CN103697896A - Unmanned aerial vehicle route planning method - Google Patents
Unmanned aerial vehicle route planning method Download PDFInfo
- Publication number
- CN103697896A CN103697896A CN201410012975.6A CN201410012975A CN103697896A CN 103697896 A CN103697896 A CN 103697896A CN 201410012975 A CN201410012975 A CN 201410012975A CN 103697896 A CN103697896 A CN 103697896A
- Authority
- CN
- China
- Prior art keywords
- node
- line
- barrier
- path
- height
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- 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 discloses an unmanned aerial vehicle route planning method. The method comprises the following steps: firstly, initializing a task map, marking a Start (xstart, ystart), a Goal (xgoal, ygoal) and the coordinate of a barrier, and calculating the minimum safety turning radius R of and unmanned aerial vehicle; secondly, setting the Start as a Node [0] and the Goal as a Node [-1], finding the coordinates of other nodes, and establishing a binary tree by using a structural body; and thirdly, reading the binary tree by using a depth-first lvalue traversing method, sequentially recording the sequences of the nodes, and storing connecting lines between every two adjacent nodes and a route into a matrix Path[], wherein the route is generated by using a Dijkstra algorithm. Compared with the prior art, the invention provides a concrete node calibration method; the diversity of the route is increased through drawing a vertical line on any position on a connecting line between two points; and a non-evolutional calculating method is adopted, so that the calculating time is shortened, the storage space is reduced, and the stability of the algorithm is improved.
Description
Technical field
The invention belongs to unmanned plane technical field, relate in particular to a kind of unmanned plane paths planning method.
Background technology
Along with the development of informationization technology, unmanned plane (UAV) is applied obtaining in military field and civil area more gradually.One of gordian technique in unmanned plane application is path planning.The object of path planning (Path Planning) is between given area, finds out a connection source and terminal, the path of Least-cost.
Path planning is a NP-Complete problem, so far, does not have yet fixing optimal algorithm.The path planning algorithm of main flow has: Dijkstra, A*, evolution algorithm (Genetic Algorithm), Artificial Potential Field Method (Artificial Potential Field) etc.But the computation complexity of these algorithms is higher, its calculated amount is along with the increase of map is index rising.
In calendar year 2001, Cem Hocaoglu and Arthur C.Sanderson have proposed a kind of computation complexity and the big or small irrelevant path planning HOCAOGLU algorithm of map in < < Planning Multiple Paths with Evolutionary Speciation > >, HOCAOGLU algorithm computation complexity is only relevant to the barrier quantity of map, map is more complicated, the node that path needs is just more, the search volume of HOCAOGLU algorithm is just larger, thereby cause the lifting of algorithm calculation cost, if and for a kind of extreme case---the map of clear, the computation complexity of HOCAOGLU algorithm is constant, HOCAOGLU algorithm has been avoided the excessive problem of most of path planning algorithms operand on big map.
Although, still there is intrinsic defect in the above-mentioned multiple advantage of HOCAOGLU algorithm.HOCAOGLU algorithm does not provide the concrete grammar of establishing node, but adopts evolution algorithm to search for; Meanwhile, HOCAOGLU algorithm, in order to reduce the search volume of evolution algorithm, is only made vertical line on the mid point of 2 lines, and this has reduced the diversity in path, often can cause algorithm search less than feasible path.
Summary of the invention
The object of this invention is to provide a kind of unmanned plane paths planning method, while utilizing HOCAOGLU algorithm calculating path to solve in prior art, cannot specifically the determining node and reduce Path diversity and then often cannot search out the problem of feasible path of existence.
