Robot device, control system, control method, and program

Abstract

A robot device (100) comprises: a camera (104) that acquires an image including a person; a drive unit (105) that causes the robot device to move; a detection unit (140) that detects a person or the face of the person from the image acquired by the camera; a determination unit (150) that determines whether face authentication of the person detected by the detection unit (140) can be executed; and a control unit (170) that, when the determination unit (150) has determined that the face authentication cannot be executed, controls the drive unit (105) such that the robot device (100) moves to a position where the face authentication is possible, or that the robot device (100) moves along a route.

Description

ROBOT DEVICE, CONTROL SYSTEM, CONTROL METHOD, AND PROGRAM

[0001] The present disclosure relates to a robot device, a control system, a control method, and a program.

[0002] As the working population decreases, there is a demand for labor-saving in work. As an example of labor-saving in work, a monitoring system has been proposed for monitoring work (see Patent Document 1).

[0003] Japanese Patent Application Laid-Open No. 2021-68974

[0004] Meanwhile, face recognition is sometimes used in surveillance operations. Face recognition is performed by comparing the facial features of people registered in advance with the facial features of people in images captured by a camera. However, the accuracy of face recognition can be reduced if the person in the image has their back turned and their face is not visible, or if the face is visible but facing the wrong direction.

[0005] An object of the present disclosure is to provide a robot device that can perform face authentication with high accuracy.

[0006] According to one aspect of the present disclosure, there is provided a robotic device including a camera that captures an image including a person, a drive unit that moves the robotic device, a detection unit that detects a person or the person's face from the image captured by the camera, a determination unit that determines whether facial authentication can be performed for the person detected by the detection unit, and a control unit that controls the drive unit to move the robotic device to a position where facial authentication is possible or along a path when the determination unit determines that facial authentication cannot be performed.

[0007] According to the present disclosure, a robot device capable of performing face authentication with high accuracy can be provided.

[0008] FIG. 1 is a diagram illustrating an overview of a first embodiment. FIG. 2 is a diagram illustrating hardware included in a robot device according to the first embodiment. FIG. 3 is a block diagram illustrating functions of a robot device according to the first embodiment. (A) and (B) are diagrams illustrating an example of a detection frame according to the first embodiment. FIG. 4 is a diagram illustrating a specific example of a method for calculating a destination position according to the first embodiment. FIG. 5 is a diagram for explaining a destination position according to the first embodiment. FIG. 6 is a flowchart illustrating an example of processing executed by a robot device according to the first embodiment. FIG. 7 is a flowchart illustrating an example of a destination position calculation process according to the first embodiment. FIG. 8 is a diagram illustrating a control system according to a second embodiment. FIG. 9 is a diagram illustrating hardware included in an information processing device according to the second embodiment. FIG. 10 is a block diagram illustrating functions of an information processing device according to the second embodiment.

[0009] Hereinafter, embodiments will be described with reference to the drawings. The following embodiments are merely examples, and various modifications are possible within the scope of the present disclosure.

[0010] First Embodiment. Fig. 1 is a diagram showing an overview of a first embodiment. Fig. 1 shows a robot device 100. The robot device 100 is a device that executes a control method. The robot device 100 is an autonomous robot. The robot device 100 performs monitoring tasks. The robot device 100 has a camera.

[0011] FIG. 1 shows a person 10. The person 10 is facing backward. Therefore, the robot device 100 cannot capture an image of the person 10's face. Therefore, the robot device 100 goes around. The bottom diagram in FIG. 1 shows the state when the robot device 100 and the person 10 are viewed from above. As shown in the bottom diagram in FIG. 1, the robot device 100 goes around. This allows the robot device 100 to capture an image of the person 10's face. Therefore, the robot device 100 can acquire an image including the face. The robot device 100 will be described in detail below.

[0012] First, we will explain the hardware of the robot device 100. Figure 2 is a diagram showing the hardware of the robot device of embodiment 1. The robot device 100 has a processor 101, a volatile storage device 102, a non-volatile storage device 103, a camera 104, and a drive unit 105.

