JP6344165B2 - Electronic equipment and angular velocity information output program - Google Patents

Description

  The present invention relates to an electronic device and an angular velocity information output 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 2008-3002 A JP 2013-108865 A

  However, in the above technique, it takes time to estimate an error including a 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 information output program capable of reducing the time required for error estimation during execution of autonomous navigation.

  The electronic device performs autonomous navigation. The electronic device obtains the first angular velocity from the first angular velocity that is the angular velocity of the electronic device in a state where the acceleration of the electronic device is less than a predetermined value and the angular velocity of the electronic device that is in a state where the acceleration is greater than or equal to a predetermined value. The storage unit stores the removed second angular velocity. The electronic device includes a determination unit that determines whether or not a value detected by an angular velocity sensor that detects an angular velocity of the electronic device is less than the predetermined value when the autonomous navigation is performed. The electronic device removes the first angular velocity from the detected value when the detected value is determined to be less than the predetermined value, and from the detected value when the detected value is determined to be greater than or equal to the predetermined value. A removing unit configured to remove the first angular velocity and the second angular velocity;

  According to one embodiment, the time required for error estimation during execution of autonomous navigation can be reduced.

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 performed by the mobile terminal according to the first embodiment. FIG. 5 is a diagram illustrating autonomous navigation when only the static bias amount is removed. FIG. 6 is a diagram illustrating autonomous navigation in a case where dynamic bias is removed by switching parameters. FIG. 7 is a diagram illustrating autonomous navigation when the first embodiment is used. FIG. 8 is a diagram for explaining the autonomous navigation by the mobile terminal according to the second embodiment. FIG. 9 is a functional block diagram illustrating a functional configuration of the mobile terminal according to the second embodiment. FIG. 10 is a diagram for explaining an example of detection of change of mobile terminal. FIG. 11 is a flowchart showing the flow of the holding change detection process. FIG. 12 is a flowchart showing the flow of the dynamic bias update process.

  Embodiments of an electronic device and an angular velocity information output 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 includes a static bias amount, which is an angular velocity of the mobile terminal 1 in a state where the acceleration of the mobile terminal is less than a predetermined value, and the mobile terminal in a state where the acceleration is greater than or equal to a predetermined value. The dynamic bias amount obtained by removing the first angular velocity from the angular velocity is stored. And the mobile terminal 1 determines whether the acceleration of the mobile terminal 1 is less than a predetermined value at the time of autonomous navigation execution. Thereafter, when it is determined that the acceleration is less than the predetermined value, the mobile terminal 1 removes the static bias amount stored in advance from the angular velocity measured by the angular velocity sensor. Moreover, the mobile terminal 1 removes the amount of dynamic bias from the angular velocity measured by the angular velocity sensor when it is determined that the acceleration is equal to or greater than a predetermined value.

  That is, the mobile terminal 1 holds in advance the static bias amount in the stationary state and the dynamic bias amount in the walking state, and selects the bias amount suitable for the state of the mobile terminal 1 during the autonomous navigation to select the angular velocity. Correct. As a result, the mobile terminal 1 can reduce the time required for error estimation.

[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 radio unit 2, an audio input / output unit 3, a storage unit 4, a geomagnetic sensor 5, an acceleration sensor 6, an angular velocity sensor 7, a touch sensor unit 8, a display unit 9, and a processor 10. Have

  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 geomagnetic sensor 5 is a sensor that measures geomagnetism, and inputs the measured geomagnetism to the processor 10.

The acceleration sensor 6 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 6 is a three-axis sensor and measures the acceleration of each axis of x, y, and z. The angular velocity sensor 7 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 7 is a triaxial sensor and measures the angular velocity of each axis of x, y, and z.

  The touch sensor unit 8 is a circuit that detects a user's operation on the display unit 9, and the display unit 9 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 8 and the display unit 9.

  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 static bias DB 11, a dynamic bias DB 12, a determination unit 13, a bias removal unit 14, and an autonomous navigation function unit 20.

  The static bias DB 11 and the dynamic bias DB 12 are databases held in the storage unit 4 or the like. The determination unit 13, the bias removal unit 14, and the autonomous navigation function unit 20 are an example of a part of an electronic circuit included in the processor 10 and a process executed by the processor 10.

