JP6474244B2 - Tire wear determination device and autonomous mobile device - Google Patents

Description

  The present invention relates to a tire wear determination device and the like.

  Conventionally, it has been common for humans to visually check road conditions and detect tire abnormalities. For example, a method of measuring the depth of a tire groove with a dedicated remaining groove measuring device when the vehicle is stopped or visually confirming the appearance of a slip sign has been performed (for example, see Patent Document 1).

  Recently, a plurality of tire wear detection devices have been disclosed for detecting tire wear (see, for example, Patent Document 2 and Patent Document 3).

Japanese Utility Model Publication No. 56-120901 JP 2011-189795 A JP 2014-178271 A

  At present, autonomous mobile devices that patrol a predetermined patrol route are appearing. This autonomous mobile device is an unmanned small mobile device, and is used for patrol, for example. Therefore, it is necessary to circulate the circulation route at a predetermined interval.

  For example, when the wear of a tire is measured visually as in the prior art, there is a problem that the autonomous mobile device must be stopped each time and the patrol operation must be stopped.

  Further, the tire wear detection devices such as Patent Document 2 and Patent Document 3 need to be separately provided on a tire or a vehicle body. In particular, there is no problem if the vehicle is a large vehicle such as a car on which a human is boarded. However, in a small autonomous mobile device, there is a space problem in providing such a device on a tire, and it is difficult to mount.

  In view of the above-described problems, an object of the present invention is to provide a tire wear determination device and the like that can determine tire wear with simple means without providing a separate device for the tire or the vehicle body. is there.

In view of the above-described problems, the tire wear determination device of the present invention is
A reference point detecting means for detecting a reference point from the position information;
First position detecting means for detecting a reference object at a reference point and detecting a first position of the reference object;
Second position detecting means for detecting, as a second position, the position of the reference object after the vehicle body turns at the reference point;
Wear that calculates the absolute value of the difference between the difference between the current first position and the second position value and the difference between the first position and the second position value when the tire is not worn as a wear determination value. A judgment value calculating means;
When the wear determination value exceeds a determination threshold, wear determination means for determining that the tire is in a worn state;
It is characterized by providing.

The autonomous mobile device of the present invention is
In an autonomous mobile device comprising position information acquisition means and image input means for taking a forward image,
Storage means for storing learning information including a determination value when the tire is not in a worn state, and a determination threshold;
Reference point detection means for detecting a reference point from the position information acquired by the position information acquisition means;
Reference object detection means for detecting a reference object from the captured image at the reference point;
Calculating means for detecting again the position of the reference object from the captured image after turning the vehicle body at the reference point, and calculating a pixel difference from the reference object detected by the reference object detection means;
When the difference between the pixel difference and the determination value exceeds a determination threshold, wear determination means for determining that the tire is in a worn state;
It is characterized by providing.

  According to the present invention, the reference point detecting means for detecting the reference point from the position information, the first position detecting means for detecting the reference object at the reference point and detecting the first position of the reference object, and the reference point A second position detecting means for detecting the position of the reference object after the turning operation of the vehicle body as a second position; a difference between the current first position and the second position value; and a state in which the tire is not worn The absolute value of the difference between the first position and the second position value is calculated as a wear determination value, and when the wear determination value exceeds the determination threshold, it can be determined that the tire is in a worn state. . Thus, it is possible to determine whether or not the tire is worn only by performing a turning operation at a fixed position.

It is a figure for demonstrating the whole autonomous mobile apparatus. It is a figure for demonstrating the whole autonomous mobile apparatus. It is a figure for demonstrating the function structure of the autonomous mobile apparatus in 1st Embodiment. It is a figure for demonstrating a patrol route. It is an operation | movement flow about the learning preservation | save process in 1st Embodiment. It is a figure for demonstrating the operation example in 1st Embodiment. It is a figure for demonstrating the operation example in 1st Embodiment. It is an operation | movement flow about the abrasion determination process in 1st Embodiment. It is a figure for demonstrating the function structure of the autonomous mobile apparatus in 2nd Embodiment. It is a figure for demonstrating the function structure of the autonomous mobile apparatus in 3rd Embodiment. It is an operation | movement flow about the learning preservation | save process in 3rd Embodiment. It is an operation | movement flow about the abrasion determination process in 3rd Embodiment. It is an operation | movement flow in 4th Embodiment. It is an operation | movement flow in 5th Embodiment. It is an operation | movement flow in 6th Embodiment. It is an operation | movement flow in 7th Embodiment.

