CN115870976A - Sampling trajectory planning method and device for mechanical arm and electronic equipment - Google Patents
Sampling trajectory planning method and device for mechanical arm and electronic equipment Download PDFInfo
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Abstract
The invention discloses a method and a device for planning a sampling track of a mechanical arm and electronic equipment, belonging to the technical field of intelligent hardware, wherein the method comprises the following steps: determining pose information of an object to be sampled on a sampling platform; determining the central positions of at least two outer surfaces of the object to be sampled except the contact surface with the sampling table according to the pose information; calculating to obtain a first track curve of the initial position of the mechanical arm of the sampling robot reaching each central position in sequence through a polynomial curve fitting algorithm; screening a target track curve from the first track curves based on the motion constraint condition; setting interpolation points on the target track curve, and generating discrete points between adjacent interpolation points; and screening the discrete points to obtain a target sampling track of the mechanical arm formed by the target discrete points which do not collide with the environmental barrier. The sampling track planning method for the mechanical arm disclosed by the invention has the advantages that the calculated amount in the track planning process is small, and the finally planned target sampling track has high reliability.
Description
Technical Field
The invention relates to the technical field of intelligent hardware, in particular to a method and a device for planning a sampling track of a mechanical arm and electronic equipment.
Background
Robots can be classified into two major categories, industrial robots and server robots. The service robots include field robots, professional cleaning robots, medical robots, logistics-use robots, inspection and maintenance robots, and the like.
The sampling robot samples the goods through the mechanical arm. Generally, the input of the sampling robot only comprises a start point and an end point of work, and the track planning is carried out on the sampling robot, so that the aim of ensuring that the mechanical arm can move from the start point to the end point in a natural and smooth mode is fulfilled, and the stability is ensured. However, the current mechanical arm trajectory planning scheme has a complex calculation process and low efficiency.
Disclosure of Invention
The embodiment of the invention aims to provide a method and a device for planning a sampling track of a mechanical arm and electronic equipment, which can solve the problems of complex calculation process and low efficiency in the conventional track planning scheme.
In order to solve the technical problems, the invention provides the following technical scheme:
the embodiment of the invention provides a sampling track planning method of a mechanical arm, which is applied to a sampling robot, wherein the method comprises the following steps:
determining pose information of an object to be sampled on a sampling platform;
determining the central positions of at least two outer surfaces of the object to be sampled except the contact surface with the sampling table according to the pose information;
calculating to obtain first track curves of the sampling robot when the initial position of the mechanical arm reaches each central position in sequence through a polynomial curve fitting algorithm, wherein the number of the first track curves is more than or equal to 2;
screening out a target track curve from the first track curves based on motion constraint conditions;
setting interpolation points on the target track curve, and generating discrete points between adjacent interpolation points;
screening the discrete points according to a preset rule to obtain target discrete points without collision with the environmental barrier;
and determining a track curve formed by the target discrete points as a target sampling track of the mechanical arm.
Optionally, the step of determining the central positions of at least two outer surfaces of the object to be sampled except for the contact surface with the sampling table according to the pose information comprises:
and determining the central positions of five outer surfaces of the object to be sampled except the surface in contact with the sampling table according to the pose information.
Optionally, the step of screening out a target trajectory curve from the first trajectory curves based on a motion constraint condition includes:
aiming at a plurality of first track curves between adjacent central positions, screening out a second track curve which meets the motion constraint of the mechanical arm and has the shortest moving distance from the plurality of first track curves;
and determining all second track curves between the adjacent central positions as target track curves.
Optionally, the step of setting interpolation points on the target trajectory curve and generating discrete points between adjacent interpolation points includes:
setting interpolation points of a plurality of multidimensional vectors on the target track curve, wherein the multidimensional vectors comprise: the position coordinate vector of the tail end point of the mechanical arm in the three-dimensional coordinate system, and the included angle vector of the tail end of the mechanical arm in the positive direction of the three-dimensional coordinate system;
discrete points are generated between adjacent interpolation points that satisfy a range of positional tolerances.
Optionally, the step of screening each discrete point according to a preset rule to obtain a target discrete point that does not collide with an environmental obstacle includes:
acquiring position distribution data of surrounding obstacles by using a depth camera;
and screening out target discrete points which do not collide with the environmental barrier in each discrete point according to the position distribution data.
