CN106980263B - Master-slave optimization method for multiple on-orbit tasks - Google Patents
Master-slave optimization method for multiple on-orbit tasks Download PDFInfo
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- CN106980263B CN106980263B CN201710225280.XA CN201710225280A CN106980263B CN 106980263 B CN106980263 B CN 106980263B CN 201710225280 A CN201710225280 A CN 201710225280A CN 106980263 B CN106980263 B CN 106980263B
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Abstract
The invention discloses a master-slave optimization method for a plurality of on-orbit tasks, which comprises the steps of firstly obtaining an optimal waypoint sequence according to a target requirement of a main layer based on the layer; then according to the main layer-based waypoint sequence of the auxiliary layer and the combination of the target requirement and the theoretical equation of the layer, the joint motion of the robot is obtained; and finally, the auxiliary layer transmits the optimization result to the main layer, the main layer improves the sequence of the waypoints according to the target requirement and the optimization result of the auxiliary layer, and transmits the sequence to the auxiliary layer, and if the index requirement is met, the circulation is ended. The invention adopts an improved genetic algorithm based on the set partial order relationship to carry out optimization solution on the master-slave optimization problem based on multiple tasks. The algorithm is intuitive in form, short in running time and high in optimization result precision, and the sum of the errors of the actual pose and the expected pose at all the waypoints can be zero. In addition, the algorithm is based on a positive kinematic equation, and singularity in the motion process of the space robot can be avoided.
Description
Technical Field
The invention belongs to the technical field of spacecraft operation planning, and particularly relates to a master-slave optimization method for multiple on-orbit tasks.
Background
Space robots have been used in recent decades to perform a number of orbital tasks such as space station assembly, orbital debris cleaning. Since operation planning is the basis for successfully completing tasks by using space robots, research on robot operation planning has become the focus in recent years. At present, the researches on the operation planning of the space robot are mainly divided into two types: point-to-point planning in task space and configuration-to-configuration planning in joint space.
In industrial production, robots are often used to perform multiple tasks in succession, so as to achieve the purposes of improving productivity and saving cost. At present, the research on the problem of multitask operation planning of the industrial robot is mature, and document [4] summarizes a research method of the task sequence problem in the process of continuously executing multiple tasks by the industrial robot, but does not relate to the motion change of each joint. Further, document [5] is based on remote laser welding of a robot, and studies on a task sequence and a robot end effector path planning problem, but does not consider joint motion of the robot.
Using space robots to perform multiple tasks in succession helps to conserve fuel, since fuel is at a premium in a rail environment. Therefore, it is necessary to research the operation planning problem of the space robot to continuously perform a plurality of tasks.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a master-slave optimization method for multiple on-orbit tasks, aiming at the deficiencies in the prior art, and the method is used for solving the operation planning problem of a space robot continuously executing multiple on-orbit tasks. In addition, in the operation planning process, each task is regarded as a waypoint, namely, the task set is regarded as a waypoint set. The end effector is required to pass each waypoint in the set of waypoints with a sum of the actual and expected pose errors at all waypoints being zero.
The invention adopts the following technical scheme:
a master-slave optimization method for multiple on-orbit tasks comprises the following steps:
s1, obtaining an optimal waypoint sequence by the main layer based on the target requirement of the main layer;
s2, obtaining the joint motion of the robot by the auxiliary layer based on the waypoint sequence of the main layer and combining the target requirement and the theoretical equation of the layer;
and S3, the auxiliary layer transmits the optimization result to the main layer, the main layer improves the waypoint sequence according to the target requirement and the optimization result of the auxiliary layer, and transmits the waypoint sequence to the auxiliary layer, and if the index requirement is met, the circulation is ended.
Preferably, the step S1 is specifically as follows:
s11, initializing the population by adopting a real number coding system;
s12, calculating a fitness value to obtain the path length;
and S13, selecting, crossing and mutating, comparing the calculation result of the step S12 with the calculation result of the previous iteration, and selecting a better one.
Preferably, the optimal waypoint sequence of the main layer is as follows:
wherein n is the number of points along the way, xiIs the position of the waypoint passed by at the ith time,
is a waypoint xiAnd a waypoint xi+1The distance between them.
Preferably, in step S2, the joint angle of the in-orbit service robot is optimized by using an improved genetic algorithm based on a positive kinematic equation, so that the spatial robot end effector moves according to the waypoint sequence obtained in step one, and the sum of the actual pose and the expected pose errors at all the waypoints is required to be zero, and the specific steps are as follows:
s21, initializing the population by adopting binary coding;
s22, calculating a fitness value to obtain the sum of the actual pose and the expected pose errors of all waypoints;
and S23, adopting selection, intersection and variation, comparing the calculation result of the step S23 with the previous calculation result, and selecting a better one.
Preferably, the positive kinematic equation of the space robot is as follows:
wherein the content of the first and second substances,
is the speed of the end-effector,
to the angular velocity of the joint, JGIs a generalized jacobian matrix.