  The static bias DB 11 is a database that stores a static bias amount. Specifically, the static bias DB 11 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 11 stores in advance the static bias amount in each of the three axes that occurs in the angular velocity sensor 7 when stopped.

  The dynamic bias DB 12 is a database that stores a dynamic bias amount. Specifically, the dynamic bias DB 12 stores the angular velocity after removing the static bias amount from the angular velocity of the mobile terminal 1 in a state where the acceleration of the mobile terminal 1 is equal to or greater than a predetermined value as the dynamic bias amount. . That is, the dynamic bias DB 12 stores in advance the amount of dynamic bias in each of the three axes that occurs in the angular velocity sensor 7 due to vibration or the like.

  The determination unit 13 is a processing unit that determines the state of the mobile terminal 1. Specifically, the determination unit 13 determines, according to the acceleration measured by the acceleration sensor 6, whether the user holding the mobile terminal 1 is stationary, walking, or any other state. The result is output to the bias removing unit 14.

  For example, when the x-axis acceleration measured by the acceleration sensor 6 is a value within a range from 0 to less than the threshold, the determination unit 13 determines that the object is stationary. Moreover, the determination part 13 determines with walking, when the acceleration of the x-axis which the acceleration sensor 6 measured is a value more than a threshold value. In addition, any acceleration may be used for the state determination, and the average of each axis can be used arbitrarily.

  The bias removing unit 14 is a processing unit that removes a bias amount according to the state of the mobile terminal 1. Specifically, the bias removing unit 14 reads out the static bias amount stored in the static bias DB 11 when the determining unit 13 determines that it is stationary or others, and based on the angular velocity measured by the angular velocity sensor 7, The target bias amount is removed and output to the autonomous navigation function unit 20.

  In addition, when the determination unit 13 determines that walking is in progress, the bias removal unit 14 reads out the static bias amount stored in the static bias DB 11 and the dynamic bias amount stored in the dynamic bias DB 12. Then, the bias removing unit 14 removes the static bias amount and the dynamic bias amount from the angular velocity measured by the angular velocity sensor 7 and outputs them to the autonomous navigation function unit 20.

  The autonomous navigation function unit 20 is a processing unit that executes autonomous navigation. Specifically, the autonomous navigation function unit 20 executes autonomous navigation using the angular velocity after the bias removal input from the bias removal unit 14. That is, the autonomous navigation function unit 20 can execute autonomous navigation using the stable gyro input from the bias removing unit 14.

  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 acceleration sensor 6 measures the acceleration of the mobile terminal 1 (S102). Subsequently, the angular velocity sensor 7 measures the angular velocity of the mobile terminal 1 (S103).

  Thereafter, the determination unit 13 determines whether the mobile terminal 1 is walking from the acceleration of the mobile terminal 1 (S104). Then, when the determination unit 13 determines that walking is in progress (S104: Yes), the bias removal unit 14 determines the static bias amount and the dynamics stored in the static bias DB 11 from the raw angular velocity measured by the angular velocity sensor 7. The dynamic bias amount stored in the dynamic bias DB 12 is removed (S105).

  On the other hand, when it is determined by the determination unit 13 that the bias removal unit 14 is not walking (S104: No), the bias removal unit 14 executes S106. That is, when it is determined that the mobile terminal 1 is in a state other than the mobile terminal 1 being stationary or walking or stationary, the bias removing unit 14 uses the raw angular velocity measured by the angular velocity sensor 7 to store the static bias DB 11. The target bias amount is removed (S106).

  Then, the bias removing unit 14 outputs the angular velocity from which the corresponding bias has been removed in S105 or S106 to the autonomous navigation function unit 20 (S107).

[effect]
As described above, the mobile terminal 1 retains the static bias amount and the dynamic bias amount measured in advance, and selects and removes an appropriate bias amount according to the state of the mobile terminal 1. Therefore, it is possible to reduce the time required for error estimation when executing autonomous navigation. Moreover, since the mobile terminal 1 can shorten the time required for error estimation, it can suppress a decrease in accuracy of autonomous navigation.

