JP2016057196A - Electronic device and correction program of angular velocity detection value - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an electronic device and a correction program of an angular velocity detection value that shorten a time taken to remove an error while performing autonomous navigation.SOLUTION: An electronic device performs autonomous navigation. A threshold of angular velocity of the electronic device subject to removal during autonomous navigation is determined based on a change in acceleration of the electronic device. During autonomous navigation, it is determined whether a detection value by an angular velocity sensor 6 for detecting the angular velocity of the electronic device is smaller than the threshold. When it is determined that the detection value is smaller than the threshold, autonomous navigation is performed by setting the detection value at 0; when it is determined that the detection value is equal to or greater than the threshold, autonomous navigation is performed using the detection value.SELECTED DRAWING: Figure 3

Description

  The present invention relates to an electronic device and an angular velocity detection value correction program.

  In recent years, smart devices such as smartphones have become widespread, and devices that perform autonomous navigation using position measurement by GPS (Global Positioning System) are also widespread. In addition, smart devices that perform autonomous navigation using an angular velocity sensor and an acceleration sensor have become widespread even indoors where GPS signals cannot be acquired.

  The small vibratory angular velocity sensor installed in smart devices is error-prone due to a static bias that fluctuates due to temperature, aging, etc., or a bias caused by vibration (hereinafter sometimes referred to as “dynamic bias”). Arise. For this reason, removal of static bias and dynamic bias is performed.

  For example, a technique is known in which stationary is determined by acceleration, the output value of the angular velocity sensor at that time is stored as a static bias amount, and the static bias amount is removed from the output value of the angular velocity sensor at the time of position measurement. Yes. Also, the estimated position, actual position, acceleration, and angular velocity are input to the Kalman filter, and the error of the acceleration sensor including the dynamic bias and the error of the angular velocity sensor are continuously estimated. A technique for removing from the output value of the sensor is known.

JP 2001-242192 A Japanese Patent Laid-Open No. 06-109477

  However, in the above technique, it takes time to remove the error including the dynamic bias amount. Specifically, it is determined whether the user who owns the smart device is walking, stopped, or moving, and the error is estimated after switching to a parameter suitable for the user's state at any time. It takes time. In addition, since it takes time until the error is estimated, the accuracy of autonomous navigation also decreases.

  The disclosed technology has been made in view of the above, and an object thereof is to provide an electronic device and an angular velocity detection value correction program capable of shortening the time required for error removal during execution of autonomous navigation.

  The electronic device performs autonomous navigation. The electronic device includes a determination unit that determines a threshold value of an angular velocity of the electronic device to be removed during the autonomous navigation based on a change in acceleration of the electronic device. The electronic device includes a determination unit that determines whether a detection value by an angular velocity sensor that detects an angular velocity of the electronic device is less than the threshold during the autonomous navigation. When the detected value is determined to be less than the threshold, the electronic device performs the autonomous navigation with the detected value set to 0. When the detected value is determined to be equal to or greater than the threshold, the electronic device uses the detected value to It has an execution part which performs autonomous navigation.

  According to one embodiment, it is possible to reduce the time taken to remove errors when performing autonomous navigation.

FIG. 1 is a diagram for explaining autonomous navigation by a mobile terminal according to the first embodiment. FIG. 2 is a diagram illustrating a hardware configuration example of the mobile terminal according to the first embodiment. FIG. 3 is a functional block diagram illustrating a functional configuration of the mobile terminal according to the first embodiment. FIG. 4 is a flowchart illustrating a flow of processing executed by the mobile terminal according to the first embodiment. FIG. 5 is a diagram for explaining the relationship between the threshold and the dynamic bias. FIG. 6 is a diagram for explaining the relationship between the change in threshold and the dynamic bias. FIG. 7 is a diagram illustrating autonomous navigation based on threshold control. FIG. 8 is a diagram for explaining the autonomous navigation when the bias is estimated. FIG. 9 is a diagram for explaining the autonomous navigation when the threshold value is fixed to a small value. FIG. 10 is a diagram illustrating the autonomous navigation according to the first embodiment.