Preferably, in step S3, the optimization result is: and the length of the path of the end effector obtained by the auxiliary layer by using a positive kinematic equation of the space robot is compared with the length of the sequence path corresponding to the main layer, and if the difference between the lengths meets the given precision, the system circulation is ended.
Compared with the prior art, the invention has at least the following beneficial effects:
the invention adopts an improved genetic algorithm based on the set partial order relationship to carry out optimization solution on the master-slave optimization problem based on multiple tasks. The algorithm is intuitive in form, short in running time and high in optimization result precision, and the sum of the errors of the actual pose and the expected pose at all the waypoints can be zero. In addition, the algorithm is based on a positive kinematic equation, and singularity in the motion process of the space robot can be avoided.
In conclusion, the invention is suitable for the space robot to continuously execute a plurality of track operation tasks, so as to save track fuel and reduce space cost.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic view of the present invention illustrating a change in position of an end effector;
FIG. 3 is a schematic diagram of the change in attitude of the end effector of the present invention;
fig. 4 is a schematic diagram of the change of the joint angle of the present invention.
Detailed Description
In order to achieve the purposes of saving rail fuel and reducing space cost, the invention provides a master-slave optimization method for a plurality of rail tasks by considering that a space robot is used for continuously executing the plurality of rail tasks. Firstly, obtaining an optimal waypoint sequence by a main layer based on the target requirement of the layer; secondly, the auxiliary layer obtains the joint motion of the robot based on the waypoint sequence of the main layer and by combining the target requirement (the sum of the actual pose and the expected pose errors at all the waypoints is zero) of the layer with a theoretical equation (a space robot kinematic equation); and finally, the auxiliary layer transmits the optimization result to the main layer, the main layer improves the sequence of the waypoints according to the target requirement and the optimization result of the auxiliary layer and transmits the sequence to the auxiliary layer, and if the index requirement is met, the circulation is ended.
Referring to fig. 1, the specific steps are as follows:
s1, main layer-finding the optimal sequence of waypoints;
based on the position of each waypoint, finding an optimal waypoint sequence, wherein the mathematical model is as follows:
wherein n is the number of points along the way, xiIs the position of the waypoint passed by at the ith time,
is a waypoint xiAnd a waypoint xi+1The distance between them.
The problem is an NP problem, an improved genetic algorithm is adopted to solve the problem, and the method specifically comprises the following steps:
s11, initializing a population, wherein a real number coding system is adopted;
wherein, the number of the waypoints is 5, the number of the chromosomes is 50, and the maximum iteration number is 100.
S12, calculating a fitness value, namely calculating the path length between waypoints according to the formula (1);
s13, selecting, crossing and mutating, and comparing the calculated result (fitness value) with the previous iteration calculated result, and selecting the better one.
Wherein the selection process is performed by a rotary game machine, the crossing process is performed by a single-point crossing, the mutation process is performed by a uniform multi-point mutation, and each point of the chromosome is subjected to a mutation processThe mutation probability of (c) is: x is umin+r(umax-umin) (r is [0,1 ]]Is [ u ] ofmax，umin]Is a variation range).
S2, an affiliated layer, seeking optimal joint movement; and obtaining the optimal joint motion based on the positive kinematic equation (formula 2) of the space robot.
Wherein the content of the first and second substances,
is the speed of the end-effector,
to the angular velocity of the joint, JGIs a generalized jacobian matrix.
Optimizing joint angles of the in-orbit service robot by adopting an improved genetic algorithm based on a positive kinematic equation, so that the space robot end effector moves according to the waypoint sequence obtained in the step one, and the sum of errors of actual poses and expected poses at all the waypoints is required to be zero, and the specific steps are as follows:
s21, initializing a population, wherein binary coding is adopted;
s22, calculating a fitness value, namely the sum of the actual pose and the expected pose errors of all waypoints;
s23, selecting, crossing and mutating, comparing the calculation result with the previous calculation result, and selecting the better one;
the selection process is carried out by adopting a rotary gambling wheel mechanism, the crossing process is carried out by adopting two-point crossing, the mutation process is carried out by adopting uniform multipoint mutation, and the mutation probability at each point of a chromosome is as follows: x is umin+r(umax-umin) (r is [0,1 ]]Is [ u ] ofmax，umin]Is a variation range).
S3, checking whether the termination condition is satisfied.
Firstly, initializing main layer parameters, optimizing the main layer according to corresponding selection, crossing and variation mechanisms to obtain an optimal waypoint sequence, and transmitting the sequence to an auxiliary layer; secondly, initializing parameters of an auxiliary layer, and carrying out selection, crossing and variation processes on the auxiliary layer by combining results of a main layer to obtain an optimal joint angle; and finally, the auxiliary layer transmits the path length of the waypoint obtained based on the joint angle obtained by optimization and the positive kinematic equation formula (2) of the space robot to the main layer, compares the path length with the path length of the waypoint expected by the main layer, and ends the system cycle if the difference between the path length and the path length meets the given precision.
