CN107901917B - A kind of automatic driving vehicle Trajectory Tracking Control method based on sliding coupling estimation of trackslipping - Google Patents
A kind of automatic driving vehicle Trajectory Tracking Control method based on sliding coupling estimation of trackslipping Download PDFInfo
- Publication number
- CN107901917B CN107901917B CN201711134569.7A CN201711134569A CN107901917B CN 107901917 B CN107901917 B CN 107901917B CN 201711134569 A CN201711134569 A CN 201711134569A CN 107901917 B CN107901917 B CN 107901917B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- slip
- wheel
- coordinate system
- speed
- 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 24
- 230000008878 coupling Effects 0.000 title claims abstract description 22
- 238000010168 coupling process Methods 0.000 title claims abstract description 22
- 238000005859 coupling reaction Methods 0.000 title claims abstract description 22
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000009795 derivation Methods 0.000 claims description 3
- 238000006467 substitution reaction Methods 0.000 claims description 3
- 238000013178 mathematical model Methods 0.000 abstract 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
- B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
Landscapes
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Human Computer Interaction (AREA)
- Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Acyclic And Carbocyclic Compounds In Medicinal Compositions (AREA)
- Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
Abstract
The invention discloses the automatic driving vehicle Trajectory Tracking Control methods based on sliding coupling estimation of trackslipping, the data that this method is detected according to the coefficient that trackslips, the motion mathematical model expression formula of slip rate and GPS-INS, desired trajectory, desired speed and the expectation yaw velocity information provided again according to automatic driving vehicle decision-making level, calculate the coefficient that trackslips, the numerical value of slip rate, then counter to be updated in the kinematics model of automatic driving vehicle, the vehicle wheel rotational speed for realizing track following is compensated and calculated, achievees the purpose that accurately to track desired trajectory.The invention has the advantages that slippage of trackslipping can constantly be calculated, the actual motion state of automatic driving vehicle more really, is accurately described and characterizes, so as to effectively accurately follow desired trajectory.
Description
The technical field is as follows:
the invention relates to the technical field of unmanned vehicles, in particular to an unmanned vehicle trajectory tracking control method based on slip-slip coupling estimation.
Background art:
unmanned vehicles are being focused and developed by many research institutes and enterprises in the world as an important direction and trend for future vehicle development. In the key technology of vehicle control of the unmanned vehicle, trajectory tracking control is a core technical method for realizing the unmanned vehicle to run according to a planned trajectory, and the control precision and the control robustness of the trajectory tracking control determine whether the unmanned vehicle can reach a specified destination according to an expected trajectory.
Currently, in the field of trajectory tracking of unmanned vehicles, a control method of the unmanned vehicle is based on a vehicle kinematic model in a rational state, that is, a vehicle kinematic model under the condition that wheels of the unmanned vehicle are not slipped and slipped is assumed, however, when the unmanned vehicle runs on an actual road condition, the wheels are commonly slipped and slipped, and particularly, the wheels are particularly obvious when the unmanned vehicle runs on a sand-gravel road surface and an ice-snow road surface, and therefore, based on the kinematic model in an ideal state, the slip and slip amount cannot be calculated in real time, and therefore, the expected trajectory cannot be effectively and accurately tracked.
The invention content is as follows:
the invention aims to solve the technical problem of providing a track tracking control method of the unmanned vehicle based on slip coupling estimation, which can calculate slip slippage from time to time and describe and represent the actual motion state of the unmanned vehicle more truly and accurately so as to effectively and accurately follow the expected track.
