CN115431260B - Mechanical arm motion planning method and system based on virtual point state backtracking - Google Patents

Mechanical arm motion planning method and system based on virtual point state backtracking Download PDF

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CN115431260B
CN115431260B CN202111479894.3A CN202111479894A CN115431260B CN 115431260 B CN115431260 B CN 115431260B CN 202111479894 A CN202111479894 A CN 202111479894A CN 115431260 B CN115431260 B CN 115431260B
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mechanical arm
path
motion
point
virtual
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CN115431260A (en
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赵瑞
吴凡
于天一
张宽
何锡明
荣志飞
姜萍
王炎娟
周心婷
马鹏德
杨少博
董万坤
师明
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Beijing Aerospace Control Center
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
    • B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning

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Abstract

The invention relates to the technical field of mechanical arm control, in particular to a mechanical arm motion planning method and a system based on virtual point state backtracking, wherein in the planning method, an intermediate mechanical arm motion scene is obtained according to an initial mechanical arm motion scene, in the initial mechanical arm motion scene, the association relation between each preset path point position and the corresponding virtual preset path point position is established, and according to the intermediate mechanical arm motion scene after the association relation is established, and carrying out linearization reconstruction on all updated first paths, unfolding path planning calculation according to a linearization mechanical arm movement scene, calculating a virtual movement path of the mechanical arm and a movement strategy corresponding to the virtual movement path, further obtaining a full-state movement strategy, realizing control on the mechanical arm, avoiding repeated planning, reducing repeated calculation amount and greatly improving path planning efficiency of the mechanical arm.

Description

Mechanical arm motion planning method and system based on virtual point state backtracking
Technical Field
The invention relates to the technical field of mechanical arm control, in particular to a mechanical arm motion planning method and system based on virtual point state backtracking of a mechanical arm.
Background
In the extraterrestrial celestial body sampling detection task, along with the gradual deepening of detection requirements and the increase of complexity of detection activities, the adoption of a mechanical arm for approaching detection and sampling return becomes a common way for engineering implementation, and the works of accessibility support of the spatial position of the mechanical arm, strategy planning for fine action implementation of the mechanical arm and the like become necessary technical paths for engineering implementation.
The teleoperation control is carried out on the mechanical arm, and a motion planning mode is generally adopted, wherein the motion planning comprises two types of path planning and track planning. In a space detection task, the accessibility problem of the mechanical arm is usually only solved and solved, namely, the mechanical arm is controlled to move from one point to another point in space and avoid an obstacle, and the problems such as movement time and the like are not required to be treated as core problems, so that teleoperation planning of the mechanical arm can be simplified into path planning, and a planner calculates and outputs a geometric path meeting the conditions.
In practical engineering application, as the space environment is unknown and various resources are complex in constraint, various constraints are comprehensively considered for teleoperation control of the mechanical arm, and a multi-branch control strategy is formed according to different constraint conditions. If under ideal conditions, the mechanical arm needs to be controlled to reach the position of the point b from the position of the point a; if part of conditions are not met, in order to meet the requirements of safety and the like, the mechanical arm needs to be controlled to move from the point a to the point b through the point p, and in the scene, a multi-branch movement strategy is formed at the point a due to the difference of the positions of movement target points. For such a mode, if planning is performed on each branch movement strategy, the planner is generally required to be called for multiple times, so that a large amount of repeated planning work is caused, the planning efficiency is reduced, and verification and implementation of the planning strategy are not facilitated.
Disclosure of Invention
The invention aims to solve the technical problem of providing a mechanical arm motion planning method and system based on virtual point state backtracking aiming at the defects of the prior art.
The technical scheme of the mechanical arm motion planning method based on virtual point state backtracking is as follows:
determining an initial mechanical arm motion scene, the initial mechanical arm motion scene comprising: the system comprises a starting position, at least one preset path point position and at least one target position, and a first path from the starting position to each target position, wherein the at least one first path comprises the at least one preset path point position;
Calculating the branch number K i of the ith preset path point position, adding K i -1 virtual preset path point positions corresponding to the ith preset path point position in the initial mechanical arm motion scene, and carrying out one-to-one correspondence replacement on the ith preset path point position in K i first paths comprising the ith preset path point position until each first path is replaced, and carrying out backtracking processing on the initial mechanical arm motion scene to obtain an intermediate mechanical arm motion scene, wherein i is a positive integer;
establishing an association relationship between each preset path point position and a corresponding virtual preset path point position in the middle mechanical arm movement scene;
according to the intermediate mechanical arm motion scene after the association relation is established, carrying out linearization reconstruction on all updated first paths to obtain a linearization mechanical arm motion scene;
calculating a virtual motion path of the mechanical arm and a motion strategy corresponding to the virtual motion path according to the linear mechanical arm motion scene unfolding path planning calculation;
and acquiring an all-state motion strategy according to the virtual motion path of the mechanical arm and the motion strategy corresponding to the virtual motion path, and controlling the mechanical arm according to the actual motion requirement and the all-state motion strategy.
The mechanical arm motion planning method based on virtual point state backtracking has the following beneficial effects:
Obtaining an intermediate mechanical arm motion scene according to an initial mechanical arm motion scene, establishing an association relation between each preset path point position and a corresponding virtual preset path point position in the initial mechanical arm motion scene, carrying out linearization reconstruction on all updated first paths according to the intermediate mechanical arm motion scene after the association relation is established, calculating virtual motion paths of the mechanical arm and motion strategies corresponding to the virtual motion paths according to the linearization mechanical arm motion scene, further obtaining an all-state motion strategy, realizing control of the mechanical arm, avoiding repeated planning, reducing repeated calculation amount and greatly improving path planning efficiency of the mechanical arm.
On the basis of the scheme, the mechanical arm motion planning method based on virtual point state backtracking can be improved as follows.