For realizing object of the present invention, the invention provides a kind of unmanned plane paths planning method, described method comprises the steps:
The first step, initialization task map, mark starting point Start (x
start, y
start), terminal Goal (x
goal, y
goal) and the coordinate of barrier, calculate the minimum safe turning radius R of described unmanned plane;
Second step, setting starting point is node Node[0] and terminal be node Node[-1], search other node coordinate, with structure, set up binary tree, described structure comprises variable: node is at the position double Position, the node coordinate int X that belong to originally on line, Y, obstacle height double Height, left child node node*Child_Left,
Right child node node*Child_Right, left father node node*Father_Left, right father node node*Father_Right,
Wherein said other node coordinate of searching, comprises the steps:
(1) for any Node[i], i=-1,0,1 ... i, makes itself and Node[i-1] between carry out line, described line belongs to line originally described in being;
(2) judge described Node[i] and described Node[i-1] between line distance,
If be less than 6R and line, by described barrier, blocked, can be judged to be and enter dead angle, return to last layer and again choose Node[i] node;
If be greater than 6R and line is blocked by barrier, K (x sets up an office
k, y
k) upper at line (Node[i-1], Node[i]), make K (x
k, y
k) from Node[i-1] along this line stepping, move to Node[i], form array K[Len]; For K[Len] upper each some K[i in barrier region], to line both sides, make vertical line H[i], record it apart from the distance at barrier edge, if this barrier is extended to map M[Width] [Height] edge this side all refuse record;
(3) at array H[i] both sides among select respectively K[i] to a value of the distance absolute value maximum at barrier edge, be designated as respectively H
mAX1and H
mAX2, the point of its correspondence is designated as K (x
mAX1, y
mAX1) and K (x
mAX2, y
mAX2); At a K (x
mAX1, y
mAX1) and K (x
mAX2, y
mAX2) on all make height H eight=H
mAXvertical line, choose K (x
mAX1, y
mAX1) and K (x
mAX2, y
mAX2) the shortest one of 2 vertical lines is Node[i+1]; Judge Node[i+1] to Node[i] and Node[i-1] between line whether have barrier, if have, Node[i+1] replace with another one point, continue to judge Node[i+1] to Node[i] and Node[i-1] between line whether have barrier, if have, make Height with
for unit stepping (if 1 of less than take 1 as unit stepping), continue to judge Node[i+1] to Node[i] and Node[i-1] between line whether have barrier, until:
(3-A): if Node[i+1] to Node[i] and Node[i-1] between the equal clear of line block; By Height, K (x
mAX, y
mAX) count Node[i+1]; Return to upper level;
If (3-B) Height progressively increases and makes K (x
mAX, y
mAX) barriers to entry object area, select another one point repeating step (3), if still fail, find and Node[i] and Node[i-1] between the some Node[i+1 that stops of clear], carry out step (3-C);
If (3-C) both sides are all without can being directly communicated with Node[i] and Node[i-1] point, search for a some Node[i] make it to meet itself and Node[i] and Node[i-1] line in, the barrier region summation of passing through is minimum.And make multiplicity add one: Count=Count+1;
If multiplicity Count meets: Count >=Level_Max-Level+1, (Level is the binary tree number of plies at this node place, Level_Max is the maximum number of plies of binary tree when front construction), force to use dijkstra's algorithm, take Node[i] be starting point, Node[i-1] carry out path planning for terminal;
If generated feasible path, record path track, and carry out step (4).
If fail, generate feasible path, judge and entered dead angle.Return to step (1) and again choose Node[i] node.
(4) check node Node[i] and left side father node Node[i-2] between line on have clear.Method is with the step that checks left side.
(5) repeat above-mentioned steps, complete binary tree foundation;
The 3rd step, reads binary tree with depth-first lvalue traversal method, record successively node sequence, deposits the line between adjacent node and the path that adopted dijkstra's algorithm to generate in matrix Path[] among.
Preferably, carry out path smooth processing, upgrade described path matrix, described step of carrying out path smooth processing specifically comprises: for each node Node[i], the A that sets up an office, B, A, B point is from Node[i], along path respectively to two side shiftings, on A, B point, respectively inside angular direction work height is the vertical line of R, when the vertical line end of the two intersects, stops, and note intersection point is O, take O as the center of circle, R is that radius is justified, and gets arc AB and replaces A-Node[i]-B broken line, and upgrade Path[].
Preferably, described barrier comprises enemy radar security area and highly protruding over the landform of unmanned plane during flying height.On map, enemy radar security area and the landform projection that highly surpasses UAV flying height are labeled as to barrier.
The present invention, compared with prior art, has proposed the concrete scaling method of a kind of node, by optional position on 2 lines, makes vertical line, has increased the diversity in path; Adopt the computing method of non-evolution, saved computing time and storage space, increased the stability of algorithm.
Accompanying drawing explanation
Fig. 1 is method flow diagram of the present invention;
Fig. 2 is the method flow diagram that the present invention searches other node;
Fig. 3 is that the present invention judges K[i] to barrier edge value schematic diagram;
Fig. 4 is that the present invention chooses Node[i+1] schematic diagram of node;
Fig. 5 is that the present invention chooses Node[i] schematic diagram of node;
Fig. 6 is the path example schematic diagram that the present invention plans;
Fig. 7 is smooth paths schematic diagram of the present invention;
Fig. 8 is specific embodiment of the invention schematic diagram;
Embodiment
In order to make object of the present invention, technical scheme and beneficial effect clearer, below in conjunction with embodiment, the present invention is further elaborated.Should be understood to specific embodiment described herein only in order to explain the present invention, be not limited to protection scope of the present invention.
