JP2009026200A - Autonomous moving device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an autonomous moving device for autonomously moving with a specific person, so as to secure the specific person. <P>SOLUTION: The autonomous moving device for autonomously moving with the specific person comprises: a surrounding environment recognition means for recognizing the specific person and its surrounding environment; a blind spot predicting means for predicting a blind spot for a moving body around the specific person; and an alerting means for alerting the moving body when the specific person is predicted to enter the blind spot. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an autonomous mobile device that moves autonomously around a specific person.

Conventionally, an automatic transport robot for automatically transporting a transported object to a destination has been proposed (for example, see Patent Document 1). In the automatic transfer robot described in Patent Document 1, the transported object is stored in the robot storage unit and moved to the specified target position while the lock unit is locked, and the robot reaches the specified target position and the handling registrant checks. When the operation is performed, the lock unit is released. Thereby, the handling registrant can reliably take out the transported object stored in the storage unit of the robot at the designated target position.
JP 2001-287183 A

  According to said automatic conveyance robot, a conveyed product can be automatically conveyed to the destination. However, no consideration is given to moving around a person so as to ensure the safety of the person.

  The present invention has been made to solve the above problems, and can be moved so as to ensure the safety of a specific person in an autonomous mobile device that moves autonomously near the specific person. An object is to provide an autonomous mobile device.

  In order to achieve the above-described object, the present invention provides an autonomous mobile device that autonomously moves around a specific person, an ambient environment recognition unit that recognizes the specific person and the surrounding environment, and the specific person. A blind spot area estimating means for estimating a blind spot area of a moving object existing around the vehicle, and an alerting means for alerting a moving object when a specific person moves in the blind spot area. And According to this configuration, the autonomous mobile device estimates the blind spot area of a moving object when a moving object exists around the specific person, and the moving object with respect to the moving object when the specific person moves in the blind spot area. Call attention. Therefore, the presence of a specific person can be recognized by surrounding mobile bodies, and a collision accident between a specific person and the mobile body can be prevented in advance.

  In the autonomous mobile device of the present invention, the blind spot area estimating means estimates the boundary line between the visible area and the blind spot area of the moving object, and the alerting means is up to the boundary line estimated by the blind spot area estimating means. Is preferably moved. According to this configuration, the autonomous mobile device estimates the boundary line between the visible area and the blind spot area of the moving object, and moves the autonomous mobile device to the estimated boundary line. Therefore, since the autonomous mobile device enters the visible area of the moving body, it is possible to make the occupant of the moving body recognize that a person is coming specifically.

  Further, in the autonomous mobile device of the present invention, the blind spot area estimation means has data of a visible area and a blind spot area based on the mobile object, and applies the data to the mobile object recognized by the surrounding environment recognition means, It is preferable to estimate the boundary line between the visible area and the blind spot area of the moving object. According to this configuration, the autonomous mobile device has the data of the visible area and the blind spot area based on the mobile object, and applies the data to the mobile object recognized by the surrounding environment recognition unit, so that the visible area of the mobile object And the boundary line of the blind spot area is estimated. Therefore, the autonomous mobile device can estimate the boundary line between the visible area and the blind spot area of the moving body relatively easily.

  Further, in the autonomous mobile device of the present invention, the surrounding environment recognition means recognizes an obstacle existing around the moving body, and the blind spot area estimation means is the blind spot of the moving object due to the obstacle recognized by the surrounding environment recognition means. It is preferable to estimate the area. According to this configuration, the autonomous mobile device recognizes an obstacle existing around the mobile object, and estimates the blind spot area of the mobile object due to the recognized obstacle. Therefore, the autonomous mobile device can call attention to the moving object in consideration of the blind spot area of the moving object due to the obstacle.

  According to the present invention, it is possible to provide an autonomous mobile device capable of moving so as to ensure the safety of a specific person while autonomously moving near the specific person.

  DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments of the invention will be described in detail with reference to the accompanying drawings. In order to facilitate the understanding of the description, the same reference numerals are given to the same components in the drawings as much as possible, and duplicate descriptions are omitted.