  Embodiments of the present invention will be described below with reference to the drawings. In the present embodiment, as an example, an example in which the present invention is applied to an autonomous mobile device to which the wear detection device according to the present invention is applied will be described.

[1. First Embodiment]
[1.1 Overall configuration]
First, the autonomous mobile device 1 in this specification will be described with reference to FIGS. 1 and 2. FIG. 1 is a diagram schematically showing the autonomous mobile device 1 from the side, and FIG. 2 is a diagram schematically showing the autonomous mobile device 2 from the top.

  The autonomous mobile device 1 has a clamshell structure in which a vehicle body 10 and an arm portion 20 are connected by a hinge portion. In addition, a position detection unit / fault detection unit is provided at the tip of the arm unit 20. For example, by providing a visual sensor (such as a camera) that can photograph the front of the vehicle body, the image of the front of the vehicle body is analyzed to detect a position or a failure is detected. Further, it is possible to recognize a specific object (reference object / reference point) by performing image processing such as edge detection from the acquired image.

  The vehicle body 10 is provided with four wheels 12. The wheels 12 are connected to the right side and the left side by endless belts 14 so that the wheels are driven. The endless belt 14 is driven by the driving force of the driving motor 16 and is connected via a gear 18.

  The drive motor 16 is driven by electric power supplied from the battery 40. The left and right drive motors 16 can be operated, and the right wheel 12 and the left wheel 12 can be driven separately.

  Here, the autonomous mobile device 1 of the present embodiment has wheels (four wheels) and is capable of stationary turning (superficial turning) as a turning operation. The drive motor 16 is provided with an encoder, and can be controlled by detecting the rotation speed of the drive motor 16. In other words, it is an unmanned autonomous mobile device that is capable of quantitative turning unlike a car on which a human is boarded.

[1.2 Functional configuration]
Next, the functional configuration of the autonomous mobile device 1 in the present embodiment will be described with reference to FIG. As shown in FIG. 3, a control unit 110, an image input unit 120, an image processing unit 130, a storage unit 140, a GPS reception unit 150, and a drive control unit 160 are connected to each other.

  The control unit 110 is a functional unit for controlling the entire autonomous mobile device 1. The control unit 110 implements various functions by reading and executing various programs stored in the storage unit 140, and includes, for example, a CPU (Central Process Unit).

  The image input unit 120 is a functional unit for inputting an image, and the input image is output to the image processing unit 130 as image data.

  The image processing unit 130 is a functional unit that performs various types of image processing based on the image data input from the image input unit 120. For example, it is possible to detect an obstacle or to detect a reference point described later.

  The storage unit 140 is a functional unit that stores various programs and various data necessary for the operation of the autonomous mobile device 1. The storage unit 140 includes, for example, a semiconductor memory, an HDD (Hard Disk Drive), or the like. Each information may be stored on the cloud server. In this case, various data and programs may be stored in the cloud server via a communication unit (not shown) and read out each time.

  The storage unit 140 stores reference object information 142, learning information 144, determination threshold information 146, and tour information 148. Details of the reference object information 142 and the learning information 144 will be described later.

  The determination threshold value information 146 stores various threshold values. For example, a wear determination threshold value is stored, and when the threshold value is exceeded, it is determined that the tire is worn.

  The tour information 148 stores map information (location information) that the autonomous mobile device 1 in the present embodiment patrols. For example, as shown in FIG. 4, when a route with a thick line is a cyclic route, this cyclic route is stored. The autonomous mobile device 1 can autonomously move the position of the thick line based on the tour information 148. As a result, it can be used for security patrols and the like.

