CN109258059A - A kind of grass trimmer method for determining position and device - Google Patents
A kind of grass trimmer method for determining position and device Download PDFInfo
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- CN109258059A CN109258059A CN201810785434.5A CN201810785434A CN109258059A CN 109258059 A CN109258059 A CN 109258059A CN 201810785434 A CN201810785434 A CN 201810785434A CN 109258059 A CN109258059 A CN 109258059A
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- grass trimmer
- angle
- accelerometer
- distance
- fusion
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01D—HARVESTING; MOWING
- A01D34/00—Mowers; Mowing apparatus of harvesters
- A01D34/006—Control or measuring arrangements
- A01D34/008—Control or measuring arrangements for automated or remotely controlled operation
Abstract
The invention discloses a kind of grass trimmer method for determining position and devices, can be accurately determined grass trimmer straight-line travelling distance independent of external world's reference with turning and turn over angle, and determine the walking position of grass trimmer based on this.The present invention carries out quadratic integral to acceleration measuring magnitude first and obtains the distance of accelerometer calculating；Grass trimmer wheel move distance is obtained using the rotational angle of angular transducer acquisition grass trimmer wheel；The distance and grass trimmer wheel move distance that accelerometer is calculated carry out Kalman filtering fusion, by fusion results labeled as grass trimmer straight trip distance；Kalman filtering fusion three times is carried out using the data of gyroscope, accelerometer, magnetometer, hall element sensor acquisition, finally obtained fusion results are labeled as grass trimmer rotational angle；According to grass trimmer straight trip distance and grass trimmer rotational angle, after obtaining the walking unit time, position of the grass trimmer relative to origin.
Description
Technical field
The present invention relates to robot field more particularly to a kind of grass trimmer method for determining position and device.
Background technique
Intelligent grass-removing assists mainly in people and completes grass cutting action, is a kind of mowing that intelligent independent mowing may be implemented
Machine.Intelligent grass-removing can be detached from the governing factor of people, to avoid wasting excessive human resources, save material resources,
And also have many advantages, such as high efficiency, high security.
So-called intelligence, which is mowed, to be referred to: artificial to delimit mowing region in advance, grass trimmer is in the region artificially delimited from master ga(u)ge
Draw path, walking, traverse region in all positions without crossing region, thus realize without repeat, exhaustive it is comprehensive from
Main operation.It among these mainly include Urine scent technology, the intelligent Path Recognition technology, intelligent barrier avoiding technology on work boundary.
Wherein, the Urine scent technology on boundary of working refers to during mowing, intelligent grass-removing can intelligent recognition cut
Careless path, so that walking will not cross boundary.Intelligent grass-removing lays fence method using electronics and carries out regional edge mostly now
Boundary is selected.But fence has the characteristics that flexibility is poor, if wanting to change region shape needs after laying fence
Again it lays, and complex region lays difficult, inefficiency.Fence is laid in outdoor simultaneously, easy to damage, and easily anticipates
Outside.Another work boundary recognition methods is to utilize GPS technology.But this technology will realize higher precision, need very
High-precision GPS, this will cause the raising of grass trimmer cost, not be suitable for household grass trimmer.Finally, can also use allow intelligence
Grass trimmer acquires endpoint data coordinate in advance, determines boundary by internal algorithm, this method strong flexibility can be according to acquisition
The data arrived flexibly determine boundary, and reply boundary is changeable, the occasion of complex boundary.But this method needs grass trimmer quasi-
Really determine motion state, that is, walked how far, how many degree turned, the accuracy of the position of coordinate acquisition point is improved with this, from
And can guarantee internal algorithm can accurately cook up zone boundary.
In addition, needing to mow according to the path walking of planning, being also required at this time can be accurate after path planning completion
Ground determines the movement position of grass trimmer, guarantees without departing from programme path.
In the prior art, most of intelligent grass-removing is used installs reference location device to mowing at the certain positions in boundary
Machine provides the determination and amendment that reference signal carries out movement position, but this method is extremely inconvenient, is only applicable to mowing range
Relatively-stationary place.
Therefore, lack a kind of no extraneous reference in the prior art, fully rely on sensor entrained by grass trimmer and determine
The method of grass trimmer position.