  Embodiments of an electronic device and an angular velocity detection value correction program disclosed in the present application will be described below in detail with reference to the drawings. Note that the present invention is not limited to the embodiments.

[Autonomous navigation of mobile terminals]
FIG. 1 is a diagram for explaining autonomous navigation by a mobile terminal according to the first embodiment. A mobile terminal 1 shown in FIG. 1 is an electronic device such as a smartphone or a mobile phone. The mobile terminal 1 performs autonomous navigation using acceleration and angular velocity. For example, as shown in FIG. 1, the mobile terminal 1 can detect and record the walking trajectory of the user who owns the mobile terminal 1 and measure the current position of the user.

  The angular velocity sensor of the mobile terminal 1 is generally a vibration type gyro sensor, and a bias component (hereinafter sometimes referred to as a dynamic bias) appears in the angular velocity output due to external acceleration. The amount of the dynamic bias is different from the bias that appears when the mobile terminal 1 is stationary (hereinafter sometimes referred to as a static bias). The magnitude of the dynamic bias is proportional to the acceleration from the outside. For example, when the user puts the mobile terminal 1 in the breast pocket, the dynamic bias amount is small, and when the mobile terminal 1 is put in the trouser pocket, the dynamic bias amount becomes large. The mobile terminal 1 estimates and eliminates this dynamic bias amount to improve the accuracy of autonomous navigation.

  Specifically, the mobile terminal 1 determines the threshold value of the angular velocity of the mobile terminal 1 to be removed during autonomous navigation based on the change in acceleration of the mobile terminal 1. And the mobile terminal 1 determines whether the detection value by the angular velocity sensor which detects the angular velocity of the mobile terminal 1 is less than a threshold value at the time of autonomous navigation. Thereafter, when the detected value is determined to be less than the threshold value, the mobile terminal 1 performs autonomous navigation with the detected value set to 0. When the detected value is determined to be equal to or greater than the threshold value, the mobile terminal 1 executes the autonomous navigation using the detected value. To do.

  That is, the mobile terminal 1 removes the angular velocity below the threshold determined by the magnitude of the vibration of the mobile terminal 1 as a dynamic bias component during the autonomous navigation of the mobile terminal 1, thereby reducing the angular velocity below the threshold. Is considered straight ahead. As a result, the mobile terminal 1 can shorten the time required for bias removal.

[Hardware configuration]
FIG. 2 is a diagram illustrating a hardware configuration example of the mobile terminal according to the first embodiment. As shown in FIG. 2, the mobile terminal 1 includes a wireless unit 2, an audio input / output unit 3, a storage unit 4, an acceleration sensor 5, an angular velocity sensor 6, a touch sensor unit 7, a display unit 8, and a processor 10.

  The wireless unit 2 is a circuit or the like that performs wireless communication with other terminals via the antenna 2a. The audio input / output unit 3 is a circuit that outputs sound from the speaker 3a and executes various processes on the sound collected by the microphone 3b.

  The storage unit 4 is a storage device that stores programs executed by the processor 10 and various data, and is a memory or a hard disk, for example.

The acceleration sensor 5 is a sensor that measures the acceleration (unit: m / s ² , Gal, G, etc.) of the mobile terminal 1, and inputs the measured acceleration to the processor 10. This acceleration sensor 5 is a three-axis sensor and measures the acceleration of each axis of x, y, and z.

  The angular velocity sensor 6 is a gyro sensor that measures the angular velocity (unit: dps) of the mobile terminal 1, and inputs the measured angular velocity to the processor 10. This angular velocity sensor 6 is a triaxial sensor and measures the angular velocity of each axis of x, y, and z.

  The touch sensor unit 7 is a circuit or the like that detects a user's operation on the display unit 8, and the display unit 8 is a display device that displays various types of information. For example, a touch panel or the like is provided by the touch sensor unit 7 and the display unit 8.

  The processor 10 is an electronic circuit or the like that controls the entire mobile terminal 1, reads out and expands a program stored in the storage unit 4, and executes various processes such as autonomous navigation.