(1) Configuration of Autonomous Mobile Device First, the configuration of the autonomous mobile device 1 according to the embodiment of the present invention will be described with reference to FIG. FIG. 1 is a block diagram showing the configuration of the autonomous mobile device 1. The autonomous mobile device 1 moves autonomously to follow the master or to guide the master around a specific person using the autonomous mobile device 1 (hereinafter referred to as “master”). In addition, the autonomous mobile device 1 recognizes the master and the surrounding environment from information acquired by the camera 10, the communication device 12, and the like.

  The camera 10 includes a pair of CCD cameras that acquire images of the master and the surrounding environment, and image processing that recognizes the master and obstacles and road signs (that is, the surrounding environment) by processing the acquired images. Part. This image processing unit extracts and recognizes a master, a surrounding moving body, an obstacle, a road sign, and the like from an image acquired by a pair of CCD cameras by edge extraction or pattern recognition processing. Also, the distance and lateral displacement from the object are obtained by the triangulation method based on the difference in the position of the object such as the master in the left and right acquired images, and the relative speed is obtained from the amount of change with respect to the distance obtained in the previous frame. The camera 10 and an electronic control device (hereinafter referred to as “ECU”) 20 described later are connected via a communication line, and information acquired by the camera 10 is transmitted to the ECU 20 via this communication line.

  The communicator 12 includes a transmitter 13 and a receiver 14, and is installed, for example, on other autonomous mobile devices and vehicles around the autonomous mobile device 1, and on traffic lights and roads installed at intersections. Information is transmitted to and received from an infrastructure such as a camera or radar. For example, the transmitter 13 transmits information such as the position and moving speed of the master to other autonomous mobile devices, vehicles traveling around the vehicle, and the like. On the other hand, the receiver 14 is, for example, information on the movement state of the master transmitted from a sensing (detection) device such as an acceleration sensor or a gyro carried by the master, the position of another pedestrian transmitted from another autonomous mobile device, Information such as travel direction and speed, information on the position, travel direction, speed, and operation status of a traveling vehicle transmitted from a vehicle traveling in the vicinity, and the position of a stopped vehicle transmitted from a vehicle parked in the vicinity And information such as the lighting state and traffic state of the traffic lights transmitted from the above-described infrastructure. Note that the communication device 12 is set to be able to transmit and receive information within a radius of about 100 m, for example.

  The communication device 12 and the ECU 20 are configured to be able to exchange information with each other by being connected via a communication line. Transmission information generated by the ECU 20 is transmitted from the ECU 20 to the transmitter 13 via this communication line. On the other hand, various ambient environment information received by the receiver 14 is transmitted to the ECU 20 via this communication line.

  Thus, in this embodiment, the master and the surrounding environment are recognized by the camera 10, the communication device 12, and the like. More specifically, for example, the position / moving direction / moving speed of the master, the position / moving direction / moving speed / operating state of other moving objects such as pedestrians / bicycles / automobiles, stationary vehicles / electric poles / falling objects, etc. The surrounding environment such as the position / shape of the obstacle and the traffic state such as the lighting state of traffic lights and road signs are recognized. In addition, for example, an attribute relating to the type of mobile object is also recognized. Here, examples of the attribute relating to the type of the moving body include classifications such as large vehicles, small vehicles, two-wheeled vehicles, and bicycles. That is, the camera 10 and the communication device 12 function as ambient environment recognition means described in the claims.

  Here, the recognition as to whether or not the person is the master is performed by, for example, putting personal ID information indicating the master on the communication information of the communication between the master and the autonomous mobile device 1 or wearing the person who has been imaged. This can be done by determining whether or not the shape and pattern of the existing clothes match those of the master trained in advance. Further, authentication techniques using fingerprints and irises may be combined.

  The ECU 20 includes a microprocessor that performs calculations, a ROM that stores programs for causing the microprocessor to execute each process, a RAM that stores various data such as calculation results, and a backup RAM in which the stored contents are held by a 12V battery. It is comprised by. With the above configuration, the visual field area / dead angle area estimation unit 22 and the actuator control unit 26 are built in the ECU 20. The actuator control unit 26 drives the speaker 30, the backlight 32, the electric motor 34, the display 44, and the like.

