CN113997284A - Inverse solution optimization method of double-arm cooperative robot based on longicorn whisker algorithm - Google Patents
Inverse solution optimization method of double-arm cooperative robot based on longicorn whisker algorithm Download PDFInfo
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- CN113997284A CN113997284A CN202111241095.2A CN202111241095A CN113997284A CN 113997284 A CN113997284 A CN 113997284A CN 202111241095 A CN202111241095 A CN 202111241095A CN 113997284 A CN113997284 A CN 113997284A
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- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
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- B25J9/00—Programme-controlled manipulators
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B25J9/00—Programme-controlled manipulators
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Abstract
The invention discloses a double-arm cooperative robot inverse solution optimization method based on a longicorn whisker algorithm, which comprises the following steps of: s1, dividing the two arms into a master arm and a slave arm, establishing a cooperative constraint equation by adopting a master-slave mode in motion planning, and calculating the slave arm according to the master arm; s2, angle of joint of slave armAs an initial value of the iteration, combining the transformation matrixObtaining the terminal pose of the slave arm; s3, judging the flight direction by using the symbolic function according to the longicorn whisker algorithm, updating X, and comparingAndsize and formDetermining the flight direction; s4, judging whether X is in the target interval, if not, returning the value of X to the previous step; s5, repeating the steps S3 and S4 to meet the conditions, wherein X is the inverse solution of the seven-axis mechanical arm. The longicorn beard algorithm is inspired by the foraging principle of the longicorn and developed, belongs to an intelligent optimization algorithm, and is not easily influenced by gradients and initial values in the iteration process, so that the seven-axis mechanical arm kinematics inverse solution meeting the precision requirement and the target interval can be quickly and accurately obtained.
Description
Technical Field
The invention belongs to the technical field of control of double-arm industrial robots, relates to an industrial robot control technology, and particularly relates to a double-arm cooperative robot inverse solution optimization method based on a longicorn whisker algorithm.
Background
With the complication of industrial tasks and the improvement of the reliability requirement of a robot system, the traditional single-arm six-degree-of-freedom robot cannot meet the requirement, the double-arm robot with the redundant degree-of-freedom design improves the working efficiency of the mechanical arm and further improves the working capacity of the industrial robot, double-arm cooperative motion planning is the key content of double-arm robot development, wherein the inverse kinematics of a seven-degree-of-freedom articulated robot is the development basis, some inverse kinematics solving methods for the six-degree-of-freedom mechanical arm are not suitable for the seven-degree-of-freedom mechanical arm, and meanwhile, optimization from the inverse kinematics angle of the robot is an important way for perfecting a double-arm cooperative space.
Disclosure of Invention
In order to solve the problems, the invention discloses a double-arm cooperative robot inverse solution optimization method based on a longicorn whisker algorithm.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a double-arm cooperative robot inverse solution optimization method based on a longicorn whisker algorithm comprises the following steps:
s1, completing double-arm cooperative motion planning by adopting a master/slave mode, and acquiring target position and target posture information of the tail end of the slave arm in the cooperative motion process;
s2, determining the current joint theta 'of the slave arm'1,θ′2,L θ′7As an iteration initial value, solving the iteration initial value according to a general expression of a homogeneous transformation matrix continuous multiplication calculation formula under a dh model of the seven-degree-of-freedom articulated robotThe rotation component and the position component are respectively corresponding to the rotation component and the position component of the pose of the terminal coordinate system of the seven-degree-of-freedom mechanical arm (slave arm), twelve equations can be obtained, and F (X) is 0, wherein X is seven joint angles to be solved;
s3, abstracting the foraging process of the longicorn into a mathematical model according to the longicorn silk algorithm, and firstly calculating a function value F of the left silkl=F(Xl) Then, calculate the function value F of the right whiskerr=F(Xr) Wherein X isl、XrRespectively representing the coordinates of the left and right whiskers of the longicorn, judging the flight direction of the next step by using a symbolic function, and adopting a calculation method: x-stepgdirgsin (F)l-Fr) Updating the value of X and substituting the obtained X value into the calculation F againl=F(Xl) And Fr=F(Xr) Judging the size of the search result to determine the next search direction;
s4, giving the joint angle of the slave arm (theta)1,θ2L θ7) Setting a target interval, judging whether the value of X is in the target interval, and if not, returning the value of X to the last calculation result;
and S5, repeating the iterative calculation of the steps S3 and S4 until the set circulation condition is reached, wherein X at the time is the inverse solution of the seven-degree-of-freedom mechanical arm meeting the interval requirement.