[Function configuration]
FIG. 3 is a functional block diagram illustrating a functional configuration of the mobile terminal according to the first embodiment. As shown in FIG. 3, the mobile terminal 1 includes a fixed value DB 11, a static bias DB 12, a vibration determination unit 13, a threshold calculation unit 14, a dynamic bias determination unit 15, a direct evolution processing unit 16, and an autonomous navigation function unit 20. Have

  The fixed value DB 11 and the static bias DB 12 are databases held in the storage unit 4 or the like. The vibration determination unit 13, the threshold calculation unit 14, the dynamic bias determination unit 15, the direct evolution processing unit 16, and the autonomous navigation function unit 20 are examples of a part of an electronic circuit included in the processor 10 and a process executed by the processor 10. .

  The fixed value DB 11 is a database that stores the maximum value of the variance of acceleration of the mobile terminal 1 and the maximum value of the threshold value of the angular velocity of the mobile terminal 1 to be removed during the autonomous navigation of the mobile terminal 1. The maximum value of the variance value and the maximum value of the threshold value are designated in advance by the user or the like.

  The static bias DB 12 is a database that stores a static bias amount. Specifically, the static bias DB 12 stores the angular velocity of the mobile terminal 1 when the acceleration of the mobile terminal 1 is less than a predetermined value as a static bias amount. That is, the static bias DB 12 stores in advance a static bias amount in each of the three axes that occurs in the angular velocity sensor 6 when stopped.

  The vibration determination unit 13 is a processing unit that calculates a shaking index indicating the magnitude and degree of shaking of the mobile terminal 1. Specifically, the vibration determination unit 13 moves by monitoring the acceleration of the mobile terminal 1 because the magnitude of the dynamic bias tends to be proportional to the behavior during movement or walking and the intensity of vibration. Judgment of behavior and vibration magnitude.

  For example, the vibration determination unit 13 acquires the acceleration detected by the acceleration sensor 5 for a predetermined time such as several seconds. Then, the vibration determination unit 13 calculates a dispersion value of the acquired acceleration, and outputs the calculated dispersion value to the threshold value calculation unit 14 as a shake index. Further, the vibration determination unit 13 can also calculate the average value or difference between the acquired maximum and minimum acceleration values as a vibration index.

  The threshold calculation unit 14 is a processing unit that determines an angular velocity threshold to be removed when the mobile terminal 1 is autonomously navigation. Specifically, the threshold value calculation unit 14 reads the maximum value of the variance value and the maximum value of the threshold value from the fixed value DB 11 when the vibration index is input from the vibration determination unit 13. Subsequently, the threshold value calculation unit 14 calculates “threshold value = swing index / (maximum value of variance value × maximum value of threshold value)”. Then, the threshold calculation unit 14 outputs the range from the + threshold to the −threshold to the dynamic bias determination unit 15 as the acceleration to be removed.

  That is, since the magnitude of the dynamic bias amount tends to be proportional to the behavior during movement or walking or the intensity of vibration, the threshold calculation unit 14 determines the maximum angular velocity threshold (+ side proportional to the magnitude of vibration). ,-Side). For example, when the threshold value is calculated as α, the threshold value calculation unit 14 outputs the maximum threshold value “α value, −α value” to the dynamic bias determination unit 15.

  The dynamic bias determination unit 15 is a processing unit that determines whether or not the angular velocity (detected value) detected by the angular velocity sensor 6 is a removal target. Specifically, when the detected angular velocity is within the range of angular velocities notified from the threshold calculation unit 14, the dynamic bias determination unit 15 determines that the target is to be removed, and directly determines that the target is a removal target and the detected value. Output to the evolution processing unit 16. On the other hand, when the detected angular velocity is outside the range of the angular velocity notified from the threshold calculation unit 14, the dynamic bias determining unit 15 determines that the detected angular velocity is not a removal target, and directly evolves the detected value and the detected value. Output to the processing unit 16.

