CN108986469A - It is a kind of to turn to the highway emergency event recognition methods that circle tangential method carries out unmanned plane path planning based on minimum safe - Google Patents
It is a kind of to turn to the highway emergency event recognition methods that circle tangential method carries out unmanned plane path planning based on minimum safe Download PDFInfo
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Abstract
The highway emergency event recognition methods that circle tangential method carries out unmanned plane path planning is turned to based on minimum safe this patent discloses a kind of, which comprises step 1: detect the generation of emergency event.Step 2: accident spot is primarily determined.Step 3: the preliminary preparation of unmanned plane path planning.Step 4: path planning is carried out with " minimum safe turns to circle tangential method ".Step 5: unmanned plane is investigated to incident area.The present invention has fast reaction speed, automation, intelligent, high reliability.
Description
Technical field
The present invention relates to field of traffic and air vehicle technique field.Specifically a kind of unmanned plane receive automatically instruction,
Track is generated, the accident point that flies to carries out highway emergency event and quickly knows method for distinguishing.
Background technique
With the sustainable growth of domestic motor vehicles ownership, freeway network mileage and road network occupation rate, highway
Accident rate also rise with it, become hinder freeway network system play efficient transportation effect an important factor for it
One.When emergency event occurs for highway, consequence is often serious, if traffic police personnel cannot reach in-situ processing in time, is easy
Cause more serious casualties.The expressway fog event in Anhui Province, dead and wounded tens people occur as before.Accident occurs
Afterwards, highway congestion is serious, and traffic police personnel can not quickly reach accident and point occurs, the concrete condition at the scene of can not also learning,
Cause scene disorder, freeway traffic is paralysed for a long time.
When emergency event occurs for highway, traditional way is that traffic police portion is notified by alarming after artificial discovery accident
Door, low efficiency is waiting for a long time, and traffic police department is in passive state.Thus when emergency event, accident discovery occur for highway
It is traffic is caused to paralyse comprehensively and the major reason of serious disaster not in time with processing.Traditional accident detection identification technology is
Be unable to satisfy China's freeway network quickly, safety, the demand of intelligent development.
With being widely used for sensor and Internet technology, intelligent transport technology is fast-developing and universal, expedites the emergence of
Traffic system wisdomization is changed, and is provided by force for the identification of express highway intelligent accident point and the quick accident identification of UAV Intelligent
Strong technical support.
The identification of expressway traffic accident point and the Fast Identification of type of fault are one relatively new classes of field of traffic
Topic.Existing method is mainly artificially to convey and instruct to unmanned plane, unmanned plane is in accident after traffic police department is connected to accident alarming information
Point, which occurs, helps traffic police personnel to carry out accident investigation.Existing method artificially participates in excessively, intelligent insufficient, accident investigation analysis
Time-consuming, and the practicability is poor;And unmanned plane is not used well, the practicability mistake that unmanned plane is used as new technical means
It is low.
Traditional path planning algorithm can be divided into " non-evolution algorithm " and " evolution algorithm " two major classes." non-evolution algorithm "
Mainly have: one-sided search method, Artificial Potential Field Method, dijkstra's algorithm;" evolution algorithm " mainly has: genetic algorithm, ant group algorithm,
Particle swarm optimization algorithm.The calculating cost of path planning is usually the function of map size, and map is bigger, the calculating of path planning
Cost becomes larger therewith.Compared with other path plannings, the characteristics of unmanned plane path planning, is presented as that gap hinders that object is sparse, small size barrier
Hinder the characteristics of object distribution is scattered, large volume distribution of obstacles is concentrated.Among unmanned plane path planning, due to map generally compared with
Greatly, and the degree of rarefication of map is higher, so the more calculating time can be wasted using legacy paths planning algorithm, and the road generated
Diameter is unstable, and not can guarantee gained path is shortest path.The path planning of unmanned plane, it should using it is simple and reliable, not by
The path generating method that map size influences.
The present invention proposes to keep unmanned plane independently right using " minimum safe turns to circle tangential method " progress unmanned plane coordinates measurement
Accident on expressway is safely and fast recognized.Detector module carries out the detection and analysis of accident point automatically, and by thing
Therefore information is sent to unmanned plane, unmanned plane is connected to after instruction and automatically generates path by " minimum safe turns to circle tangential method ", preceding
The identification for acting event is clicked through toward accident.This method solve expressway traffic accident test and analyze in personnel are depended on unduly, phase
Than there is better accuracy, rapidity and reliability in conventional method.