The invention provides a track tracking control method of an unmanned vehicle based on slip-slip coupling estimation, which comprises the following steps:
step 1: receiving an expected track and an expected track tracking speed signal planned by a decision layer of the unmanned vehicle, setting an initial pre-aiming distance d, and selecting a point which is away from the vehicle by the pre-aiming distance d in the expected track as a pre-aiming point qdReading current state data of the vehicle collected by the GPS-INS combined positioning system;
step 2: establishing a kinematics model based on wheel slip and body slip of the unmanned vehicle:
defining a ground inertia coordinate system sigma I, a vehicle body coordinate system sigma b,
pose of the vehicle body under an inertial coordinate system: q. q.sI＝[x1 y1 θ1]T
Pose of the vehicle body under the vehicle body coordinate system: q. q.sb＝[xb yb θb]T
And thetaI＝θbθ, is the vehicle heading angle,
the speed conversion relation between the inertial coordinate system and the vehicle body coordinate system is as follows:
is provided with
Then
Under a vehicle coordinate system, defining the length direction of a vehicle body as a longitudinal direction x, the width direction of the vehicle body as a transverse direction y, and the slip coefficient of a left wheel as slThe slip coefficient of the right wheel is srRadius of wheel r, left wheel rotation speed omegalLinear velocity vlRotation speed omega of right wheel of vehicle bodyrLinear velocity vrThe longitudinal speed of the vehicle is vbxThe yaw rate of the vehicle is omega, the width of the center of the wheel is 2L,
the sliding coefficient of the whole vehicle sliding is i, and the vehicle transverse speed is vby，
Establishing a vehicle kinematic model based on slip, spin and slip under an inertial coordinate system:
and step 3: according to the vehicle kinematic model based on the slip and slip, the slip coefficient s of the left wheel is solvedlCoefficient of slip s of the right wheelrExpression (c):
and 4, step 4: establishing a track tracking error model under vehicle coordinates:
namely, it is
Wherein,representing the track error in the vehicle body coordinate system,representing the pose of the expected track point in an inertial coordinate system, i.e. the pre-aiming point qdThe pose of (a);representing the current pose of the vehicle in an inertial coordinate system;
and 5: and (3) carrying out derivation on the tracking error model to obtain a tracking error state equation:
step 6: according to the state equation of the track tracking error in the step 5, adopting a control law of track tracking control based on slip coefficients:
wherein v is1For the speed control input of the right wheel, v2Is the speed control input to the left wheel,
wherein the gain factor k is controlled1、k2、k3Greater than zero and having an upper bound;
and 7: controlling the vehicle to run according to the input of the control rate in the step 6, and then obtaining the current pose of the vehicle in an inertial coordinate system according to the data detected and recorded by the GPS-INSI.e. qc＝qIVelocity in inertial frameThe yaw angular speed omega of the vehicle body is obtained by measuring the rotating speeds omega of the left and the right wheels according to the encoder1、ωr；
And 8: according to v under the vehicle body coordinate systembx、vbyV and under the inertial coordinate systemIx、vIyThe relationship is as follows:
calculate vbx、vbyAnd slip ratioAnd isThen i is put in,ω1、ωr、S in step 3l、srA calculation formula of sl、sr；
And step 9: s calculated in step 8l、srDesired velocity vdDesired yaw rate ωdControl law substituting in step 6And selecting a control gain coefficient k1、k2、k3To be calculatedSolving the required rotation speeds of the wheels on both sides of the control vehicle under the estimation of the slip-slip coupling of the driving wheels in the substitution step 2Is marked as
Step 10: the rotating speeds of the wheels on the two sides of the vehicle calculated according to the step 9The vehicle control unit sends the calculated wheel rotating speed signal to an actuator for driving the wheel and controls the wheel to move at the speed;
step 11: and (5) repeatedly executing the actions from the step 4 to the step 10, and finally realizing the accurate tracking of the expected track at the expected speed.
Preferably, the unmanned vehicle track tracking control method based on slip-slip coupling estimation is characterized in that the pose q of the expected track is obtaineddDesired velocity vdAnd desired yaw rate ωdAre all data output by the decision layer.
Preferably, according to the track tracking control method of the unmanned vehicle based on slip-slip coupling estimation, the unmanned vehicle is a two-wheel vehicle, a four-wheel vehicle or a six-wheel vehicle.
Preferably, according to the method for controlling the trajectory tracking of the unmanned vehicle based on the slip-slip coupling estimation, the unmanned vehicle is engine-driven or motor-driven.
Preferably, according to the method for controlling the trajectory tracking of the unmanned vehicle based on slip-slip coupling estimation, the encoder is an absolute encoder.
The invention has the beneficial effects that:
1. the slip coefficient and slip rate model of the unmanned vehicle are introduced into the kinematics model of the unmanned vehicle, so that the actual motion state of the unmanned vehicle can be described and represented more truly and accurately;
2. the model can solve the mathematical relation expression of slip coefficient and slip rate, thus providing a model for calculating the slip coefficient and the slip rate;
3. according to the track tracking control method based on slip-slip coupling estimation, the numerical values of the slip coefficient and the slip rate can be calculated according to the data obtained by the mathematical expression of the slip coefficient and the slip rate and the GPS-INS detection and the expected track, the expected speed and the expected yaw angular speed information given by the decision layer of the unmanned vehicle, and then the numerical values are reversely substituted into the kinematic model of the unmanned vehicle to compensate and calculate the wheel rotating speed for realizing track tracking, so that the aim of accurately tracking the expected track is fulfilled.
