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

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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
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tractor
caterpillar tractor
deviation
coordinate component
caterpillar
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孙飞
王海晶
史志中
芦海涛
刘军
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Nanjing Tianchen Li Electronic Technology Co Ltd
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Nanjing Tianchen Li Electronic Technology Co Ltd
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    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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 or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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 or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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 or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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; 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; 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; 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
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D2201/00Application
    • G05D2201/02Control of position of land vehicles
    • G05D2201/0201Agriculture or harvesting machine

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)

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Cited By (4)

* 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
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

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

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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
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

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