JP2011053060A - Program, information storage medium, error measurement method for acceleration sensor, error-measuring device for acceleration sensor and game system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a program for calculating offset error information and sensitivity error information of an acceleration sensor, based on the detection information obtained, regardless of the orientation of the acceleration sensor, and to provide an information storage medium, an error measurement method for acceleration sensors, an error-measuring device and a game system. <P>SOLUTION: Six sets of acceleration information, based on the detected information of an acceleration sensor 20, are substituted into a variable of an equation of an ellipsoid, including six parameters corresponding to the sensitivities and offsets in the three detection axis detections of the acceleration sensor 20 orthogonal to one another that form simultaneous quadratic equations with the six parameters as the unknowns. The simultaneous quadratic equations are reduced to simultaneous linear equations, with each being represented by an equation with at least one of the six unknowns and containing five new unknowns, and the simultaneous linear equations are solved. The original six unknowns are calculated based on the five new unknowns, and offset error information and sensitivity error information of the three detection axis directions of the acceleration sensor are calculated, based on the calculation results. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a program, an information storage medium, an acceleration sensor error measurement method, an acceleration sensor error measurement device, and a game system.

  Recently, there is a game device that can be used as a game input by providing an acceleration sensor in a game controller to detect the direction and movement of the controller. In such a game device, a game is realized in which the direction and movement of an object in the game space are controlled according to the detected direction and movement, and a game image including the object is generated.

JP 2003-225467 A

  In such a game, it is important to generate a game image that operates consistently according to the direction and movement of the controller. However, there is an error (individual difference) in the acceleration sensor built in the controller. Therefore, when developing a game that uses an acceleration sensor, even if it is confirmed that it operates correctly with some controllers, there remains uncertainty about the operation with other controllers.

  Conventionally, as a method for measuring the error of the acceleration sensor, the acceleration sensor is set to a state where each detection axis direction of the acceleration sensor is set upward and downward, and only gravitational acceleration is applied to each detection axis direction. A technique for calculating an offset error and a sensitivity error in each detection axis direction of the acceleration sensor has been performed.

  However, with this method, the error cannot be measured accurately unless it is stationary with each detection axis direction of the acceleration sensor accurately aligned upward and downward. was there.

  The present invention has been made in view of the above problems, and according to some aspects of the present invention, based on the detection information obtained regardless of the orientation of the acceleration sensor, the offset error information of the acceleration sensor. And a program capable of calculating sensitivity error information, an information storage medium, an error measuring method and error measuring apparatus for an acceleration sensor, and a game system can be provided.

  (1) The present invention is a program for calculating offset error information and sensitivity error information of an acceleration sensor, and includes six parameters corresponding to each sensitivity and each offset in three detection axis directions orthogonal to each other of the acceleration sensor. Simultaneous equations for creating simultaneous quadratic equations composed of six quadratic equations with six parameters as unknowns by substituting six sets of acceleration information based on the detection information of the acceleration sensor into variables of ellipsoidal equations The creation unit and the simultaneous quadratic equations include five new unknowns each represented by an equation including at least one of the six unknowns, and five linear equations that do not include any of the six unknowns. A simultaneous equation calculation unit that solves the simultaneous linear equations by reducing the simultaneous equations, and the six new values from the new unknown values. It calculates the value of the number, as the acceleration error calculator based on the calculation result to calculate an offset error information and the sensitivity error information of the three detection axis of the acceleration sensor, causes a computer to function, and a program. The present invention also relates to an information storage medium that can be read by a computer and stores (records) a program that causes a main device to function as each of the above-described units.

  The offset error information of the acceleration sensor may be the offset error itself, or may be any other information that can uniquely derive the offset error.

  Similarly, the sensitivity error information of the acceleration sensor may be the sensitivity error itself, or may be any other information that can uniquely derive the sensitivity error.

  According to the present invention, if any six sets of acceleration information based on the detection information of the acceleration sensor can be obtained, the offset error information and the sensitivity error information of the acceleration sensor can be calculated algebraically. Therefore, even if the detection information in the state in which each detection axis direction of the acceleration sensor is accurately set to the upward and downward directions as in the conventional method cannot be obtained, the offset error is based on the detection information obtained regardless of the orientation of the acceleration sensor. Information and sensitivity error information can be calculated.

  In addition, it takes time for the calculation to converge in a method in which the solution of the simultaneous quadratic equation is obtained by iterative calculation with a computer by Newton's method (Newton-Raphson method). Since it is reduced to a linear equation and solved algebraically, the calculation time can be shortened.

  (2) Further, in the program and the information storage medium according to the present invention, the simultaneous equation calculation unit is configured such that the coefficient matrix of the simultaneous linear equation includes all other elements whose absolute values of the diagonal elements are not diagonal elements. The simultaneous linear equations may be created so as to be larger than the absolute value.

  For example, by generating six sets of acceleration information according to a predetermined rule and generating simultaneous linear equations according to a predetermined rule from simultaneous quadratic equations, all other elements whose diagonal elements are not diagonal elements in absolute value A coefficient matrix that is larger than the absolute value of can be created.

  In this way, the solution can be obtained and the calculation error can be reduced without performing pivot selection in the calculation process of the simultaneous linear equations, and the simultaneous linear equations can be stably and accurately increased without increasing the calculation load. Can be solved.

  (3) Further, in the program and the information storage medium according to the present invention, the simultaneous equation calculation unit includes the two pieces of acceleration information having a maximum value and a minimum value in the first detection axis direction among the six sets of acceleration information. Is created by subtracting the other from one of the two quadratic equations obtained by substituting each of the ellipsoidal equations into the equation variables, and one of the linear equations is created. Subtract the other from one of the two quadratic equations obtained by substituting the two acceleration information having the maximum and minimum values in the second detection axis direction into the variables of the ellipsoidal equation. Another one of the linear equations is created based on the obtained polynomial, and the two pieces of acceleration information having the maximum and minimum values in the third detection axis direction among the six sets of acceleration information are Substituting for each variable in the ellipsoid equation One may be created other one of said linear equations based on the polynomial obtained by subtracting one from the two quadratic equation is.

  For example, the simultaneous equation calculation unit detects the two pieces of acceleration information having the maximum and minimum values in the first detection axis direction among the six sets of acceleration information, and uses the two pieces of acceleration information as equations of the ellipsoid. One of the linear equations is created based on a polynomial obtained by subtracting the other from one of the two quadratic equations obtained by substituting each of the variables, and among the six sets of acceleration information, From two of the two quadratic equations obtained by detecting the two acceleration information having the maximum and minimum values in the detection axis direction of 2 and substituting the two acceleration information into the variables of the ellipsoidal equation, respectively. Another one of the linear equations is created based on a polynomial obtained by subtracting the other, and the two accelerations having the maximum and minimum values in the third detection axis direction among the six sets of acceleration information Information is detected, and the two pieces of acceleration information are Another one of the linear equations may be created based on a polynomial obtained by subtracting the other from one of the two quadratic equations obtained by substituting each of the variables in the circular equation. .

  Further, for example, the simultaneous equation calculation unit has the maximum value in the first detection axis direction, the minimum value in the first detection axis direction, and the second detection axis direction in the six sets of acceleration information. The acceleration information with a maximum value, a minimum value in the second detection axis direction, a maximum value in the third detection axis direction, and a minimum value in the third detection axis direction is determined in advance. Two acceleration information obtained by substituting the two acceleration information having the maximum and minimum values in the first detection axis direction into variables of the ellipsoidal equation among the six sets of acceleration information. One of the linear equations is created based on a polynomial obtained by subtracting the other from one of the quadratic equations, and the value in the second detection axis direction is maximum and minimum among the six sets of acceleration information Obtained by substituting the two pieces of acceleration information into the variables of the ellipsoid equation, respectively. Another one of the linear equations is created based on a polynomial obtained by subtracting the other from one of the two quadratic equations, and the value in the third detection axis direction is included in the six sets of acceleration information. Based on a polynomial obtained by subtracting the other from one of two quadratic equations obtained by substituting the maximum and minimum two pieces of acceleration information into the variables of the ellipsoidal equation, One of these may be created.

  In this way, in the coefficient matrix of the simultaneous linear equations, the absolute values of the three diagonal elements included in the three rows corresponding to at least three linear equations become relatively large and are included in the three rows. Other elements can be made almost zero. Therefore, in the calculation process of the simultaneous linear equations, at least the calculation for these three linear equations can reduce the calculation error, so that it becomes easy to solve the simultaneous linear equations stably and accurately. .

  (4) Further, in the program and the information storage medium according to the present invention, the simultaneous equation calculation unit is a polynomial obtained by calculating any two quadratic equations of the simultaneous quadratic equation or a polynomial obtained by modifying the polynomial. The simultaneous linear equations may be created by associating an expression composed of the six unknowns included in each term or an expression obtained by multiplying the expression by a real number with the five new unknowns.

For example, the simultaneous equation calculation unit includes a, b, c as sensitivity parameters in the three detection axis directions of the acceleration sensor, and three offset parameters in the detection axis direction of the acceleration sensor, among the six parameters. P, q, and r, respectively, the five new unknowns α, β, γ, δ, ε are expressed as α = p, β = (a ² / b ² ) q, γ = (a ² / c ² ) The simultaneous linear equations may be created with r, δ = a ² / b ² and ε = a ² / c ² .

  (5) In the program and the information storage medium according to the present invention, the simultaneous equation calculation unit is configured so that predetermined three axes orthogonal to each other in a three-dimensional space formed by the three detection axes of the acceleration sensor are in the direction of gravity. The three sets of acceleration information based on the three sets of detection information obtained in the opposite direction (ie, the direction in which gravity is applied) or the vicinity thereof, and the predetermined three axes are the gravity direction or the vicinity thereof, respectively. The simultaneous quadratic equations may be created using three sets of the acceleration information based on the three sets of detection information obtained in a state of facing.

  In this way, the six points corresponding to the six sets of acceleration information are positioned sufficiently apart from each other in the three-dimensional space created by the three detection axes of the acceleration sensor, so that the six sets of acceleration information can be used. The ellipsoidal equation can be specified with higher accuracy. That is, the offset error information and sensitivity error information of the acceleration sensor can be calculated with higher accuracy.

(6) In the program and the information storage medium according to the present invention, the simultaneous equation creating unit sets the three detection axes of the acceleration sensor as an x-axis, a y-axis, and a z-axis, and among the six parameters, The sensitivity parameters of the acceleration sensor in the x-axis direction, y-axis direction, and z-axis direction are a, b, and c, respectively, and the x-axis direction, y-axis direction, and z-axis direction offset parameters of the acceleration sensor are respectively shown. When p, q, r, the equation {(x−p) / a} ² + {(y−q) / b} ² + {(z−r) / c} ² = 1 as the ellipsoidal equation. May be used.

  (7) The program and the information storage medium according to the present invention may include an acceleration information generation unit that acquires the detection information of the acceleration sensor and generates the acceleration information based on the acquired detection information. .

  (8) In the program and the information storage medium according to the present invention, the acceleration information generation unit determines whether or not the acceleration due to the motion of the acceleration sensor is negligible based on the detection information, The acceleration information may be generated based on the detection information in a state where the acceleration due to the motion of the acceleration sensor can be ignored.

  The “state where the acceleration due to movement can be ignored” is a state where the acceleration due to movement is 0 or close to 0, and includes a state where the acceleration sensor is stationary or moving at a constant speed.

  In this way, each piece of acceleration information more accurately reflects the gravitational acceleration components in the three detection axis directions, so that the ellipsoidal equation can be specified more accurately. That is, the offset error information and sensitivity error information of the acceleration sensor can be calculated with higher accuracy.

  (9) Further, in the program and the information storage medium according to the present invention, the acceleration information generation unit causes the acceleration due to the movement of the acceleration sensor if the fluctuation range of the detection information satisfies a predetermined condition for a predetermined time. You may make it determine with it being in a state which can be disregarded.

  The “state in which the fluctuation range of the detection information satisfies a predetermined condition” may be, for example, a state in which the fluctuation range of the detection information is a predetermined value or less or less than a predetermined value.