As shown in Figure 1, the invention provides a kind of unmanned plane paths planning method, described method comprises the steps:
Step S101, initialization task map, mark starting point Start (x
start, y
start), terminal Goal
(xgoal, y
goal) and the coordinate of barrier, calculate the minimum safe turning radius R of described unmanned plane;
Initialization map, is divided into grid by the mission area of this flight of UAV, and according to dividing mode, calculates the minimum safe turning radius of UAV.According to mission requirements and concrete condition, on map, enemy radar security area and the landform projection that highly surpasses UAV flying height are labeled as to barrier.
Step S102, setting starting point is node Node[0] and terminal be node Node[-1], search other node coordinate, with structure, set up binary tree, described structure comprises variable: node is at the position double Position, the node coordinate int X that belong to originally on line, Y, obstacle height double Height, left child node node*Child_Left, right child node node*Child_Right, left father node node*Father_Left, right father node node*Father_Right are as follows in detail, and with structure, Node sets up binary tree.
Wherein said other node coordinate of searching, comprises the steps, as shown in Figure 2:
Step S201, starts;
Step S202, Node[i] and Node[i-1] between line on whether have barrier if so, to jump to step S203; If not, jump to step S208;
(1) for any Node[i], i=-1,0,1 ... i, makes itself and Node[i-1] between carry out line, described line belongs to line originally described in being;
(2) judge described Node[i] and described Node[i-1] between line distance,
If be less than 6R and line, by described barrier, blocked, can be judged to be and enter dead angle, return to last layer and again choose Node[i] node;
Step S203, at Node[i] and Node[i-1] between line on find the highest point of perpendicular line and intersection, barrier edge;
If be greater than 6R and line is blocked by barrier, K (x sets up an office
k, y
k) upper at line (Node[i-1], Node[i]), make K (x
k, y
k) from Node[i-1] along this line stepping, move to Node[i], form array K[Len]; For K[Len] upper each some K[i in barrier region], to line both sides, make vertical line H[i], record it apart from the distance at barrier edge, if this barrier is extended to map M[Width] [Height] edge this side all refuse record; As shown in Figure 3, K[i] some upside numerical value be effective.
(3) at array H[i] both sides among select respectively K[i] to a value of the distance absolute value maximum at barrier edge, be designated as respectively H
mAX1and H
mAX2, the point of its correspondence is designated as K (x
mAX1, y
mAX1) and K (x
mAX2, y
mAX2); At a K (x
mAX1, y
mAX1) and K (x
mAX2, y
mAX2) on all make height H eight=H
mAXvertical line, choose K (x
mAX1, y
mAX1) and K (x
mAX2, y
mAX2) the shortest one of 2 vertical lines is Node[i+1]; As shown in Figure 4.
Step S204, take k as Node[i+1], increase gradually vertical line height until intersect with barrier;
Whether step S205, there is Node[i+1] make itself and Node[i] and Node[i-1] between line on do not have barrier if not, jump to step S206; If so, jump to step S208;
Judge Node[i+1] to Node[i] and Node[i-1] between line whether have barrier, if have, Node[i+1] replace with another one point, continue to judge Node[i+1] to Node[i] and Node[i-1] between line whether have barrier, if have, make Height with
for unit stepping (if 1 of less than take 1 as unit stepping), continue to judge Node[i+1] to Node[i] and Node[i-1] between line whether have barrier, until:
Step S206, i=i-1, returns to last layer and reorientates; Jump to step S203;
(3-A): if Node[i+1] to Node[i] and Node[i-1] between the equal clear of line block; By Height, K (x
mAX, y
mAX) count Node[i+1]; Return to upper level;
If (3-B) Height progressively increases and makes K (x
mAX, y
mAX) barriers to entry object area, select another one point repeating step (3), if still fail, find and Node[i] and Node[i-1] between the some Node[i+1 that stops of clear], carry out step (3-C);
If (3-C) both sides are all without can being directly communicated with Node[i] and Node[i-1] point, search for a some Node[i] make it to meet itself and Node[i] and Node[i-1] line in, the barrier region summation of passing through is minimum.And make multiplicity add one: Count=Count+1; As shown in Figure 5,
If multiplicity Count meets: Count >=Level_Max-Level+1, (Level is the binary tree number of plies at this node place, Level_Max is the maximum number of plies of binary tree when front construction), force to use dijkstra's algorithm, take Node[i] be starting point, Node[i-1] carry out path planning for terminal;
Step S207, i=i+1, processes next node; Jump to step S202;
Step S208, Node[i+1] whether be that if so, terminal jumps to step S209; Jump to if not step S207;
Step S209, finishes.