[0013] The processor 101 controls the entire robotic device 100. For example, the processor 101 is a central processing unit (CPU) or a field programmable gate array (FPGA). The processor 101 may be a multiprocessor. The robotic device 100 may also have a processing circuit.

[0014] The volatile storage device 102 is a main storage device of the robot device 100. For example, the volatile storage device 102 is a random access memory (RAM). The nonvolatile storage device 103 is an auxiliary storage device of the robot device 100. For example, the nonvolatile storage device 103 is a hard disk drive (HDD) or a solid state drive (SSD).

[0015] The camera 104 is an RGB (Red Green Blue) camera, an RGB-D (Depth) camera, or an infrared camera. The camera 104 captures an image of an object. For example, the camera 104 captures an image of the person 10. The driving unit 105 drives the robot device 100.

[0016] Next, a description will be given of the functions of the robot device 100. Fig. 3 is a block diagram showing the functions of the robot device according to embodiment 1. The robot device 100 includes a storage unit 110, an imaging unit 120, an acquisition unit 130, a detection unit 140, a determination unit 150, a calculation unit 160, and a control unit 170.

[0017] The storage unit 110 may be realized as a storage area secured in the volatile storage device 102 or the non-volatile storage device 103. The imaging unit 120 is realized by a camera 104. Some or all of the acquisition unit 130, detection unit 140, determination unit 150, calculation unit 160, and control unit 170 may be realized by a processing circuit. Furthermore, some or all of the acquisition unit 130, detection unit 140, determination unit 150, calculation unit 160, and control unit 170 may be realized as program modules executed by the processor 101. For example, the program executed by the processor 101 is also referred to as a control program. For example, the control program is recorded on a recording medium.

[0018] The storage unit 110 stores various information. The imaging unit 120 captures images using the camera 104. The acquisition unit 130 acquires the images captured by the imaging unit 120. The acquisition unit 130 acquires position information of the robot device 100. For example, the acquisition unit 130 acquires the position information of the robot device 100 from a GPS (Global Positioning System) sensor included in the robot device 100.

[0019] The detection unit 140 detects a person or a person's face from an image captured by the camera 104. The detection is performed using an image recognition technique. The image recognition technique may be a technique using a trained model or a technique using Haar-Like features.

[0020] The determination unit 150 determines whether or not facial authentication of a person appearing in an image is possible. First, the determination unit 150 determines whether or not the person was detected by the detection unit 140. If a person was detected, the determination unit 150 determines whether the detected detection frame is larger than a certain size. If it is determined that the size is large, the detection unit 140 performs face detection, and the determination unit 150 determines whether or not the face was detected. If a face was detected, the determination unit 150 determines whether or not facial authentication is possible. Whether or not facial authentication is possible is determined as follows: First, the facial features of the person whose face was detected are extracted. Next, the facial features of multiple people registered in a database are compared with the facial features of the person photographed by the camera. Whether or not facial authentication is possible is determined based on whether the degree of match between the features in the comparison is equal to or greater than a predetermined value. The database that stores information about people's facial features for facial authentication is a storage device or recording medium that can read and write information, and is, for example, placed on the cloud or in a building monitored by a robot device and sends and receives information to and from the robot device via a network, or is attached to the robot device.

[0021] Furthermore, if the face of a person cannot be accurately authenticated, that is, with the desired accuracy, because features cannot be extracted from the face of the person captured in the camera, or because facial features are extracted but cannot be sufficiently matched during authentication, the robot device 100 moves to enable accurate authentication of the face of the person, for example, by moving closer to capture a larger image of the face of the person or by changing its orientation to capture the face from as close to the front as possible. Capturing a larger image of the face refers to processing that includes enlarging the detection frame of the person or face captured in the camera. Capturing the face from as close to the front as possible refers to actions that include moving to capture the person captured in the camera from the front or diagonal front.

[0022] Possible movements of the robot device 100 include, for example, moving closer to the person so as to enlarge the detection frame for detecting the person or the person's face, or moving to a calculated position where the accuracy of extracting or matching facial features when authenticating the person's face is high (also referred to as a position where the person's face is clearly visible). These methods will be described in detail later.