  The GPS receiving unit 150 is a functional unit for receiving a signal from a GPS (Global Positioning System) satellite and outputting position information of the autonomous mobile device 1.

  The drive control unit 160 is a functional unit for controlling the driving of the autonomous mobile device 1 (for example, the drive motor 16 in FIG. 2). By controlling the drive motor 16, operations such as forward movement, backward movement, and turning are possible.

[1.3 Process flow]
Next, the flow of processing in this embodiment will be described. First, a reference point serving as a reference is detected, and processing for storing learning information including a determination value (learning information storage processing) is executed. And the abrasion of a tire (wheel) is determined by performing a wear determination process.

  Here, the learning information includes a value in a state where the tire is not worn (for example, a state after a new tire is mounted, or a state where the tire groove has a normal value or more) as a determination value. In this learning information, for example, the number of pixels in a state where the tire is not worn, the angle, the value such as azimuth information, the normal value of a parameter used for wear determination such as a difference, and the like are stored as the determination value. ing.

  That is, a value for determining whether or not the wear state is present during an operation in a wear determination process described later is included. In addition, parameters such as the position of the reference point and the road surface condition may be stored in the learning information. This learning information may be stored in advance or downloaded from the cloud. In this embodiment, the case where the autonomous mobile device 1 generates learning information will be described below.

[1.3.1 Learning information storage process]
First, the learning information storage process will be described with reference to FIG. First, the position information of the autonomous mobile device 1 is detected and a reference point is determined (step S102). Usually, when learning information is stored, it is necessary to perform the learning at the same position, so the position information is determined as a reference point. For example, it is performed at the same place as a base (base), a charging place, or a standby place.

  If position information cannot be detected, processing such as detecting position information again may be performed. In addition, the position information of the present embodiment is detected from the GPS signal received by the GPS receiving unit 150, but other methods (for example, the traveling information and the position information based on the moving distance are detected or the traveling is performed. The detection may be based on the position information received from the position information output device provided in the place, or the position information may be detected from the image data input by the image input unit 120).

  Here, the reference object is detected from the input image, and the position of the reference object is detected (step S104). What is detected as the reference object may be set in advance, or may be arbitrarily set with reference to image data. Further, the detected reference object is stored as reference object information 142 together with the reference point.

  After the reference object is detected, a certain amount of turning motion is performed (step S106). Here, after performing a certain amount of turning operation, the reference object is detected again, and the position of the reference object is detected (step S108). If the reference object cannot be detected, error reprocessing is executed (step S114), and this process is executed again (step S102).

  Here, the error reprocessing may be processing such that the turning operation is performed again (that is, the reverse turning operation is performed), or processing for allowing the user to select a procedure. Alternatively, the learning storage data processing may simply be aborted as an error.

  If the reference object can be detected (step S108; Yes), the difference between the position of the reference object detected in step S104 and the position of the reference object detected in step S108 is calculated (step S110). Then, the difference calculated in step S110 is stored as learning information 144 in association with the reference object (step S112).

  Here, reference object recognition will be described with reference to the drawings. For example, FIG. 6 shows the state when the reference object is detected in step S104 of FIG.

  First, an image is captured at the reference point by the image input unit 120 (for example, a camera). At this time, image processing is performed, a reference object is detected, and a position (for example, X coordinate) in the image is calculated.

  Here, it is assumed that the reference object is an extension having a diameter of about 30 cm (for example, a utility pole). As an example, edge detection can be considered as image processing for detecting a reference object, but it may be detected by other methods such as recognition by the color of the object.

  Next, by receiving the information of the encoder, the drive motor 16 is rotated by a certain amount, and the ground is turned. After the turning operation, an image is taken in the same manner, and the position of the reference object is calculated in the same manner.

  The state of the autonomous mobile device 1 at this time is shown in FIG. In FIG. 7A, after recognizing the reference object, a turning operation is performed. For example, as shown in FIG. 7B, the turning operation is performed in the R direction. Then, the position of the reference object changes and the difference D is calculated. This difference D is the amount by which the reference object has moved as shown in the lower diagram of FIG. Then, the movement amount (difference D) of the reference object is stored as learning information.

