CN114643581A - Double-mechanical-arm collision-prevention track planning method and system based on improved artificial potential field method - Google Patents
Double-mechanical-arm collision-prevention track planning method and system based on improved artificial potential field method Download PDFInfo
- Publication number
- CN114643581A CN114643581A CN202210415041.1A CN202210415041A CN114643581A CN 114643581 A CN114643581 A CN 114643581A CN 202210415041 A CN202210415041 A CN 202210415041A CN 114643581 A CN114643581 A CN 114643581A
- Authority
- CN
- China
- Prior art keywords
- mechanical
- potential field
- arm
- mechanical arms
- collision
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 102
- 238000001514 detection method Methods 0.000 claims description 11
- 238000011217 control strategy Methods 0.000 claims description 10
- 230000008859 change Effects 0.000 abstract description 5
- 230000010355 oscillation Effects 0.000 abstract description 5
- 238000004364 calculation method Methods 0.000 abstract description 3
- 230000004048 modification Effects 0.000 abstract description 3
- 238000012986 modification Methods 0.000 abstract description 3
- 238000004422 calculation algorithm Methods 0.000 abstract description 2
- 239000012636 effector Substances 0.000 description 11
- 230000009471 action Effects 0.000 description 10
- 230000001133 acceleration Effects 0.000 description 5
- 239000000463 material Substances 0.000 description 4
- 230000007547 defect Effects 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 230000002265 prevention Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000003466 welding Methods 0.000 description 1
Images
Classifications
-
- 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
- B25J9/1666—Avoiding collision or forbidden zones
Landscapes
- Engineering & Computer Science (AREA)
- Robotics (AREA)
- Mechanical Engineering (AREA)
- Manipulator (AREA)
Abstract
The invention discloses a double-mechanical-arm collision avoidance trajectory planning method and system based on an improved artificial potential field method, which improves the artificial potential field method: in the improved artificial potential field method, the potential field force is directly related to the joint speed of the mechanical arm. The change not only reduces the calculation amount of the algorithm, but also solves the problem of the oscillation of the mechanical arm at the target. A threshold distance is set in a gravitational field function in the artificial potential field method, and when the distance between the mechanical arm and the target point is larger than the threshold distance, the gravitational force is not increased any more, but is equal to a constant. This modification avoids the robot arm being subjected to excessive gravitational forces when it is relatively far from the target point.
Description
Technical Field
The invention relates to the technical field of trajectory planning, in particular to a method and a system for planning a collision-prevention trajectory of double mechanical arms by using an improved artificial potential field method.
Background
The double-mechanical arm system has higher flexibility and higher working efficiency than a single mechanical arm. Currently, the double-mechanical-arm system is applied to various industrial occasions, such as carrying, loading, assembling, welding and the like. However, the two robot arm systems often share the same working space, so that the two robot arms need to be coordinately controlled to avoid collision between the robot arms. The coordination control strategies of the double-mechanical-arm system mainly comprise master/slave coordination control, hybrid position/force control, dynamic coordination control and the like. Wherein the master/slave coordination control is most suitable to be combined with the collision-prevention track planning of the double-mechanical arm system. The principle of the robot is that two mechanical arms are respectively set as a master mechanical arm and a slave mechanical arm, and the slave mechanical arm avoids collision with the master mechanical arm in the modes of time delay action, speed change, working range limitation and the like. The scholars also put forward methods of adopting time scheduling, B spline interpolation to locally change the track of the mechanical arm, adopting heuristic rules to generate the track of the mechanical arm and the like for the two mechanical arms. However, many existing methods affect the working efficiency of the mechanical arm, and some methods are complex in calculation and long in solving time, so that the coordination movement and collision avoidance trajectory planning of the two mechanical arms are not facilitated.
The principle of the traditional artificial potential field method (TAPF) is to establish a virtual artificial potential field in a motion space of two mechanical arms, wherein the virtual artificial potential field consists of a gravitational field and a repulsive force field. The gravitational field is set at the target point and the repulsive field is set at the obstacle. The mechanical arm avoids the obstacle under the action of the repulsive field and reaches the target point of the track under the action of the gravitational field. However, this method has some problems in that the potential field force in the conventional artificial potential field method is related to the joint acceleration of the robot arm, which causes the robot arm to have an acceleration of 0 but still have a velocity when reaching the target point, thereby causing the robot arm to oscillate near the target point. In addition, the magnitude of the attractive force in the conventional manual potential field method is proportional to the distance from the mechanical arm to the attractive force field, and when the mechanical arm is far away from the target point, the potential field attractive force is large, which may cause the two mechanical arms to collide.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a double-mechanical-arm collision-prevention track planning method based on an improved artificial potential field method, which is simple and convenient to calculate, high in solving speed, higher in safety and capable of generating the motion track of a double-mechanical-arm system in advance through offline planning.
