DESCRIPTION
Title of Invention: ROBOT AND NOISE REMOVING METHOD FOR THE
ROBOT
Technical Field
[0001]
The present invention relates to a robot and a noise
removing method for the robot and, more particularly, to a
control method for the robot.
Background Art
[0002]
When an arm of a robot is actuated and stopped, the arm
oscillates. When the arm oscillates, since the robot cannot
perform work with high position accuracy, the robot sometimes
stays on standby until the arm stops the oscillation. When
the speed of the arm is increased, since the oscillation during
the stop of the arm increases, time until the stop of the
oscillation increases. Therefore, for example, a method of
reducing residual oscillation using an inertia sensor in a
robot is disclosed in PTL 1. The residual oscillation occurs
because large elasticity is present between a motor and the
distal end of an arm. Rotation information of the motor can
be acquired using only a position sensor represented by an
2
•
encoder. However, information concerning the distal end of
the arm can be more accurately acquired by attaching the inertia
sensor. This information is fed back to a control unit to
reduce the residual oscillation.
Citation List
Patent Literature
[0003]
PTL 1: Japanese Patent No. 3,883,544
Summary of Invention
Technical Problem
[0 a04]
To use the inertia sensor, it is necessary to take noise
into account. In particular, in a gyro sensor of an oscillation
type, when mechanical oscillation is applied to the gyro sensor,
extremely large detuning frequency noise occurs. When a
feedback system that controls the arm using an output of the
inertia sensor is built, sometimes, the feedback system
oscillates and the robot does not operate. Therefore, there
is a demand for a robot that prevents oscillation of the
feedback system including the inertia sensor.
Solution to Problem
[0005]
3
i,
I
,;
~
•
II
, The invention is made to solve at least a part of the
problems described above, and it can be achieved as the
following forms or application examples.
[0006]
[Application Example 1]
A robot according to this application example includes:
an arm; an arm coupling section connected to the arm and
including a driving source that pivots or translates the arm;
a base connected to the arm coupling section; an angle sensor
that detects a pivoting angle of the driving source; an inertia
sensor that is attached to the arm and detects inertial force
acting on the arm; a noise filter that removes noise from an
output of the inertia sensor; a control unit that controls a
pivoting action of the arm; a noise detecting unit that detects
a noise frequency of the inertia sensor from an output of the
angle sensor and the output of the inertia sensor; and a
filter-constant determining unit that determines, using the
noise frequency, a noise filter characteristic of the noise
filter for removing noise.
[0007]
According to the application example, the arm is
connected to the base via the arm coupling section. The arm
coupling section includes the driving source. The driving
source pivots or translates the arm. The control uni t controls
the driving source to thereby control a pivoting action of the
4
•
arm. The angle sensor is set in the driving source. The angle
sensor detects a pivoting angle of the driving source. The
control unit recognizes a pivoting state of the arm on the basis
of information concerning the pivoting angle of the driving
source.
[0008]
The inertia sensor is attached to the arm. The control
unit recognizes a pivoting state of the arm using an output
of the inertia sensor. The noise detecting unit detects a noise
frequency in noise peculiar to the inertia sensor using an
output of the angle sensor and the output of the inertia sensor.
The filter-constant determining unit determines a noise filter
characteristic using the noise frequency. The noise filter
characteristic is determiped according to a characteristic
peculiar to the inertia sensor. The noise filter is connected
to the inertia sensor. The noise filter removes noise from
the output of the inertia sensor according to the noise filter
characteristic. Therefore, the control unit can control the
arm using the output of the inertia sensor in which the noise
is reduced. As a result I the control unit can prevent
oscillation of a feedback system including the inertia sensor.
[0009]
. [Application Example 2]
In the robot according to the application example
described above, it is preferable that the noise detecting uni t
5
detects a noise frequency of a signal output by the inertia
sensor using a frequency distribution of a signal output by
the angle sensor and a frequency distribution of the signal
output by the inertia sensor.
[0010]
According to this application example, the frequency
distribution of the signal output by the angle sensor and the
frequency distribution of the signal output by the inertia
sensor are used. Therefore, it is possible to separate a
frequency distribution of a signal of a noise component from
an oscillation frequency distribution of a signal detected by
the inertia sensor. As a result, it is possible to accurately
specify a noise frequency.
[0011]
[Application Example 3]
In the robot according to the application example
described above, it is preferable that the noise filter is a
band removing filter.
[0012]
According to this application example, it is possible
to reduce a change in a phase in bands other than a band of
a frequency that should be removed. It is possible to remove
a signal in a band of a frequency of a noise component from
a signal output by the inertia sensor.
[0013]
6
[Application Example 4]
In the robot according to the application example
described above, it is preferable that the filter-constant
determining unit determines a filter constant referring to the
noise frequency and a table.
[0014]
According to this application example, it is possible
to determine a filter constant without requiring complicated
calculation. Therefore, it is possible to reduce loads
related to calculation.
[0015]
[Application Example 5]
In the robot according to the application example
described above, it is preferable that the noise filter is
mounted on the control unit as software.
[0016]
According to this application example, electronic
components and the like included in the noise filter are
unnecessary. It is possible to reduce man-hour for soldering
and the like. Therefore, it is possible to manufacture the
robot with high productivity.
