CN109520507A - A kind of unmanned plane real-time route planing method based on improvement RRT - Google Patents
A kind of unmanned plane real-time route planing method based on improvement RRT Download PDFInfo
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Abstract
The invention belongs to unmanned plane operating technology fields, disclose a kind of based on the unmanned plane real-time route planing method for improving RRT, building local rolling window；The setting of sub-objective point；Local RRT tree algorithm stochastical sampling planning；Algorithm termination principle.The present invention is improved and is merged to the algorithm for being only applicable to Global motion planning originally, using the environmental information according to known to part, is constructed window, is determined specific item punctuate by some way, explored in the environment using Global motion planning algorithm.During window rolls and advances, the environmental information in window is constantly updated, and is realized that figure and feedback are built in planning, is eventually arrived at target point.For RRT algorithm, Global motion planning, this improved method based on rolling window are compared, random search need not be carried out to entire space, but planning is limited in the window of numerous continuous updating, and the range of random search reduces, calculation amount reduces, and may be implemented to plan online.
Description
Technical field
The invention belongs to unmanned plane operating technology field more particularly to a kind of unmanned plane real-time routes based on improvement RRT
Planing method.
Background technique
It is fitted currently, the prior art commonly used in the trade is such that Quick Extended random tree (RRT) paths planning method has
Many advantages, such as Ying Xingqiang, formation speed be fast, probability completeness, but it must be fixed against known global map, it just can be carried out rule
It draws.So in general RRT is a kind of Global Planning, the real-time routes that cannot achieve unmanned plane are generated.But with nothing
Extensiveization of man-machine application, only consider in task environment indoors a global static barrier be it is inadequate, deposited in indoor environment
In uncertain and dynamic barrier, corresponding Robot dodge strategy should be also studied.Sector planning is to local information collection
And feasible path is cooked up within a certain area, when environment is Dynamic Uncertain, sector planning can be in real time with newly scanning number
According to so that programme path is again to make a response to environmental change.It is real that such online planning system meets planning well
Shi Xing, it is therefore an objective to really realize independent navigation and the flight of unmanned plane.Common sector planning method has rolling window planning, moves
State planning, Artificial Potential Field planing method etc..
Rolling window planning is also referred to as dynamic window method (Dynamic Window Approach, DWA), its original substantially
Reason is to carry out forecast analysis, feedback regulation action planning to action according to local environmental information manufacturing planning window.Rolling window
Method is a kind of feasible method for online coordinates measurement, and window planning each time only generates the path in a local environment,
Next track points are reached, are planned next time further according to the environmental information of detection, do not need disposably to complete for the overall situation
Environment detection.
Artificial Potential Field Method is a kind of thought based on potential energy in analogy physics, and path planning problem is analogized in space
The problem of finding potential energy optimal solution.Target point is regarded as the point of the potential energy minimum in space (can be approximately considered is 1 potential energy point) by it,
The potential energy of barrier is infinity in space, simulates unmanned plane by the attraction of target point and the repulsive force of barrier, thus
The potential energy field of a Manual definition is obtained in space, unmanned plane can be intended to move on low-potential energy direction, form one
The track that potential energy gradually decreases, if potential energy field be in space it is continuous and only have a minimum when, gesture can be reached
It can minimum point, i.e. target point.But when the potential energy field in space has multiple minimums, then the local minimum point of non-targeted point will lead to
Potential energy more low spot can not be found after unmanned plane arrival Local Minimum causes path planning to lose to can not reach target point forever
It loses.
In conclusion problem of the existing technology is:
(1) algorithm of the prior art is only applicable to Global motion planning, causes to be restricted, inconvenient, reduces service efficiency.
(2) it needing to carry out random search to entire space in the prior art, the range of random search is big, and calculation amount increases,
It can not effectively realize online planning.
Solve the difficulty and meaning of above-mentioned technical problem:
Existing mature technology is all the path planning carried out in situation known to global map.Actually in many feelings
Under condition, unmanned plane is to execute task in circumstances not known.Therefore global map also can not just be obtained ahead of time, and then can not carry out complete
The path planning of office.This, which allows for Global Planning, above has limitation in application.
Thus propose the improvement RRT algorithm based on rolling window.Due to only planning the path near unmanned plane, thus it is complete
Local figure need not be known.This greatly promotes unmanned plane in the survival ability of circumstances not known.