[0023] A method for moving the robot device 100 based on the size of the detection frame will be described. When a person is included in the image and the detection frame of the person in the image is smaller than a predetermined frame, the control unit 170 may control the driving unit 105 to move closer to the person. An example of the detection frame is shown below.

[0024] 4A and 4B are diagrams illustrating examples of detection frames according to the first embodiment. FIG. 4A illustrates an image 20. The image 20 includes a person. FIG. 4A illustrates a detection frame 21. As described above, the determination unit 150 determines whether or not the face of the person can be recognized. If the detection unit 140 detects a person using a small detection frame 21, the distance between the robot device 100 and the person is large, and the determination unit 150 may not be able to detect the face of the person even if the person is facing forward. Therefore, the control unit 170 controls the driving unit 105 to approach the person. The distance to approach the person may be predetermined. The control unit 170 also controls the driving unit 105 to align the center position in the width direction of the image captured by the camera with the center position 22 of the detection frame 21. This control allows the robot to move toward the person's direction 23. After the robot device 100 approaches the person, the control unit 170 instructs the camera 104 to capture an image. The camera 104 captures an image of the person. Fig. 4(B) shows an image 30 obtained by capturing the image. Fig. 4(B) also shows a detection frame 31. Note that the detection frame 31 is larger than a predetermined frame. This means that the robot device 100 is closer to the person, and it is expected that the accuracy of face detection and face authentication after person detection will be improved.

[0025] A method for the robot device 100 to calculate and move to a position where a person's face is clearly visible in the camera will be described. When the detection frame 31 is larger than a predetermined frame but face authentication is not possible, the calculation unit 160 calculates a position where face authentication is possible. The calculation of this position will be described using a specific example. The position will be referred to as the target position.

[0026] 5 is a diagram showing a specific example of a method for calculating a destination position according to the first embodiment. FIG. 5 shows a distance 40 between the robot device 100 and the person 10. The distance 40 is also referred to as a first distance. The distance 40 can be obtained by the following method.

[0027] When the camera 104 is an RGB camera, the acquisition unit 130 acquires the trained model from the storage unit 110 or an external device. For example, the external device is a cloud server. The external device is not shown in the drawing. The acquisition unit 130 inputs an image into the trained model, and the trained model outputs the distance 40. In this way, the acquisition unit 130 can obtain the distance 40.

[0028] Furthermore, several examples of methods for obtaining the distance 40 are given below. Note that the method for obtaining the distance 40 may be other than the methods described below. One method will be described. When the camera 104 is an RGB camera, the obtaining unit 130 obtains the distance 40 from the image captured by the RGB camera using the Shape From Focus / Defocus method.

[0029] The second method will be described. The acquisition unit 130 acquires the distance 40 based on the approximate height of the person 10, the height of the detection frame in the image, the focal length, and a similarity relationship between the distance 40.

[0030] A third method will be described below: When the camera 104 is an RGB-D camera, the acquisition unit 130 acquires depth information obtained from the generated image as the distance 40 .

[0031] The four-eye method will be described below: If the robot device 100 has an infrared sensor, the acquisition unit 130 acquires the distance 40 based on information obtained from the infrared sensor.

[0032] The five-eye method will be described. If the robot device 100 has a distance sensor, the acquisition unit 130 acquires the distance 40 based on information obtained from the distance sensor. The distance sensor here is, for example, a LiDAR.

[0033] The acquisition unit 130 acquires a distance 41 between the person 10 and the destination position 42. The distance 41 is a predetermined distance. For example, the acquisition unit 130 acquires the distance 41 from the storage unit 110 or an external device. The distance 41 is also referred to as a second distance.

[0034] Here, the calculation unit 160 may subtract a value from the distance 41 if the statistically processed value of the image brightness is equal to or less than a predetermined value. For example, an average value based on a predetermined sample may be used as the statistical processing. Furthermore, the calculation unit 160 may perform statistical processing on the brightness of the entire image, or on the brightness within a detection frame in which a person or face is detected. A statistically processed value equal to or less than the predetermined value means that the image is dark overall. In other words, this means that the brightness of the environment in which the person 10 was captured was dark. Therefore, if the robot device 100 captures an image at the target position 42 without changing the distance 41, the brightness of the image obtained by the capture will be dark. If the image brightness is dark, the accuracy of face recognition will decrease. Therefore, the calculation unit 160 shortens the distance 41. As a result, when the robot device 100 captures an image at the target position 42, the size of the face included in the image obtained by the capture will be larger. This improves the accuracy of face recognition.

