and the noise detecting means is a sound level meter within a certain distance around the communication robot. The communication robot system according to claim 3 , wherein the noise level is detected by acquiring the noise level.

According to the invention of claim 4 , a plurality of sound level meters (114) are provided dispersed in the environment, and the sound level meter (114) detects the noise level at the installation location and outputs it to the noise detection means (100, S7). . The noise detection means (100, S7) acquires the noise level from the sound level meter (114) within a certain distance around the communication robot (12), thereby detecting the noise level around the communication robot (12).

Thus, by using only the sound level meter around the communication robot, the noise level around the communication robot can be accurately detected .

The invention of claim 5 is a communication robot that executes communication behavior with a human being, and a congestion degree identifying means for identifying a surrounding congestion degree, and
Communication behavior determining means for determining communication behavior based on the detection result of the congestion degree identifying means, and the communication behavior determining means alleviates congestion as communication behavior when the congestion degree identifying means identifies “congestion”. A communication robot that determines behavior.
The invention according to claim 6 is a communication robot that performs communication behavior with a human being, and determines a communication behavior based on a congestion degree identifying means for identifying a surrounding congestion degree and a detection result of the congestion degree identifying means. The communication action determining means is a communication robot that determines an action of collecting humans as a communication action when the congestion degree identifying means identifies that it is “sparse” .

In the invention of claim 5 and claim 6 , the communication robot (12) includes a congestion degree identifying means (52, S47) and a communication action determining means (52, S49, S53). The congestion degree identifying means (52, S47) identifies the degree of congestion around the communication robot (12), and the communication behavior determining means (52, S49, S53) determines the communication behavior based on the detection result of the congestion degree identifying means. Then, the communication robot (12) executes the determined communication behavior with the human.
In the invention of claim 5, when the congestion degree identifying means determines that the congestion degree is high, the communication action determining means determines a communication action that reduces congestion such as guiding a person to move to another place. To do. On the other hand, when it is determined that the communication robot is free and the degree of congestion is low, the communication action determining means determines the communication action for gathering humans.

The invention of claim 7, further comprising a noise detecting means for detecting an ambient noise level, congestion identification means for identifying the degree of congestion on the basis of the noise level detected by the noise detecting means, according to claim 5 or 6, wherein It is a communication robot.

In the invention of claim 7, the communication robot (12) includes a noise detection means (30) for detecting a noise level around the communication robot (12), and the congestion degree identification means (52, S47) is a noise detection means (30). ) Identifies the degree of congestion based on the detected noise level .

  According to the present invention, by determining the communication behavior of the communication robot based on the degree of congestion around the communication robot, the communication robot can make a person act according to the surrounding situation.

  The above object, other objects, features and advantages of the present invention will become more apparent from the following detailed description of embodiments with reference to the drawings.

  Referring to FIG. 1, a communication robot system (hereinafter simply referred to as “system”) 10 of this embodiment is a communication robot (hereinafter simply referred to as “robot”) 12, a server 100, an infrared camera system 112, and noise. A computer 116 having a total of 114 is included, each connected via a network 118.

  As shown in FIG. 2, the robot 12 has a human-like body and is, for example, an interaction-oriented one for the purpose of communicating with a communication target such as a human being. A function of performing communication behavior (hereinafter, also referred to as “communication behavior”) using at least one of (voice).

  The robot 12 includes a carriage 14, and wheels 16 for autonomously moving the robot 12 are provided on the lower surface of the carriage 14. The wheel 16 is driven by a wheel motor (indicated by reference numeral “74” in FIG. 3 showing the internal configuration of the robot 12), and moves the carriage 14, that is, the robot 12 in any direction, front, rear, left, and right.

  Although not shown in FIG. 2, a collision sensor (indicated by reference numeral “82” in FIG. 3) is attached to the front surface of the carriage 14, and the collision sensor 82 detects contact of a person or other obstacle to the carriage 14. Detect. When contact with an obstacle is detected during the movement of the robot 12, the driving of the wheels 16 is immediately stopped and the movement of the robot 12 is suddenly stopped.