Further, the calculating the branch number K i of the i-th preset path point position includes:
Calculating the branch number K i of the ith preset path point position according to a first formula, wherein the first formula is as follows: k i＝(Kin)i×(Kout)i,(Kin)i represents: the total number of first path branches directly reaching the ith preset waypoint position obtained from all first paths including the ith preset waypoint position, (K out)i represents the total number of second path branches directly starting from the ith preset waypoint position obtained from all paths including the ith preset waypoint position).
Further, the association relationship includes a half equivalent relationship and a full equivalent relationship, the full equivalent relationship representing: the second path branches after updating of any two positions in the ith preset path point position and the corresponding K i -1 virtual preset path point positions are the same, and the half-equivalence relation represents: the i-th preset path point position and any two positions in the corresponding K i -1 virtual preset path point positions are respectively updated, and at least one of the updated second path branches is different.
The technical scheme of the mechanical arm motion planning system based on virtual point state backtracking is as follows:
the system comprises a scene preprocessing module, a calculation backtracking module, a correlation module, a linearization reconstruction module, a path planning module and a control module;
The scene preprocessing module is used for: determining an initial mechanical arm motion scene, the initial mechanical arm motion scene comprising: the system comprises a starting position, at least one preset path point position and at least one target position, and a first path from the starting position to each target position, wherein the at least one first path comprises the at least one preset path point position;
The calculation backtracking module is used for: calculating the branch number K i of the ith preset path point position, adding K i -1 virtual preset path point positions corresponding to the ith preset path point position in the initial mechanical arm motion scene, and carrying out one-to-one correspondence replacement on the ith preset path point position in K i first paths comprising the ith preset path point position until each first path is replaced, and carrying out backtracking processing on the initial mechanical arm motion scene to obtain an intermediate mechanical arm motion scene, wherein i is a positive integer;
The association module is used for: establishing an association relationship between each preset path point position and a corresponding virtual preset path point position in the middle mechanical arm movement scene;
The linearization reconstruction module is used for: according to the intermediate mechanical arm motion scene after the association relation is established, carrying out linearization reconstruction on all updated first paths to obtain a linearization mechanical arm motion scene;
the path planning module is used for: calculating a virtual motion path of the mechanical arm and a motion strategy corresponding to the virtual motion path according to the linear mechanical arm motion scene unfolding path planning calculation;
The control module is used for:
calculating a virtual motion path of the mechanical arm and a motion strategy corresponding to the virtual motion path according to the linear mechanical arm motion scene unfolding path planning calculation;
and acquiring an all-state motion strategy according to the virtual motion path of the mechanical arm and the motion strategy corresponding to the virtual motion path, and controlling the mechanical arm according to the actual motion requirement and the all-state motion strategy.
The mechanical arm motion planning system based on virtual point state backtracking has the following beneficial effects:
Obtaining an intermediate mechanical arm motion scene according to an initial mechanical arm motion scene, establishing an association relation between each preset path point position and a corresponding virtual preset path point position in the initial mechanical arm motion scene, carrying out linearization reconstruction on all updated first paths according to the intermediate mechanical arm motion scene after the association relation is established, calculating virtual motion paths of the mechanical arm and motion strategies corresponding to the virtual motion paths according to the linearization mechanical arm motion scene, further obtaining an all-state motion strategy, realizing control of the mechanical arm, avoiding repeated planning, reducing repeated calculation amount and greatly improving path planning efficiency of the mechanical arm.
On the basis of the scheme, the mechanical arm motion planning system based on virtual point state backtracking can be improved as follows.
Further, the calculation backtracking module is specifically configured to:
Calculating the branch number K i of the ith preset path point position according to a first formula, wherein the first formula is as follows: k i＝(Kin)i×(Kout)i,(Kin)i represents: the total number of first path branches directly reaching the ith preset waypoint position obtained from all first paths including the ith preset waypoint position, (K out)i represents the total number of second path branches directly starting from the ith preset waypoint position obtained from all paths including the ith preset waypoint position).
Further, the association relationship includes a half equivalent relationship and a full equivalent relationship, the full equivalent relationship representing: the second path branches after updating of any two positions in the ith preset path point position and the corresponding K i -1 virtual preset path point positions are the same, and the half-equivalence relation represents: the i-th preset path point position and any two positions in the corresponding K i -1 virtual preset path point positions are respectively updated, and at least one of the updated second path branches is different.
The storage medium of the invention stores instructions, and when the instructions are read by a computer, the computer is caused to execute the mechanical arm motion planning method based on virtual point state backtracking.
An electronic device of the present invention includes a processor and the storage medium described above, where the processor executes instructions in the storage medium.
Drawings
Fig. 1 is a schematic flow diagram of a robot arm motion planning method based on virtual point state backtracking according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an initial robotic arm motion scenario;
FIG. 3 is a schematic view of a first path;
FIG. 4 is a schematic diagram of a second first path;
FIG. 5 is a schematic diagram of a third first path;
FIG. 6 is a schematic diagram of an intermediate robotic arm motion scenario;
FIG. 7 is a schematic diagram of a motion scenario of an intermediate mechanical arm after an association is established;
FIG. 8 is a schematic diagram of a linearized mechanical arm motion scenario;
Fig. 9 is a schematic flow chart of a robot arm motion planning system based on virtual point state backtracking according to an embodiment of the present invention.
Detailed Description
As shown in fig. 1, a mechanical arm motion planning method based on virtual point state backtracking in an embodiment of the present invention includes the following steps:
S1, determining an initial mechanical arm movement scene, wherein the initial mechanical arm movement scene comprises the following steps: the system comprises a starting position, at least one preset path point position and at least one target position, and a first path from the starting position to each target position, wherein the at least one first path comprises at least one preset path point position, the starting position, the preset path point position and the target position can be set according to actual conditions, and the first path from the starting position to each target position represents: controlling a first path from a starting position to each target position of the tail end point of the mechanical arm;
S2, calculating the branch number K i of the ith preset path point position, adding K i -1 virtual preset path point positions corresponding to the ith preset path point position in the initial mechanical arm motion scene, and carrying out one-to-one correspondence replacement on the ith preset path point position in K i first paths comprising the ith preset path point position until each first path is replaced, and carrying out backtracking processing on the initial mechanical arm motion scene to obtain an intermediate mechanical arm motion scene, wherein i is a positive integer; the backtracking processing is performed on the initial mechanical arm movement scene, specifically: and backtracking the initial mechanical arm movement scene by utilizing all the additionally-arranged virtual preset path point positions to obtain an intermediate mechanical arm movement scene.
S3, establishing an association relation between each preset path point position and a corresponding virtual preset path point position in the middle mechanical arm movement scene;
s4, carrying out linearization reconstruction on all updated first paths according to the intermediate mechanical arm motion scene with the association relation established, and obtaining a linearized mechanical arm motion scene;
s5, calculating a virtual motion path of the mechanical arm and a motion strategy corresponding to the virtual motion path according to the linear mechanical arm motion scene unfolding path planning calculation;
S6, acquiring a full-state motion strategy according to the virtual motion path of the mechanical arm and the motion strategy corresponding to the virtual motion path, and controlling the mechanical arm according to the actual motion requirement and the full-state motion strategy.
Obtaining an intermediate mechanical arm motion scene according to an initial mechanical arm motion scene, establishing an association relation between each preset path point position and a corresponding virtual preset path point position in the initial mechanical arm motion scene, carrying out linearization reconstruction on all updated first paths according to the intermediate mechanical arm motion scene after the association relation is established, calculating virtual motion paths of the mechanical arm and motion strategies corresponding to the virtual motion paths according to the linearization mechanical arm motion scene, further obtaining an all-state motion strategy, realizing control of the mechanical arm, avoiding repeated planning, reducing repeated calculation amount and greatly improving path planning efficiency of the mechanical arm.
Preferably, in the above technical solution, the calculating the branch number K i of the i-th preset path point position includes:
Calculating the branch number K i of the ith preset path point position according to a first formula, wherein the first formula is as follows: k i＝(Kin)i×(Kout)i,(Kin)i represents: the total number of first path branches directly reaching the ith preset waypoint position obtained from all first paths including the ith preset waypoint position, (K out)i represents the total number of second path branches directly starting from the ith preset waypoint position obtained from all paths including the ith preset waypoint position).
Preferably, in the above technical solution, the association relationship includes a half equivalent relationship and a full equivalent relationship, where the full equivalent relationship represents: the second path branches after updating of any two positions in the ith preset path point position and the corresponding K i -1 virtual preset path point positions are the same, and the half-equivalence relation represents: the i-th preset path point position and any two positions in the corresponding K i -1 virtual preset path point positions are respectively updated, and at least one of the updated second path branches is different.
Wherein at least one of the updated second path branches is embodied differently: at least one of the updated second path branches is different in state, or/and at least one of the updated second path branches is different in position.
The following describes a mechanical arm motion planning method based on virtual point state backtracking according to an embodiment, which specifically comprises the following steps:
S20, determining an initial mechanical arm movement scene, wherein the initial mechanical arm movement scene comprises a starting position, 3 preset path point positions and 2 target positions, wherein the starting position is marked as an O point, the 3 preset path point positions are respectively marked as an E point, a P point and a B point, the 2 target positions are respectively marked as an E point and a T point, and the initial mechanical arm movement scene comprises three first paths which are respectively:
1) First path: from point O to point E, the motion path is o→point a→point E, labeled as motion path θ 1,θ1 = [ O, a, E ], the motion strategy is: Ω 1＝[ωOA,ωAE ], wherein ω OA represents: control parameters for controlling the end point of the mechanical arm from point O to point a, ω AE denotes: control parameters for controlling the end point of the mechanical arm from point a to point E are shown in fig. 3.
2) The second first path: from point O to point T, the motion path is O point→a point→b point→e point, labeled as motion path θ 2,θ2 = [ O, a, B, T ], the motion strategy is: Ω 1＝[ωOA,ωAB,ωBT ], wherein ω OA represents: control parameters for controlling the end point of the mechanical arm from point O to point a, ω AB denotes: control parameters for controlling the end point of the mechanical arm from point a to point B, ω BT represents: control parameters for controlling the end point of the robot arm from point B to point T are shown in fig. 4.
3) Third first path: from point O to point T, the motion path is: o point-a point-P point-B point-E point, labeled as motion path θ 3,θ3 = [ O, a, P, B, T ], motion strategy is: Ω 1＝[ωOA,ωAP,ωPB,ωBT ], wherein ω OA represents: control parameters for controlling the end point of the mechanical arm from point O to point a, ω AP denotes: the control parameter is used for controlling the tail end point of the mechanical arm from the point A to the point P; omega PB represents: control parameters for controlling the tail end point of the mechanical arm from the point P to the point B; omega BT represents: control parameters for controlling the end point of the robot arm from point B to point T are shown in fig. 5.
S21, calculating the branch number K i of the ith preset path point position:
1) For example, the branch number of point a is calculated, specifically:
3 first paths including the point A are respectively the first path theta 1, the second path theta 2 and the first third path theta 3, and in the first path theta 1, the first path branches directly reaching the point A are O point-A point; in the second first path θ 2, the first path branches directly reaching the point a are O-point a, and in the third first path θ 3, the first path branches directly reaching the point a are O-point a, and since the three first path branches are the same, the total number of the first path branches directly reaching the point a is determined to be 1, namely, the point O-point a;
In the first path, a second path directly starting from the point A is branched into the point A-E; in the second first path, the second path directly from the point A is branched into the point A to the point B; in the third first path, a second path directly starting from the point A is branched into the point A-P; determining that the total number of branches of the second path directly from the point A is 3, namely, the point A-E, the point A-B and the point A-P, and calculating the branch number of the point A by a first formula as follows: 1×3=3;
1) For example, the branch number of point B is calculated, specifically:
All the first paths including the point B have 2 paths, namely the second first path θ 2 and the first third path θ 3, in the second first path θ 1, the first paths directly reaching the point B branch into the point a→the point B, in the third first path θ 3, the first paths directly reaching the point B branch into the point p→the point B, and then the total number of the first paths directly reaching the point B is determined to be 2, and the total number of the first paths directly reaching the point B is determined to be respectively: point a-point B and point P-point B;
In the second first path, the second path directly from the point B is branched into the point B-T; in the third first path, a second path directly starting from the point B is branched into the point B-T; since the two second path branches are identical, determining that the total number of the second path branches directly from the point B is 1, and calculating the branch number of the point B by the first formula is as follows: 2×1=2;
3) For example, the branch number of the P point is calculated, specifically:
All first paths including the P-th point have 1: in the third path θ 3, the first path branches directly reaching the point P are determined to be the point a→the point P, and the total number of the first path branches directly reaching the point B is determined to be 1, namely the point a→the point P;
In the third first path, a second path directly starting from the point P is branched into the point P-T; the total number of branches of the second path directly from the point P is determined to be 1, and the branch number of the point P is calculated by a first formula to be: 1×1=1;
S22, determining a movement scene of the middle mechanical arm, and specifically:
1) Adding virtual preset path point positions corresponding to the point A, wherein the number of the virtual preset path point positions is 3-1=2, and the virtual preset path point positions are respectively marked as A1 point and A2 point;
2) Adding virtual preset path point positions corresponding to the point B, wherein the number of the virtual preset path point positions is 2-1=1, and the virtual preset path point positions are marked as the point B1;
3) And adding virtual preset path point positions corresponding to the P points, wherein the number of the virtual preset path point positions is 1-1=0, namely, the virtual preset path point positions corresponding to the P points are not added.
The position parameters and the gesture parameters of the K i -1 virtual preset path point positions corresponding to the ith preset path point position are the same as those of the ith preset path point position;
Then, the ith preset path point position in the K i first paths including the ith preset path point position is replaced in a one-to-one correspondence mode, and the obtained result is: θ 1＝[O,A,E],θ2＝[O,A1,B,E],θ3 = [ O, A2, P, B1, T ], performing backtracking processing on the initial mechanical arm motion scene according to the updated "θ 1＝[O,A,E],θ2＝[O,A1,B,E],θ3 = [ O, A2, P, B1, T ]" to obtain an intermediate mechanical arm motion scene, as shown in fig. 6;
Since the position parameter and the gesture parameter of the K i -1 virtual preset waypoint positions corresponding to the i preset waypoint position are the same as the position parameter and the gesture parameter of the i preset waypoint position, then: omega OA is the same as omega OA1、ωOA2, omega A2P is the same as omega AP, omega PB1 is the same as omega PB, and omega B1T is the same as omega BT, wherein omega OA1 represents: control parameters for controlling the end point of the mechanical arm from the O point to the A1 point, ω OA2 represents: control parameters for controlling the end point of the mechanical arm from the O point to the A2 point, ω A2P represents: control parameters for controlling the end point of the mechanical arm from the point A2 to the point P, ω PB1 represents: control parameters for controlling the end point of the mechanical arm from point P to point B1, ω B1T represents: control parameters for controlling the tail end point of the mechanical arm from the point B1 to the point T;
S23, establishing an association relation, specifically: in the motion scene of the intermediate mechanical arm, establishing an association relationship between each preset path point position and a corresponding virtual preset path point position, and specifically:
1) And establishing an association relation among the point A, the point A1 and the point A2, wherein the updated theta 1＝[O,A,E],θ2＝[O,A1,B,T],θ3 = [ O, A2, P, B1 and T ], and then:
1) The updated second path branch corresponding to the point A is A-E, the updated second path branch corresponding to the point A1 is A1-B, the updated second path branch corresponding to the point A2 is A2-P, and the second path branches of the point A, the point A1 and the point A2 are determined to be different;
judging that the association relationship between the point A and the point A1 is a half-equivalent relationship, the association relationship between the point A and the point A2 is a half-equivalent relationship, and the association relationship between the point A1 and the point A2 is a half-equivalent relationship;
2) The updated second path branch corresponding to the point B is b→t, and the updated second path branch corresponding to the point B1 is B1→t, and since the point B and the point B1 are identical, it is determined that the second path branches of the point B and the point B1 are different, and therefore the association relationship between the point B and the point B1 is determined to be an equivalent relationship, and an intermediate mechanical arm motion scene after the association relationship is established is obtained, as shown in fig. 7.
S24, determining a linearized mechanical arm motion scene: according to the intermediate mechanical arm motion scene after the association relation is established, carrying out linearization reconstruction on all updated first paths to obtain a linearization mechanical arm motion scene, and specifically:
According to the intermediate robot arm movement scene after the association relationship is established shown in fig. 7, since the point A, A and the point A2 are in half-equivalent relationship and the point B, B is in full-equivalent relationship, it is known that the points A1, A2 and B1 can all be reached through the safety path. Adding a state backtracking process from the point E to the point A1 and from the point B to the point A2, and simplifying the positions corresponding to the full equivalent relation, namely carrying out linearization reconstruction on all updated first paths to obtain a linearization mechanical arm movement scene, as shown in fig. 8;
s25, path planning:
calculating a virtual motion path of the mechanical arm and a motion strategy corresponding to the virtual motion path according to the linear mechanical arm motion scene unfolding path planning calculation; virtual motion path to start position to last target position in the linearized robot arm motion scene, then:
The virtual motion path θ from O point to T point is obtained from fig. 8 as: o- & gt A- & gt E- & gt A1- & gt B- & gt A2- & gt P- & gt B- & gt T, marked as theta= [ O, A, E, A1, B, A2, P, B, T ], a motion strategy omega corresponding to a virtual motion path can be planned at one time according to the virtual motion path, omega= [ omega OA,ωAE,ωEA1,ωA1B,ωBA2,ωA2P,ωPB,ωBT ], wherein omega OA represents a control parameter for controlling the tail end point of the mechanical arm from O point to A point, omega AE represents a control parameter for controlling the tail end point of the mechanical arm from A point to E point, omega EA1 represents a control parameter for controlling the tail end point of the mechanical arm from E point to A1 point, omega A1B represents a control parameter for controlling the tail end point of the mechanical arm from A1 point to B point, omega BA2 represents a control parameter for controlling the tail end point of the mechanical arm from B point to A2 point, omega A2P represents a control parameter for controlling the tail end point of the mechanical arm from A2 point to P point, omega PB represents a control parameter for controlling the tail end point of the mechanical arm from P point to B point, omega BT represents a control parameter for controlling the tail end point of the mechanical arm from E point to A point, omega A1B represents a control parameter for controlling the mechanical arm from E point to A1 point, omega 3725 and omega 3749 represents a control parameter for controlling the tail end point from B point to A2 point of the mechanical arm, omega 3723 and omega 3756 represents a motion strategy is equivalent to omega 3723.
S26, acquiring an all-state motion strategy according to a virtual motion path of the mechanical arm and a motion strategy corresponding to the virtual motion path, and specifically:
1) Obtaining control parameters for controlling the mechanical arm from the point O to the point E, according to the conditions that θ= [ O, A, E, A1, B, A2, P, B, T ] and Ω= [ ω OA,ωAE,ωEA1,ωAB,ωBA2,ωAP,ωPB,ωBT ] known, by executing ω OA,ωAE in sequence, the mechanical arm can be controlled from the point O to the point E, and therefore, the corresponding first motion strategy is: [ omega OA,ωAE ], the motion path is O point-A point-E point;
2) Obtaining control parameters for controlling the mechanical arm from the O point to the T point, wherein according to the conditions that θ= [ O, A, E, A1, B, A2, P, B, T ] and Ω= [ omega OA,ωAE,ωEA1,ωAB,ωBA2,ωAP,ωPB,ωBT ], the mechanical arm can be controlled from the O point to the T point by sequentially executing ω OA、ωAB and ω BT, so that the corresponding second motion strategy is [ omega OA,ωAB,ωBT ], and the motion path is O point, A point, B point and E point;
Moreover, as can be seen from θ= [ O, a, E, A1, B, A2, P, B, T ] and Ω= [ ω OA,ωAE,ωEA1,ωAB,ωBA2,ωAP,ωPB,ωBT ], by sequentially executing ω OA、ωAP、ωPB,ωBT and ω BT, the control of the mechanical arm from the O point to the T point can also be achieved, and the corresponding third motion strategy is [ ω OA,ωAP,ωPB,ωBT ], and the corresponding motion path is: o point → a point → P point → B point → E point.
When a user needs to pass the mechanical arm from the point O to the point E through the point A, the first motion strategy is a full-state motion strategy, the mechanical arm is controlled according to the first motion strategy, and the mechanical arm can be controlled by using the second motion strategy and the third motion strategy as the full-state motion strategy;
according to the three specific motion strategies, the control of the tail end point of the mechanical arm is realized, in the existing path planning mode, operations such as omega OA, omega AE and the like are required to be repeatedly carried out when the path is calculated once, and in the application, the starting position can be planned to the last target position in the linearized mechanical arm motion scene at one time through the linearized mechanical arm motion scene obtained through linearization reconstruction, and then different control parameters are selected according to the requirements so as to control the mechanical arm.
In the application, a backtracking state of a virtual point bearing mechanical arm is constructed aiming at a mechanical arm multi-branch motion scene in a target point control mode, a concept of equivalent starting points and equivalent target points is introduced, the mechanical arm multi-branch motion scene is reconstructed through equivalent processing, and mechanical arm multi-branch motion behaviors are longitudinally decomposed into a plurality of single-branch motion behaviors to form a plurality of single-branch motion strategies.
And carrying out linearization construction on the mechanical arm multi-branch motion scene after equivalent construction in a fusion state backtracking process to obtain a set of virtual motion paths theta and a set of motion strategies omega of the mechanical arm after linearization construction, and optimizing the motion paths and the motion strategy sets based on an equivalent relation.
After the linearization construction, the planner expands planning calculation according to the motion path and the motion strategy set, and then classifies and outputs corresponding motion strategies according to the actual motion path branches.
Wherein, the motion behavior based on the setting of virtual points and the state backtracking process is decomposed. And traversing the next path possibly reached by the mechanical arm at each path point to the target point, longitudinally disassembling multiple branches of the mechanical arm motion into multiple single branch processes according to the method, and analyzing the motion path and motion strategy of each single branch process of the mechanical arm. On the basis, corresponding virtual points are set, and on the path points with the branch number of K, the virtual points with the number of K-1 are added and used for bearing the backtracking state of the mechanical arm, so that the mechanical arm movement scene based on the virtual points is constructed.
And carrying out equivalent treatment on the mechanical arm motion scene remodeled by the virtual point to obtain an equivalent structure of the mechanical arm multi-branch motion scene.
In the scene of multi-branch motion of the mechanical arm with equivalent structure, the state backtracking process is added according to the motion of the decomposed mechanical arm. And then, simplifying the equivalent relationship to obtain a linearization relationship scene structure of the multi-branch motion of the mechanical arm.
And under the mechanical arm motion linearization control mode, obtaining a mechanical arm virtual motion path and a motion control strategy set, and completing calculation in a centralized way through one-time planning. The actual mechanical arm movement path branch control strategies are contained in the calculation aggregate, and the planning results of the branch movement control strategies are output by the actual movement path classification.
The invention provides a linearization programming method for a multi-branch motion control strategy of a mechanical arm of a space detection task by analyzing the multi-branch motion scene of the mechanical arm in the space detection task. According to the method, the multi-branch motion scene of the mechanical arm is analyzed, the state backtracking is used as a core processing method, the equivalent concept is introduced to simplify the processing, and the multi-branch motion behavior planning method of the mechanical arm is deeply optimized. The method greatly reduces the problem of repeated planning, effectively improves the efficiency of strategy planning, provides favorable conditions for verification and implementation of planning strategies, effectively optimizes the generation mode of the mechanical arm motion control strategy, and has higher engineering application value for planning and verification of complex multi-branch motions of the mechanical arm. The method can be practically applied to strategy planning and verification of multi-branch movement behaviors of the mechanical arm in deep space exploration and manned aerospace tasks.
