CN109388140B - Improved pure tracking control method for ground vehicle path tracking - Google Patents
Improved pure tracking control method for ground vehicle path tracking Download PDFInfo
- Publication number
- CN109388140B CN109388140B CN201811066889.8A CN201811066889A CN109388140B CN 109388140 B CN109388140 B CN 109388140B CN 201811066889 A CN201811066889 A CN 201811066889A CN 109388140 B CN109388140 B CN 109388140B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- delta
- course
- small
- circular arc
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 30
- 239000013256 coordination polymer Substances 0.000 claims description 76
- 238000012937 correction Methods 0.000 claims description 38
- 238000012544 monitoring process Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 4
- 238000005516 engineering process Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 238000005259 measurement Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000010355 oscillation Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
Landscapes
- Engineering & Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Vehicle Body Suspensions (AREA)
- Steering Control In Accordance With Driving Conditions (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
The invention discloses an improved pure tracking control method for tracking a ground vehicle path, which relates to the field of ground vehicle navigation control.
Description
Technical Field
The invention relates to the field of ground vehicle navigation control, in particular to an improved pure tracking control method for ground vehicle path tracking.
Background
In recent years, with the rapid development of automatic control technology, navigation technology and sensing detection technology, the ground vehicle automatic driving technology is greatly improved. In the commercial and agricultural fields, vehicle autopilot technology can liberate manpower and improve traffic or operating efficiency. The key to ground vehicle autopilot is two areas, the accurate measurement and control of vehicle position. The accurate measurement of the vehicle position can be completed through modern navigation technology, centimeter-level positioning measurement can be realized, and the accurate control of the vehicle position has certain challenges. The key point of the accurate control of the vehicle position is path tracking control, and the existing path tracking control method mainly comprises PID control, fuzzy control, optimal control and pure tracking control. PID control is based on an error generation control strategy, does not depend on a specific mathematical model, is widely applied, but is difficult to set control parameters and needs certain experience and a large number of experiments; the fuzzy control does not depend on a vehicle model, but needs the experience of experts to formulate a control rule, and has large tracking error and difficult rapid correction; the optimal control depends on accurate vehicle kinematics and dynamic models, and the vehicle kinematics and dynamic models have poor robustness and adaptability aiming at different road conditions of different vehicles; the pure tracking method is a geometric method, control parameters are few, algorithm design simulates the driving behavior of a human and has foresight, but the influence of the foresight distance is large, and even if a dynamic adjustment method is used for self-adaptive selection, when the expected rotation angle of the front wheel is large, path tracking error oscillation caused by excessive adjustment still occurs.
The invention with the publication number of CN105867377A discloses an automatic navigation control method for agricultural machinery, which considers the vehicle speed and the curvature of a planned path, realizes the dynamic adjustment of a forward looking distance based on the vehicle speed and the curvature, and then combines fuzzy control and a pure tracking algorithm to obtain a front wheel expected corner so as to realize the path tracking control of the agricultural machinery. The method does not consider the situation that the path tracking error can oscillate due to the fact that the expected rotation angle of the front wheel is large, and the stable and accurate tracking of the planned path is difficult to achieve when the expected rotation angle is large. To solve the above problems, chening et al (see chening et al, a pure tracking model improvement algorithm, light industrial machinery 2014,32(4):69-72.) propose an improved pure tracking algorithm based on the principle of analyzing the error of the pure tracking model algorithm, decompose path tracking into three steps, and respectively calculate the expected rotation angle of the front wheel of each step. The method can improve the path tracking accuracy to a certain extent, but the method obtains the expected turning angle of the front wheel in each step by simplifying the model and approximating, the obtained parameters are rough and cannot be dynamically adjusted according to the actual driving condition, and the obtained parameters are optimized aiming at the characteristic condition and lack of universality.
Disclosure of Invention
In order to overcome the drawbacks of the above-described technical methods, it is an object of the present invention to provide an improved pure tracking control method for ground vehicle path tracking. The method integrates the positive and negative of the vehicle transverse deviation and the relationship between the vehicle course deviation and the ideal straight line correction course angle to select a proper path tracking method, and realizes path tracking control with good stability and high precision.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
improved pure tracking control method for ground vehicle path trackingThe method judges the relation between course deviation and ideal straight line correction course angle according to the navigation parameters provided by a vehicle navigation system, and selects a small circular arc path tracking algorithm or a large circular arc path tracking algorithm by combining the positive and negative of the transverse deviation: establishing a field plane coordinate system xoy by taking two random vertical boundaries of a field as x and y axes and an intersection point of the two boundaries as an origin o, wherein the current position of the vehicle is C (x)c,yc) The desired position is C' (x)c’,yc') and a first preview point P (x)p,yp) The second preview point is P' (x)p’,yp’) C ' P is a planned path (the direction from C ' to P is the positive direction of the planned path), the difference value of the horizontal coordinates of the current position C and the expected position C ' is a horizontal deviation Δ x, Δ x is a negative value when the current position C is deviated to the left of the expected position C ', and Δ x is a positive value when the current position C of the vehicle is deviated to the right of the expected position C '; the line segment CP is an ideal straight line correction course of the vehicle track, the positive direction points to P from C, an included angle formed by the positive direction of the CP and the positive direction of the planned path C 'P is an ideal straight line correction course angle, the ideal straight line correction course angle is a negative value when the positive direction of the CP is left relative to the positive direction of the C' P, and the ideal straight line correction course angle is a positive value when the positive direction of the CP is right; the real-time course of the vehicle is CE, the positive direction points to E from C, an included angle formed by the positive direction of the CE and the positive direction of the planned path C 'P is course deviation delta theta, when the positive direction of the CE deviates to the left relative to the positive direction of the C' P, the delta theta is a negative value, and when the positive direction deviates to the right, the delta theta is a positive value; the circular arc CP is an arc correction path; when the vehicle course deviation delta theta is larger than the ideal straight line correction course angle, namely CE is on the right side of CP, and the transverse deviation is positive, a small arc path tracking algorithm is adopted; when the vehicle course deviation delta theta is larger than the ideal straight line correction course angle, namely CE is on the right side of CP, and the transverse deviation is negative, a large circular arc path tracking algorithm is adopted; when the vehicle course deviation delta theta is smaller than the ideal straight line correction course angle, namely CE is on the left side of CP, and the transverse deviation is negative, a small arc path tracking algorithm is adopted; the vehicle course deviation delta theta is smaller than an ideal straight line correction course angle, namely CE is on the left side of CP, and the transverse deviation is positive, a large circular arc path tracking algorithm is adopted; when the vehicle course deviation delta theta is equal to the ideal straight line correction course angle, the steering wheel is back to the right and the vehicle runs according to the current course angle.
Further, the small arc path tracking algorithm is realized and corrected through the following steps:
(1) each control period is 1 external circulation large period, the 1 external circulation large period comprises a plurality of internal circulation small periods, the default of the number of the internal circulation times is set to be 4, and the internal circulation times can be adjusted according to actual needs;
(2) obtaining a first group of navigation positioning data in a new outer circulation period, determining a point coordinate of a first pre-aiming point P, calculating a circle center radius corresponding to a small circular arc, and converting the circle center radius into a front wheel expected corner;
(3) controlling the front wheels of the vehicle to steer according to the expected turning angle of the front wheels, and enabling the vehicle to start to run along the CP circular arc route;
(4) monitoring the course deviation delta theta and the transverse deviation delta x of the vehicle in an inner circulation small period, if the delta theta delta x is larger than 0, continuing to run along the CP circular arc route, judging whether the position of the vehicle is on the inner side or the outer side of the CP circular arc, and performing small-amplitude adjustment on the front wheel steering according to the judgment result to correct the actual track of the vehicle; if delta theta, delta x and delta x are not more than 0, entering a small internal circulation period II;
(5) changing the point of the pre-aiming point from a first point P of the pre-aiming point to a second point P 'of the pre-aiming point within a small internal cycle period, judging the relation between the real-time course CE of the vehicle and a new ideal straight line correction course CP' and the positive and negative of a transverse deviation delta x, and if the CE is positioned at the left side of the CP 'and delta x is less than 0, or the CE is positioned at the right side of the CP' and delta x is more than 0, continuing to run along the circular arc course of the CP; if CE is on the left side of CP 'and delta x is greater than 0, or CE is on the right side of CP' and delta x is less than 0, then entering into inner loop small period;
(6) In the inner circulation small period III, the front wheel is controlled to be aligned, the vehicle runs according to a new ideal straight course CP ', and the actual track of the vehicle is adjusted in a small amplitude according to the relative position relation between the real-time position of the vehicle and the CP';
(7) and (5) repeating the steps (4) to (6) until the external circulation large period is finished.
Further, the great circular arc path tracking algorithm is realized by the following steps:
(1) each control period is 1 external cycle, the 1 external cycle large period comprises a plurality of internal cycle small periods, the internal cycle times are set to be 4 by default, and the internal cycle times can be adjusted according to actual needs;
(2) obtaining a first group of navigation positioning data in a new outer circulation large period, determining a first pre-aiming point P, calculating the circle center radius corresponding to the large circular arc, and converting the circle center radius into a front wheel expected corner;
(3) controlling the front wheels of the vehicle to steer according to the expected turning angle of the front wheels, and enabling the vehicle to start to run along the CP circular arc route;
(4) monitoring the course deviation delta theta and the transverse deviation delta x of the vehicle in an inner circulation small period, if delta theta x delta x is less than 0, continuing to run along the CP circular arc route, judging whether the position of the vehicle is on the inner side or the outer side of the CP circular arc, and performing small-amplitude adjustment on the front wheel steering according to the judgment result to correct the actual track of the vehicle; if delta theta and delta x are more than or equal to 0, entering a small internal circulation period II;
(5) In the internal circulation small period II, controlling the front wheel of the vehicle to be aligned, directly continuing to run according to the course angle of 0 degree, and carrying out small adjustment on the actual track of the vehicle according to the real-time position of the vehicle;
(6) and (5) repeating the steps (4) to (5) until the external circulation large period is finished.
The method for determining the preview point comprises the following steps: the forward looking distance can be a preset value or obtained by a dynamic calculation method considering the vehicle speed and the curvature of the planned path, a point closest to the current position of the vehicle is searched on the planned path, the forward looking distance is intercepted by taking the point as a starting point to obtain a first pre-aiming point P, and the forward looking distance is intercepted by 2 times to obtain a second pre-aiming point P'.
The invention has the beneficial effects that:
the invention improves the pure tracking algorithm, comprehensively considers the positive and negative of the vehicle transverse deviation and the relation between the vehicle course deviation and the ideal straight line correction course angle, selects a proper path tracking method, can dynamically adjust the advancing direction of the vehicle according to the real-time motion state of the vehicle, particularly can solve the problem of over-adjustment when the expected turning angle of the front wheel is larger, and can realize path tracking control with good stability and high precision.
Drawings
FIG. 1A is a schematic diagram of a small arc path tracking algorithm when Δ x >0 and CE is to the right of CP;
FIG. 1B is a schematic diagram of a small arc path tracking algorithm when Δ x <0 and CE is to the left of CP;
FIG. 2A is a schematic diagram of a large circular arc path tracking algorithm when Δ x >0 and CE is to the left of CP;
FIG. 2B is a schematic diagram of the great circle path tracking algorithm when Δ x <0 and CE is to the right of CP;
FIG. 3 is a flow chart of a small arc path tracking algorithm;
fig. 4 is a flowchart of a large circular arc path tracking algorithm.
Detailed Description
For a further understanding of the present invention, reference is made to the following description taken in conjunction with the accompanying drawings and examples, but the invention is not limited to the following examples.
With reference to fig. 1A, 1B and fig. 2A and 2B, a field plane coordinate system xoy is established with two arbitrary perpendicular boundaries of a field as x and y axes and an intersection point of the two boundaries as an origin o, and a current position of a vehicle is C (x)c,yc) The desired position is C' (x)c’,yc') and a first preview point P (x)p,yp) The second preview point is P' (x)p’,yp’) C ' P is a planned path (the direction from C ' to P is the positive direction of the planned path), the difference value of the horizontal coordinates of the current position C and the expected position C ' is a horizontal deviation Δ x, Δ x is a negative value when the current position C is deviated to the left of the expected position C ', and Δ x is a positive value when the current position C of the vehicle is deviated to the right of the expected position C '; the line segment CP is an ideal straight line correction course (the direction P from C is the positive direction of the ideal straight line correction course), an included angle formed by the positive direction of the CP and the positive direction of the planned path C 'P is an ideal straight line correction course angle, when the positive direction of the CP deviates to the left relative to the positive direction of the C' P, the ideal straight line correction course angle is a negative value, and when the positive direction deviates to the right, the ideal straight line correction course angle is a positive value; the real-time course of the vehicle is CE (the direction from C to E is the positive direction of the real-time course of the vehicle), an included angle formed by the positive direction of the CE and the positive direction of the C 'P of the planned path is course deviation delta theta, when the positive direction of the CE deviates to the left relative to the positive direction of the C' P, the delta theta is a negative value, and when the positive direction deviates to the right, the delta theta is a positive value; the circular arc CP is an arc line school A positive path.
An improved pure tracking control method for ground vehicle path tracking is characterized in that the method judges the relationship between the vehicle course deviation and the ideal straight line correction course angle according to the navigation parameters provided by a vehicle navigation system, and selects a small circular arc path tracking algorithm or a large circular arc path tracking algorithm by combining the positive and negative of the transverse deviation: when CE is on the right side of CP and delta x is greater than 0, adopting a small arc path tracking algorithm; when CE is on the right side of CP and delta x is less than 0, adopting a great arc path tracking algorithm; when CE is on the left side of CP and delta x is less than 0, adopting a small arc path tracking algorithm; when CE is on the left side of CP and delta x is greater than 0, adopting a large circular arc path tracking algorithm; when the course deviation is equal to the ideal straight line correction course angle, the steering wheel returns to the positive state and runs according to the current course angle.
As shown in fig. 1A, 1B and 3, although the vehicle can reach the first pre-aiming point P by traveling along the circular arc CP, the course deviation near the point P is too large, and the lateral deviation increases due to overshoot that inevitably occurs after the point P, so that the vehicle must start the second pre-aiming point P 'after the point P in advance and gradually deviate from the circular arc CP to travel toward the second pre-aiming point P' when the course deviation before the point P is not too large. Therefore, the small arc path tracking algorithm is realized and corrected through the following steps:
(1) Each control period is 1 external circulation large period, the 1 external circulation large period comprises a plurality of internal circulation small periods, the default of the number of the internal circulation times is set to be 4, and the internal circulation times can be adjusted according to actual needs;
(2) obtaining a first group of navigation positioning data in a new outer circulation period, determining a point coordinate of a first pre-aiming point P, calculating a circle center radius corresponding to a small circular arc, and converting the circle center radius into a front wheel expected corner;
(3) controlling the front wheels of the vehicle to steer according to the expected turning angle of the front wheels, and enabling the vehicle to start to run along the CP circular arc route;
(4) monitoring the course deviation delta theta and the transverse deviation delta x of the vehicle in an inner circulation small period, if the delta theta delta x is larger than 0, continuing to run along the CP circular arc route, judging whether the position of the vehicle is on the inner side or the outer side of the CP circular arc, and performing small-amplitude adjustment on the front wheel steering according to the judgment result to correct the actual track of the vehicle; if delta theta, delta x and delta x are not more than 0, entering a small internal circulation period II;
(5) changing the pre-aiming point from the point P to the next pre-aiming point P 'in a small internal circulation period, judging the relation between the real-time course CE of the vehicle and the new ideal straight line correction course CP' and the positive and negative of the transverse deviation delta x, and if the CE is on the left side of the CP 'and delta x is less than 0, or the CE is on the right side of the CP' and delta x is greater than 0, continuing to run along the circular arc course of the CP; if CE is on the left side of CP 'and delta x is greater than 0, or CE is on the right side of CP' and delta x is less than 0, then entering into inner loop small period;
(6) In the inner circulation small period III, the front wheel is controlled to be aligned, the vehicle runs according to a new ideal straight course CP ', and the actual track of the vehicle is adjusted in a small amplitude according to the relative position relation between the real-time position of the vehicle and the CP';
(7) and (5) repeating the steps (4) to (6) until the external circulation large period is finished.
As shown in fig. 2A, 2B, and 4, since the orthodrome trajectory does not greatly deviate from the planned path at the point P of the first preview point, no further correction is needed, and the orthodrome path tracking algorithm is implemented through the following steps:
(1) each control period is 1 external cycle, the 1 external cycle large period comprises a plurality of internal cycle small periods, the internal cycle times are set to be 4 by default, and the internal cycle times can be adjusted according to actual needs;
(2) obtaining a first group of navigation positioning data in a new outer circulation large period, determining a point coordinate of a first pre-aiming point P, calculating a circle center radius corresponding to a large circular arc, and converting the circle center radius into a front wheel expected corner;
(3) controlling the front wheels of the vehicle to steer according to the expected turning angle of the front wheels, and enabling the vehicle to start to run along the CP circular arc route;
(4) monitoring the course deviation delta theta and the transverse deviation delta x of the vehicle in an inner circulation small period, if delta theta x delta x is less than 0, continuing to run along the CP circular arc route, judging whether the position of the vehicle is on the inner side or the outer side of the CP circular arc, and performing small-amplitude adjustment on the front wheel steering according to the judgment result to correct the actual track of the vehicle; if delta theta and delta x are more than or equal to 0, entering a small internal circulation period II;
(5) In the internal circulation small period II, controlling the front wheel of the vehicle to be aligned, directly continuing to run according to the course angle of 0 degree, and carrying out small adjustment on the actual track of the vehicle according to the real-time position of the vehicle;
(6) and (5) repeating the steps (4) to (5) until the external circulation large period is finished.
The method for determining the preview point comprises the following steps: the forward looking distance can be a preset value or obtained by a dynamic calculation method considering the vehicle speed and the curvature of the planned path, a point closest to the current position of the vehicle is searched on the planned path, the forward looking distance is intercepted by taking the point as a starting point to obtain a first forward pointing point P, and a forward looking distance which is 2 times of the forward looking distance is intercepted to obtain a second forward pointing point P'; the foresight distance preset value is calculated by a formula L ═ T × V, wherein L is the foresight distance, T is the control external circulation large period time, and V is the vehicle running speed; the forward looking distance dynamic calculation method is that L is equal to Lp+k1V+k2Ω, wherein LpBase of forward looking distance, k1Is a velocity coefficient, the value is positive, k2The curve coefficient is negative, and omega is the curve of the planned path of the vehicle.
The foregoing detailed description is intended to illustrate and not limit the invention, which is intended to be within the spirit and scope of the appended claims, and any changes and modifications that fall within the true spirit and scope of the invention are intended to be covered by the following claims.
Claims (5)
1. An improved pure tracking control method for ground vehicle path tracking is characterized in that the method judges the relationship between the real-time course angle of a vehicle and an ideal straight line correction course angle according to navigation parameters provided by a vehicle navigation system, and selects a small circular arc path tracking algorithm or a large circular arc path tracking algorithm by combining the positive and negative of transverse deviation: establishing a field plane coordinate system xoy by taking two random vertical boundaries of a field as x and y axes and an intersection point of the two boundaries as an origin o, wherein the current position of the vehicle is C (x)c,yc) The desired position is C' (x)c’,yc') and a first preview point P (x)p,yp) The second preview point is P' (x)p’,yp’) And C' P is the planned path,the direction P from C 'is the positive direction of the planned path, the difference value of the horizontal coordinates of the current position C and the expected position C' is a horizontal deviation delta x, the delta x is a negative value when the current position C is deviated to the left compared with the expected position C ', and the delta x is a positive value when the current position C of the vehicle is deviated to the right compared with the expected position C'; the line segment CP is an ideal straight line correction course of the vehicle track, the positive direction points to P from C, an included angle formed by the positive direction of the CP and the positive direction of the planned path C 'P is an ideal straight line correction course angle, the ideal straight line correction course angle is a negative value when the positive direction of the CP is left relative to the positive direction of the C' P, and the ideal straight line correction course angle is a positive value when the positive direction of the CP is right; the real-time course of the vehicle is CE, the positive direction points to E from C, an included angle formed by the positive direction of the CE and the positive direction of the planned path C 'P is course deviation delta theta, when the positive direction of the CE deviates to the left relative to the positive direction of the C' P, the delta theta is a negative value, and when the positive direction deviates to the right, the delta theta is a positive value; the circular arc CP is an arc correction path; in the field plane coordinate system xoy, the current position of the vehicle is C (x) c,yc) The desired position is C' (x)c’,yc') and the preview point position is P' (x)p,yp) The lateral deviation is delta x, the course deviation is delta theta, the line segment CP is an ideal straight line correction course of the vehicle track, the circular arc CP is an arc correction course, and the line segment CE is a real-time course of the vehicle;
when the vehicle course deviation delta theta is larger than the ideal straight line correction course angle, namely CE is on the right side of CP, and the transverse deviation delta x is a positive value, a small arc path tracking algorithm is adopted;
when the vehicle course deviation delta theta is larger than the ideal straight line correction course angle, namely CE is on the right side of CP, and the transverse deviation delta x is a negative value, a large circular arc path tracking algorithm is adopted;
when the vehicle course deviation delta theta is smaller than the ideal straight line correction course angle, namely CE is on the left side of CP, and the transverse deviation delta x is a negative value, a small arc path tracking algorithm is adopted;
when the vehicle course deviation delta theta is smaller than the ideal straight line correction course angle, namely CE is on the left side of the CP, and the transverse deviation delta x is a positive value, a large circular arc path tracking algorithm is adopted;
when the vehicle course deviation delta theta is equal to the ideal straight line correction course angle, the steering wheel is back to the right and the vehicle runs according to the current course angle.
2. The improved pure track control method for ground vehicle path tracking as claimed in claim 1 wherein said small arc path tracking algorithm is implemented and modified by the steps of:
Step one), each control period is 1 external circulation large period, the 1 external circulation large period comprises a plurality of internal circulation small periods, the default of the number of internal circulation times is set to be 4, and the number of the internal circulation times can be adjusted according to actual needs;
step two), obtaining a first group of navigation positioning data in a new outer circulation period, determining a coordinate of a point P of a first pre-aiming point, calculating a circle center radius corresponding to a small circular arc, and converting the circle center radius into an expected corner of a front wheel;
step three), controlling the front wheels of the vehicle to steer according to the expected turning angle of the front wheels, and enabling the vehicle to start to run along the CP circular arc route;
step four), monitoring the course deviation delta theta and the transverse deviation delta x of the vehicle in an inner circulation small period, if the delta theta x delta x is larger than 0, continuing to drive along the CP circular arc route, judging whether the position of the vehicle is on the inner side or the outer side of the CP circular arc, and performing small-amplitude adjustment on the front wheel steering according to the judgment result to correct the actual track of the vehicle; if delta theta, delta x and delta x are not more than 0, entering a small internal circulation period II;
step five), changing the pre-aiming point from a first pre-aiming point P to a second pre-aiming point P 'in an inner circulation small period, judging the relation between the real-time course CE of the vehicle and a new ideal straight line correction course CP' and the positive and negative of a transverse deviation delta x, and if the CE is positioned at the left side of the CP 'and delta x is less than 0, or the CE is positioned at the right side of the CP' and delta x is more than 0, continuing to drive along the circular arc course of the CP; if CE is on the left side of CP 'and delta x is greater than 0, or CE is on the right side of CP' and delta x is less than 0, then entering into inner loop small period;
Step six), controlling the front wheel to be aligned in the inner circulation small period (c), enabling the vehicle to run according to the new ideal linear course CP ', and performing small-amplitude adjustment on the actual track of the vehicle according to the relative position relationship between the real-time position of the vehicle and the CP';
step seven), repeating the steps four) to six) until the external circulation large period is finished.
3. The improved pure track control method for ground vehicle path tracking according to claim 1, characterized in that said great circle path tracking algorithm is implemented by the following steps:
step one), each control period is 1 external cycle, 1 external cycle large period comprises a plurality of internal cycle small periods, the number of internal cycle times is set to be 4 by default, and the internal cycle times can be adjusted according to actual needs;
step two), obtaining a first group of navigation positioning data in a new outer circulation large period, determining a first pre-aiming point P, calculating the circle center radius corresponding to the large circular arc, and converting the circle center radius into a front wheel expected corner;
step three), controlling the front wheels of the vehicle to steer according to the expected turning angle of the front wheels, and enabling the vehicle to start to run along the CP circular arc route;
step four), monitoring the course deviation delta theta and the transverse deviation delta x of the vehicle in an inner circulation small period, if the delta theta x delta x is less than 0, continuing to drive along the CP circular arc route, judging whether the position of the vehicle is on the inner side or the outer side of the CP circular arc, and performing small-amplitude adjustment on the front wheel steering according to the judgment result to correct the actual track of the vehicle; if delta theta and delta x are more than or equal to 0, entering a small internal circulation period II;
Step five), controlling the front wheel of the vehicle to be aligned in an inner circulation small period II, directly continuing to run according to a course angle of 0 degree, and carrying out small adjustment on the actual track of the vehicle according to the real-time position of the vehicle;
step six), repeating the steps four) to five) until the external circulation large period is finished.
4. An improved pure tracking control method for ground vehicle path tracking according to any of claims 2-3, characterized in that the preview point determination method is: firstly determining the forward looking distance, then searching the point closest to the current position of the vehicle on the planned path, taking the closest point as a starting point, forwardly intercepting the forward looking distance to obtain a first forward aiming point P, and forwardly intercepting twice the forward looking distance to obtain a second forward aiming point P'.
5. The improved pure tracking control method for ground vehicle path tracking according to claim 4, characterized in that the forward looking distance can be a preset value or obtained by a dynamic calculation method considering vehicle speed and planned path curvature.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811066889.8A CN109388140B (en) | 2018-09-13 | 2018-09-13 | Improved pure tracking control method for ground vehicle path tracking |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811066889.8A CN109388140B (en) | 2018-09-13 | 2018-09-13 | Improved pure tracking control method for ground vehicle path tracking |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109388140A CN109388140A (en) | 2019-02-26 |
| CN109388140B true CN109388140B (en) | 2021-08-03 |
Family
ID=65418917
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811066889.8A Active CN109388140B (en) | 2018-09-13 | 2018-09-13 | Improved pure tracking control method for ground vehicle path tracking |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109388140B (en) |
Families Citing this family (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110955245B (en) * | 2019-12-09 | 2021-06-08 | 深圳市银星智能科技股份有限公司 | Path tracking method and device, mobile robot and non-transitory computer readable storage medium |
| CN113460033B (en) * | 2020-03-31 | 2023-04-07 | 华为技术有限公司 | Automatic parking method and device |
| CN112540617B (en) * | 2020-12-16 | 2022-10-18 | 天奇自动化工程股份有限公司 | Navigation deviation rectifying method for mobile platform |
| CN112678726B (en) * | 2020-12-18 | 2022-07-29 | 江苏智库智能科技有限公司 | Forklift AGV kinematics model-based goods taking positioning method and system |
| CN112527000B (en) * | 2020-12-23 | 2021-10-26 | 中南大学 | Local path planning method and system for mine underground intelligent driving |
| CN113252040B (en) * | 2021-05-08 | 2022-10-18 | 云南财经大学 | Improved AGV trolley two-dimensional code arc navigation method |
| CN113467460B (en) * | 2021-07-09 | 2024-03-12 | 江苏大学 | Agricultural machine path tracking method and system based on double-circular forward looking distance |
| CN113741463B (en) * | 2021-09-07 | 2023-11-10 | 北京理工大学 | Fixed-point and directional parking control method and system for unmanned ground maneuvering platform |
| CN114093164B (en) * | 2021-11-15 | 2022-08-19 | 上海市城乡建设和交通发展研究院 | Dynamic traffic flow identification and correction method, device and equipment based on vehicle track |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3993156A (en) * | 1975-02-19 | 1976-11-23 | Robert Bosch G.M.B.H. | Guidance system for guiding trackless vehicles along a path defined by an A-C energized conductor |
| JP2008230484A (en) * | 2007-03-22 | 2008-10-02 | Yokogawa Denshikiki Co Ltd | Automatic steering device and automatic steering method |
| CN105892459A (en) * | 2016-04-01 | 2016-08-24 | 清华大学 | Non-time-based differential drive robot set-point tracking control method |
| CN106950955A (en) * | 2017-03-17 | 2017-07-14 | 武汉理工大学 | Based on the ship's track-keepping control method for improving LOS bootstrap algorithms |
| CN107643763A (en) * | 2017-09-20 | 2018-01-30 | 中国航空工业集团公司沈阳飞机设计研究所 | A kind of aircraft is unpowered to give an encore energy track integrated control method |
| CN107656527A (en) * | 2017-10-13 | 2018-02-02 | 南京农业大学 | The gain switching nonlinear control method of agri-vehicle path trace |
| CN107943060A (en) * | 2017-12-29 | 2018-04-20 | 上海司南卫星导航技术股份有限公司 | A kind of automatic pilot, method and computer-readable medium along tracking straight line guiding vehicle |
-
2018
- 2018-09-13 CN CN201811066889.8A patent/CN109388140B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3993156A (en) * | 1975-02-19 | 1976-11-23 | Robert Bosch G.M.B.H. | Guidance system for guiding trackless vehicles along a path defined by an A-C energized conductor |
| JP2008230484A (en) * | 2007-03-22 | 2008-10-02 | Yokogawa Denshikiki Co Ltd | Automatic steering device and automatic steering method |
| CN105892459A (en) * | 2016-04-01 | 2016-08-24 | 清华大学 | Non-time-based differential drive robot set-point tracking control method |
| CN106950955A (en) * | 2017-03-17 | 2017-07-14 | 武汉理工大学 | Based on the ship's track-keepping control method for improving LOS bootstrap algorithms |
| CN107643763A (en) * | 2017-09-20 | 2018-01-30 | 中国航空工业集团公司沈阳飞机设计研究所 | A kind of aircraft is unpowered to give an encore energy track integrated control method |
| CN107656527A (en) * | 2017-10-13 | 2018-02-02 | 南京农业大学 | The gain switching nonlinear control method of agri-vehicle path trace |
| CN107943060A (en) * | 2017-12-29 | 2018-04-20 | 上海司南卫星导航技术股份有限公司 | A kind of automatic pilot, method and computer-readable medium along tracking straight line guiding vehicle |
Non-Patent Citations (3)
| Title |
|---|
| 交通信息影响下的动态路径选择模型研究;石小法等;《公路交通科技》;20000831;第17卷(第4期);第35-37页 * |
| 吊舱推进的小型水面无人船航迹控制系统设计;燕聃聃等;《船海工程》;20170831;第46卷(第4期);第210-214页 * |
| 拖拉机路径跟踪的变论域模糊控制;陈志刚等;《江苏农业科学》;20180716;第46卷(第13期);第216-219页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109388140A (en) | 2019-02-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109388140B (en) | Improved pure tracking control method for ground vehicle path tracking | |
| CN107390691B (en) | AGV path tracking method | |
| CN108725585B (en) | Trajectory tracking control method and device for autonomous parking of vehicle | |
| CN113204236B (en) | Intelligent agent path tracking control method | |
| CN104571112B (en) | Pilotless automobile lateral control method based on turning curvature estimation | |
| US9499197B2 (en) | System and method for vehicle steering control | |
| CN110109451B (en) | Novel geometric path tracking algorithm considering path curvature | |
| CN107943020B (en) | Automatic deviation rectifying method for tire crane cart | |
| KR101196374B1 (en) | Path planning system for mobile robot | |
| US11334083B2 (en) | Route tracking method for mobile vehicle | |
| CN109947123A (en) | A kind of unmanned plane path trace and automatic obstacle avoiding method based on line of sight guidance rule | |
| CN108732921B (en) | Transverse extension preview switching control method for automatic driving automobile | |
| CN107037818A (en) | A kind of path following method of pilotless automobile | |
| CN109656250A (en) | A kind of path following method of laser fork truck | |
| CN111487976B (en) | Backing track tracking method | |
| CN113815646B (en) | Intelligent driving method of vehicle, vehicle and readable storage medium | |
| CN111158379B (en) | Steering wheel zero-bias self-learning unmanned vehicle track tracking method | |
| CN106647770A (en) | Field turning path planning and control method used for farm machinery driverless driving | |
| CN110789530B (en) | Four-wheel independent steering-independent driving vehicle trajectory tracking method and system | |
| CN110928290A (en) | Quintic curve path planning method and lane center line maintenance method | |
| CN112109732A (en) | Intelligent driving self-adaptive curve pre-aiming method | |
| CN113406960B (en) | Real-time path planning and control method for ground steering of agricultural unmanned vehicle | |
| CN113844535B (en) | Active steering control method based on steering wheel torque | |
| Wang et al. | Path tracking control for autonomous harvesting robots based on improved double arc path planning algorithm | |
| CN113467475B (en) | Mecanum wheel omnidirectional mobile robot track tracking sliding mode control method |
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 |