  The visual field area / dead angle area estimation unit 22 estimates the visual field area and the blind spot area of the moving object when it is determined that the moving object exists in the surrounding environment recognized by the camera 10, the communication device 12, and the like. The visual field area / dead angle area estimation unit 22 estimates the visual field area and blind spot area of the moving body according to each of a large vehicle, a small vehicle, a two-wheeled vehicle, a bicycle, and the like. For example, when the moving body is an automobile, the visual field area is a range that can be seen by the driver through the windshield and the side glass, and the blind spot area is a range that is hidden from the front pillar or the like and cannot be seen by the driver. In addition, a range hidden behind an obstacle on the road surface and invisible from the moving body is also estimated as a blind spot area.

  The visual field area / dead angle area estimation unit 22 stores data on the visual field area and the blind spot area of the moving object for each type of the moving object in order to estimate the visual field area and the blind spot area of the moving object. Here, the data of the visual field area and the blind spot area is data in which the visual field area and the blind spot area are set based on the position and direction of the moving body. When the position or direction of a moving body existing in the surrounding environment is recognized by the camera 10 or the communication device 12 or the like, the visual field area / dead angle area estimation unit 22 displays the visual field area at the recognized position and direction of the mobile body. Then, by applying the data of the blind spot area, the coordinate range of the visual field area and the blind spot area of the actual moving body is calculated.

  The actuator controller 26 alerts the moving body when the master moves in the blind spot area, and prevents the master from coming into contact with the moving body. The actuator controller 26 alerts the moving body by moving the autonomous mobile device 1 or driving a backlight, a speaker, or the like. For example, when the master is about to enter the visual field from the blind spot area of the moving object, the actuator control unit 26 autonomously reaches the boundary line between the visual field area and the blind spot area of the mobile object before the master reaches the visual field area. The moving device 1 is moved. Thereby, the autonomous mobile device can be moved to a position that can be seen from the moving body, and the moving body can be notified of the presence of the master.

  That is, the visual field area / blind spot area estimation unit 22 constituting the ECU 20 functions as a blind spot area estimating unit described in the claims. Moreover, the actuator control part 26 functions as an alerting means described in the claims.

  The speaker 30 is connected to the ECU 20, and alerts the master and the surroundings by issuing a warning sound, audio information, and the like according to a control signal output from the actuator control unit 26. The backlight 32 is also connected to the ECU 20 and is driven by the actuator control unit 26 to emit attention to the master and the surroundings by emitting light of a color corresponding to the degree of danger, for example. The electric motor 34 is also connected to the ECU 20, is driven by the actuator control unit 26, and moves the autonomous mobile device 1 by rotating the wheels 36 attached to the electric motor 34. Further, an input device 42 such as a button or a touch panel is connected to the ECU 20 so that the master can input information and make settings for the ECU 20.

(2) Alerting process of autonomous mobile device Next, referring to FIG. 2 together, the flow of the operation inside the autonomous mobile device 1 that moves so as to ensure the safety of the master will be described. FIG. 2 is a flowchart showing a flow of processing procedures performed in the autonomous mobile device 1. The process shown in the flowchart of FIG. 2 is mainly performed by the ECU 20, and is repeatedly executed at a predetermined timing from when the autonomous mobile device 1 is turned on until it is turned off.

  First, in step S <b> 1, the ECU 20 acquires information such as the position, moving direction, moving speed, and type of a moving body existing around the master from the camera 10 and the communication device 12. The ECU 20 recognizes the moving body around the master by acquiring information on the moving body from the camera 10 and the communication device 12.