  The straight evolution processing unit 16 is a processing unit that determines the straightness of the mobile terminal 1. Specifically, if the detected angular velocity is within the threshold range, the straight evolution processing unit 16 estimates that the detected angular velocity is a dynamic bias amount, and regards the movement of the mobile terminal 1 as straight ahead. . Further, if the detected angular velocity is outside the threshold range, the straight evolution processing unit 16 estimates the detected angular velocity as an angular velocity generated when the mobile terminal 1 turns, and moves the mobile terminal 1 straight ahead. Consider it not.

  For example, when the dynamic bias determination unit 15 notifies that the detection value of the angular velocity sensor 6 is a removal target, the direct evolution processing unit 16 changes the detection value to 0 and sets the detection value to 0 as an autonomous navigation function. To the unit 20. That is, the direct evolution processing unit 16 executes autonomous navigation on the assumption that the current angular velocity of the mobile terminal 1 is zero.

  Further, when the dynamic bias determination unit 15 is notified that the detection value of the angular velocity sensor 6 is not to be removed, the direct evolution processing unit 16 reads the static bias amount from the static bias DB 12 and uses the detection value. A value obtained by subtracting the static bias amount is output to the autonomous navigation function unit 20. That is, the direct evolution processing unit 16 executes autonomous navigation on the assumption that the current angular velocity of the mobile terminal 1 is “detection value−static bias amount”.

  The autonomous navigation function unit 20 is a processing unit that executes autonomous navigation. Specifically, the autonomous navigation function unit 20 performs autonomous navigation using the angular velocity after bias removal input from the direct evolution processing unit 16. That is, the autonomous navigation function unit 20 can execute autonomous navigation using the stable gyro input from the direct evolution processing unit 16.

  For example, the autonomous navigation function unit 20 specifies the current position of the mobile terminal 1 from the angular velocity after the bias is removed. In addition, the autonomous navigation function unit 20 accumulates the identified current position and generates a trajectory of the mobile terminal 1. Furthermore, the autonomous navigation function unit 20 can also generate the travel distance, travel time, etc. of the mobile terminal 1.

[Process flow]
FIG. 4 is a flowchart illustrating a flow of processing executed by the mobile terminal according to the first embodiment. As shown in FIG. 4, when the autonomous navigation of the mobile terminal 1 is started (S101: Yes), the vibration determination unit 13 acquires and accumulates the acceleration of the mobile terminal 1 detected by the acceleration sensor (S102). ).

  Then, the vibration determination unit 13 calculates a dispersion value of the accumulated acceleration (S103). Subsequently, the threshold value calculation unit 14 calculates a threshold value of the angular velocity using the calculated dispersion value, and determines a dynamic bias removal range (S104).

  Thereafter, when the dynamic bias determination unit 15 acquires the angular velocity (detected value) detected by the angular velocity sensor 6 (S105: Yes), the dynamic bias determining unit 15 determines whether the angular velocity (detected value) is equal to or greater than the absolute value of the threshold (S106). ).

  When the dynamic bias determination unit 15 determines that the detected value is less than the absolute value of the threshold (S106: Yes), the straight evolution processing unit 16 sets the angular velocity to 0 (S107), and the angular velocity = 0. Is output to the autonomous navigation function unit 20 (S108).

  On the other hand, when the dynamic bias determination unit 15 determines that the detected value is equal to or greater than the absolute value of the threshold (S106: No), the direct evolution processing unit 16 removes the static bias amount from the angular velocity (detected value). (S109), the angular velocity after removal is output to the autonomous navigation function unit 20 (S110).

  Then, when the use of the angular velocity sensor 6 continues (S111: No), the direct evolution processing unit 16 repeats S102 and subsequent steps. On the other hand, when the use of the angular velocity sensor 6 ends (S111: Yes), the direct evolution processing unit 16 ends the process.

[Relationship between threshold and dynamic bias]
Next, the removal target range based on the threshold value calculated by the threshold value calculation unit 14 will be described. FIG. 5 is a diagram for explaining the relationship between the threshold and the dynamic bias.