Summary of the invention
In view of the problems of the existing technology, the present invention provides a kind of based on the unmanned plane real-time route rule for improving RRT
The method of drawing.
The invention is realized in this way a kind of based on the unmanned plane real-time route planing method for improving RRT, including following step
It is rapid:
Step 1: building local rolling window obtains local environmental information, building office by the sensor of UAV flight
Portion's rolling window；
Step 2: the setting of sub-objective point, specific item punctuation bit are selected on the boundary of rolling window on boundary
Point that is feasible and meeting certain global map condition, as sub-objective point；
Step 3: local RRT tree algorithm stochastical sampling planning, it is to terminate that the planning in window, which not arrived sub-goal,
Window edge whether is reached as termination condition using the planning of feasible path, when RRT extends to window edge, is then stopped to sub-goal
Point planning, establishes new Rolling Planning centered on new node；
Step 4: algorithm termination principle.
Further, in step 1, local rolling window is constructed, specifically:
Local environmental information is obtained by the sensor of UAV flight, the window of planning is driven in the form of the period, often
The window area of the primary system plan is Ein (qR(tt)=p | p ∈ C, d (q, qR(t))≤R }, qR(t) it indicates in rolling window
The heart, R are the radiuses of rolling window, generally the radius of investigation of sensor.
Further, in step 2, the setting of sub-objective point is specifically included:
It will be located on rolling window boundary and be located at current point and target point qgoalPoint on line is as specific item punctuate
qtemp goal；
By (xc, yc) center as current scrolling window, radius is that the circle of dotted line of R is rolling window range, (xg,
yg) it is global object point, (xt0, yto) be window center Yu target point line and circle of dotted line intersection point, be defined as sub-objective
Point qtemp goal。
Because during RRT branch is expanded, the direction of growth of branch depends on qrandRandom selection, do not reach at target point
When, as long as the q generatedrandIn area of feasible solutions and close to specific item punctuate qtemp goal, branch will be to feasible and deviation target point
Direction growth.If specific item punctuate, on barrier, the RRT of standard can not be reached if planning, at this time then in the upper random generation of circle
Feasible specific item punctuate, it is therefore an objective to the feasible path for reaching window edge is quickly generated in region.
2 π of theta=rand () (2)
At this point, the random node selection of RRT should consider and the relationship of specific item punctuate and how stop search in window.
Further, in step 3, local RRT tree algorithm stochastical sampling planning is specifically included:
Definition circle is upper random a little and horizontal line angulation is θ=β+α, and β is qrandThe angle of polaron target point, will
The selection of θ is configured to a normal function symmetrical about α；I.e.
β=randn π
Therefore the angle beta in (- 180 °, 180 °) interior random distribution is constructed, with the selection of angle beta polaron target point
qrand；
Planning in window not arrived sub-goal to terminate, because specific item punctuate, which is likely to be in, threatens area, but
Window edge whether is reached as termination condition using the planning of feasible path, when RRT extends to window edge, is then stopped to sub-goal
Point planning, establishes new Rolling Planning centered on new node.
Further, in step 4, algorithm termination principle, specially
When rolling window is rolled to global object point again and again, as global object point qgoalFor in rolling window
In the range of, i.e. d (qgoal, qR(t))≤R, then directly with qgoalIt is planned as target point, reaches qgoal, algorithm terminates.
Another object of the present invention is to provide rolling RRT algorithm substantially process it is as follows:
(1) variable of RRT tree in rolling window is initialized；
(2) judge qgoalWhether it is located in rolling window, if it is goes to step 3, be not to go to step 4；
(3) by qgoalAs target point, node q is generated at random on boundaryrand；
(4) sub-objective point q is obtained on rolling window boundarytempgoal, random node q is generated on boundaryrand；
(5) in the nearest tree node q of current Tree Species Selectionnear, and node q is generated according to certain step-lengthnew；
(6) in qnear、qnewCollision detection is carried out on line；
(7) judge qnewWhether be in can fly area and qnear、qnewClear is distributed on line, if being unsatisfactory for, returns to step
Rapid 2, step 6 is gone to if meeting；
(8) by qnewTree list is added, judgement is to reach qgoal, if not then going to step 9；It is to terminate algorithm；
(9) judge whether that the boundary for reaching rolling window if it is goes to step 10 if not then return step 2；
(10) from qnewReverse search obtains local path, and with qnewCentered on establish new rolling window, return step
1；
In conclusion advantages of the present invention and good effect are as follows:
The present invention can be improved and be merged to the algorithm for being only applicable to Global motion planning originally, using according to known to part
Environmental information, construct window, specific item punctuate is determined by some way, then in the environment using Global motion planning algorithm into
Row is explored.During window rolls and advances, the environmental information in window is constantly updated, and realizes that figure and feedback are built in planning, most
Zhongdao reaches target point.For RRT algorithm, Global motion planning, this improved method based on rolling window, it is not necessary to whole are compared
A space carries out random search, but planning is limited in the window of numerous continuous updating, and the range of random search reduces,
Calculation amount reduces, and may be implemented to plan online.