The solution idea of the invention is as follows: virtual points for bearing the back trace state of the mechanical arm are introduced, the motion behaviors of the multi-branch mechanical arm are subjected to linearization treatment in a mode of decomposition, equivalence, back trace and the like, a mechanical arm motion field Jing Jian with branches is used as a linear motion control scene with consistent control logic, and the complex multi-branch motion path control strategy planning of the extraterrestrial celestial body sampling detection mechanical arm is optimized.
The method for linearising the multi-branch movement behavior of the detecting mechanical arm based on the extraterrestrial celestial body sampling of the virtual point state backtracking comprises the following steps:
s30, decomposing multi-branch motions, and setting a simple typical mechanical arm multi-branch motion scene as shown in FIG. 2 to obtain an initial mechanical arm motion scene;
As can be seen from fig. 2, the mechanical arm starts to move from the O point, the mechanical arm can select a predetermined movement path in the drawing, and the multi-branch movement of the mechanical arm is disassembled into three first paths according to the path point, as shown in fig. 3, fig. 4 and fig. 5, respectively, and the specific analysis of each first path is referred to above, which is not repeated herein;
S31, setting virtual points: in fig. 2, point a is taken as a starting point, i.e. a starting position, and 3 different movement target points, i.e. preset path point positions, E, B, P are selected according to different constraints, so as to form a target point 3 branch movement strategy, wherein the branch number K out is 3;
Point B is taken as the target point and can be reached by 2 different motion start points A, P, thereby forming a start point 2 branch motion strategy, the branch number K in of which is 2.
Adding virtual points with the set number of K-1 on the path point with the branch number of K, and adding virtual points A1 and A2 based on the branch number of K out of the point A, wherein the positions and the postures of the virtual points are the same as those of the point A; based on the branch number K in of the point B, the virtual point B1 is added, and the position and the gesture are the same as those of the point B.
S32, state backtracking: and in the typical multi-branch movement scene of the mechanical arm, after the mechanical arm moves from the point A to the point E, setting a virtual point of the next movement, and moving from the virtual point as a starting point to the point B, wherein the virtual point is a bearing object for carrying out state backtracking on the mechanical arm, and is set as A1, and other virtual point setting modes are the same as the state backtracking mode.
When the state of the mechanical arm is backtracked, the motion variable can be simplified, and only the position, the gesture, the safety and the like of the virtual point are considered. Obtaining a movement scene of the middle mechanical arm shown in fig. 6;
s33, establishing an equivalence point concept: since the states of position, posture, safety, accessibility, etc. are the same when the target point control modes A, A, A2 are adopted as the starting points, but the state parameters of the target points E, B, P are different, A, A, A2 are equivalent as the starting points, i.e., half equivalent.
B. When B1 is used as a starting point, the states of position, posture, safety, accessibility and the like are the same, and the state parameters of the target point T are the same, so B, B is full equivalent.
Reconstructing the motion scene of the middle mechanical arm shown in fig. 6 through equivalent processing to obtain the motion scene of the middle mechanical arm with the association relation established as shown in fig. 7;
S34, backtracking the linearization state of the equivalent reconstruction scene:
based on the mechanical arm multi-branch motion scene reconstructed by the equivalence relation shown in fig. 7, since the points A, A and A2 are equivalent in starting point and the point B, B is full equivalent, the points A1, A2 and B1 can all be reached through the safe path.
The state backtracking process is added from the point E to the point A1 and from the point B to the point A2, and the full equivalent points are simplified, so that the multi-branch motion scene of the mechanical arm can be linearly reconstructed into the linear motion scene of the mechanical arm shown in fig. 8;
S35, generating a multi-branch motion linearization construction control strategy:
According to fig. 8, in this type of control mode, the linearized virtual motion path θ= [ O, a, E, A1, B, A2, P, B, T ], motion strategy Ω= [ ω OA,ωAE,ωEA1,ωA1B,ωBA2,ωA2P,ωPB,ωBT ].
Since A, A1 and A2 are equivalent as starting points when the multi-branch motion of the mechanical arm is in a linearization structure, the motion strategy Ω= [ ω OA,ωAE,ωEA1,ωAB,ωBA2,ωAP,ωPB,ωBT ] is controlled by the parameter ω A1B＝ωAB,ωA2P＝ωAP.
Consider 3 actual motion paths theta 1,θ2,θ3 before linearization construction, corresponding motion control strategies
S36, planning a multi-branch motion strategy of the mechanical arm after linearization construction. After the linearization construction, when planning the multi-branch motion scene cases of the typical mechanical arm, the planner carries out planning calculation of the motion control strategy omega according to the linearized virtual motion path theta of the mechanical arm.
And according to the 3 actual motion paths theta 1,θ2,θ3, classifying and outputting the corresponding motion strategies omega 1,Ω2,Ω3, and completing the planning of each branch motion strategy through one planning process.
The beneficial effects of the invention are as follows:
1) The method realizes the decomposition of the complex multi-branch motion of the extraterrestrial celestial body sampling and detecting mechanical arm, so as to retrieve the equivalence relation and carry out the state backtracking linearization multi-branch motion model, thereby greatly improving the planning efficiency.
2) The simplification of strategy planning verification mode under the complex multi-branch motion scene of the extraterrestrial celestial body sampling and detecting mechanical arm is realized.
3) The optimization of the control strategy under the complex motion scene of the extraterrestrial celestial body sampling and detecting mechanical arm is realized.
The invention realizes planning and verification of the multi-branch motion strategy of the extraterrestrial celestial body sampling detection mechanical arm, improves the path planning and verification efficiency, optimizes the multi-branch motion behavior control strategy of the mechanical arm, and saves planning and verification resources.
