CN109459031A - A kind of unmanned plane RRT method for optimizing route based on greedy algorithm - Google Patents
A kind of unmanned plane RRT method for optimizing route based on greedy algorithm Download PDFInfo
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- CN109459031A CN109459031A CN201811477330.4A CN201811477330A CN109459031A CN 109459031 A CN109459031 A CN 109459031A CN 201811477330 A CN201811477330 A CN 201811477330A CN 109459031 A CN109459031 A CN 109459031A
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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
- G01C21/20—Instruments for performing navigational calculations
Abstract
The invention belongs to unmanned plane applied technical fields, a kind of unmanned plane RRT method for optimizing route based on greedy algorithm are disclosed, with qinitFor current point qi, initialize n=0；From qiStart to Q centrostigma qm‑nCarry out collision detection, n ∈ [0,1,2... (m-i-1)], i.e., in qiWith qm‑nLine on uniformly take at a certain distance a little；It judges whether there is a little on barrier or except map, turns to step 4 if it exists, otherwise turn to step 5；There are barriers, i.e., for line by that can not fly area, n=n+1 judges qiIt whether is qm‑n‑1, if it is i=i+1；Otherwise it returns；There is no barriers, connect qiAnd qm‑n, make qi=qm‑nGo to step 6；Judge whether i is equal to m；It is to terminate program.The present invention is for unmanned plane RRT algorithm path planning, with shortening its path, result made to reach instantly optimal using greedy thought, path point is reduced, and path significantly optimized, and has certain engineering value using upper in unmanned plane or other robot path planning.
Description
Technical field
The invention belongs to unmanned plane applied technical field more particularly to a kind of paths unmanned plane RRT based on greedy algorithm
Optimization method.
Background technique
Currently, the prior art commonly used in the trade is such that
RRT algorithm, which is called, quickly expands random tree method, is a kind of method based on sampling, by generating in feas ible space
Random point carries out path planning.Stochastical sampling in the random tree method of Quick Extended space first, then using starting point as expansion
The root node of tree, scans for surroundings nodes.Feasible node is chosen as path point by collision detection, and root node is added
List.By the way that search tree is constantly oriented to white space, the random tree route map there are access is constructed, is reached until expanding tree
Terminate expansion tree within ending range, finally since terminal the root node of reverse search path point upper level until starting point,
A feasible path is thus formed as flight path.RRT advantage: without carrying out Accurate Model to environment, reduce operation
Amount and program complexity；With probability completeness, a feasible path can be centainly cooked up as long as having access；Conveniently add
Add various dynamics and kinematical constraint；Without local minimum problem, seldom there is the case where endless loop and collision；It shows
The property that regional area is quickly planned, and can quick avoidance by the method for stochastical sampling.RRT disadvantage: due to from node
Search has certain blindness and diversity outward, all different per the route generated all the way；The route planned simultaneously is very
Complications do not have optimality, and most of is not shortest path, and it is elongated that random search also results in planning time；It is needed when planning
It learns global map in advance, actually belongs to segregation reasons, it is necessary to just can be carried out planning after exploring to global map.
In conclusion problem of the existing technology is:
(1) in the prior art, how tortuous RRT algorithm generation path is, and generating path point has randomness, and path does not have most
Dominance causes planning time long, wastes time, and reduces working efficiency.
(2) in the prior art unmanned plane cannot smoothly be turned with certain speed on path, non-stop flight so that work not
With continuity, using effect is reduced.
Solve the difficulty and meaning of above-mentioned technical problem:
The specific unmanned plane of one frame, necessarily there is certain endurance.When complex space executes task, if according to the side RRT
The path flight that method is cooked up, then will appear the case where loitering, can not non-stop flight.This makes the too fast of power consumption,
Reduce effective time and the speed of execution task.
The path that RRT algorithmic rule goes out is than more tortuous, in certain access, certainly exist certain destinations with across multiple
Barrier is equally not present between destination after destination.If by certain methods, by these across destination reject, then can
The distance and tortuosity in path is effectively reduced.
Summary of the invention
In view of the problems of the existing technology, the present invention provides a kind of, and the path unmanned plane RRT based on greedy algorithm is excellent
Change method.How tortuous RRT algorithm generation path is, and generating path point has randomness, and path does not have optimality, in order to make RRT
The path of generation is optimized, the smoothing algorithm that the invention enables paths to shorten, smooth, in order to make unmanned plane on path with one
Determine rate smoothing turning, non-stop flight, joined the curve-fitting method based on interpolation method, optimize track.