If generated feasible path, record path track, and carry out step (4).
If fail, generate feasible path, judge and entered dead angle.Return to step (1) and again choose Node[i] node.
(4) check node Node[i] and left side father node Node[i-2] between line on have clear.Method is with the step that checks left side.
(5) repeat above-mentioned steps, complete binary tree foundation;
Step S103, reads binary tree with depth-first lvalue traversal method, record successively node sequence, deposits the line between adjacent node and the path that adopted dijkstra's algorithm to generate in matrix Path[] among.As shown in Figure 6.
The present invention determines to carry out path smooth processing according to particular problem, if desired processes, for each node Node[i], the A that sets up an office, B.A, B point is from Node[i], along path, respectively to two side shiftings, on A, B point, respectively inside angular direction work height is the vertical line of R, when the vertical line end of the two intersects, stops, note intersection point is O.Take O as the center of circle, and R is that radius is justified, and gets arc AB and replaces A-Node[i]-B broken line, as shown in Figure 7, and upgrade Path[], final, matrix Path[] be path.
As shown in Figure 8, be specific embodiments of the invention.
Test map: size 1000 * 1000, map center has the barrier of a radius 100, separately in random coordinates, generates the circular barrier of 5 radius 30-130, and total barrier area takes up an area 18.84% of figure.
Unmanned plane radius of turn is made as 10.
This algorithm has carried out 100 tests on this map, is about 1.41 seconds average calculating operation time, and traditional dijkstra's algorithm needs 10.61 seconds consuming time.
The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.
Claims (3)
1. a unmanned plane paths planning method, is characterized in that, described method comprises the steps:
The first step, initialization task map, mark starting point Start (x
start, y
start), terminal Goal (x
goal, y
goal) and the coordinate of barrier, calculate the minimum safe turning radius R of described unmanned plane;
Second step, setting starting point is node Node[0] and terminal be node Node[-1], search other node coordinate, with structure, set up binary tree, described structure comprises variable: node is at the position double Position, the node coordinate int X that belong to originally on line, Y, obstacle height double Height, left child node node*Child_Left, right child node node*Child_Right, left father node node*Father_Left, right father node node*Father_Right
Wherein said other node coordinate of searching, comprises the steps:
(1) for any Node[i], i=-1,0,1 ... i, makes itself and Node[i-1] between carry out line, described line belongs to line originally described in being;
(2) judge described Node[i] and described Node[i-1] between line distance,
If be less than 6R and line, by described barrier, blocked, can be judged to be and enter dead angle, return to last layer and again choose Node[i] node;
If be greater than 6R and line is blocked by barrier, K (x sets up an office
k, y
k) upper at line (Node[i-1], Node[i]), make K (x
k, y
k) from Node[i-1] along this line stepping, move to Node[i], form array K[Len]; For K[Len] upper each some K[i in barrier region], to line both sides, make vertical line H[i], record it apart from the distance at barrier edge, if this barrier is extended to map M[Width] [Height] edge this side all refuse record;
(3) at array H[i] both sides among select respectively K[i] to a value of the distance absolute value maximum at barrier edge, be designated as respectively H
mAX1and H
mAX2, the point of its correspondence is designated as K (x
mAX1,y
mAX1) and K (x
mAX2, y
mAX2); At a K (x
mAX1, y
mAX1) and K (x
mAX2, y
mAX2) on all make height H eight=H
mAXvertical line, choose K (x
mAX1, y
mAX1) and K (x
mAX2, y
mAX2) the shortest one of 2 vertical lines is Node[i+1]; Judge Node[i+1] to Node[i] and Node[i-1] between line whether have barrier, if have, Node[i+1] replace with another one point, continue to judge Node[i+1] to Node[i] and Node[i-1] between line whether have barrier, if have, make Height with
for unit stepping (if 1 of less than take 1 as unit stepping), continue to judge Node[i+1] to Node[i] and Node[i-1] between line whether have barrier, until:
(3-A): if Node[i+1] to Node[i] and Node[i-1] between the equal clear of line block; By Height, K (x
mAX, y
mAX) count Node[i+1]; Return to upper level;
If (3-B) Height progressively increases and makes K (x
mAX, y
mAX) barriers to entry object area, select another one point repeating step (3), if still fail, find and Node[i] and Node[i-1] between the some Node[i+1 that stops of clear], carry out step (3-C);
If (3-C) both sides are all without can being directly communicated with Node[i] and Node[i-1] point, search for a some Node[i] make it to meet itself and Node[i] and Node[i-1] line in, the barrier region summation of passing through is minimum.And make multiplicity add one: Count=Count+1;
If multiplicity Count meets: Count >=Level_Max-Level+1, (Level is the binary tree number of plies at this node place, Level_Max is the maximum number of plies of binary tree when front construction), force to use dijkstra's algorithm, take Node[i] be starting point, Node[i-1] carry out path planning for terminal;
If generated feasible path, record path track, and carry out step (4).