In another embodiment, the method comprises:
s40, longitudinally decomposing multi-branch movement of the mechanical arm before the teleoperation task of the extraterrestrial celestial body sampling detection mechanical arm begins;
s41, calculating the number of branches corresponding to the movement path points of the mechanical arm, and adding virtual points with the number of K-1 on the path points with the number of branches of K.
S42, backtracking the state of the mechanical arm, loading the state of the backtracking mechanical arm on the virtual point, simplifying the backtracking motion variable, and considering only the position, the gesture, the safety and the like of the virtual point.
S43, introducing an equivalence point concept, and analyzing the half equivalence and full equivalence relation of the path point through the motion control parameters.
S44, simplifying the multi-branch motion scene of the mechanical arm traced back through the virtual point, and simplifying the control mode on the basis of clear equivalence relation. Reconstructing the multi-branch motion scene of the mechanical arm through an equivalence relation.
S45, adding a state backtracking process to the equivalent reconstructed mechanical arm motion scene, and carrying out linearization construction on the mechanical arm multi-branch motion scene.
And S46, in the mechanical arm movement scene with the linearization structure, the planner calculates the virtual movement path theta and the movement strategy omega set of the mechanical arm according to the unfolding planning calculation of the multi-branch movement path of the mechanical arm after the linearization structure.
S47, according to the actual motion path branches, corresponding motion strategies are classified and output.
The invention provides a linearization programming method for a multi-branch motion control strategy of a mechanical arm of a space detection task by analyzing the multi-branch motion scene of the mechanical arm in the space detection task. According to the method, the multi-branch motion scene of the mechanical arm is analyzed, the state backtracking is used as a core processing method, the equivalent concept is introduced to simplify the processing, and the multi-branch motion behavior planning method of the mechanical arm is deeply optimized. The method greatly reduces the problem of repeated planning, effectively improves the efficiency of strategy planning, provides favorable conditions for verification and implementation of planning strategies, effectively optimizes the generation mode of the mechanical arm motion control strategy, and has higher engineering application value for planning and verification of complex multi-branch motions of the mechanical arm. The method can be practically applied to strategy planning and verification of multi-branch movement behaviors of the mechanical arm in deep space exploration and manned aerospace tasks.
In the above embodiments, although steps S1, S2, etc. are numbered, only specific embodiments of the present application are given, and those skilled in the art may adjust the execution sequence of S1, S2, etc. according to the actual situation, which is also within the scope of the present application, and it is understood that some embodiments may include some or all of the above embodiments.
As shown in fig. 9, a robot arm motion planning system 200 based on virtual point state backtracking according to an embodiment of the present invention includes a scene preprocessing module 210, a calculation backtracking module 220, an association module 230, a linearization reconstruction module 240, a path planning module 250 and a control module 260;
the scene preprocessing module 210 is configured to: determining an initial mechanical arm motion scene, the initial mechanical arm motion scene comprising: the system comprises a starting position, at least one preset path point position and at least one target position, and a first path from the starting position to each target position, wherein the at least one first path comprises the at least one preset path point position;
the calculation backtracking module 220 is configured to: calculating the branch number K i of the ith preset path point position, adding K i -1 virtual preset path point positions corresponding to the ith preset path point position in the initial mechanical arm motion scene, and carrying out one-to-one correspondence replacement on the ith preset path point position in K i first paths comprising the ith preset path point position until each first path is replaced, and carrying out backtracking processing on the initial mechanical arm motion scene to obtain an intermediate mechanical arm motion scene, wherein i is a positive integer;
The association module 230 is configured to: establishing an association relationship between each preset path point position and a corresponding virtual preset path point position in the middle mechanical arm movement scene;
the linearization reconstruction module 240 is configured to: according to the intermediate mechanical arm motion scene after the association relation is established, carrying out linearization reconstruction on all updated first paths to obtain a linearization mechanical arm motion scene;
The path planning module 250 is configured to: calculating a virtual motion path of the mechanical arm and a motion strategy corresponding to the virtual motion path according to the linear mechanical arm motion scene unfolding path planning calculation;
the control module 260 is configured to:
calculating a virtual motion path of the mechanical arm and a motion strategy corresponding to the virtual motion path according to the linear mechanical arm motion scene unfolding path planning calculation;
and acquiring an all-state motion strategy according to the virtual motion path of the mechanical arm and the motion strategy corresponding to the virtual motion path, and controlling the mechanical arm according to the actual motion requirement and the all-state motion strategy.
Obtaining an intermediate mechanical arm motion scene according to an initial mechanical arm motion scene, establishing an association relation between each preset path point position and a corresponding virtual preset path point position in the initial mechanical arm motion scene, carrying out linearization reconstruction on all updated first paths according to the intermediate mechanical arm motion scene after the association relation is established, calculating virtual motion paths of the mechanical arm and motion strategies corresponding to the virtual motion paths according to the linearization mechanical arm motion scene, further obtaining an all-state motion strategy, realizing control of the mechanical arm, avoiding repeated planning, reducing repeated calculation amount and greatly improving path planning efficiency of the mechanical arm.
Preferably, in the above technical solution, the calculation backtracking module 220 is specifically configured to:
Calculating the branch number K i of the ith preset path point position according to a first formula, wherein the first formula is as follows: k i＝(Kin)i×(Kout)i,(Kin)i represents: the total number of first path branches directly reaching the ith preset waypoint position obtained from all first paths including the ith preset waypoint position, (K out)i represents the total number of second path branches directly starting from the ith preset waypoint position obtained from all paths including the ith preset waypoint position).
Preferably, in the above technical solution, the association relationship includes a half equivalent relationship and a full equivalent relationship, where the full equivalent relationship represents: the second path branches after updating of any two positions in the ith preset path point position and the corresponding K i -1 virtual preset path point positions are the same, and the half-equivalence relation represents: the i-th preset path point position and any two positions in the corresponding K i -1 virtual preset path point positions are respectively updated, and at least one of the updated second path branches is different.
The steps for implementing the corresponding functions by the parameters and the unit modules in the robot motion planning system 200 based on virtual point state backtracking according to the present invention can refer to the parameters and the steps in the embodiment of the robot motion planning method based on virtual point state backtracking according to the present invention, which are not described herein.
The storage medium of the embodiment of the invention stores instructions, and when a computer reads the instructions, the computer is caused to execute the mechanical arm motion planning method based on virtual point state backtracking.
An electronic device of the present invention includes a processor and the storage medium described above, where the processor executes instructions in the storage medium. Wherein, the electronic equipment can be selected from computers, mobile phones and the like.
Those skilled in the art will appreciate that the present invention may be implemented as a system, method, or computer program product.
Accordingly, the present disclosure may be embodied in the following forms, namely: either entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or entirely software, or a combination of hardware and software, referred to herein generally as a "circuit," module "or" system. Furthermore, in some embodiments, the invention may also be embodied in the form of a computer program product in one or more computer-readable media, which contain computer-readable program code.
Any combination of one or more computer readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.

Claims (2)

1. A mechanical arm motion planning method based on virtual point state backtracking is characterized by comprising the following steps:
determining an initial mechanical arm motion scene, the initial mechanical arm motion scene comprising: the system comprises a starting position, at least one preset path point position and at least one target position, and a first path from the starting position to each target position, wherein the at least one first path comprises the at least one preset path point position;
Calculating the branch number K i of the ith preset path point position, adding K i -1 virtual preset path point positions corresponding to the ith preset path point position in the initial mechanical arm motion scene, and carrying out one-to-one correspondence replacement on the ith preset path point position in K i first paths comprising the ith preset path point position until each first path is replaced, and carrying out backtracking processing on the initial mechanical arm motion scene to obtain an intermediate mechanical arm motion scene, wherein i is a positive integer;
establishing an association relationship between each preset path point position and a corresponding virtual preset path point position in the middle mechanical arm movement scene;
according to the intermediate mechanical arm motion scene after the association relation is established, carrying out linearization reconstruction on all updated first paths to obtain a linearization mechanical arm motion scene;
calculating a virtual motion path of the mechanical arm and a motion strategy corresponding to the virtual motion path according to the linear mechanical arm motion scene unfolding path planning calculation;
Acquiring an all-state motion strategy according to a virtual motion path of the mechanical arm and a motion strategy corresponding to the virtual motion path, and controlling the mechanical arm according to actual motion requirements and the all-state motion strategy;
The calculating the branch number K i of the i-th preset path point position includes:
Calculating the branch number K i of the ith preset path point position according to a first formula, wherein the first formula is as follows: k i＝(Kin)i×(Kout)i,(Kin)i represents: the total number of first path branches directly reaching the ith preset waypoint position obtained from all first paths including the ith preset waypoint position, (K out)i represents the total number of second path branches directly starting from the ith preset waypoint position obtained from all paths including the ith preset waypoint position;
The association relationship comprises a half equivalent relationship and a full equivalent relationship, and the full equivalent relationship represents: the second path branches after updating of any two positions in the ith preset path point position and the corresponding K i -1 virtual preset path point positions are the same, and the half-equivalence relation represents: the i-th preset path point position and any two positions in the corresponding K i -1 virtual preset path point positions are respectively updated, and at least one of the updated second path branches is different.
2. The mechanical arm motion planning system based on virtual point state backtracking is characterized by comprising a scene preprocessing module, a calculation backtracking module, an association module, a linearization reconstruction module, a path planning module and a control module;
The scene preprocessing module is used for: determining an initial mechanical arm motion scene, the initial mechanical arm motion scene comprising: the system comprises a starting position, at least one preset path point position and at least one target position, and a first path from the starting position to each target position, wherein the at least one first path comprises the at least one preset path point position;
The calculation backtracking module is used for: calculating the branch number K i of the ith preset path point position, adding K i -1 virtual preset path point positions corresponding to the ith preset path point position in the initial mechanical arm motion scene, and carrying out one-to-one correspondence replacement on the ith preset path point position in K i first paths comprising the ith preset path point position until each first path is replaced, and carrying out backtracking processing on the initial mechanical arm motion scene to obtain an intermediate mechanical arm motion scene, wherein i is a positive integer;
The association module is used for: establishing an association relationship between each preset path point position and a corresponding virtual preset path point position in the middle mechanical arm movement scene;
The linearization reconstruction module is used for: according to the intermediate mechanical arm motion scene after the association relation is established, carrying out linearization reconstruction on all updated first paths to obtain a linearization mechanical arm motion scene;
the path planning module is used for: calculating a virtual motion path of the mechanical arm and a motion strategy corresponding to the virtual motion path according to the linear mechanical arm motion scene unfolding path planning calculation;
The control module is used for: calculating a virtual motion path of the mechanical arm and a motion strategy corresponding to the virtual motion path according to the linear mechanical arm motion scene unfolding path planning calculation;
Acquiring an all-state motion strategy according to a virtual motion path of the mechanical arm and a motion strategy corresponding to the virtual motion path, and controlling the mechanical arm according to actual motion requirements and the all-state motion strategy;
the calculation backtracking module is specifically configured to:
Calculating the branch number K i of the ith preset path point position according to a first formula, wherein the first formula is as follows: k i＝(Kin)i×(Kout)i,(Kin)i represents: the total number of first path branches directly reaching the ith preset waypoint position obtained from all first paths including the ith preset waypoint position, (K out)i represents the total number of second path branches directly starting from the ith preset waypoint position obtained from all paths including the ith preset waypoint position;
The association relationship comprises a half equivalent relationship and a full equivalent relationship, and the full equivalent relationship represents: the second path branches after updating of any two positions in the ith preset path point position and the corresponding K i -1 virtual preset path point positions are the same, and the half-equivalence relation represents: the i-th preset path point position and any two positions in the corresponding K i -1 virtual preset path point positions are respectively updated, and at least one of the updated second path branches is different.
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