Summary of the invention
It is an object of the invention to overcome the identification of current expressway traffic accident point and type of fault to spend time length, personnel
Serious, stability difference problem is relied on, the advantage that unmanned plane flexibility ratio is high, use cost is small is given full play to, proposes that one kind is based on
" minimum safe turns to circle tangential method " carries out the highway emergency event recognition methods of unmanned plane path planning.
The invention firstly uses freeway traffic wave theory and sensor detectings, to the detector number of highway
According to being handled, to analyze highway lane state, the accident spot of emergency event is determined;Then, sharp
Accident information is sent to unmanned plane with wireless communication technique;Finally, " minimum safe turns to circle tangential method " is utilized to generate nobody
Machine optimal flight paths allow unmanned plane quickly to reach incident area and execute task, complete accident point accurate positioning and accident
Classification identification;Quick, the accurate and efficient identification for reaching highway emergency event, provides reliably for accident handling decision
Foundation is executed, to mitigate influence of the highway emergency event to highway normal pass.
For achieving the above object, the specific technical solution of the present invention is as follows:
Step 1: the generation of emergency event is detected.Whether can detecte on highway by the duty situation of detector has
Emergency event occurs.Detector be divided into occupy with vacant two states, when vehicle is square on the detector, detector is to occupy shape
State;Conversely, being blank state.When highway wagon flow is current normal, occupying and vacant the phenomenon that being alternately present occurs in detector.
When accident occurs, it is usually associated with traffic jam.After the accident, it is zero that road flow speeds in accident point upstream, which weaken rapidly,
It blocks, the detector of accident point upstream will become continuing possession state;The detector in accident point downstream will become continuing sky
State is set, until accident is cleaned.It can determine whether burst accident according to the state of detector, when detector is occupied
Time or when by vacant time Δ t > T, identification has traffic accident.
Wherein, T is time threshold, indicates that the wagon flow in non-traffic congestion on highway passes through detector, detector
Appearance occupies and idle alternate maximum time interval;A variety of ginsengs such as T and the region location where date, moment, highway
Number is related, it will be appreciated that the setting of T will be configured according to specific highway, the detection of highway between different provinces and cities
T set by device is not quite similar, and needs to be obtained according to statistical analysis.
Step 2: accident spot is primarily determined.Determine after the accident, the occupied time started t of upstream detector1,
Downstream detector is by t at the beginning of vacant2It is all determined therewith.Volume of traffic q (/h), the average speed v (km/h) of wagon flow
It can be directly calculated by the data that detector calculates.
The determination basis traffic shock wave of accident spot is theoretical.When calculating road normal pass, traffic current density k (/km):
Traffic current density k when congestion in roadjIt can be obtained by statistical analysis.Calculate the opposite position of accident point and detector
It sets:
Wherein: uwFor traffic shock wave velocity of wave;Δt*For traffic wave propagation time;Δ q is the changing value of the volume of traffic;Δ k is traffic
The changing value of current density;q2For the magnitude of traffic flow in downstream at vehicle density interface;q1For the friendship of upstream at vehicle density interface
Through-current capacity k2For the traffic current density in downstream at vehicle density interface;k1Traffic flow for upstream at vehicle density interface is close
Degree.Δ L is distance of the accident point to detector.The longitude and latitude of detector is it is known that after Δ L is calculated, the coordinate of accident point
It obtains therewith.Accident information is sent to the unmanned plane nearest apart from accident point by detector, and unmanned plane is waited to fly to accident click-through
Row investigation.
Step 3: the preliminary preparation of unmanned plane path planning.The calculating cost of path planning is usually map size
The function of Size=lengthwidth, length are the length of map, and width is the width of map.Unmanned plane path planning it
In, since the value of map size Size is generally large, and the degree of rarefication of map is higher, so using legacy paths planning algorithm meeting
The more calculating time is wasted, and the path generated is unstable, not can guarantee gained path is shortest path.According to highway
The sparse environmental quality of locating barrier, set forth herein " minimum safe turn to circle tangential method " of a kind of simple possible to generate road
Diameter, unrelated with the size of map, the flight environment of vehicle applicability sparse for barrier is very strong.It determines and is respectively accorded in this method first
Number meaning: the coordinate x of map X-axis, the coordinate y of Y-axis, the drone flying height H of restriction, unmanned plane maximum flying speed
VMAX, unmanned plane maximum yaw speed (flat turning velocity) ωMAX, unmanned plane cruising speed VC, unmanned plane minimum turning radius R,
Calculate the minimum turning radius of unmanned plane
Assuming that most of section in unmanned plane during flying is all the high-altitude flight in limit flying height H.According to unmanned plane
Restriction flight high speed H, will height higher than H object marker be barrier, path is labeled in the barrier in flight range
On the map of planning, by the map projection of three-dimensional path planning to two-dimensional surface.