The invention has the beneficial effects that:
the longicorn beard algorithm used by the invention is developed by being inspired by the foraging principle of the longicorn, belongs to one kind of intelligent optimization algorithm, and is not easily influenced by the gradient and the initial value in the iteration process, so that the inverse solution of the seven-degree-of-freedom mechanical arm kinematics meeting the precision requirement and the target interval can be rapidly and accurately obtained in real time.
Drawings
FIG. 1 is a schematic view of a spatial coordinate system established by a seven-degree-of-freedom mechanical arm according to the present invention;
fig. 2 is a flow chart of an algorithm according to the present invention.
Detailed Description
The present invention will be further illustrated with reference to the accompanying drawings and specific embodiments, which are to be understood as merely illustrative of the invention and not as limiting the scope of the invention.
As shown in fig. 2, a double-arm cooperative robot inverse solution optimization method based on a longicorn whisker algorithm: the method comprises the following steps:
s1, completing double-arm cooperative motion planning by adopting a master/slave mode, and acquiring target position and target posture information of the tail end of the slave arm in the cooperative motion process;
the method comprises the following specific steps:
and S11, determining a double-arm cooperative motion planning mode, finishing double-arm cooperative motion planning by adopting a master/slave mode, and establishing a double-arm cooperative constraint equation according to a motion relation in double-arm cooperative motion. The position and the attitude information of the tail end of the main arm are calculated according to the angles of all joints of the main arm, and then the target position and the target attitude information of the tail end of the slave arm are calculated according to the motion constraint relation of the two arms.
The specific operation steps of step S2 include:
s21, determining a dh model of the automatic operation machine: first a coordinate system is established. ZiThe coordinate axis establishment rule is the axial direction of the i +1 joint; xiCoordinate axis establishing rule is along ZiAnd Zi-1Common perpendicular to the axes and directed away from Zi-1The direction of the axis; when the two joint axes intersect, the outer product Z of the direction of the X axis and the direction vectori×Zi-1Parallel or anti-parallel; y isiCoordinate axis establishment rule is that direction satisfies XiAxis, ZiAxis constituting Xi,Yi,ZiThe condition of a right-hand rectangular coordinate system; origin OiEstablishing a rule of ZiAnd XiThe intersection point of (a). If the two axes are parallel, then O is selectediThe point makes the distance to the next link zero. As shown in FIG. 1, the diamond shape indicates that the axis of rotation is parallel to the paperThe surface and the ring indicate that the rotation axis is perpendicular to the straight surface.
The DH parameter. Length of connecting rod aiIs the distance between the two joint axes, i.e. ZiAxis and Zi-1The length of the common perpendicular to the shaft; connecting rod torsion angle alphaiAt an angle between the axes of the two joints, i.e. about XiAxis (according to the right-hand rule) by Zi-1Axial direction ZiA shaft; link distance diIs two common vertical lines alphaiAnd alphai-1A distance therebetween, i.e. XiAxis and Xi-1The distance between the axes; angle of rotation theta of connecting rodiIs two common vertical lines alphaiAnd alphai-1Angle therebetween, i.e. around Zi-1Axis (according to right-hand rule) by Xi-1Axial direction XiA shaft.
The dh parameters specifically selected for this patent are shown in table 1.
S22, taking each joint angle theta 'where the seven-degree-of-freedom articulated robot is currently located'1To theta'7As an iteration initial angle;
s23, general expression for DH matrix transformation:
from the general expression for DH matrix transformation described above and table 1, we can see:
s24, obtaining the following product according to the matrix continuous multiplication:
twelve equations can be derived, determining the fitness function as:
wherein the unknown number X is a joint angle,representing the ith row and the jth column element of the 4 x 4 matrix, and so on.