  Here, the conventional autonomous navigation and the autonomous navigation according to the first embodiment are compared. FIG. 5 is a diagram illustrating autonomous navigation when only the static bias amount is removed. As shown in FIG. 5, when the user is walking, that is, when the mobile terminal 1 is moving, the dynamic bias continues to be generated, but only the static bias amount is removed. As a result, since the dynamic bias amount continues to be accumulated in the locus by the autonomous navigation of the mobile terminal 1, a locus that is significantly different from the actual locus that is the actual locus of the user is generated.

  FIG. 6 is a diagram showing the autonomous navigation in the case where the dynamic bias is removed by switching the parameter, and shows the time change of the bias. In the example shown in FIG. 6, the user holding the mobile terminal 1 repeats walking, stopping, walking, stopping, and walking. Therefore, the generated bias amount is a dynamic bias, a static bias, a dynamic bias, a static bias, and a dynamic bias.

  Here, when the mobile terminal 1 stops in a state where the bias amount is deleted using the dynamic bias parameter, the mobile terminal 1 designates the parameter for stoppage. At this time, if a designation error or a long time is taken for designation, the locus of autonomous navigation will bend even though the actual locus is straight. In addition, when the mobile terminal 1 deletes the bias amount using the static bias parameter even though the mobile terminal 1 is moving, the mobile terminal 1 is straight even though the actual locus is straight. The locus of autonomous navigation will bend.

  On the other hand, FIG. 7 is a figure which shows the autonomous navigation at the time of using Example 1, and shows the time change of a bias. As shown in FIG. 7, the mobile terminal 1 according to the first embodiment provides an appropriate bias amount even when the user holding the mobile terminal 1 repeats walking, stopping, walking, stopping, and walking. Can be selected and removed instantly. For this reason, the error between the trajectory of the mobile terminal 1 by the autonomous navigation and the actual trajectory of the user of the mobile terminal 1 is reduced, and the mobile terminal 1 can realize highly reliable autonomous navigation.

  In the first embodiment, an example in which the dynamic bias amount and the static bias amount are measured and stored in advance has been described. However, the dynamic bias amount can be updated as appropriate. For example, the mobile terminal 1 can update the dynamic bias amount when there is a change from the posture when the dynamic bias amount is measured in advance.

  Therefore, as an example, in Example 2, the mobile terminal 1 holds posture information obtained by measuring the dynamic bias amount and the static bias amount at the start of autonomous navigation, and the posture changes when the mobile terminal 1 is changed. In this case, an example in which the dynamic bias amount is updated will be described. The posture information includes, for example, axis information and vibration direction. Moreover, since the hardware configuration of the mobile terminal 1 is the same as that of FIG. 1, detailed description is abbreviate | omitted.

[Autonomous navigation of mobile terminals]
FIG. 8 is a diagram for explaining the autonomous navigation by the mobile terminal according to the second embodiment. As illustrated in FIG. 8, the mobile terminal 1 performs autonomous navigation while moving while being held by the user while correcting the angular velocity using the static bias amount and the dynamic bias amount held in advance.

  When the mobile terminal 1 detects that the user has moved the mobile terminal 1, the mobile terminal 1 reestimates the dynamic bias amount and updates the retained dynamic bias amount. Thereafter, the mobile terminal 1 performs autonomous navigation while correcting the angular velocity using the static bias amount held in advance and the updated dynamic bias amount.

[Function configuration]
FIG. 9 is a functional block diagram illustrating a functional configuration of the mobile terminal according to the second embodiment. As illustrated in FIG. 9, the mobile terminal 1 includes a static bias DB 11, a dynamic bias DB 12, a determination unit 13, a bias removal unit 14, a switch detection unit 15, a static bias estimation unit 16, and a dynamic bias estimation unit 17. The autonomous navigation function unit 20 is included.

  Since the static bias DB 11, the dynamic bias DB 12, the determination unit 13, the bias removal unit 14, and the autonomous navigation function unit 20 have the same configuration as that of the first embodiment, detailed description thereof is omitted. In addition, the mobile terminal 1 holds posture information obtained by measuring the dynamic bias amount and the static bias amount in a memory or the like when the autonomous navigation is started.

  The change-over detection unit 15 is a processing unit that detects the change of the mobile terminal 1. Specifically, the change-over detection unit 15 detects that the mobile terminal 1 has been changed according to a change in the axis of the mobile terminal 1 in the direction of the acceleration of gravity. For example, the changeover detection unit 15 detects changeover when there is a change in the direction and magnitude of the acceleration of gravity that the mobile terminal 1 receives.