  This will be explained using specific values. First, when the horizontal width of the image is 1920 pixels, the difference D is calculated as 600 pixels. In this case, 600 pixels are stored as learning information. In the present embodiment, the amount of movement of the reference object is described using pixels. However, for example, it may be obtained as a ratio (%) to the horizontal width.

[1.3.2 Wear determination processing]
Next, the wear determination process will be described with reference to FIG. First, a reference point is detected from position information (step S152), and a reference object is detected when the reference point is reached (step S154). When the reference object is detected, the position of the reference object is detected, and then a certain amount of turning operation is performed (step S156). Then, the position of the reference object after the turning motion is detected (step S158), and if the reference object cannot be detected, error reprocessing is executed (step S158; No → step S162).

  If a reference object is detected, the difference between the position of the reference object before turning and the position of the reference object after turning is calculated (step S158; Yes → step S160). Here, steps S152 to S160 and S162 of the wear determination process are the same as steps S102 to SS110 and S114 of the learning information storage process of FIG.

  Further, it is assumed that the constant force turning operation in step S156 is applied with the same force as the constant amount turning operation in step S106. That is, the same rotational speed is given to the drive motor 16. Here, when the tire is worn, even if the rotation speed of the motor is the same, the tire is idle, the rotation amount of the vehicle body is small, and the movement amount of the reference object in the image is also small.

  Subsequently, the learning information 144 is read (step S170), and a wear determination value is calculated from the difference between the calculated difference and the difference stored in the learning information 144 (step S172). The wear determination value is an absolute value of the difference between the above differences, and when the determination threshold value stored in the determination threshold information 146 is exceeded, it is determined that the tire is worn due to idle rotation ( Step S174; Yes → Step S178). On the other hand, when the wear determination value does not exceed the determination threshold value, it is determined to be normal (step S174; No → step S176).

As a specific example, it is assumed that the tire is worn and the difference in the movement amount is calculated as 300 pixels. In this case, for example, when the threshold value is 200 pixels, as described above, the difference is 600 pixels in the normal state (the tire is not worn, the idle state is not generated).
Abrasion judgment value | 600−300 | = 300 pixels> judgment threshold (200 pixels)
It becomes. Therefore, it is determined that wear due to idling has occurred.

  Thus, according to the present embodiment, it is possible to determine that a predetermined grip force or the like cannot be exhibited due to wear of the tire by simply performing a certain amount of turning operation. Therefore, it is possible to easily determine whether or not the tire is worn without making a visual check or providing a dedicated device.

[2. Second Embodiment]
Next, the second embodiment will be described. In the second embodiment, an embodiment in which an LRF (laser range finder) is used instead of image processing for obstacle detection will be described.

  Here, the functional configuration of the autonomous mobile device 2 in the second embodiment will be described with reference to FIG. As shown in FIG. 9, the autonomous mobile device 2 according to the second embodiment includes a control unit 110, a storage unit 140, a GPS reception unit 150, a drive control unit 160, and an LRF 210.

  The LRF 210 is a laser sighting machine, and detects an obstacle or each object by using a laser.

  Specifically, the distance from the irradiation point is measured by looking at the time (or phase difference, etc.) from the laser irradiation until the reflected light is detected.

  The two-dimensional scanning type can detect the position / distance of an obstacle at a certain height by scanning the laser two-dimensionally (horizontal direction). The three-dimensional scanning type is basically the same as the two-dimensional scanning type, but enables three-dimensional distance measurement by scanning not only in the horizontal direction but also in the vertical direction. .

  The LRF of this embodiment may be either a two-dimensional scanning type or a three-dimensional scanning type. Further, for the detection of the reference object, the position of the reference object can be detected by detecting an edge having a large distance difference.

  In the present embodiment, by using the LRF 210, for example, processing such as image capturing, image input, and image processing becomes unnecessary.