  (10) In the program and the information storage medium according to the present invention, the acceleration information generation unit may generate the acceleration information based on a plurality of the detection information acquired at the predetermined time.

  For example, the acceleration information generation unit may use, as the acceleration information, an average value of all or part of the plurality of detection information acquired at the predetermined time.

  In this way, the influence of random noise and rounding error included in the detection information of the acceleration sensor can be reduced, so that the offset error information and sensitivity error information of the acceleration sensor can be calculated with higher accuracy.

  (11) Further, the present invention is an acceleration sensor error measuring method for calculating offset error information and sensitivity error information of an acceleration sensor, in a three-dimensional space formed by three detection axes orthogonal to each other of the acceleration sensor. The detection information of the acceleration sensor is acquired in a state where the first axis among predetermined three axes orthogonal to each other faces in the reverse direction of the gravity direction or the vicinity thereof, and the first acceleration information is obtained based on the detection information. A first acceleration information generation step to be generated, and detection information of the acceleration sensor is acquired in a state where the first axis faces the gravity direction or the vicinity thereof, and second acceleration information is generated based on the detection information. The second acceleration information generation step, and the detection information of the acceleration sensor is acquired in a state where the second axis of the predetermined three axes faces the direction opposite to or near the gravity direction; A third acceleration information generating step for generating third acceleration information based on the detection information; and acquiring the detection information of the acceleration sensor in a state where the second axis faces the gravity direction or its vicinity. A fourth acceleration information generating step for generating fourth acceleration information based on the information, and the acceleration sensor in a state in which the third axis of the predetermined three axes faces the direction opposite to or near the gravity direction. And a fifth acceleration information generation step for generating fifth acceleration information based on the detection information, and detection of the acceleration sensor in a state where the third axis faces the gravity direction or its vicinity. A sixth acceleration information generation step of acquiring information and generating sixth acceleration information based on the detection information; and 6 corresponding to each sensitivity and each offset in the three detection axis directions of the acceleration sensor The first acceleration information, the second acceleration information, the third acceleration information, the fourth acceleration information, the fifth acceleration information, and the sixth , The simultaneous equation creating step of creating simultaneous quadratic equations composed of six quadratic equations with the six parameters as unknowns, and the simultaneous quadratic equations at least one of the six unknowns. Simultaneous equations that solve the simultaneous linear equations by reducing them to five linear equations that include five new unknowns, each of which includes five new unknowns that are each represented by an equation that includes one of the six unknowns. Calculating the six unknown values from the calculation step and the five new unknown values; And an error calculating step for calculating offset error information and sensitivity error information.

  According to the present invention, offset error information and sensitivity error information can be calculated based on detection information obtained regardless of the orientation of the acceleration sensor, and the simultaneous quadratic equation can be reduced to the simultaneous linear equation to be algebraic. The calculation time can be shortened.

  Further, according to the present invention, the six points corresponding to the six sets of acceleration information are positioned sufficiently apart from each other on the three-dimensional space formed by the three detection axes of the acceleration sensor. Can be used to specify the ellipsoidal equation more accurately. That is, the offset error information and sensitivity error information of the acceleration sensor can be calculated with higher accuracy.

  (12) Further, the present invention is an error measuring apparatus for an acceleration sensor that measures offset error information and sensitivity error information of the acceleration sensor, acquires detection information of the acceleration sensor, and based on the acquired detection information The variable of the ellipsoidal equation including six parameters corresponding to the acceleration information generation unit that generates six sets of acceleration information and the sensitivity and each offset in the three detection axis directions orthogonal to each other of the acceleration sensor. A set of simultaneous equations and a simultaneous equation creating unit that creates simultaneous quadratic equations composed of six quadratic equations with the six parameters as unknowns; and the simultaneous quadratic equations are set as at least one of the six unknowns. A set of five linear equations that contain five new unknowns, each of which is represented by an equation containing one, and that do not contain any of the six unknowns. A simultaneous equation calculator that solves the simultaneous linear equations by reducing the equations, and calculates the six unknown values from the five new unknown values, and the three detections of the acceleration sensor based on the calculation results The present invention relates to an error measurement apparatus for an acceleration sensor, including an acceleration error calculation unit that calculates offset error information and sensitivity error information in the axial direction.

  According to the present invention, offset error information and sensitivity error information can be calculated based on detection information acquired regardless of the orientation of the acceleration sensor, and the simultaneous quadratic equations can be reduced to simultaneous linear equations algebraically. Since it solves, the calculation time can be shortened.

  (13) Further, the present invention is a game system for performing game calculation by acquiring detection information of the acceleration sensor from an input device including an acceleration sensor that detects an acceleration that changes according to an input operation of the player, Based on the detection information of the acceleration sensor, the offset error information and sensitivity error information of the acceleration sensor are calculated and stored in a storage unit; the offset error information stored in the storage unit; and A game calculation unit that corrects detection information of the acceleration sensor based on sensitivity error information and performs a game calculation, and the acceleration error measurement unit acquires the detection information of the acceleration sensor from the input device. An acceleration information generation unit that generates six sets of acceleration information based on the acquired detection information, and the acceleration sensor 3 orthogonal to each other. From the six quadratic equations in which the six sets of acceleration information are substituted into the variables of the ellipsoidal equation including the six parameters corresponding to the sensitivity and the offset in the detection axis direction, and the six parameters are unknown. A simultaneous equation creating unit for creating the simultaneous quadratic equation, and the simultaneous quadratic equation including five new unknowns each represented by an expression including at least one of the six unknowns and the six unknowns A simultaneous equation calculation unit that solves the simultaneous linear equations by reducing the simultaneous linear equations to five simultaneous equations that do not include any of the above, and calculates the values of the six unknowns from the five new unknown values. An acceleration error calculation unit for calculating offset error information and sensitivity error information in the three detection axis directions of the acceleration sensor based on the calculation result; and the offset error Including an acceleration error setting unit to store the broadcast and the sensitivity error information in the storage unit, and relates to a game system.

  According to the present invention, it is possible to calculate offset error information and sensitivity error information based on detection information obtained regardless of the orientation of the acceleration sensor before starting the game calculation. Therefore, in order to measure the offset error information and the sensitivity error information of the acceleration sensor, there is no trouble for the player to hold the input device so that each detection axis of the acceleration sensor is accurately upward and downward. And since the detection information of an acceleration sensor is correct | amended based on the offset error information and sensitivity error information which were memorize | stored in the memory | storage part, the game calculation which reflected player's input operation more correctly can be performed.

  (14) In the game system according to the present invention, the acceleration error measurement unit acquires the detection information to obtain the offset error information and the sensitivity when the game program is started or when an acceleration error measurement event occurs. Error information may be calculated, and the calculated offset error information and sensitivity error information may be stored in the storage unit.

  For example, an acceleration error measurement event may be generated spontaneously by a player performing a predetermined operation input, or an acceleration error measurement event is generated by determining whether or not a predetermined condition is satisfied by the game system. You may make it determine whether to make it carry out.

The functional block diagram of the error measuring device of an acceleration sensor. 2A to 2D are schematic external views of the measurement target device. The figure which represented the sphere represented by Formula (8) typically. The figure which represented typically the ellipsoid represented by Formula (9). The figure for demonstrating the relationship of the ellipsoid represented by six measured values (six sets of acceleration information) and Formula (9). The figure for demonstrating the structure of an independent simultaneous equation. The figure for demonstrating the structure of an independent simultaneous equation. The figure for demonstrating the structure of an independent simultaneous equation. The figure for demonstrating the structure of an independent simultaneous equation. The figure for demonstrating the structure of an independent simultaneous equation. The figure for demonstrating the structure of an independent simultaneous equation. The figure for demonstrating the structure of an independent simultaneous equation. The figure which shows arrangement | positioning of the six measured values obtained by the measurement shown in Table 1. FIG. The figure which shows an example of the time series of the measured value of the uniaxial direction in any one of x, y, and z. The flowchart which shows the process example of the error measuring apparatus of the acceleration sensor of this embodiment. The flowchart which shows the process example which produces | generates acceleration information. The flowchart which shows the process example for improving the error measurement precision of an acceleration sensor further. The functional block diagram of the game system of this embodiment. The flowchart which shows the process example of the game system of this embodiment.

  DESCRIPTION OF EMBODIMENTS Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the drawings. The embodiments described below do not unduly limit the contents of the present invention described in the claims. Also, not all of the configurations described below are essential constituent requirements of the present invention.

1. 1. Accelerometer error measurement device 1-1. Configuration FIG. 1 is an example of a functional block diagram of an error measurement device for an acceleration sensor. Note that the error measurement device for an acceleration sensor according to the present embodiment does not have to include all of the components shown in FIG. Hereinafter, the “acceleration sensor error measurement device” is referred to as an “acceleration error measurement device”.

  The acceleration error measurement device 1 according to the present embodiment performs processing for measuring offset error information and sensitivity error information of the acceleration sensor 20 included in the measurement target device 2.

  In the present embodiment, the measurement target device 2 includes an acceleration sensor 20, a microcomputer 22, and a communication unit 24. For example, the measurement target device 2 may be a game controller as shown in FIGS. 2A to 2C or a mobile phone as shown in FIG.

  The acceleration sensor 20 detects acceleration in three axial directions (x-axis direction, y-axis direction, and z-axis direction) orthogonal to each other. When the orientation of the measurement target device 2 changes, the orientation of the acceleration sensor 20 also changes. In addition, the direction of the acceleration sensor varies depending on the measurement target device. For example, in the measurement target device 2 shown in FIGS. 2 (A) to 2 (D), the three detection axis directions of each acceleration sensor 20 are the directions shown in FIGS. 2 (A) to 2 (D). Yes.

  The acceleration sensor 20 detects acceleration for three axes at regular time intervals (for example, 5 msec), and the acceleration value (detection information) detected by the acceleration sensor 20 is transmitted to the acceleration error measurement device 1 by the communication unit 24. Sent.

  The microcomputer (microcomputer) 22 performs processing for transmitting the acceleration value (detection information) detected by the acceleration sensor 20 to the acceleration error measurement device 1 via the communication unit 24.

  The communication unit 24 includes an antenna and a wireless module, and wirelessly transmits data to the acceleration error measurement device 1 by a communication method such as Bluetooth (registered trademark). The communication unit 24 sequentially transmits acceleration values (detection information) detected by the acceleration sensor 20 to the acceleration error measurement device 1 at predetermined time intervals. Note that the communication unit 24 may be connected to the acceleration error measurement device 1 with a communication cable and transmit the detection information via the communication cable.

  The acceleration error measuring apparatus 1 according to the present embodiment includes a processing unit 10, a storage unit 30, an operation unit 32, a display unit 34, an information storage medium 36, a communication unit 38, and a sound output unit 40.

  The storage unit 30 is a work area such as the processing unit 10 or the communication unit 38, and its function can be realized by hardware such as RAM (VRAM).

  The operation unit 32 is used by the user to input operation data for instructing the start or end of error measurement of the acceleration sensor, and the function can be realized by an operation button, a touch panel display, a keyboard, a mouse, and the like.

  The display unit 34 outputs information instructed by the processing unit 10 and functions as a CRT display, LCD (liquid crystal display), OELD organic EL display, PDP (plasma display panel), touch panel type display, or It can be realized by hardware such as an HMD (head mounted display).

  The sound output unit 40 outputs a sound instructed by the processing unit 10, and its function can be realized by hardware such as a speaker or headphones.

  The communication unit 38 includes an antenna and a wireless module, and receives data from the measurement target device 2 via the communication unit 24 of the measurement target device 2 by a communication method such as Bluetooth (registered trademark). For example, the communication unit 38 sequentially receives detection information from the acceleration sensor 20 in the measurement target device 2 at predetermined time intervals.

  The communication unit 38 may communicate with the server via a network (Internet). The function can be realized by various processors, hardware such as a communication ASIC, a network interface card, or a program. The communication unit 38 can perform both wired and wireless communications.