[0035] The acquisition unit 130 may acquire information about distance directly from the external device or various sensor devices described above, or may acquire information about distance indirectly by converting information output from the external device or the device. In other words, the acquisition unit 130 not only performs information acquisition processing but also performs arithmetic processing such as converting the acquired information into information about distance.

[0036] When the height of the detection frame in the image is equal to or greater than a predetermined value, the calculation unit 160 may add a value to the distance 41. This allows the robot device 100 to capture an image of a tall person at an appropriate size.

[0037] Furthermore, the acquisition unit 130 acquires information indicating the direction of the person 10 or the direction of the face of the person 10, which is identified from the image captured by the camera 104. The information indicating the direction of the person 10 or the direction of the face of the person 10 here is identified using image analysis technology. The information indicating the direction of the person 10 captured by the camera 104 or the direction of the face of the person 10 is also referred to as direction information. Note that the information indicating the direction of the person 10 is not limited to being identified from external features such as the skeletal shape of the person 10, but may also be identified using information regarding the direction in which the person 10 moves when walking or running.

[0038] The calculation unit 160 then calculates the destination position 42 based on the position information of the robot device 100, the orientation information, the distance 40, and the distance 41. The control unit 170 controls the drive unit 105 and the imaging unit 120 in conjunction with the movement to the destination position 42 calculated by the calculation unit 160, and points the camera 104 toward the face of the person 10. The robot device 100 uses the information on the destination position 42 calculated by the calculation unit 160 to capture an image of the person 10 with the camera 104 when moving around to get in front of the person 10, or after moving around to get in front of the person 10.

[0039] Here, it will be explained that not only information indicating the facial orientation of the person 10, but also information indicating the orientation of the person 10 can be used as orientation information. The facial orientation of the person 10 is basically directed forward. However, if there is something bothering the person, the person may turn their face in a direction other than the forward direction by, for example, shaking their head. Therefore, if the facial orientation changes unexpectedly, information on the orientation of the person 10 is first identified. In this case, using the information on the orientation of the person 10, it is possible to estimate the facial orientation when the person 10 faces forward or when they turn their face at a predetermined angle from the forward direction, i.e., when they shake their head at a predetermined angle, and generate information on the facial orientation of the person 10. In this way, information indicating the orientation of the person 10 can also be used as information indicating the facial orientation of the person 10, and therefore the information indicating the identified orientation of the person 10 can also be used as orientation information for facial authentication of the person 10.

[0040] The information on the facial orientation of person 10 may include not only the facial orientation when facing forward, but also the facial orientation when facing a direction within an angle range of 0° to 45°, which is directly in front of the face, as described below. This angle range may also be used as a predetermined angle when generating information on the facial orientation of person 10 from the orientation of person 10.

[0041] In addition, the acquisition unit 130 may acquire information regarding orientation, associate the acquired orientation information with information about the person 10 and information about the face of the person 10, and store these in the memory unit 110 of the robot device 100 or in the memory unit of the control system described below.

[0042] Furthermore, the calculation unit 160 may calculate a path along which the robot device 100 moves to the calculated destination position 42, i.e., a movement path. The method for calculating the movement path at this time may be a method of linearly interpolating the position information of the robot device 100 and the destination position 42, or a method of two-dimensionally interpolating in a wraparound manner using spline interpolation or the like. The robot device 100 may move along the movement path calculated in this manner.

[0043] FIG. 6 is a diagram illustrating a target position according to the first embodiment. The target position 42 is preferably located in a frontal direction of the face. In FIG. 6, the target position 42a is located in a frontal direction of the face. The target position 42 for the robot device 100 to perform face authentication does not necessarily have to be located in a frontal direction of the face. For example, the target position 42 may be located in an angle range from 0°, which is directly in front of the face, to positions 42b and 42c, which are 45° apart.