If fail, generate feasible path, judge and entered dead angle.Return to step (1) and again choose Node[i] node.
(4) check node Node[i] and left side father node Node[i-2] between line on have clear.Method is with the step that checks left side.
(5) repeat above-mentioned steps, complete binary tree foundation;
The 3rd step, reads binary tree with depth-first lvalue traversal method, record successively node sequence, deposits the line between adjacent node and the path that adopted dijkstra's algorithm to generate in matrix Path[] among.
2. unmanned plane paths planning method according to claim 1, it is characterized in that, carry out path smooth processing, upgrade described path matrix, described step of carrying out path smooth processing specifically comprises: for each node Node[i], A, B set up an office, A, B point is from Node[i], along path, respectively to two side shiftings, on A, B point, respectively inside angular direction work height is the vertical line of R, when intersecting, the vertical line end of the two stops, note intersection point is O, take O as the center of circle, and R is that radius is justified, get arc AB and replace A-Node[i]-B broken line, and upgrade Path[].
3. unmanned plane paths planning method according to claim 1 and 2, is characterized in that, described barrier comprises enemy radar security area and highly surpasses the landform projection of unmanned plane during flying height.On map, enemy radar security area and the landform projection that highly surpasses UAV flying height are labeled as to barrier.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410012975.6A CN103697896A (en) | 2014-01-13 | 2014-01-13 | Unmanned aerial vehicle route planning method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410012975.6A CN103697896A (en) | 2014-01-13 | 2014-01-13 | Unmanned aerial vehicle route planning method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN103697896A true CN103697896A (en) | 2014-04-02 |
Family
ID=50359508
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410012975.6A Pending CN103697896A (en) | 2014-01-13 | 2014-01-13 | Unmanned aerial vehicle route planning method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103697896A (en) |
Cited By (31)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104406593A (en) * | 2014-12-03 | 2015-03-11 | 广西民族大学 | Method for determining optimal route of airway of unmanned aerial vehicle |
| CN104596516A (en) * | 2014-11-24 | 2015-05-06 | 中国海洋大学 | Unmanned aerial vehicle coverage flight path planning based on dynamic newly-added adjacent area |
| CN105241466A (en) * | 2015-11-02 | 2016-01-13 | 中山大学 | Three-dimensional navigation method and device for aircraft |
| CN105487554A (en) * | 2016-01-12 | 2016-04-13 | 武汉顶翔智控科技有限公司 | Multi-rotor unmanned aerial vehicle automatic homeward flight path planning algorithm |
| CN106525047A (en) * | 2016-10-28 | 2017-03-22 | 重庆交通大学 | Unmanned aerial vehicle path planning method based on floyd algorithm |
| CN106843243A (en) * | 2016-03-22 | 2017-06-13 | 北京京东尚科信息技术有限公司 | The management method of UAS and unmanned plane route |
| CN107092265A (en) * | 2017-06-22 | 2017-08-25 | 义乌文烁光电科技有限公司 | A kind of sorting trolley path planning method suitable for matrix form warehouse |
| CN107168344A (en) * | 2017-05-17 | 2017-09-15 | 哈尔滨工程大学 | A kind of UUV approaches air route generation method during seabed operation |
| CN107270910A (en) * | 2017-06-13 | 2017-10-20 | 南宁市勘察测绘地理信息院 | Single-lens oblique photograph boat flies line design method, system and method for imaging of taking photo by plane |
| CN107479558A (en) * | 2017-09-22 | 2017-12-15 | 中国人民解放军63983部队 | Vehicle field paths planning method based on vehicle movement model |