Detailed description of the invention
Fig. 1 is provided in an embodiment of the present invention based on the unmanned plane real-time route planing method flow chart for improving RRT.
Fig. 2 is rolling RRT sub-goal point selection figure provided in an embodiment of the present invention.
Fig. 3 is simulation result of the rolling RRT provided in an embodiment of the present invention in round barrier；
In figure: a q=50；B is q=30；C is q=20；D is q=10.
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.
Application principle of the invention is described in detail with reference to the accompanying drawing.
As shown in Figure 1, it is provided in an embodiment of the present invention based on the unmanned plane real-time route planing method for improving RRT, including
Following steps:
S101: building local rolling window obtains local environmental information, building part by the sensor of UAV flight
Rolling window；
S102: the setting of sub-objective point, specific item punctuation bit is on the boundary of rolling window, i.e., selection can on boundary
The point for going and meeting certain global map condition, as sub-objective point；
S103: local RRT tree algorithm stochastical sampling planning, it is to terminate that the planning in window, which not arrived sub-goal, with
It is termination condition that whether the planning of feasible path, which reaches window edge, when RRT extends to window edge, is then stopped to specific item punctuate
Planning, establishes new Rolling Planning centered on new node；
S104: algorithm termination principle.
In step S101, building local rolling window provided in an embodiment of the present invention, specifically:
Local environmental information is obtained by the sensor of UAV flight, the window of planning is driven in the form of the period, often
The window area of the primary system plan is Win (qR(t))=p | p ∈ C, d (q, qR(t))≤R }, qR(t) it indicates in rolling window
The heart, R are the radiuses of rolling window, generally the radius of investigation of sensor.
In step S102, the setting of sub-objective point provided in an embodiment of the present invention is specifically included:
It will be located on rolling window boundary and be located at current point and target point qgoalPoint on line is as specific item punctuate
qtemp goal；
By (xc, yc) center as current scrolling window, radius is that the circle of dotted line of R is rolling window range, (xg,
yg) it is global object point, (xt0, yto) be window center Yu target point line and circle of dotted line intersection point, be defined as sub-objective
Point qtrmp goal。
Because during RRT branch is expanded, the direction of growth of branch depends on qrandRandom selection, do not reach at target point
When, as long as the q generatedrandIn area of feasible solutions and close to specific item punctuate qtemp goal, branch will be to feasible and deviation target point
Direction growth.If specific item punctuate, on barrier, the RRT of standard can not be reached if planning, at this time then in the upper random generation of circle
Feasible specific item punctuate, it is therefore an objective to the feasible path for reaching window edge is quickly generated in region.
2 π of theta=rand () (2)
At this point, the random node selection of RRT should consider and the relationship of specific item punctuate and how stop search in window.
In step S103, RRT tree algorithm stochastical sampling planning in part provided in an embodiment of the present invention is specifically included:
Definition circle is upper random a little and horizontal line angulation is θ=β+α, and β is qrandThe angle of polaron target point, will
The selection of θ is configured to a normal function symmetrical about α；I.e.
β=randn π
Therefore the angle beta in (- 180 °, 180 °) interior random distribution is constructed, with the selection of angle beta polaron target point
qrand；
Planning in window not arrived sub-goal to terminate, because specific item punctuate, which is likely to be in, threatens area, but
Window edge whether is reached as termination condition using the planning of feasible path, when RRT extends to window edge, is then stopped to sub-goal
Point planning, establishes new Rolling Planning centered on new node.
In step S105, algorithm termination principle provided in an embodiment of the present invention, specially
When rolling window is rolled to global object point again and again, as global object point qgoalFor in rolling window
In the range of, i.e. d (qgoal, qR(t))≤R, then directly with qgoalIt is planned as target point, reaches qgoal, algorithm terminates.
The substantially process provided in an embodiment of the present invention for rolling RRT algorithm is as follows:
(1) variable of RRT tree in rolling window is initialized；
(2) judge qgoalWhether it is located in rolling window, if it is goes to step 3, be not to go to step 4；
(3) by qgoalAs target point, node q is generated at random on boundaryrand；
(4) sub-objective point q is obtained on rolling window boundarytemp goal, random node q is generated on boundaryrand；
(5) in the nearest tree node q of current Tree Species Selectionnear, and node q is generated according to certain step-lengthnew；
(6) in qnear、qnewCollision detection is carried out on line；
(7) judge qnewWhether be in can fly area and qnear、qnewClear is distributed on line, if being unsatisfactory for, returns to step
Rapid 2, step 6 is gone to if meeting；
(8) by qnewTree list is added, judgement is to reach qgoal, if not then going to step 9；It is to terminate algorithm；
(9) judge whether that the boundary for reaching rolling window if it is goes to step 10 if not then return step 2；
(10) from qnewReverse search obtains local path, and with qnewCentered on establish new rolling window, return step
1；
Working principle part provided in an embodiment of the present invention:
Using rolling window planning algorithm as basic framework, using RRT algorithm as Path Planning in each window, and lead to
The trimming in path is crossed with smoothly, the RRT expansion tree of regional area is formed, connects current point and sub-objective point, realize movement
Control and feedback regulation, update window information after reaching new path point, carry out path planning with RRT method again.
Application principle of the invention is described in further detail combined with specific embodiments below；
Embodiment 1；
1, local rolling window is constructed
Local environmental information is obtained by the sensor of UAV flight, and the window of planning is driven in the form of the period
Dynamic, defining the window area planned each time is Win (q_R (t))={ p | p ∈ C, d (q, q_R (t))≤R }, and q_R (t) is indicated
The center of rolling window, R are the radiuses of rolling window, generally the radius of investigation of sensor.Above-mentioned window is also referred to as unmanned plane
View field.
Since unmanned plane is in real-time routes planning and during independent navigation, it is desirable to keep certain speed continuous
Flight, without advancing again after stopping waiting window planning next time to produce path.So for non-stop flight, it is necessary to
Before not reaching sub-objective point, with regard to carrying out next window planning in advance, the target point when preplanning is regarded and is advised next time
Draw the center of window.After obtaining Rolling Planning route next time, unmanned plane is then completed specifically to plan left point and next road
The stepping of diameter and path smooth processing.The component environment information for knowing next window in advance is needed exist for, is slightly less than so defining R
The radius of investigation of sensor is to can satisfy the scrolling windows that building is greater than one under the local environment that detector obtains
Mouthful.
2, the selection of sub-objective point
The selection of sub-objective point in rolling RRT, it should meet the mapping that it is global object point, and can
It is a feasible path point with avoiding obstacles region.In general, in order to fully utilize the office in rolling window
Portion's environmental information, define specific item punctuation bit on the boundary of rolling window, i.e., selected on boundary it is feasible and meet certain the overall situation
The point of mapping condition, as sub-objective point.Here
It will be located on rolling window boundary and be located at current point and target point qgoalPoint on line is as specific item punctuate
qtemp goal。
As shown in Fig. 2, by (xc, yc) center as current scrolling window, radius is that the circle of dotted line of R is rolling window
Range, (xg, yg) it is global object point, (xt0, yto) be window center Yu target point line and circle of dotted line intersection point, be defined as office
Portion specific item punctuate qtemp goal。
Because during RRT branch is expanded, the direction of growth of branch depends on qrandRandom selection, do not reach at target point
When, as long as the q generatedrandIn area of feasible solutions and close to specific item punctuate qtemp goal, branch will be to feasible and deviation target point
Direction growth.If specific item punctuate, on barrier, the RRT of standard can not be reached if planning, at this time then in the upper random generation of circle
Feasible specific item punctuate, it is therefore an objective to the feasible path for reaching window edge is quickly generated in region.
2 π of theta=rand () (2)
At this point, the random node selection of RRT should consider and the relationship of specific item punctuate and how stop search in window.
3, part RRT algorithm stochastic sampling strategy
From the point of view of the expanding course set each time from RRT, random node qrandSelection be have in entire space it is random
Property, here qrandSelectional restriction on the boundary of rolling window, developed, qrandCircumference in Fig. 2 will be selected as with Probability p
On specific item punctuate (xt0, yto), the probability selection of (1-p) is any point on circumference, such as the random point (x in figuret, yt).Institute
With qrandIt can be intended to point close apart from specific item punctuate on circumference to choose, and bigger closer to specific item punctuate probability, if qrand?
It is then chosen again on barrier.
As shown in Fig. 2, definition circle is upper random a little and horizontal line angulation is θ=β+α, β is qrandDeviate sub-goal
The angle of point, is configured to a normal function symmetrical about α for the selection of θ.I.e.
β=randn π
Therefore the angle beta in (- 180 °, 180 °) interior random distribution is constructed, with the selection of angle beta polaron target point
qrand。
Planning in window not arrived sub-goal to terminate, because specific item punctuate, which is likely to be in, threatens area, but
Window edge whether is reached as termination condition using the planning of feasible path, when RRT extends to window edge, is then stopped to sub-goal
Point planning, establishes new Rolling Planning centered on new node.
4, algorithm termination principle
When rolling window is rolled to global object point again and again, as global object point qgoalFor in rolling window
In the range of, i.e. d (qgoal, qR(t))≤R, then directly with qgoalIt is planned as target point, reaches qgoal, algorithm terminates.
Embodiment 2；
The substantially process provided in an embodiment of the present invention for rolling RRT algorithm is as follows:
(1) variable of RRT tree in rolling window is initialized；
(2) judge whether to be located in rolling window, if it is go to step 3, be not to go to step 4；
(3) it will be used as target point, generate node at random on boundary
(4) sub-objective point is obtained on rolling window boundary, and random node is generated on boundary；
(5) in the nearest tree node of current Tree Species Selection, and node is generated according to certain step-length；
(6) collision detection is carried out on, line；
(7) judge whether that return step 2 if being unsatisfactory for such as meet in that can fly clear distribution on area and line
Then go to step 6；
(8) it will be added and set list, judgement is to reach, if not then going to step 9；It is to terminate algorithm；
(9) judge whether that the boundary for reaching rolling window if it is goes to step 10 if not then return step 2；
(10) local path is obtained from reverse search, and establishes new rolling window centered on, return step 1；
Application principle of the invention is described in further detail below with reference to specific l-G simulation test；
L-G simulation test 1；
The simulated environment of 500X500 is set, there is the round barrier of 4 distributions, rolling window radius is 100, explores step
A length of 50, starting point coordinate is (50,50), and terminal point coordinate is (400,400), respectively to step-length q=50 less than normal, 30,20,10
Situation is emulated, other parameters K=10000, p=0.3, rolling window radius R=100, and main investigate keeps away barrier
Hinder situation.And compare its executive condition with standard RRT in the case where identical step-length and probability.Computer hardware equipment is
Intel (R) single core processor 2.1GHz, inside saves as 4GB.Simulated program is worked out under MATLAB environment.
As shown in figure 3, the simulation result provided by the invention for rolling RRT in round barrier；
Wherein, q=50 in Fig. 3-a；Q=30 in Fig. 3-b；Q=20 in Fig. 3-c；Q=10 in Fig. 3-d；
As shown in figure 3, show in simulating, verifying this algorithm in real-time average cost 0.02s with regard to an achievable window
Planningization, first time window plan the deadline in 0.01-0.08s, in the case where not considering that unmanned plane is mobile and spending the time,
Planning time is short to meet the needs of unmanned plane real-time online path planning.
The selection strategy of random node is to be intended to the growth of specific item punctuate, and specific item punctuate is the mapping of global object, therefore
The generation of local tree is intended to target growth to a certain extent.Group target point is directly reflecting for global object point always
When penetrating, programme path can be very straight, although small step-length number of nodes in sector planning is more fastly for planning efficiency, shows
Different feature when for Global motion planning.The long route that generates of small step is shorter than big step-length, and generation number of windows is few, path smooth, and
It is more advantageous to the kinematical constraint for realizing unmanned plane, small step-length has given full play to advantage in sector planning
This algorithm for by RRT algorithm be applied to unmanned plane online in real time planning in have certain engineer application valence
Value.
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 (7)
1. a kind of based on the unmanned plane real-time route planing method for improving RRT, which is characterized in that described based on improvement RRT's
Unmanned plane real-time route planing method, comprising the following steps:
Step 1: building local rolling window obtains local environmental information by the sensor of UAV flight, constructs part rolling
Dynamic window；
Step 2: the setting of sub-objective point, specific item punctuation bit select feasible on the boundary of rolling window on boundary
And meet the point of certain global map condition, as sub-objective point；
Step 3: the planning of local RRT tree algorithm stochastical sampling, the planning in window not arrived sub-goal to terminate, with can
It is termination condition that whether the planning of walking along the street diameter, which reaches window edge, when RRT extends to window edge, then stops advising to specific item punctuate
It draws, new Rolling Planning is established centered on new node；
Step 4: algorithm termination principle.
2. as described in claim 1 based on the unmanned plane real-time route planing method for improving RRT, which is characterized in that the step
In rapid one, local rolling window is constructed, specifically:
Local environmental information is obtained by the sensor of UAV flight, the window of planning is driven in the form of the period, each time
The window area of planning is Win (qR(t))=p | p ∈ C, d (q, qR(t))≤R }, qR(t) center of rolling window is indicated, R is
The radius of rolling window, the generally radius of investigation of sensor.
3. as described in claim 1 based on the unmanned plane real-time route planing method for improving RRT, which is characterized in that the step
In rapid two, the setting of sub-objective point is specifically included:
It will be located on rolling window boundary and be located at current point and target point qgoalPoint on line is as specific item punctuate qtemp goal；
By (xc, yc) center as current scrolling window, radius is that the circle of dotted line of R is rolling window range, (xg, yg) it is complete
Office's target point, (xt0, yto) be window center Yu target point line and circle of dotted line intersection point, be defined as sub-objective point
qtemp goal:
If specific item punctuate, on barrier, the RRT of standard can not be reached if planning, then feasible specific item is generated at random on circle
Punctuate, it is therefore an objective to the feasible path for reaching window edge is quickly generated in region；
2 π of theta=rand ()；
The random node selection of RRT should consider and the relationship of specific item punctuate and how stop search in window.
4. as described in claim 1 based on the unmanned plane real-time route planing method for improving RRT, which is characterized in that the step
In rapid three, the planning of local RRT tree algorithm stochastical sampling is specifically included: circle on it is random any with horizontal line angulation for θ=β+
α, β are qrandThe selection of θ is configured to a normal function symmetrical about α by the angle of polaron target point:
β=randn π；
The angle beta in (- 180 °, 180 °) interior random distribution is constructed, q is selected with angle beta polaron target pointrand；When RRT prolongs
Window edge is reached, then stops planning to specific item punctuate, new Rolling Planning is established centered on new node.
5. as described in claim 1 based on the unmanned plane real-time route planing method for improving RRT, which is characterized in that the step
In rapid four, algorithm termination principle, specifically:
When rolling window is rolled to global object point again and again, as global object point qgoalFor in the model of rolling window
In enclosing, i.e. d (qgoal, qR(t))≤R, then directly with qgoalIt is planned as target point, reaches qgoal, algorithm terminates.
6. as described in claim 1 based on the unmanned plane real-time route planing method for improving RRT, which is characterized in that the base
In improve RRT unmanned plane real-time route planing method the following steps are included:
(1) variable of RRT tree in rolling window is initialized；
(2) judge qgoalWhether it is located in rolling window, if it is goes to step (3), be not to go to step (4)；
(3) by qgoalAs target point, node q is generated at random on boundaryrand；
(4) sub-objective point q is obtained on rolling window boundarytempgoal, random node q is generated on boundaryrand；
(5) in the nearest tree node q of current Tree Species Selectionnear, and node q is generated according to certain step-lengthnew；
(6) in qnear、qnewCollision detection is carried out on line；
(7) judge qnewWhether be in can fly area and qnear、qnewClear is distributed on line, the return step if being unsatisfactory for
(2), step (6) are gone to if meeting；
(8) by qnewTree list is added, judgement is to reach qgoal, if not then going to step (9)；It is to terminate algorithm；
(9) judge whether that the boundary for reaching rolling window if it is goes to step (10) if not then return step (2)；
(10) from qnewReverse search obtains local path, and with qnewCentered on establish new rolling window, return step (1).
7. a kind of nothing using based on the unmanned plane real-time route planing method for improving RRT described in claim 1~6 any one
It is man-machine.
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