  As illustrated in FIG. 5, when the threshold value calculation unit 14 calculates the α value as the threshold value, the dynamic bias determination unit 15 sets a range Y from the + α value to the −α value as a removal target. That is, the dynamic bias determination unit 15 determines that the angular velocity within the range Y is a dynamic bias component received by the angular velocity sensor 6 when the mobile terminal 1 shakes when the mobile terminal 1 goes straight. Therefore, when the detected value of the angular velocity sensor 6 is within the range Y, the dynamic bias determination unit 15 executes the autonomous navigation by removing the dynamic bias amount by setting the detected value to 0.

  On the other hand, the dynamic bias determination unit 15 excludes the range Z1 that is equal to or greater than the + α value and the range Z2 that is equal to or less than the −α value from being removed. That is, the dynamic bias determination unit 15 possesses the mobile terminal 1 instead of the dynamic bias component received by the angular velocity sensor 6 when the mobile terminal 1 oscillates when the mobile terminal 1 travels straight in the range Z1 and the range Z2. An angular velocity generated by the user turning is determined. Therefore, when the detected value of the angular velocity sensor 6 is within the range Z1 or the range Z2, the dynamic bias determination unit 15 causes the autonomous navigation to be executed with a value obtained by removing the static bias amount from the detected value.

[Relationship between threshold change and dynamic bias]
Since the threshold calculation unit 14 periodically calculates a threshold, the threshold also changes periodically. Therefore, an example will be described in which the range to be removed changes depending on the change in the threshold calculated by the threshold calculation unit 14. FIG. 6 is a diagram for explaining the relationship between the change in threshold and the dynamic bias.

  In FIG. 6, since the mobile terminal 1 is stored in a relatively narrow place such as a breast pocket from time 0 to time t1, the mobile terminal 1 is not greatly shaken during straight progress. From time t1 to t2, the mobile terminal 1 is stored in a relatively wide place such as a pants pocket, so that the mobile terminal 1 shakes greatly during straight progress. Further, since the mobile terminal 1 is stored in a very narrow place such as a dedicated storage case from the time t2 to the time t3, the mobile terminal 1 is very little shaken during the straight advance.

  In such a state, the mobile terminal 1 calculates the threshold as Y1 from time 0 to t1, and processes the angular velocity of “+ Y1 to −Y1” as a removal target. During the subsequent time t1 to t2, the mobile terminal 1 calculates the threshold as Y2 (Y2> Y1) using the acceleration within a predetermined range from the time t1 to t2, and sets the angular velocity of “+ Y2 to −Y2”. Process as a removal target. Furthermore, during the subsequent time t2 to t3, the mobile terminal 1 calculates the threshold as Y0 (Y1> Y0) using the acceleration within a predetermined range from time t2 to t3, and the angular velocity of “+ Y0 to −Y0”. Is processed as a removal target.

[effect]
As described above, the mobile terminal 1 appropriately changes the threshold according to the magnitude of the shaking of the mobile terminal 1 and removes the dynamic bias component, so that highly accurate autonomous navigation can be maintained. FIG. 7 is a diagram illustrating autonomous navigation based on threshold control. As shown in FIG. 7, the user who has the mobile terminal 1 goes straight with some shaking, and then performs a bending operation.

  Even in such a case, the mobile terminal 1 can remove, as a dynamic bias component, shaking generated due to the influence of the storage location of the mobile terminal. Therefore, as shown in the lower diagram of FIG. 7, the mobile terminal 1 can accurately detect the straight traveling state and the bent state, and execute autonomous navigation.

  Here, the conventional autonomous navigation and the autonomous navigation according to the first embodiment are compared. FIG. 8 is a diagram for explaining the autonomous navigation when the bias is estimated, and is a technique of estimating straight travel during autonomous navigation and estimating and removing the dynamic bias at that time. 8A shows the time change of the angular velocity (detected value) detected during straight traveling, and FIG. 8B shows the time change of the dynamic bias estimated following A in FIG. C in FIG. 4 indicates the time change of the angular velocity (AB) used for autonomous navigation. In addition, the locus | trajectory by autonomous navigation is calculated by the integral value of angular velocity.