Summary of the invention
The present invention provides a kind of grass trimmer method for determining position and devices, and existing grass trimmer movement position is overcome to determine
The disadvantage of method flexibility difference only relies on mower vehicle set sensor just and can determine that grass trimmer position, the party without extraneous reference
Method is flexible and convenient, is simple and efficient.In order to achieve the above objectives, the present invention adopts the following technical scheme:
A kind of grass trimmer method for determining position, comprising:
S1, initial position is labeled as origin.
S2, grass trimmer are walked the unit time, the acceleration that the measurement of accelerometer obtains in the acquisition units time, to acceleration
Degree carries out quadratic integral, obtains the distance of accelerometer calculating, and the distance that accelerometer calculates is inaccurate.
S3, it converts to obtain the turnning circle and angle of grass trimmer wheel, turnning circle and angle using hall element sensor
Degree combines the radius of grass trimmer wheel to obtain grass trimmer wheel move distance.
S4, the distance that accelerometer is calculated and grass trimmer wheel move distance carry out Kalman filtering fusion, will merge
Result queue is grass trimmer straight trip distance.Because the distance that the hall signal number of hall element sensor passback is converted into may
It can be not allowed because of wheel-slip, and the distance that accelerometer calculates may be because that drift, temperature drift cause the error of accumulation at two
After person is via Kalman filtering, confidence level of the grass trimmer wheel move distance at a distance from accelerometer calculating is considered, by two
Distance, which carries out fusion, can be obtained by accurate travel distance.
S5, three-level Kalman is carried out using the data of gyroscope, accelerometer, magnetometer, hall element sensor acquisition
Finally obtained fusion results are labeled as grass trimmer rotational angle by filtering fusion；
S6, kept straight on according to grass trimmer distance and grass trimmer rotational angle, after obtaining the walking unit time, grass trimmer is relative to origin
Position.
Further, in S5, the fusion of three-level Kalman filtering includes:
S51, by gyroscope acquisition angle rate integrating, obtain gyroscope integral angle, three axis accelerometer acquires three sides respectively
To acceleration, by the acceleration calculation collected obtain accelerometer calculate angle.Gyroscope integrates angle and there is accumulation
Error, it is larger that accelerometer calculates angle noise.
S52, gyroscope is integrated to angle and accelerometer calculating angle progress level-one Kalman filtering fusion, is merged
Angle afterwards.Fused angle compensates for gyroscope integral angle accumulated error, accelerometer calculates that angle noise is big to be lacked
It falls into, because accelerometer can make up the defect that gyroscope output zero point is affected by temperature, so that integral error greatly reduces, and
Gyroscope integral angle can then reduce the output noise that accelerometer calculates angle.
S53, the absolute angle of magnetometer acquisition and fused angle are subjected to second kalman filter fusion, obtain two
The fused angle of grade.
Hall element sensor is installed, the distance of vehicle wheel rotation corresponds to sensor and measures suddenly on S54, grass trimmer wheel
That signal number.Its left and right wheels is inverted when grass trimmer is turned with same angular velocity, so grass trimmer rotational angle can correspond to
The angle that wheel turns over also then corresponds to hall signal number.Therefore the Hall that can be acquired by hall element sensor is believed
Number number obtains the rotational angle of grass trimmer, this angle will not be affected by magnetic fields and change.Hall element sensor is surveyed
Angle after the angle of rotation and two level fusion that obtain carries out the fusion of three-level Kalman filtering, and obtained result queue is grass trimmer rotation
Angle.
The present invention also provides a kind of determining devices of grass trimmer position, comprising: accelerometer, gyroscope, magnetometer,
Hall element sensor.Wherein accelerometer, gyroscope and magnetometer are placed in grass trimmer vehicle body central axes, and and ground level.
Hall element sensor is placed in inside mowing motor, for recording motor turnning circle.
The walking of grass trimmer is divided into turning and straight trip, and the variation of orientation angle is not present in straight trip process, and turning process is not deposited
In the variation of displacement, therefore according to travel distance and rotational angle, position of the grass trimmer with respect to starting point can be calculated.