| CN107924188A (en) * | 2016-07-04 | 2018-04-17 | 深圳市大疆创新科技有限公司 | Flight path planning, control method and the system of a kind of unmanned plane |
| CN108225333A (en) * | 2018-01-12 | 2018-06-29 | 中国电子科技集团公司第二十八研究所 | A kind of optimal path generation method for flight course planning |
| CN108638071A (en) * | 2018-05-22 | 2018-10-12 | 四川超影科技有限公司 | A kind of crusing robot optimal path dynamic programming method |
| CN108803660A (en) * | 2018-06-22 | 2018-11-13 | 苏州得尔达国际物流有限公司 | Shipping unmanned aerial vehicle group paths planning method |
| CN108958293A (en) * | 2018-09-07 | 2018-12-07 | 济南大学 | A kind of unmanned plane paths planning method |
| CN108986469A (en) * | 2018-07-04 | 2018-12-11 | 北京航空航天大学 | 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 |
| CN109839953A (en) * | 2019-02-19 | 2019-06-04 | 上海交通大学 | The trajectory planning and speed planning method for transferring smooth based on Bezier |
| WO2019127019A1 (en) * | 2017-12-26 | 2019-07-04 | 深圳市道通智能航空技术有限公司 | Path planning method and device for unmanned aerial vehicle, and flight management method and device |
| CN110118558A (en) * | 2019-04-25 | 2019-08-13 | 芜湖智久机器人有限公司 | A kind of envelope construction method, device and the memory of AGV fork truck |
| CN110162095A (en) * | 2019-06-19 | 2019-08-23 | 西北工业大学 | A kind of unmanned plane under threatening environment quickly makes a return voyage method |
| CN110207708A (en) * | 2019-06-25 | 2019-09-06 | 重庆邮电大学 | A kind of unmanned aerial vehicle flight path device for planning and method |
| CN110319836A (en) * | 2019-04-09 | 2019-10-11 | 华东理工大学 | A kind of path planning control method and device with the minimum target of energy loss |
| CN110579214A (en) * | 2019-10-16 | 2019-12-17 | 中国人民解放军国防科技大学 | unmanned aerial vehicle path planning method and device |
| CN111123903A (en) * | 2018-10-30 | 2020-05-08 | 武汉理工大学 | Unmanned ship obstacle avoidance method based on circular track unit |
| CN111426302A (en) * | 2020-04-14 | 2020-07-17 | 西安航空职业技术学院 | Unmanned aerial vehicle high accuracy oblique photography measurement system |
| CN111595340A (en) * | 2020-04-20 | 2020-08-28 | 广东博智林机器人有限公司 | Path determining method and device and electronic equipment |
| 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 |
| CN112525198A (en) * | 2020-11-23 | 2021-03-19 | 广州极飞科技有限公司 | Operation route planning method and related device |
| CN113093787A (en) * | 2021-03-15 | 2021-07-09 | 西北工业大学 | Unmanned aerial vehicle trajectory planning method based on velocity field |
| CN113359865A (en) * | 2021-08-03 | 2021-09-07 | 深圳奥雅设计股份有限公司 | Unmanned aerial vehicle flight path generation method and system |
| CN113704370A (en) * | 2021-07-12 | 2021-11-26 | 南昌大学 | Path planning algorithm based on multi-mode multi-objective optimization algorithm |
-
2014
- 2014-01-13 CN CN201410012975.6A patent/CN103697896A/en active Pending
Cited By (45)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104596516A (en) * | 2014-11-24 | 2015-05-06 | 中国海洋大学 | Unmanned aerial vehicle coverage flight path planning based on dynamic newly-added adjacent area |
| CN104406593A (en) * | 2014-12-03 | 2015-03-11 | 广西民族大学 | Method for determining optimal route of airway of unmanned aerial vehicle |
| CN105241466A (en) * | 2015-11-02 | 2016-01-13 | 中山大学 | Three-dimensional navigation method and device for aircraft |
| CN105487554B (en) * | 2016-01-12 | 2018-01-23 | 武汉顶翔智控科技有限公司 | A kind of multi-rotor unmanned aerial vehicle is maked a return voyage path planning algorithm automatically |
| CN105487554A (en) * | 2016-01-12 | 2016-04-13 | 武汉顶翔智控科技有限公司 | Multi-rotor unmanned aerial vehicle automatic homeward flight path planning algorithm |
| CN106843243A (en) * | 2016-03-22 | 2017-06-13 | 北京京东尚科信息技术有限公司 | The management method of UAS and unmanned plane route |
| US11016488B2 (en) | 2016-07-04 | 2021-05-25 | SZ DJI Technology Co., Ltd. | Aerial operation support and real-time management |