  Next, in step S2, the ECU 20 calculates a visual field area and a blind spot area of the moving body. The ECU 20 calculates the coordinate range of the actual visual field area and blind spot area of the mobile object by applying the data of the visual field area and blind spot area to the position and direction of the mobile object recognized in step S1. For example, when the moving body is a pedestrian M1, as shown in FIG. 3A, a coordinate range that includes only the visual field area A1 and no blind spot area is calculated. For example, when the moving body is the automobile M2, as shown in FIG. 3B, the coordinate range in which the areas hidden by the left and right front pillars in the visual field area A1 become the blind spot areas A2 and A3 is calculated. Is done.

  Further, when an obstacle is found in the visual field area of the moving body, the ECU 20 calculates an area behind the obstacle as a blind spot area hidden by the obstacle based on the viewpoint of the moving body. Then, the ECU 20 combines the coordinate range of the blind spot area due to the obstacle with the coordinate range of the visual field area and the blind spot area calculated in step S2. Thereby, for example, when the moving body is the pedestrian M1, as shown in FIG. 4A, coordinates in which the area hidden in the obstacles G4 and G5 in the visual field area A1 becomes the blind spot areas A4 and A5. The range is calculated. For example, when the moving body is the automobile M2, as shown in FIG. 4B, in addition to the blind spot areas A2 and A3 due to the left and right front pillars, the area hidden by the obstacle G6 is the blind spot area A6. The coordinate range is calculated.

  Next, in step S3, the ECU 20 detects a boundary line between the visual field area and the blind spot area using the coordinate range of the visual field area and the blind spot area. In particular, the ECU 20 detects a boundary line closest to the master among the boundary lines formed by the visual field area and the blind spot area.

  Next, in step S4, the ECU 20 determines whether or not the movement path of the master intersects the boundary line. Here, the ECU 20 proceeds to the process of step S5 when the movement route of the master intersects the boundary line. On the other hand, the ECU 20 returns to the process of step S1 when the movement route of the master does not intersect the boundary line.

  Next, in step S5, when the master reaches a predetermined distance before the boundary line, the ECU 20 controls the electric motor 34 and the wheels 36 so that the autonomous mobile device 1 is moved to the intersection between the movement path of the master and the boundary line. Move. Then, the ECU 20 causes the autonomous mobile device 1 to wait until the master arrives at the intersection position. Thereby, the moving body is alerted that the master moves in the blind spot area. Therefore, it is possible to prevent a collision between the moving body and the master. Note that the autonomous mobile device 1 may alert a moving object by emitting light, sound, or the like around it.

(3) Operation Example of Autonomous Mobile Device A specific operation example of the autonomous mobile device 1 will be described with reference to FIGS. 5 and 6.

  In the operation example of FIG. 5, the autonomous mobile device 1 recognizes the automobile M2 that is about to turn right at the intersection. And the autonomous mobile apparatus 1 calculates the coordinate range of visual field area A1 and blind spot area A2, A3 of the motor vehicle M2 using the data of the visual field area and blind spot area of a general vehicle. Next, the autonomous mobile device 1 detects the boundary line B1 that is the boundary line between the visual field area A1 and the blind spot area A2 and is closest to the master P, moves to the boundary line B1, and waits until the master P arrives. . By such an operation of the autonomous mobile device 1, it is possible to alert the driver of the automobile M2 that the master P enters the blind spot area from the visual field area, and to the master P at the boundary line B1. You can be informed.

  In the operation example of FIG. 6, the autonomous mobile device 1 recognizes the automobile M2 that is about to turn right at the intersection. And the autonomous mobile apparatus 1 estimates the visual field area A1 and blind spot area A2, A3 of a vehicle using the data of the visual field area and blind spot area of a common vehicle. Further, the autonomous mobile device 1 recognizes that the bicycle M3 is approaching the intersection based on information from the fixed camera C installed at the intersection that is the infrastructure. And the autonomous mobile apparatus 1 calculates the visual field area A7 and blind spot area A8 of the bicycle M3 using the data of the visual field area and blind spot area of a general bicycle. Next, the autonomous mobile device 1 detects the boundary line B2 that is the boundary line between the visual field area A7 and the blind spot area A8 and is closest to the master P, moves to the boundary line B2, and waits until the master P arrives. . By such an operation of the autonomous mobile device 1, it is possible to alert the bicycle M3 that the master P enters the visual field area A7 from the blind spot area A8, and that is the boundary line B2 to the master P. I can let you know.