The embodiment of the invention provides a sampling track planning device of a mechanical arm, which is applied to a sampling robot, wherein the device comprises:
the first determining module is used for determining the pose information of an object to be sampled on the sampling table;
the second determination module is used for determining the central positions of at least two outer surfaces of the object to be sampled except the contact surface with the sampling table according to the pose information;
the calculation module is used for calculating to obtain first track curves of the sampling robot when the initial position of the mechanical arm reaches each central position in sequence through a polynomial curve fitting algorithm, wherein the number of the first track curves is more than or equal to 2;
the first screening module is used for screening a target track curve from the first track curves based on motion constraint conditions;
the setting module is used for setting interpolation points on the target track curve and generating discrete points between adjacent interpolation points;
the second screening module is used for screening the discrete points according to a preset rule to obtain target discrete points which do not collide with the environmental barrier;
and the third determining module is used for determining a track curve formed by the target discrete points as a target sampling track of the mechanical arm.
Optionally, the second determining module is specifically configured to:
and determining the central positions of five outer surfaces of the object to be sampled except the surface in contact with the sampling table according to the pose information.
Optionally, the first screening module comprises:
the first submodule is used for screening out a second track curve which meets the motion constraint of the mechanical arm and has the shortest moving distance from a plurality of first track curves aiming at the plurality of first track curves between adjacent central positions;
and the second submodule is used for determining all second track curves between the adjacent central positions as target track curves.
Optionally, the setting module includes:
a third sub-module, configured to set interpolation points of a plurality of multidimensional vectors on the target trajectory curve, where the multidimensional vectors include: the position coordinate vector of the tail end point of the mechanical arm in the three-dimensional coordinate system, and the included angle vector of the tail end of the mechanical arm in the positive direction of the three-dimensional coordinate system;
and the fourth sub-module is used for generating discrete points meeting the position tolerance range between adjacent interpolation points.
Optionally, the second screening module comprises:
the fifth sub-module is used for acquiring position distribution data of surrounding obstacles by using the depth camera;
and the sixth submodule is used for screening out target discrete points which do not collide with the environmental barrier in each discrete point according to the position distribution data.
An embodiment of the present invention provides an electronic device, which includes a processor, a memory, and a program or an instruction stored in the memory and executable on the processor, where the program or the instruction is executed by the processor to implement the steps of any one of the above methods for planning a sampling trajectory of a robot.
The embodiment of the invention provides a readable storage medium, wherein a program or an instruction is stored on the readable storage medium, and when the program or the instruction is executed by a processor, the program or the instruction realizes the steps of the sampling trajectory planning method for any mechanical arm.
According to the sampling track planning scheme of the mechanical arm, provided by the embodiment of the invention, a plurality of first track curves are fitted through a polynomial, the first track curves are screened according to the motion constraint conditions of the mechanical arm to obtain target track curves, then the target track curves are interpolated, discrete points are generated between adjacent interpolated points, finally, target discrete points which do not collide with an obstacle are screened from a plurality of generated discrete points, and finally, a target sampling track of the mechanical arm is obtained. The smoothness of the track can be ensured through polynomial fitting and motion constraint, and the target discrete points capable of avoiding the obstacles are selected through the discrete points between interpolation and filtering interpolation, so that the reliability of the determined target sampling track is ensured.
Drawings
Fig. 1 is a flowchart illustrating steps of a method for planning a sampling trajectory of a robot according to an embodiment of the present disclosure;
FIG. 2 is a diagram illustrating a first trajectory curve obtained by polynomial curve fitting in an embodiment of the present application;
FIG. 3 is a diagram illustrating a target trajectory curve determined based on motion constraints in an embodiment of the present application;
FIG. 4 is a schematic diagram showing discrete points between two interpolation points;
fig. 5 is a block diagram showing a configuration of a sampling trajectory planning apparatus of a robot according to an embodiment of the present invention;
fig. 6 is a block diagram showing a configuration of an electronic device according to an embodiment of the present application.
Detailed Description
To make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments.
The sampling trajectory planning scheme for the mechanical arm provided by the embodiment of the present application is described in detail through specific embodiments and application scenarios thereof in conjunction with the accompanying drawings.
As shown in fig. 1, a sampling trajectory planning method for a mechanical arm according to an embodiment of the present application includes the following steps:
step 101: and determining the pose information of the object to be sampled on the sampling platform.