| US11703865B2 (en) | 2016-07-04 | 2023-07-18 | SZ DJI Technology Co., Ltd. | Aerial operation support and real-time management |
| CN107924188A (en) * | 2016-07-04 | 2018-04-17 | 深圳市大疆创新科技有限公司 | Flight path planning, control method and the system of a kind of unmanned plane |
| CN106525047B (en) * | 2016-10-28 | 2019-07-02 | 重庆交通大学 | A kind of unmanned plane paths planning method based on floyd algorithm |
| CN106525047A (en) * | 2016-10-28 | 2017-03-22 | 重庆交通大学 | Unmanned aerial vehicle path planning method based on floyd algorithm |
| CN107168344B (en) * | 2017-05-17 | 2020-01-17 | 哈尔滨工程大学 | Method for generating air route in process of UUV (unmanned Underwater vehicle) approaching seabed operation |
| CN107168344A (en) * | 2017-05-17 | 2017-09-15 | 哈尔滨工程大学 | A kind of UUV approaches air route generation method during seabed operation |
| CN107270910A (en) * | 2017-06-13 | 2017-10-20 | 南宁市勘察测绘地理信息院 | Single-lens oblique photograph boat flies line design method, system and method for imaging of taking photo by plane |
| CN107092265A (en) * | 2017-06-22 | 2017-08-25 | 义乌文烁光电科技有限公司 | A kind of sorting trolley path planning method suitable for matrix form warehouse |
| CN107479558A (en) * | 2017-09-22 | 2017-12-15 | 中国人民解放军63983部队 | Vehicle field paths planning method based on vehicle movement model |
| WO2019127019A1 (en) * | 2017-12-26 | 2019-07-04 | 深圳市道通智能航空技术有限公司 | Path planning method and device for unmanned aerial vehicle, and flight management method and device |
| CN108225333A (en) * | 2018-01-12 | 2018-06-29 | 中国电子科技集团公司第二十八研究所 | A kind of optimal path generation method for flight course planning |
| CN108225333B (en) * | 2018-01-12 | 2020-03-24 | 中国电子科技集团公司第二十八研究所 | Optimal path generation method for air route planning |
| CN108638071A (en) * | 2018-05-22 | 2018-10-12 | 四川超影科技有限公司 | A kind of crusing robot optimal path dynamic programming method |
| CN108803660B (en) * | 2018-06-22 | 2021-06-18 | 苏州得尔达国际物流有限公司 | Freight transport unmanned aerial vehicle group path planning method |
| CN108803660A (en) * | 2018-06-22 | 2018-11-13 | 苏州得尔达国际物流有限公司 | Shipping unmanned aerial vehicle group paths planning method |
| CN108986469A (en) * | 2018-07-04 | 2018-12-11 | 北京航空航天大学 | 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 |
| CN108958293B (en) * | 2018-09-07 | 2021-08-06 | 济南大学 | Unmanned aerial vehicle path planning method |
| CN108958293A (en) * | 2018-09-07 | 2018-12-07 | 济南大学 | A kind of unmanned plane paths planning method |
| CN111123903A (en) * | 2018-10-30 | 2020-05-08 | 武汉理工大学 | Unmanned ship obstacle avoidance method based on circular track unit |
| CN109839953A (en) * | 2019-02-19 | 2019-06-04 | 上海交通大学 | The trajectory planning and speed planning method for transferring smooth based on Bezier |
| 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 |
| CN110319836B (en) * | 2019-04-09 | 2021-02-09 | 华东理工大学 | Path planning control method and device with lowest energy loss as target |
| CN110319836A (en) * | 2019-04-09 | 2019-10-11 | 华东理工大学 | A kind of path planning control method and device with the minimum target of energy loss |
| CN110118558A (en) * | 2019-04-25 | 2019-08-13 | 芜湖智久机器人有限公司 | A kind of envelope construction method, device and the memory of AGV fork truck |
| CN110162095A (en) * | 2019-06-19 | 2019-08-23 | 西北工业大学 | A kind of unmanned plane under threatening environment quickly makes a return voyage method |
| CN110162095B (en) * | 2019-06-19 | 2022-05-27 | 西北工业大学 | Rapid return method of unmanned aerial vehicle in threat environment |
| CN110207708A (en) * | 2019-06-25 | 2019-09-06 | 重庆邮电大学 | A kind of unmanned aerial vehicle flight path device for planning and method |
| CN110579214A (en) * | 2019-10-16 | 2019-12-17 | 中国人民解放军国防科技大学 | unmanned aerial vehicle path planning method and device |