In order to achieve the purpose, the invention is realized by the following technical scheme:
in a first aspect, the invention provides a double-mechanical-arm collision avoidance trajectory planning method based on an improved artificial potential field method, which comprises the following steps:
step 1: making a control strategy of the two mechanical arms, and setting the priority of the two mechanical arms;
step 2: acquiring size data of the mechanical arms, and establishing three-dimensional models and kinematic models of the two mechanical arms according to the acquired size data;
and step 3: establishing a collision detection model of the double mechanical arms according to the three-dimensional model and the kinematics model;
and 4, step 4: determining all passing points of the working paths of the two mechanical arms, including a starting point, a first intermediate point, a second intermediate point and a target point, and finishing interpolation fitting among all the passing points to obtain complete initial tracks of the two mechanical arms;
and 5: the method comprises the steps that a collision model is used for detecting an initial track in an off-line mode, when a collision risk is detected between two mechanical arms, a manual potential field method is improved to start acting and modify the initial track of the slave mechanical arms, a virtual gravitational field and a repulsive force field are generated in a working space of a double-mechanical-arm system by the manual potential field method, the gravitational field is arranged at a target point of the slave mechanical arms, a threshold value distance is set in a gravitational field function, and the repulsive force field is arranged at each joint of the master mechanical arm; the modified trajectory is obtained by improving the artificial potential field method.
As a further technical scheme, the master/slave coordination control is used as a control strategy of the double mechanical arms.
As a further technical scheme, in the step 2, measuring size data of the mechanical arm, and establishing a three-dimensional model of the mechanical arm by using software according to the obtained size data; and calculating the size data to obtain a D-H parameter table of the mechanical arm, and establishing a kinematic model and a URDF file of the double-mechanical-arm system according to a standard D-H parameter method.
As a further technical solution, the collision detection model in step 3 may determine whether there is a collision risk between the two mechanical arms by calculating the distance from the mechanical arm to the main mechanical arm off-line.
As a further technical scheme, in the step 4, a straight line interpolation function is adopted to fit the distance from the starting point to the first intermediate point and the distance from the second intermediate point to the terminal point, and a cubic polynomial interpolation function is adopted to fit the track from the first intermediate point to the second intermediate point.
In a second aspect, the present invention further provides a system for planning collision avoidance trajectories of two robots based on an improved artificial potential field method, including:
a first module: the control strategy of the two mechanical arms is formulated, and the priority of the two mechanical arms is set;
and a second module: the robot arm three-dimensional modeling system is configured to acquire size data of the robot arm, and establish a three-dimensional model and a kinematic model of two robot arms according to the acquired size data;
and a third module: configured to build a collision detection model of the two robots from the three-dimensional model and the kinematics model;
and a module IV: the method comprises the steps that all passing points of a working path of the two mechanical arms are determined, wherein the passing points comprise a starting point, a first intermediate point, a second intermediate point and a target point, interpolation fitting between all the passing points is completed, and complete initial tracks of the two mechanical arms are obtained;
and a fifth module: the system comprises a collision model, an improved manual potential field method, a virtual gravitational field and a repulsive force field, wherein the collision model is used for detecting an initial track in an off-line manner, when a collision risk exists between two mechanical arms, the improved manual potential field method starts to act and modifies the initial track of the slave mechanical arms, the improved manual potential field method generates the virtual gravitational field and the repulsive force field in a working space of a double-mechanical-arm system, the gravitational field is arranged at a target point of the slave mechanical arms and a threshold value distance is set in a gravitational field function, and the repulsive force field is arranged at each joint of the master mechanical arms; the modified trajectory is obtained by improving the artificial potential field method.
As a further technical solution, in the module one, master/slave coordination control is used as a control strategy of the double robots.
As a further technical solution, the second module is configured to measure dimensional data of the mechanical arm, and establish a three-dimensional model of the mechanical arm using software according to the obtained dimensional data; and calculating the size data to obtain a D-H parameter table of the mechanical arm, and establishing a kinematic model and a URDF file of the double-mechanical-arm system according to a standard D-H parameter method.