In the embodiment of the application, an object to be sampled is placed on a sampling platform, a sampling robot plans a sampling track of a mechanical arm based on information such as the pose of the sampling object on the sampling platform and the position of the mechanical arm of the sampling robot, and then the mechanical arm is controlled to move according to the sampling track so as to finish sampling work of the object to be sampled.
The method for planning the sampling track of the mechanical arm is applied to a main control module of electronic equipment or a sampling robot, and the electronic equipment can be equipment with an analysis function, such as a server and a computer. A storage medium in the electronic device or the sampling robot stores a sampling track planning program of the mechanical arm, a processor of the electronic device or a main control module of the sampling robot runs the program in the storage medium to execute a sampling track planning flow of the mechanical arm, and the sampling track of the mechanical arm is planned for the sampling robot before the sampling robot samples an object to be sampled.
In the actual implementation process, the position and the attitude of the object to be sampled on the sampling platform can be detected by using the depth camera, and the position and attitude data of the object to be sampled is obtained.
Step 102: and determining the central positions of at least two outer surfaces except the contact surface with the sampling table in the object to be sampled according to the pose information.
In the actual implementation process, the central positions of two outer surfaces of an object to be sampled can be determined, and correspondingly, two sampling points are provided; the center positions of the three outer surfaces of the object to be sampled can also be determined, and accordingly the number of sampling points is three. In an alternative embodiment, the central positions of five outer surfaces of the object to be sampled except the contact surface with the sampling table can be determined according to the pose information of the object to be sampled. The central positions of the five outer surfaces are determined, correspondingly, the number of sampling points is five, the more sampling points are, the more comprehensive the sample of the object to be sampled is, and the more accurate and reliable the finally obtained acquisition result is.
Step 103: and calculating to obtain a first track curve of the initial position of the mechanical arm of the sampling robot reaching each central position in sequence through a polynomial curve fitting algorithm.
In the embodiment of the present application, a first trajectory curve obtained by calculation when the initial position of the mechanical arm of the sampling robot sequentially reaches the center positions of the 5 outer surfaces of the object to be sampled is described as an example. The specific generation process of the trajectory curve is as follows, taking the central positions of the 5 outer surfaces as central position 1, central position 2, central position 3, central position 4 and central position 5 respectively: generating a first track curve from the initial position of the mechanical arm to the central position 1, generating a first track curve from the central position 1 to the central position 2, generating a first track curve from the central position 2 to the central position 3, generating a first track curve from the central position 3 to the central position 4, and generating a first track curve from the central position 4 to the central position 5.
The first trajectory curve between any two points can be obtained by n-degree polynomial curve fitting, and the value of n determines the number of the first trajectory curves which are finally fitted. In the embodiment of the present application, n (max) > n > =1 may be set, where n (max) is set according to a system environment. When n is 1, the trajectory curve of the mechanical arm is a straight line, but sometimes the straight line trajectory is not satisfied in the kinematic constraint of the mechanical arm, so a plurality of first trajectory curves are generated and screened in the next step, and therefore the number of the first trajectory curves between any two points is greater than or equal to 2. A schematic diagram of a first trajectory curve between any two points obtained by a polynomial curve fitting algorithm is shown in fig. 2.
Step 104: and screening out a target track curve from the first track curves based on the motion constraint condition.
One way to screen out a target trajectory curve from the first trajectory curves, optionally based on motion constraints, may be as follows:
firstly, aiming at a plurality of first track curves between adjacent central positions, screening out a second track curve which meets the motion constraint of the mechanical arm and has the shortest moving distance from the plurality of first track curves;
and secondly, determining all second track curves between the adjacent central positions as target track curves.
The target trajectory curve screening method provided in this optional embodiment determines a second trajectory curve from a plurality of first trajectory curves between adjacent central positions, and then sequentially connects the second trajectory curves between adjacent two points to form a target trajectory curve, so as to ensure that the target trajectory curve is the shortest moving distance of the mechanical arm on the premise of satisfying the motion constraint condition. The generated target trajectory curve is schematically shown in fig. 3.
Step 105: interpolation points are set on the target trajectory curve, and discrete points are generated between adjacent interpolation points.