Step 4: path planning is carried out with " minimum safe turns to circle tangential method ".
Whether the first step has barrier between starting point and target point.If starting point (xA,yA) and target point (xB,yB) between do not have
There is barrier, ideal shortest path L is determined according to Euclidean distance0LengthThen it is European away from
From for L0As actual optimum path, coordinates measurement.Conversely, carrying out unmanned plane path according to " minimum safe turns to circle tangential method "
Planning.
Second step obtains minimum safe and turns to circle.As starting point (xA,yA) and target point (xB,yB) between when having barrier,
Make the circumscribed circle O, radius R of the nearest barrier contour line of distance A point0, marked on map and furthermore meet round heart O (xO,
yO).In view of the minimum turning radius R of unmanned plane, using O point as the center of circle, radius R1=R0+ R makees to justify again, obtains minimum safe
Turn to circle O1.It crosses starting point A and target point B is round O1Tangent line, obtain point of contact C1, D1And C2, D2。
Third step calculates secure path length and retains optimal path.By second step, available secure path is line
SectionArc segmentCompareWithSize, the small conduct optimal path l of selective valueAC
+lCDRetain.
lCD=θ R1 (5)
Wherein, θ is line segment SCDIn circle O1Middle pair of central angle:
4th step, the path planning of remaining area.Judge that target point B and minimum safe turn to circle O1Between point of contact D it
Between whether have barrier, clear then selects line segment lDBAs unmanned plane path;Conversely, unmanned plane relocates, D point is set
It is set to new starting point A;The first step is carried out to the iteration of third step, path is generated, completes unmanned plane path planning.
Step 5: unmanned plane is investigated to incident area.Unmanned plane is reached along path generated where accident point
Region carries out accident point accurate positioning, data back and accident pattern identification.
The technical advantages of the present invention are that:
The present invention has fast reaction speed, automation, intelligent, high reliability.
(1) passivity of the invention according to existing technologies when finding highway emergency event, Personnel Dependence, propose
Using the road networking accident detection technology of detector, accident point region, accident hair can be being determined rapidly after the accident
The raw time.
(2) present invention changes the previous working method that accident instruction is manually sent to unmanned plane, is changed to accident detection device
Accident instruction is sent from trend unmanned plane.Instruction transmitting step is simplified, the time can be greatly saved;Personnel are not depended on simultaneously, are referred to
The accuracy of transmission is enabled to improve.
(3) present invention proposes a kind of new suitable expressway traffic accident investigation according to the deficiency for having coordinates measurement algorithm
Path generating method used in unmanned plane --- " minimum safe turns to circle tangential method ";This method and existing coordinates measurement are calculated
For method compared to simpler, stability is high, can effectively solve the problems, such as the coordinates measurement of expressway traffic accident investigation unmanned plane, make nobody
Machine is in the most short interior identification for completing traffic accident.
Detailed description of the invention
Fig. 1 is traffic accident detection method schematic diagram of the invention;
Fig. 2 is coordinates measurement schematic diagram of the present invention under simple situation;
Fig. 3 is path planning process schematic diagram of the invention.
In Fig. 1, A: cross section B where detector: cross section C where detector: cross section P where detector: accident
Point uw1: the accident traffic shock wave velocity of wave propagated to accident point upstream
uw2: to the accident traffic shock wave velocity of wave of accident point downstream travel
In Fig. 2,1: unmanned plane 2: barrier 3: minimum safe turns to circle 4: circumscribed circle 5: barrier 6: accident vehicle
7: highway A: starting point B: target point C1、C2: starting point and the minimum point of contact D for turning to circle1、D2: target point and minimum steering
Round point of contact
Specific embodiment
In order to which the purpose of the present invention, technical solution and beneficial effect is more clearly understood, with reference to embodiments, to this
Invention is further elaborated.Below with reference to attached drawing of the invention, to the technical solution of the present invention in the specific implementation into
Clear, the complete description of row.