4. The track tracking control method based on slip-slip coupling estimation provided by the invention can calculate the real conditions of vehicle slip and wheel slip at any time, and improve the environmental adaptability of the unmanned vehicle track tracking, such as icy snow, slippery wet and soft slippery road surface, and still can accurately track the expected track, therefore, the track tracking control method greatly improves the track tracking accuracy of the unmanned vehicle in a complex road environment.
Description of the drawings:
FIG. 1 is a schematic representation of coordinates in the present invention;
FIG. 2 is a schematic diagram of a tracking error model in the present invention;
FIG. 3 is a schematic view of a slip model in the present invention;
fig. 4 is a control block schematic of the present invention.
The specific embodiment is as follows:
the following describes an unmanned vehicle trajectory tracking control method based on slip-slip coupling estimation according to the present invention with reference to the accompanying drawings and specific embodiments:
the unmanned vehicle comprises a GPS-INS combined positioning system, an encoder for acquiring wheel rotation speed data and a vehicle control unit for sending the rotation speed of a driving motor to the vehicle control unit.
As shown in fig. 1, fig. 2, fig. 3 and fig. 4, the invention relates to a method for tracking and controlling a track of an unmanned vehicle based on slip-slip coupling estimation, which comprises the following steps:
step 1: receiving an expected track and an expected track tracking speed signal planned by a decision layer of the unmanned vehicle, setting an initial pre-aiming distance d, and selecting a point which is away from the vehicle by the pre-aiming distance d in the expected track as a pre-aiming point qdReading the current state data of the vehicle collected by the GPS-INS combined positioning system;
step 2: establishing a kinematics model based on wheel slip and body slip of the unmanned vehicle:
defining a ground inertia coordinate system sigma I, a vehicle body coordinate system sigma b,
pose of the vehicle body under an inertial coordinate system: q. q.sI＝[xI yI θI]T
Pose of the vehicle body under the vehicle body coordinate system: q. q.sb＝[xb yb θb]T
And thetaI＝θbθ, is the vehicle heading angle,
the speed conversion relation between the inertial coordinate system and the vehicle body coordinate system is as follows:
is provided with
Then
Under a vehicle coordinate system, defining the length direction of a vehicle body as a longitudinal direction x, the width direction of the vehicle body as a transverse direction y, and the slip coefficient of a left wheel as slThe slip coefficient of the right wheel is srRadius of wheel r, left wheel rotation speed omegalLinear velocity vlRotation speed omega of right wheel of vehicle bodyrLinear velocity vrThe longitudinal speed of the vehicle is vbxThe yaw rate of the vehicle is omega, the width of the center of the wheel is 2L,
the sliding coefficient of the whole vehicle sliding is i, and the vehicle transverse speed is vby，
Establishing a vehicle kinematic model based on slip, spin and slip under an inertial coordinate system:
and step 3: according to the vehicle kinematic model based on the slip and slip, the slip coefficient s of the left wheel is solvedlCoefficient of slip s of the right wheelrExpression (c):
and 4, step 4: establishing a track tracking error model under vehicle coordinates:
namely, it is
Wherein,representing the track error in the vehicle body coordinate system,representing the pose of the expected track point in an inertial coordinate system, i.e. the pre-aiming point qdThe pose of (a);representing the current pose of the vehicle in an inertial coordinate system;
and 5: and (3) carrying out derivation on the tracking error model to obtain a tracking error state equation:
step 6: according to the state equation of the track tracking error in the step 5, adopting a control law of track tracking control based on slip coefficients:
wherein v is1For the speed control input of the right wheel, v2Is the speed control input to the left wheel,
wherein the gain factor k is controlled1、k2、k3Greater than zero and having an upper bound;
and 7: controlling the vehicle to run according to the input of the control rate in the step 6, and then obtaining the current pose of the vehicle in an inertial coordinate system according to the data detected and recorded by the GPS-INSI.e. qc＝qIVelocity in inertial frameThe yaw angular speed omega of the vehicle body is obtained by measuring the rotating speeds omega of the left and the right wheels according to the encoderl、ωr；
And 8: according to v under the vehicle body coordinate systembx、vbyV and under the inertial coordinate systemlx、vIyThe relationship is as follows:
calculate vbx、vbyAnd slip ratioAnd isThen i is put in,ωl、ωr、S in step 3l、srA calculation formula of sl、sr；
And step 9: s calculated in step 8l，srDesired velocity vdDesired yaw rate ωdControl law substituting in step 6And selecting a control gain coefficient k1、k2、k3To be calculatedSolving the required rotation speeds of the wheels on both sides of the control vehicle under the estimation of the slip-slip coupling of the driving wheels in the substitution step 2Is marked as
Step 10: the rotating speeds of the wheels on the two sides of the vehicle calculated according to the step 9The vehicle control unit sends the calculated wheel rotating speed signal to an actuator for driving the wheel and controls the wheel to move at the speed;
step 11: and (5) repeatedly executing the actions from the step 4 to the step 10, and finally realizing the accurate tracking of the expected track at the expected speed.
