CN110262479A - A kind of estimation of caterpillar tractor kinematics and deviation calibration method - Google Patents

A kind of estimation of caterpillar tractor kinematics and deviation calibration method Download PDF

Info

Publication number
CN110262479A
CN110262479A CN201910448762.0A CN201910448762A CN110262479A CN 110262479 A CN110262479 A CN 110262479A CN 201910448762 A CN201910448762 A CN 201910448762A CN 110262479 A CN110262479 A CN 110262479A
Authority
CN
China
Prior art keywords
tractor
caterpillar tractor
deviation
model
coordinate component
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.)
Pending
Application number
CN201910448762.0A
Other languages
Chinese (zh)
Inventor
孙飞
王海晶
史志中
芦海涛
刘军
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Nanjing Tianchen Li Electronic Technology Co Ltd
Original Assignee
Nanjing Tianchen Li Electronic Technology Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Nanjing Tianchen Li Electronic Technology Co Ltd filed Critical Nanjing Tianchen Li Electronic Technology Co Ltd
Priority to CN201910448762.0A priority Critical patent/CN110262479A/en
Publication of CN110262479A publication Critical patent/CN110262479A/en
Priority to PCT/CN2019/115000 priority patent/WO2020238011A1/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0223Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0276Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
    • G05D1/0278Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/08Control of attitude, i.e. control of roll, pitch, or yaw
    • G05D1/0891Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for land vehicles
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/11Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • G06F17/12Simultaneous equations, e.g. systems of linear equations
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/11Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • G06F17/13Differential equations
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/16Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Theoretical Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Algebra (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Operations Research (AREA)
  • Computing Systems (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)

Abstract

The invention discloses a kind of estimation of caterpillar tractor kinematics and deviation calibration methods, belong to agricultural machinery automatic Pilot technical field, now propose following scheme, it includes the following steps, construct caterpillar tractor kinematics model, in a practical situation, since surface relief changes, GNSS double antenna installation deviation factor, cause heading angle deviation, path trace effect is caused to be deteriorated, for simplified model, it is certain value that heading angle deviation, which can be approximately considered, choose east orientation displacement coordinate component, north orientation displacement coordinate component, tractor speed, north orientation displacement coordinate component, tractor speed, tractor course angle is measured as systematic perspective, the caterpillar tractor kalman Filtering Model of building is nonlinear model.The present invention quickly can accurately estimate the heading angle deviation due to caused by surface relief variation, GNSS antenna installation deviation etc., to compensate to course angle, improve system to the adaptability on ground.