  The processing unit 10 (processor) performs processing based on detection information of the acceleration sensor 20 received from the measurement target device 2, a program developed from the information storage medium 36 to the storage unit 30, and the like.

  The processing unit 10 according to the present embodiment includes an acceleration information generation unit 11, simultaneous equation creation unit 12, simultaneous equation calculation unit 13, and acceleration error calculation unit 14. Further, the processing unit 10 may include a display control unit 15 and a sound output control unit 16.

  The acceleration information generation unit 11 acquires the detection information of the acceleration sensor 20 from the measurement target device 2 and performs a process of generating acceleration information based on the acquired detection information.

  For example, the acceleration information generation unit 11 determines whether or not the acceleration due to the motion of the acceleration sensor 20 can be ignored based on the detection information of the acceleration sensor 20, and the acceleration due to the motion of the acceleration sensor 20 can be ignored. The acceleration information may be generated based on the detection information at.

  In addition, for example, the acceleration information generation unit 11 determines the acceleration due to the motion of the acceleration sensor 20 if a state in which the fluctuation range of the detection information of the acceleration sensor 20 satisfies a predetermined condition (for example, a state where the variation is less than a predetermined value) continues for a predetermined time. May be determined to be in a state that can be ignored.

  Further, for example, the acceleration information generation unit 11 generates the acceleration information based on a plurality of detection information acquired at the predetermined time (for example, an average of all or part of the plurality of detection information acquired at the predetermined time). The value may be acceleration information).

  The simultaneous equation creating unit 12 is based on the detection information of the acceleration sensor 20 based on the detection information of the acceleration sensor 20 as variables of an ellipsoidal equation including six parameters corresponding to the respective sensitivity and offset in the three detection axis directions orthogonal to each other. A set of acceleration information is substituted, and a process of creating simultaneous quadratic equations composed of six quadratic equations with the six parameters as unknowns is performed.

For example, the simultaneous equation creating unit 12 sets the three detection axes of the acceleration sensor 20 as the x-axis, y-axis, and z-axis, and among the six parameters, the x-axis direction, the y-axis direction, and the z-axis direction of the acceleration sensor 20 When the sensitivity parameters are a, b, and c, and the offset parameters of the acceleration sensor 20 in the x-axis direction, y-axis direction, and z-axis direction are p, q, and r, respectively, The equation {(x−p) / a} ² + {(y−q) / b} ² + {(z−r) / c} ² = 1 may be used.

  The simultaneous equation calculation unit 13 includes the five new unknowns represented by the equations including at least one of the six unknowns as the simultaneous quadratic equation created by the simultaneous equation creation unit 12 and the six unknowns. A process of solving the simultaneous linear equations by reducing the simultaneous linear equations to five linear equations that do not include any of them is performed.

  Further, for example, the simultaneous equation calculation unit 13 converts the simultaneous linear equations so that the coefficient matrix of the simultaneous linear equations has an absolute value of the diagonal elements larger than the absolute values of all other elements that are not diagonal elements. You may make it create.

  Further, for example, the simultaneous equation calculation unit 13 calculates two pieces of acceleration information having the maximum and minimum values in the first detection axis direction among the six sets of acceleration information based on the detection information of the acceleration sensor 20 as an ellipsoidal equation. One of the linear equations is created based on a polynomial obtained by subtracting the other from one of the two quadratic equations obtained by substituting each of the variables. Based on a polynomial obtained by subtracting the other from one of two quadratic equations obtained by substituting the two acceleration information with the maximum and minimum values in the detection axis direction into variables of the ellipsoidal equation, respectively. It is obtained by creating another one of the equations and substituting two acceleration information having the maximum and minimum values in the third detection axis direction into the variables of the ellipsoidal equation among the six sets of acceleration information. Subtract the other from one of the two quadratic equations It may be created other one of linear equations based on the obtained polynomial Te.

  Further, for example, the simultaneous equation calculation unit 13 includes the six unknowns included in each term of a polynomial obtained by calculating any two quadratic equations of the simultaneous quadratic equation or a polynomial obtained by modifying the polynomial. A simultaneous linear equation may be created by associating a formula obtained by multiplying the formula or a formula obtained by multiplying the formula with the five new unknowns.

  Further, for example, the simultaneous equation calculation unit 13 is obtained in a state in which predetermined three axes orthogonal to each other in the three-dimensional space formed by the three detection axes of the acceleration sensor 20 face the opposite direction of the gravity direction or the vicinity thereof. Using three sets of acceleration information based on the three sets of detection information and three sets of acceleration information based on the three sets of detection information obtained in a state in which the predetermined three axes face the gravity direction or the vicinity thereof, respectively. A simultaneous quadratic equation may be created.

  The acceleration error calculation unit 14 calculates the six unknown values from the five new unknown values obtained by the simultaneous equation calculation unit 13, and based on the calculation results, the acceleration error calculation unit 14 calculates the three detection axis directions. Processing for calculating offset error information and sensitivity error information is performed.

  The display control unit 15 performs processing for displaying predetermined information on the display unit 34. For example, the display control unit 15 may cause the display unit 34 to display information indicating measurement start and measurement end, offset error information and sensitivity error information of the measurement result, and the like. Further, the display control unit 15 displays information indicating the end of measurement when a state that satisfies a predetermined condition of the detection information of the acceleration sensor 20 after the start of measurement (for example, a state that is equal to or less than a predetermined value) continues for a predetermined time. You may make it display on.

  The sound output control unit 16 performs a process of outputting a predetermined sound from the sound output unit 40. For example, the sound control unit 16 may cause the display unit 34 to output a sound indicating the start or end of measurement from the sound output unit 40. In addition, the sound control unit 16 generates a sound indicating the end of measurement when a state in which the fluctuation range of the detection information of the acceleration sensor 20 satisfies a predetermined condition (for example, a state where the variation is not more than a predetermined value) continues for a predetermined time after the measurement starts. You may make it output from the sound output part 40. FIG.

  The information storage medium 36 (a computer-readable medium) stores programs, data, and the like, and functions as an optical disk (CD, DVD), magneto-optical disk (MO), magnetic disk, hard disk, magnetic tape. Alternatively, it can be realized by a memory (ROM). The processing unit 10 performs various processes of the present embodiment based on a program (data) stored in the information storage medium 36. That is, the information storage medium 36 stores a program for causing the computer to function as each unit of the present embodiment (a program for causing the computer to execute the processing of each unit).

  Note that a program (data) for causing a computer to function as each unit of the present embodiment is distributed from the storage unit or the information storage medium of the server to the information storage medium 36 (or the storage unit 30) via the network. It may be. Use of such server information storage media is also within the scope of the present invention.

1-2. Error measurement method of acceleration sensor 1-2-1. Meaning of error T is the true acceleration acting on the acceleration sensor. It is assumed that T includes not only acceleration due to motion but also gravity. For example, when the sensor is stationary, T = 1G. “G” is a unit of acceleration, and 1G = 9.80665 m / s ² . Strictly speaking, the magnitude of gravity (gravity acceleration) varies depending on latitude, altitude, etc., but since the difference is slight, it is assumed here to be a constant value. It is assumed that the value obtained by measuring with the sensor is M for the true acceleration T. At this time, the difference E between M and T is defined as error E as shown in the following equation (1).

  Since the magnitude of the error E varies depending on the value of T, E is expressed as a function of T. Since the second and higher order components of T are small, E is approximated by a first order equation of T as shown in the following equation (2).

Since the deviation of the measured value M at T = 0 is e ₀ , e ₀ is called an offset error (also called 0G error). On the other hand, e ₁ is called a sensitivity error because it corresponds to a sensitivity shift of the sensor. If there is no error, e ₀ = 0 and e ₁ = 0. The relationship between M and T is expressed by the following equation (3).

1-2-2. Accelerometer error measurement (1 axis)
Consider a method of measuring an offset error and a sensitivity error for only one detection axis (one of x, y, z) of an acceleration sensor. When the sensor output in a stationary state is measured with the detection axis direction of the acceleration sensor directed directly above or directly below, the error can be obtained as follows.

A measured value (corresponding to the above-described detection information) in a stationary state with the detection axis directed right above is assumed to be m ₁ . Since the true acceleration value in this state is 1G, the following equation (4) is obtained from equation (3).

Similarly, the measured value in a stationary state with the detection axis directed directly below is m ₂ . Since the true acceleration value in this state is −1G, the following equation (5) is obtained from equation (3).

When e ₀ and e ₁ are obtained from the equations (4) and (5), the following equations (6) and (7) are obtained.

The unit of e ₀ is G, and e ₁ is unitless (dimensionless). Thus, if the direction of the detection axis of the acceleration sensor can be matched with the vertical direction, the error can be easily obtained.

  It is assumed that the acceleration sensor is built in the game controller. When the shape of the controller is box-shaped and the direction of the surface (the direction of the normal of the surface) matches the detection axis direction of the acceleration sensor, error measurement can be easily performed. If the controller is placed on a surface that can be regarded as a horizontal plane (for example, on a desk), the detection axis of the acceleration sensor can be aligned in the vertical direction.

  However, when the shape of the controller is a curved surface, or when the outer shape of the controller does not match the direction of the detection axis of the acceleration sensor, it takes time and effort to align the detection axis of the sensor in the vertical direction. For example, it is necessary to adjust the direction while supporting the controller and search for a direction that maximizes (or minimizes) the measured value.

1-2-3. Accelerometer error measurement (in any direction)
1-2-3-1. Ellipsoidal equations Let's consider a method that can measure errors without worrying about the orientation of the acceleration sensor. Assume that the controller on which the acceleration sensor is mounted is stationary in various directions and the sensor output value is examined. The measurement is performed N times while changing the direction each time, and the values of the respective x, y, and z axes are x _i , y _i , and z _i (i = 1, 2,..., N), respectively. . However, the unit of acceleration is G.

Since only 1G gravity is acting on the controller, the vector (x _i , y _i , z _i ) has a magnitude of 1 if there is no error in the acceleration sensor. Therefore, the following equation (8) is established, and all the N measurement values are on a spherical surface having a radius of 1 centered on the origin. FIG. 3 is a diagram schematically showing the sphere represented by the formula (8).

  On the other hand, considering the error of the acceleration sensor, the scale (enlargement / reduction) due to the sensitivity error and the parallel movement due to the offset error are added in the x, y and z axis directions. Therefore, instead of the sphere of equation (8), the main axis is an ellipsoid (axis aligned ellipsoid) parallel to the x, y, and z axes as in the following equation (9). However, a> 0, b> 0, and c> 0. FIG. 4 is a diagram schematically showing the ellipsoid represented by Expression (9).

  The center coordinates p, q, and r correspond to offset errors in the x, y, and z directions, respectively, and a-1, b-1, and c-1 correspond to sensitivity errors in the x, y, and z directions, respectively. If the ellipsoidal equation is determined, the error of the acceleration sensor is obtained.

1-2-3-2. Solving Equations Since there are six unknowns in equation (9), p, q, r, a, b, and c, six equations are required to find a solution. Therefore, using the six measurement values (x ₁ , y ₁ , z ₁ ), (x ₂ , y ₂ , z ₂ ),..., (X ₆ , y ₆ , z ₆ ), Make simultaneous equations. As shown in FIG. 5, the six measurement values (corresponding to the six sets of acceleration information) are placed on the surface of the ellipsoid represented by Expression (9).

  Since these simultaneous equations are quadratic equations of unknowns p, q, r, a, b, and c, it is difficult to solve them. Therefore, it is reduced to simultaneous linear equations as follows.

  First, when the equation (10a) is subtracted from the equation (10b) and transformed, the following equation (11) is obtained.

  Here, the unknown is replaced as follows.

  Then, Expression (11) becomes a linear expression of α, β, γ, δ, ε as in the following Expression (13).

Similarly, two formulas are selected from the formulas (10a) to (10f), and a difference between them is taken to create a linear formula. Since two formulas are selected from the six formulas, ₆ C ₂ = 15 formulas can be formed, of which five are independent. Α, β, γ, δ, ε can be obtained by solving the quinary simultaneous linear equations.

  p, q, and r are obtained by the following equation (14).