Preferably, in the present invention, the pose q of the desired trajectorydDesired velocity vdAnd desired yaw rate ωdAre all data output by the decision layer.
Preferably, in the present invention, the unmanned vehicle is a two-wheel or four-wheel or six-wheel vehicle.
Preferably, in the present invention, the unmanned vehicle is engine-driven or motor-driven.
Preferably, in the present invention, the encoder is an absolute encoder.
The above-described embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements of the technical solution of the present invention may be made by those skilled in the art without departing from the spirit of the present invention, which is defined by the claims.
Claims (5)
1. A track tracking control method of an unmanned vehicle based on slip-slip coupling estimation is characterized by comprising the following steps: the method comprises the following steps:
step 1: receiving an expected track and an expected track tracking speed signal planned by a decision layer of the unmanned vehicle, setting an initial pre-aiming distance d, and selecting a point which is away from the vehicle by the pre-aiming distance d in the expected track as a pre-aiming point qdReading current state data of the vehicle collected by the GPS-INS combined positioning system;
step 2: establishing a kinematics model based on wheel slip and body slip of the unmanned vehicle:
defining a ground inertia coordinate system sigma I, a vehicle body coordinate system sigma b,
pose of the vehicle body under an inertial coordinate system: q. q.sI＝[xI yI θI]T
Pose of the vehicle body under the vehicle body coordinate system: q. q.sb＝[xb yb θb]T
And thetaI＝θbθ, is the vehicle heading angle,
the speed conversion relation between the inertial coordinate system and the vehicle body coordinate system is as follows:
is provided with
Then
Under a vehicle coordinate system, defining the length direction of a vehicle body as a longitudinal direction x, the width direction of the vehicle body as a transverse direction y, and the slip coefficient of a left wheel as slThe slip coefficient of the right wheel is srRadius of wheel r, left wheel rotation speed omegalLinear velocity vlRotation speed omega of right wheel of vehicle bodyrLinear velocity vrThe longitudinal speed of the vehicle is vbxThe yaw rate of the vehicle is omega, the width of the center of the wheel is 2L,
the sliding coefficient of the whole vehicle sliding is i, and the vehicle transverse speed is vby，
Establishing a vehicle kinematic model based on slip, spin and slip under an inertial coordinate system:
and step 3: according to the vehicle kinematic model based on the slip and slip, the slip coefficient s of the left wheel is solvedlCoefficient of slip s of the right wheelrExpression (c):
and 4, step 4: establishing a track tracking error model under vehicle coordinates:
namely, it is
Wherein,representing the track error in the vehicle body coordinate system,representing the pose of the expected track point in an inertial coordinate system, i.e. the pre-aiming point qdThe pose of (a);representing the current pose of the vehicle in an inertial coordinate system;
and 5: and (3) carrying out derivation on the tracking error model to obtain a tracking error state equation:
step 6: according to the state equation of the track tracking error in the step 5, adopting a control law of track tracking control based on slip coefficients:
wherein v is1For the speed control input of the right wheel, v2For the speed control input of the left wheel, vcFor vehicle longitudinal speed control input, ωcIs a vehicle yaw rate control input,
wherein the gain factor k is controlled1、k2、k3Greater than zero and having an upper bound;
and 7: controlling the vehicle to run according to the input of the control rate in the step 6, and then obtaining the vehicle according to the data detected and recorded by the GPS-INSCurrent position and attitude of vehicle under inertial coordinate systemI.e. qc＝qIVelocity in inertial frameThe yaw angular speed omega of the vehicle body is obtained by measuring the rotating speeds omega of the left and the right wheels according to the encoderl、ωr；