Description

A kind of estimation of caterpillar tractor kinematics and deviation calibration method
Technical field
The present invention relates to agricultural machinery automatic Pilot technical field more particularly to a kind of estimation of caterpillar tractor kinematics and partially Poor calibration method.
Background technique
With the rapid development of GNSS high-precision Technique of Satellite Navigation and Positioning, automatic Pilot and information technology, Modern Agriculture Industry just gradually develops to the direction of Digital Agriculture, precision agriculture.Tractor as a kind of common agricultural equipment, it is information-based, Intelligence degree is of great significance to the development of precision agriculture.
Tractor can be divided into wheeled tractor and caterpillar tractor according to walking manner.Compared with wheeled tractor, Caterpillar tractor has many advantages, such as that contact surface is big, grounding pressure is small, traction adhesion property is good, is not easy to skid, and is more suitable in item Operation in part relatively rugged environment, such as snowfield, hillside, miriness, meadow, plateau have effectively filled up wheeled dilatory The deficiency of machine.However in caterpillar tractor automatic Pilot operation process, since there is a large amount of in actual job environment Uncertain interference, such as complicated state on cultivation farmland ground, kinematics model is inaccurate, GNSS antenna setting angle is inclined The factors such as difference, GPS signal are blocked and reflected, system noise and extraneous environmental noise interfere, cause tractor position and attitude phase Close information and occur abnormal etc., seriously affect caterpillar tractor automatic Pilot control precision, not only cause peasant household's operation intensity and Economic cost increases, and has been greatly reduced agricultural tillage efficiency and land utilization ratio.
The present invention is directed to the problem of caterpillar tractor automatic Pilot control technology, proposes a kind of crawler type and drags The estimation of machine drawing kinematics and deviation calibration method, to realize the accurate estimation of caterpillar tractor position and attitude information, enhancing system The adaptability and anti-interference united to external environment improve caterpillar tractor automated driving system homework precision.The present invention Purpose be then real-time and accurately estimate heading angle deviation, and to course angle by designing suitable estimation method It compensates and corrects, to improve system to the adaptability of environment.
Summary of the invention
The purpose of the present invention is draw in actual job environment due to being interfered by many factors for caterpillar tractor The problem that the control effect risen is poor, homework precision is low, the present invention propose a kind of caterpillar tractor kinematics of anti-interference factor Estimation and deviation calibration method, the algorithm can quickly Accuracy extimate go out since surface relief variation, the installation of GNSS double antenna are inclined Course angle error caused by the factors such as difference, and course angle is compensated, to improve the control of caterpillar tractor automatic Pilot Adaptability of the algorithm to the various environmental disturbances factors such as ground.
To achieve the goals above, present invention employs following technical solutions:
A kind of estimation of caterpillar tractor kinematics and deviation calibration method, include the following steps,
S1 constructs caterpillar tractor kinematics model:
Wherein, x is caterpillar tractor east orientation displacement coordinate component, and y is north orientation displacement coordinate component, and v drags for crawler type Machine drawing travel speed,For caterpillar tractor course angle, ω is caterpillar tractor car body angular speed;
S2: since caterpillar tractor is when being turned to, angular speed is equal at revolver, right wheel and mass center, therefore can derive Out:
Wherein, vlFor the travel speed for left track, vrFor the travel speed for right side track, R is turning radius, and b is Width of the carbody;
S3: simultaneous equations solution can obtain:
S4: it can be released by formula (3) and (6):
In formula, u is left and right track speed differential, as control amount;
S5: in agricultural machinery automatic Pilot operation process, to guarantee crop cultivation quality, uniform rectilinear is in tractor setting Movement, therefore can obtain:
S6: in a practical situation, since surface relief variation, GNSS double antenna installation deviation factor cause course angle inclined Difference causes path trace effect to be deteriorated, and is simplified model, and can be approximately considered heading angle deviation is steady state value, then has:
S7: by S1-S6 process, the caterpillar tractor kalman filtering nonlinear differential equation model of building is as follows:
S8: east orientation displacement coordinate component x, north orientation displacement coordinate component y, tractor speed v, tractor course angle are chosen And heading angle deviation δ is as system state amount, it is fast with east orientation displacement coordinate component x, north orientation displacement coordinate component y, tractor Spend v, tractor course angleIt measures, then has as systematic perspective:
Wherein, X is system estimation vector, and Z is systematic observation vector;
The caterpillar tractor kalman Filtering Model constructed in S9:S7 is nonlinear model, using EKF filtering algorithm, By Method of Obtaining Jacobian Matrix, model is linearized to obtain corresponding system linear state space equation:
S10: discrete model construction is obtained into state-transition matrix Φ and observing matrix H:
S11: process noise covariance matrix Q and observation noise covariance matrix R is chosen:
S12: init state vector X, covariance matrix P and observation state vector Z:
X (0)=E [X (0)] (19);
P (0)=var [X (0)] (20);
Z (0)=Z0(21);
Wherein, X (0), P (0), Z (0) are respectively the initial of state vector X, covariance matrix P and observation state vector Z Value;
S13:Kalman filter state one-step prediction:
S14: one-step prediction covariance matrix is calculated:
P (k+1 | k)=Φ (k+1 | k) P (k | k) ΦT(k+1|k)+Q(k+1) (23);
S15: Kalman gain is calculated:
K (k+1)=P (k+1 | k) HT(k+1)[H(k+1)P(k+1|k)HT(k+1)+R(k+1)]-1(24);
S16: estimated value is calculated:
S17: covariance matrix is updated:
P (k+1)=[I-K (k+1) H (k+1)] P (k+1 | k) (26);
Wherein, in formula (22-26), k+1 indicates that subsequent time, k indicate current time,For system state estimation Amount, K are kalman gain.
Preferably, further include step S18, constantly repeat step S13-S17.
Preferably, further include step S19, during carrying out off-line analysis debugging using real data, adjust observation and make an uproar Sound matrix, process noise matrix and covariance matrix meet actual course angle to reach desired filter effect, and estimate Deviation compensates course angle.
Compared with prior art, the beneficial effects of the present invention are:
(1) estimation of caterpillar tractor kinematics and deviation calibration method that the present invention realizes quickly can be estimated accurately The heading angle deviation due to caused by surface relief variation, GNSS antenna installation deviation etc. improves to compensate to course angle Adaptability of the system to ground;
(2) present invention can be to caterpillar tractor automatic Pilot control algolithm data source by using EKF filtering algorithm Be filtered, reduce data noise, reduce external environmental interference factor and system noise to caterpillar tractor from The influence of dynamic control loop performance improves caterpillar tractor automated driving system control precision and system stability;
(3) calculation amount of the present invention is small, and real-time is high, in contrast, can be by caterpillar tractor automatic Pilot performance boost 25% or so.
Detailed description of the invention
Fig. 1 is caterpillar tractor kinematics model.
Fig. 2 is kalman filtering estimation flow chart.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.
Referring to Fig.1-2, a kind of caterpillar tractor kinematics estimation and deviation calibration method, include the following steps,
Step 1: building caterpillar tractor kinematics model:
Wherein, x is caterpillar tractor east orientation displacement coordinate component, and y is north orientation displacement coordinate component, and v drags for crawler type Machine drawing travel speed,For caterpillar tractor course angle, ω is caterpillar tractor car body angular speed;
Step 2: angular speed is equal at revolver, right wheel and mass center, therefore can since caterpillar tractor is when being turned to It derives:
Wherein, vlFor the travel speed for left track, vrFor the travel speed for right side track, R is turning radius, and b is Width of the carbody.
Step 3: simultaneous equations solution can obtain:
Step 4: can be released by formula (3) and (6):
In formula, u is left and right track speed differential, as control amount;
Step 5:, to guarantee crop cultivation quality, tractor setting is done at the uniform velocity in agricultural machinery automatic Pilot operation process Linear motion, therefore can obtain:
Step 6: in a practical situation, due to surface relief variation, GNSS double antenna installation deviation factor, causing course Angular displacement causes path trace effect to be deteriorated, and is simplified model, and being approximately considered heading angle deviation is certain value, then has:
The purpose of the present invention is then that it is inclined can real-time and accurately to estimate course angle by designing suitable estimation method Poor δ, and course angle is compensated and corrected;
Step 7: by the above process, the caterpillar tractor kalman that the present invention constructs filters nonlinear differential equation Model is as follows:
Step 8: choosing east orientation displacement coordinate component x, north orientation displacement coordinate component y, tractor speed v, tractor course AngleAnd heading angle deviation δ with east orientation displacement coordinate component x, north orientation displacement coordinate component y, is drawn as system state amount Machine speed v, tractor course angleIt measures, then has as systematic perspective:
Wherein, X is system estimation vector, and Z is systematic observation vector.
Step 9: the caterpillar tractor kalman Filtering Model constructed in the 7th step is nonlinear model, the present invention is adopted Model is linearized to obtain corresponding system linear state space side by Method of Obtaining Jacobian Matrix with EKF filtering algorithm Journey:
Step 10: discrete model construction is obtained state-transition matrix Φ and observing matrix H:
Step 11: choosing process noise covariance matrix Q and observation noise covariance matrix R:
Process noise covariance matrix Q:
The selection of observation noise covariance matrix R: by acquiring in a period of time (10~20min) caterpillar tractor certainly Dynamic control loop pose data east orientation displacement coordinate component x, north orientation displacement coordinate component y, tractor traveling in quiescing process Speed v, tractor course angleAnd ask standard deviation to obtain systematic observation noise covariance matrix R each group of data respectively, it draws N=3 times when the observation noise covariance matrix R of machine in the process of running is static:
It is worth noting that, Q, R for choosing are not definite value herein, it can modify and adjust according to filter effect, directly Until reaching promising result.
Step 12: by acquisition caterpillar tractor, the east orientation (under automatic driving mode) is displaced seat during the motion Mark component x, north orientation displacement coordinate component y, tractor speed v, tractor course angleControl amount u and car body angular velocity omega, and As observation vector Z;
Step 13: init state vector X, covariance matrix P and observation state vector Z:
X (0)=E [X (0)] (19);
Z (0)=Z0(21);
Wherein, X (0), P (0), Z (0) are respectively the initial of state vector X, covariance matrix P and observation state vector Z Value, the size of P (0) will directly affect EKF convergence speed of the algorithm;
Step 14: Kalman filter state one-step prediction:
Step 15: calculating one-step prediction covariance matrix:
P (k+1 | k)=Φ (k+1 | k) P (k | k) ΦT(k+1|k)+Q(k+1) (23);
Step 16: calculating Kalman gain:
K (k+1)=P (k+1 | k) HT(k+1)[H(k+1)P(k+1|k)HT(k+1)+R(k+1)]-1(24);
Step 17: calculating estimated value:
Step 18: updating covariance matrix:
P (k+1)=[I-K (k+1) H (k+1)] P (k+1 | k) (26);
Wherein, in formula (22-26), k+1 indicates that subsequent time, k indicate current time,For system state estimation Amount, K are kkalman gain;
Step 19: constantly repeating step the ten four-the 18;
During the present invention carries out off-line analysis debugging using real data, observation noise matrix R, process noise are adjusted Matrix Q and covariance matrix P (0) meets actual heading angle deviation to course to reach desired filter effect, and estimate Angle compensates;
The present invention estimates caterpillar tractor kinematics and calibration method is applied to caterpillar tractor automatic Pilot mistake Journey is filtered, data processing, estimated course angular displacement, online to reach preferable control effect;
Caterpillar tractor kinematics proposed by the present invention estimation and deviation calibration method can quickly Accuracy extimate due to Course angle error caused by surface relief changes specifically includes to improve control algolithm to the adaptability of ground fluctuations The following:
(1) estimation of caterpillar tractor kinematics and deviation calibration method that the present invention realizes quickly can be estimated accurately The heading angle deviation due to caused by surface relief variation, GNSS antenna installation deviation etc. improves to compensate to course angle Adaptability of the system to ground;
(2) present invention can be to caterpillar tractor automatic Pilot control algolithm data source by using EKF filtering algorithm Be filtered, reduce data noise, reduce external environmental interference factor and system noise to caterpillar tractor from The influence of dynamic control loop performance improves caterpillar tractor automated driving system control precision and system stability;
(3) calculation amount of the present invention is small, and real-time is high, in contrast, can be by caterpillar tractor automatic Pilot performance boost 25% or so.
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto, Anyone skilled in the art in the technical scope disclosed by the present invention, according to the technique and scheme of the present invention and its Inventive concept is subject to equivalent substitution or change, should be covered by the protection scope of the present invention.