  FIG. 10 is a diagram for explaining an example of detection of change of mobile terminal. The horizontal axis of the mobile terminal 1 is the x axis, the vertical axis is the y axis, and the depth is the z axis. And the state which the mobile terminal 1 estimated the amount of dynamic biases in advance is the state shown in the left figure of FIG. 10, and is the state which receives gravity in the negative direction of the y-axis. Assume that the mobile terminal 1 is changed from this state to a state where it receives gravity in the negative direction of the x-axis as shown in the right diagram of FIG.

  In other words, when the autonomous navigation is started, the change-over detection unit 15 holds the direction and size in which the mobile terminal 1 receives gravity at the start, and the direction in which the mobile terminal 1 receives gravity periodically. And measure the size. Then, the change detection unit 15 determines that the change has occurred when the direction in which the mobile terminal 1 receives gravity or the magnitude of gravity changes, and transmits a reset signal to the dynamic bias estimation unit 17.

  For example, the change detection unit 15 detects the occurrence of change when the axis of the mobile terminal 1 that receives gravity changes, when the axis is the same but the magnitude of gravity changes, or when the axis and size change.

  Further, the change-over detection unit 15 repeats the change-over detection while the autonomous navigation is being executed. That is, when the change of the mobile terminal 1 is detected, the change-of-change detecting unit 15 holds the posture information at that time and uses it for subsequent change determination. Then, the change detection unit 15 transmits a reset signal to the dynamic bias estimation unit 17 every time a new change occurs from the previous change.

  The static bias estimation unit 16 is a processing unit that estimates a bias received by the angular velocity sensor 7 when the mobile terminal 1 is not moving. Specifically, the static bias estimation unit 16 estimates the angular velocity measured by the angular velocity sensor 7 as a static bias amount when the acceleration of the mobile terminal 1 is at a predetermined value or less, and stores it in the static bias DB 11. To do.

  Note that the static bias amount varies little depending on the axis, but the static bias amount can be periodically estimated and updated. For example, the static bias estimation unit 16 estimates the static bias amount at an arbitrary timing such as a timing when the mobile terminal 1 is turned on, a timing when autonomous navigation is started, or a timing when autonomous navigation is not executed. be able to.

  The dynamic bias estimation unit 17 is a processing unit that estimates the dynamic bias amount and updates the dynamic bias DB 12 when the mobile terminal 1 is switched. Specifically, when the reset signal is input from the change detection unit 15, the dynamic bias estimation unit 17 determines the movement of the mobile terminal 1 measured within a certain time when the movement of the mobile terminal 1 is determined to go straight. The amount of dynamic bias is estimated using the angular velocity.

  For example, the dynamic bias estimator 17 uses a period during which the removed angular velocity is a constant value or the angular velocity after removal falls within a predetermined range after removing the static bias amount from the angular velocity measured by the angular velocity sensor 7. It is determined that 1 is traveling straight. In addition, the dynamic bias estimation unit 17 determines that the period in which the change in the geomagnetism vector measured by the geomagnetic sensor 5 is less than the threshold is the state in which the mobile terminal 1 is traveling straight.

  As another method, the dynamic bias estimator 17 averages the angular velocities at predetermined intervals, and the slope of the cumulative increase in angular velocities of each axis of the mobile terminal 1 is constant below the theoretical maximum value. It is also possible to determine that the period during which the fluctuation of the average value is equal to or less than the threshold is a state in which the mobile terminal 1 is traveling straight.

  For example, the dynamic bias estimation unit 17 calculates an average value of angular velocities every 10 seconds. That is, the dynamic bias estimation unit 17 calculates a moving average of angular velocities. Specifically, the dynamic bias estimation unit 17 calculates the average value A of the angular velocities in the period A, calculates the average value B of the angular velocities for the period B for the next 10 seconds, and then the period C for the next 10 seconds. An average value C of angular velocities is calculated for.