  A polygonal column sensor mounting panel 18 is provided on the carriage 14, and an ultrasonic distance sensor 20 is mounted on each surface of the sensor mounting panel 18. The ultrasonic distance sensor 20 measures the distance between the mounting panel 18, that is, the person mainly around the robot 12.

  In addition to the sensor mounting panel 18, the bodies 22 and 24 of the robot 12 are also mounted on the carriage 14. The body bodies 22 and 24 stand upright, and the lower part thereof is surrounded by the sensor mounting panel 18. The body is composed of a lower body 22 and an upper body 24, which are connected by a connecting portion 26. The connecting portion 26 includes a lifting mechanism (not shown), and the height of the upper body 24, that is, the height of the robot 12 can be changed by using the lifting mechanism. The lifting mechanism is driven by a waist motor (indicated by reference numeral “72” in FIG. 3) as will be described later.

  One omnidirectional camera 28 and one microphone 30 are provided in the approximate center of the upper body 24. The omnidirectional camera 28 is a camera that uses a solid-state image sensor such as a CCD or a CMOS, for example, and images the surroundings of the robot 12. The microphone 30 captures ambient sounds, particularly human voice.

  Shoulder joints 32R and 32L are attached to both shoulders of the upper body 24, and upper arms 34R and 34L are connected to the shoulder joints 32R and 32L. The shoulder joint 32R controls the angle of the upper arm 34R around the X, Y, and Z axes orthogonal to each other, and the shoulder joint 32L adjusts the angle of the upper arm 34L to each of the A, B, and C axes that are orthogonal to each other. Control around the axis.

  Forearms 38R and 38L are attached to the tips of upper arms 34R and 34L via elbow joints 36R and 36L, respectively. The elbow joints 36R and 36L control the angles of the forearms 38R and 38L around the W axis and the D axis.

  Although not shown in FIG. 2, touch sensors (generally indicated by reference numeral 80 in FIG. 3) are provided on shoulder joints 32R and 32L, upper arms 34R and 34L, and forearms 38R and 38L of upper body 24, respectively. . The touch sensor 80 detects whether a person has touched these parts of the robot 12.

  Spheres 40R and 40L corresponding to hands are fixedly attached to the tips of the forearms 38R and 38L, respectively. However, when a finger function (gripping, grasping, picking, etc.) is required, a “hand” in the shape of a human hand can be used instead of the spheres 40R and 40L.

  A head 44 is attached to a central upper portion of the upper body 24 via a neck joint 42. The neck joint 42 has three degrees of freedom orthogonal to each other, the S axis, the T axis, and the U axis, and controls the angle around each axis. A speaker 46 is provided at a position corresponding to the human mouth of the head 44. The speaker 46 is used for the robot 12 to communicate with surrounding people by voice or voice. However, the speaker 46 may be provided in another part of the robot 12, for example, the trunk.

  In addition, eyeball portions 48R and 48L are provided at positions corresponding to the eyes of the head 44, and eye cameras 50R and 50L are fixed in the eyeball portions 48R and 48L, respectively. The eyeball portions 48R and 48L are attached to predetermined positions in the head 44 via an eyeball support portion (not shown), and the eyeball support portion has two degrees of freedom orthogonal to each other, α axis and β axis, Angle control around each axis. The eye cameras 50R and 50L are cameras that use a solid-state image sensor such as a CCD or a CMOS.

  FIG. 3 is a block diagram showing the internal configuration of the robot 12. The robot 12 includes a microcomputer or CPU 52 for overall control. The CPU 52 is connected to a memory 56, a motor control board 58, a sensor input / output board 60, a voice input / output board 62, and a communication LAN board 64 through a bus 54. Is done.

  The memory 56 includes a ROM, an HDD, a RAM, and the like (not shown). A program (called an action module), data, and the like for controlling the body movement of the robot 12 are stored in advance in the ROM or HDD, and the CPU 52 executes processing according to this program. The RAM can be used as a temporary storage memory and a working memory.