With unidirectional two lane shown in FIG. 1, no entrance ring road interference, uniformly straight highway is traffic arrival rate
Research object.Assuming that the uniformly distributed a set of detector means of the every 1km of highway, i.e. L in Fig. 1AB=LBC=1km, T=2km;
The time threshold T=10s of detector;35 timesharing at the morning 10, traffic accident occurs for P point in Fig. 1, and cause of accident is unknown;Two
Lane is blocked simultaneously, and vehicular traffic is impassable.
Step 1: the generation of emergency event is detected.Traffic injury time t0=10:35:00, it is assumed that in morning 10:35:
When 22, residence time Δ t=12s > T=10s of the automobile at the A on detector, accident occurs for detector judgement.
Step 2: accident spot is primarily determined.Detector detector calculates t automatically at A in Fig. 11=10:35:
10;Similarly, detector calculates t at B2=10:35:20.Thing before being occurred simultaneously according to the data accident of detector recording
Therefore at point wagon flow volume of traffic q0=2100 (/h), average speed v0=70 (km/h);Traffic flow when calculating normal pass is close
Degree(/km);Therefore the traffic condition before occurring at accident point is (0, k0, 0)=(2100/h, 30/km,
70km/h).Obviously, it is assumed that the average traffic length of this section of highway is 8m (can be measured by detector), considers front and back vehicle
Spacing, then traffic current density when congestion in road can be estimated as kj=100/km;Therefore close to the friendship of the road upstream of accident point
Logical situation becomes (0, kj, 0)=(0,100/km, 0);Traffic condition close to the road downstream of accident point becomes (0,0, v0)
=(0,0,70km/h);Calculate the accident traffic shock wave velocity of wave propagated to accident point upstream that traffic accident causes:It is contrary with wagon flow that value is that negative shows, before have been described above and upstream propagate, uw1It should take
Positive value, therefore uw1=30km/h;Similarly, to the accident traffic shock wave velocity of wave of accident point downstream travel:Calculate the relative position of accident point and detector, Δ L=uw·Δt*.Accident point P in Fig. 1
The distance of cross section A where to upstream detector is L1=uw1×(t1-t0), cross section B where accident point P to downstream detector
Distance be L2=uw2×(t2-t0).Detector networking, the coordinate where detector can directly determine;Thus between detector
Distance L can be directly obtained.It is assumed that detector is uniformly distributed, L=1km.Due to being with vehicle when selecting material time point
The time for passing in and out detector is linear module, and the distance of travelled by vehicle is less than the distance between accident point to downstream detector.
Obviously have: L1+L2≤L.For convenience of calculation, L is taken1+L2=L.Simultaneous Equations primary Calculation accident point position:
Xie Zhi is obtainedUnit conversion is carried out, chronomere becomes the second (s), and length unit becomes
Rice (m), speed unit are meter per second (m/s);Substitute into data,I.e. accident point is in cross
At the 241.7m of section A downstream, the coordinate of accident point obtains therewith.Accident information is sent to nearest apart from accident point by detector
Unmanned plane waits the unmanned plane accident point that flies to be investigated.
Step 3: the preliminary preparation of unmanned plane path planning.After being connected to accident dot position information, unmanned plane carries out task
Map initialization.As shown in Fig. 2, initialization task map includes: that (1) will be above the nothing limited in three-dimensional path planning map
The landform and object of man-machine flying height H is labeled as barrier;(2) map of three-dimensional path planning is completed to the throwing of two-dimensional surface
Shadow;It (3) is A by starting mark, target point, that is, accident point is labeled as B, and starting point A (x is marked on 2D path planning mapA,
yA), target point B (xB,yB) and barrier coordinate;(4) the minimum safe turning radius R of the unmanned plane is calculated,Wherein, ωMAXFor unmanned plane maximum yaw speed (flat turning velocity), VCFor unmanned plane cruising speed.
Step 4: path planning is carried out with " minimum safe turns to circle tangential method ".
1. judging whether there is barrier between starting point and target point.Upper starting point A (x according to the mapA,yA), target point B
(xB,yB) and barrier coordinate, it is to be understood that whether have barrier between A, B.A, clear between B, then according to Euclidean distance
Determine ideal shortest path L0LengthConversely, according to " minimum safe turns to circle tangent line
Method " carries out unmanned plane path planning.Scene as shown in Figure 2 has barrier 5 between A, B, thus needs by the way that " minimum safe turns
To circle tangential method " carry out A, B between path planning.