[0044] To enable face authentication even when the image is not from the front, image information for authentication, which captures the face of a known person known not to be a suspicious person, from the front or from an oblique angle is recorded in advance in a database, and the robot device 100 moves so as to capture the image of the person's face from a direction that can capture the facial features contained in the recorded image information. Therefore, the more directions in which the face of a known person is captured as image information for authentication, the easier it is for the robot device 100 to perform authentication using a camera.

[0045] However, if one attempts to achieve a desired level of accuracy in face recognition, the matching process will take time, and since the person being photographed by the camera will move during that time, it is expected that face recognition will not be performed smoothly. Therefore, in order to perform face recognition smoothly and accurately, a database may be registered with multiple pieces of face information for the same person, with different shooting conditions or shooting directions, and a large amount of information indicating facial features may be recorded, thereby enabling smooth matching and authentication, or a technology may be used to three-dimensionally estimate the shape or features of the face that are not included in the image at the time of capturing the face information for at least one of the face information registered in the database and the face to be recognized, thereby enabling highly versatile matching.

[0046] If facial authentication can be performed smoothly, it becomes possible to quickly determine whether the person is a known person registered in the database or an unregistered person, which leads to increasing the practicality of surveillance using the camera mounted on the robot device 100.

[0047] Next, the processing executed by the robot device 100 will be described using a flowchart. FIG. 7 is a flowchart illustrating an example of the processing executed by the robot device of embodiment 1. (Step S11) The imaging unit 120 captures an image. (Step S12) The acquisition unit 130 acquires the image captured by the imaging unit 120. (Step S13) The detection unit 140 performs human detection on the image acquired by the acquisition unit 130. The detection unit 140 determines whether or not a human has been detected. If a human has been detected, the processing proceeds to step S14. If a human has not been detected, the control unit 170 controls the robot device 100 to perform monitoring work on a different area. Thereafter, the processing proceeds to step S11. (Step S14) The determination unit 150 determines whether the size of the detection frame used to detect a human by the detection unit 140 is equal to or larger than a certain size. If the size of the detection frame is smaller than the certain size, the processing proceeds to step S15. If the size of the detection frame is larger than the certain size, the processing proceeds to step S16. (Step S15) The control unit 170 controls the robot device 100 to approach the monitoring target. Then, the process proceeds to step S11. (Step S16) The determination unit 150 determines whether or not the face of the person can be detected. If the face of the person can be detected, the process proceeds to step S18. If the face of the person cannot be detected, the process proceeds to step S17. (Step S17) The robot device 100 executes a destination position calculation process. Thereafter, the control unit 170 controls the robot device 100 to move to the calculated destination position. Note that the robot device 100 may move along the calculated movement path instead of moving to the calculated destination position. Then, the process proceeds to step S11.

[0048] (Step S18) The robotic device 100 performs face authentication. The robotic device 100 determines the result of the face authentication. If face authentication is successful, the process ends. If face authentication is not successful, the process proceeds to step S19. (Step S19) The robotic device 100 executes a destination position calculation process. Thereafter, the control unit 170 controls the robotic device 100 to move to the calculated destination position. Note that the robotic device 100 may move along the calculated movement path instead of moving to the calculated destination position. Then, the process proceeds to step S11.

[0049] FIG. 8 is a flowchart showing an example of the destination position calculation process according to the first embodiment. The process in FIG. 8 corresponds to steps S17 and S19. (Step S21) The acquisition unit 130 acquires the distance 40. (Step S22) The acquisition unit 130 acquires orientation information. (Step S23) The acquisition unit 130 acquires the distance 41. (Step S24) The acquisition unit 130 acquires the position information of the robot device 100. (Step S25) The calculation unit 160 calculates the destination position 42 based on the orientation information, the position information of the robot device 100, the distance 40, and the distance 41.

[0050] When performing face recognition on a person who is not registered in the database (such as a suspicious person), the judgment unit 150 may determine that face recognition is not possible, and may interrupt the face recognition process and output an alert if the number of times face recognition is not possible exceeds a predetermined number, in order to avoid continuing to repeat the face recognition process.