  The motor control board 58 is configured by a DSP (Digital Signal Processor), for example, and controls a motor for driving a body part such as an arm or a head. That is, as shown in FIGS. 2 and 3, the motor control board 58 receives control data from the CPU 52 and adjusts the right arm motor 66 that controls the angles of the right shoulder joint 32R and the right elbow joint 36R. The motor control board 58 adjusts the left arm motor 68 that controls the left shoulder joint 32L and the left elbow joint 36L. The motor control board 58 further includes a head motor 70 that controls the angle of the neck joint 42, a waist motor 72 that drives the lifting mechanism, a wheel motor 74 that drives the wheel 16, and a right eyeball motor that controls the angle of the right eyeball portion 48R. 76 and a left eyeball motor 78 that controls the angle of the left eyeball portion 48L.

  Each of the above-described motors of this embodiment is a stepping motor or a pulse motor to simplify the control except for the wheel motor 74, but may be a DC motor similarly to the wheel motor 74.

  The sensor input / output board 60 is also constituted by a DSP, and takes in signals from each sensor and camera and gives them to the CPU 52. That is, data relating to the reflection time from each ultrasonic distance sensor 20, video signals from the omnidirectional camera 28 and the eye cameras 50R and 50L, and signals from the touch sensor 80 and the collision sensor 82 are transmitted through the sensor input / output board 60. Input to the CPU 52.

  The synthesized voice data is given from the CPU 52 to the speaker 46 via the voice input / output board 62, and voice or voice according to the data is output from the speaker 46. Also, the voice input from the microphone 30 is taken into the CPU 52 via the voice input / output board 62.

  The communication LAN board 64 is also constituted by a DSP. The communication LAN board 64 gives the transmission data given from the CPU 52 to the wireless communication device 84 and causes the wireless communication device 84 to send the transmission data. The communication LAN board 64 receives data via the wireless communication device 84 and provides the received data to the CPU 52.

  The infrared camera system 112 shown in FIG. 1 includes an infrared camera system 112 and a computer (not shown) such as a PC or WS, and this computer is connected to the server 100 via a network 118.

  As shown in FIG. 4, for example, the two infrared camera systems 112 are arranged in different directions with respect to the robot 12 with an interval between them on the ceiling of the target space 120 where the robot 12 exists. Thus, the distance to the robot is calculated using the principle of triangulation, and the position (coordinate data) of the robot 12 is obtained. Then, the computer of the infrared camera system 112 transmits the position of the robot 12 to the server 100 in response to a request from the server 100.

  Further, at least one sound level meter 114 shown in FIG. 1 is connected to the computer 116, and the computer 116 is connected to the server 100 via the network 118. As shown in FIG. 4, in this embodiment, eight sound level meters 114a, 114b... 114h (collectively referred to as 114) are provided in a distributed manner in the environment of the target space 120 where the robot 12 exists. The sound level meters 114 are arranged, for example, at intervals over the entire ceiling of the target space 120, and their positions are recorded in the server 100 in advance. The sound level meter 114 measures the noise level at the installation location, and outputs the noise level measured by the computer 116 connected to the sound level meter 114 to the server 100 in response to a request from the server 100.

  Specifically, when a person is around the sound level meter 114, the sound level meter 114 picks up a sound caused by the person and measures the noise level. As shown in FIG. 5 showing the results obtained by the inventors' experiments, the noise level (dB) generally increases as the number of humans (total number of people) increases. The degree of human congestion can be grasped to some extent. Using this, the noise level is measured by the noise meter 114 existing around the robot 12, and the degree of congestion around the robot 12 is acquired from the noise level. The robot 12 communicates with humans based on the degree of congestion around the robot 12.

  That is, the server 100 acquires coordinate data transmitted from the infrared camera system 112 and acquires the position of the robot 12. Next, the sound level meter 114 existing within a certain distance L centering on the position of the robot 12 is selected, and the noise level of the sound level meter 114 is acquired from the computer 116 connected to the sound level meter 114. Then, the degree of congestion around the robot 12 is identified from the noise level, and the robot 12 is caused to execute a communication action according to the degree of congestion around the robot 12. The fixed distance L is appropriately determined depending on the number and position of the sound level meters 114.