Claims (3)

1. a kind of caterpillar tractor kinematics estimation and deviation calibration method, which is characterized in that include the following steps,
S1 constructs caterpillar tractor kinematics model:
Wherein, x is caterpillar tractor east orientation displacement coordinate component, and y is north orientation displacement coordinate component, and v is caterpillar tractor Travel speed,For caterpillar tractor course angle, ω is caterpillar tractor car body angular speed;
S2: since caterpillar tractor is when being turned to, angular speed is equal at revolver, right wheel and mass center, therefore can derive:
Wherein, vlFor the travel speed for left track, vrFor the travel speed for right side track, R is turning radius, and b is car body Width;
S3: simultaneous equations solution can obtain:
S4: it can be released by formula (3) and (6):
In formula, u is left and right track speed differential, as control amount;
S5: in agricultural machinery automatic Pilot operation process, to guarantee crop cultivation quality, uniform rectilinear's fortune is done in tractor setting It is dynamic, therefore can obtain:
S6: it in a practical situation, since surface relief variation, GNSS double antenna installation deviation factor cause heading angle deviation, leads It causes path trace effect to be deteriorated, is simplified model, can be approximately considered heading angle deviation is steady state value, then have:
S7: by S1-S6 process, the caterpillar tractor kalman filtering nonlinear differential equation model of building is as follows:
S8: east orientation displacement coordinate component x, north orientation displacement coordinate component y, tractor speed v, tractor course angle are chosenAnd Heading angle deviation δ as system state amount, with east orientation displacement coordinate component x, north orientation displacement coordinate component y, tractor speed v, Tractor course angleIt measures, then has as systematic perspective:
Wherein, X is system estimation vector, and Z is systematic observation vector;
The caterpillar tractor kalman Filtering Model constructed in S9:S7 is that nonlinear model is passed through using EKF filtering algorithm Method of Obtaining Jacobian Matrix linearizes model to obtain corresponding system linear state space equation:
S10: discrete model construction is obtained into state-transition matrix Φ and observing matrix H:
S11: process noise covariance matrix Q and observation noise covariance matrix R is chosen:
S12: init state vector X, covariance matrix P and observation state vector Z:
X (0)=E [X (0)] (19);
P (0)=var [X (0)] (20);
Z (0)=Z0(21);
Wherein, X (0), P (0), Z (0) are respectively the initial value of state vector X, covariance matrix P and observation state vector Z;
S13:Kalman filter state one-step prediction:
S14: one-step prediction covariance matrix is calculated:
P (k+1 | k)=Φ (k+1 | k) P (k | k) ΦT(k+1|k)+Q(k+1) (23);
S15: Kalman gain is calculated:
K (k+1)=P (k+1 | k) HT(k+1)[H(k+1)P(k+1|k)HT(k+1)+R(k+1)]-1(24);
S16: estimated value is calculated:
S17: covariance matrix is updated:
P (k+1)=[I-K (k+1) H (k+1)] P (k+1 | k) (26);
Wherein, in formula (22-26), k+1 indicates that subsequent time, k indicate current time,For system state estimation amount, K is Kalman gain.
2. a kind of caterpillar tractor kinematics estimation according to claim 1 and deviation calibration method, which is characterized in that Further include step S18, constantly repeats step S13-S17.
3. a kind of caterpillar tractor kinematics estimation according to claim 2 and deviation calibration method, which is characterized in that Further include step S19, during carrying out off-line analysis debugging using real data, adjusts observation noise matrix, process noise Matrix and covariance matrix with reach desired filter effect, and estimate meet actual heading angle deviation to course angle into Row compensation.
CN201910448762.0A 2019-05-28 2019-05-28 A kind of estimation of caterpillar tractor kinematics and deviation calibration method Pending CN110262479A (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201910448762.0A CN110262479A (en) 2019-05-28 2019-05-28 A kind of estimation of caterpillar tractor kinematics and deviation calibration method
PCT/CN2019/115000 WO2020238011A1 (en) 2019-05-28 2019-11-01 Kinematics estimation and deviation calibration method for crawler-type tractor

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910448762.0A CN110262479A (en) 2019-05-28 2019-05-28 A kind of estimation of caterpillar tractor kinematics and deviation calibration method

Publications (1)

Publication Number Publication Date
CN110262479A true CN110262479A (en) 2019-09-20

Family

ID=67915572

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910448762.0A Pending CN110262479A (en) 2019-05-28 2019-05-28 A kind of estimation of caterpillar tractor kinematics and deviation calibration method

Country Status (2)

Country Link
CN (1) CN110262479A (en)
WO (1) WO2020238011A1 (en)

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111532337A (en) * 2020-05-18 2020-08-14 新乡北方车辆仪表有限公司 Control method for comprehensive double-current electric transmission
CN111766879A (en) * 2020-06-24 2020-10-13 天津大学 Intelligent vehicle formation system based on autonomous collaborative navigation
WO2020238011A1 (en) * 2019-05-28 2020-12-03 南京天辰礼达电子科技有限公司 Kinematics estimation and deviation calibration method for crawler-type tractor
CN112147656A (en) * 2020-09-09 2020-12-29 无锡卡尔曼导航技术有限公司 GNSS double-antenna course installation angle offset estimation method
CN112146561A (en) * 2020-09-09 2020-12-29 无锡卡尔曼导航技术有限公司 Hall angle sensor installation angle offset estimation method
CN113900126A (en) * 2021-12-07 2022-01-07 广东皓行科技有限公司 Double-antenna position determination method and device
CN115480579A (en) * 2022-10-13 2022-12-16 华侨大学 Crawler-type mobile machine, and method, device and medium for tracking and controlling established track thereof