The beneficial effects of the present invention are:
The distance that the present invention is converted using accelerometer calculated distance and hall element sensor is mutually melted
Conjunction obtains the operating range information of grass trimmer；More letters are carried out using accelerometer, gyroscope, magnetometer and hall element sensor
Number multi-level fusion, obtains grass trimmer and turns over angle information in real time, only used accelerometer, the gyro that grass trimmer itself carries
Instrument, magnetometer and hall element sensor, not any extraneous reference source are corrected the walking position to determine grass trimmer, are abandoned
External reference source, avoid reference source damage and caused by can not carry out the defect of autonomous intelligence mowing, be based on this position
It determines method, position of the grass trimmer relative to original coordinates point can be accurately obtained, acquisition when dividing region so as to improve
The accuracy of data point, and planned the accuracy of traveling planning path behind path.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to needed in the embodiment
Attached drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for ability
For the those of ordinary skill of domain, without creative efforts, it can also be obtained according to these attached drawings other attached
Figure.
Fig. 1 is the flow chart of the method for the present invention；
Fig. 2 is the fusion flow chart of distance；
Fig. 3 is the fusion flow chart of angle；
Fig. 4 is intelligent grass-removing walking conceptual scheme；
Fig. 5 is each device placement location and connection figure.
Specific embodiment
Technical solution in order to enable those skilled in the art to better understand the present invention, With reference to embodiment to this
Invention is described in further detail.
The embodiment of the invention provides a kind of grass trimmer method for determining position, need using a kind of grass trimmer position really
Determine device.A kind of determining device of grass trimmer position, as shown in Figure 5, comprising: accelerometer, gyroscope, magnetometer, Hall member
Part sensor, master controller, wherein accelerometer, gyroscope and magnetometer are placed in grass trimmer vehicle body central axes, and and the surface water
It is flat；Hall element sensor is placed in inside mowing motor, for recording motor turnning circle, master controller acquire accelerometer,
The parameter of gyroscope, magnetometer, hall element sensor, and carry out operation and control.
A kind of flow diagram of grass trimmer method for determining position is as shown in Figure 1, comprising:
The acceleration that the measurement of accelerometer obtains in the acquisition units time, obtains speed by once integrating, and carries out to speed
Primary integral obtains the distance of accelerometer calculating, obtains inaccurate straight trip distance A.
The hall element sensor that counting is installed inside motor utilizes hall element sensor acquisition grass trimmer wheel
Rotational angle, the radius of rotational angle combination grass trimmer wheel obtain grass trimmer wheel move distance B.
The distance and grass trimmer wheel move distance that accelerometer is calculated carry out Kalman filtering fusion, by fusion results
Labeled as grass trimmer straight trip distance.Because the distance that is converted into of hall signal number of angle Hall element sensor passback may be because
Be not allowed for wheel-slip, and accelerometer calculate distance may be because drift, temperature drift cause accumulation error, the two via
After Kalman filtering, consider that grass trimmer wheel move distance B calculates the confidence level of distance A with accelerometer, by two distances
Carrying out fusion can be obtained by accurate travel distance C, as shown in Figure 3.
Three-level Kalman filtering is carried out using the data of gyroscope, accelerometer, magnetometer, hall element sensor acquisition
Finally obtained fusion results are labeled as grass trimmer rotational angle by fusion.Wherein, three-level Kalman filtering, which merges, includes:
By gyroscope acquisition angle rate integrating, gyroscope integral angle a is obtained, three axis accelerometer acquires three directions respectively
Acceleration obtains accelerometer by the acceleration calculation collected and calculates angle b.Gyroscope integrates angle and there is accumulation mistake
Difference, it is larger that accelerometer calculates angle noise.
Gyroscope is integrated into angle a and accelerometer calculates angle b and carries out the fusion of level-one Kalman filtering, after obtaining fusion
Angle c.Fused angle compensates for gyroscope integral angle accumulated error, accelerometer calculates that angle noise is big to be lacked
It falls into, because accelerometer can make up the defect that gyroscope output zero point is affected by temperature, so that integral error greatly reduces, and
Gyroscope integral angle can then reduce the output noise that accelerometer calculates angle.
But fused angle c lacks the reference value amendment independently of grass trimmer, the absolute angle that magnetometer is acquired
Second kalman filter fusion is carried out with fused angle, the angle d after obtaining two level fusion.
Hall element sensor is installed on grass trimmer wheel, since the turning of grass trimmer is set as left and right wheels with identical angle
Speed forward and rear biography, so grass trimmer angle of turn corresponds to the distance of vehicle wheel rotation, and vehicle wheel rotation distance corresponds to suddenly
The hall signal number of your element sensor acquisition.It is absolute angle by the angle of rotation e that hall element sensor converts, no
It will receive the influence in magnetic field and change.Angle d after angle of rotation e and two level fusion that hall element sensor is converted into
The fusion of row three-level Kalman filtering is obtaining as a result, being labeled as grass trimmer rotational angle f, as shown in Figure 3.
According to grass trimmer straight trip distance and grass trimmer rotational angle, after obtaining the walking unit time, grass trimmer is relative to original
The position of point.
As shown in figure 4, the walking process of intelligent grass-removing is divided into: keeping straight on and to turn any angle curved.Straight trip certain distanceCertain angle is turned over later, a distance of keeping straight on again, turn over angle, so recycle, can accurately control every
Primary straight trip distance and angle of turn, thus record turn over each time angle and straight trip distance can in the hope of grass trimmer relative to
The position of original starting point.After it can accurately control the walking position of grass trimmer, intelligent grass-removing can be made to get rid of external ginseng
The constraint in source is examined, realizes that accurately contexture by self path and path are walked.
The beneficial effects of the present invention are:
The distance that the present invention is converted using accelerometer calculated distance and hall element sensor is mutually melted
Conjunction obtains the operating range information of grass trimmer；More letters are carried out using accelerometer, gyroscope, magnetometer and hall element sensor
Number multi-level fusion, obtains grass trimmer and turns over angle information in real time, only used accelerometer, the gyro that grass trimmer itself carries
Instrument, magnetometer and hall element sensor, not any extraneous reference source are corrected the walking position to determine grass trimmer, are abandoned
External reference source, avoid reference source damage and caused by can not carry out the defect of autonomous intelligence mowing, be based on this position
It determines method, position of the grass trimmer relative to original coordinates point can be accurately obtained, acquisition when dividing region so as to improve
The accuracy of data point, and planned the accuracy of traveling planning path behind path.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
In the technical scope disclosed by the present invention, any changes or substitutions that can be easily thought of by those familiar with the art, all answers
It is included within the scope of the present invention.Therefore, protection scope of the present invention should be subject to the protection scope in claims.
Claims (3)
1. a kind of grass trimmer method for determining position characterized by comprising
S1, initial position is labeled as origin；
S2, grass trimmer are walked the unit time, the acceleration that the measurement of accelerometer obtains in the acquisition units time, to the acceleration
Degree carries out quadratic integral, obtains the distance of accelerometer calculating；
S3, the circle number and angle that wheel turns over, the circle number and angle knot are obtained using the signal that hall element sensor acquires
The radius for closing the grass trimmer wheel obtains the angle that grass trimmer wheel move distance and grass trimmer turn over；
S4, by the distance that the accelerometer calculates and the grass trimmer wheel movement that the hall element sensor converts away from
From Kalman filtering fusion is carried out, by fusion results labeled as grass trimmer straight trip distance；
S5, the fusion of three-level Kalman filtering is carried out using the data of gyroscope, the accelerometer, magnetometer acquisition, it will be final
Obtained fusion results are labeled as grass trimmer rotational angle；
S6, kept straight on according to the grass trimmer distance and the grass trimmer rotational angle, after obtaining the walking unit time, grass trimmer phase
For the position of the origin.
2. according to the method described in claim 1, in the S5, the three-level Kalman filtering fusion includes:
S51, by the gyroscope acquisition angle rate integrating, obtain gyroscope integral angle, accelerometer acquires x, y, z-axis respectively
The acceleration in three directions obtains accelerometer by the acceleration calculation in three directions and calculates angle;
S52, the gyroscope is integrated to angle and accelerometer calculating angle progress level-one Kalman filtering fusion, obtained
Fused angle；
S53, the absolute angle of magnetometer acquisition and the fused angle are subjected to second kalman filter fusion, obtain two
The fused angle of grade；
Angle after S54, the angle that the hall element sensor is converted and the two level fusion carries out three-level karr
Graceful filtering fusion, obtained result queue are the grass trimmer rotational angle.
3. a kind of determining device of grass trimmer position characterized by comprising accelerometer, gyroscope, magnetometer, Hall member
Part sensor, wherein accelerometer, gyroscope and magnetometer are placed in grass trimmer vehicle body central axes, and and ground level；Hall member
Part sensor is placed in inside mowing motor, for recording motor turnning circle.
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| CN201810785434.5A CN109258059B (en) | 2018-07-17 | 2018-07-17 | Method and device for determining position of mower |
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| CN201810785434.5A CN109258059B (en) | 2018-07-17 | 2018-07-17 | Method and device for determining position of mower |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109900296A (en) * | 2019-03-22 | 2019-06-18 | 华南农业大学 | A kind of agricultural machinery working travel speed detection system and detection method |
| CN112567960A (en) * | 2020-12-02 | 2021-03-30 | 衢州学院 | Intelligent weeding robot |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201673130U (en) * | 2010-04-27 | 2010-12-15 | 丹东奥龙射线仪器有限公司 | Wheel-type X-ray flaw detection robot device |
| US20120001582A1 (en) * | 2010-07-02 | 2012-01-05 | Woodward Hrt, Inc. | Controller for actuation system employing kalman estimator incorporating effect of system structural stiffness |
| CN103170962A (en) * | 2013-03-08 | 2013-06-26 | 北京工业大学 | Desktop type double-wheel self-balancing robot |
| CN103630136A (en) * | 2013-12-05 | 2014-03-12 | 中国航空无线电电子研究所 | Optimum navigational parameter fusion method based on three-level filtering under redundant sensor configuration |
| CN106767804A (en) * | 2016-12-28 | 2017-05-31 | 华中科技大学 | The multidimensional data measurement apparatus and method of a kind of moving object |
| CN106843294A (en) * | 2017-03-22 | 2017-06-13 | 江南大学 | A kind of method for eliminating the axle drift of head course and motor-field interference |
| CN107272718A (en) * | 2017-06-19 | 2017-10-20 | 歌尔科技有限公司 | Attitude control method and device based on Kalman filtering |
-
2018
- 2018-07-17 CN CN201810785434.5A patent/CN109258059B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201673130U (en) * | 2010-04-27 | 2010-12-15 | 丹东奥龙射线仪器有限公司 | Wheel-type X-ray flaw detection robot device |
| US20120001582A1 (en) * | 2010-07-02 | 2012-01-05 | Woodward Hrt, Inc. | Controller for actuation system employing kalman estimator incorporating effect of system structural stiffness |
| CN103170962A (en) * | 2013-03-08 | 2013-06-26 | 北京工业大学 | Desktop type double-wheel self-balancing robot |
| CN103630136A (en) * | 2013-12-05 | 2014-03-12 | 中国航空无线电电子研究所 | Optimum navigational parameter fusion method based on three-level filtering under redundant sensor configuration |
| CN106767804A (en) * | 2016-12-28 | 2017-05-31 | 华中科技大学 | The multidimensional data measurement apparatus and method of a kind of moving object |
| CN106843294A (en) * | 2017-03-22 | 2017-06-13 | 江南大学 | A kind of method for eliminating the axle drift of head course and motor-field interference |
| CN107272718A (en) * | 2017-06-19 | 2017-10-20 | 歌尔科技有限公司 | Attitude control method and device based on Kalman filtering |
Non-Patent Citations (1)
| Title |
|---|
| 邹波，张华，姜军: "《多传感器信息融合的改进扩展卡尔曼滤波定姿》", 《计算机应用研究》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109900296A (en) * | 2019-03-22 | 2019-06-18 | 华南农业大学 | A kind of agricultural machinery working travel speed detection system and detection method |
| CN112567960A (en) * | 2020-12-02 | 2021-03-30 | 衢州学院 | Intelligent weeding robot |
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| CN109258059B (en) | 2021-06-22 |
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