(4) Effect of this embodiment The effect of this embodiment is demonstrated.

  The autonomous mobile device 1 according to the present embodiment estimates a blind spot area of a moving object when a moving object exists around the master, and alerts the moving object when the master moves in the blind spot area. Do. Therefore, the presence of the master can be recognized by surrounding mobile bodies, and a collision accident between the master and the mobile body can be prevented in advance.

  Moreover, the autonomous mobile device 1 according to the present embodiment estimates the boundary line between the visible area and the blind spot area of the moving object, and moves the autonomous mobile device 1 to the estimated boundary line. Therefore, since the autonomous mobile device 1 enters the visible area of the moving body, it is possible to make the occupant of the moving body recognize that a person is coming specifically.

  Further, the autonomous mobile device 1 according to the present embodiment has data of a visible area and a blind spot area based on the moving body, and applies the data to the moving body recognized by the surrounding environment recognition means, Estimate the boundary line between the visible area and the blind spot area. Therefore, the autonomous mobile device 1 can relatively easily estimate the boundary line between the visible area and the blind spot area of the moving body.

  In addition, the autonomous mobile device 1 according to the present embodiment recognizes an obstacle existing around the moving body, and estimates a blind spot area of the moving body due to the recognized obstacle. Therefore, the autonomous mobile device 1 can alert the moving body in consideration of the blind spot area of the moving body due to the obstacle.

  Although the embodiments of the present invention have been described above, the present invention is not limited to the above-described embodiments, and various modifications can be made. For example, as means for recognizing the master and the surrounding environment, sensors such as laser radar and millimeter wave radar may be used in addition to the camera 10 and the communication device 12 described above.

  Moreover, in the said embodiment, although the wheel 36 and the electric motor 34 were used as a moving means and its driving force source of the autonomous mobile device 1, a moving means and its driving force source should be restricted to the wheel 36 and the electric motor 34. For example, a caterpillar or a small engine can be used.

It is a block diagram which shows the structure of the autonomous mobile apparatus which concerns on this embodiment. It is a flowchart which shows the flow of the alerting process of an autonomous mobile device. It is a 1st schematic diagram which shows the visual field area and blind spot area of a moving body. It is a 2nd schematic diagram which shows the visual field area and blind spot area of a moving body. It is a 1st schematic diagram which shows the specific operation example of an autonomous mobile apparatus. It is a 2nd schematic diagram which shows the specific operation example of an autonomous mobile apparatus.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Autonomous mobile device, 10 ... Camera, 12 ... Communication apparatus, 13 ... Transmitter, 14 ... Receiver, 22 ... Visual field area and blind spot area estimation part, 26 ... Actuator control part, 30 ... Speaker, 32 ... Back light, 34 ... Electric motor, 36 ... Wheel, 42 ... Input device, 44 ... Display.

Claims (4)

In an autonomous mobile device that moves autonomously around a specific person,
Ambient environment recognition means for recognizing the specific person and the surrounding environment;
Blind spot area estimating means for estimating a blind spot area of a moving object existing around the specific person;
When the specific person moves in the blind spot area, attention calling means for calling attention to the moving body;
An autonomous mobile device comprising: The blind spot area estimating means estimates a boundary line of a visible area and a blind spot area of a moving object,
The autonomous mobile device according to claim 1, wherein the alerting means moves the autonomous mobile device to a boundary estimated by the blind spot area estimating means.   The blind spot area estimating means has data of a visible area and a blind spot area based on a moving object, and applies the data to the moving object recognized by the surrounding environment recognition means, so that the visible area and blind spot of the moving object are obtained. The autonomous mobile device according to claim 2, wherein the boundary line of the area is estimated. The surrounding environment recognition means recognizes an obstacle existing around the moving body,
The autonomous moving apparatus according to any one of claims 1 to 3, wherein the blind spot area estimating unit estimates a blind spot area of a moving body due to the obstacle recognized by the surrounding environment recognizing unit.

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