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114200925B (en) * 2021-11-10 2024-05-14 江苏大学 Tractor path tracking control method and system based on self-adaptive time domain model prediction
CN114545944B (en) * 2022-02-24 2024-04-16 合肥工业大学 AGV course positioning navigation method based on magnetic nail magnetic field intensity correction
CN117270535B (en) * 2023-09-25 2024-03-12 青岛农业大学 Auxiliary navigation system suitable for crawler-type potato harvester and control method

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH03266173A (en) * 1990-03-16 1991-11-27 Nec Corp Equation analyzer
WO2002051740A1 (en) * 2000-12-27 2002-07-04 Hoei Shokai Co., Ltd Container
WO2008018188A1 (en) * 2006-08-08 2008-02-14 Kyoto University Eigen value decomposing device and eigen value decomposing method
CN206161820U (en) * 2016-11-04 2017-05-10 首都师范大学 System based on extension kalman particle filter
CN107991110A (en) * 2017-11-29 2018-05-04 安徽省通信息科技有限公司 A kind of caterpillar type robot slides parameter detection method
CN107991060A (en) * 2017-11-20 2018-05-04 南京航空航天大学 Based on adaptive and iterative algorithm load distribution type fiber-optic discrimination method
CN108279025A (en) * 2017-12-22 2018-07-13 中国船舶重工集团公司第七0七研究所 A kind of fiber optic gyro compass quick accurate alignment method based on gravitation information
CN108438048A (en) * 2018-04-04 2018-08-24 上海华测导航技术股份有限公司 A kind of novel caterpillar tractor automatic steering control system and control method
CN108592911A (en) * 2018-03-23 2018-09-28 南京航空航天大学 A kind of quadrotor kinetic model/airborne sensor Combinated navigation method
CN108693773A (en) * 2018-04-04 2018-10-23 南京天辰礼达电子科技有限公司 A kind of automatic driving of agricultural machinery landslide deviation adaptive estimation method
CN109240082A (en) * 2018-08-25 2019-01-18 南京理工大学 A kind of caterpillar mobile robot sliding formwork cloud model cross-coupling control method

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102673569B (en) * 2012-05-25 2015-10-28 同济大学 Vehicle-state is calculated device, method and is used the vehicle of this device
CN107633141B (en) * 2017-09-22 2018-08-21 中国水利水电科学研究院 A kind of discrimination method of one-dimension mathematical model pumping station performance curve coefficients
CN107804315B (en) * 2017-11-07 2019-07-16 吉林大学 It is a kind of to consider to drive people's vehicle collaboration rotating direction control method that power is distributed in real time
CN108454628B (en) * 2018-04-17 2019-06-04 吉林大学 A kind of driver turns to rolling optimization control method in people's vehicle collaboration of ring
CN110262479A (en) * 2019-05-28 2019-09-20 南京天辰礼达电子科技有限公司 A kind of estimation of caterpillar tractor kinematics and deviation calibration method

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH03266173A (en) * 1990-03-16 1991-11-27 Nec Corp Equation analyzer
WO2002051740A1 (en) * 2000-12-27 2002-07-04 Hoei Shokai Co., Ltd Container
WO2008018188A1 (en) * 2006-08-08 2008-02-14 Kyoto University Eigen value decomposing device and eigen value decomposing method
CN206161820U (en) * 2016-11-04 2017-05-10 首都师范大学 System based on extension kalman particle filter
CN107991060A (en) * 2017-11-20 2018-05-04 南京航空航天大学 Based on adaptive and iterative algorithm load distribution type fiber-optic discrimination method
CN107991110A (en) * 2017-11-29 2018-05-04 安徽省通信息科技有限公司 A kind of caterpillar type robot slides parameter detection method
CN108279025A (en) * 2017-12-22 2018-07-13 中国船舶重工集团公司第七0七研究所 A kind of fiber optic gyro compass quick accurate alignment method based on gravitation information
CN108592911A (en) * 2018-03-23 2018-09-28 南京航空航天大学 A kind of quadrotor kinetic model/airborne sensor Combinated navigation method
CN108438048A (en) * 2018-04-04 2018-08-24 上海华测导航技术股份有限公司 A kind of novel caterpillar tractor automatic steering control system and control method
CN108693773A (en) * 2018-04-04 2018-10-23 南京天辰礼达电子科技有限公司 A kind of automatic driving of agricultural machinery landslide deviation adaptive estimation method
CN109240082A (en) * 2018-08-25 2019-01-18 南京理工大学 A kind of caterpillar mobile robot sliding formwork cloud model cross-coupling control method