  The other functional configurations of the first embodiment are the same, and the learning information storage process and the wear determination process are the same, and thus detailed description thereof is omitted.

[3. Third Embodiment]
Next, a third embodiment will be described. The third embodiment describes an embodiment in which the autonomous mobile device is equipped with a geomagnetic sensor and wear determination is performed based on the geomagnetic sensor.

[3.1 Functional configuration]
Here, the functional configuration of the autonomous mobile device 3 in the third embodiment will be described with reference to FIG. The autonomous mobile device 3 includes a control unit 110, an image input unit 120, a storage unit 140, a GPS reception unit 150, a drive control unit 160, and a geomagnetic sensor unit 310.

  The geomagnetic sensor unit 310 is a geomagnetic sensor (orientation sensor) and is a functional unit that can detect the direction in which the autonomous mobile device 3 is facing. When the azimuth sensor is used, it is possible to obtain information on which body is facing directly from the data received from the sensor. Therefore, the reference point detection is performed in comparison with the first embodiment and the second embodiment. This processing is unnecessary.

  In addition, since the direction has a clear reference, it is possible to turn anywhere and detect a tire abnormality, so that an effect that the condition of the reference position can be relaxed can be expected. However, if the road surface condition is not constant, care must be taken because the slippage varies.

  The functional configuration of the third embodiment is the same as that of the first embodiment with respect to the functional configuration other than the geomagnetic sensor, and a description thereof will be omitted. In the present embodiment, the image input unit 120 is a functional unit that is used to detect an obstacle or the like. For example, the LRF 210 described in the second embodiment may be used instead.

[3.2 Process flow]
Next, a processing flow in the third embodiment will be described with reference to the drawings.

[3.2.1 Learning information storage process]
First, the learning information storage process will be described with reference to FIG. First, the direction information of the autonomous mobile device 3 is detected (step S302). If the azimuth detection is successful, the detected azimuth information (for example, “an angle such as 90.5 degrees”) is stored as the reference object information 142.

  Thereafter, a certain amount of turning operation is performed (step S304; Yes → step S306), and the direction information is detected again (step S308).

  If the direction detection has failed, error processing is executed (step S320). With error processing, it is good also as detecting azimuth | direction information again, and you may perform a process again from step S302.

  Subsequently, when the azimuth detection is successful and the azimuth information is detected, the azimuth information is compared with the azimuth information stored in the reference object information 142, and the difference is calculated (step S310; Yes → step S312). The calculated difference is stored as learning information 144 (step S314), and this process ends.

[3.2.2 Wear determination processing]
Next, the wear determination process will be described with reference to FIG. First, orientation information is detected (step S352). When the azimuth detection is successful and the azimuth information is detected, a certain amount of turning operation is performed (step S354; Yes → step S356).

  Then, the direction information after the turning motion is detected (step S358), and when the direction cannot be detected, error reprocessing is executed (step S360; No → step S370).

  When the direction information is detected, the difference between the direction information in step S352 and the direction information in step S358 is detected (step S360; Yes → step S362).

  Subsequently, the learning information 144 is read (step S364), and the absolute value of the difference between the calculated difference and the difference stored in the learning information 144 is calculated as a wear determination value (step S366). Here, when the wear determination value exceeds the determination threshold for determining wear stored in the determination threshold information 146, it is determined that the tire is worn (step S368; Yes → step S374). On the other hand, when the wear determination value does not exceed the determination threshold value, it is determined to be normal (step S368; No → step S372).

For example, it is assumed that the rotation amount in the learning information storing process is 30 degrees and the threshold value is 5 degrees. And when the rotation amount in the wear determination process is 22 degrees, the difference is
Wear judgment value | 30-22 | degree | degree = 8 degree> judgment threshold value (5 degree)
It becomes. Therefore, it is determined that the tire is worn.

[4. Fourth Embodiment]
Next, a fourth embodiment will be described. The fourth embodiment is an embodiment in which the wear level is determined in a plurality of stages by having a plurality of determination thresholds.

  FIG. 13 is a flowchart for explaining the flow of processing of this embodiment. FIG. 13 is obtained by replacing the processing after step S172 of FIG. 8 in the first embodiment.

  First, a wear determination value is calculated from the absolute value of the difference between the difference and the difference stored in the learning information 144 (step S172). When the calculated wear determination value is equal to or less than the first threshold value, it is determined that the wear is normal (step S402; No → step S404). Here, when the wear determination value is greater than the first threshold value and equal to or less than the second threshold value, the wear level is determined to be level 1 (step S402; Yes → Step S406; No → Step S408).

  When the wear determination value exceeds the second threshold, the wear level is determined to be level 2 (step S402; Yes → Step S406; Yes → Step S410).

  Thus, according to the present embodiment, it is possible to determine a plurality of wear levels. Thereby, for example, in the case of the wear level 1, it is possible to call attention, and in the wear level 2, it is possible to stop the operation or change the moving speed of the autonomous mobile device according to the wear level.

[5. Fifth Embodiment]
Next, a fifth embodiment will be described. In addition to the fourth embodiment, the fifth embodiment is an embodiment in which a turning operation is performed at predetermined intervals.

  The wear determination process is performed, for example, at a fixed time every day or at the end of the tour. In this case, when the wear determination process is executed, a turning operation is performed. Therefore, there is a user who thinks that the tire is worn by the turning operation.

  Therefore, an embodiment will be described in which the turning operation is not performed so much while the wear level is normal, and the frequency is increased when the wear level is advanced.

  In addition, this embodiment is combined with 4th Embodiment (1st Embodiment), and the wear level determined in 4th Embodiment is used. Further, the operation flow of FIG. 14 is processing in which steps S152 to S156 of FIG. 8 are replaced.

  First, a reference point is detected from position information (step S152), and when a reference object is detected (step S154), it is determined whether or not the wear level is normal (step S502). When the wear level is normal, 1 is added to the determination variable n (step S502; Yes → step S504). If the wear level is 1, 2 is added to the variable n (Step S502; No → Step S506; Yes → Step S508). If the wear level is 2, 3 is added to the variable n (Step S502). No → Step S506; No → Step S510).

  And when the variable n is 3 or more, the variable n is cleared (step S512; Yes-> step S514), and a fixed amount turning operation | movement is performed (step S156).

  Thus, if the wear level is normal, the turning operation is executed about once every three times, about once every two times when the wear level is 1, and every time when the wear level is two.

[6. Sixth Embodiment]
Subsequently, a sixth embodiment will be described. The sixth embodiment is an embodiment in which idling is detected by changing the acceleration.

  This is because the slipperiness varies depending on the acceleration method (sudden acceleration is more likely to cause idling), so the speed acceleration should be tested step by step to determine which acceleration method caused the idling. Thus, it becomes possible to evaluate the wear state of the tire in stages. In the case of a DC motor, there are PWM control, PAM control, etc., but if the former, the rotation speed of the motor can be controlled by changing the duty ratio, and if the latter, the output voltage value is changed.

  FIG. 15 is an operation flow when combined with the third embodiment. For example, in steps S354 to S362, the acceleration is changed in order of A1, A2,..., An (step S602). In this case, A1 <A2 <... <An.

  Thereby, it is determined at which acceleration the wear determination value has exceeded the determination threshold value for the first time (threshold determination processing (step S604)). In addition, it is possible to determine the wear level by changing a plurality of determination thresholds.

  Moreover, it is good also as a process which escapes from the loop of step S602 in the threshold value determination process, when a wear determination value exceeds the determination threshold value.

[7. Seventh Embodiment]
Subsequently, a seventh embodiment will be described. The seventh embodiment is a process of changing the operation speed of the autonomous mobile device 1 based on the determined wear level. This process may be executed after the wear determination process of each embodiment.

  That is, when the wear level is normal, the operation speed is set to “5 km / h” (step S702; Yes → step S704). When the wear level is “1”, the operation speed is set to “3 km / h” (Step S702; No → Step S706; Yes → Step S708). When the wear level is “2”, the operation speed is set to “1 km / h” (Step S702; No → Step S706; No → Step S710).

  Thus, by applying this embodiment, it is possible to change the operation speed of the autonomous mobile device.

  As described above, when the invention of the present specification is applied, the ease of slipping in an actual environment can be evaluated by evaluating data at the time of ground turning in an actual machine body, for example. Also, because the tires are worn, it is possible to detect if slippery conditions occur during turning while traveling, and it is possible to take measures such as slowing the speed of the aircraft Become. As a result, it is possible to prevent dangers such as sliding and collision in autonomous driving.

[8. Modified example]
The embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to this embodiment, and the design and the like within the scope of the present invention are also within the scope of the claims. include.

  In the above-described embodiment, the tire (wheel) has been described as the wear determination. However, the wear determination / consumption determination can be similarly performed if a turning operation / rotation operation is used. For example, when the arm portion rotates, by detecting the reference point when the arm portion is rotated, for example, it is possible to detect a state such as the wear state of the rotating portion and the condition of the bearing.

  In addition, the program that operates in each device in the embodiment is a program (a program that causes a computer to function) that controls the CPU and the like so as to realize the functions of the above-described embodiments. Information handled by these devices is temporarily stored in a temporary storage device (for example, RAM) at the time of processing, then stored in various ROM or HDD storage devices, and read and corrected by the CPU as necessary. • Writing is performed.

  In addition, when distributing to the market, the program can be stored and distributed in a portable recording medium, or transferred to a server computer connected via a network such as the Internet. In this case, of course, the storage device of the server computer is also included in the present invention.

DESCRIPTION OF SYMBOLS 1 Autonomous mobile device 110 Control part 120 Image input part 130 Image processing part 140 Storage part 142 Reference | standard object information 144 Learning information 146 Judgment threshold value information 148 Travel information 150 GPS receiving part 160 Drive control part

Claims (6)

A reference point detecting means for detecting a reference point from the position information;
First position detecting means for detecting a reference object at a reference point and detecting a first position of the reference object;
Second position detecting means for detecting, as a second position, the position of the reference object after the vehicle body turns at the reference point;
Wear that calculates the absolute value of the difference between the difference between the current first position and the second position value and the difference between the first position and the second position value when the tire is not worn as a wear determination value. A judgment value calculating means;
When the wear determination value exceeds a determination threshold, wear determination means for determining that the tire is in a worn state;
A tire wear determination device comprising: It further comprises image input means for inputting an image,
The tire wear determination apparatus according to claim 1, wherein a reference object is recognized and determined from the image. A laser sighting machine,
The tire wear determination apparatus according to claim 1, wherein the laser sighting machine recognizes and determines a reference object by irradiating a laser. In a tire wear determination device equipped with a geomagnetic sensor,
A reference point detecting means for detecting a reference point from the position information;
First detection means for detecting first orientation information by the geomagnetic sensor at a reference point;
Second detection means for detecting second azimuth information from the geomagnetic sensor after the vehicle turns at a reference point;
The absolute value of the difference between the difference between the current first orientation information and the second orientation information and the difference between the first orientation information and the second orientation information when the tire is not worn is calculated as the wear determination value. Wear judgment value calculating means for
When the wear determination value exceeds a determination threshold, wear determination means for determining that the tire is in a worn state;
A tire wear determination device comprising:   An autonomous mobile device equipped with the tire wear determination device according to any one of claims 1 to 4. In an autonomous mobile device comprising position information acquisition means and image input means for taking a forward image,
Storage means for storing learning information including a determination value when the tire is not in a worn state, and a determination threshold;
Reference point detection means for detecting a reference point from the position information acquired by the position information acquisition means;
Reference object detection means for detecting a reference object from the captured image at the reference point;
Calculating means for detecting again the position of the reference object from the captured image after turning the vehicle body at the reference point, and calculating a pixel difference from the reference object detected by the reference object detection means;
Wear determination means for determining that the tire is in a worn state when the difference between the pixel difference and the determination value exceeds a determination threshold;
An autonomous mobile device comprising:

Images