As a further technical solution, the collision detection model is configured to determine whether the two arms have a collision risk by calculating the distance from the arm to the master arm offline.
As a further technical solution, the module four is configured to adopt a linear interpolation function to fit the distance from the starting point to the first intermediate point and the distance from the second intermediate point to the end point, and adopt a cubic polynomial interpolation function to fit the track from the first intermediate point to the second intermediate point.
The beneficial effects of the above-mentioned embodiment of the present invention are as follows:
the invention provides a double-mechanical-arm collision avoidance trajectory planning method based on an improved artificial potential field method. Firstly, the method provides a collision detection model, the track of the mechanical arm is modified locally after collision is detected so as to realize collision prevention, and compared with a collision prevention method for modifying the track globally, the method reduces the influence on the working efficiency of the two mechanical arms. Secondly, the method improves the artificial potential field method, solves the problems of overlarge attraction and terminal oscillation in the artificial potential field method, and reduces the calculated amount. Finally, simulation test is carried out on the method, and the result shows that the method is high in convergence and solving speed, and under the action of the method, the two mechanical arms always keep a safe distance in the moving process.
In the improved artificial potential field method, the potential field force is directly related to the joint speed of the mechanical arm. The change not only reduces the calculation amount of the algorithm, but also solves the problem of the oscillation of the mechanical arm at the target; a threshold distance is set in a gravitational field function in the artificial potential field method, and when the distance between a mechanical arm and the gravitational field is larger than the threshold distance, the gravitational force is not increased any more, but is equal to a constant.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
Fig. 1 is a schematic diagram of an object-gantry two-robot loading system according to this embodiment;
FIG. 2 is a schematic three-dimensional model of the robot arm according to the present embodiment;
FIG. 3 is a D-H parameter table of the robot arm of the present embodiment;
fig. 4, 5, and 6 are position relationships of geometric bodies in the collision detection model according to the present embodiment;
fig. 7 is a collision avoidance trajectory of the dual-robot system of the present embodiment;
fig. 8 shows the distance between the robot arm R1 and the end effector of the robot arm R2 according to the present embodiment.
In the figure: 11 host machine the robot arm, 12 slave robot arm, 13 robot gripper, 14 conveyer belt, 15 vehicle to be loaded, 16 gantry, 21 robot base, 22 robot rotation axis, 23 robot rotation axis, 24 robot rotation axis, 25 robot rotation axis, 26 robot rotation axis, 27 robot rotation axis.
Detailed Description
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an", and/or "the" are intended to include the plural forms as well, unless the invention expressly state otherwise, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof;
as introduced by the background art, the defects in the prior art are that, in order to solve the technical problems, the invention provides a method and a system for planning a collision-prevention track of two mechanical arms based on an improved artificial potential field method.
Example 1
Referring to fig. 1, in this embodiment, the gantry dual-robot loading system shown in fig. 1 is selected as an implementation object of the method of the present invention, and key devices of the gantry dual-robot loading system include a master robot 11, a slave robot 12, a robot gripper 13, a conveyor belt 14, a vehicle to be loaded 15, and a gantry 16; the invention provides a double-mechanical-arm collision avoidance track planning method based on an improved artificial potential field method, which comprises the following steps of:
the method comprises the following steps:
step 1: the two arms are respectively set as a master arm R1 and a slave arm R2 according to a master/slave coordination control principle, and the priority of the master arm is set to be higher than that of the slave arm. When collision risk between the two mechanical arms is detected, the initial track of the master mechanical arm with high priority is not changed, and the collision between the two mechanical arms is avoided by changing the track of the slave mechanical arm with low priority.
Step 2: the model of the mechanical arm selected for use in this example is KUKA KR 270R3100 ultra K. And measuring the size data of the mechanical arm, including the shape and the size of a large arm, a small arm, a rotating shaft and the like. Establishing a three-dimensional model of the mechanical arm in Solidworks software according to the measured dimension data, wherein the three-dimensional model of the mechanical arm refers to a figure 2; D-H parameters of the robot arm are calculated according to the dimensions of the robot arm, and please refer to FIG. 3 for a D-H parameter table. Alpha in FIG. 3iIs the connecting rod torsion angle, piIs the length of the connecting rod, diIs connecting rod torque, θiIs a joint variable, i ═ 1,2, …, 6. And establishing a kinematic model and a URDF file of the mechanical arm according to the D-H parameter table.