S3, known as f (x) 0, is each of twelve equationsThe equation contains seven unknowns, and F is judged by utilizing the skyhook foraging process to simplify an abstract model according to the skyhook-whisker algorithml=F(Xl) And Fr=F(Xr) Size of (2), said XlRepresenting the left whisker coordinate, X, of a longicornrRepresenting the coordinates of the right beard of the longicorn, and X represents the coordinates of the mass center; and judging the flight direction of the next step by using a sign function, and updating the value of X: x-stepgdirgsin (F)l-Fr) (ii) a Bringing the new X into XlAnd XrIn the expression of (1), and judging F againl=F(Xl) And Fr=F(Xr) The size of (d);
the method comprises the following specific steps:
s31, obtaining a random vector dir ═ rand (n,1) of the direction of the vector in which the right tendril points to the left tendril, according to the foraging principle of the longicorn; where n refers to the number of unknowns, dir represents the orientation, and rand (n,1) is a function for generating an n × 1 order random vector;
s32, normalizing the orientation of the vector pointing from the right hamulus palpus to the left palpus, which is expressed as: dir/norm (dir), where norm () represents a function that evaluates to a vector norm, such that X can be derivedl-Xr=d0gdir, then the left whisker position X can be obtainedl=X+d0gdir/2; the right whisker position X is also obtainedr=X-d0gdir/2, wherein d0Representing the distance between the left and right whiskers;
s33, calculating the function value F of the left beardl=F(Xl) And the right whisker function value Fr=F(Xr) The size of (d);
s34, judging the next flight direction by using a sign function sign (), and updating the value of X: x-stepgdirgsin (F)l-Fr) Where step represents the step size, the resulting new X is substituted into XlAnd XrIn the expression of (1), and judging F againl=F(Xl) And Fr=F(Xr) The size of (2).
S4, setting a target interval of inverse solution for each joint angle, and continuing the next operation when the newly obtained X value meets the requirement of the target interval; and if the target interval requirement is not met, returning the X value to the result obtained in the previous step, and continuing the next operation.
And repeating the iterative calculation of the steps S3 and S4 until the set circulation condition is reached, wherein X at the moment is the inverse solution of the seven-degree-of-freedom joint robot meeting the requirement of the target interval.
In conclusion, the invention has high precision and quick convergence, and can quickly and accurately calculate the inverse solution of the wrist offset type automatic operation machine in real time.
It should be noted that the above-mentioned contents only illustrate the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and it is obvious to those skilled in the art that several modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations fall within the protection scope of the claims of the present invention.
Claims (7)
1. A double-arm cooperative robot inverse solution optimization method based on a longicorn whisker algorithm is characterized by comprising the following steps:
s1, completing double-arm cooperative motion planning by adopting a master/slave mode, and acquiring target position and target posture information of the tail end of the slave arm in the cooperative motion process;
s2, determining the joint theta of each current position of the slave arm1’、θ2’Lθ7The' is used as an iteration initial value and then solved according to a general expression of a homogeneous transformation matrix continuous multiplication calculation formula under a DH model of the seven-degree-of-freedom articulated robotRespectively corresponding the rotation component and the position component to the rotation component and the position component of the pose of the seven-degree-of-freedom mechanical arm tail end coordinate system to obtain twelve equations, wherein F (X) is 0, and X is seven joint angles to be solved;
s3, abstracting the foraging process of the longicorn into a mathematical model according to the longicorn silk algorithm, and firstly calculating a function value F of the left silkl=F(Xl) Then, calculate the function value F of the right whiskerr=F(Xr) Wherein X isl、XrRespectively representing the coordinates of the left and right whiskers of the longicorn, judging the flight direction of the next step by using a symbolic function, and adopting a calculation method: x-stepgdirgsin (F)l-Fr) Updating the value of X and substituting the obtained X value into the calculation F againl=F(Xl) And Fr=F(Xr) Judging the size of the search result to determine the next search direction;
s4, giving the joint angle of the slave arm (theta)1、θ2Lθ7) Setting a target interval, judging whether the value of X is in the target interval, and if not, returning the value of X to the last calculation result;
and S5, repeating the iterative calculation of the steps S3 and S4 until the set circulation condition is reached, wherein X at the time is the inverse solution of the seven-degree-of-freedom mechanical arm meeting the interval requirement.
2. The inverse solution optimizing method for the double-arm cooperative robot based on the longicorn whisker algorithm as claimed in claim 1, wherein the specific operation steps of the step S1 include:
s11, determining a double-arm cooperative motion planning mode, finishing double-arm cooperative motion planning by adopting a master/slave mode, and establishing a double-arm cooperative constraint equation according to a motion relation in double-arm cooperative motion; the position and the attitude information of the tail end of the main arm are calculated according to the angles of all joints of the main arm, and then the target position and the target attitude information of the tail end of the slave arm are calculated according to the motion constraint relation of the two arms.
3. The inverse solution optimizing method for the double-arm cooperative robot based on the longicorn whisker algorithm as claimed in claim 2, wherein the specific operation steps of the step S2 include:
s21, determining a DH model of the seven-degree-of-freedom joint robot: firstly, establishing a coordinate system; ziThe coordinate axis establishment rule is the axial direction of the i +1 joint; xiCoordinate axis establishing rule is along ZiAnd Zi-1Common perpendicular to the axes and directed away from Zi-1The direction of the axis; when the two joint axes intersect, the outer product Z of the direction of the X axis and the direction vectori×Zi-1Parallel or anti-parallel; y isiCoordinate axis establishment rule is that direction satisfies XiAxis, ZiAxis constituting Xi,Yi,ZiThe condition of a right-hand rectangular coordinate system; origin OiEstablishing a rule of ZiAnd XiThe intersection point of (a); if the two axes are parallel, then O is selectediThe point makes the distance to the next link zero;
s22, taking the current joint angle theta of the seven-degree-of-freedom joint robot1' to theta7' as an iteration initial angle;
s23, general expression for DH matrix transformation:
wherein the length of the connecting rod aiIs the distance between the two joint axes, i.e. ZiAxis and Zi-1The length of the common perpendicular to the shaft; connecting rod torsion angle alphaiAt an angle between the axes of the two joints, i.e. about XiAxis of, by Zi-1Axial direction ZiA shaft; link distance diIs two common vertical lines alphaiAnd alphai-1A distance therebetween, i.e. XiAxis and Xi-1The distance between the axes; angle of rotation theta of connecting rodiIs two common vertical lines alphaiAnd alphai-1Angle therebetween, i.e. around Zi-1Axis of Xi-1Axial direction XiA shaft;
Twelve equations were found, let it be f (X) ═ 0, where the unknown number X is seven joint angles;
twelve equations are derived, and the fitness function is determined to be:
4. The inverse solution optimizing method for the double-arm cooperative robot based on the longicorn whisker algorithm as claimed in claim 3, wherein the specific operation steps of the step S3 include:
s31, obtaining a random vector dir ═ rand (n,1) of the direction of the vector in which the right tendril points to the left tendril, according to the foraging principle of the longicorn; where n refers to the number of unknowns, dir represents the orientation, and rand (n,1) is a function for generating an n × 1 order random vector;
s32, normalizing the orientation of the vector pointing from the right hamulus palpus to the left palpus, which is expressed as: dir/norm (dir), where norm () represents a function that evaluates to a vector norm, resulting in Xl-Xr=d0gdir, then find the left whisker position Xl=X+d0gdir/2; the right whisker position X is also obtainedr=X-d0gdir/2, wherein d0Representing the distance between the left and right whiskers;
s33, calculating the function value F of the left beardl=F(Xl) And the right whisker function value Fr=F(Xr) The size of (d);
s34, using notationThe number sign () determines the next flight direction and updates the value of X: x-stepgdirgsin (F)l-Fr) Where step represents the step size, the resulting new X is substituted into XlAnd XrIn the expression of (1), and judging F againl=F(Xl) And Fr=F(Xr) The size of (2).
5. The inverse solution optimizing method for the double-arm cooperative robot based on the longicorn whisker algorithm as claimed in claim 4, wherein the specific operation steps of the step S4 include:
s41, setting a target interval of inverse solution for each joint angle, and continuing the next operation when the newly obtained X value meets the requirement of the target interval; and if the target interval requirement is not met, returning the X value to the result obtained in the previous step, and continuing the next operation.
6. The inverse solution optimization method for double-arm cooperative robot based on longicorn whisker algorithm as claimed in claim 5, wherein step is variable step length, and step d0gc, where c is a constant, step ═ stepgap is used in each iteration step, where gap is between 0 and 1 and close to 1.
7. The inverse solution optimization method for double-arm cooperative robots based on the longicorn whisker algorithm as recited in claim 6, wherein eta takes a value of 0.95.
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CN113434982A (en) * | 2021-07-07 | 2021-09-24 | 合肥工业大学 | Inverse kinematics solution method of electric intelligent bionic climbing robot |
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CN109591014A (en) * | 2018-12-18 | 2019-04-09 | 武汉科技大学 | A kind of Dual-Arm Coordination method for carrying of both arms cooperation robot |
CN110919638A (en) * | 2019-11-15 | 2020-03-27 | 华中科技大学 | 3+4 new-configuration double-arm cooperative robot machining system and method |
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