  In the method shown in FIG. 8, when the mobile terminal 1 is held in a place where the acceleration varies greatly such as a pants pocket, the amount of dynamic bias is irregular even if the way of walking or holding is constant. May affect the trajectory of autonomous navigation. For this reason, a time Y for appropriately estimating the dynamic bias amount occurs.

  This time Y is the time required for the mobile terminal 1 to follow the actual straight movement (A in FIG. 8). Therefore, as shown in “autonomous navigation by C (PDR trajectory)” in FIG. 8, a difference occurs between the actual trajectory and the autonomous navigation at the timing to follow, that is, the dynamic bias estimation timing. Moreover, since the difference generated for each estimated timing is accumulated, the quality of the subsequent autonomous navigation deteriorates. The actual trajectory is a user's actual trajectory.

  Subsequently, an example of setting a threshold for determining a removal target will be described. FIG. 9 is a diagram for explaining the autonomous navigation when the threshold value is fixed to a small value, and shows the time change of the dynamic bias. A period P1 shown in FIG. 9 is a period during which the mobile terminal 1 is largely moving but is moving straight. Further, a period P2 shown in FIG. 9 is a period in which the mobile terminal 1 has a small swing and is gently bent.

  As shown in FIG. 9, since the mobile terminal 1 determines the removal target with a small threshold, the mobile terminal 1 determines that the angular velocity detected in the period P1 is not the removal target. As a result, the mobile terminal 1 determines that the period P1 is not straight but bent, and reflects the dynamic bias as a turn on the trajectory. Therefore, in the trajectory by autonomous navigation, the actual trajectory becomes a trajectory in which the straight traveling period P1 is bent, and an accurate trajectory cannot be generated.

  When the threshold value is large, the period P2 in which the angular velocity of gentle bending occurs is determined as a dynamic bias. In that case, in the locus by autonomous navigation, the period P2 in the actual locus is a straight locus, and an accurate locus cannot be generated.

  On the other hand, FIG. 10 is a diagram for explaining the autonomous navigation according to the first embodiment, and shows the time change of the dynamic bias. FIG. 10 illustrates autonomous navigation in a state where an appropriate threshold is set according to the variance value of the acceleration of the mobile terminal 1. Note that the periods P1 and P2 shown in FIG. 10 are the same as the states described in FIG.

  As shown in FIG. 10, since the mobile terminal 1 can set an appropriate threshold value and set a dynamic bias removal range, the mobile terminal 1 can determine that the vehicle travels straight along the actual locus for the period P1, and the actual locus for the period P2. It can be judged as a gentle turn on the street. As a result, the locus by autonomous navigation using the method according to the first embodiment (autonomous navigation after processing) can accurately reflect the actual locus.

  By the way, although estimation of the dynamic bias using GPS, a geomagnetic sensor, RF (Radio Frequency) tag, etc. can be considered, the mobile terminal 1 provided with various sensors becomes high in cost and processing amount. It is also conceivable to estimate the dynamic bias using a Kalman filter. However, the Kalman filter has a high processing load, and it is difficult to realize the processing with a sensor hub microcomputer or the like generally used in a mobile terminal such as a portable terminal, and sometimes other processing is under pressure.

  On the other hand, the mobile terminal 1 uses a low-cost vibration type angular velocity sensor and acceleration sensor to execute a light load process such as dispersion monitoring of acceleration sensor values. And even if the dynamic bias amount fluctuates, the mobile terminal 1 can coexist with other functions that use the angular velocity before removing the dynamic bias even if the bending continues at a certain significant angular velocity. In addition, the mobile terminal 1 can remove the dynamic bias of the angular velocity sensor. As a result, the gyro autonomous navigation with improved straightness suitable for a general human walking style composed of a straight part and a turning angle is achieved. realizable.

  Although the embodiments of the present invention have been described so far, the present invention may be implemented in various different forms other than the embodiments described above.

[Mobile terminal shaking index]
In the first embodiment, an example in which the mobile terminal 1 calculates a shaking index using a variance value of acceleration or the like has been described. However, for example, an angular velocity or a geomagnetic sensor can also be used. For example, the mobile terminal 1 can acquire the angular velocity for a certain period, set the maximum value and the minimum value as the removal range, and can also set the removal range using an average value of the angular velocity for the certain period. .