And step 3: in order to conveniently analyze the collision problem, the two-mechanical-arm three-dimensional model is simplified into a geometric model. Consider the end effector of the master arm R2 to have a radius RaRegarding the joint of the main robot arm R1 as the radius RbThe link of the master arm R1 is regarded as having a length of lbA cylinder of radius rc. The distances between the end effector of the main mechanical arm R2 and the joint and the connecting rod of the main mechanical arm R1 are respectively [ d1,…,di]And [ d1,…,dj]The distance between the end effector of the main arm R1 and the end effector of the main arm R2 is dk. Referring to fig. 4, 5, and 6, in the drawings, R1J, R1L, and R1E represent a joint region, a link region, and an end effector region of the robot arm R1, respectively, and R2E represents an end effector region of the robot arm R2. And calculating the distances of the two mechanical arms at the same time in the track according to the kinematic model, and determining that the two mechanical arms collide when one of the following conditions in the formula (1) is met.
In the formula ds1,ds2,ds3The minimum safe distance from the end effector of the mechanical arm R2 to the joint, link and end effector of the mechanical arm R1. In this example ds1,ds2,ds3The values of (A) are 0.8m,0.8m,1.28m, respectively.
And 4, step 4: determining all the passing points of the working paths of the two mechanical arms, wherein the passing points comprise a starting point, a first intermediate point, a second intermediate point and a target point. The starting point is located at a material grabbing position at the tail end of the conveyor belt, the first intermediate point is located above the material grabbing position, the second intermediate point is located above a material stacking position of the vehicle to be loaded, and the target point is located at the material stacking position of the vehicle to be loaded. And fitting the distances from the starting point to the first intermediate point and from the second intermediate point to the end point by adopting a straight line interpolation function. And fitting the track from the first intermediate point to the second intermediate point by adopting a cubic polynomial interpolation function.
The interpolation function of the cubic polynomial is shown in formula (2).
In the formula, theta (t),
respectively represent joint angle, joint angular velocity, joint angular acceleration, a0,a1,a2,a3Respectively representing the coefficients of the interpolation function. And finishing interpolation fitting between all the passing points to obtain complete initial tracks of the two mechanical arms.
And 5: and (3) detecting an initial track off line by using a collision model, and when a collision risk between the two mechanical arms is detected, improving the manual potential field method to start acting and modifying the initial track of the mechanical arms. A virtual force field is provided in the joint space of the two robot system, and the virtual force field only acts on the robot R2 to change the trajectory thereof. The gravitational field of the improved artificial potential field method is arranged at the target point of the mechanical arm R2, and the gravitational field function is shown as formula (3):
in the formula, KattIs the coefficient of gravity, ρ (q, q)g) Is a vector whose value is the current position q of the robot arm to the target point qgIn the direction from the robot arm to the target point position, dqIs the distance between the robot arm and the target point, rqIs the critical operating distance, U, of the gravitational fieldkIs a constant. The potential field force function of the gravitational field is shown in equation (4):
in the formula FkIs a constant. The repulsive fields are set at 6 joints of the robot arm R1. According to the traditional manual potential field method, the mechanical arm is subjected to a potential field force Kattρ(q,qg). Since the robot arm R2 is far from the target point just before the collision risk is detected, it is subjected to a large potential force, which requires the robot arm R2 to instantaneously generate a large acceleration, which may damage the robot arm joint. However, the improved artificial potential field method sets a threshold distance r in the gravitational field functionqWhen the distance between the robot arm R2 and the target point is greater than the threshold distance, the potential field force applied to the robot arm is constant FkThe safe operation of the mechanical arm R2 is ensured.
The repulsion field function of the improved artificial potential field method is shown in formula (5):
in the formula KrepIs the coefficient of repulsion, ρ (q, q)o) Is a vector whose value is the current position q of the mechanical arm to the obstacle qoIn the direction from the arm to the position of the obstacle, diIs the distance, R, between the joint of the robot arm R2 and the robot arm R1sIs the critical operating distance of the repulsive field. The potential field force function of the repulsive field is shown in equation (6):
the global potential field is composed of all virtual gravitational field and repulsive force occasions in the working space of the double-mechanical-arm system, and the potential field function is shown as a formula (7):
where U represents the global potential field and n is the number of links of the robot arm. The function of global potential field force is shown in equation (8):
the global potential field force is related to the joint speed of the mechanical arm, which can be obtained by the formula (9-11):
M＝JF T(θ1,θ2,…,θ6)F(9
where M is the joint moment, JFIs a matrix of the jacobian matrix,
is the joint velocity of the robot arm, BJIs the moment of inertia of the mechanical arm joint. If according to the traditional artificial potential field method, the mechanical arm obtains the joint from the global potential field forceSpeed of rotation
This causes the robot arm to reach the target point with the joint acceleration of 0 but the joint velocity of not 0, and the robot arm continues to move without stopping at the target point due to this inertial velocity. The improved artificial potential field method directly relates the potential field force and the joint speed, when the mechanical arm moves to a target point, the joint speed is also reduced to 0, and the mechanical arm stops at the target point, so that the oscillation phenomenon is solved.