  When the equation (10a) is transformed, the following equation (15) is obtained, and a is obtained from this equation.

  b and c are obtained by the following equation (16).

  P, q, and r obtained by the above calculation are offset errors in the x, y, and z directions, respectively. Further, a-1, b-1, and c-1 are sensitivity errors in the x, y, and z directions, respectively.

1-2-3-3. Configuration of independent simultaneous equations When solving the simultaneous equations (10a) to (10f), two equations were selected from these six quadratic equations, and a linear equation was created by taking the difference between them. Since there are ₆ C ₂ = 15 ways to select the equation, 15 linear equations can be created. However, only 5 of them are independent. I explain this using graph theory. In order to make the formula numbers easier to see, (a), (b),..., (F) are written instead of (10a), (10b),. .

  As shown in FIG. 6, six nodes (points) A, B,..., F are arranged, and each means a quadratic expression (a), (b),. To do. Expressions (a), (b),..., (F) are referred to as node expressions of nodes A, B,. A linear expression created from the difference between two node expressions is represented by an edge (line segment) connecting the nodes. For example, the edge AB in FIG. 7 means a linear expression (a)-(b). A linear expression corresponding to an edge will be referred to as an edge expression. The simultaneous linear equations are represented as a graph as shown in FIG. 8, for example. FIG. 8 shows five linear expressions.

  As described above, when the simultaneous linear equations are associated with the graph, the following can be said.

  “A necessary and sufficient condition for the simultaneous linear equations to be independent is that the graph does not contain cycles.”

  A cycle is a closed path, also called a closed path. FIG. 8 is an example of a graph representing an independent simultaneous linear equation. In contrast, FIG. 9 is not independent because it includes cycles B-C-E-B (including dependent equations).

  The relationship between the independence of simultaneous linear equations and the cycle of the graph is derived as follows.

[Requirements]
In the graph of FIG. 10, there are two edge expressions (a)-(b) and (b)-(c). From these two formulas, the primary formula (a)-(c) can be made by calculating ((a)-(b)) + ((b)-(c)). Therefore, the state of FIG. 11 in which the edge AC is added to FIG. 10 includes a dependent expression. Generalizing this idea leads to "If the graph contains cycles, the edge expression contains a dependent expression".

[Sufficient conditions]
On the other hand, “the edge expression is independent if the graph does not include a cycle” can be explained as follows. The removal of one edge from the graph that does not contain cycles, graphs two parts (subgraph) divided into G ₁ and G _2. For example, when the edge CE is removed from the graph of FIG. 8, G ₁ = {{A, B, C, D}, {AB, BC, CD}} and G ₂ = {{E, F} as shown in FIG. , {EF}}. Consider whether or not a new edge expression (c)-(e) can be created from the four edge expressions in FIG. When making edge expression containing (c), for example, (c) - as in (a), will always those containing the node type of the other nodes in G _1. Similarly, it includes node type other nodes of the edge type always G ₂ including (e). Since there is no node common to G ₁ and G ₂ , if a linear expression including both (c) and (e) is created, for example, (c) − (e) − (a) + (f) However, the terms other than (c) and (e) always remain without disappearing. Therefore, the edge formulas (c)-(e) cannot be made from the state of FIG. Therefore, the edge formulas (c)-(e) are independent in the graph of FIG. For the same reason, the edge formulas (b) to (c) in FIG. 8 are also independent.

Further, the fact that the edge formulas (a) to (b) in FIG. 8 are independent is explained as follows. When the edge AB is removed from this graph, one of the remaining subgraphs G ₁ and G ₂ becomes only the node A (has no edge). Since there is no edge expression including the expression (a), the edge expressions (a)-(b) cannot be created from the existing edge expressions. Therefore, in the graph of FIG. 8, the edge formulas (a)-(b) are independent. For the same reason, the edge expressions (c)-(d) and (e)-(f) in FIG. 8 are also independent.

  Generalizing the above idea leads to “If the graph does not contain cycles, the edge expression is independent”.

  A graph that does not include a cycle has a (one or more) tree structure. Moreover, when two trees are connected by one edge, it becomes one tree. Therefore, using a given node to create a graph that does not include cycles and has the maximum number of edges results in a single tree.

  In trees, it is known that the number of edges is one less than the number of nodes. From the above, when there are six node expressions, up to five independent primary expressions can be created.

1-2-3-4. Improvement of calculation accuracy Calculation for obtaining an error from six measured values corresponds to obtaining an ellipsoid passing through six points in a three-dimensional space. Therefore, in order to improve the accuracy of the calculation result, the six measured values x _i , y _i , and z _i (i = 1, 2,..., 6) should be separated as much as possible in the xyz space. Intuitively guessed. This can also be understood from the fact that the relative accuracy of the coefficient of equation (13) decreases when the measured values are close to each other.

  There are various algorithms for solving simultaneous linear equations, but many of them (Gauss elimination, Gauss-Jordan method, Gauss-Seidel method, etc.) have small values (absolute values) of the diagonal elements of the coefficient matrix. In some cases, the accuracy of the solution is degraded, and a problem that the solution cannot be obtained occurs. For this reason, when creating simultaneous linear equations, it is important that the absolute values of the diagonal elements of the coefficient matrix are increased.

Therefore, when measuring x ₁ , y ₁ , and z ₁ , the x axis of the acceleration sensor is directed substantially upward. Similarly, as shown in Table 1, six measurements are performed by changing the direction. The orientation need not be accurate. By setting in this way, the six measurement values are positioned sufficiently apart from each other in the xyz space.

FIG. 13 shows the arrangement of the measurement values m _{1 to} m ₆ obtained by the six measurements shown in Table 1 on the surface of the ellipsoid represented by Expression (9). For example, if the x-axis direction of the acceleration sensor is in a state where the x-axis direction is exactly upward, that is, directly above (the direction opposite to the direction of gravity) and is stationary, the measured value m ₁ is (a + p, q, r), and the acceleration sensor x-axis direction accurately measure m ₂ if a stationary state facing downward i.e. beneath direction (gravity direction) of becomes (-a + p, q, r ). Similarly, if the state where the y-axis direction of the acceleration sensor is stationary facing up direction measurements _{m 3 (p, b + q} , r) becomes, the y-axis direction of the acceleration sensor is oriented directly below direction still measurements _{m 4} if a state of being becomes (p, -b + q, r ). Similarly, if the state where the z-axis direction of the acceleration sensor is stationary facing up direction measurements m ₅ is (p, q, c + r ) becomes, z-axis direction of the acceleration sensor is oriented directly below direction still In this state, the measured value m ₆ is (p, q, −c + r).

However, the direction in which the x-axis, y-axis, and z-axis of the acceleration sensor are aligned does not have to be accurate, and may be directed to the vicinity of the directly above direction or the directly below direction. Even in this case, the measurement values m _{1 to} m ₆ are within a predetermined range centered on the measurement value when the x-axis, y-axis, and z-axis of the acceleration sensor are aligned directly above or below (see FIG. 13). In the xyz space, the positions are sufficiently separated from each other.

  Further, if the acceleration sensor has normal accuracy, a≈1, b≈1, c≈1, p≈0, q≈0, r≈0, so each measured value is approximately as follows.

  Therefore, the simultaneous linear equations are constructed as follows.

  That is, first, formula (10a) -formula (10b), formula (10c) -formula (10d), formula (10e) -formula (10f), formula (10a) -formula (10c) + formula (10b) -formula The following formulas (18a) to (18e) are obtained from (10d), formula (10a) -formula (10e) + formula (10b) -formula (10f).

  Next, when the equation (12) is substituted into the equations (18a) to (18e), a simultaneous linear equation including the following equations (19a) to (19e) is obtained.

  Accordingly, in the simultaneous linear equations consisting of the equations (19a) to (19e), if the coefficient matrix having the coefficients of α, β, γ, δ, and ε as M, the equation (19a) to (19e) The simultaneous linear equations can be expressed as follows.

  The coefficient matrix M is as shown in the following equation (21).

  Then, from the equation (17), the coefficient matrix M has approximately the following values, and the absolute values of the diagonal elements are larger than the absolute values of the other elements.

  By using this coefficient matrix, simultaneous linear equations can be solved stably and accurately.

  In general, measurement is performed by changing the direction of the acceleration sensor according to a predetermined rule, and simultaneous linear equations are created from the simultaneous quadratic equations (10a) to (10f) using the obtained six measured values according to the predetermined rule. By doing so, it is possible to obtain a coefficient matrix in which the absolute values of diagonal elements are larger than the absolute values of other elements.

1-2-4. Detection of the stationary state When measuring the error of the acceleration sensor using the above method, the acceleration sensor needs to be stationary at the time of measurement. Originally, it is not necessary to perform an accelerating motion, so a constant velocity linear motion is allowed, but in reality it is easier to stop.

  When the measurement value hardly fluctuates for a certain period of time, it is determined to be stationary. Strictly speaking, this criterion is not correct. This is because a place where an OK determination should be given only in a state where the acceleration motion is not performed (including a stationary state) is OK even if the motion is performed at a constant acceleration. However, in reality, if the constant acceleration motion continues to some extent, it should move in that direction, so if it can be confirmed that it is not moving (when placed on a desk, etc.) Absent.

As an actual example, if the state where the fluctuation range of the measured value is 0.03 G or less continues for 1 second, it is determined that the object is stationary. A value obtained by averaging the measurement values for one second is treated as one measurement value (x _i , y _i , z _i ). Further, by taking the average in this way, the influence of random noise and sensor rounding errors can be reduced, and the reliability of the measured value can be increased.

A specific example of the process in which the acceleration error measurement device 1 according to the present embodiment determines whether or not the measurement target device 2 (acceleration sensor 20) is stationary will be described with reference to FIG. FIG. 14 is a diagram illustrating an example of a time series of measurement values in one of the x-axis direction, the y-axis direction, and the z-axis direction (for example, the x-axis direction), and the measurement interval is 5 msec. Acceleration error measuring apparatus 1 starts the acquisition of the measured values of the acceleration sensor at time t _1, the variation width of the measured values of the following conditions 0.03G determines whether lasting 1 second. Specifically, first, at time t ₆ after the elapse of the time t ₁ 1 sec, the fluctuation range of the measurements taken in one second of time t ₁ ~t ₆ is determined to or less than 0.03G To do. For example, it may be determined whether or not the difference between the maximum value and the minimum value of the measurement values acquired in one second from time t _{1 to} t ₆ is 0.03 G or less.

Here, the fluctuation range of the measurement value acquired in one second from time t _{1 to} t ₆ is larger than 0.03 G (measurement value (minimum value) at time t ₃ and measurement value (maximum value) at time t _4. ) difference 0.03G larger) for the acceleration error measuring apparatus 1, then, at time _{t 7} after a lapse of 5msec from time _{t 6,} newly obtains the measured value of the acceleration sensor, the time _t 2 ~ fluctuation width of the measurement values obtained in one second of t ₇ is equal to or less 0.03 g. As described above, the acceleration error measuring apparatus 1 newly acquires the measured value of the acceleration sensor until the fluctuation range of the measured value acquired in the past 1 second (the latest 1 second) becomes 0.03G or less every 5 msec. Repeat the process. The acceleration error measuring apparatus 1, since the fluctuation range of the measured value of one second from time t ₅ to time t ₉ (difference between the maximum value and the minimum value) is equal to or less than 0.03 g, measured device 2 (acceleration sensor 20) is determined to be stationary, and ends the acquisition of the measured values at the time t _9.

However, the acceleration error measuring device 1, in one second from time t ₅ to time t _6, one of the fluctuation range of the measured values of the other two axially (e.g., y-axis and z-axis direction) 0. If it exceeds 03G, it is determined that the measurement target device 2 (acceleration sensor 20) is not stationary, and the three-axis direction is maintained until all the fluctuation ranges of the measurement values in the three-axis direction are 0.03G or less for 1 second. Continue to acquire the measured value.

The acceleration error measuring apparatus 1 handles, a value obtained by averaging the measured values in the three axis directions of one second from time _{t 5} to time _{t 9} 1 single measurements _{(x i, y i, z} i) as . That is, if the same process is performed six times in total, six measured values (x ₁ , y ₁ , z ₁ ) to (x ₆ , y) as average values with reduced influence of random noise and sensor rounding error are obtained. ₆ , z ₆ ).

In the example of FIG. 14, in the determination at time t ₆ , the measurement value at time t ₃ (minimum value at time t _{1 to} t ₆ ) and the measurement value at time t ₄ (time t _{1 to} t _6). It can be seen that the difference in the maximum value at (1) is greater than 0.03G. Therefore, when a time elapses after the time point t ₃ 1 sec to t _8, at any time t ₇ ~t ₈ also is clear that the fluctuation range of the measurements taken in the past one second is greater than 0.03G Therefore, the determination process may not be performed at times t _{7 to} t ₈ .

1-3. Processing of Acceleration Sensor Error Measuring Device Next, a processing example of the acceleration sensor error measuring device of the present embodiment will be described with reference to the flowchart of FIG.

First, the acceleration error measuring apparatus 1 includes six sets of acceleration information (x ₁ , y ₁ , z ₁ ) to (x ₆ ) in the variable (x, y, z) of the ellipsoidal equation shown in Expression (9). , Y ₆ , z ₆ ) are substituted respectively, and simultaneous quadratic equations composed of six quadratic equations with a, b, c, p, q, and r shown in equations (10a) to (10f) as unknowns. Step S10 for creating the simultaneous equations.

  Next, the simultaneous quadratic equations having unknown numbers a, b, c, p, q, and r created in step S20 are composed of five linear equations having α, β, γ, δ, and ε as unknown numbers. A step S20 for solving the simultaneous linear equation by reducing to the linear equation, a simultaneous equation calculating step.

Here, the correspondence relationship between α, β, γ, δ, ε and a, b, c, p, q, r is defined in advance. For example, as shown in Equation (12), Equation (10a) - formula contained in each term of the polynomial obtained by (10b) (11), unknowns a, b, c, p, q, composed of r formula ^{p, (a 2 / b 2} ) q, (a 2 / C ² ) r, a ² / b ² , a ² / c ² may be associated with the unknowns α, β, γ, δ, ε. Further, for example, the expressions p, (a ² / b ² ) q, (a ² / c ² ) r, a ² / b ² , and a ² / c ² are converted into constants included in each term of the polynomial (11). Equations 2p, 2 (a ² / b ² ) q, 2 (a ² / c ² ) r, a ² / b ² , and a ² / c ² multiplied by real numbers in FIG. You may make it correspond. Further, for example, an expression composed of unknown numbers a, b, c, p, q, r included in each polynomial term obtained by transforming the polynomial (11) or an expression obtained by multiplying the expression by a real number is an unknown number α, β, You may make it respond | correspond with (gamma), (delta), and (epsilon).

  In step S20, the acceleration error measuring apparatus 1 performs a predetermined calculation on the six quadratic equations shown in the equations (10a) to (10f) to create simultaneous linear equations. For example, as described above, formula (10a) -formula (10b), formula (10c) -formula (10d), formula (10e) -formula (10f), formula (10a) -formula (10c) + formula (10b ) -Formula (10d), Formula (10a) -Formula (10e) + Formula (10b) -Formula (10f) may be used to create the linear equations (19a) to (19e).

  Finally, the acceleration error measuring apparatus 1 calculates the values of the unknowns a, b, c, p, q, r from the values of the unknowns α, β, γ, δ, ε obtained in step S20, and based on the calculation results. Step S30 for calculating offset error information (eg, p, q, r) and sensitivity error information (eg, a-1, b-1, c-1) in the three detection axis directions of the acceleration sensor, and an acceleration error calculating step.

  Next, a processing example in which the acceleration sensor error measurement device of the present embodiment generates acceleration information will be described with reference to the flowchart of FIG.

  First, the acceleration error measurement device 1 acquires detection information of the acceleration sensor 20 from the measurement target device 2 until a predetermined time T elapses (steps S50 and S60).

  When the predetermined time T has elapsed (in the case of Yes in step S60), the acceleration error measuring apparatus 1 next determines that the fluctuation range of the detection information acquired in the past T time is a predetermined value (in the example shown in FIG. 4, 0.03G ) It is determined whether or not (step S70).

  In step S70, when the fluctuation range of the detection information is larger than the predetermined value (No in step S70), the acceleration error measurement device 1 acquires the next detection information of the acceleration sensor 20 (step S80), and again. The determination process of step S70 is performed.

In step S70, when the fluctuation range of the detection information is equal to or smaller than a predetermined value (Yes in step S70), the acceleration error measurement device 1 calculates an average value of the detection information acquired in the past T time to obtain acceleration information ( x _i , y _i , z _i ) (step S90).

The acceleration error measuring apparatus 1 creates six sets of acceleration information (x ₁ , y ₁ , z ₁ ) to (x ₆ , y ₆ , z ₆ ) by repeating the processing of steps S50 to S90 six times.

  A processing example for further improving the error measurement accuracy of the acceleration sensor will be described with reference to the flowchart of FIG.

  First, the ξ axis of three axes (ξ axis, 邇 I, 謗 I) orthogonal to each other in the three-dimensional space created by the three detection axes (x axis, y axis, z axis) of the acceleration sensor 20 The measurement target device 2 is set so that is directed right above (opposite to the direction of gravity) or the vicinity thereof (step S100). Here, the ξ axis, 邇 i, and 謗 で are predetermined three axes orthogonal to each other, and may be determined in consideration of, for example, the shape of the measurement target device 2. Note that the ξ axis, 邇, and 謗 may coincide with the three detection axes (x-axis, y-axis, and z-axis) of the acceleration sensor 20, respectively. In this case, the processing according to the flowchart of FIG. It becomes processing corresponding to.

Next, for example, according to the flowchart shown in FIG. 16, a process of generating acceleration information (x ₁ , y ₁ , z ₁ ) is performed (step S110).

  Steps S100 and S110 correspond to a first acceleration information generation step.

  Next, the measurement target device 2 is set so that the ξ axis faces directly below (gravity direction) or the vicinity thereof (step S120).

Next, the acceleration information (x ₂ , y ₂ , z ₂ ) is generated according to the flowchart shown in FIG. 16, for example (step S130).

  Steps S120 and S130 correspond to a second acceleration information generation step.

Next, the measurement target device 2 is set so that the heel is directed right above or in the vicinity thereof (step S140), and, for example, according to the flowchart shown in FIG. 16, acceleration information (x ₃ , y ₃ , z ₃ ) Is generated (step S150).

  Steps S140 and S150 correspond to a third acceleration information generation step.

Next, the measurement target device 2 is set so that the heel is directed directly downward or in the vicinity thereof (step S160). For example, according to the flowchart shown in FIG. 16, the acceleration information (x ₄ , y ₄ , z ₄ ) Generation processing is performed (step S170).

  Steps S160 and S170 correspond to a fourth acceleration information generation step.

Next, the measurement target device 2 is set so that the heel is directed upward or in the vicinity thereof (step S180), and, for example, according to the flowchart shown in FIG. 16, acceleration information (x ₅ , y ₅ , z ₅ ) Is generated (step S190).

  Steps S180 and S190 correspond to a fifth acceleration information generation step.

Next, the measurement target device 2 is set so that the heel is directed downward or in the vicinity thereof (step S200). For example, according to the flowchart shown in FIG. 16, the acceleration information (x ₆ , y ₆ , z ₆ ) Generation processing is performed (step S210).

  Steps S200 and S210 correspond to a sixth acceleration information generation step.

  Finally, for example, according to the flowchart shown in FIG. 15, calculation processing of offset error information and sensitivity error information of the acceleration sensor 20 is performed (step S220).

1-4. Effects of this Embodiment According to this embodiment, arbitrary six sets of acceleration information (x ₁ , y ₁ , z ₁ ) to (x ₆ , y ₆ , z ₆ ) based on the detection information of the acceleration sensor 20 are obtained. If so, the offset errors p, q, r and sensitivity errors a-1, b-1, c-1 of the acceleration sensor 20 can be calculated algebraically. Therefore, even if detection information in a state in which each detection axis direction of the acceleration sensor 20 is accurately aligned upward and downward as in the conventional method cannot be obtained, it is based on the detection information obtained regardless of the direction of the acceleration sensor 20. Offset errors p, q, r and sensitivity errors a-1, b-1, c-1 can be calculated.

  In addition, in the method of obtaining the solution of the simultaneous quadratic equation by iterative calculation with a computer by Newton method (Newton-Raphson method), it takes time until the calculation converges. However, according to the present embodiment, the simultaneous quadratic equation ( Since 10a) to (10f) are reduced to simultaneous linear equations and solved algebraically, the calculation time can be shortened.

  Further, in the present embodiment, if the coefficient matrix M is set as shown in Expression (22), the absolute values of the diagonal elements of the coefficient matrix M become larger than the absolute values of the other elements. A solution can be obtained without performing pivot selection in the calculation process of the following equations (19a) to (19e), and the calculation error becomes smaller. Therefore, the simultaneous linear equations (19a) to (19e) can be stably and accurately solved without increasing the calculation load.

Further, in the present embodiment, as shown in FIG. 17, six sets of acceleration information obtained by making the ξ axis, 邇 i, and 謗 i orthogonal to each other point in the vicinity of the directly upward direction and the vicinity of the directly downward direction ( If x ₁ , y ₁ , z ₁ ) to (x ₆ , y ₆ , z ₆ ) are used, six sets of acceleration information are obtained on the xyz space created by the x-axis, y-axis, and z-axis of the acceleration sensor 20. Corresponding 6 points are located sufficiently away from each other. Therefore, since the ellipsoidal equation (9) can be specified with higher accuracy by using these six sets of acceleration information, the offset errors p, q, r and sensitivity errors a-1, b-1 of the acceleration sensor 20 are identified. , C−1 can be calculated with higher accuracy.

In the present embodiment, as shown in FIG. 16, when the fluctuation range of the detection information of the acceleration sensor 20 is equal to or less than a predetermined value, the average value of the detection information acquired at the predetermined time is obtained for a predetermined time. If acceleration information (x ₁ , y ₁ , z ₁ ) to (x ₆ , y ₆ , z ₆ ) is taken, acceleration information (x ₁ , y ₁ , z ₁ ) to (x ₆ , y ₆ , z ₆ ) Since the gravitational acceleration components in the x, y, and z axis directions are more accurately reflected, the ellipsoidal equation (9) can be specified with higher accuracy. In addition, since the influence of random noise and rounding error included in the detection information of the acceleration sensor 20 can be reduced, the offset errors p, q, r and sensitivity errors a-1, b-1, c-1 of the acceleration sensor 20 are reduced. Can be calculated with higher accuracy.

  In the present embodiment, assuming a game controller as the measurement target device 2, the offset error and sensitivity error of the acceleration sensor included in the game controller are known. You can test the operation of the application in the maximum state.

2. Game system 2-1. Configuration FIG. 18 is an example of a functional block diagram of the game system of the present embodiment. In the game system of the present embodiment, it is not necessary to include all the units shown in FIG. 18, and a part of the game system may be omitted.

  The game system according to this embodiment includes a main body device 100, an input device 200, an information storage medium 180, a display unit (display device) 190, a speaker 192, and a light source 198.

  The input device 200 includes an acceleration sensor 210, an imaging unit 220, a speaker 230, a vibration unit 240, a microcomputer 250, and a communication unit 260.

  The acceleration sensor 210 detects acceleration in three axes (x axis, y axis, and z axis). That is, the acceleration sensor 210 can detect accelerations in the vertical direction, the horizontal direction, and the front-rear direction. Note that the acceleration sensor 210 detects acceleration every certain time (for example, 5 msec). The acceleration value (detection information) detected by the acceleration sensor 210 is transmitted to the main body device 100 by the communication unit 260.

  The imaging unit 220 includes an infrared filter 222, a lens 224, an imaging element (image sensor) 226, and an image processing circuit 228. The infrared filter 222 is disposed in front of the input device 200 and allows only infrared light from light incident from the light source 198 disposed in association with the display unit 190 to pass therethrough. The lens 224 collects the infrared light that has passed through the infrared filter 222 and emits it to the image sensor 226. The image pickup device 226 is a solid-state image pickup device such as a CMOS sensor or a CCD, for example, and picks up infrared rays collected by the lens 224 to generate a picked-up image. The captured image generated by the image sensor 226 is processed by the image processing circuit 228. For example, a captured image obtained from the image sensor 226 is processed to detect a high-luminance portion, and position information (specific position) of the light source in the captured image is detected. If there are a plurality of light sources, position information on the captured image is detected. Further, the detected position information is transmitted to the main device 100 by the communication unit 260.

  The speaker 230 outputs the sound acquired from the main body device 100 via the communication unit 260.

  The vibration unit (vibrator) 240 receives the vibration signal transmitted from the main body device 100 and operates based on the vibration signal.

  The microcomputer (microcomputer) 250 performs control for outputting sound and control for operating the vibrator in accordance with the received data from the main body device 100. In addition, a process for transmitting the acceleration value (detection information) detected by the acceleration sensor 210 to the main body device 100 via the communication unit 260 or the position information detected by the imaging unit 220 via the communication unit 260 is performed. Processing to be transmitted to the apparatus 100 is performed.

  The communication unit 260 includes an antenna and a wireless module, and wirelessly transmits and receives data to and from the main body device 100 using a communication method such as Bluetooth (registered trademark). The communication unit 260 sequentially transmits the acceleration value (detection information) detected by the acceleration sensor 210, the position information detected by the imaging unit 220, and the like to the main body device 100 sequentially at predetermined time intervals. Note that the communication unit 260 may be connected to the main apparatus 100 via a communication cable, and may transmit and receive information via the communication cable.

  The input device 200 may be, for example, a controller as shown in FIGS. 2A to 2C. As the operation unit 270, a button, a lever (analog pad), a mouse, a cross key, An operator such as a touch panel display may be further provided. In addition, the input device 200 may include a gyro sensor that detects an angular velocity that changes according to the input operation of the player.

  Further, the input device 200 may be one that the player holds and moves, or one that the player wears and moves. Further, the input device 200 includes a controller imitating an actual tool such as a sword-type controller or gun-type controller held by the player, or a glove-type controller worn by the player (attached to the hand of the player). included. The input device 200 also includes a main device 100 (game device, portable game device) integrated with the input device 200, a mobile phone, and the like.

  Next, the main body apparatus 100 of this embodiment will be described. The main device 100 according to the present embodiment includes a storage unit 170, a processing unit 110, and a communication unit 196.

  The storage unit 170 is a work area such as the processing unit 110 and the communication unit 194, and the function thereof can be realized by hardware such as a RAM (VRAM).

  In particular, the storage unit 170 of the present embodiment includes a main storage unit 172, a drawing buffer 174, and a sound data storage unit 176. The main storage unit 172 serves as a work area such as the processing unit 110 and the communication unit 194, and the function thereof can be realized by hardware such as a RAM (VRAM). The drawing buffer 174 stores the image generated by the drawing unit 140.

  In addition, the sound data storage unit 176 stores a confirmation sound indicating a response of the input device 200 to the input operation of the player and a sound effect output in accordance with the game calculation process. A plurality of types of confirmation sounds are stored according to the detection information. In addition, a plurality of types of sound effects are stored according to motion and a given event. A plurality of types of confirmation sounds may be stored in accordance with the direction of acceleration detected by the acceleration sensor 210 (upward, downward, leftward, rightward, forward, and backward).

  The information storage medium 180 (computer-readable medium) stores programs, data, and the like, and functions as an optical disk (CD, DVD), magneto-optical disk (MO), magnetic disk, hard disk, and magnetic tape. Alternatively, it can be realized by a memory (ROM). The processing unit 110 performs various processes of the present embodiment based on a program (data) stored in the information storage medium 180. That is, the information storage medium 180 stores a program for causing a computer to function as each unit of the present embodiment (a program for causing a computer to execute processing of each unit). The information storage medium 180 includes a memory card that stores player personal data, game save data, and the like.

  The display unit 190 outputs an image generated by the processing unit 110, and functions thereof are a CRT display, an LCD (liquid crystal display), an OELD organic EL display, a PDP (plasma display panel), a touch panel display, Alternatively, it can be realized by hardware such as an HMD (head mounted display).

  The speaker 192 outputs sound reproduced by the sound control unit 150, and the function can be realized by hardware such as a speaker or headphones. Note that the speaker 192 may be a speaker provided in the display unit. For example, when a television (a home television receiver) is used as the display unit 190, a television speaker can be used.

  The light source 198 is, for example, an LED, and is disposed in association with the display unit 190.

  The communication unit 196 can communicate with another main body device (game device) via a network (Internet). The function can be realized by various processors, hardware such as a communication ASIC, a network interface card, or a program. The communication unit 196 can perform both wired and wireless communication.

  The communication unit 196 includes an antenna and a wireless module, and transmits and receives data to and from the input device 200 via the communication unit 260 of the input device 200 by a communication method such as Bluetooth (registered trademark). For example, the communication unit 196 transmits sound data such as a confirmation sound and a sound effect, and a vibration signal to the input device 200, and information detected by the acceleration sensor 210 and the image sensor 226 in the input device 200 is predetermined. Receive at intervals.

  Note that a program (data) for causing a computer to function as each unit of the present embodiment is distributed from the storage unit and the information storage medium of the server to the information storage medium 180 (or the storage unit 170) via the network. It may be. Use of such server information storage media is also within the scope of the present invention.

  The processing unit 110 (processor) performs game calculation processing, image generation processing, sound control processing, or the like based on the detection information received from the input device 200 or a program developed from the information storage medium 180 to the storage unit 170. Do.

  In particular, the processing unit 110 of this embodiment includes an acceleration error measurement unit 120, a game calculation unit 130, a drawing unit 140, a sound control unit 150, and a vibration control unit 160.

  The acceleration error measurement unit 120 includes an acceleration information generation unit 121, simultaneous equation creation unit 122, simultaneous equation calculation unit 123, acceleration error calculation unit 124, and acceleration error setting unit 125.

  The acceleration information generation part 121 acquires the detection information of the acceleration sensor 210 from the input device 200, and performs the process which produces | generates acceleration information based on the acquired detection information.

  For example, the acceleration information generation unit 121 determines whether or not the acceleration due to the motion of the acceleration sensor 210 can be ignored based on the detection information of the acceleration sensor 210, and the acceleration due to the motion of the acceleration sensor 210 can be ignored. The acceleration information may be generated based on the detection information at.

  In addition, for example, the acceleration information generation unit 121 determines that the acceleration due to the motion of the acceleration sensor 210 if a state in which the fluctuation range of the detection information of the acceleration sensor 210 satisfies a predetermined condition (for example, a state that is not more than a predetermined value) continues for a predetermined time. May be determined to be in a state that can be ignored.

  Further, for example, the acceleration information generation unit 121 generates the acceleration information based on the plurality of detection information acquired at the predetermined time (for example, an average of all or part of the plurality of detection information acquired at the predetermined time). The value may be acceleration information).

  The simultaneous equation creating unit 122 includes six parameters a, b, c, and a corresponding to each sensitivity and each offset in three detection axis directions (x-axis direction, y-axis direction, and z-axis direction) orthogonal to each other of the acceleration sensor 210. Six sets of acceleration information based on detection information of the acceleration sensor 210 are substituted into variables of an ellipsoidal equation including p, q, and r, and six parameters a, b, c, p, q, and r are set as unknowns. A process of creating simultaneous quadratic equations composed of six quadratic equations is performed.

For example, the simultaneous equation creating unit 122 sets the equation {(x−p) / a} ² + {(y−q) / b} ² + {(z−r) / c} ² = 1 as an ellipsoidal equation. You may make it use.

  The simultaneous equation calculation unit 123 converts the simultaneous quadratic equation created by the simultaneous equation creation unit 122 into five new expressions each represented by an expression including at least one of six unknowns a, b, c, p, q, and r. The unknowns α, β, γ, δ, and ε, and the simultaneous equations that consist of five linear equations that do not include any of the six unknowns a, b, c, p, q, and r. A process for solving the linear equation is performed.

  In addition, for example, the simultaneous equation calculation unit 123 converts the simultaneous linear equations so that the coefficient matrix of the simultaneous linear equations is larger than the absolute values of all other elements whose diagonal elements are not diagonal elements. You may make it create.

  In addition, for example, the simultaneous equation calculation unit 123 includes two pieces of acceleration information having a maximum value and a minimum value in the first detection axis direction (for example, the x-axis direction) among the six sets of acceleration information based on the detection information of the acceleration sensor 210. One of the linear equations is created based on a polynomial obtained by subtracting the other from one of the two quadratic equations obtained by substituting each into the variable of the ellipsoidal equation, and the six sets of acceleration information Among the two quadratic equations obtained by substituting the two acceleration information having the maximum and minimum values in the second detection axis direction (for example, the y-axis direction) into the variables of the ellipsoidal equation, respectively. The other one of the linear equations is created based on the polynomial obtained by subtracting, and among the six sets of acceleration information, the values in the third detection axis direction (for example, the z-axis direction) are the maximum and minimum values. Two pieces of acceleration information are converted into variables of the ellipsoid equation. It may be created other one of linear equations based on the polynomial obtained from one of the two quadratic equation obtained by substituting, respectively by subtracting the other.

  For example, the simultaneous equation calculation unit 123 includes six unknowns a and b included in each term of a polynomial obtained by calculating any two quadratic equations of the simultaneous quadratic equation or a polynomial obtained by modifying the polynomial. , C, p, q, r, or an expression obtained by multiplying the expression by a real number is made to correspond to five new unknowns α, β, γ, δ, ε to create simultaneous linear equations Also good.

  In addition, for example, the simultaneous equation calculation unit 123 includes three predetermined axes (ξ axis, 邇 i) orthogonal to each other in a three-dimensional space created by the three detection axes (x axis, y axis, z axis) of the acceleration sensor 210. , 謗 b) each of three sets of acceleration information based on the three sets of detection information obtained in the state where each of them is directed in the direction opposite to the gravity direction (directly upward direction) or the vicinity thereof, and the predetermined three axes (ξ axis, 邇It is also possible to create simultaneous quadratic equations using three sets of acceleration information based on three sets of detection information obtained in a state in which a, b) are directed in the direction of gravity (directly below) or in the vicinity thereof. Good.

  The acceleration error calculation unit 124 calculates the values of six unknowns a, b, c, p, q, r from the values of the five new unknowns α, β, γ, δ, ε obtained by the simultaneous equation calculation unit 123. Calculation is performed, and offset error information and sensitivity error information in the three detection axis directions (x-axis direction, y-axis direction, and z-axis direction) of the acceleration sensor 210 are calculated based on the calculation result.

  The acceleration error setting unit 125 performs processing for storing the offset error information and sensitivity error information calculated by the acceleration error calculation unit 124 in the storage unit 170.

  The acceleration error measurement unit 120 acquires detection information of the acceleration sensor 210 and calculates offset error information and sensitivity error information when the game program is started or when an acceleration error measurement event occurs, and the calculated offset is calculated. A series of processes for storing the error information and the sensitivity error information in the storage unit 170 may be performed. In this case, for example, when a mode (acceleration error information setting mode) for measuring error information of the acceleration sensor 210 and storing it in the storage unit 170 is set, an acceleration error measurement event may be generated. . Then, the player may voluntarily set the acceleration error information setting mode by performing a predetermined operation input, or the processing unit 110 determines whether a predetermined condition is satisfied and sets the acceleration error information. Whether or not to set the mode may be determined.

  The game calculation unit 130 displays various objects (polygon, free-form surface, or surface) such as characters (player characters, enemy characters), moving objects (cars, airplanes, etc.), buildings, trees, pillars, walls, maps (terrain), etc. The object is arranged and set in the object space. In other words, the position and rotation angle of the object in the world coordinate system (synonymous with direction and direction) are determined, and the rotation angle (rotation angle around the X, Y, and Z axes) is determined at that position (X, Y, Z). Arrange objects.

  In addition, the game calculation unit 130 performs a virtual camera (viewpoint) control process for generating an image that can be seen from a given (arbitrary) viewpoint in the object space. Specifically, processing for controlling the position (X, Y, Z) or rotation angle (rotation angle about the X, Y, Z axis) of the virtual camera (processing for controlling the viewpoint position, the line-of-sight direction or the angle of view) I do.

  For example, when an object (for example, a character) is photographed from behind using a virtual camera, the position or rotation angle of the virtual camera (the direction of the virtual camera) so that the virtual camera follows changes in the position or rotation of the object. To control. In this case, the virtual camera can be controlled based on information such as the position, rotation angle, or speed of the object. Alternatively, the virtual camera may be controlled to rotate at a predetermined rotation angle or to move along a predetermined movement path. In this case, the virtual camera is controlled based on the virtual camera data for specifying the position (movement path) or rotation angle of the virtual camera. When there are a plurality of virtual cameras (viewpoints), the above control process is performed for each virtual camera.

  In addition, the game calculation unit 130 performs a movement / motion calculation (movement / motion simulation) of a model (character, car, airplane, etc.). That is, based on a program (movement / motion algorithm), motion data, or the like, a process of moving the model in the object space or moving the object (motion, animation) is performed. Specifically, object movement information (position, rotation angle, speed, or acceleration) and motion information (position or rotation angle of each part that constitutes the object) are sequentially transmitted every frame (1/60 seconds). Perform the required simulation process. A frame is a unit of time for performing object movement / motion processing (simulation processing) and image generation processing.

  The drawing unit 140 performs drawing processing based on the results of various processing (game calculation processing) performed by the processing unit 110, thereby generating an image and outputting the image to the display unit 190. When a so-called three-dimensional game image is generated, first, vertex data (vertex position coordinates, texture coordinates, color data, normal vector, α value, etc.) of each vertex defining a display object (object, model) is included. Display object data (object data, model data) is input, and vertex processing is performed based on vertex data included in the input display object data. When performing the vertex processing, vertex generation processing (tessellation, curved surface division, polygon division) for re-dividing the polygon may be performed as necessary. In vertex processing, geometry processing such as vertex movement processing, coordinate transformation (world coordinate transformation, camera coordinate transformation), clipping processing, perspective transformation, or light source processing is performed, and the display object is configured based on the processing result. The given vertex data is changed (updated, adjusted) for the vertex group. Then, rasterization (scan conversion) is performed based on the vertex data after the vertex processing, and the surface of the polygon (primitive) is associated with the pixel. Subsequent to rasterization, pixel processing (fragment processing) for drawing pixels constituting an image (fragments constituting a display screen) is performed. In pixel processing, various processes such as texture reading (texture mapping), color data setting / changing, translucent composition, anti-aliasing, etc. are performed to determine the final drawing color of the pixels that make up the image, and perspective transformation is performed. The drawing color of the object is output (drawn) to the drawing buffer 176 (buffer that can store image information in units of pixels; VRAM, rendering target). That is, in pixel processing, per-pixel processing for setting or changing image information (color, normal, luminance, α value, etc.) in units of pixels is performed. Thereby, an image that can be seen from the virtual camera (given viewpoint) set in the object space is generated. Note that when there are a plurality of virtual cameras (viewpoints), an image can be generated so that an image seen from each virtual camera can be displayed as a divided image on one screen.

  The vertex processing and pixel processing performed by the drawing unit 140 are realized by hardware that enables polygon (primitive) drawing processing to be programmed by a shader program written in a shading language, so-called programmable shaders (vertex shaders and pixel shaders). May be. Programmable shaders can be programmed with vertex-level processing and pixel-level processing, so that the degree of freedom of rendering processing is high, and the expressive power can be greatly improved compared to fixed rendering processing by hardware. .

  The drawing unit 140 performs geometry processing, texture mapping, hidden surface removal processing, α blending, and the like when drawing the display object.

  In the geometry processing, processing such as coordinate conversion, clipping processing, perspective projection conversion, or light source calculation is performed on the display object. Then, display object data after geometric processing (after perspective projection conversion) (position coordinates of vertex of the display object, texture coordinates, color data (luminance data), normal vector, α value, etc.) is stored in the main storage unit 172. Saved.

  Texture mapping is a process for mapping a texture (texel value) stored in the storage unit 170 to a display object. Specifically, the texture (surface properties such as color (RGB) and α value) is read from the storage unit 170 using texture coordinates or the like set (given) at the vertex of the display object. Then, a texture that is a two-dimensional image is mapped to a display object. In this case, processing for associating pixels with texels, bilinear interpolation or the like is performed as texel interpolation.

  As the hidden surface removal processing, hidden surface removal processing can be performed by a Z buffer method (depth comparison method, Z test) using a Z buffer (depth buffer) in which Z values (depth information) of drawing pixels are stored. . That is, when drawing pixels corresponding to the primitive of the object are drawn, the Z value stored in the Z buffer is referred to. Then, the Z value of the referenced Z buffer is compared with the Z value at the drawing pixel of the primitive, and the Z value at the drawing pixel is a Z value (for example, a small Z value) on the near side when viewed from the virtual camera. In some cases, the drawing process of the drawing pixel is performed and the Z value of the Z buffer is updated to a new Z value.

  α blending (α synthesis) is a translucent synthesis process (usually α blending, addition α blending, subtraction α blending, or the like) based on an α value (A value). For example, in normal α blending, a process for obtaining a color obtained by combining two colors by performing linear interpolation with the α value as the strength of synthesis is performed.

  The α value is information that can be stored in association with each pixel (texel, dot), and is, for example, plus alpha information other than color information indicating the luminance of each RGB color component. The α value can be used as mask information, translucency (equivalent to transparency and opacity), bump information, and the like.

  The sound control unit 150 receives sounds (including confirmation sounds and sound effects) stored in the sound data storage unit 176 based on the results of various processes (game calculation process, etc.) performed by the processing unit 110 as input devices. A process of outputting from at least one of the speaker 230 and the speaker 192 is performed.

  The vibration control unit 160 performs a process of causing the vibration unit 240 provided in the input device to vibrate.

  Note that the game system of the present embodiment may be a system dedicated to the single player mode in which only one player can play, or may be a system having a multiplayer mode in which a plurality of players can play. Further, when a plurality of players play, a game image or a game sound provided to the plurality of players may be generated using one main device and a display unit. Alternatively, it may be generated by distributed processing using a plurality of game devices connected via a network (transmission line, communication line) or the like. In addition, in the present embodiment, when a game is played by a plurality of players, it is determined whether or not a predetermined condition is satisfied based on detection information for each input device of the plurality of players, sound control based on the determination result, Perform vibration control.

2-2. Specific Processing of the Present Embodiment Next, a processing example of the game system of the present embodiment will be described using the flowchart of FIG.

  When the game program is activated, main device 100 first determines whether or not the mode is the acceleration error information setting mode (step S300).

When the acceleration error information setting mode is set (No in step S300), the main device 100 displays a display for instructing the player to fix the input device 200 in the first posture via the display unit 190. This is performed (step S310). The first posture is a predetermined posture determined in advance, for example, a posture in which the ξ axis (which may coincide with the x-axis) faces directly above or in the vicinity thereof. When the player uses the assisting tool or the like to fix the input device 200 to the first posture, the main body device 100 acquires the detection information of the acceleration sensor 210, and the first set of acceleration information (x ₁ , y ₁ , z _1). ) Is generated (step S320). The process of step S320 may be the same as the process shown in the flowchart of FIG.

Next, the main device 100 performs a display for instructing the player to fix the input device 200 in the second posture via the display unit 190 (step S330). The second posture is a predetermined posture, for example, a posture in which the ξ axis (which may coincide with the x-axis) faces directly below or in the vicinity thereof. When the player fixes the input device 200 to the second posture, the main device 100 acquires the detection information of the acceleration sensor 210 and generates the second set of acceleration information (x ₂ , y ₂ , z ₂ ) (step S340). ). The process of step S340 may be the same as the process shown in the flowchart of FIG.

Next, the main body device 100 performs a display for instructing the player to fix the input device 200 in the third posture via the display unit 190 (step S350). The third posture is a predetermined posture, for example, a posture in which the eyelid (which may coincide with the y-axis) faces directly above or in the vicinity thereof. When the player fixes the input device 200 in the third posture, the main device 100 acquires the detection information of the acceleration sensor 210 and generates the third set of acceleration information (x ₃ , y ₃ , z ₃ ) (step S360). ). The process of step S360 may be the same as the process shown in the flowchart of FIG.

Next, the main device 100 performs a display for instructing the player to fix the input device 200 in the fourth posture via the display unit 190 (step S370). The fourth posture is a predetermined posture, for example, a posture in which the eyelid (which may coincide with the y-axis) faces directly below or in the vicinity thereof. When the player fixes the input device 200 to the fourth posture, the main device 100 acquires the detection information of the acceleration sensor 210 and generates the fourth set of acceleration information (x ₄ , y ₄ , z ₄ ) (step S380). ). The process in step S380 may be the same as the process shown in the flowchart of FIG.

Next, the main body device 100 performs a display for instructing the player to fix the input device 200 in the fifth posture via the display unit 190 (step S390). The fifth posture is a predetermined posture, for example, a posture in which the eyelid (which may coincide with the z-axis) faces directly above or in the vicinity thereof. When the player fixes the input device 200 to the fifth posture, the main device 100 acquires the detection information of the acceleration sensor 210 and generates the fifth set of acceleration information (x ₅ , y ₅ , z ₅ ) (step S400). ). The process of step S400 may be the same as the process shown in the flowchart of FIG.

Next, the main device 100 performs a display for instructing the player to fix the input device 200 in the sixth posture via the display unit 190 (step S410). The sixth posture is a predetermined posture, for example, a posture in which the eyelid (which may coincide with the z-axis) faces directly below or in the vicinity thereof. When the player fixes the input device 200 in the sixth posture, the main device 100 acquires the detection information of the acceleration sensor 210 and generates the sixth set of acceleration information (x ₆ , y ₆ , z ₆ ) (step S420). ). The process of step S420 may be the same as the process shown in the flowchart of FIG.

Next, the main body device 100 uses the six sets of acceleration information (x ₁ , y ₁ , z ₁ ) to (x ₆ , y ₆ , z ₆ ) generated in steps S 310 to S 320 to perform 3 of the acceleration sensor 210. The offset error information and sensitivity error information in the two detection axis directions are calculated (step S430). The process of step S430 may be the same as the process shown in the flowchart of FIG.

  Next, the main device 100 stores the offset error information and sensitivity error information in the three detection axis directions of the acceleration sensor 210 calculated in step S430 in the storage unit 170 (step S440). Here, the main unit 100 may write the information into the information storage medium 180 in order to use the offset error information and the sensitivity error information at the next activation of the game program.

  Then, main device 100 starts a game calculation, and performs the game calculation while correcting the acquired detection information of acceleration sensor 210 based on the offset error information and the sensitivity error information stored in storage unit 170 (step S450). ).

  On the other hand, if it is not the acceleration error information setting mode in step S300 (No in step S300), the main body device 100 displays the offset error information and sensitivity error information of the acceleration sensor 210 defined in advance in association with the input device 2. Based on this, game calculation is performed while correcting the acquired detection information of the acceleration sensor 210 (step S450). Further, when the offset error information and the sensitivity error information are stored in the information storage medium 180 by performing the processes of steps S310 to S440 in the past, the main body device 100 stores the offset error information and the sensitivity error information from the information storage medium 180. May be read out and written into the storage unit 170, and the acquired detection information of the acceleration sensor 210 may be corrected.

  If the acceleration error information setting mode is set immediately after the start (immediately before step S300), each time the game program is started, the acceleration sensor 210 is detected using the latest offset error information and sensitivity error information. Information can be corrected. In this way, for example, it is possible to perform correction in consideration of the influence of temperature and noise when starting the game program. Further, the acceleration error information setting mode is set when the offset error information and the sensitivity error information are not stored in the information storage medium 180 or when a predetermined time or more has elapsed since being stored in the information storage medium 180. By doing so, it is possible to save the player from having to perform an operation of fixing the input device in a predetermined posture every time the game program is started.

  As described above, according to the game system of the present embodiment, the offset error and the sensitivity error can be calculated based on the detection information obtained regardless of the direction of the acceleration sensor 210 before starting the game calculation. Therefore, in order to measure the offset error and the sensitivity error of the acceleration sensor 210, the player does not have to bother to hold the input device 200 so that each detection axis of the acceleration sensor 210 is accurately upward and downward.

  In the present embodiment, if an error measurement program for the acceleration sensor 210 is incorporated in the application (game program) and the offset error and sensitivity error of the acceleration sensor 210 are measured when the application is activated, the application is stored in the acceleration sensor 210. By correcting the detection information, it is possible to perform a game calculation that more accurately reflects the input operation of the player without being affected by the offset error and the sensitivity error.

  In addition, this invention is not limited to this embodiment, A various deformation | transformation implementation is possible within the range of the summary of this invention.

  The present invention includes configurations that are substantially the same as the configurations described in the embodiments (for example, configurations that have the same functions, methods, and results, or configurations that have the same objects and effects). In addition, the invention includes a configuration in which a non-essential part of the configuration described in the embodiment is replaced. In addition, the present invention includes a configuration that exhibits the same operational effects as the configuration described in the embodiment or a configuration that can achieve the same object. Further, the invention includes a configuration in which a known technique is added to the configuration described in the embodiment.

DESCRIPTION OF SYMBOLS 1 Acceleration error measuring apparatus, 2 measuring object apparatus, 10 process part, 11 acceleration information generation part, 12 simultaneous equation preparation part, 13 simultaneous equation calculation part, 14 acceleration error calculation part, 15 display control part, 16 sound output control part, 20 acceleration sensor, 22 microcomputer, 24 communication unit, 30 storage unit, 32 operation unit, 34 display unit, 36 information storage medium, 38 communication unit, 40 sound output unit, 100 main unit, 110 processing unit, 120 acceleration error measurement unit 121 acceleration information generation unit, 122 simultaneous equation creation unit, 123 simultaneous equation calculation unit, 124 acceleration error calculation unit, 125 acceleration error setting unit, 130 game calculation unit, 140 drawing unit, 150 sound control unit, 160 vibration control unit, 170 storage unit, 172 main storage unit, 174 drawing buffer, 176 sound data storage unit, 180 information Storage medium, 190 display unit, 192 speaker, 196 communication unit, 198 light source, 200 input device, 210 acceleration sensor, 220 imaging unit, 222 infrared filter, 224 lens, 226 image sensor, 228 image processing circuit, 230 speaker, 240 vibration Part, 250 microcomputer, 260 communication part, 270 operation part

Claims (15)

A program for calculating offset error information and sensitivity error information of an acceleration sensor,
Six sets of acceleration information based on detection information of the acceleration sensor are substituted into variables of an ellipsoidal equation including six parameters corresponding to each sensitivity and each offset in three detection axis directions orthogonal to each other of the acceleration sensor. A simultaneous equation creating unit that creates simultaneous quadratic equations composed of six quadratic equations with the six parameters as unknowns;
The simultaneous quadratic equation includes five linear equations each including five new unknowns each represented by an expression including at least one of the six unknowns and not including any of the six unknowns. A simultaneous equation calculator that solves the linear equations by reducing them to equations;
As an acceleration error calculator that calculates the six unknown values from the five new unknown values and calculates offset error information and sensitivity error information in the three detection axis directions of the acceleration sensor based on the calculation result , A program that makes a computer work. In claim 1,
The simultaneous equation calculation unit
A program that creates the simultaneous linear equations so that the coefficient matrix of the simultaneous linear equations has an absolute value of a diagonal element larger than absolute values of all other elements that are not diagonal elements. In claim 1 or 2,
The simultaneous equation calculation unit
One of two quadratic equations obtained by substituting the two pieces of acceleration information having the maximum and minimum values in the first detection axis direction among the six sets of acceleration information into variables of the ellipsoidal equation, respectively. One of the linear equations is created based on a polynomial obtained by subtracting the other from the two pieces of acceleration information having the maximum and minimum values in the second detection axis direction among the six sets of acceleration information , Another one of the linear equations is created based on a polynomial obtained by subtracting the other from one of the two quadratic equations obtained by substituting for each of the ellipsoidal equation variables, Among the two sets of acceleration information, one of the two quadratic equations obtained by substituting the two pieces of acceleration information having the maximum and minimum values in the third detection axis direction into variables of the ellipsoidal equation, respectively, is obtained. Based on the polynomial obtained by subtracting To create one of the other equations, program. In any one of Claims 1 thru | or 3,
The simultaneous equation calculation unit
An equation composed of the six unknowns included in each polynomial term obtained by calculating any two quadratic equations of the simultaneous quadratic equations or a polynomial obtained by transforming the polynomial, or the equation multiplied by a real number A program for creating the simultaneous linear equations by associating an equation with the five new unknowns. In any one of Claims 1 thru | or 4,
The simultaneous equation calculation unit
Three sets of detection information based on three sets of detection information obtained in a state in which predetermined three axes orthogonal to each other in the three-dimensional space created by the three detection axes of the acceleration sensor face the reverse direction of the gravity direction or the vicinity thereof. Using the acceleration information and three sets of the acceleration information based on the three sets of the detection information obtained in a state where the predetermined three axes are respectively directed in the gravity direction or the vicinity thereof, the simultaneous quadratic equations are obtained. A program to create. In any one of Claims 1 thru | or 5,
The simultaneous equation creating unit
The three detection axes of the acceleration sensor are x-axis, y-axis, and z-axis, and among the six parameters, the sensitivity parameters of the acceleration sensor in the x-axis direction, y-axis direction, and z-axis direction are a and b, respectively. , C, where the offset parameters of the acceleration sensor in the x-axis direction, y-axis direction, and z-axis direction are p, q, and r, respectively, the equation {(x−p) / A program using a} ² + {(y−q) / b} ² + {(z−r) / c} ² = 1. In any one of Claims 1 thru | or 6.
A program including an acceleration information generation unit that acquires the detection information of the acceleration sensor and generates the acceleration information based on the acquired detection information. In claim 7,
The acceleration information generation unit
Based on the detection information, it is determined whether or not the acceleration due to the motion of the acceleration sensor can be ignored, and the acceleration information based on the detection information in a state where the acceleration due to the motion of the acceleration sensor can be ignored. Generate a program. In claim 8,
The acceleration information generation unit
The program which determines that the acceleration by the motion of the said acceleration sensor is a state which can be disregarded if the state where the fluctuation range of the said detection information satisfy | fills predetermined conditions continues for a predetermined time. In claim 9,
The acceleration information generation unit
A program for generating the acceleration information based on a plurality of the detection information acquired at the predetermined time.   An information storage medium readable by a computer, wherein the program according to any one of claims 1 to 9 is stored. An acceleration sensor error measurement method for calculating acceleration sensor offset error information and sensitivity error information,
In the three-dimensional space formed by three detection axes orthogonal to each other of the acceleration sensor, the first axis of the predetermined three axes orthogonal to each other faces in the direction opposite to or near the gravity direction. A first acceleration information generation step of acquiring detection information and generating first acceleration information based on the detection information;
A second acceleration information generation step of acquiring detection information of the acceleration sensor in a state in which the first axis faces the gravity direction or the vicinity thereof, and generating second acceleration information based on the detection information;
The detection information of the acceleration sensor is acquired in a state where the second axis of the predetermined three axes is directed in the direction opposite to or near the gravity direction, and third acceleration information is generated based on the detection information. A third acceleration information generation step;
A fourth acceleration information generation step of acquiring detection information of the acceleration sensor in a state where the second axis faces the gravity direction or the vicinity thereof, and generating fourth acceleration information based on the detection information;
The detection information of the acceleration sensor is acquired in a state in which the third of the predetermined three axes is in the direction opposite to or near the gravity direction, and fifth acceleration information is generated based on the detection information. A fifth acceleration information generation step;
A sixth acceleration information generation step of acquiring detection information of the acceleration sensor in a state in which the third axis faces the gravity direction or the vicinity thereof, and generating sixth acceleration information based on the detection information;
The first acceleration information, the second acceleration information, and the third acceleration are included in variables of an ellipsoidal equation including six parameters corresponding to the sensitivity and offset in the three detection axis directions of the acceleration sensor. Information, the fourth acceleration information, the fifth acceleration information, and the sixth acceleration information are substituted, and a simultaneous quadratic equation including six quadratic equations having the six parameters as unknowns is created. Equation creation step;
The simultaneous quadratic equation includes five linear equations each including five new unknowns each represented by an expression including at least one of the six unknowns and not including any of the six unknowns. A simultaneous equation calculation step for solving the linear equations by reducing the equations,
An error calculation step of calculating the six unknown values from the five new unknown values and calculating offset error information and sensitivity error information in the three detection axis directions of the acceleration sensor based on the calculation results; A method for measuring an error of an acceleration sensor, including: An acceleration sensor error measuring device that measures offset error information and sensitivity error information of an acceleration sensor,
An acceleration information generation unit that acquires detection information of the acceleration sensor and generates six sets of acceleration information based on the acquired detection information;
The six sets of acceleration information are substituted into variables of an ellipsoidal equation including six parameters corresponding to the sensitivity and offset in the three detection axis directions orthogonal to each other of the acceleration sensor, and the six parameters are unknown. A simultaneous equation creating unit for creating simultaneous quadratic equations consisting of six quadratic equations,
The simultaneous quadratic equation includes five linear equations each including five new unknowns each represented by an expression including at least one of the six unknowns and not including any of the six unknowns. A simultaneous equation calculator that solves the linear equations by reducing them to equations;
An acceleration error calculator that calculates the six unknown values from the five new unknown values and calculates offset error information and sensitivity error information in the three detection axis directions of the acceleration sensor based on the calculation results; , An error measuring device for an acceleration sensor. A game system that obtains detection information of the acceleration sensor from an input device including an acceleration sensor that detects an acceleration that changes according to an input operation of the player, and performs a game calculation.
An acceleration error measurement unit that calculates offset error information and sensitivity error information of the acceleration sensor based on the detection information of the acceleration sensor and stores the information in a storage unit;
A game calculation unit that corrects detection information of the acceleration sensor based on the offset error information and the sensitivity error information stored in the storage unit and performs a game calculation;
The acceleration error measurement unit includes:
An acceleration information generation unit that acquires the detection information of the acceleration sensor from the input device, and generates six sets of acceleration information based on the acquired detection information;
The six sets of acceleration information are substituted into variables of an ellipsoidal equation including six parameters corresponding to the sensitivity and offset in the three detection axis directions orthogonal to each other of the acceleration sensor, and the six parameters are unknown. A simultaneous equation creating unit for creating simultaneous quadratic equations consisting of six quadratic equations,
The simultaneous quadratic equation includes five linear equations each including five new unknowns each represented by an expression including at least one of the six unknowns and not including any of the six unknowns. A simultaneous equation calculator that solves the linear equations by reducing them to equations;
An acceleration error calculator that calculates the six unknown values from the five new unknown values and calculates offset error information and sensitivity error information in the three detection axis directions of the acceleration sensor based on the calculation results; ,
An acceleration error setting unit that stores the offset error information and the sensitivity error information in the storage unit. In claim 14,
The acceleration error measurement unit includes:
When the game program is started or when an acceleration error measurement event occurs, the detection information is acquired, the offset error information and the sensitivity error information are calculated, and the calculated offset error information and the sensitivity error information are A game system stored in a storage unit.

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