Referring to fig. 2-4, fig. 2 and 3 depict the position and attitude changes of the end effector during movement, respectively; as can be seen from fig. 2 and 3, optimization using the improved genetic algorithm can result in the end effector reaching a specified waypoint at a specified time and zero pose error at each waypoint. Fig. 4 depicts the change of each joint angle, and the curve is smooth.
The present invention requires that the end effector of the space robot system pass five waypoints (pose data see table 1) and requires that the sum of the actual and expected pose errors at all waypoints be zero.
TABLE 1 presents the position data for each given waypoint
According to the position data of each waypoint given in table 1, an optimized sequence of waypoints is required to be obtained and the terminal is required to execute the movement according to the optimized sequence of waypoints, and the movement time between adjacent waypoints is 5 s. It is required that the end effector can accurately reach a waypoint of a given pose. Using a modified genetic algorithm to optimize firstly the sequence of waypoints and secondly the joint angle such that the end effector moves exactly according to the sequence of waypoints obtained and arrives exactly at the next waypoint within a specified time
The above-mentioned contents are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical idea of the present invention falls within the protection scope of the claims of the present invention.
Claims (3)
1. A master-slave optimization method for a plurality of on-orbit tasks is characterized by comprising the following steps:
s1, obtaining an optimal waypoint sequence by the main layer based on the target requirement of the layer, wherein the optimal waypoint sequence is as follows:
s11, initializing the population by adopting a real number coding system;
s12, calculating a fitness value to obtain the path length;
s13, selecting, crossing and mutating, comparing the calculation result of the step S12 with the calculation result of the previous iteration, and selecting the better one, wherein the optimal waypoint sequence of the main layer is as follows:
wherein n is the number of points along the way, xiIs the position of the waypoint passed by at the ith time,
is a waypoint xiAnd a waypoint xi+1The distance between them;
s2, obtaining the joint motion of the robot by the aid of the main layer-based waypoint sequence of the affiliated layer and the combination of the target requirement and the theoretical equation of the layer, optimizing joint angles of the in-orbit service robot by the aid of an improved genetic algorithm based on a positive kinematic equation, enabling the space robot end effector to move according to the waypoint sequence obtained in the first step, and requiring the sum of errors of actual poses and expected poses of all waypoints to be zero, wherein the specific steps are as follows:
s21, initializing the population by adopting binary coding;
s22, calculating a fitness value to obtain the sum of the actual pose and the expected pose errors of all waypoints;
s23, selecting, crossing and mutating, comparing the calculation result of the step S23 with the previous calculation result, and selecting the better one;
and S3, the auxiliary layer transmits the optimization result to the main layer, the main layer improves the waypoint sequence according to the target requirement and the optimization result of the auxiliary layer, and transmits the waypoint sequence to the auxiliary layer, and if the index requirement is met, the circulation is ended.
2. The master-slave optimization method for multiple on-orbit tasks according to claim 1, wherein the positive kinematic equation of the space robot is as follows:
wherein the content of the first and second substances,
is the speed of the end-effector,
to the angular velocity of the joint, JGIs a generalized jacobian matrix.
3. The method according to claim 1, wherein in step S3, the optimization result is: and the length of the path of the end effector obtained by the auxiliary layer by using a positive kinematic equation of the space robot is compared with the length of the sequence path corresponding to the main layer, and if the difference between the lengths meets the given precision, the system circulation is ended.
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| CN103143819A (en) * | 2013-03-22 | 2013-06-12 | 浙江正特集团有限公司 | Automatic welding machine and control method thereof |
| DE102013203381A1 (en) * | 2012-03-15 | 2013-09-19 | GM Global Technology Operations LLC (n. d. Ges. d. Staates Delaware) | METHOD AND SYSTEM FOR TRAINING AN ROBOT USING A RESPONSIBLE DEMONSTRATION SUPPORTED BY PEOPLE |
| CN104331547A (en) * | 2014-10-23 | 2015-02-04 | 北京控制工程研究所 | Space mechanical arm structure parameter optimization method based on operability |
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| CN102161198A (en) * | 2011-03-18 | 2011-08-24 | 浙江大学 | Mater-slave type co-evolution method for path planning of mobile manipulator in three-dimensional space |
| DE102013203381A1 (en) * | 2012-03-15 | 2013-09-19 | GM Global Technology Operations LLC (n. d. Ges. d. Staates Delaware) | METHOD AND SYSTEM FOR TRAINING AN ROBOT USING A RESPONSIBLE DEMONSTRATION SUPPORTED BY PEOPLE |
| CN103143819A (en) * | 2013-03-22 | 2013-06-12 | 浙江正特集团有限公司 | Automatic welding machine and control method thereof |
| CN104331547A (en) * | 2014-10-23 | 2015-02-04 | 北京控制工程研究所 | Space mechanical arm structure parameter optimization method based on operability |
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