  Then, the dynamic bias estimation unit 17 determines that the difference between the average value A and the average value B is equal to or less than the threshold value, and the difference between the average value B and the average value C is equal to or less than the threshold value. When the cumulative slope is constant below the theoretical maximum value, it is determined that the mobile terminal 1 is traveling straight from period A to period C. As a result, the dynamic bias estimation unit 17 calculates the average value of the angular velocities from the period A to the period C, estimates the calculated average value as the dynamic bias amount, and stores the dynamic bias stored in the dynamic bias DB 12. Update quantity.

  When estimating the dynamic bias amount, the angular velocity after removal with the static bias amount removed is used, and when specifying the period, even if the angular velocity after removal with the static bias amount removed is It may be an angular velocity.

  Then, the dynamic bias estimation unit 17 calculates an average value of the angular velocities after the static bias removal within the specified period, and stores the calculated average value in the dynamic bias DB 12 as a new dynamic bias amount. Note that the dynamic bias estimation unit 17 can use another method for the state in which the mobile terminal 1 is traveling straight ahead, or use a known method using azimuth information, position information by GPS, or the like. You can also.

[Changeover detection processing]
FIG. 11 is a flowchart showing the flow of the holding change detection process. The change-over detection unit 15 accumulates the acceleration measured by the acceleration sensor 6 every second for each axis of xyz (S201). The one second shown here is merely an example, and can be set arbitrarily.

  Subsequently, the transfer detection unit 15 detects the axis, direction, and value having the maximum absolute value within the predetermined period accumulated in S201 (S202). For example, the holding detection unit 15 detects an absolute value “X” in the minus direction of the x axis.

  Thereafter, the change detection unit 15 determines whether the maximum axis and direction held at the start of autonomous navigation or the previous change detection is different from the maximum axis and direction detected in S202, or whether the stored value is larger than the latest value. (S203).

  Here, if there is no change in the maximum axis and direction and the latest value detected in S202 is smaller than the stored value (S203: No), the change detection unit 15 resets the accumulation (S204). , S201 and subsequent steps are repeated.

  Then, when there is a change in the maximum axis and direction, or the latest value detected in S202 is larger than the stored value (S203: Yes), the change-over detection unit 15 executes S205.

  That is, the transfer detection unit 15 adds 0.25 G × sample frequency as an offset to the latest value, and stores the maximum axis, direction, and the value after the offset addition detected in S202. Note that the offset is added to prevent erroneous detection. In other words, it is because it is not determined that a small change in tilt, that is, a slight change in inclination due to walking or the like, is a change.

  Thereafter, the change-over detection unit 15 detects change-over (S206), and outputs a reset signal to the dynamic bias estimation unit 17 to execute a dynamic bias update process (S207).

[Update processing]
FIG. 12 is a flowchart showing the flow of the dynamic bias update process. As shown in FIG. 12, when receiving the reset signal, the dynamic bias estimation unit 17 acquires the angular velocity from the angular velocity sensor 7 (S301), and removes the static bias amount from the acquired angular velocity (S302).

  Then, the dynamic bias estimation unit 17 repeats S301 and S302 for a predetermined time (S303: No), and accumulates the angular velocity from which the static bias amount is removed.

  Thereafter, when the dynamic bias estimation unit 17 accumulates the angular velocity from which the static bias amount has been removed for a certain time (S303: Yes), the dynamic bias estimation unit 17 determines whether the mobile terminal 1 is traveling straight from the accumulated angular velocity (S304).

  If the dynamic bias estimation unit 17 determines that the mobile terminal 1 is not going straight (S305: No), the accumulated information is reset, and S301 and subsequent steps are repeated.

  On the other hand, when the dynamic bias estimation unit 17 determines that the mobile terminal 1 is traveling straight (S305: Yes), the average value of the angular velocity after removing the static bias amount accumulated within a certain period is calculated. Calculate (S306). Then, the dynamic bias estimation unit 17 updates the dynamic bias amount stored in the dynamic bias DB 12 with the calculated average value of the angular velocities (S307).

[effect]
As described above, the mobile terminal 1 can update the dynamic bias amount when a change in position is detected, in other words, when there is a change from the previous posture in which the dynamic bias amount is measured. In addition, the mobile terminal 1 has a minimum configuration of the angular velocity sensor 7 and the acceleration sensor 6, so that even if the user changes the state of walking, stopping, and stopping, or changing the way the terminal is held, the processing load is light. However, the dynamic bias can be removed from the measured angular velocity in a short time. As a result, since the mobile terminal 1 can accurately follow the change in the dynamic bias amount, it is possible to realize highly accurate autonomous navigation.