2. obtaining minimum safe turns to circle.As shown in Fig. 2, according to the contour generating circumscribed circle O of barrier 5, radius is
R0, marked on map and furthermore meet round heart O (xO,yO).In view of the minimum turning radius R of unmanned plane, using O point as the center of circle, half
Diameter R1=R0+ R makees to justify again, obtains minimum safe and turns to circle O1.It crosses starting point A and target point B is round O1Tangent line, obtain point of contact
C1, D1And C2, D2。
3. calculating secure path length and retaining optimal path.By one step above, two secure path: line segment can be obtainedArc segmentThe length for comparing two paths, selects optimal path, comparesWith
Size, the small conduct optimal path l of selective valueAC+lCDRetain.
Solving equations?
Then
In Fig. 3 situation,Therefore by line segmentArc segmentIt is saved as path.
4. the path planning of remaining area.In Fig. 3 situation, point D1There is no barrier between target point B, therefore line segmentFor
Suitable path, by pathIt is saved.
Step 5: unmanned plane is investigated to incident area.Unmanned plane is along path generated: line segmentArc segmentLine segmentFlight reaches accident point region.There is a certain error for the calculated accident point longitude and latitude of step 3,
Accident point accurate positioning is carried out by the GPS module of unmanned plane.Meanwhile unmanned plane is taken photo by plane incident area by the camera carried
Video carries out data back by 4G network, and surface personnel carries out type of fault really according to the video data of passback
Recognize.
Claims (2)
1. a kind of turn to the highway emergency event identification side that circle tangential method carries out unmanned plane path planning based on minimum safe
Method, which is characterized in that the described method includes:
Step 1: detecting the generation of emergency event, by detector duty situation when detector by the holding time or by it is vacant when
Between Δ t > T when, identification have traffic accident;
Step 2: accident spot is primarily determined;Calculate the relative position of accident point and detector:
Wherein: uwFor traffic shock wave velocity of wave;Δt*For traffic wave propagation time;Δ q is the changing value of the volume of traffic;Δ k is that traffic flow is close
The changing value of degree;q2For the magnitude of traffic flow in downstream at vehicle density interface;q1For the traffic flow of upstream at vehicle density interface
Measure k2For the traffic current density in downstream at vehicle density interface;k1For the traffic current density of upstream at vehicle density interface;
Step 3: unmanned plane path planning tentatively prepares;Calculate the minimum turning radius of unmanned plane;And according to the restriction of unmanned plane
Flying height H, the object marker by height higher than H is barrier, is labeled in path planning to the barrier in flight range
On map, by the map projection of three-dimensional path planning to two-dimensional surface;
Step 4: unmanned plane during flying path planning is carried out with " minimum safe turns to circle tangential method ", the step 4 includes: head
First, determine between unmanned plane during flying starting point and target point whether there is barrier;If starting point (xA,yA) and target point (xB,yB) between
There is no barrier, then Euclidean distanceAs actual optimum path, coordinates measurement;If really
Determine have barrier between unmanned plane during flying starting point and target point, turns to circle tangential method according to minimum safe and carry out unmanned plane path rule
It draws;The minimum safe special project circle tangential method includes making the circumscribed circle O of the nearest barrier contour line of distance A point, and radius is
R0, marked on map and furthermore meet round heart O (xO,yO);In view of the minimum turning radius R of unmanned plane, using O point as the center of circle, half
Diameter R1=R0+ R makees to justify again, obtains minimum safe and turns to circle O1, then cross starting point A and target point B and be round O1Tangent line, obtain
Point of contact C1, D1And C2, D2;Obtained secure path is line segmentArc segment CompareWithSize, the small conduct optimal path l of selective valueAC+lCDRetain;Then judge that target point B and minimum safe are turned to justify
O1Between point of contact D between whether have barrier, clear then selects line segment lDBAs unmanned plane path;Conversely, unmanned plane
Again residual paths are planned, set new starting point A for D point;Circle tangential method is turned to according to minimum safe and generates path, is completed
Unmanned plane path planning;
Step 5: unmanned plane flies to incident area according to the path of planning and is investigated;Unmanned plane is arrived along path generated
Up to accident point region, accident point accurate positioning, data back and accident pattern identification are carried out.