[0017]
[Application Example 6]
A robot according to this application example includes:
an arm body to which plural arms and plural arm coupling
7
sections connected to the plural arms and including driving
sources that pivot or translate the plural arms are alternately
coupled; a base connected to the arm body; plural angle sensors
that detect pivoting angles of the driving sources; plural
inertia sensors that detect inertial force acting on the plural
arms; plural noise filters that remove noise from outputs of
the inertia sensors; a control unit that controls pivoting
actions of the plural arms; a noise detecting unit that detects
noise frequencies of the plural inertia sensors from outputs
of the plural angle sensors and the outputs of the plural
inertia sensors; and a filter-constant determining unit that
determines, using the noise frequencies, noise filter
characteristics of the noise filters for removing noise.
[0018]
According to this application example, the robot
includes the arm body to which the arms and the arm coupling
sections are alternately coupled. Consequently, the arms can
move freely. The plural arms are set and the plural inertia
sensors that detect inertial force acting on the arms are set.
The plural arm coupling sections are set. The plural angle
sensors are set in the arm body.
[0019]
The noise detecting unit detects noise frequencies of
the inertia sensors from outputs of the plural angle sensors
and outputs of the plural
8
inertia sensors. The
filter-constant determining unit determines noise filter
characteristics corresponding to the inertia sensors using the
noise frequencies. Therefore, the noise filters can remove
noise of the inertia sensors. As a result, in the robot
including the arm body to which the arms and the arm coupling
sections are alternately coupled, as in the robot according
to the application example explained above, the control unit
can prevent oscillation of a feedback system including the
inertia sensors.
[0020]
[Application Example 7]
In the robot according to the application example
described above, it is preferable that the noise detecting uni t
detects noise frequencies of signals output by the inertia
sensors using frequency distributions of signals output by the
angle sensors and frequency distributions of the signals output
by the inertia sensors.
[0021]
According to this application example, the frequency
distributions of the signals output by the angle sensors and
the frequency distributions of the signals output by the
inertia sensors are used. Therefore, it is possible to
separate frequency distributions of signals of noise
components from oscillation frequency distributions of
signals detected by the inertia sensors. As a result, it is
9
possible to accurately specify noise frequencies.
[0022]
[Application Example 8]
In the robot according to the application example
described above, it is preferable that the noise filters are
band removing filters.
[0023]
According to this application example, a change in a
phase decreases in bands other than a band of a frequency that
should be removed. Therefore, it is possible to remove signals
of bands of frequencies of noise components from signals output
by the inertia sensors.
[0024]
[Application Example 9]
In the robot according to the application example
described above, it is preferable that the filter-constant
determining unit determines a filter constant referring to the
noise frequencies and a table.
[0025]
According to this application example, it is possible
to determine a filter constant without requiring complicated
calculation. Therefore, it is possible to reduce loads
related to calculation.
[0026]
[Application Example 10]
10
"
In the robot according to the application example
described above, it is preferable that the noise filters are
mounted on the control unit as software.
[0027]
According to this application example, electronic
components and the like included in the noise filters are
unnecessary. It is possible to reduce man-hour for soldering
and the like. Therefore, it is possible to manufacture the
robot with high productivity.
[0028]
[Application Example 11]
A noise removing method for a robot according to this
application example comprises: a driving-source-angle
detecting step of detecting a pivoting angle of a driving
source; an arm-inertial-force detecting step of detecting,
using an inertia sensor, inertial force acting on an arm; a
noise component detecting step of detecting a noise frequency
of the inertia sensor using a signal of the pivoting angle
detected in the driving-source-angle detecting step and a
signal of the inertial force detected in the arm-inertial-force
detecting step; a filter-constant determining step of
determining a noise filter characteristic for removing noise
from the detected information; a noise removing step of
removing noise with a noise filter based on the noise filter
characteristic.
11
•
[0029]
According to this application example, a pivoting angle
of the driving source is detected in the driving-source-angle
detecting step. Inertial force acting on the arm is detected
using the inertia sensor in the arm-inertial-force detecting
step. Subsequently, in the noise component detecting step,
a noise frequency of the inertia sensor is detected using a
signal of the pivoting angle detected in the
driving-source-angle detecting step and a signal of the
inertial force detected in the arm-inertial-force detecting
step. In the filter-constant determining step, a noise filter
characteristic, which is a characteristic for removing noise,
is determined from the detected information. Noise is removed
by a noise filter based on the noise filter characteristic in
the noise removing step.
[0030]
Therefore, it is possible to set the noise f il ter
characteristic to be a characteristic for removing noise
peculiar to the inertia sensor. Therefore, it is possible to
accurately remove the noise in the noise removing step. As
a result, it is possible to prevent oscillation of a feedback
system including the inertia sensor.
Brief Description of Drawings
[0031]
12
•
[Fig. 1] A block diagram showing a schematic
configuration of a robot according to a first embodiment.
[Fig. 2] A flowchart for showing a process for removing
noise from a sensor output signal.
[Fig. 3] Diagrams for explaining the process for
removing noise from a sensor output signal.
[Fig. 4] Diagrams for explaining the process for
removing noise from a sensor output signal.
[Fig. 5] A block diagram showing a schematic
configuration of a robot according to a second embodiment.
[Fig. 6] Diagrams for explaining a process for removing
noise from a sensor output signal.
Description of Embodiments
[0032]
Embodiments of the invention are explained below with
re ference to the accompanying drawings. In the figures
referred to below, in order to show layers and members in sizes
of recognizable degrees, scales of the layers and the members
are set different from actual scales.
[0033]
(First Embodiment)
In this embodiment, a robot and a characteristic arm
control method performed by the robot are explained with
reference to Figs. 1 to 4C. Fig. 1 is a block diagram showing
13
.,
a schematic configuration of a robot according to the first
embodiment.
[0034]
As shown in Fig. 1, a robot 100 includes a base 105. An
arm coupling section 104 is set on the inside of the base 105.
In the arm coupling section 104, an angle sensor 106, a motor
103 functioning as a driving source, and a torque transmitting
mechanism 102 are arranged in this order on the same axis. One
end of an output shaft of the motor 103 is connected to the
angle sensor 106. The angle sensor 106 includes an encoder
and detects a pivoting angle of the motor 103. The other end
of the output shaft of the motor 103 is connected to an input
shaft of the torque transmitting mechanism 102. The torque
transmitting mechanism 102 is a reduction gear set to a
predetermined reduction ratio. Therefore, a pivoting angle
of an output shaft of the torque transmitting mechanism 102
is a value obtained by dividing the pivoting angle of the motor
103 by the reduction ratio.
[0035]
The output shaft of the torque transmitting mechanism
102 is connected to one end of an arm 101. Therefore, the arm
101 pivoting according to the pivoting of the motor 103. A
robot hand 112 is set at the other end of the arm 101. An inertia
sensor 107 is set on the robot hand 112. The inertia sensor
107 is a gyro sensor of an oscillation type. The inertia sensor
14
107 detects angular velocity of the arm 101 at the time when
the arm 101 pivots.
[0036]
The robot 100 includes a control device 113. The control
device 113 includes a CPU (central processing unit) that
functions as a processor to perform various kinds of arithmetic
processing and a memory that stores various kinds of
information. In addition, the control device 113 is connected
to the CPU via an input and output interface and a data bus.
The control device 113 includes, as main functional units, a
control unit 108, a noise detecting unit 109, a filter-constant
determining unit 110, and a filter 111 functioning as a noise
filter. These functions are incorporated in software and
stored in the memory. The CPU carries out the functions
according to the software.
(0037]
The control unit 108 includes a function of controlling
a pivoting action of the arm 101 and an action of the robot
hand 112. The noise detecting unit 109 receives the input of
a signal of the pivoting angle of the motor 103 output by the
angle sensor 106 and a signal of the pivoting angular velocity
of the arm 101 output by the inertia sensor 107. The noise
detecting unit 109 includes a function of detecting a noise
frequency included in an output signal of the inertia sensor
107. The noise frequency is also referred to as detuning
15
,
frequency.
[0038]
The filter-constant determining unit 110 includes a
function of setting a constant of the filter 111 referring to
the noise frequency and a constant table. The filter 111
receives the input of the signal of the pivoting angular
velocity of the arm 101 output by the inertia sensor 107. The
filter 111 includes a function of removing noise from the signal
of pivoting angular velocity on the basis of the set constant.
[0039]
Flows of signals are explained below. Firs t, the control
unit 108 outputs a driving signal to the motor 103.
Consequently, the motor 103 operates and the arm 101 pivots.
The angle sensor 106 outputs a motor angle signal indicating
the pivoting angle of the motor 103 to the control unit 108
and the noise detecting unit 109. The inertia sensor 107
outputs an arm angular velocity signal, which is a signal of
the pivoting angular velocity of the arm 101, to the noise
detecting unit 109 and the filter 111.
[0040]
The noise detecting unit 109 receives the input of the
motor angle signal and the arm angular velocity signal and
calculates a noise frequency. The noise detecting unit 109
outputs information concerning the calculated noise frequency
to the filter-constant determining
16
unit 110. The
filter-constant determining unit 110 computes the constant of
the filter 111 from the information concerning the noise
frequency. The filter-constant determining unit 110 sets the
constant of the filter 111. The filter 111 receives the input
of the arm angular velocity signal from the inertia sensor 107.
The filter 111 removes noise from the arm angular velocity
signal using the set constant and outputs the arm angular
velocity signal to the control unit 108.
[0041]
Fig. 2 is a flowchart for explaining a process for
removing noise from a sensor output signal. In Fig. 2, step
Sl is equivalent to an arm driving step. This step is a step
of the control unit 108 driving the motor 103 and pivoting the
arm 101. Step Sl is performed in parallel to other steps. Step
S2 is equivalent to a driving-source-angle detecting step.
This step is a step of the angle sensor 106 detecting an angle
of the motor 103 and outputting a motor angle signal. The
process shifts to step S3. Step S3 is equivalent to an
arm-inertial-force detecting step. This step is a step of the
inertia sensor 107 detecting and outputting angular velocity
of the arm 101. The process shifts to step 84. Step 82 and
step S3 are performed in parallel.
[0042]
Step 84 is equivalent to a filter-constant deciding step.
This step is a step of deciding whether the constant of the
17
)
filter 111 is changed. When the constant is changed, the
process shifts to step 85. When the constant is not changed,
the process shifts to step 87. 8tep 85 is equivalent to a
noise-component detecting step. This step is a step of the
noise detecting unit 109 calculating a noise frequency peculiar
to the inertia sensor 107. The process shifts to step 86. 8tep
86 is equivalent to a f ilter- constant determining step. This
step is a step of the filter-constant determining unit 110
setting the constant of the filter 111 referring to the noise
frequency. The process shifts to step 87. 8tep 87 is
equivalent to a noise removing step. This step is a step of
the filter 111 receiving the input of the arm angular velocity
signal from the inertia sensor 107, removing noise, and
outputting the arm angular velocity signal to the control unit
108. The process for removing noise from a sensor output signal
is ended.
[0043]
Fig. 3 and Fig. 4 are diagrams for explaining the process
for removing noise from a sensor output signal. The method
of removing noise from a sensor output signal is explained in
detail with reference to Fig. 3 and Fig. 4 with the figures
associated wi th the steps shown in Fig. 2. 8teps 81 to 83 are
steps performed using a publicly- known technique. Therefore,
explanation of the steps is omitted. In the filter-constant
determining step of step 84, it is decided whether the constant
18
of the filter 111 is set. The constant of the filter 111 only
has to be set once after the filter 111 is replaced and does
not need to be reset until the filter 111 is replaced again.
When the constant needs to be changed according to a change
in the environment, the constant of the filter 111 may be set
again.
[0044]
Fig. 3 illustrates graphs corresponding to the
noise-component detecting step of step 85. In Fig. 3, the
abscissa indicates a frequency. The frequency is higher on
the right side than on the left side. In Figs. 3 (a) and 3 (b) ,
the ordinate indicates intensity. The intensity is higher on
the upper side than on the lower side. In Fig. 3(c), the
ordinate indicates an intensity ratio. The intensity ratio
is higher on the upper side than on the lower side. The noise
detecting unit 109 receives the input of the motor angle signal
output by the angle sensor 106. The noise detecting unit 109
divides the motor angle signal by a reduction ratio. The motor
angle signal is a signal that changes according to time set
as a parameter. The noise detecting unit 109 differentiates
the motor angle signal wi th the time. Consequently, an angular
velocity signal of the arm 101 is obtained. The noise detecting
unit 109 subjects the divided motor angle signal to Fourier
transform to thereby calculate a first angular velocity
spectrum 114 serving as a frequency distribution shown in Fig.
19
3 (a) .
(0045]
The noise detecting unit 109 receives the input of the
arm angular velocity signal output by the inertia sensor 107.
The arm angular velocity signal is a signal that changes
according to time set as a parameter. The noise detecting uni t
109 subjects the arm angular velocity signal of the inertia
sensor 107 to Fourier transform to thereby calculate a second
angular velocity spectrum 115 serving as a frequency
distribution shown in Fig. 3 (b) In the second angular
velocity spectrum 115, two places of frequencies where the
intensity is at the peak are formed. One is a pivoting speed
frequency 115a by the pivoting of the arm 101 and the other
is a noise frequency 115b peculiar to the inertia sensor 107.
[0046]
Subsequently, the noise detecting unit 109 divides the
second angular velocity spectrum 115 by the first angular
velocity spectrum 114. As a result, a third angular velocity
spectrum 116 shown in Fig. 3(c) is calculated. In the third
angular velocity spectrum 116, the peak of the pivoting speed
frequency 115a decreases and only the peak of the noise
frequency 115b remains. Consequently, the noise frequency
115b can be detected.
(0047]
Fig. 4 illustrates diagrams corresponding to the
20
filter-constant determining step of step 86. Fig. 4(a) is a
block diagram showing the filter 111. The block diagram can
be represented as indicated by the following formulas.
[0048]
a: A first constant 402 serving as a filter constant.
b: A second constant 403 serving as a filter constant.
c: A third constant 404 serving as a filter constant.
d: A fourth constant 405 serving as a filter constant.
e: A fifth constant 406 serving as a filter constant.
z". A delay element 401.
[0049]
[Math. 1]
a + bZ-1 +cZ-2
1- dZ-1
- eZ-2
[0050]
A noise fil ter characteristic, which is a characteristic
for the filter 111 to remove noise, is determined by the first
to fifth constants 402 to 406. Fig. 4(b) shows an example of
a constant table 117 serving as a table referred to when a filter
constant is set. As shown in Fig. 4 (b), in the constant table
117, the first to fifth constants 402 to 406 are set to
correspond to the noise frequency 115b. The width of a cutoff
frequency is not specifically limited. In this embodiment,
an example in which the width of the cutoff frequency is 50
Hz is shown in the constant table 117. The width of the cutoff
21
,
frequency is also referred to as removal band. The constant
table 117 is not limited to this example and is desirably
calculated by performing an experiment beforehand. The
filter-constant determining unit 110 determines the first to
fifth constants 402 to 406 referring to the noise frequency
115b and the constant table 117. The filter-constant
determining unit 110 sets the first to fifth constants 402 to
406 as parameters of the filter Ill.
[0051]
Fig. 4(c) is a graph showing a noise filter
characteristic of the filter Ill. The ordinate indicates a
gain. The gain is higher on the upper side than on the lower
side. The abscissa indicates a frequency. The frequency is
higher on the right side than on the left side. A filter
characteristic line 118 indicates a frequency characteristic
of the filter 111 for allowing a signal to pass. As shown in
Fig. 4(c), the filter characteristic line 118 indicates a
characteristic for attenuating a signal of a frequency within
a removal band l18a around the noise frequency 115b. The filter
III is a band removing filter that allows signals of frequencies
lower and higher than the removal band 118a around the noise
frequency 115b to pass.
[0052]
In the noise removing step of step 87, the arm angular
velocity signal is input to the filter Ill. The first to fifth
22
, ,
constants 402 to 406 are already set in the f ilter 111 .
. Therefore, the filter 111 removes noise of the noise frequency
115b from the arm angular velocity signal and outputs the arm
angular velocity signal to the control unit 108. The step of
removing noise from a sensor output signal is ended.
[0053]
As explained above, with the robot 100 according to this
embodiment, effects explained below can be obtained.
(1) According to this embodiment, the noise detecting
unit 109 detects the noise frequency 115b in noise peculiar
to the inertia sensor 107 using an output of the angle sensor
106 and an output of the inertia sensor 107. The
filter-constant determining unit 110 determines a noise filter
characteristic using the noise frequency 115b. The noise
filter characteristic corresponds to a characteristic
peculiar to the inertia sensor 107. The filter 111 is connected
to the inertia sensor 107. The filter 111 removes noise from
the output of the inertia sensor 107 according to the noise
filter characteristic. Therefore, the control unit 108 can
control the arm 101 using the output of the inertia sensor 107
in which noise is attenuated. As a result, the control unit
108 can prevent oscillation of a feedback system including the
inertia sensor 107.
[0054]
(2) According to this embodiment, the first angular
23
,
velocity spectrum 114 pf the output of the angle sensor 106
and the second angular velocity spectrum 115 of the output of
the inertia sensor 107 are used. Therefore, it is possible
to separate a signal of the noise frequency 115b from an
oscillation frequency distribution of a signal detected by the
inertia sensor 107. As a result, it is possible to accurately
specify the noise frequency 115b.
[0055]
(3) According to this embodiment, the filter
characteristic line 118 of the filter 111 indicates the band
removing filter. Therefore, it is possible to reduce a change
in a phase in bands other than a band of a frequency that should
be removed. Further, it is possible to remove a signal in a
band of a frequency of a noise component from a signal output
by the inertia sensor 107.
[0056]
(4) According to this embodiment, the filter-constant
determining unit 110 determines a filter constant from the
noise frequency 115b referring to the constant table 117.
Therefore, since it is possible to determine a filter constant
without requiring complicated calculation, it is possible to
reduce loads related to calculation.
[0057]
(5) According to this embodiment, the filter 111 is
mounted on the control device 113 as software. Therefore,
24
,
electronic components and the like included in the filter 111
are unnecessary. It is possible to reduce man-hour for
soldering and the like. Therefore, it is possible to provide
the robot 100 that can be manufactured with high productivity.
[0058]
(6) According to this embodiment, the pivoting angle of
the motor 103 is detected in the driving-source-angle detecting
step of step S2. The angular velocity of the arm 101 is detected
using the inertia sensor 107 in the arm-inertial-force
detecting step of step S3 . Subsequently, in the
noise-component detecting step of step S5, the noise frequency
115b of the inertia sensor 107 is detected using the signal
of the pivoting angle detected in the driving-source-angle
detecting step and the signal of the inertial force detected
in the arm-inertial-force detecting step. In the
filter-constant determining step of step S6, the noise filter
characteristic, which is the characteristic for removing noise
from the detected information, is determined. In the noise
removing step of step S7, noise is removed by the filter 111
based on the noise filter characteristic.
[0059]
Therefore, since the noise fi Iter characteristic is the
characteristic of noise peculiar to the inertia sensor 107,
it is possible to accurately remove noise in the noise removing
step. As a result, it is possible to prevent oscillation of
25
the feedback system including the inertia sensor 107.
[0060]
(7) According to this embodiment 1 the control device 113
automatically detects the noise frequency 115b of the inertia
sensor 107. The filter-constant determining unit 110
automatically sets the first to fifth constants 402 to 406 of
the filter 111 that removes noise of the noise frequency 115b.
The filter 111 removes noise of the inertia sensor 107.
Consequently1 it is possible to stabilize the feedback system
including the inertia sensor 107. Since a filter constant is
set without operation by an operator 1 it is possible to operate
the robot 100 with high productivity.
[0061]
(Second Embodiment)
Next, a robot and a characteristic noise removing method
performed by the robot are explained with reference to Fig.
5 and Fig. 6. This embodiment is different from the first
embodiment in that the number of arms is increased from one
to two. Explanation of similarities to the first embodiment
is omitted.
[0062]
That iS I in this embodiment 1 the number of arms is two
as shown in a block diagram showing a schematic configuration
according to the second embodiment of Fig. 5. A robot 500
includes a base 509. In the base 509 1 a first angle sensor
26
,
510, a first motor 504 functioning as a driving source, and
a first torque transmitting mechanism 503 are arranged in this
order one on top of another on the same axis. The first torque
transmitting mechanism 503 and the first motor 504 configure
a first arm coupling section 505.
[0063]
A first arm 501 is connected to an output shaft of the
first torque transmitting mechanism 503. The first arm 501
pivots according to driving of the first motor 504. Forms of
the base 509, the first angle sensor 510, the first arm coupling
section 505, and the first arm 501 are the same as the forms
of the base 105, the angle sensor 106, the arm coupling section
104, and the arm 101 according to the first embodiment.
Therefore, explanation of the base 509, the first angle sensor
510, the first arm coupling section 505, and the first arm 501
is omitted.
[0064]
In the first arm 501, on the opposite side of the first
arm coupling section 505, a second angle sensor 511, a second
motor 507 functioning as a driving source, and a second torque
transmitting mechanism 506 are arranged in this order one on
top of another on the same axis. The second torque transmitting
mechanism 506 and the second motor 507 configure a second arm
coupling section 508. The first torque transmitting mechanism
503 is a reduction gear that reduces speed at a reduction ratio
27
of a first reduction ratio. The second torque transmitting
mechanism 506 is a reduction gear that reduces speed at a
reduction ratio of a second reduction ratio. Forms of the
second angle sensor 511 and the second arm coupling section
508 are the same as the forms of the first angle sensor 510
and the first arm coupling section 505. Therefore,
explanation of the second angle sensor 511 and the second arm
coupling section 508 is omitted. In the first arm SOl, a first
inertia sensor 512 is set near the second angle sensor 511.
[0065]
A second arm 502 is connected to an output shaft of the
second torque transmitting mechanism 506. The second arm 502
pivots according to driving of the second motor 507. The first
arm SOl, the second arm 502, the first arm coupling section
505, and the second arm coupling section 508 configure an arm
body 521. In the second arm 502, a robot hand 522 is set at
an end on the opposite side of the second arm coupling section
508. A second inertia sensor 513 is set on the robot hand 522.
The first inertia sensor 512 and the second inertia sensor 513
are gyro sensors of an oscillation type. The first inertia
sensor 512 detects angular velocity of the first arm 501 at
the time when the first arm 501 pivots. The second inertia
sensor 513 detects absolute angular velocity of the second arm
502 with respect to the base 509.
[0066]
28
The robot 500 includes a control device 523. Like the
control device 113 in the first embodiment, the control device
523 includes a CPU (central processing unit) , a memory, an input
and output interface, and a data bus and includes the same
functions. As main functional units, the control device 523
includes a control unit 514, a first noise detecting unit 515,
a first filter-constant determining unit 517, and a first
filter 519 functioning as a noise filter. The control unit
the first noise detecting unit 515, the first
filter-constant determining unit 517, and the first filter 519
respectively include functions same as the functions of the
control unit 108, the noise detecting unit 109, the
filter-constant determining unit 110, and the filter III in
the first embodiment.
[0067]
Further, as main functional units, the control device
523 includes a second noise detecting unit 516, a second
filter-constant determining unit 518, and a second filter 520
functioning as a noise filter. The second filter-constant
determining unit 518 and the second filter 520 respectively
include functions same as the functions of the filter-constant
determining unit 110 and the filter III in the first embodiment.
The second noise detecting unit 516 includes a function similar
to the function of the noise detecting unit 109 in the first
embodiment. The second noise detecting unit 516 is different
29
'• 4
from the noise detecting unit 109 in that signals of the two
angle sensors, i. e., the first angle sensor 510 and the second
angle sensor 511 are input to the second noise detecting uni t
516. These functions are incorporated in software and stored
in the memory. The CPU carries out the functions according
to the software.
[0068]
In a series of process for removing noise from a sensor
output signal, the arm driving step of step 81 to the
filter-constant deciding step of step 84 are the same as those
in the first embodiment. Therefore, explanation of the steps
is omitted. In step 85, the first noise detecting unit 515
detects a noise frequency of the first inertia sensor 512 and
the second noise detecting unit 516 detects a noise frequency
of the second inertia sensor 513. Processing contents carried
out by the first noise detecting unit 515, the first
filter-constant determining unit 517, and the first filter 519
in steps 85 to 87 are the same as the processing contents carried
out by the noise detecting unit 109, the filter-constant
determining unit 110, and the filter 111 in the first embodiment.
Therefore, explanation of the processing contents is omitted.
Processing contents carried out by the second noise detecting
unit 516 are explained.
[0069]
Fig. 6 illustrates diagrams for explaining the process
30
for removing noise from a sensor output signal and are graphs
corresponding to the noise-component detecting step of step
S5. In Fig. 6, the abscissa indicates a frequency. The
frequency is higher on the right side than on the left side.
In Figs. 6 (a) and 6 (b) , the ordinate indicates intensity. The
intensity is higher on the upper side than on the lower side.
In Fig. 6(c), the ordinate indicates an intensity ratio. The
intensity ratio is higher on the upper side than on the lower
side.
[0070]
The second noise detecting unit 516 receives the input
of a first motor angle signal output by the first angle sensor
510, a second motor angle signal output by the second angle
sensor 511, and a second arm angular velocity signal' output
by the second inertia sensor 513. The second noise detecting
unit 516 divides the first motor angle signal by the first
reduction ratio. The second noise detecting unit 516 divides
the second motor angle signal by the second reduction ratio.
Subsequently, the second noise detecting unit 516 forms a
connected motor signal obtained by connecting the divided first
motor angle signal and the divided second motor angle signal.
[0071]
A motor angle signal is a signal that changes according
to time set as a parameter. The second noise detecting unit
516 differentiates the connected motor signal with the time.
31
~lI,
•
Consequently, a connected angular velocity signal obtained by
connecting angular velocity signals of the first arm 501 and
the second arm 502 is obtained. The second noise detecting
unit 516 subjects the connected angular velocity signal to
Fourier trans form to thereby calculate a fourth angular
velocity spectrum 524 serving as a frequency distribution shown
in Fig. 6 (a) .
[0072]
The second noise detecting unit 516 receives the input
of the second arm angular velocity signal output by the second
inertia sensor 513. The second arm angular velocity signal
is a signal that changes according to time set as a parameter.
The second noise detecting unit 516 subjects the second arm
angular velocity signal to Fourier transform to thereby
calculate a fifth angular velocity spectrum 525 serving as a
frequency distribution shown in Fig. 6 (b) . In the fifth
angular velocity spectrum 525, three places of frequencies
where the intensity is at the peak are formed. One is a first
pivoting speed frequency 525a by the pivoting of the first arm
501, another is a second pivoting speed frequency 525b by the
pivoting of the second arm 502, and the other is a noise
frequency 525c peculiar to the second inertia sensor 513.
[0073]
Subsequently, the second noise detecting unit 516
divides the fifth angular velocity spectrum 525 by the fourth
32
33
• •
filter-constant determining unit 518 sets the determined
constant in the second filter 520. Consequently, in the noise
removing step of step 87, noise is removed from the second arm
angular velocity signal. The process for removing noise from
a sensor output signal is ended.
[0075]
As explained above, wi th the robot 500 according to thi s
embodiment, effects explained below can be obtained.
(1) According to this embodiment, the second noise
detecting unit 516 automatically detects the noise frequency
of the second inertia sensor 513. The second filter-constant
for cancelling the noise frequency 525c. The second
angular velocity spectrum 524. As a result, a sixth angular
velocity spectrum 526 shown in Fig. 6(c) is calculated. In
the sixth angular velocity spectrum 526, the peaks of the first
pivoting speed frequency 525a and the second pivoting speed
frequency 525b decrease and only the peak of the noise frequency
525c remains. Consequently, the noise frequency 525c can be
detected.
[0074]
In the filter-constant determining step of step 86, the
noise frequency 525c is output from the second noise detecting
unit 516 to the second filter-constant determining unit 518.
The second filter-constant determining unit 518 determines,
according to a table prepared in advance, a filter constant
•
34
•
• •
As a result, in the robot 500
[0077]
Embodiments of the invention are not limited to the
determining unit 518 automatically sets the constant of the
second filter 520 for removing noise. The second filter 520
removes noise of the second inertia sensor 513. Consequently,
the control device 523 can stably drive a feedback system
including the second inertia sensor 513.
[0076]
(2) According to this embodiment, the robot 500 includes
the arm body in which the arms and the arm coupling sections
are al ternately coupled. Therefore, the first arm 501 and the
second arm 502 can move freely. The second noise detecting
unit 516 detects the noise frequency 525c of the second inertia
sensor 513 from outputs of the first angle sensor 510 and the
second angle sensor 511 and an output of the second inertia
sensor 513. The second filter-constant determining unit 518
determines a noise filter characteristic corresponding to the
second inertia sensor 513 using the noise frequency 525c.
Therefore, the second filter 520 can remove noise of the second
noise detecting unit 516.
including the arm body in which the arms and the arm coupling
sections are alternately coupled, as in the robot 100 according
to the first embodiment, the control unit 514 can prevent
oscillation of the feedback system including the second inertia
sensor 513.
•
. .
embodiments explained above. Various alterations and
improvements can be applied to the embodiments. Modifications
are explained below.
(Modification 1)
In the first embodiment, the robot 100 is a robot of a
horizontal mul ti - j oint robot form. However, a form of a robot
is not limited to this. The method explained above can be used
for robots of various forms such as a vertical multi-joint robot,
a Cartesian coordinate robot, and a parallel link robot. In
this case, noise of an inertia sensor can be removed using a
method same as the method explained above.
[0078]
In the case of the Cartesian coordinate robot, since an
inertia sensor moves linearly, an acceleration sensor is used.
In this case, noise peculiar to the acceleration sensor can
be detected using data such as a rotation angle of a rotary
motor and a moving distance of a linear motor and an output
of the acceleration sensor. The noise of the acceleration
sensor can be removed using a filter.
[0079]
(Modification 2)
In the first embodiment, the first to fifth constants
402 to 406 are determined using the constant table 117. However,
the determination of the first to fifth constants 402 to 406
is not limited to this. A formula for calculating the first
35
..
to fifth constants 402 to 406 may be used. Consequently, it
is possible to more finely set the first to fifth constants
402 to 406.
[0080]
(Modification 3)
In the first embodiment, the filter III is the band
removing filter. However, the filter III may be a low-pass
filter. The filter III may be any filter as long as the filter
can remove noise of the inertia sensor 107. Since the number
of constants is smaller in the low-pass filter than in the band
removing filter, it is possible to reduce an amount of data
stored in the memory.
[0081]
(Modification 4)
In the first embodiment, the angle of the arm 101 is
detected using the angle sensor 106 and the inertia sensor 107.
After the constant of the filter III is set, the angle of the
arm 101 may be detected using only the inertia sensor 107. It
is possible to easily detect the angle of the arm 101. The
contents of the modifications 1 to 4 can be applied to the second
embodiment as well.
[0082]
(Modification 5)
In the second embodiment, the robot includes the two arms.
However, the number of arms may be three or more. In this case,
36
, •
..
the arms can perform a more complicated action.
[0083]
(Modification 6)
In the second embodiment, the connected motor signal
obtained by connecting the first motor angle signal divided
by the first reduction ratio and the second motor angle signal
divided by the second reduction ratio is formed. The second
noise detecting unit 516 calculates the fourth angular velocity
spectrum 524 using the connected motor signal. However, a
method of calculating the fourth angular velocity spectrum 524
is not limited to this. First, the first arm angular velocity
spectrum is calculated from the first motor angle signal
divided by the first reduction ratio. Subsequently, the
second arm angular velocity spectrum is calculated from the
second motor angle signal divided by the second reduction ratio.
The fourth angular velocity spectrum 524 may be calculated
using the first arm angular velocity spectrum and the second
arm angular velocity spectrum. A method with a short
calculation time may be selected.
Reference Signs List
[0084]
100, 500: robot, 101: arm, 103: motor functioning as
driving source, 104: arm coupling section, lOS, 509: base, 106:
angle sensor, 107: inertia sensor, 108,514: control unit, 109:
37
•
,
• . .
noise detecting unit, 110: filter-constant determination unit,
111: filter functioning as noise filter, 114: first angular
velocity spectrum serving as frequency distribution, 115:
second angular velocity spectrum serving as frequency
distribution, 115b, 525c: noise frequency, 117: constant table
serving as table, 402: first constant serving as filter
constant, 403: second constant serving as filter constant, 404:
third constant serving as filter constant, 405: fourth constant
serving as filter constant, 406: fifth constant serving as
filter constant, 501: first arm, 502: second arm, 504: first
motor functioning as driving source, 505: first arm coupling
section, 507: second motor serving as driving source, 508:
second arm coupling section, 510: first angle sensor, 511:
second angle sensor, 512: first inertia sensor, 513: second
inertia sensor, 515: first noise detecting unit, 516: second
noise detecting unit, 517: first filter constant determining
unit, 518: second filter constant determining unit, 519: first
filter functioning as noise filter, 520: second filter
functioning as noise filter, 521: arm body, 524: fourth angular
velocity spectrum serving as frequency distribution, 525:
fifth angular velocity spectrum serving as frequency
distribution
38

.. . .
WE CLAIM
[Claim 1]
A robot comprising:
an arm;
an arm coupling section connected to the arm and
including a driving source that pivots or translates the arm;
a base connected to the arm coupling section;
an angle sensor that detects a pivoting angle of the
driving sourcei
an inertia sensor that is attached to the arm and detects
inertial force acting on the arm;
a noise filter that removes noise from an output of the
inertia sensor;
a control unit that controls a pivoting action of the
arm;
a noise detecting unit that detects a noise frequency
of the inertia sensor from an output of the angle sensor and
the output of the inertia sensor; and
a filter-constant determining unit that determines,
using the noise frequency, a noise filter characteristic of
the noise filter for removing noise.
[Claim 2]
The robot according to claim 1, wherein the noise
detecting unit detects a noise frequency of a signal output
39
by the inertia sensor using a frequency distribution of a signal
output by the angle sensor and a frequency distribution of the
signal output by the inertia sensor.
[Claim 3]
The robot according to claim 2 I wherein the noise filter
is a band removing filter.
[Claim 4]
The robot according to claim 3 I wherein the
filter-constant determining unit determines a filter constant
referring to the noise frequency and a table.
[Claim 5]
The robot according to claim 4 I wherein the noise filter
is mounted on the control unit as software.
[Claim 6]
A robot comprising:
an arm body to which plural arms and plural arm coupling
sections connected to the plural arms and including driving
sources that pivot or translate the plural arms are alternately
coupled;
a base connected to the arm body;
plural angle sensors that detect pivoting angles of the
driving sources;
plural inertia sensors that detect inertial force acting
on the plural arms;
plural noise filters that remove noise from outputs of
40
( ..
. '
[Claim 11]
A noise removing methoB for a robot comprising:
a driving-source-angle detecting step of detecting a
pivoting angle of a driving source;
an arm-inertial-force detecting step of detecting I using
an inertia sensor, inertial .force acting on an arm;
a noise component detecting step of detecting a noise
frequency of the inertia sensor using a signal of the pivoting
angle detected in the driving-source-angle detecting step and
a signal of the inertial force detected in the
arm-inertial-force detecting stepi
a filter-constant determining step of determining a
noise filter characteristic for removing noise from the
detected information; and
a noise removing step of removing noise with a noise
filter based on the noise filter characteristic.
this day of 2013.