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020238011A1 (en) * 2019-05-28 2020-12-03 南京天辰礼达电子科技有限公司 Kinematics estimation and deviation calibration method for crawler-type tractor
CN111532337A (en) * 2020-05-18 2020-08-14 新乡北方车辆仪表有限公司 Control method for comprehensive double-current electric transmission
CN111532337B (en) * 2020-05-18 2022-01-07 新乡北方车辆仪表有限公司 Control method for comprehensive double-current electric transmission
CN111766879A (en) * 2020-06-24 2020-10-13 天津大学 Intelligent vehicle formation system based on autonomous collaborative navigation
CN112147656A (en) * 2020-09-09 2020-12-29 无锡卡尔曼导航技术有限公司 GNSS double-antenna course installation angle offset estimation method
CN112146561A (en) * 2020-09-09 2020-12-29 无锡卡尔曼导航技术有限公司 Hall angle sensor installation angle offset estimation method
CN112147656B (en) * 2020-09-09 2021-05-04 无锡卡尔曼导航技术有限公司 GNSS double-antenna course installation angle offset estimation method
CN113900126A (en) * 2021-12-07 2022-01-07 广东皓行科技有限公司 Double-antenna position determination method and device
CN115480579A (en) * 2022-10-13 2022-12-16 华侨大学 Crawler-type mobile machine, and method, device and medium for tracking and controlling established track thereof

Also Published As

Publication number Publication date
WO2020238011A1 (en) 2020-12-03

Similar Documents

Publication Publication Date Title
CN110262479A (en) A kind of estimation of caterpillar tractor kinematics and deviation calibration method
Bevly et al. Cascaded Kalman filters for accurate estimation of multiple biases, dead-reckoning navigation, and full state feedback control of ground vehicles
US10352829B2 (en) Automatic calibration method of an angle sensor for an automatic drive control system of a farm machine
Zhang et al. Tractor path tracking control based on binocular vision
US20210282310A1 (en) Method and system for estimating surface roughness of ground for an off-road vehicle to control steering
US20210283973A1 (en) Method and system for estimating surface roughness of ground for an off-road vehicle to control steering
Bevly et al. Comparison of INS vs. carrier‐phase DGPS for attitude determination in the control of off‐road vehicles
US11685381B2 (en) Method and system for estimating surface roughness of ground for an off-road vehicle to control ground speed
Eaton et al. Autonomous farming: Modelling and control of agricultural machinery in a unified framework
Yin et al. Development of autonomous navigation system for rice transplanter
WO2012027082A1 (en) Automatic control of passive, towed implements
CN105987696A (en) Low-cost vehicle automatic driving design realization method
CN111610523B (en) Parameter correction method for wheeled mobile robot
CN111238471A (en) Sideslip angle estimation method and estimator suitable for agricultural machine linear navigation
Oksanen et al. Guidance system for agricultural tractor with four wheel steering
CN107943060A (en) A kind of automatic pilot, method and computer-readable medium along tracking straight line guiding vehicle
AU2020104234A4 (en) An Estimation Method and Estimator for Sideslip Angle of Straight-line Navigation of Agricultural Machinery
WO2019173769A1 (en) Kalman filter for an autonomous work vehicle system
CN110530361A (en) A kind of steering angle estimator based on agricultural machinery double antenna GNSS automated navigation system
Wang et al. Autonomous maneuvers of a robotic tractor for farming
CN111158379A (en) Steering wheel zero-bias self-learning unmanned vehicle track tracking method
CN111703432A (en) Real-time estimation method for sliding parameters of intelligent tracked vehicle
CN110716565A (en) Track vehicle navigation track tracking control system
Bevly High speed, dead reckoning, and towed implement control for automatically steered farm tractors using GPS
CN104132664A (en) Method for estimation of slippage of agricultural tracked 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
RJ01 Rejection of invention patent application after publication

Application publication date: 20190920

RJ01 Rejection of invention patent application after publication