CN113885487A - Path tracking method, system, device and computer readable storage medium - Google Patents
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Abstract
The invention provides a path tracking method, a system, a device and a computer readable storage medium, wherein the method comprises the following steps: s1, obtaining a global path plan; s2, acquiring a speed space in each control period; s3, sampling in a velocity space to obtain a motion parameter containing velocity v and curvature k; s4, in the next control period, taking v as a linear velocity and 1/k as a circular arc track of curvature radius to move, wherein the positive and negative of k indicate the direction of angular velocity; s5, evenly dividing the circular arc track into n sections, wherein n is the number of sampling points; s6, simulating a motion track for each group of motion parameters, and calculating corresponding track point coordinates; and S7, calculating the track cost according to the track point coordinates, selecting the track with the lowest cost, converting the motion parameters into (v, omega) and issuing the (v, omega) motion parameters. The path tracking method, the system, the device and the computer readable storage medium can improve the path tracking precision.
Description
Technical Field
The present invention relates to the field of path tracking technologies, and in particular, to a path tracking method, system, apparatus, and computer-readable storage medium.
Background
An Automated Guided Vehicle (AGV), also commonly referred to as an AGV cart or a transport Vehicle equipped with an electromagnetic or optical automatic guide device, capable of traveling along a predetermined guide path, having safety protection and various transfer functions, is a transport Vehicle that does not require a driver in industrial applications, and uses a rechargeable battery as a power source. Generally, the traveling route and behavior can be controlled by a computer, or the traveling route is set up by using an electromagnetic track (electromagnetic path-following system), the electromagnetic track is adhered to the floor, and the unmanned transport vehicle moves and acts by means of the information brought by the electromagnetic track.
NURBS Non-Uniform Rational B-Splines (Non-Uniform Rational B-Splines) is an excellent modeling approach, with the specific explanation:
non-uniformity: it is meant that the range of influence of one control vertex can be varied.
Rational: meaning that each NURBS object can be defined by a rational polynomial form expression.
B-Spline (B-Spline): means that a curve is constructed with a route, interpolated between one or more points.
The TADPF traversable anchored Path tracking method (Traversability-anchored Dynamic Path Following) is a Path tracking method in AGV autonomous navigation.
Traversability-anchored (traversable anchor): the method is based on obstacle traversable information provided by a global navigation function, and ensures that the AGV safely runs when the obstacle exists.
Dynamic Path Following: and the reference points are utilized in the global path, and the local path configuration related to the AGV is comprehensively considered, so that the smoothness and stability of path tracking are ensured.
A DWA Dynamic Window method (Dynamic Window Approach) is a local path planning method, and the specific explanation is as follows:
DynamicWindow (dynamic window): the method is characterized in that the speed sampling space is limited within a feasible dynamic range according to the acceleration and deceleration performance of the AGV.
When the current AGV carries out path planning, the path tracking precision is not high.
Disclosure of Invention
In view of the above, the technical problem to be solved by the present invention is to provide a path tracking method, system, device and computer readable storage medium, which can improve the path tracking accuracy.
The technical scheme of the invention is realized as follows:
a path tracking method, comprising:
s1, obtaining a global path plan;
s2, acquiring a speed space in each control period;
s3, sampling in a velocity space to obtain a motion parameter containing velocity v and curvature k;
s4, in the next control period, taking v as a linear velocity and 1/k as a circular arc track of curvature radius to move, wherein the positive and negative of k indicate the direction of angular velocity;
s5, evenly dividing the circular arc track into n sections, wherein n is the number of sampling points;
s6, simulating a motion track for each group of motion parameters, and calculating corresponding track point coordinates;
and S7, calculating the track cost according to the track point coordinates, selecting the track with the lowest cost, converting the motion parameters into (v, omega) and issuing the (v, omega) motion parameters.
Preferably, the global path plan is generated by a B-spline;
given n +1 control points P0，P1，...，PnAnd a node vector T ═ T0，t1，...，tmB spline curve of degree p is defined by control points and node vector T:
wherein, PiIs a control point, Ni，p(t) represents the ith p-th (p +1 th order) B-spline basis function; t is tiCalled node, half-open interval [ t ]i，ti+1) Is the ith node interval and is a node interval,
then for a uniform B-spline, its ith p-th (p +1 th order) B-spline basis function formula is:
the control point method is obtained by reversely solving the control points through the model value points.