  The server 100 processes this communication action according to the flowchart shown in FIG. When the server 100 starts the process of communication behavior, in step S1, the robot 12, for example, by the utterance as "Hello", and / or by operating such as raising the arm, pay attention to the robot 12 with respect to human beings. Depending on the behavior of the robot 12, a person around the robot 12 may say “Oh, it is a robot 12”, or a person away from the robot 12 may notice the robot 12 and gather around the robot 12. Therefore, sounds accompanying human voices and actions are generated.

  At this time, it is determined whether or not the robot 12 is speaking in step S3, and if it is speaking, “YES” is determined and the process returns to step S3 and waits until the utterance ends. If the speech is not being spoken and “NO”, the main source of the sound generated around the robot 12 is a human.

  Therefore, the position of the robot 12 in the target space 120 is acquired from the coordinate data transmitted from the infrared camera system 112 in step S5. In step S 7, the noise level is acquired from the sound level meter 114 existing within a certain range around the robot 12. For example, in FIG. 4, for example, three sound level meters 114 b, 114 c, and 114 e that are in a circle having a constant distance (radius) L around the position of the robot 12 are selected. The noise levels Nb, Nc, and Ne around the sound level meters 114b, 114c, and 114e are measured by the sound level meters 114b, 114c, and 114e, and the noise level N around the robot 12 is calculated from the noise levels Nb, Nc, and Ne. To do. For the calculation, the noise level N around the robot 12 is obtained from the noise level Nb, Nc, Ne of each sound level meter 114b, 114c, and 114e and the ratio of the distance, using, for example, Equation 1. The ratio of the distances between the sound level meters 114b, 114c, and 114e is based on the distances Lb, Lc, and Le from the noise level meters 114b, 114c, and 114e to the robot 12. The sound level meter 114c is (Lc / Lb + Lc + Le), and the sound level meter 114e is (Le / Lb + Lc + Le).

  Next, in step S9 shown in FIG. 6, the noise level N around the robot 12 is applied to the noise level-congestion degree table, and the current congestion degree around the robot 12 is checked. For example, the noise level N around the robot 12 calculated above is compared with the noise level in the noise level-congestion degree table shown in FIG. 7, and if the noise level N is equal to or greater than the maximum noise level X1, the congestion degree is determined to be congested. The That is, when there are many people around the robot 12, many sounds are generated due to the people, the noise level is high, and the robot 12 is congested. On the other hand, if the noise level N is lower than the minimum noise level X2, it is determined that the degree of congestion is sparse. If there are not many people around the robot 12, the noise caused by the people is small, so the noise level around the robot 12 is low and the degree of congestion is sparse. In other cases, that is, when the noise level N is smaller than the maximum noise level X1 and equal to or less than the minimum noise level X2, the degree of congestion is determined to be normal. Note that the maximum noise level X1 and the minimum noise level X2 are appropriately determined according to the size of the target space 120, the purpose of use of the robot 12, and the like.

  When the degree of congestion around the robot 12 is determined, this is output to the CPU 52 of the robot 12. Based on this, the CPU 52 performs processing according to the flowchart shown in FIG. When starting the processing, the CPU 52 acquires the degree of congestion around the robot 12 from the server 100 in step S21.

  In step S23, it is determined whether or not the degree of congestion is congested. If it is congested, “YES” is determined, and an action to alleviate congestion is executed in step S25. For example, the robot 12 speaks “Go over there” or takes an action that urges a human to move away from the robot 12 by raising the arm in a desired direction. As a result, it is possible to ensure a safe state by avoiding a dangerous state due to a large number of humans pushing against each other. In addition, in venues such as poster sessions and exhibitions, not only is it possible to avoid the dangers caused by crowding around the robot 12, but it is difficult to hear explanations and it is difficult to see the exhibits when people gather in one place. , Guide them to other places and manage the venue smoothly.

  On the other hand, if it is determined in step S23 that the degree of congestion is not crowded and “NO”, it is next determined in step S27 whether the degree of congestion is sparse. If the degree of congestion is sparse, “YES” is determined here, and in step S29, the robot 12 executes an action of collecting humans. For example, he or she speaks “Come here” or behaves by waving his hand up and down to direct a person to come to the robot 12. As a result, humans gather around the robot 12 and draw customers.