Through the first five steps, the collision avoidance tracks of the two mechanical arms are obtained. Specifically, the robot arm URDF file may be visualized with the robotisys toolbox tool in Matlab. Knowing the track of the end effector of the mechanical arm, obtaining the track of the joint space of the mechanical arm by solving the inverse kinematics solution of the mechanical arm, and planning the motion of the mechanical arm according to the track of the joint space of the mechanical arm. The collision avoidance process of the mechanical arm is realized through simulation:
the distance between the two mechanical arms on the Y axis is 2.25m, and the central coordinates of the bases are respectively [0,0 ]]And [0,2.25,0]. Arm R1 is from the initial point [1.5, -1.2, -0.5%]Move to target point [2,0.5, -1]Mechanical arm R2 from the initial point [1.5,3.45, -0.5%]Move to a target point [2,1, -1]. The two mechanical arms detect collision risks when t is 2.9s, the improved manual potential field method starts to act, the mechanical arm R2 avoids the R1 under the action of the virtual repulsive field, the R1 returns to an initial point after completing a stacking task, and the R2 reaches a target point under the action of the virtual gravitational field. See figure 7 for collision avoidance trajectories for robotic arms R1 and R2. Distance between the robot arm R1 and the R2 end execution please refer to FIG. 8. As can be seen from fig. 8, the improved artificial potential field method is prior to the convergence of the conventional artificial potential field method, and the distance between the robot arm R2 and the end effector of the robot arm R1 is always greater than the minimum safe distance d during collision avoidances3. The mechanical arm R2 under the action of the improved artificial potential field method moves to the target point smoothly, and the phenomenon of oscillation at the target point does not occur.
Example 2
The embodiment provides a double-mechanical-arm collision avoidance trajectory planning system based on an improved artificial potential field method, and the system comprises:
a first module: the robot control system is configured to formulate control strategies of the two mechanical arms and set the priority of the two mechanical arms;
and a second module: the robot arm three-dimensional modeling system is configured to acquire size data of the robot arm, and establish a three-dimensional model and a kinematic model of two robot arms according to the acquired size data;
and a third module: configured to establish a collision detection model of the two robots from the three-dimensional model and the kinematics model;
and a module IV: the method comprises the steps that all passing points of a working path of the two mechanical arms are determined, wherein the passing points comprise a starting point, a first intermediate point, a second intermediate point and a target point, interpolation fitting between all the passing points is completed, and complete initial tracks of the two mechanical arms are obtained;
and a fifth module: the system comprises a collision model, an improved manual potential field method, a virtual gravitational field and a repulsive force field, wherein the collision model is used for detecting an initial track in an off-line manner, when a collision risk exists between two mechanical arms, the improved manual potential field method starts to act and modifies the initial track of the slave mechanical arms, the improved manual potential field method generates the virtual gravitational field and the repulsive force field in a working space of a double-mechanical-arm system, the gravitational field is arranged at a target point of the slave mechanical arms and a threshold value distance is set in a gravitational field function, and the repulsive force field is arranged at each joint of the master mechanical arms; the modified trajectory is obtained by improving the artificial potential field method.
The specific steps of each module described above may refer to embodiment 1, where module one corresponds to step 1 in embodiment 1, module two corresponds to step 2 in embodiment 1, module three corresponds to step 3 in embodiment 1, module four corresponds to step 4 in embodiment 1, and module five corresponds to step 5 in embodiment 1, which is not described herein again.