Preferably, the speed space is a value range of the current linear speed and angular speed.
Preferably, the velocity space is sampled by an average sampling method.
Preferably, the calculating the trajectory cost includes:
and evaluating the cost of all tracks by utilizing an evaluation function, wherein the evaluation criteria comprise obstacle avoidance capability, the fit degree with the global path and the smooth degree of movement.
A path tracking system, comprising:
the planning module is used for obtaining global path planning;
the acquisition module is used for acquiring a speed space in each control period;
the sampling module is used for sampling in a velocity space to obtain a motion parameter containing velocity v and curvature k;
the control module is used for moving an arc track with v as a linear speed and 1/k as a curvature circle radius in the next control period, and the positive and negative properties of k indicate the direction of angular velocity;
the dividing module is used for averagely dividing the circular arc track into n sections, wherein n is the number of sampling points;
the processing module is used for simulating a motion track for each group of motion parameters and calculating corresponding track point coordinates;
and the selection module is used for calculating the track cost according to the track point coordinates, selecting the track with the lowest cost, converting the motion parameters of the track into (v, omega) and issuing the (v, omega).
Preferably, the global path plan is generated by a B-spline;
given n +1 control points P0，P1，...，PnAnd a node vector T ═ T0，t1，...，tmB spline curve of degree p is defined by control points and node vector T:
wherein, PiIs a control point, Ni，p(t) represents the ith p-th (p +1 th order) B-spline basis function; t is tiCalled node, half-open interval [ t ]i，ti+1) Is the ith node interval and is a node interval,
then for a uniform B-spline, its ith p-th (p +1 th order) B-spline basis function formula is:
the control point method is obtained by reversely solving the control points through the model value points.
Preferably, the speed space is a value range of the current linear speed and angular speed;
and/or;
the speed space is sampled by adopting an average sampling method.
A path tracing apparatus comprising a memory and a processor; the memory for storing a computer program; the processor, when executing the computer program, for implementing the path tracing method according to any of claims 1-5.
Computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the path tracking method according to any one of claims 1 to 5.
The path tracking method, the system, the device and the computer readable storage medium combine path tracking and local path planning to improve the path tracking precision.
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Fig. 1 is a schematic structural diagram of a path tracking method according to an embodiment of the present invention;
fig. 2 is a block diagram of a path tracking system according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a path tracking method, including:
s101, obtaining a global path plan;
s102, acquiring a speed space in each control period;
s103, sampling in a velocity space to obtain a motion parameter containing velocity v and curvature k;
s104, in the next control period, taking v as a linear velocity and 1/k as an arc track of a curvature circle radius to move, wherein the positive and negative properties of k indicate the direction of angular velocity;
s105, averagely dividing the circular arc track into n sections, wherein n is the number of sampling points;
s106, simulating a motion track for each group of motion parameters, and calculating corresponding track point coordinates;
and S107, calculating the track cost according to the track point coordinates, selecting the track with the lowest cost, converting the motion parameters into (v, omega) and issuing the (v, omega) motion parameters.
Therefore, the path tracking method provided by the invention combines path tracking with local path planning, thereby improving the path tracking precision. The specific implementation process is as follows:
according to the embodiment of the invention, a B spline generates a global path;
given n +1 control points P0，P1，...，PnAnd a node vector T ═ T0，t1，...，tmThe p-th order B-spline curve is defined by these control points and the node vector T
Wherein, PiIs a control point, Ni，p(t) denotes the ith p-th (p +1 th order) B-spline basis function. Wherein, tiCalled node, half-open interval [ t ]i，ti+1) Is the ith node interval and is a node interval,
then for a uniform B-spline, its ith p-th (p +1 th order) B-spline basis function formula is:
the control point method is obtained by reversely solving the control points through the model value points.
In each control period, acquiring a speed space, namely the value ranges of the current linear speed and angular speed (or curvature);
sampling in a velocity space, and obtaining a motion parameter comprising a velocity v and a curvature k by adopting an average sampling method;
for the next control period, namely, the circular arc track motion with v as a linear velocity and 1/k as a curvature radius, the positive and negative properties of k indicate the direction of the angular velocity (the anticlockwise direction is positive, and the clockwise direction is negative);
counting the number of sampling points as n, and averagely dividing the circular arc track into n sections;
for each group of motion parameters (v, k), simulating a certain small section of arc track (the control period is short, and the control period can be also approximately processed by straight line) in the future, namely calculating the coordinate of a track point corresponding to each section;
evaluating the cost of all tracks by using an evaluation function which is obtained by design, wherein the evaluation criterion comprises obstacle avoidance capability, the fit degree with a global path, the smooth degree of movement and the like, and the evaluation function is linear superposition of the cost of each part according to weight; the initial weights may arrange for obstacle avoidance, fit to the global path, smoothness of motion, each bit 1/3
And after the cost of each track is obtained, selecting one track with the lowest cost, converting the corresponding motion parameter into (v, omega) and issuing the (v, omega).
As shown in fig. 2, an embodiment of the present invention provides a path tracking system, including:
a path tracking system, comprising:
a planning module 11, configured to obtain a global path plan;
an obtaining module 12, configured to obtain a speed space in each control period;
the sampling module 13 is configured to sample in a velocity space to obtain a motion parameter including a velocity v and a curvature k;
the control module 14 is used for moving an arc track with v as a linear velocity and 1/k as a curvature radius in the next control period, wherein the positive and negative properties of k indicate the direction of angular velocity;
a dividing module 15, configured to averagely divide the arc trajectory into n segments, where n is a sampling point number;
the processing module 16 is used for simulating a motion track for each group of motion parameters and calculating corresponding track point coordinates;
and the selection module 17 is used for calculating the track cost according to the track point coordinates, selecting the track with the lowest cost, converting the motion parameters of the track into (v, omega) and issuing the (v, omega).
According to the embodiment of the invention, a B spline generates a global path;
given n +1 control points P0，P1，...，PnAnd a node vector T ═ T0，t1，...，tmThe p-th order B-spline curve is defined by these control points and the node vector T
Wherein, PiIs a control point, Ni，p(t) denotes the ith p-th (p +1 th order) B-spline basis function. Wherein, tiCalled node, half-open interval [ t ]i，ti+1) Is the ith node interval and is a node interval,
then for a uniform B-spline, its ith p-th (p +1 th order) B-spline basis function formula is:
the control point method is obtained by reversely solving the control points through the model value points.
In each control period, acquiring a speed space, namely the value ranges of the current linear speed and angular speed (or curvature);
sampling in a velocity space, and obtaining a motion parameter comprising a velocity v and a curvature k by adopting an average sampling method;
for the next control period, namely, the circular arc track motion with v as a linear velocity and 1/k as a curvature radius, the positive and negative properties of k indicate the direction of the angular velocity (the anticlockwise direction is positive, and the clockwise direction is negative);
counting the number of sampling points as n, and averagely dividing the circular arc track into n sections;
for each group of motion parameters (v, k), simulating a certain small section of arc track (the control period is short, and the control period can be also approximately processed by straight line) in the future, namely calculating the coordinate of a track point corresponding to each section;
evaluating the cost of all tracks by using an evaluation function which is obtained by design, wherein the evaluation criterion comprises obstacle avoidance capability, the fit degree with a global path, the smooth degree of movement and the like, and the evaluation function is linear superposition of the cost of each part according to weight; the initial weights may arrange for obstacle avoidance, fit to the global path, smoothness of motion, each bit 1/3
And after the cost of each track is obtained, selecting one track with the lowest cost, converting the corresponding motion parameter into (v, omega) and issuing the (v, omega).
The embodiment of the invention also provides a path tracking device, which comprises a memory and a processor; the memory for storing a computer program; the processor is configured to implement the above path tracking method when executing the computer program.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the storage medium, and when the computer program is executed by a processor, the path tracking method is implemented.
Through the above description of the embodiments, those skilled in the art will clearly understand that the present application can be implemented by software plus necessary general-purpose hardware, and certainly can also be implemented by special-purpose hardware including special-purpose integrated circuits, special-purpose CPUs, special-purpose memories, special-purpose components and the like. Generally, functions performed by computer programs can be easily implemented by corresponding hardware, and specific hardware structures for implementing the same functions may be various, such as analog circuits, digital circuits, or dedicated circuits. However, for the present application, the implementation of a software program is more preferable. Based on such understanding, the technical solutions of the present application may be substantially embodied in the form of a software product, which is stored in a readable storage medium, such as a floppy disk, a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the method of the embodiments of the present application.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. The procedures or functions according to the embodiments of the present application are all or partially generated when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, e.g., the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. A computer-readable storage medium may be any available medium that a computer can store or a data storage device, such as a server, a data center, etc., that is integrated with one or more available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
Finally, it is to be noted that: the above description is only a preferred embodiment of the present invention, and is only used to illustrate the technical solutions of the present invention, and not to limit the protection scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (10)
1. A path tracking method, comprising:
s1, obtaining a global path plan;
s2, acquiring a speed space in each control period;
s3, sampling in a velocity space to obtain a motion parameter containing velocity v and curvature k;
s4, in the next control period, taking v as a linear velocity and 1/k as a circular arc track of curvature radius to move, wherein the positive and negative of k indicate the direction of angular velocity;
s5, evenly dividing the circular arc track into n sections, wherein n is the number of sampling points;
s6, simulating a motion track for each group of motion parameters, and calculating corresponding track point coordinates;
and S7, calculating the track cost according to the track point coordinates, selecting the track with the lowest cost, converting the motion parameters into (v, omega) and issuing the (v, omega) motion parameters.
2. The path tracking method of claim 1, wherein the global path plan is generated by B-spline;
given n +1 control points P0，P1，...，PnAnd aNode vector T ═ T0，t1，...，tmB spline curve of degree p is defined by control points and node vector T:
wherein, PiIs a control point, Ni，p(t) represents the ith p-th (p +1 th order) B-spline basis function; t is tiCalled node, half-open interval [ t ]i，ti+1) Is the ith node interval and is a node interval,
then for a uniform B-spline, its ith p-th (p +1 th order) B-spline basis function formula is:
the control point method is obtained by reversely solving the control points through the model value points.
3. The path tracking method according to claim 1, wherein the velocity space is a range of values of the current linear velocity and angular velocity.
4. The path tracking method according to claim 1, wherein the velocity space is sampled by an average sampling method.
5. The path tracking method of claim 1, wherein the calculating a trajectory cost comprises:
and evaluating the cost of all tracks by utilizing an evaluation function, wherein the evaluation criteria comprise obstacle avoidance capability, the fit degree with the global path and the smooth degree of movement.
6. A path tracking system, comprising:
the planning module is used for obtaining global path planning;
the acquisition module is used for acquiring a speed space in each control period;
the sampling module is used for sampling in a velocity space to obtain a motion parameter containing velocity v and curvature k;
the control module is used for moving an arc track with v as a linear speed and 1/k as a curvature circle radius in the next control period, and the positive and negative properties of k indicate the direction of angular velocity;
the dividing module is used for averagely dividing the circular arc track into n sections, wherein n is the number of sampling points;
the processing module is used for simulating a motion track for each group of motion parameters and calculating corresponding track point coordinates;
and the selection module is used for calculating the track cost according to the track point coordinates, selecting the track with the lowest cost, converting the motion parameters of the track into (v, omega) and issuing the (v, omega).
7. The path tracking system of claim 6, wherein the global path plan is generated by a B-spline;
given n +1 control points P0，P1，...，PnAnd a node vector T ═ T0，t1，...，tmB spline curve of degree p is defined by control points and node vector T:
wherein, PiIs a control point, Ni，p(t) represents the ith p-th (p +1 th order) B-spline basis function; t is tiCalled node, half-open interval [ t ]i，ti+1) Is the ith node interval and is a node interval,
then for a uniform B-spline, its ith p-th (p +1 th order) B-spline basis function formula is:
the control point method is obtained by reversely solving the control points through the model value points.
8. The path tracking system of claim 6, wherein the velocity space is a range of values for a current linear velocity and angular velocity;
and/or;
the speed space is sampled by adopting an average sampling method.
9. A path tracing apparatus comprising a memory and a processor; the memory for storing a computer program; the processor, when executing the computer program, for implementing the path tracing method according to any of claims 1-5.
10. Computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when being executed by a processor, carries out a path tracking method according to any one of claims 1-5.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115632146A (en) * | 2022-10-25 | 2023-01-20 | 重庆地大工业技术研究院有限公司 | Method for optimizing rate of fuel cell stack in loading process |
| CN115826500A (en) * | 2022-10-31 | 2023-03-21 | 深圳市汇川技术股份有限公司 | Track smoothing method, electronic device and readable storage medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105549597A (en) * | 2016-02-04 | 2016-05-04 | 同济大学 | Unmanned vehicle dynamic path programming method based on environment uncertainty |
| CN108460494A (en) * | 2018-03-27 | 2018-08-28 | 歌尔科技有限公司 | A kind of method, apparatus and robot of robot trajectory's processing |
| CN108640040A (en) * | 2018-03-28 | 2018-10-12 | 华南农业大学 | A kind of pose adjusts path planing method of intelligent forklift |
| CN109947119A (en) * | 2019-04-23 | 2019-06-28 | 东北大学 | A mobile robot autonomous following system and method based on multi-sensor fusion |
| CN110147221A (en) * | 2019-05-27 | 2019-08-20 | 广西大学 | A verifiable random number generation method and verification method based on B-spline curve |
| CN110703762A (en) * | 2019-11-04 | 2020-01-17 | 东南大学 | A hybrid path planning method for surface unmanned boats in complex environments |
| CN111208807A (en) * | 2018-11-06 | 2020-05-29 | 苏州艾吉威机器人有限公司 | AGV motion control method based on B spline curve |
| CN113625703A (en) * | 2021-06-30 | 2021-11-09 | 苏州艾吉威机器人有限公司 | Dynamic path tracking method |
-
2020
- 2020-07-02 CN CN202010634055.3A patent/CN113885487A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105549597A (en) * | 2016-02-04 | 2016-05-04 | 同济大学 | Unmanned vehicle dynamic path programming method based on environment uncertainty |
| CN108460494A (en) * | 2018-03-27 | 2018-08-28 | 歌尔科技有限公司 | A kind of method, apparatus and robot of robot trajectory's processing |
| CN108640040A (en) * | 2018-03-28 | 2018-10-12 | 华南农业大学 | A kind of pose adjusts path planing method of intelligent forklift |
| CN111208807A (en) * | 2018-11-06 | 2020-05-29 | 苏州艾吉威机器人有限公司 | AGV motion control method based on B spline curve |
| CN109947119A (en) * | 2019-04-23 | 2019-06-28 | 东北大学 | A mobile robot autonomous following system and method based on multi-sensor fusion |
| CN110147221A (en) * | 2019-05-27 | 2019-08-20 | 广西大学 | A verifiable random number generation method and verification method based on B-spline curve |
| CN110703762A (en) * | 2019-11-04 | 2020-01-17 | 东南大学 | A hybrid path planning method for surface unmanned boats in complex environments |
| CN113625703A (en) * | 2021-06-30 | 2021-11-09 | 苏州艾吉威机器人有限公司 | Dynamic path tracking method |
Non-Patent Citations (4)
| Title |
|---|
| 王洪斌等: "基于改进的A* 算法与动态窗口法的移动机器人路径规划", 机器人, vol. 42, no. 3, 31 May 2020 (2020-05-31) * |
| 田永永;李梁华;: "基于速度方向判定的动态窗口法", 农业装备与车辆工程, no. 08, 10 August 2018 (2018-08-10) * |
| 郁伉;肖本贤;李艳红;: "受非完整性约束的移动机器人路径跟踪算法", 合肥工业大学学报(自然科学版), no. 09, 28 September 2010 (2010-09-28) * |
| 陈宗海主编: "系统仿真技术及其应用 第16卷", 31 August 2015, 中国科学技术大学出版社 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115632146A (en) * | 2022-10-25 | 2023-01-20 | 重庆地大工业技术研究院有限公司 | Method for optimizing rate of fuel cell stack in loading process |
| CN115826500A (en) * | 2022-10-31 | 2023-03-21 | 深圳市汇川技术股份有限公司 | Track smoothing method, electronic device and readable storage medium |
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