And 8: according to v under the vehicle body coordinate systembx、vbyV and under the inertial coordinate systemIx、vIyThe relationship is as follows:
calculate vbx、vbyAnd slip ratioAnd isThen i is put in,ωl、ωr、S in step 3l、srA calculation formula of sl、sr；
And step 9: s calculated in step 81、srDesired velocity vdDesired yaw rate ωdControl law substituting in step 6And selecting a control gain coefficient k1、k2、k3Will countCalculatingSolving the required rotation speeds of the wheels on both sides of the control vehicle under the estimation of the slip-slip coupling of the driving wheels in the substitution step 2Is marked as
Step 10: the rotating speeds of the wheels on the two sides of the vehicle calculated according to the step 9The vehicle control unit sends the calculated wheel rotating speed signal to an actuator for driving the wheel and controls the wheel to move at the speed;
step 11: and (5) repeatedly executing the actions from the step 4 to the step 10, and finally realizing the accurate tracking of the expected track at the expected speed.
2. The unmanned vehicle trajectory tracking control method based on slip-slip coupling estimation of claim 1, wherein: pose q of the expected trajectorydDesired velocity vdAnd desired yaw rate ωdAre all data output by the decision layer.
3. The unmanned vehicle trajectory tracking control method based on slip-slip coupling estimation of claim 1, wherein: the unmanned vehicle is a two-wheel vehicle, a four-wheel vehicle or a six-wheel vehicle.
4. The unmanned vehicle trajectory tracking control method based on slip-slip coupling estimation of claim 1, wherein: the unmanned vehicle is driven by an engine or a motor.
5. The unmanned vehicle trajectory tracking control method based on slip-slip coupling estimation of claim 1, wherein: the encoder is an absolute encoder.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711134569.7A CN107901917B (en) | 2017-11-16 | 2017-11-16 | A kind of automatic driving vehicle Trajectory Tracking Control method based on sliding coupling estimation of trackslipping |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711134569.7A CN107901917B (en) | 2017-11-16 | 2017-11-16 | A kind of automatic driving vehicle Trajectory Tracking Control method based on sliding coupling estimation of trackslipping |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107901917A CN107901917A (en) | 2018-04-13 |
| CN107901917B true CN107901917B (en) | 2019-07-26 |
Family
ID=61844407
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711134569.7A Active CN107901917B (en) | 2017-11-16 | 2017-11-16 | A kind of automatic driving vehicle Trajectory Tracking Control method based on sliding coupling estimation of trackslipping |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107901917B (en) |
Families Citing this family (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108098770A (en) * | 2017-12-14 | 2018-06-01 | 张辉 | A kind of Trajectory Tracking Control method of mobile robot |
| CN108897319A (en) * | 2018-06-23 | 2018-11-27 | 广州市柯乐名迪电子科技有限公司 | Automatic Pilot method, apparatus and system based on digital geometry figure |
| CN110377017B (en) * | 2018-08-15 | 2022-11-08 | 北京京东乾石科技有限公司 | Method and device for controlling unmanned equipment to turn |
| CN110171416B (en) * | 2018-09-28 | 2021-11-12 | 腾讯科技（深圳）有限公司 | Vehicle running control method and device, computer readable medium and electronic equipment |
| CN109606352B (en) * | 2018-11-22 | 2020-06-26 | 江苏大学 | Vehicle path tracking and stability coordination control method |
| CN110160527B (en) * | 2019-05-06 | 2020-08-28 | 安徽红蝠智能科技有限公司 | Mobile robot navigation method and device |
| CN110703754B (en) * | 2019-10-17 | 2021-07-09 | 南京航空航天大学 | Path and speed highly-coupled trajectory planning method for automatic driving vehicle |
| CN111142520B (en) * | 2019-12-24 | 2022-03-11 | 中国科学院合肥物质科学研究院 | Planning and control method of crawler-type unmanned vehicle on cliff obstacle road |
| CN113341996A (en) * | 2021-06-25 | 2021-09-03 | 江苏高瞻数据科技有限公司 | Intelligent control device and method for unmanned vehicle to track preset track |
| CN113734317A (en) * | 2021-09-18 | 2021-12-03 | 北京控制工程研究所 | Kinematic positioning method for swinging arm suspension frame structure inspection device |