One way to optionally set interpolation points on the target trajectory curve may be: and setting a plurality of interpolation points of the multi-dimensional vectors on the target track curve, and generating discrete points meeting the position tolerance range between adjacent interpolation points. The schematic diagram of the discrete points between two interpolation points is shown in fig. 4, and it can be seen from fig. 4 that each interpolation point attachment is provided with a plurality of discrete points.
Wherein, the multidimensional vector comprises: and the tail end of the mechanical arm faces to an included angle vector in the positive direction of the three-dimensional coordinate system.
For example: each interpolation point may be set to a six-dimensional vector x, y, z, θ _ x, θ _ y, θ _ z, which represents the position and orientation of the tip of a sample swab held by the end of the robotic arm. Wherein, x, y and z respectively represent the position coordinates of the end point of the mechanical arm on the xyz axis, and theta _ x, theta _ y and theta _ z respectively represent the included angle of the end point of the mechanical arm towards the positive direction of the xyz axis.
Step 106: and screening the discrete points according to a preset rule to obtain target discrete points without collision with the environmental barrier.
One way to optionally screen the discrete points according to the preset rule to obtain the target discrete points without collision with the environmental obstacle is as follows: firstly, acquiring position distribution data of surrounding obstacles by using a depth camera; and secondly, screening out target discrete points which do not collide with the environmental barrier from the discrete points according to the position distribution data.
The mode of screening the target discrete points based on the position distribution information of the surrounding fault objects optionally can effectively avoid collision of the mechanical arm with the surrounding obstacles in the moving process.
It should be noted that the above is only a way of optionally screening out a target discrete point from a plurality of discrete points, and in an actual implementation process, a person skilled in the art may flexibly set a discrete point screening tool and a rule, so as to ensure that the screened target discrete point does not collide with an environmental obstacle.
Step 107: and determining a track curve formed by the discrete points of each target as a target sampling track of the mechanical arm.
In the embodiment of the application, the sampling trajectory planning method for the mechanical arm in the embodiment of the application is executed once each time a sampling object is replaced in the sampling platform. After the target sampling track of the mechanical arm is determined through the sampling track planning method provided by the embodiment of the application, the mechanical arm is controlled to sequentially reach each target discrete point according to the target sampling track, and the sampling action of the object to be sampled is completed.
According to the sampling trajectory planning method for the mechanical arm, a plurality of first trajectory curves are fitted through a polynomial, the first trajectory curves are screened according to motion constraint conditions of the mechanical arm to obtain target trajectory curves, then interpolation is carried out on the target trajectory curves, discrete points are generated between adjacent interpolation points, finally, target discrete points which do not collide with an obstacle are screened from a plurality of generated discrete points, and finally, a target sampling trajectory of the mechanical arm is obtained. The smoothness of the track can be guaranteed through polynomial fitting and motion constraint, points capable of avoiding obstacles are selected through discrete points between interpolation and filtering interpolation, and the reliability of the determined target sampling track is guaranteed.
Fig. 5 is a block diagram of a structure of a sampling trajectory planning apparatus for a robot according to an embodiment of the present disclosure.
The embodiment of the application provides a sampling track planning device of arm is applied to the sampling robot, the device includes following functional module:
a first determining module 501, configured to determine pose information of an object to be sampled on a sampling bench;
a second determining module 502, configured to determine, according to the pose information, center positions of at least two outer surfaces of the object to be sampled, except for a surface in contact with the sampling stage;
a calculating module 503, configured to calculate, through a polynomial curve fitting algorithm, first trajectory curves when the initial positions of the mechanical arms of the sampling robot sequentially reach the central positions, where the number of the first trajectory curves is greater than or equal to 2;
a first screening module 504, configured to screen a target trajectory curve from the first trajectory curves based on a motion constraint condition;
a setting module 505, configured to set interpolation points on the target trajectory curve, and generate discrete points between adjacent interpolation points;
the second screening module 506 is configured to screen each discrete point according to a preset rule to obtain a target discrete point that does not collide with an environmental barrier;
the third determining module 507 is configured to determine a trajectory curve formed by the target discrete points as a target sampling trajectory of the mechanical arm.
Optionally, the second determining module is specifically configured to:
and determining the central positions of five outer surfaces of the object to be sampled except the surface in contact with the sampling table according to the pose information.
Optionally, the first screening module comprises:
the first submodule is used for screening out a second track curve which meets the motion constraint of the mechanical arm and has the shortest moving distance from a plurality of first track curves aiming at the plurality of first track curves between adjacent central positions;
and the second sub-module is used for determining all second track curves between the adjacent central positions as target track curves.