  Further, since the mobile terminal 1 can determine that the geomagnetic sensor changes straight if the change of the geomagnetic sensor is within a predetermined range, the removal range can also be set using the acceleration or angular velocity measured during the predetermined time. In addition, the mobile terminal 1 can prepare a table in which the shaking index and the threshold are associated with each other, and can set the range of the angular velocity to be removed using the table.

[system]
Further, each configuration of the illustrated apparatus does not necessarily need to be physically configured as illustrated. That is, it can be configured to be distributed or integrated in arbitrary units. Further, all or any part of each processing function performed in each device may be realized by a CPU and a program analyzed and executed by the CPU, or may be realized as hardware by wired logic.

  In addition, among the processes described in this embodiment, all or part of the processes described as being performed automatically can be performed manually, or the processes described as being performed manually can be performed. All or a part can be automatically performed by a known method. In addition, the processing procedure, control procedure, specific name, and information including various data and parameters shown in the above-described document and drawings can be arbitrarily changed unless otherwise specified.

  Note that the mobile terminal 1 described in the present embodiment can execute the same function as the process described in FIG. 3 and the like by reading and executing the angular velocity detection value correction program. For example, the mobile terminal 1 expands a program having functions similar to those of the vibration determination unit 13, the threshold calculation unit 14, the dynamic bias determination unit 15, the direct evolution processing unit 16, and the autonomous navigation function unit 20 in the memory. And the mobile terminal 1 performs the process which performs the process similar to the vibration determination part 13, the threshold value calculation part 14, the dynamic bias determination part 15, the direct evolution process part 16, and the autonomous navigation function part 20, Processing similar to that in the above embodiment can be executed.

  This program can be distributed via a network such as the Internet. The program can be executed by being recorded on a computer-readable recording medium such as a hard disk, a flexible disk (FD), a CD-ROM, an MO, and a DVD, and being read from the recording medium by the computer.

1 Mobile terminal 11 Fixed value DB
12 Static bias DB
DESCRIPTION OF SYMBOLS 13 Vibration determination part 14 Threshold value calculation part 15 Dynamic bias determination part 16 Direct evolution processing part 20 Autonomous navigation function part

Claims (4)

In electronic devices that perform autonomous navigation,
A determination unit that determines a threshold value of an angular velocity of the electronic device to be removed during the autonomous navigation based on a change in acceleration of the electronic device;
A determination unit that determines whether or not a detection value by an angular velocity sensor that detects an angular velocity of the electronic device is less than the threshold value during the autonomous navigation;
When the detected value is determined to be less than the threshold value, the autonomous navigation is executed with the detected value set to 0, and when the detected value is determined to be greater than or equal to the threshold value, the autonomous navigation is executed using the detected value. An electronic device comprising: an execution unit that performs:   The determination unit determines, as the threshold value, a value obtained by dividing the acceleration dispersion value of the electronic device by a value obtained by multiplying a predetermined maximum value of the dispersion value and a predetermined maximum value of the threshold value. The electronic device according to claim 1.   When the detected value is determined to be equal to or greater than the threshold value, the execution unit uses the detected value after removing the angular velocity in a state where the acceleration of the electronic device is less than a predetermined value from the detected value, and the autonomous navigation The electronic device according to claim 1, wherein the electronic device is executed. To electronic devices that perform autonomous navigation,
Based on the change in acceleration of the electronic device, determine a threshold value of the angular velocity of the electronic device to be removed during the autonomous navigation,
At the time of the autonomous navigation, it is determined whether the detection value by the angular velocity sensor that detects the angular velocity of the electronic device is less than the threshold value,
When the detected value is determined to be less than the threshold value, the autonomous navigation is executed with the detected value set to 0, and when the detected value is determined to be greater than or equal to the threshold value, the autonomous navigation is executed using the detected value. An angular velocity detection value correction program characterized by causing processing to be executed.

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