[0051] Next, a specific example of face recognition will be described. The robot device 100 is located on a certain floor in a building. The robot device 100 is patrolling at night. The robot device 100 captures an image of the surroundings. A person is included in the image obtained by capturing the image. The person has their back turned. Therefore, the robot device 100 cannot detect the person's face. The robot device 100 moves to a target position. The robot device 100 then captures an image of the person. The robot device 100 performs face recognition. If the person is not a security guard or employee, the robot device 100 outputs an alert.

[0052] According to the first embodiment, when the robot device 100 is unable to capture an image of a person's face, the robot device 100 moves to a position where it can capture an image of the person's face. Then, the robot device 100 captures an image of the person's face. In this way, the robot device 100 can obtain an image including the face.

[0053] Second Embodiment Next, a second embodiment will be described. In the second embodiment, differences from the first embodiment will be mainly described. In the second embodiment, descriptions of commonalities with the first embodiment will be omitted. In the first embodiment, a case where the robot device 100 executes all of the processing has been described. In the second embodiment, a case where some of the processing is executed by an external device will be described.

[0054] 9 is a diagram showing a control system according to a second embodiment. The control system includes an information processing device 200 and a robotic device 300. The information processing device 200 and the robotic device 300 communicate with each other via a network. For example, the information processing device 200 is a server. The robotic device 300 includes a camera and a driving unit.

[0055] Next, a description will be given of the hardware included in the information processing device 200. Fig. 10 is a diagram showing the hardware included in the information processing device of embodiment 2. The information processing device 200 includes a processor 201, a volatile storage device 202, and a non-volatile storage device 203.

[0056] The processor 201 controls the entire information processing device 200. For example, the processor 201 is a CPU, an FPGA, or the like. The processor 201 may be a multiprocessor. The information processing device 200 may also include a processing circuit.

[0057] The volatile storage device 202 is a main storage device of the information processing device 200. For example, the volatile storage device 202 is a RAM. The nonvolatile storage device 203 is an auxiliary storage device of the information processing device 200. For example, the nonvolatile storage device 203 is an HDD or an SSD.

[0058] Next, a description will be given of the functions of the information processing device 200. Fig. 11 is a block diagram showing the functions of the information processing device of embodiment 2. The information processing device 200 has a storage unit 210, an acquisition unit 220, a detection unit 230, a determination unit 240, a calculation unit 250, and a control unit 260.

[0059] The storage unit 210 may be realized as a storage area secured in the volatile storage device 202 or the non-volatile storage device 203. Some or all of the acquisition unit 220, detection unit 230, determination unit 240, calculation unit 250, and control unit 260 may be realized by a processing circuit. Furthermore, some or all of the acquisition unit 220, detection unit 230, determination unit 240, calculation unit 250, and control unit 260 may be realized as program modules executed by the processor 201.

[0060] The functions of the acquisition unit 220, the detection unit 230, the determination unit 240, and the calculation unit 250 are almost the same as the functions of the acquisition unit 130, the detection unit 140, the determination unit 150, and the calculation unit 160. For example, the acquisition unit 220 acquires an image captured by a camera included in the robot device 300, position information of the robot device 300, a distance 40 between the robot device 300 and a person, and a predetermined distance 41.

[0061] As described above, the functions of the acquisition unit 220, the detection unit 230, the determination unit 240, and the calculation unit 250 are almost the same as the functions of the acquisition unit 130, the detection unit 140, the determination unit 150, and the calculation unit 160. Therefore, detailed descriptions of the functions of the acquisition unit 220, the detection unit 230, the determination unit 240, and the calculation unit 250 will be omitted.

[0062] The control unit 260 instructs the robot device 300 to move to the destination position 42 and capture an image at the destination position 42. When the robot device 300 receives the instruction, it moves to the destination position 42. When the robot device 300 arrives at the destination position 42, it captures an image of the person.

[0063] When a person is included in the image and the detection frame of the person in the image is smaller than a predetermined frame, the control unit 260 may instruct the robot device 300 to move closer to the person. Furthermore, the control unit 260 may calculate the center coordinates of the detection frame, identify the direction of the center coordinates, and instruct the robot device 300 to move in that direction.