Finally, it is also noted that relational terms such as first and second, and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The double-mechanical-arm collision avoidance track planning method based on the improved artificial potential field method is characterized by comprising the following steps:
step 1: formulating a control strategy of the two mechanical arms, and setting the priority of the two mechanical arms;
step 2: acquiring size data of the mechanical arms, and establishing three-dimensional models and kinematic models of the two mechanical arms according to the acquired size data;
and step 3: establishing a collision detection model of the double mechanical arms according to the three-dimensional model and the kinematics model;
and 4, step 4: determining all passing points of the working paths of the two mechanical arms, including a starting point, a first intermediate point, a second intermediate point and a target point, and finishing interpolation fitting among all the passing points to obtain complete initial tracks of the two mechanical arms;
and 5: the method comprises the steps that a collision model is used for detecting an initial track in an off-line mode, when a collision risk between two mechanical arms is detected, an improved manual potential field method starts to act and modifies the initial track of the slave mechanical arms, a virtual gravitational field and a repulsive force field are generated in a working space of a double mechanical arm system by the improved manual potential field method, the gravitational field is arranged at a target point of the slave mechanical arms, a threshold value distance is arranged in a gravitational field function, and the repulsive force field is arranged at each joint of the master mechanical arms; the modified trajectory is obtained by improving the artificial potential field method.
2. The method for planning collision avoidance trajectory of two robots based on the improved artificial potential field method according to claim 1, wherein in step 1, master/slave coordination control is used as a control strategy for the two robots.
3. The method for planning the collision avoidance trajectory of the two mechanical arms based on the improved artificial potential field method as claimed in claim 1, wherein in step 2, the dimensional data of the mechanical arm is measured, and a three-dimensional model of the mechanical arm is established by using software according to the obtained dimensional data; and calculating the size data to obtain a D-H parameter table of the mechanical arm, and establishing a kinematic model and a URDF file of the double-mechanical-arm system according to a standard D-H parameter method.
4. The method for planning collision avoidance trajectory of two robot arms based on the improved artificial potential field method according to claim 1, wherein the collision detection model in step 3 can determine whether the two robot arms have collision risk by calculating the distance from the robot arm to the master robot arm off-line.
5. The method for planning the collision-avoidance trajectory of the two mechanical arms based on the improved artificial potential field method as claimed in claim 1, wherein in step 4, a linear interpolation function is used to fit the distance from the starting point to the first intermediate point and the distance from the second intermediate point to the end point, and a cubic polynomial interpolation function is used to fit the trajectory from the first intermediate point to the second intermediate point.
6. The utility model provides a two robotic arms are kept away and are bumped track planning system based on improve artifical potential field method which characterized in that includes:
a first module: the control strategy of the two mechanical arms is formulated, and the priority of the two mechanical arms is set;
and a second module: the robot arm three-dimensional modeling system is configured to acquire size data of the robot arm, and establish a three-dimensional model and a kinematic model of two robot arms according to the acquired size data;
and a third module: configured to build a collision detection model of the two robots from the three-dimensional model and the kinematics model;
and a module IV: the method comprises the steps that all passing points of a working path of the two mechanical arms are determined, wherein the passing points comprise a starting point, a first intermediate point, a second intermediate point and a target point, interpolation fitting between all the passing points is completed, and complete initial tracks of the two mechanical arms are obtained;
and a fifth module: the system comprises a collision model, an improved manual potential field method, a virtual gravitational field and a repulsive force field, wherein the collision model is used for detecting an initial track in an off-line manner, when a collision risk exists between two mechanical arms, the improved manual potential field method starts to act and modifies the initial track of the slave mechanical arms, the improved manual potential field method generates the virtual gravitational field and the repulsive force field in a working space of a double-mechanical-arm system, the gravitational field is arranged at a target point of the slave mechanical arms and a threshold value distance is set in a gravitational field function, and the repulsive force field is arranged at each joint of the master mechanical arms; the modified trajectory is obtained by improving the artificial potential field method.
7. The method for planning collision avoidance trajectory of two robots based on improved artificial potential field method according to claim 6, wherein in module one, master/slave coordination control is used as a control strategy of two robots.
8. The improved artificial potential field method-based double-manipulator collision avoidance trajectory planning method according to claim 6, wherein the second module is configured to measure dimension data of the manipulator, and establish a three-dimensional model of the manipulator by using software according to the obtained dimension data; and calculating the size data to obtain a D-H parameter table of the mechanical arm, and establishing a kinematic model and a URDF file of the double-mechanical-arm system according to a standard D-H parameter method.
9. The method for planning collision avoidance trajectory of two robot arms based on the improved artificial potential field method according to claim 6, wherein the collision detection model is configured to determine whether the two robot arms are at risk of collision by calculating the distance from the robot arm to the master robot arm offline.