  If it is determined that the determination in step S27 is not sparse but “NO”, it is determined in step S31 that the degree of congestion is normal, and a normal action is executed in step S33. For example, the robot 12 speaks or moves “Let's play.”

  In step S35, it is determined whether or not there is an end request. If there is no end request and it is determined “NO”, the process returns to step S21. On the other hand, if there is an end request, “YES” is determined and the processing of the robot 12 ends. Accordingly, the server 100 also determines whether or not there is an end request in step S11 shown in FIG. 6. If “NO” and it is determined that there is no end request, the process returns to step S1, and conversely ends with “YES”. If it is determined that there is a request, the process is also terminated and the communication action of the robot 12 is terminated.

  As described above, the degree of congestion around the robot 12 is identified, and the robot 12 executes a communication action accordingly, so that the robot 12 can make a person act according to the surrounding situation.

  In addition, since the noise level around the robot 12 can be measured by the sound level meter 114 and then a certain degree of congestion can be grasped, the degree of congestion around the robot 12 can be easily obtained.

  Furthermore, since only the noise level meter 114 around the robot 12 is used based on the position of the robot 12 in the target space 120, the noise level around the robot 12 can be accurately detected.

  Note that the noise level measured by the sound level meter 114 was used as a method of acquiring the degree of congestion around the robot 12, but the ultrasonic distance attached to the omnidirectional camera 28 and sensor mounting panel 18 provided on the upper body 24. Other modalities sensors such as sensor 20 or laser range finder can also be utilized. For example, when the omnidirectional camera 28 is used, a video signal from the omnidirectional camera 28 is processed to extract a skin color area, and if the area of the skin color area is large, there are many people around the robot 12 and the degree of congestion is “congested”. It is judged that. On the other hand, if the area of the skin color region is small, it is determined that there are few people around the robot 12 and the degree of congestion is “sparse”.

  In the above-described embodiment, the robot 12 receives the congestion degree data from the server 100 and determines the communication action. However, the server 100 may determine the degree of congestion and present communication actions (for example, steps S25, S29, and S33 in FIG. 8) to the CPU 52 of the robot 12 via the network 118 based on the degree of congestion. Good.

  The robot 12 according to another embodiment of the present invention is substantially the same as the system 10 shown in FIG. 1, but in the system 10 shown in FIG. 1, the noise level is measured by the sound level meter 114 installed in the target space 120, As a result, the server 100 determines the degree of congestion around the robot 12, and the robot 12 determines and executes a communication action based on the degree of congestion. On the other hand, in this other embodiment, the noise level around the robot 12 is measured by the microphone 30 provided on the body of the robot 12, and the degree of congestion is determined from the noise level measured by the robot 12 itself. Determine and implement communication behavior. Since other parts are the same as those of the robot 12 shown in FIG.

  The CPU 52 of the robot 12 processes the communication behavior according to the flowchart shown in FIG. When the CPU52 starts the process of communication behavior, in step S41, from the speaker 46, for example, to output the sound as "Hello", and / or more to work, towards the human attention to the robot 12, the human voice Ya Triggers sounds associated with actions. In step S43, it is determined whether or not the robot 12 is speaking. If “YES” is being spoken, the process returns to step S43. On the other hand, if “NO” is not being spoken, the ambient sound from the microphone 30 is captured by the person around the robot 12 in step S45, and the noise level N around the robot 12 is measured. In step S47, the degree of congestion around the robot 12 is checked from the noise level N based on the noise level-congestion degree table shown in FIG. The method of calculating the degree of congestion is the same as step S7 in FIG. However, in step S7 shown in FIG. 6, the noise level N around the robot 12 is detected based on the noise levels acquired from the plurality of sound level meters 114. Here, the microphone 30 directly detects the noise level N around the robot 12. The point to detect is different.