2. a kind of turn to the highway emergency event identification side that circle tangential method carries out unmanned plane path planning based on minimum safe
Method, which is characterized in that the coordinate x of map X-axis, the coordinate y of Y-axis, the drone flying height H of restriction, the flight of unmanned plane maximum
Speed VMAX, unmanned plane maximum yaw speed (flat turning velocity) ωMAX, unmanned plane cruising speed VC, unmanned plane minimum turning half
Diameter R calculates the minimum turning radius of unmanned plane are as follows:
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Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110487272A (en) * | 2019-05-21 | 2019-11-22 | 西北大学 | A kind of rotor wing unmanned aerial vehicle economized path optimization method of dog leg path camber line |
CN114578839A (en) * | 2022-03-10 | 2022-06-03 | 思翼科技(深圳)有限公司 | Unmanned aerial vehicle path calculation system and method based on big data |
CN117193382A (en) * | 2023-11-07 | 2023-12-08 | 北京申立通科技服务有限公司 | Unmanned aerial vehicle flight path determining method and system |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101697255A (en) * | 2009-10-22 | 2010-04-21 | 姜廷顺 | Traffic safety system with functions of jam warning and visibility detecting and operation method thereof |
CN102419596A (en) * | 2011-11-20 | 2012-04-18 | 北京航空航天大学 | Vector-field-based small-sized unmanned plane wind-field anti-interference self-adaptive control method |
CN103116360A (en) * | 2013-01-31 | 2013-05-22 | 南京航空航天大学 | Unmanned aerial vehicle obstacle avoidance controlling method |
CN103176476A (en) * | 2013-03-08 | 2013-06-26 | 北京航空航天大学 | Autonomous approach route planning method for gliding unmanned aerial vehicles |
CN103697896A (en) * | 2014-01-13 | 2014-04-02 | 西安电子科技大学 | Unmanned aerial vehicle route planning method |
CN106483974A (en) * | 2015-09-02 | 2017-03-08 | 中国航空工业第六八研究所 | A kind of fixed-wing unmanned plane closely geometry barrier-avoiding method |
CN106813667A (en) * | 2017-02-20 | 2017-06-09 | 北京经纬恒润科技有限公司 | A kind of Route planner and device based on no-fly zone constraint |
CN106845803A (en) * | 2016-12-31 | 2017-06-13 | 广东省特种设备检测研究院 | A kind of special equipment and harmful influence accident emergency method of disposal based on unmanned plane |
-
2018
- 2018-08-08 CN CN201810896732.1A patent/CN108986469B/en not_active Expired - Fee Related
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101697255A (en) * | 2009-10-22 | 2010-04-21 | 姜廷顺 | Traffic safety system with functions of jam warning and visibility detecting and operation method thereof |
CN102419596A (en) * | 2011-11-20 | 2012-04-18 | 北京航空航天大学 | Vector-field-based small-sized unmanned plane wind-field anti-interference self-adaptive control method |
CN103116360A (en) * | 2013-01-31 | 2013-05-22 | 南京航空航天大学 | Unmanned aerial vehicle obstacle avoidance controlling method |
CN103176476A (en) * | 2013-03-08 | 2013-06-26 | 北京航空航天大学 | Autonomous approach route planning method for gliding unmanned aerial vehicles |
CN103697896A (en) * | 2014-01-13 | 2014-04-02 | 西安电子科技大学 | Unmanned aerial vehicle route planning method |
CN106483974A (en) * | 2015-09-02 | 2017-03-08 | 中国航空工业第六八研究所 | A kind of fixed-wing unmanned plane closely geometry barrier-avoiding method |
CN106845803A (en) * | 2016-12-31 | 2017-06-13 | 广东省特种设备检测研究院 | A kind of special equipment and harmful influence accident emergency method of disposal based on unmanned plane |
CN106813667A (en) * | 2017-02-20 | 2017-06-09 | 北京经纬恒润科技有限公司 | A kind of Route planner and device based on no-fly zone constraint |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110487272A (en) * | 2019-05-21 | 2019-11-22 | 西北大学 | A kind of rotor wing unmanned aerial vehicle economized path optimization method of dog leg path camber line |
CN114578839A (en) * | 2022-03-10 | 2022-06-03 | 思翼科技(深圳)有限公司 | Unmanned aerial vehicle path calculation system and method based on big data |
CN114578839B (en) * | 2022-03-10 | 2022-11-29 | 思翼科技(深圳)有限公司 | Unmanned aerial vehicle path calculation system and method based on big data |
CN117193382A (en) * | 2023-11-07 | 2023-12-08 | 北京申立通科技服务有限公司 | Unmanned aerial vehicle flight path determining method and system |
CN117193382B (en) * | 2023-11-07 | 2024-05-03 | 北京同兴世纪科技有限公司 | Unmanned aerial vehicle flight path determining method and system |
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