[0064] According to the second embodiment, when the robot device 300 cannot capture an image of a person's face, the robot device 300 moves to a position where it can capture an image of the person's face. Then, the robot device 300 captures an image of the person's face. This allows the control system to obtain an image including the face.

[0065] In the second embodiment, the information processing device 200 includes the storage unit 210, the acquisition unit 220, the detection unit 230, the determination unit 240, the calculation unit 250, and the control unit 260, but is not limited to this. For example, some of these units may be included in the robot device 300.

[0066] The features of the above-described embodiments can be combined with each other as appropriate.

[0067] 10 Person, 20 Image, 21 Detection frame, 22 Center coordinates, 23 Direction, 30 Image, 31 Detection frame, 40 Distance, 41 Distance, 42 Target position, 42a Target position, 42b, 42c Position, 100 Robot device, 101 Processor, 102 Volatile storage device, 103 Non-volatile storage device, 104 Camera, 105 Driving unit, 110 Storage unit, 120 Imaging unit, 130 Acquisition unit, 140 Detection unit, 150 Determination unit, 160 Calculation unit, 170 Control unit, 200 Information processing device, 201 Processor, 202 Volatile storage device, 203 Non-volatile storage device, 210 Storage unit, 220 Acquisition unit, 230 Detection unit, 240 Determination unit, 250 calculation unit, 260 control unit, 300 robot device.

Claims

1. 1. A robotic device, comprising: A camera for capturing images including people; A drive unit that moves the robot device; a detection unit that detects a person or a face of the person from an image acquired by the camera; a determination unit that determines whether face authentication can be performed on the person detected by the detection unit; a control unit that controls the driving unit so that, when the determination unit determines that face authentication cannot be performed, the robot device moves to a position where face authentication is possible or the robot device moves along a route; Equipped with Robot device.

2. The control unit is Based on the direction of the person photographed by the camera or the direction of the face of the person, the driving unit is controlled so as to move to a position around the front of the person or along a path so as to enable face authentication. The robotic device according to claim 1 .

3. an acquisition unit that acquires orientation information indicating a direction of the person photographed by the camera or a direction of the face of the person, position information of the robot device, a first distance that is a distance between the robot device and the person photographed by the camera, and a second distance that is a distance for photographing the person photographed by the camera at a desired size; a calculation unit that calculates a position or a route where face authentication is possible based on the orientation information, the position information, the first distance, and the second distance acquired by the acquisition unit; Equipped with The robot device according to claim 1 or 2.

4. The control unit is When the detection result of the detection unit indicates that the detection frame is smaller than a predetermined frame standard, the drive unit is controlled so as to approach the person photographed by the camera. The robot device according to claim 1 or 2.

5. The calculation unit is if a value obtained by statistically processing the brightness of the image captured by the camera is equal to or smaller than a predetermined value, a value is subtracted from the second distance, and the position is calculated using the second distance after the subtraction. The robot device according to claim 3.

6. The control unit is controlling the driving unit so as to align a center position in a width direction of an image captured by the camera with a center position of a detection frame of a person captured by the camera or a detection frame of a face of the person; The robot device according to claim 4.

7. A control system including a robot device having a camera and a driving unit for acquiring an image including a person, and an information processing device, a detection unit that detects a person or a face of the person from an image acquired by the camera; a determination unit that determines whether face authentication can be performed on the person detected by the detection unit; a control unit that controls the driving unit so that the robot device moves to a position where face authentication is possible or moves along a route when the determination unit determines that face authentication cannot be performed; Equipped with Control system.

8. A method for controlling a robot device having a camera for acquiring an image including a person and a driving unit, comprising: detecting a person or a face of the person from an image captured by the camera; determining whether facial authentication of the detected person can be performed; controlling the driving unit so that, when it is determined that face authentication cannot be performed, the robotic device moves to a position where face authentication can be performed or moves along a path; A control method comprising:

9. A program for controlling the operation of a robot device having a camera for acquiring an image including a person and a driving unit, detecting a person or a face of the person from an image captured by the camera; determining whether facial authentication of the detected person can be performed; controlling the driving unit so that, when it is determined that face authentication cannot be performed, the robotic device moves to a position where face authentication is possible or moves along a path; A program that executes a process including: