This application is based on and claims priority to Japanese Patent Application No. 2016-159895, filed on Aug. 17, 2016, the entire content of which is incorporated herein by reference.
The present invention relates to a robot control device suitable for controlling a robot arm through visual servoing.
One conventional technique for controlling a robot arm is visual servoing in which the position and the orientation of a moving workpiece (object) are continuously measured by a visual sensor, such as a camera, and the robot arm is made to follow the object on the basis of the measurement results (for example, Publication of Japanese Patent No. 4265088 and Japanese Unexamined Patent Application, Publication No. 2011-143494).
According to a first aspect, the present invention provides a robot control device including: a feature-point detecting unit that detects, from an image of an object acquired by a visual sensor, the positions of a plurality of feature points on the object, in a predetermined cycle; a position/orientation calculating unit that updates, in the predetermined cycle, respective equations of motion of the plurality of feature points on the basis of the detected positions of the plurality of feature points and that calculates the position or orientation of the object on the basis of the positions of the plurality of feature points calculated from the updated equations of motion; and a robot-arm-movement control unit that controls the movement of a robot arm so as to follow the object, on the basis of the calculated position or orientation of the object.
A robot system according to an embodiment of the present invention will be described in detail below with reference to the drawings. Note that, in this specification, a hat disposed above an English character symbol is referred to as “(English character symbol)hat” or “{circumflex over ( )}” a bar disposed above an English character symbol is referred to as “(English character symbol)bar” or “
As shown in
The workpiece 7 is placed on a conveying device 6, such as a belt conveyor or a rotary table, and is moved according to the movement of the conveying device 6.
Note that, in this embodiment, although the camera 2 is supported by the stand 3, the position thereof is not limited thereto, and the camera 2 may be mounted on the robot arm 4.
The configuration of the robot control device 5, which is provided in the robot system 1, will be described in detail below with reference to
As shown in
The feature-point detecting unit 51 is connected to the camera 2 and is connected to the equation-of-motion updating unit 521 and the weight calculating unit 523, which are provided in the position/orientation calculating unit 52. The equation-of-motion updating unit 521 is connected to the feature-point-position calculating unit 522. The feature-point-position calculating unit 522 is connected to the weight calculating unit 523 and the rotation/position-matrix calculating unit 524. The weight calculating unit 523 is connected to the rotation/position-matrix calculating unit 524.
The rotation/position-matrix calculating unit 524 is connected to the trajectory generating unit 531, which is provided in the robot-arm-movement control unit 53. The trajectory generating unit 531 is connected to the singular-point avoiding unit 532. The trajectory generating unit 531 and the singular-point avoiding unit 532 are connected to the adding unit 533. The adding unit 533 is connected to the robot arm 4.
The feature-point detecting unit 51 is configured to perform pattern matching using a preset shape with respect to an image that includes the workpiece 7 captured by the camera 2 and to detect the positions yk(tik) of a plurality of feature points on the workpiece 7 in the image that matches this shape. Here, specifically, the detected position yk(tik) expresses, for a k-th feature point, the position vector including x, y, and z directions at time tik at which the camera detects the workpiece.
The equation-of-motion updating unit 521 is configured to update the equation of motion of each feature point by using the position yk(tik) of the feature point, which is detected by the feature-point detecting unit 51. The position of each feature point detected from the image acquired by the camera 2 can be expressed as in Equation (1) by using an equation of motion.
yk(tik)=fk[yk(ti-1k),tik]+vik (1)
Here, fk[yk(ti-1k),tik] represents the equation of motion of each feature point, and vik represents sensor noise. Specifically, the position vector detected at the time tik is expressed on the basis of: an equation of motion that is updated by using the position yk(ti-1k) detected at time which is one cycle before; and the sensor noise.
Note that the equation of motion of each feature point can be expressed by Equation (2) and Equation (3), for example.
Here, xk(t) represents the nine-dimensional vector including the position, the velocity, and the acceleration of each feature point at time t, w(t) represents an acceleration vector, which is a factor of velocity change at the feature point, and v(t) represents noise obtained at the time of detection using the camera.
More specifically, the equation-of-motion updating unit 521 calculates ykbar(tik) by the following Equation (4) and Equation (5), thereby updating each equation of motion.
ŷk(tik)=fk[
Here, ykhat(tik) is a calculated value obtained by using the equation of motion updated, at the time tik, by using the position ykbar(ti-1k) at the time ti-1k, which is one cycle before. Furthermore, ykbar(tiK) in Equation (5) represents the position of each feature point, calculated in consideration of both the detected value yk(tik), which is detected by the camera 2 at the time tik, and the calculated value ykhat(tik), which is calculated by using Equation (4). Note that, in Equation (5), Fk(tik) represents a gain of the difference between yk(tik) and ykhat(tik).
The feature-point-position calculating unit 522 is configured to calculate the position ykhat(tnow) of each feature point at the current time tnow, as in Equation (6), by using the equation of motion updated by using the position ykbar(tik) at the time tik, which is calculated as described above.
ŷk(tnow)=fk[
The weight calculating unit 523 is configured to calculate a weight for each feature point. Specifically, the weight calculating unit 523 calculates, as the weight for each feature point, the covariance Σkhat(tnow) of the position of the feature point at the current time tnow, as shown in Equation (7), such that the importance of a feature point becomes higher as the feature point is detected a larger number of times (higher frequency) by the camera 2.
{circumflex over (Σ)}k(tnow)=gk[
Here, gk is the result obtained after calculating the covariance for an equation of motion fk, as shown in Equation (8).
gk=Cov(fk) (8)
Furthermore, Σkbar(tik) is the covariance calculated in consideration of both the covariance of the detected value y(tik) detected by the camera 2 at the time tik, and the covariance of the calculated value ykhat(tik) calculated by the equation of motion.
Note that, if there is a feature point that cannot be detected, the position of that feature point is calculated by using information obtained when the feature point was detected in the previous cycle.
The rotation/position-matrix calculating unit 524 is configured to use the covariance Σkhat(tnow), which is calculated by the weight calculating unit 523, and the position ykhat(tnow) of the feature point, which is calculated by the feature-point-position calculating unit 522, to calculate, by Equation (9), a rotation matrix and a position matrix of the workpiece 7, in which each feature point is weighted.
Here, Rw represents the rotation matrix of the workpiece 7 in the robot-world coordinate system, Tw represents the position matrix of the workpiece 7 in the robot-world coordinate system, and sk represents the position (vector including the x, y, and z directions) of a feature point, viewed from the object coordinate system fixed to the workpiece 7. However, if there is a feature point that is not detected, the result obtained when the feature point was detected in the previous cycle is used as the position of the feature point.
The trajectory generating unit 531 is configured to generate a trajectory of the robot arm 4. Specifically, the trajectory generating unit 531 calculates the differences between: the position and the orientation (a rotation matrix Rr and a position matrix Tr) of the current TCP generated by the robot-arm-movement control unit 53; and the position and the orientation (the rotation matrix Rw and the position matrix Tw) of the workpiece 7 that were calculated by the position/orientation calculating unit 52, and multiplies these differences by the inverse of the Jacobian (the inverse matrix of the Jacobian), thereby calculating the differences for each axis angle, i.e., a command velocity qdot* for the robot arm 4.
{dot over (q)}*=IK(ΔR,ΔT)=J+(q)h(ΔR,ΔT) (10)
Here, J+ is the inverse of the Jacobian transformation between axis positions and perpendicular positions. h(ΔR,ΔT) is a function indicating that the differences ΔR and ΔT of the position and the orientation are multiplied by a proportional gain, and the proportional gain is adjusted according to the movement frequency of the workpiece 7 to be followed.
The singular-point avoiding unit 532 is configured to generate an interpolation velocity Δqdot for an avoidance movement by Equation (11) when the current TCP generated by the robot-arm-movement control unit 53 is close to a singular point.
Δ{dot over (q)}=(I−J+(q)J(q))p(q) (11)
Here, p(q) is a function for correcting the velocity and is a correction velocity for each axis. The correction velocity p(q) for each axis can be obtained from Equation (12) and Equation (13).
H(q) is an expression indicating robot manipulability (manipulability). As shown in Equation (13), the correction velocity p(q) for each axis is calculated from partial differentiation of H(q).
In the above-described Equation (13), λ0 represents the proportional gain for avoiding a singular point. Note that the proportional gain λ0 becomes 0 when the position and the orientation of the TCP are not close to a singular point, and the value of λ0 is increased when the position and the orientation of the TCP are close to a singular point.
The adding unit 533 is configured to add the command velocity qdot* which is generated by the trajectory generating unit 531, and the interpolation velocity Δqdot*, which is calculated by the singular-point avoiding unit, to calculate an each-axis velocity command qdot for the robot arm 4.
{dot over (q)}={dot over (q)}*+Δ{dot over (q)} (14)
The robot arm 4 is controlled according to the calculated each-axis velocity command qdot.
The operation of the robot control device 5, which has the above-described configuration, will be described below with reference to
First, an image acquired by the camera 2 is input to the robot control device 5 (Step S1 in
Next, the processing for calculating the position and the orientation of the workpiece 7, which is performed in Step S3 in
First, the equation-of-motion updating unit 521 calculates the actual position ykbar(tik) of each feature point at the time tik, which is obtained on the basis of: the detected position yk(tik) of the feature point, which is detected at the time tik by the feature-point detecting unit 51; and the calculated position ykhat(tik) of the feature point at the time tik, which is calculated from the equation of motion updated at the time ti-1k (see Equation (4) and Equation (5)). Then, the calculated actual position ykbar(tik) is used to update the equation of motion (Step S21 in
Then, the feature-point-position calculating unit 522 calculates the position ykhat(tnow) of the feature point at the current time tnow by using the updated equation of motion, as shown in Equation (6) (Step S22 in
In this way, because the equation of motion is updated for each interpolation cycle of the robot arm 4, even when the workpiece 7 randomly moves, it is possible to accurately calculate the current position of the workpiece 7.
Next, the weight calculating unit 523 calculates the covariance Σkhat(tnow) of the position ykhat(tnow) of the feature point at the current time tnow by Equation (7) on the basis of both the covariance of the detected position yk(tik) of the feature point, which is detected at the time tik by the feature-point detecting unit 51, and the covariance of the calculated position ykhat(tik) of the feature point at the time tik, which is calculated from the equation of motion updated at the time ti-1k (Step S23).
Then, the rotation/position-matrix calculating unit 524 calculates a rotation matrix Rw and a position matrix Tw of the workpiece 7 by Equation (9) by using the covariance Σkhat(tnow), which is calculated by the weight calculating unit 523 and which serves as a weight, and the position ykhat(tnow) of the feature point, calculated by the feature-point-position calculating unit 522 (Step S24 in
In this way, because each feature point is weighted such that the importance of a feature point becomes higher as the feature point is detected a larger number of times by the camera 2, even if part of the workpiece 7 is blocked by obstacle or the like, for example, and thus, there is a feature point that cannot be detected, the robot arm 4 can be made to precisely follow the workpiece 7.
Next robot-arm-movement control processing performed in Step S4 of
First, the trajectory generating unit 531 calculates the position and the orientation (the rotation matrix Rr and the position matrix Tr) of the TCP of the robot arm 4 (Step S31 in
Next, the singular-point avoiding unit 532 checks whether the position and the orientation of the TCP of the robot arm 4, which are calculated by the trajectory generating unit 531, are close to a singular point (Step S34 in
Finally, the command velocity qdot* for each axis, which is generated by the trajectory generating unit 531, and the interpolation velocity Δqdot, which is generated by the singular-point avoiding unit 532, are added to calculate a velocity command for each axis of the TCP of the robot arm 4 (Step S37 in
By doing so, a singular point can be avoided.
Although the embodiment of the present invention has been described above in detail with reference to the drawings, the specific configurations are not limited to those in the embodiment, and design changes etc. that do not depart from the scope of the present invention are also encompassed.
As a result, the above-described embodiment leads to the following aspect.
According to a first aspect, the present invention provides a robot control device including: a feature-point detecting unit that detects, from an image of an object acquired by a visual sensor, the positions of a plurality of feature points on the object, in a predetermined cycle; a position/orientation calculating unit that updates, in the predetermined cycle, respective equations of motion of the plurality of feature points on the basis of the detected positions of the plurality of feature points and that calculates the position or orientation of the object on the basis of the positions of the plurality of feature points calculated from the updated equations of motion; and a robot-arm-movement control unit that controls the movement of a robot arm so as to follow the object, on the basis of the calculated position or orientation of the object.
According to the robot control device of the above-described first aspect, the feature-point detecting unit detects, from an image of an object acquired by the visual sensor, the positions of a plurality of feature points on the object in a predetermined cycle. Next, the position/orientation calculating unit updates, in the predetermined cycle, equations of motion of the plurality of feature points on the basis of the positions of the plurality of feature points detected by the feature-point detecting unit. Furthermore, the position/orientation calculating unit calculates anew the positions of the plurality of feature points from the updated equations of motion and calculates the position or orientation of the object on the basis of the calculated positions of the plurality of feature points. Then, the robot-arm-movement control unit controls the robot arm so as to follow the object, on the basis of the position or orientation of the object calculated by the position/orientation calculating unit.
In this way, because the equation of motion of each feature point is updated in the predetermined cycle, building of an equation of motion of an object is enabled online. As a result, the robot arm can be made to follow an object that moves randomly, with high accuracy.
In the above-described robot control device, the position/orientation calculating unit may weight the plurality of feature points on the object on the basis of the frequencies of detection of the plurality of feature points.
By doing so, even if part of the plurality of feature points is blocked by obstacle or the like, and thus, the position or orientation of the object cannot be directly detected by a visual sensor, the position of each feature point calculated from the equation of motion and the position of each feature point that can be detected by the visual sensor are weighted on the basis of the frequencies of detection to calculate the position of the object, thereby making it possible to make the robot arm accurately follow the object.
In the above-described robot control device, the robot-arm-movement control unit may be provided with a singular-point avoiding unit that avoids a singular point of the robot arm.
With this configuration, a singular point can be avoided, thus making it possible to avoid an operational problem, such as abnormally fast rotation of a particular joint in the robot arm.
According to the present invention, an advantageous effect is afforded in that the robot arm can be made to accurately follow a workpiece that randomly moves.
Number | Date | Country | Kind |
---|---|---|---|
2016-159895 | Aug 2016 | JP | national |
Number | Name | Date | Kind |
---|---|---|---|
4302138 | Zarudiansky | Nov 1981 | A |
4575297 | Richter | Mar 1986 | A |
4623183 | Aomori | Nov 1986 | A |
4783107 | Parker | Nov 1988 | A |
4942538 | Yuan | Jul 1990 | A |
4957320 | Ulrich | Sep 1990 | A |
5004391 | Burdea | Apr 1991 | A |
5280265 | Kramer | Jan 1994 | A |
5437490 | Mimura | Aug 1995 | A |
5501498 | Ulrich | Mar 1996 | A |
5548667 | Tu | Aug 1996 | A |
5579444 | Dalziel | Nov 1996 | A |
5631861 | Kramer | May 1997 | A |
5748854 | Watanabe | May 1998 | A |
5967580 | Rosheim | Oct 1999 | A |
6016385 | Yee | Jan 2000 | A |
6042555 | Kramer | Mar 2000 | A |
6044183 | Pryor | Mar 2000 | A |
6249718 | Gilliland | Jun 2001 | B1 |
6278906 | Piepmeier | Aug 2001 | B1 |
6565563 | Agee | May 2003 | B1 |
6701296 | Kramer | Mar 2004 | B1 |
6924787 | Kramer | Aug 2005 | B2 |
7313464 | Perreault | Dec 2007 | B1 |
7862522 | Barclay | Jan 2011 | B1 |
7877165 | Sugiyama | Jan 2011 | B2 |
7957583 | Boca | Jun 2011 | B2 |
8219352 | Taguchi | Jul 2012 | B2 |
8255079 | Linn | Aug 2012 | B2 |
8350806 | Nagasaka | Jan 2013 | B2 |
8467903 | Ihrke | Jun 2013 | B2 |
8483880 | de la Rosa Tames | Jul 2013 | B2 |
9030674 | Bonin | May 2015 | B2 |
9108321 | Emoto et al. | Aug 2015 | B2 |
9122275 | Kim | Sep 2015 | B2 |
9321176 | Sun | Apr 2016 | B1 |
9333648 | Kim | May 2016 | B2 |
9383895 | Vinayak | Jul 2016 | B1 |
9427874 | Rublee | Aug 2016 | B1 |
9492923 | Wellman | Nov 2016 | B2 |
9545717 | Kim | Jan 2017 | B2 |
9616568 | Russell | Apr 2017 | B1 |
9669543 | Stubbs | Jun 2017 | B1 |
9868212 | Hinterstoisser | Jan 2018 | B1 |
10131051 | Goyal | Nov 2018 | B1 |
20040106916 | Quaid | Jun 2004 | A1 |
20040266276 | Hariki | Dec 2004 | A1 |
20070078564 | Hoshino | Apr 2007 | A1 |
20070152619 | Sugiyama | Jul 2007 | A1 |
20070282485 | Nagatsuka | Dec 2007 | A1 |
20080204425 | Nagasaka | Aug 2008 | A1 |
20080240889 | Yokoyama | Oct 2008 | A1 |
20090285664 | Kim | Nov 2009 | A1 |
20090302626 | Dollar | Dec 2009 | A1 |
20090306825 | Li | Dec 2009 | A1 |
20100010670 | Matsukuma | Jan 2010 | A1 |
20100070246 | Choi | Mar 2010 | A1 |
20100098324 | Fujieda | Apr 2010 | A1 |
20100103106 | Chui | Apr 2010 | A1 |
20100138039 | Moon | Jun 2010 | A1 |
20100176615 | Okuda | Jul 2010 | A1 |
20100215257 | Dariush | Aug 2010 | A1 |
20100292837 | Takahashi | Nov 2010 | A1 |
20110118877 | Hwang | May 2011 | A1 |
20110238213 | Nagasaka | Sep 2011 | A1 |
20110288681 | Hayakawa | Nov 2011 | A1 |
20120078419 | Kim | Mar 2012 | A1 |
20120123589 | Kim | May 2012 | A1 |
20130041502 | Shi | Feb 2013 | A1 |
20130057004 | Murata | Mar 2013 | A1 |
20130173055 | Kim | Jul 2013 | A1 |
20130238125 | Suzuki | Sep 2013 | A1 |
20130238129 | Rose | Sep 2013 | A1 |
20130245828 | Tateno | Sep 2013 | A1 |
20130273968 | Rhoads | Oct 2013 | A1 |
20140012416 | Negishi | Jan 2014 | A1 |
20140067126 | Watanabe | Mar 2014 | A1 |
20140074291 | Emoto | Mar 2014 | A1 |
20140163731 | Shi | Jun 2014 | A1 |
20140226136 | Gagnon | Aug 2014 | A1 |
20140293009 | Nakazato | Oct 2014 | A1 |
20140371910 | Hayashi | Dec 2014 | A1 |
20150019013 | Rose | Jan 2015 | A1 |
20150124057 | Yamazaki | May 2015 | A1 |
20150290795 | Oleynik | Oct 2015 | A1 |
20150314452 | Tateno | Nov 2015 | A1 |
20160058519 | Herr | Mar 2016 | A1 |
20160059412 | Oleynik | Mar 2016 | A1 |
20160155235 | Miyatani | Jun 2016 | A1 |
20160167227 | Wellman | Jun 2016 | A1 |
20160167228 | Wellman | Jun 2016 | A1 |
20160232654 | Suzuki | Aug 2016 | A1 |
20170097232 | Anderson-Sprecher | Apr 2017 | A1 |
Number | Date | Country |
---|---|---|
103459102 | Dec 2013 | CN |
103646391 | Mar 2014 | CN |
104786226 | Jul 2015 | CN |
105740899 | Jul 2016 | CN |
2708334 | Mar 2014 | EP |
2002018754 | Jan 2002 | JP |
2002163639 | Jun 2002 | JP |
2003311674 | Nov 2003 | JP |
4265088 | May 2009 | JP |
2010515995 | May 2010 | JP |
2011143494 | Jul 2011 | JP |
2011161615 | Aug 2011 | JP |
2012236254 | Dec 2012 | JP |
2014161937 | Sep 2014 | JP |
2015000454 | Jan 2015 | JP |
2016103230 | Jun 2016 | JP |
Entry |
---|
Japanese Office Action dated Sep. 4, 2018, for Japanese Patent Application No. 2016-159895. |
Japanese Search Report from Registered Search Organization dated Sep. 4, 2018, for Japanese Patent Application No. 2016-159895. |
Yongxiang Fan, Hsien-Chung Lin, et al., “Object Position and Orientation Tracking for Manipulators Considering Nonnegligible Sensor Physics”, Proceedings of ISFA2016, 2016 International Symposium on Flexible Automation, Aug. 1-3, 2016, Cleveland, Ohio, U.S.A. |
“Kinematics—Inverse Kinematic Singularity, Redundancy”, Centre for Robotics Research—School of Natural and Mathematical Sciences—King's College London, undated. |
Japanese Decision to Grant a Patent dated Mar. 12, 2019, for Japanese Patent Application No. 2016-159895. |
Chinese Office Action dated Jun. 5, 2019, for Chinese Patent Application No. 201710687596.0. |
Number | Date | Country | |
---|---|---|---|
20180050452 A1 | Feb 2018 | US |