| CN110579214B (en) * | 2019-10-16 | 2022-06-14 | 中国人民解放军国防科技大学 | Unmanned aerial vehicle path planning method and device |
| CN111426302B (en) * | 2020-04-14 | 2022-03-25 | 西安航空职业技术学院 | Unmanned aerial vehicle high accuracy oblique photography measurement system |
| CN111426302A (en) * | 2020-04-14 | 2020-07-17 | 西安航空职业技术学院 | Unmanned aerial vehicle high accuracy oblique photography measurement system |
| CN111595340A (en) * | 2020-04-20 | 2020-08-28 | 广东博智林机器人有限公司 | Path determining method and device and electronic equipment |
| CN111595340B (en) * | 2020-04-20 | 2023-03-21 | 广东博智林机器人有限公司 | Path determining method and device and electronic equipment |
| CN112525198A (en) * | 2020-11-23 | 2021-03-19 | 广州极飞科技有限公司 | Operation route planning method and related device |
| CN113093787A (en) * | 2021-03-15 | 2021-07-09 | 西北工业大学 | Unmanned aerial vehicle trajectory planning method based on velocity field |
| CN113704370A (en) * | 2021-07-12 | 2021-11-26 | 南昌大学 | Path planning algorithm based on multi-mode multi-objective optimization algorithm |
| CN113359865A (en) * | 2021-08-03 | 2021-09-07 | 深圳奥雅设计股份有限公司 | Unmanned aerial vehicle flight path generation method and system |
| CN113359865B (en) * | 2021-08-03 | 2021-11-16 | 深圳奥雅设计股份有限公司 | Unmanned aerial vehicle flight path generation method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103697896A (en) | Unmanned aerial vehicle route planning method | |
| CN102435200B (en) | Rapid path planning method | |
| Stucky | On applying viewshed analysis for determining least-cost paths on digital elevation models | |
| CN109186617B (en) | Method and system for automatically generating lane-level topological relation based on visual crowdsourcing data and memory | |
| CN106525047B (en) | A kind of unmanned plane paths planning method based on floyd algorithm | |
| CN103528585B (en) | A kind of paths planning method of equidistantly not cutting apart the region of can passing through | |
| JP6919949B2 (en) | How to rapidly plan the wake of smart aircraft under multiple constraints | |
| CN102147260B (en) | Electronic map matching method and device | |
| CN107389079B (en) | High-precision path planning method and system | |
| CN103336526B (en) | Based on the robot path planning method of coevolution population rolling optimization | |
| CN101944095A (en) | Path planning method and system | |
| CN107228673A (en) | Route planner and device | |
| CN101122468A (en) | Interest point information storing method and navigation method using interest point information | |
| CN111121785B (en) | Road-free path planning method based on graph search | |
| CN103697895A (en) | Method for determining optimal path of flight vehicle based on self-adaptive A star algorithm | |
| CN108334080A (en) | A kind of virtual wall automatic generation method for robot navigation | |
| CN109357678A (en) | A kind of multiple no-manned plane paths planning method based on heterogeneousization dove colony optimization algorithm | |
| CN114440916B (en) | Navigation method, device, equipment and storage medium | |
| CN103940420A (en) | Method for designing equal-voyage great circle route | |
| CN103559213A (en) | Efficient spatial nearest neighbor query method for highway networks | |
| CN103970837A (en) | Discontinuous DEM classified manufacturing method based on urban land and vertical planning | |
| CN104699791A (en) | Lost floating car track path recovery method | |
| CN101996516A (en) | Path planning pretreatment method based on vector method | |
| CN111596664B (en) | Unmanned vehicle path planning method based on three-layer architecture | |
| CN116167235A (en) | Road network model generation method, device and equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20140402 |