  In addition, the mobile terminal 1 can also perform autonomous navigation using the dynamic bias amount before the update from the changeover detection to the dynamic bias update. Thereafter, the mobile terminal 1 can also correct the angular velocity calculated during the update by using the difference between the dynamic bias amount before the update and the dynamic bias amount after the update. As a result, the mobile terminal 1 can realize highly accurate autonomous navigation even when the dynamic bias amount is being updated.

  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.

[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 processing described with reference to FIGS. 3 and 9 by reading and executing the angular velocity information output program. For example, the mobile terminal 1 stores a program having functions similar to those of the determination unit 13, the bias removal unit 14, the change detection unit 15, the static bias estimation unit 16, the dynamic bias estimation unit 17, and the autonomous navigation function unit 20. Expand to. Then, the mobile terminal 1 performs a process of executing processes similar to those of the determination unit 13, the bias removal unit 14, the change detection unit 15, the static bias estimation unit 16, the dynamic bias estimation unit 17, and the autonomous navigation function unit 20. By executing, the same processing as 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 Static bias DB
12 Dynamic bias DB
DESCRIPTION OF SYMBOLS 13 Judgment part 14 Bias removal part 15 Change detection part 16 Static bias estimation part 17 Dynamic bias estimation part 20 Autonomous navigation function part

Claims (6)

In electronic devices that perform autonomous navigation,
A first angular velocity that is an angular velocity of the electronic device in a state where the acceleration of the electronic device is less than a predetermined value, and a second that is obtained by removing the first angular velocity from the angular velocity of the electronic device in a state where the acceleration is a predetermined value or more. A storage unit for storing the angular velocity of
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 predetermined value when the autonomous navigation is performed;
When the detected value is determined to be less than the predetermined value, the first angular velocity is removed from the detected value, and when the detected value is determined to be greater than or equal to the predetermined value, the first angular velocity is determined from the detected value. And an removing unit that removes the second angular velocity. In accordance with a change in the axis of the electronic device that is the direction of acceleration of gravity, a detection unit that detects a change in the posture of the electronic device;
When it is detected by the detection unit that the attitude of the electronic device has changed, the second angular velocity is calculated using the detection value detected within a predetermined time when the movement of the electronic device is determined to be straight. The electronic apparatus according to claim 1, further comprising an update unit that estimates and updates the second angular velocity stored in the storage unit with the estimated result.   The update unit identifies a period during which the change in the detection value after removing the first angular velocity from the detection value is less than a threshold as the certain time, and the detection value calculated within the specified period The electronic apparatus according to claim 2, wherein the second angular velocity stored in the storage unit is updated with an average value.   The update unit identifies a period during which the change in the geomagnetism vector measured by the geomagnetic sensor is less than a threshold value as the predetermined time, and detects after removing the first angular velocity from the detection value within the identified period The electronic apparatus according to claim 2, wherein the second angular velocity stored in the storage unit is updated with an average value.   The updating unit is configured to change the average value obtained by averaging the detected values at a predetermined interval, and the inclination of accumulation of the detected values in each axis of the electronic device is constant below a theoretical maximum value as the fixed time. Specifies a period during which the threshold value is equal to or less than a threshold value, and updates the second angular velocity stored in the storage unit with an average value of the detected values after the first angular velocity is removed from the detected values within the specified period. The electronic apparatus according to claim 2, wherein: To electronic devices that perform autonomous navigation,
At the time of executing the autonomous navigation, it is determined whether or not a detection value by an angular velocity sensor that detects an angular velocity of the electronic device is less than a predetermined value,
A first angular velocity that is an angular velocity of the electronic device when the acceleration of the electronic device is less than the predetermined value and a first angular velocity that is removed from the angular velocity of the electronic device when the acceleration is equal to or greater than a predetermined value. 2 is referred to, and when the detected value is determined to be less than the predetermined value, the first angular velocity is removed from the detected value, and the detected value is determined to be greater than or equal to the predetermined value. If so, an angular velocity information output program for executing processing for removing the first angular velocity and the second angular velocity from the detected value.

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