  Next, in step S49, it is determined whether or not the degree of congestion around the robot 12 is congested. If it is congested, “YES” is determined, and an action to alleviate the congestion is executed in step S51. On the other hand, if it is determined in step S49 that the degree of congestion is not “NO”, it is next determined in step S53 whether the degree of congestion is sparse. If the degree of congestion is sparse and it is determined “YES”, the robot 12 executes an action of collecting humans in step S55. On the other hand, if it is determined that the determination in step S53 is not sparse but “NO”, it is determined that the congestion level is normal in step S57, and the normal action is executed in step S59.

  In step S61, it is determined whether or not there is a termination request. If there is no termination request and it is determined "NO", the process returns to step S41. On the other hand, if it is determined that there is an end request “YES”, the processing of the CPU 52 ends and the communication action of the robot 12 ends.

  Note that the communication behavior of the robot 12 shown in step S51, step S55, and step S59 is the same as the communication behavior of the robot 12 shown in step S25, step S29, and step 33 shown in FIG. 8, respectively.

  Further, in this embodiment, measurement of the noise level around the robot 12, identification of the degree of congestion, and determination of communication behavior of the robot 12 are all performed by the CPU 52 of the robot 12, but some of them are other devices, etc. You may go on.

FIG. 1 is an illustrative view showing one example of a communication robot system of the present invention. FIG. 2 is an illustrative view for explaining the appearance of the robot shown in FIG. 1 embodiment. FIG. 3 is an illustrative view showing an electrical configuration of the robot shown in FIGS. 1 and 2. FIG. 4 is an illustrative view showing an arrangement of a target space where a robot exists. FIG. 5 is a graph showing the relationship between the number of people around the sound level meter (total number of people) and the noise level at the installation location. FIG. 6 is a flowchart showing processing of communication behavior of the server shown in FIG. FIG. 7 is an illustrative view showing a noise level-congestion degree table in FIG. 1 embodiment. FIG. 8 is a flowchart showing processing of communication behavior of the CPU shown in FIG. FIG. 9 is a flowchart showing the processing of the communication behavior of the CPU of the communication robot according to another embodiment of the present invention.

Explanation of symbols

10 ... Communication robot system 12 ... Communication robot 52 ... CPU
30 ... Microphone 100 ... Server 120 ... Target space 112 ... Infrared camera system 114 ... Sound level meter

Claims (7)

A communication robot that performs communication actions with humans,
A congestion degree identifying means for identifying a surrounding congestion degree, and a communication behavior determining means for determining a communication behavior of the communication robot based on a detection result of the congestion degree identifying means ,
The communication behavior determining unit is a communication robot system that determines an action for reducing congestion as the communication behavior when the congestion degree identifying unit identifies “congestion” . A communication robot that performs communication actions with humans,
A congestion degree identifying means for identifying a surrounding congestion degree, and
Communication behavior determining means for determining the communication behavior of the communication robot based on the detection result of the congestion degree identifying means;
A communication robot system , wherein the communication behavior determining unit determines a behavior of collecting people as the communication behavior when the congestion degree identifying unit identifies “sparse” . The congestion identifying means includes a noise detecting means for detecting an ambient noise level, communication robot system to identify, according to claim 1 or 2, wherein the congestion level based on the noise level detected by said noise detecting means. And further including a plurality of sound level meters each outputting a noise level at the installation location and distributed in the environment,
The communication robot system according to claim 3 , wherein the noise detection unit detects the noise level by acquiring a noise level from a sound level meter within a certain distance around the communication robot. A communication robot that performs communication actions with humans,
A congestion degree identifying means for identifying a surrounding congestion degree, and
Communication behavior determining means for determining communication behavior based on the detection result of the congestion degree identifying means,
The communication behavior determining means is a communication robot that determines an action to alleviate congestion as the communication action when the congestion degree identifying means identifies it as “congested” . A communication robot that performs communication actions with humans,
A congestion degree identifying means for identifying a surrounding congestion degree, and a communication behavior determining means for determining a communication action based on a detection result of the congestion degree identifying means ,
The communication behavior determining means is a communication robot that determines an action of gathering humans as the communication action when the congestion degree identifying means identifies “sparse” . The communication robot according to claim 5 , further comprising a noise detection unit that detects a surrounding noise level, wherein the congestion level identification unit identifies the congestion level based on a noise level detected by the noise detection unit.

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