10. The improved artificial potential field method-based double-manipulator collision avoidance trajectory planning method according to claim 6, wherein the module IV is configured to fit a linear interpolation function to a first intermediate point from the starting point and a distance from a second intermediate point to the end point, and fit a cubic polynomial interpolation function to a trajectory from the first intermediate point to the second intermediate point.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210415041.1A CN114643581B (en) | 2022-04-20 | 2022-04-20 | Double-mechanical-arm collision avoidance track planning method and system based on improved artificial potential field method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210415041.1A CN114643581B (en) | 2022-04-20 | 2022-04-20 | Double-mechanical-arm collision avoidance track planning method and system based on improved artificial potential field method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114643581A true CN114643581A (en) | 2022-06-21 |
| CN114643581B CN114643581B (en) | 2024-01-19 |
Family
ID=81997203
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210415041.1A Active CN114643581B (en) | 2022-04-20 | 2022-04-20 | Double-mechanical-arm collision avoidance track planning method and system based on improved artificial potential field method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114643581B (en) |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5483630A (en) * | 1990-07-12 | 1996-01-09 | Hitachi, Ltd. | Method and apparatus for representing motion of multiple-jointed object, computer graphic apparatus, and robot controller |
| JP2003241836A (en) * | 2002-02-19 | 2003-08-29 | Keio Gijuku | Control method and apparatus for free-running mobile unit |
| JP2012011498A (en) * | 2010-06-30 | 2012-01-19 | Toshiba Corp | System and method for operating robot arm |
| CN104029203A (en) * | 2014-06-18 | 2014-09-10 | 大连大学 | Path planning method for implementation of obstacle avoidance for space manipulators |
| CN108153298A (en) * | 2017-04-19 | 2018-06-12 | 中国北方车辆研究所 | A kind of legged type robot traction control method and system based on improvement Artificial Potential Field |
| CN110471420A (en) * | 2019-08-23 | 2019-11-19 | 苏州浪潮智能科技有限公司 | A kind of machine barrier-avoiding method and device based on Artificial Potential Field Method |
| EP3634695A1 (en) * | 2017-05-29 | 2020-04-15 | Franka Emika GmbH | Collision handling by a robot |
| CN111546343A (en) * | 2020-05-13 | 2020-08-18 | 浙江工业大学 | Method and system for planning route of defense mobile robot based on improved artificial potential field method |
| CN112327831A (en) * | 2020-10-20 | 2021-02-05 | 大连理工大学 | Factory AGV track planning method based on improved artificial potential field method |
| CN112596525A (en) * | 2020-12-16 | 2021-04-02 | 中国地质大学（武汉） | Robot path planning method based on genetic algorithm and improved artificial potential field method |
| CN113334379A (en) * | 2021-05-30 | 2021-09-03 | 南京理工大学 | Master-slave following and collision avoidance method based on virtual force |
| CN113858210A (en) * | 2021-11-01 | 2021-12-31 | 贵州大学 | Mechanical arm path planning method based on hybrid algorithm |
| CN113997291A (en) * | 2021-11-23 | 2022-02-01 | 南方电网电力科技股份有限公司 | Machine manpower-guided autonomous control method and related device |
| CN114028153A (en) * | 2021-09-18 | 2022-02-11 | 深圳华鹊景医疗科技有限公司 | Rehabilitation robot and control method thereof |
| CN114355937A (en) * | 2021-12-31 | 2022-04-15 | 江苏理工学院 | Unmanned vehicle local path planning method based on improved artificial potential field method |
-
2022
- 2022-04-20 CN CN202210415041.1A patent/CN114643581B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5483630A (en) * | 1990-07-12 | 1996-01-09 | Hitachi, Ltd. | Method and apparatus for representing motion of multiple-jointed object, computer graphic apparatus, and robot controller |
| JP2003241836A (en) * | 2002-02-19 | 2003-08-29 | Keio Gijuku | Control method and apparatus for free-running mobile unit |
| JP2012011498A (en) * | 2010-06-30 | 2012-01-19 | Toshiba Corp | System and method for operating robot arm |
| CN104029203A (en) * | 2014-06-18 | 2014-09-10 | 大连大学 | Path planning method for implementation of obstacle avoidance for space manipulators |
| CN108153298A (en) * | 2017-04-19 | 2018-06-12 | 中国北方车辆研究所 | A kind of legged type robot traction control method and system based on improvement Artificial Potential Field |
