CN107843262A - A kind of method of farm machinery all standing trajectory path planning - Google Patents
A kind of method of farm machinery all standing trajectory path planning Download PDFInfo
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- CN107843262A CN107843262A CN201711041170.4A CN201711041170A CN107843262A CN 107843262 A CN107843262 A CN 107843262A CN 201711041170 A CN201711041170 A CN 201711041170A CN 107843262 A CN107843262 A CN 107843262A
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
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Abstract
The method of the farm machinery all standing trajectory path planning of the invention, it is related to unmanned agricultural machinery Path Planning Technique field, target farmland is divided into by several adjacent regions with barrier using Boustrophedon decomposition algorithms first, by each area assignment K, represent whether the region has covered, 0 is not covered as, has been covered as 1；The optimal path of covering all areas is found out using genetic algorithm again；Agricultural machinery takes straight line to come and go operation in region, and agricultural machinery retrieves K values while according to the path operation planned, if K values are 0, according to path operation；If K values are 1, subsequent region is turned to；To avoid repeating making overlay area already, introduce A* algorithms and find agricultural machinery to the optimal path of subsequent region, until all areas reach all standing effect.The technology realizes the coverage rate higher to ground than other technologies, while improves operating efficiency, reduces overlapping and omits, saves time and energy.
Description
Technical field
The present invention relates to a kind of unmanned agricultural machinery paths planning method, specifically a kind of unmanned agricultural machinery all standing traversal road
The design method of footpath planning algorithm, belong to robot path planning's technical field.
Background technology
As the technology of GIS, GPS and various sensors improves and extensive use, the self-navigation of agricultural machinery and various
Agriculture intelligent robot turns into the focus of people's research.Traditional agriculture machinery is driven in farm work, generally by driver's
Sense organ judges the position of agricultural machinery and speed, is so difficult to carry out accurate judgement to its current location, operation often occurs overlapping
And omission, it is particularly overlapping to large area even more so.And generally require to carry out night work in busy farming season, at this moment only rely on
The sense organ and micro-judgment of driver is just more difficult to control agricultural machinery to complete agronomic conditions in strict accordance with projected route, it is difficult to ensures agronomy
The requirement of operation, so as to influence agricultural production.Therefore the self-navigation of agricultural machinery is needed to complete agricultural production.And path planning is
The core of automated navigation system.Agricultural machinery is completed the job task in given plot, just must in advance standardized in advance make
Industry reference path, and reference path quality directly affects operation into amount.Path planning must all standing.
Have much currently for the algorithm of complete coverage path planning, be mostly based on genetic algorithm, the method for all standing at present
Coverage rate height is only ensure that, and repetitive rate is more；And the low algorithm of repetitive rate is taught in cumbersome, agricultural machinery work is not suitable for
Industry.Due to the various complex road conditions on agro-farming soil, the working path of agricultural machinery is not in general wire path but one kind is covered entirely
The planar path of lid formula, and different from the overlay path of general mobile robot.At present, unmanned agricultural machinery can be also applicable without a set of
Optimal complete coverage path planning method.So to realize overwrite job of the unmanned agricultural machinery to field completely style, and reduce operation
The overlapping and omission of covering.It is necessary to design a kind of algorithm for the complete coverage path planning for being adapted to unmanned agricultural machinery working.
The content of the invention
Coverage rate can not be successfully managed for existing complete coverage path planning technology and does not reach requirement, and repetitive rate is high to be lacked
Point, the present invention specially create a kind of brand-new complete coverage path planning algorithm for agricultural machinery, and nothing is realized for agricultural machinery
People, which drives, provides technical conditions.
The method of the farm machinery all standing trajectory path planning of the present invention, comprises the following steps：
A) farm environment, is represented first, is divided target farmland and barrier segmentation using Boustrophedon decomposition algorithms
The region adjacent into several, by each area assignment K, represent whether the region has covered, the region is not covered as 0, has covered
Cover as 1；
B) optimal path of covering all areas, is found out using genetic algorithm again；
C), agricultural machinery takes straight line to come and go operation in region, and agricultural machinery retrieves K while according to the path operation planned
Value, if K values are 0, according to path operation；If K values are 1, subsequent region is turned to；
D) it is, to avoid repetition work overlay area already, the shortest path of introducing A* algorithms searching agricultural machinery to subsequent region, directly
Reach all standing effect to all areas.
This method is combined using Boustrophedon cell decompositions and genetic algorithm, applied to agricultural machinery
In complete coverage path planning, based on this, the technology realizes the coverage rate higher to ground than other technologies；Pass through A* algorithms again
Effective path planning, improves operating efficiency, reduces overlapping and omits, saves time and energy.
Brief description of the drawings
Fig. 1 is the demonstration graph using Boustrophedon decomposition algorithm generation units；
Fig. 2 is the environment tree figure obtained by Fig. 1 unit decompositions.
Embodiment
For the technical characterstic for illustrating the present invention program can be understood, below by embodiment, and its accompanying drawing is combined, it is right
The present invention is described in detail.
The first step：Using Boustrophedon unit decomposition algorithms, farmland map is resolved into little module.
Boustrophedon unit decomposition algorithms are a kind of accurately cell decompositions, the list based on this decomposition thought
Member has the characteristics that：Unit must have two sides be it is parallel, and other two while be the border of barrier or environment while
Boundary.Its principle is as follows：With the inswept target area of straight line, when the connective change that straight line is run into, that is, new list is produced
Member.
With reference to Fig. 1, following explanation is done before Boustrophedon unit decomposition algorithms are described：One is established in the environment
Individual two-dimensional coordinate system, be laterally X-axis, be longitudinally Y-axis, origin is scheduled on the upper left corner, and agricultural machinery working starting point is along major axis (x-axis or y
Axle)；Scan line is that a straight line parallel to Y-axis, barrier Polygons Representation, and barrier are isolated danger；When
When scan line enters or leaves barrier, the connective of scan line produces change, and produces new unit.By scan line enter and
Leave barrier and be defined as IN events and OUT events, the region for defining barrier left is an area, is defined directly over barrier
Region is 2nd area, and the right for defining barrier is 3rd area, and the underface for defining barrier is 4th area.
It is as follows with reference to Fig. 2, its arthmetic statement：Scan line scans since Y-axis, when IN events occur, in region
The generation of one one unit of end of extent, the areas of Bing bis- and 3rd area respectively start the generation of a unit；Continue to sweep in 2nd area and 3rd area
Retouch, IN events occur for the areas of Dang bis- or 3rd area, and Ze Gai areas repeat the unit generation of previous step；The areas of Dang bis- and 3rd area occur
OUT events, then terminate the generation of two units, start the generation of a new unit.
K values are introduced in this algorithm；By the region assignment K of each division, for representing whether the region has covered, if
The region is not covered as 0, and it is then 1 to have covered.
Second step：The optimal overlay path of all submodules of step 1 division is obtained using genetic algorithm, is embodied as agriculture
The optimization working path of machine.
After the segmentation that farmland module and barrier are completed using Boustrophedon decomposition methods, by all little modules in farmland
The optimal overlay path of a submodule is drawn using genetic algorithm compiling.The path covers whole region from starting point,
All submodules in whole region are compiled into a data chain, such as by all submodules in Fig. 2 be compiled into 1. → 2. → 6. →
7. → 10. → 9. → 8. → 6. → 4. → 3. → 5. → Data-Link, agricultural machinery reaches according to compiled optimization path operation
The all standing of all submodules.
3rd step：To avoid repeating making overlay area already, introduce A* algorithms and find agricultural machinery to the shortest path of subsequent region
Footpath, and then generate optimal all standing path.
To avoid the repetition operation of overlay area, agricultural machinery is retrieved while the path operation planned according to step 2
K values, if K values are 0, according to path operation；If K values are 1, i.e. the region has covered；In order to not repeat to make overlay area already
A* algorithms are introduced, find agricultural machinery to the shortest path of subsequent region.Such as compiled Data-Link template 1. → 2. → 6. → 7.
→ 10., 10. → 9. → 8. → 6. → 4. → 3. in, agricultural machinery sequentially implements operation according to this to farmland, is completed when from 1. region job
During to 8. region, it is detected simultaneously by K values and represents that 6. region has covered, directly skip the region and carry out subsequent region operation, now
An optimal path is drawn using A* algorithms between the starting point two point of the end point to 4. region in 8. region, agricultural machinery is according to this
Path enters subsequent region operation, until covering all areas.
In above-mentioned narration, submodule, little module and " region " different statement, refer both to mono- using Boustrophedon
The unit that first decomposition algorithm resolves into map, it is under different context using different expression, the statement is properer.
The key point of the present invention is to introduce K values to represent whether the region is capped and avoid repeating the A* algorithms that operation introduces
Agricultural machinery is found to the shortest path of subsequent region.
The complete coverage path planning that this invention can be used under simple farm environment, coverage rate is high, and reduction is unnecessary
Repetition, can be suitably used for the planning in the optimal all standing path of unmanned agricultural machinery.
Claims (5)
1. a kind of method of farm machinery all standing trajectory path planning, it is characterized in that：Comprise the following steps：
A) farm environment, is represented first, if being divided into target farmland and barrier using Boustrophedon decomposition algorithms
Dry adjacent region, by each area assignment K, represents whether the region has covered, is not covered as 0, has been covered as 1；
B) optimal path of covering all areas, is found out using genetic algorithm again；
C), agricultural machinery takes straight line to come and go operation in region, and agricultural machinery retrieves K values while according to the path operation planned,
If K values are 0, according to path operation；If K values are 1, subsequent region is turned to；
D), to avoid repeating making overlay area already, A* algorithms is introduced and find agricultural machinery to the optimal path of subsequent region, until institute
There is region to reach all standing effect.
2. the method for farm machinery all standing trajectory path planning according to claim 1, it is characterized in that：Using
During Boustrophedon decomposition algorithms, a two-dimensional coordinate system is established in the environment, is laterally X-axis, longitudinal direction is Y-axis, and origin is fixed
In the upper left corner, agricultural machinery working starting point is along major axis (x-axis or y-axis)；Scan line is a straight line parallel to Y-axis, and barrier is used
Polygons Representation, and barrier is isolated danger；When scan line enters or leaves barrier, the connective production of scan line
Changing, and new unit is produced, scan line is entered and left into barrier is defined as IN events and OUT events, defines obstacle
The region of thing left is an area, and the region defined directly over barrier is 2nd area, and the right for defining barrier is 3rd area, definition barrier
The underface for hindering thing is 4th area.
3. the method for farm machinery all standing trajectory path planning according to claim 2, it is characterized in that：Scan line is from Y
Axle starts to scan, and when IN events occur, the generation of one unit of end of extent in region, the areas of Bing bis- and 3rd area respectively open
The generation of one unit of beginning；Continued to scan in 2nd area and 3rd area, the areas of Dang bis- or 3rd area generation IN events, in the repetition of Ze Gai areas
The unit generation of one step；OUT events occur for the areas of Dang bis- and 3rd area, then terminate the generation of two units, start a new unit
Generation.
4. the method for farm machinery all standing trajectory path planning according to claim 1, it is characterized in that：Implementation steps b)
When, after the segmentation for completing farmland module and barrier, farmland all areas are drawn into a submodule using genetic algorithm compiling
Optimal overlay path：The path covers whole region, all submodules in whole region is compiled into one from starting point
Data chain, agricultural machinery reach all standing of all submodules according to compiled optimization path operation.
5. the method for farm machinery all standing trajectory path planning according to claim 1, it is characterized in that：Using A* algorithms
The end point that region is finished in operation draws an optimal path, agriculture between 2 points of starting point for needing to start operating area
Machine enters subsequent region operation according to the optimal path.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108681321A (en) * | 2018-04-10 | 2018-10-19 | 华南理工大学 | A kind of undersea detection method that unmanned boat collaboration is formed into columns |
| CN110375735A (en) * | 2018-09-18 | 2019-10-25 | 天津京东深拓机器人科技有限公司 | Paths planning method and device |
| CN110502007A (en) * | 2019-07-23 | 2019-11-26 | 浙江工业大学 | A kind of automation casting concrete all standing trajectory path planning method |
| CN111176286A (en) * | 2020-01-06 | 2020-05-19 | 重庆邮电大学 | Mobile robot path planning method and system based on improved D-lite algorithm |
| WO2020147326A1 (en) * | 2019-01-18 | 2020-07-23 | 丰疆智能科技研究院(常州)有限公司 | Route management system and management method thereof |
| CN112097762A (en) * | 2020-09-11 | 2020-12-18 | 上海高仙自动化科技发展有限公司 | Path planning method and device, robot and storage medium |
| CN112965485A (en) * | 2021-02-03 | 2021-06-15 | 武汉科技大学 | Robot full-coverage path planning method based on secondary region division |
| CN113359699A (en) * | 2021-05-08 | 2021-09-07 | 五邑大学 | Full-coverage path planning method and device and storage medium |
| CN114323019A (en) * | 2021-11-30 | 2022-04-12 | 潍坊中科晶上智能装备研究院有限公司 | Method for planning all-covering path of agricultural machinery in complex environment |
| WO2023125512A1 (en) * | 2021-12-31 | 2023-07-06 | 丰疆智能(深圳)有限公司 | Navigation path planning method and apparatus, and storage medium |
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Cited By (13)
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| CN108681321B (en) * | 2018-04-10 | 2021-05-14 | 华南理工大学 | Underwater detection method for unmanned ship cooperative formation |
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| CN110375735A (en) * | 2018-09-18 | 2019-10-25 | 天津京东深拓机器人科技有限公司 | Paths planning method and device |
| CN110375735B (en) * | 2018-09-18 | 2021-05-25 | 北京京东乾石科技有限公司 | Path planning method and device |
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| CN110502007A (en) * | 2019-07-23 | 2019-11-26 | 浙江工业大学 | A kind of automation casting concrete all standing trajectory path planning method |
| CN111176286A (en) * | 2020-01-06 | 2020-05-19 | 重庆邮电大学 | Mobile robot path planning method and system based on improved D-lite algorithm |
| CN112097762A (en) * | 2020-09-11 | 2020-12-18 | 上海高仙自动化科技发展有限公司 | Path planning method and device, robot and storage medium |
| CN112965485A (en) * | 2021-02-03 | 2021-06-15 | 武汉科技大学 | Robot full-coverage path planning method based on secondary region division |
| CN113359699A (en) * | 2021-05-08 | 2021-09-07 | 五邑大学 | Full-coverage path planning method and device and storage medium |
| CN113359699B (en) * | 2021-05-08 | 2024-01-12 | 五邑大学 | Full-coverage path planning method, device and storage medium |
| CN114323019A (en) * | 2021-11-30 | 2022-04-12 | 潍坊中科晶上智能装备研究院有限公司 | Method for planning all-covering path of agricultural machinery in complex environment |
| WO2023125512A1 (en) * | 2021-12-31 | 2023-07-06 | 丰疆智能(深圳)有限公司 | Navigation path planning method and apparatus, and storage medium |
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Application publication date: 20180327 |