The invention is realized in this way first obtaining a connection source based on RRT algorithm before carrying out greedy algorithm
qinitWith target point qgoalPath, the point q on original pathiPath in ∈ Q, i=1,2...m but Q is excessively tortuous, because
This needs to be smoothed by greedy algorithm.It is so-called smooth, it refers to rejecting the point that need not be passed by.
In point set Q, the process based on greedy algorithm path smooth are as follows:
Step 1: with qinitAs current point qi, initialize n=0；
Step 2: from qiStart to Q centrostigma qm-nCarry out collision detection, n ∈ [0,1,2... (m-i-1)], i.e., in qiWith
qm-nLine on uniformly take at a certain distance a little；
Step 3: whether the uniform point generated in judgment step two is on barrier or except map.Due to RRT algorithm
It is Global motion planning algorithm, having known in advance can be by space Cfree and Obstacles Cobs.It only needs to calculate qiWith qm-n
Line on point, the distance of the point in distance Cobs, can judge whether there is point on barrier or map it
Outer point.Step 4 is turned to if it exists, turns to step 5 if it does not exist；It uniformly takes a little and can be counted according to the following formula apart from calculating
It calculates, wherein d is distance, and x, y are respectively abscissa and ordinate in plane, and R is the step-length uniformly taken a little；
Step 4: there are barriers, i.e., for line by that can not fly area, n=n+1 judges qiIt whether is qm-n-1, if it is
I=i+1 goes to 6；Otherwise, return step two；
Step 5: being not present barrier, connects qiAnd qm-n, make qi=qm-nGo to step 6；
Step 6: judge whether i is equal to m；If it is terminate program, otherwise go to step 2.
Another object provided by the invention is for the above process, the greedy algorithm pseudocode provided, specifically:
(1) i=1 is initialized, n=0, m are path point quantity
(2)fori≠m
(3) to qiAnd qm-nCarry out collision detection；
(4)ifcollision(qi, qm-n)=0
(5) q is connectediAnd qm-n, by qm-nNew path list is added；
(6) i=m-n, n=0, continue；
(7) else n=n+1；
(8)ifi≠m-n-1
(9)continue；
(10)else i++；
(11)end
(12)end
(13)end。
In conclusion advantages of the present invention and good effect are as follows: such as attached drawing 2- Fig. 6, wherein short broken line is that RRT algorithm obtains
Path, it is clear that be very tortuous.Long broken line is the result that destination is rejected by greedy algorithm.Obviously the point that long broken line passes through
Many less, the path by the region that this makes is more smooth.As shown in table 1, by being reduced before the ratio of smoothed out path
A part of length, the path distance for being shorten, and help to save through time and kinergety.
The excessively tortuous situation in the path that the present invention is obtained for unmanned plane RRT algorithm path planning, devises using greedy
The method that center algorithm rejects unnecessary destination.By rejecting redundancy destination, optimize broken line curvature, to reach the mesh for shortening path
, so that program results is reached instantly optimal, path point is reduced, and path has obtained significantly optimizing, in unmanned plane or other machines
People's path planning has certain engineering value using upper.
Detailed description of the invention
Fig. 1 is the unmanned plane RRT method for optimizing route process flow diagram flow chart provided in an embodiment of the present invention based on greedy algorithm.
Fig. 2 is greedy algorithm path smooth schematic diagram provided in an embodiment of the present invention.
Fig. 3 is the smooth schematic diagram of barrier map path provided in an embodiment of the present invention.
Fig. 4 is map path smooth schematic diagram in labyrinth provided in an embodiment of the present invention.
Fig. 5 is provided in an embodiment of the present invention to smooth rear path fitting schematic diagram.
Fig. 6 is provided in an embodiment of the present invention to original path fitting schematic diagram.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not used to
Limit the present invention.
In order to keep generation path shorter and less turnover, it should smoothing algorithm be added, the smoothing algorithm used here is
Greedy algorithm.Greedy algorithm refers in Solve problems, always makes the best selection of present case, is not subject in global optimum
Consider, but reaches locally optimal solution in some sense.In path smooth, the strategy of greedy algorithm is to obtain path
On, the optimal feasible path of distance is obtained as far as possible.
Greedy algorithm path smooth process provided in an embodiment of the present invention: one is obtained by RRT algorithm first and is connected
Point qinitWith target point qgoalPath, the point q on original pathi∈ Q, i=1,2...m, in point set Q:
As shown in Figure 1, the unmanned plane RRT method for optimizing route provided in an embodiment of the present invention based on greedy algorithm include with
Lower step:
S101: with qinitAs current point qi, initialize n=0；
S102: from qiStart to Q centrostigma qm-nCarry out collision detection, n ∈ [0,1,2... (m-i-1)], i.e., in qiWith qm-n
Line on uniformly take at a certain distance a little；
S103: it judges whether there is a little on barrier or except map, turns to S104 if it exists, turn to if it does not exist
S105；
S104: there are barriers, i.e., for line by that can not fly area, n=n+1 judges qiIt whether is qm-n-1, if it is i
=i+1, goes to 6；Otherwise, S102 is returned；
S105: being not present barrier, connects qiAnd qm-n, make qi=qm-nGo to S106；
S106: judge whether i is equal to m；If it is terminate program, otherwise go to S102.
Greedy algorithm pseudocode provided in an embodiment of the present invention, specifically:
(1) i=1 is initialized, n=0, m are path point quantity
(2)fori≠m
(3) to qiAnd qm-nCarry out collision detection；
(4)ifcollision(qi, qm-n)=0
(5) q is connectediAnd qm-n, by qm-nNew path list is added；
(6) i=m-n, n=0, continue；
(7) else n=n+1；
(8)ifi≠m-n-1
(9)continue；
(10)else i++；
(11)end
(12)end
(13)end。
Application principle of the invention is described in further detail below with reference to specific l-G simulation test；
Improved RRT algorithm is obtained by the present invention, including standard RRT algorithm, smoothing algorithm, curve fitting algorithm combine
Improvement RRT algorithm.
As Figure 3-Figure 4, simulating, verifying experimental enviroment is round barrier map and labyrinth type map.Parameter setting: K
=10000, p=0.3, step-length q=30.
Operating condition one: round barrier map, starting point [50,50] terminal [350,425]
Operating condition two: labyrinth type map, starting point [60,60] terminal [400,400]
As shown in table 1, to improving front and back algorithm performance to when analyzing；
Table 1: front and back algorithm performance comparison is improved
As a result: after smoothing algorithm carries out path optimization, generating path length and obviously shorten, smoothed out path is pointed out
It is aobvious to reduce；In round barrier map, smoothing algorithm reduces the ratio substantially 19.08% of distance, in labyrinth type map
The distance ratio substantially 16.70% of reduction；It is reduced to units substantially in the ground path in graphs point of this research.It demonstrates flat
Sliding algorithm reduces path length and tortuous useful effect.
As shown in Fig. 5-Fig. 6, in the map of complex environment labyrinth, it is quasi- that B-spline is carried out to smoothed out route (black line segment)
Path (green curve) after conjunction is easy to happen the collision with barrier；If be fitted to original route, seldom send out
Raw collision, and route has also obtained smoothly.
So after being smoothed, carrying out curve to the path after smoothing processing in the avoidance of simple environment
Fitting, gained route levels off to optimal.
In complex environment, can there are two types of strategies, first is that be only smoothed, the straight-line segment after being optimized, nobody
Machine control strategy is to go to after path point stops, and deflecting continues to next path point, path is shorter level off to it is optimal；
Second of strategy is only to carry out curve fitting, and unmanned plane can be with average rate smoothly through path, and route is slightly tortuous, but ensure that nothing
Man-machine flight safety.
As a result: the present invention has for unmanned plane RRT algorithm path planning and shortens its path, makes to tie using greedy thought
Fruit reaches instantly optimal, and path point is reduced, and path obtained significantly optimizing, in unmanned plane or other robot path planning
There is certain engineering value using upper.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (4)
1. a kind of unmanned plane RRT method for optimizing route based on greedy algorithm, which is characterized in that described based on greedy algorithm
The greedy algorithm path smooth process of unmanned plane RRT method for optimizing route: a connection source q is obtained by RRT algorithminitWith
Target point qgoalPath, the point q on original pathi∈ Q, i=1,2...m, in point set Q.
2. the unmanned plane RRT method for optimizing route based on greedy algorithm as described in claim 1, which is characterized in that the base
It is specifically included in the unmanned plane RRT method for optimizing route of greedy algorithm:
Step 1: with qinitAs current point qi, initialize n=0；
Step 2: from qiStart to Q centrostigma qm-nCarry out collision detection, n ∈ [0,1,2... (m-i-1)], i.e., in qiWith qm-n's
It is uniformly taken at a certain distance a little on line；
Step 3: it judges whether there is a little on barrier or except map, turns to step 4 if it exists, turn to if it does not exist
Step 5；
Step 4: there are barriers, i.e., for line by that can not fly area, n=n+1 judges qiIt whether is qm-n-1, if it is i=i
+ 1, go to 6；Otherwise, return step two；
Step 5: being not present barrier, connects qiAnd qm-n, make qi=qm-nGo to step 6；
Step 6: judge whether i is equal to m；If it is terminate program, otherwise go to step 2.
3. the unmanned plane RRT method for optimizing route based on greedy algorithm as claimed in claim 2, which is characterized in that described greedy
Center algorithm pseudocode specifically:
(1) i=1 is initialized, n=0, m are path point quantity；
(2)fori≠m；
(3) to qiAnd qm-nCarry out collision detection；
(4)if collision(qi, qm-n)=0
(5) q is connectediAnd qm-n, by qm-nNew path list is added；
(6) i=m-n, n=0, continue；
(7) elsen=n+1；
(8)ifi≠m-n-1
(9)continue；
(10)else i++；
(11)end
(12)end
(13)end。
4. a kind of nothing using the unmanned plane RRT method for optimizing route described in claims 1 to 3 any one based on greedy algorithm
It is man-machine.
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| CN110162104A (en) * | 2019-06-14 | 2019-08-23 | 哈尔滨工业大学 | The RRT unmanned plane paths planning method of imitative Driver Vision perception |
| CN110260875A (en) * | 2019-06-20 | 2019-09-20 | 广州蓝胖子机器人有限公司 | A kind of method in Global motion planning path, Global motion planning device and storage medium |
| CN110361017A (en) * | 2019-07-19 | 2019-10-22 | 西南科技大学 | A kind of full traverse path planing method of sweeping robot based on Grid Method |
| CN111736582A (en) * | 2019-03-19 | 2020-10-02 | 北京奇虎科技有限公司 | Path processing method and device, electronic equipment and computer readable storage medium |
| CN111752281A (en) * | 2020-07-13 | 2020-10-09 | 浪潮软件股份有限公司 | Mobile robot path planning method and system based on improved RRT algorithm |
| CN112229410A (en) * | 2020-10-15 | 2021-01-15 | 西华大学 | Wheelchair user path planning method based on greedy algorithm |
| CN112711267A (en) * | 2020-04-24 | 2021-04-27 | 江苏方天电力技术有限公司 | Unmanned aerial vehicle autonomous inspection method based on RTK high-precision positioning and machine vision fusion |
| CN112799069A (en) * | 2020-12-30 | 2021-05-14 | 上海海事大学 | Ice region navigation sea ice obstacle avoidance path generation method based on navigation radar image |
| CN113124891A (en) * | 2021-04-20 | 2021-07-16 | 东软睿驰汽车技术（沈阳）有限公司 | Driving path planning method and related device |
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| CN111752281A (en) * | 2020-07-13 | 2020-10-09 | 浪潮软件股份有限公司 | Mobile robot path planning method and system based on improved RRT algorithm |
| CN112229410A (en) * | 2020-10-15 | 2021-01-15 | 西华大学 | Wheelchair user path planning method based on greedy algorithm |
| CN112799069A (en) * | 2020-12-30 | 2021-05-14 | 上海海事大学 | Ice region navigation sea ice obstacle avoidance path generation method based on navigation radar image |
| CN112799069B (en) * | 2020-12-30 | 2024-02-13 | 上海海事大学 | Method for generating sea ice obstacle avoidance path of ice region navigation based on navigation radar image |
| CN113124895A (en) * | 2021-04-19 | 2021-07-16 | 武汉齐物科技有限公司 | Code table navigation route generation method and code table |
| CN113124891A (en) * | 2021-04-20 | 2021-07-16 | 东软睿驰汽车技术（沈阳）有限公司 | Driving path planning method and related device |
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| RJ01 | Rejection of invention patent application after publication |