Optionally, the setting module includes:
a third sub-module, configured to set interpolation points of a plurality of multidimensional vectors on the target trajectory curve, where the multidimensional vectors include: the position coordinate vector of the tail end point of the mechanical arm in the three-dimensional coordinate system, and the included angle vector of the tail end of the mechanical arm in the positive direction of the three-dimensional coordinate system;
and the fourth sub-module is used for generating discrete points meeting the position tolerance range between adjacent interpolation points.
Optionally, the second screening module comprises:
the fifth sub-module is used for acquiring position distribution data of surrounding obstacles by using the depth camera;
and the sixth submodule is used for screening out target discrete points which do not collide with the environmental barrier in each discrete point according to the position distribution data.
The sampling track planning device for the mechanical arm, provided by the embodiment of the application, comprises a plurality of first track curves, wherein the first track curves are fitted through a polynomial, a target track curve is obtained by screening the first track curves according to motion constraint conditions of the mechanical arm, interpolation is carried out on the target track curve, discrete points are generated between adjacent interpolation points, a target discrete point which does not collide with an obstacle is finally screened out from a plurality of generated discrete points, and a target sampling track of the mechanical arm is finally obtained. The smoothness of the track can be guaranteed through polynomial fitting and motion constraint, points capable of avoiding obstacles are selected through discrete points between interpolation and screening interpolation, and the reliability of the determined target sampling track is guaranteed.
The sampling trajectory planning device of the mechanical arm shown in fig. 5 in the embodiment of the present application may be a device, or may be a component, an integrated circuit, or a chip in a server. The sampling trajectory planning device of the robot arm shown in fig. 5 in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system (Android), an iOS operating system, or other possible operating systems, which is not specifically limited in the embodiments of the present application.
The sampling trajectory planning device for the mechanical arm shown in fig. 5 provided in the embodiment of the present application can implement each process implemented by the method embodiment of fig. 1, and is not described here again to avoid repetition.
Optionally, as shown in fig. 6, an electronic device 600 is further provided in an embodiment of the present application, and includes a processor 601, a memory 602, and a program or an instruction stored in the memory 602 and executable on the processor 601, where the program or the instruction is executed by the processor 601 to implement each process of the embodiment of the sampling trajectory planning method for a mechanical arm, and can achieve the same technical effect, and in order to avoid repetition, the description is omitted here.
It should be noted that the electronic device in the embodiment of the present application includes the server described above.
The embodiment of the present application further provides a readable storage medium, where a program or an instruction is stored, and when the program or the instruction is executed by a processor, the program or the instruction implements each process of the embodiment of the method for planning a sampling trajectory of a mechanical arm, and can achieve the same technical effect, and in order to avoid repetition, the description is not repeated here.
The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and so on.
The embodiment of the present application further provides a chip, where the chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is configured to run a program or an instruction to implement each process of the embodiment of the method for planning a sampling trajectory of a mechanical arm, and can achieve the same technical effect, and in order to avoid repetition, the description is omitted here.
It should be understood that the chips mentioned in the embodiments of the present application may also be referred to as system-on-chip, system-on-chip or system-on-chip, etc.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a component of' 8230; \8230;" does not exclude the presence of another like element in a process, method, article, or apparatus that comprises the element.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A sampling track planning method of a mechanical arm is applied to a sampling robot, and is characterized by comprising the following steps:
determining pose information of an object to be sampled on a sampling table;
according to the pose information, determining the central positions of at least two outer surfaces of the object to be sampled except the surface in contact with the sampling table;
calculating to obtain first track curves of the initial positions of the mechanical arms of the sampling robot reaching the central positions in sequence through a polynomial curve fitting algorithm, wherein the number of the first track curves is more than or equal to 2;
screening out a target track curve from the first track curves based on motion constraint conditions;
setting interpolation points on the target track curve, and generating discrete points between adjacent interpolation points;
screening the discrete points according to a preset rule to obtain target discrete points without collision with the environmental barriers;
and determining a track curve formed by the target discrete points as a target sampling track of the mechanical arm.
2. The method according to claim 1, wherein the step of determining the central positions of at least two outer surfaces of the object to be sampled except the surface in contact with the sampling table according to the pose information comprises:
and determining the central positions of five outer surfaces of the object to be sampled except the surface in contact with the sampling table according to the pose information.
3. The method of claim 1, wherein the step of selecting a target trajectory profile from the first trajectory profiles based on motion constraints comprises:
aiming at a plurality of first track curves between adjacent central positions, screening out a second track curve which meets the motion constraint of the mechanical arm and has the shortest moving distance from the plurality of first track curves;
and determining all second track curves between the adjacent central positions as target track curves.
4. The method of claim 1, wherein the step of placing interpolation points on the target trajectory curve and generating discrete points between adjacent interpolation points comprises:
setting interpolation points of a plurality of multidimensional vectors on the target track curve, wherein the multidimensional vectors comprise: the position coordinate vector of the tail end point of the mechanical arm in the three-dimensional coordinate system, and the included angle vector of the tail end of the mechanical arm in the positive direction of the three-dimensional coordinate system;
discrete points are generated between adjacent interpolation points that satisfy a range of positional tolerances.
5. The method according to claim 1, wherein the step of screening each discrete point according to a preset rule to obtain a target discrete point having no collision with an environmental obstacle comprises:
acquiring position distribution data of surrounding obstacles by using a depth camera;
and screening out target discrete points which do not collide with the environmental barrier in each discrete point according to the position distribution data.
6. A sampling track planning device of a mechanical arm is applied to a sampling robot, and is characterized by comprising:
the first determining module is used for determining the pose information of an object to be sampled on the sampling table;
the second determination module is used for determining the central positions of at least two outer surfaces of the object to be sampled except the contact surface with the sampling table according to the pose information;
the calculation module is used for calculating and obtaining first track curves of the sampling robot when the initial position of the mechanical arm reaches each central position in sequence through a polynomial curve fitting algorithm, wherein the number of the first track curves is more than or equal to 2;
the first screening module is used for screening a target track curve from the first track curves based on motion constraint conditions;
the setting module is used for setting interpolation points on the target track curve and generating discrete points between adjacent interpolation points;
the second screening module is used for screening the discrete points according to a preset rule to obtain target discrete points which do not collide with the environmental barrier;
and the third determining module is used for determining a track curve formed by the target discrete points as a target sampling track of the mechanical arm.
7. The apparatus of claim 6, wherein the second determining module is specifically configured to:
and determining the central positions of five outer surfaces of the object to be sampled except the surface in contact with the sampling table according to the pose information.
8. The apparatus of claim 6, wherein the first screening module comprises:
the first submodule is used for screening out a second track curve which meets the motion constraint of the mechanical arm and has the shortest moving distance from a plurality of first track curves aiming at the plurality of first track curves between adjacent central positions;
and the second submodule is used for sequentially reaching the combination of the second track curves of the central positions from the initial position of the mechanical arm of the sampling robot to determine the second track curve as a target track curve.
9. The apparatus of claim 6, wherein the setup module comprises:
a third sub-module, configured to set interpolation points of a plurality of multidimensional vectors on the target trajectory curve, where the multidimensional vectors include: the position coordinate vector of the tail end point of the mechanical arm in the three-dimensional coordinate system, and the included angle vector of the tail end of the mechanical arm in the positive direction of the three-dimensional coordinate system;
and the fourth sub-module is used for generating discrete points meeting the position tolerance range between adjacent interpolation points.
10. An electronic device comprising a processor, a memory, and a program or instructions stored on the memory and executable on the processor, the program or instructions when executed by the processor implementing the steps of the method of sampling trajectory planning for a robotic arm according to any of claims 1-5.
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| KR20210093193A (en) * | 2020-12-21 | 2021-07-27 | 베이징 바이두 넷컴 사이언스 앤 테크놀로지 코., 엘티디. | A method, an apparatus, an electronic device, a storage medium, a roadside device, a cloud control platform, and computer program product for processing trajectory |
| WO2022183790A1 (en) * | 2021-03-02 | 2022-09-09 | 北京旷视机器人技术有限公司 | Path planning method and apparatus, mobile robot, storage medium, and program |
| CN113246139A (en) * | 2021-06-15 | 2021-08-13 | 电子科技大学中山学院 | Mechanical arm motion planning method and device and mechanical arm |
| CN114633258A (en) * | 2022-04-24 | 2022-06-17 | 中国铁建重工集团股份有限公司 | Method for planning mechanical arm movement track in tunnel environment and related device |
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