| CN115158332B (en) * | 2022-07-25 | 2024-09-13 | 东风越野车有限公司 | Slip rate determining method and vehicle control system of four-wheel steering vehicle |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102358287A (en) * | 2011-09-05 | 2012-02-22 | 北京航空航天大学 | Trajectory tracking control method used for automatic driving robot of vehicle |
| CN106671982A (en) * | 2017-01-09 | 2017-05-17 | 厦门大学 | Multi-intelligent agent based unmanned electric car automatic overtaking system and method |
| CN106926840A (en) * | 2017-03-13 | 2017-07-07 | 北京理工大学 | A kind of vehicle extremal dynamic model Trajectory Tracking Control System |
| CN108098770A (en) * | 2017-12-14 | 2018-06-01 | 张辉 | A kind of Trajectory Tracking Control method of mobile robot |
-
2017
- 2017-11-16 CN CN201711134569.7A patent/CN107901917B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102358287A (en) * | 2011-09-05 | 2012-02-22 | 北京航空航天大学 | Trajectory tracking control method used for automatic driving robot of vehicle |
| CN106671982A (en) * | 2017-01-09 | 2017-05-17 | 厦门大学 | Multi-intelligent agent based unmanned electric car automatic overtaking system and method |
| CN106926840A (en) * | 2017-03-13 | 2017-07-07 | 北京理工大学 | A kind of vehicle extremal dynamic model Trajectory Tracking Control System |
| CN108098770A (en) * | 2017-12-14 | 2018-06-01 | 张辉 | A kind of Trajectory Tracking Control method of mobile robot |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107901917A (en) | 2018-04-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107901917B (en) | A kind of automatic driving vehicle Trajectory Tracking Control method based on sliding coupling estimation of trackslipping | |
| CN108098770A (en) | A kind of Trajectory Tracking Control method of mobile robot | |
| CN107963126B (en) | Large-curvature automatic driving steering control method for multi-axle steering vehicle | |
| CN108725585B (en) | Trajectory tracking control method and device for autonomous parking of vehicle | |
| Dominguez et al. | Comparison of lateral controllers for autonomous vehicle: Experimental results | |
| CN104881030B (en) | Unmanned vehicle side Longitudinal data tracking and controlling method based on fast terminal sliding formwork principle | |
| Ding et al. | Event-triggered vehicle sideslip angle estimation based on low-cost sensors | |
| Son et al. | Robust multirate control scheme with predictive virtual lanes for lane-keeping system of autonomous highway driving | |
| Pentzer et al. | Model‐based prediction of skid‐steer robot kinematics using online estimation of track instantaneous centers of rotation | |
| CN106020200A (en) | AGV driven by wheel hub motor and its path planning method | |
| CN112486156B (en) | Automatic tracking control system and control method for vehicle | |
| Kang et al. | Multirate lane-keeping system with kinematic vehicle model | |
| US8930058B1 (en) | System and method for controlling a vehicle traveling along a path | |
| US10214223B1 (en) | Method and apparatus for determining vehicle location based on motor feedback | |
| CN105172793B (en) | The pose evaluation method of autonomous driving vehicle | |
| CN109823393A (en) | A kind of intelligent driving Vehicle tracing control method | |
| Setiawan et al. | Path tracking controller design of four wheel independent steering automatic guided vehicle | |
| Liu et al. | Slip-aware motion estimation for off-road mobile robots via multi-innovation unscented Kalman filter | |
| CN107697065A (en) | Automatic parking control method for general parking scene | |
| Kegelman | Learning from professional race car drivers to make automated vehicles safer | |
| JP6216545B2 (en) | Autonomous traveling vehicle, autonomous vehicle traveling system, and autonomous traveling vehicle control method | |
| CN113589685B (en) | Vehicle moving robot control system and method based on deep neural network | |
| KR102560143B1 (en) | Driving characteristics modeling method of logistics robot for virtual simulation | |
| Choi et al. | Optimal sensor fusion and position control of a low-price self-driving vehicle in short-term operation conditions | |
| Gao et al. | Path Tracking Control of Micro-tracked mobile robot |
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 |