| EP3634695A1 (en) * | 2017-05-29 | 2020-04-15 | Franka Emika GmbH | Collision handling by a robot |
| CN110471420A (en) * | 2019-08-23 | 2019-11-19 | 苏州浪潮智能科技有限公司 | A kind of machine barrier-avoiding method and device based on Artificial Potential Field Method |
| CN111546343A (en) * | 2020-05-13 | 2020-08-18 | 浙江工业大学 | Method and system for planning route of defense mobile robot based on improved artificial potential field method |
| CN112327831A (en) * | 2020-10-20 | 2021-02-05 | 大连理工大学 | Factory AGV track planning method based on improved artificial potential field method |
| CN112596525A (en) * | 2020-12-16 | 2021-04-02 | 中国地质大学（武汉） | Robot path planning method based on genetic algorithm and improved artificial potential field method |
| CN113334379A (en) * | 2021-05-30 | 2021-09-03 | 南京理工大学 | Master-slave following and collision avoidance method based on virtual force |
| CN114028153A (en) * | 2021-09-18 | 2022-02-11 | 深圳华鹊景医疗科技有限公司 | Rehabilitation robot and control method thereof |
| CN113858210A (en) * | 2021-11-01 | 2021-12-31 | 贵州大学 | Mechanical arm path planning method based on hybrid algorithm |
| CN113997291A (en) * | 2021-11-23 | 2022-02-01 | 南方电网电力科技股份有限公司 | Machine manpower-guided autonomous control method and related device |
| CN114355937A (en) * | 2021-12-31 | 2022-04-15 | 江苏理工学院 | Unmanned vehicle local path planning method based on improved artificial potential field method |
Non-Patent Citations (2)
| Title |
|---|
| 史亚飞;张力;刘子煊;吕一平;: "基于速度场的人工势场法机械臂动态避障研究", 机械传动, no. 04, pages 44 - 50 * |
| 薛阳等: "基于改进人工势场法的双机械臂避障路径规划", 机械传动, vol. 44, no. 3, pages 39 - 44 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114643581B (en) | 2024-01-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP2660013B1 (en) | Method of controlling seven-shaft multi-joint robot, control program, and robot control device | |
| Kaldestad et al. | Collision avoidance with potential fields based on parallel processing of 3D-point cloud data on the GPU | |
| CN108582071A (en) | A kind of method of industrial robot programming route diagnosis and speed-optimization | |
| CN111469129A (en) | Double-mechanical-arm-based ship hull plate curved surface forming collision-free motion planning method | |
| WO2023069292A1 (en) | Nonlinear trajectory optimization for robotic devices | |
| CN115890735B (en) | Mechanical arm system, mechanical arm, control method of mechanical arm system, controller and storage medium | |
| CN111496783B (en) | Inverse kinematics solving method for 6R industrial robot | |
| CN114310914A (en) | Fuzzy self-adaptive iterative trajectory tracking control method and system for multi-degree-of-freedom mechanical arm | |
| CN109176480A (en) | A kind of sliding-mode control and system of parallel robot | |
| Yang et al. | Collision avoidance trajectory planning for a dual-robot system: using a modified APF method | |
| CN112703090B (en) | Robot control device, robot control method, and storage medium | |
| CN114643581B (en) | Double-mechanical-arm collision avoidance track planning method and system based on improved artificial potential field method | |
| KR20120092235A (en) | Apparatus for controlling mobile robot and method of the same | |
| Muller-Karger et al. | Hyperbolic trajectories for pick-and-place operations to elude obstacles | |
| JP2021082222A (en) | Information processing method, robot system, article manufacturing method, and information processing unit | |
| Zhang et al. | Kuka youBot arm shortest path planning based on geodesics | |
| CN113146637B (en) | Robot Cartesian space motion planning method | |
| Bae et al. | A dynamic visual servoing of robot manipulator with eye-in-hand camera | |
| Chávez et al. | Kinematic and dynamic modeling of the phantomx ax metal hexapod mark iii robot using quaternions | |
| Borangiu et al. | Constraints-based motion planning for an automatic, flexible laser scanning robotized platform | |
| Zhao et al. | Kinematic Modelling Analysis and Simulation of 6-DOF Manipulator | |
| Juan et al. | Analysis and simulation of a 6R robot in virtual reality | |
| Yuxuan | Review of trajectory planning for industrial robots | |
| Luan et al. | Structural dynamics simulation analysis of industrial robot arm based on Kane method | |
| Kuppan Chetty et al. | A heuristic approach towards path planning and obstacle avoidance control of planar manipulator |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |