CN103901892A - Control method and system of unmanned aerial vehicle - Google Patents
Control method and system of unmanned aerial vehicle Download PDFInfo
- Publication number
- CN103901892A CN103901892A CN201410076856.7A CN201410076856A CN103901892A CN 103901892 A CN103901892 A CN 103901892A CN 201410076856 A CN201410076856 A CN 201410076856A CN 103901892 A CN103901892 A CN 103901892A
- Authority
- CN
- China
- Prior art keywords
- path
- flight
- point
- grating map
- unmanned plane
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 25
- 230000004888 barrier function Effects 0.000 claims description 25
- 230000002093 peripheral effect Effects 0.000 claims description 17
- 238000004364 calculation method Methods 0.000 claims description 2
- 238000010586 diagram Methods 0.000 description 8
- 230000007613 environmental effect Effects 0.000 description 6
- 238000003491 array Methods 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 239000000284 extract Substances 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000012512 characterization method Methods 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 239000004615 ingredient Substances 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000005096 rolling process Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Landscapes
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
The invention provides a control method and system of an unmanned aerial vehicle. The method includes the following steps that scanning is performed to generate a grid map of the flight environment, and area demarcation is performed on the flight environment according to the grid map information; according to the grid map and the area demarcation result, a flight path is planned through an A* algorithm; a plurality of path points are selected form the planned flight path, and the shortest distances from the path points to surrounding obstacles are respectively calculated; when the shortest distance between one path point and the corresponding obstacle is larger than the radius of safety, the aircraft can fly along the path point, and when the shortest distance is smaller than the radius of safety, the flight path is planned through a wall-following algorithm so that the aircraft can fly. According to the method, area demarcation is performed on the flight environment according to the map information, the A* algorithm and the wall-following algorithm are combined to plan the flight path, and thus the efficiency and the safety of autonomous flight of the unmanned aerial vehicle are improved and good expansibility is achieved.
Description
Technical field
The present invention relates to unmanned plane technical field, particularly a kind of control method of unmanned plane and system.
Background technology
Unmanned plane can pass through outfit external sensor, and by planning layer algorithm, makes unmanned plane possess environmental information collection, modeling, the ability of goal task planning, decomposition, execution.And then can bring into play key player in fields such as post-disaster search and rescue, infrastructure supervision.
The navigation of unmanned plane is one of them important ingredient.The navigation research of unmanned plane lead be for solve by Durrant ?three key issues proposing of Whyte H F: 1) " now where? ", 2) " where going to? ", 3) " how going to this place? "Can be subdivided into again and be solved complete known environment according to application scenarios, part known environment and the completely navigation problem of circumstances not known.Wherein, the path planning under known environment has been obtained plentiful and substantial achievement in research completely, and Visual Graph method, Grid Method etc. can both be realized the requirement of global path planning efficiently.
To part, navigation unknown and circumstances not known completely is main study hotspot in recent years at present, and to part, navigation unknown and circumstances not known completely mainly adopts Artificial Potential Field Method, fuzzy logic method, the modes such as rolling window law of planning are navigated, and existing mode can make navigation behavior lack " foresight ", and single navigation programming there will be local stuck, sink into part and minimize and explore path and the problem such as repeat.Therefore, cannot, according to the flexible toggle path planning of the variation of environment mode, be unfavorable for the all-round exploration of complicated unknown flight environment of vehicle, greatly increase danger.
Summary of the invention
Object of the present invention is intended at least solve one of above-mentioned technological deficiency.
For this reason, one aspect of the present invention provides a kind of control method of unmanned plane.
Another aspect of the present invention proposes a kind of control system of unmanned plane.
In view of this, the embodiment of one aspect of the present invention proposes a kind of control method of unmanned plane, comprises the following steps: region description step, scans and generates the grating map of flight environment of vehicle, and according to described grating map, described flight environment of vehicle is carried out to region description; Path planning step, according to described grating map and region description result, utilizes A
*algorithmic rule flight path; Minimum distance calculation step is chosen multiple paths point from the described flight path of planning, calculates respectively the bee-line of described multiple path point and peripheral obstacle; And the first flight step, in the time that the bee-line of respective path point and described peripheral obstacle is greater than radius of safety, described unmanned plane flies along this path point.
According to the method for the embodiment of the present invention, information is carried out region description to flight environment of vehicle according to the map, by A
*algorithm and wall ?following algorithm combine to plan flight path, improved efficiency and the security of unmanned plane autonomous flight, there is good extendability simultaneously.
In one embodiment of the invention, also comprise: route adjust step, in the time that the bee-line of described respective path point is less than described radius of safety, by wall ?following algorithm adjust this path point and flight path afterwards thereof, and path point and the bee-line of peripheral obstacle after guaranteeing to adjust is greater than described safe distance; And second flight step, using adjust after multiple path points fly as flight path.
In one embodiment of the invention, described region description step specifically comprises: the grating map that generates described flight environment of vehicle according to the depth information of described flight environment of vehicle; According to described grating map, each grid of described grating map is identified; And being connected so that described flight environment of vehicle is carried out to region description in abutting connection with grid of barrier will be comprised according to recognition result.
In one embodiment of the invention, path planning step specifically comprises: according to current location, described grating map and described region description result selected target point; Utilize A
*algorithm calculates the flight path from described current location to described selected target point.
The present invention embodiment has on the other hand proposed a kind of control system of unmanned plane, comprising: description module, for generating the grating map of flight environment of vehicle, and according to described grating map, described flight environment of vehicle is carried out to region description; Planning module, for according to described grating map and region description result, utilizes A
*algorithmic rule flight path; Computing module, for choosing multiple paths point from the described flight path of planning, and calculates respectively the bee-line of described multiple path point and peripheral obstacle; And flight module, in the time that respective path point is greater than radius of safety with the bee-line of described peripheral obstacle, the path point using this path point in flight path flies.
According to the system of the embodiment of the present invention, information is carried out region description to flight environment of vehicle according to the map, by A
*algorithm and wall ?following algorithm combine to plan flight path, improved efficiency and the security of unmanned plane autonomous flight, there is good extendability simultaneously.
In one embodiment of the invention, also comprise: adjusting module, in the time that the bee-line of described respective path point is less than described radius of safety, by wall ?following algorithm adjust this path point and flight path afterwards thereof, and guarantee that the path point after adjustment is greater than described safe distance with the bee-line of described peripheral obstacle, the multiple path points after adjusting fly as flight path.
In one embodiment of the invention, described description module specifically comprises: generation unit, for generate the grating map of described flight environment of vehicle according to the depth information of described flight environment of vehicle; Recognition unit, for identifying each grid of described grating map according to described grating map; And description unit, for will comprising being connected so that described flight environment of vehicle is carried out to region description in abutting connection with grid of barrier according to recognition result.
In one embodiment of the invention, described planning module specifically comprises: determining unit, for according to current location, described grating map and described region description result selected target point; And planning unit, for utilizing A
*algorithm calculates the flight path from described current location to described selected target point.
The aspect that the present invention is additional and advantage in the following description part provide, and part will become obviously from the following description, or recognize by practice of the present invention.
Accompanying drawing explanation
The present invention above-mentioned and/or additional aspect and advantage will become from the following description of the accompanying drawings of embodiments obviously and easily and understand, wherein,
Fig. 1 is the process flow diagram of the control method of unmanned plane according to an embodiment of the invention;
Fig. 2 is the schematic diagram that can reach row judgement according to the path point of the embodiment of the present invention;
Fig. 3 is the path planning schematic diagram according to the embodiment of the present invention; And
Fig. 4 is according to the structural representation of the control system of the unmanned plane of the embodiment of the present invention.
Embodiment
Describe embodiments of the invention below in detail, the example of embodiment is shown in the drawings, and wherein same or similar label represents same or similar element or has the element of identical or similar functions from start to finish.Be exemplary below by the embodiment being described with reference to the drawings, only for explaining the present invention, and can not be interpreted as limitation of the present invention.
In description of the invention, it will be appreciated that, term " " center ", " longitudinally ", " laterally ", " on ", D score, " front ", " afterwards ", " left side ", " right side ", " vertically ", " level ", " top ", " end ", " interior ", orientation or the position relationship of indications such as " outward " are based on orientation shown in the drawings or position relationship, only the present invention for convenience of description and simplified characterization, rather than device or the element of indication or hint indication must have specific orientation, with specific orientation structure and operation, therefore can not be interpreted as limitation of the present invention.In addition, term " first ", " second " be only for describing object, and can not be interpreted as indication or hint relative importance.
In description of the invention, it should be noted that, unless otherwise clearly defined and limited, term " installation ", " being connected ", " connection " should be interpreted broadly, and for example, can be to be fixedly connected with, and can be also to removably connect, or connect integratedly; Can be mechanical connection, can be also electrical connection; Can be to be directly connected, also can indirectly be connected by intermediary, can be the connection of two element internals.For the ordinary skill in the art, can concrete condition understand above-mentioned term concrete meaning in the present invention.
Fig. 1 is the process flow diagram of the control method of unmanned plane according to an embodiment of the invention.As shown in Figure 1, according to the control method of the unmanned plane of the embodiment of the present invention, comprise the following steps: scan and generate the grating map of flight environment of vehicle, and according to grating map, flight environment of vehicle is carried out to region description (step 101).According to grating map and region description result, utilize A
*algorithmic rule flight path (step 103).From the flight path of planning, choose multiple paths point, calculate respectively the bee-line (step 105) of multiple path points and peripheral obstacle.In the time that respective path point is greater than radius of safety with the bee-line of peripheral obstacle, unmanned plane is along this path point flight (step 107).
According to the method for the embodiment of the present invention, information is carried out region description to flight environment of vehicle according to the map, by A
*algorithm and wall ?following algorithm combine to plan flight path, improved efficiency and the security of unmanned plane autonomous flight, there is good extendability simultaneously.
In step 101, generate the grating map of flight environment of vehicle according to the depth information of flight environment of vehicle.According to grating map, each grid of grating map is identified.Being connected so that flight environment of vehicle is carried out to region description in abutting connection with grid of barrier will be comprised according to recognition result.
In one embodiment of the invention, according to the depth information of a certain height levels in the flight environment of vehicle of certain frequency scanning unmanned plane, and generate the grating map of flight environment of vehicle according to this depth information by airborne sensors such as two-dimensional laser range finders.Wherein, the information of grating map adopts two-dimensional array storage, and in array, ranks number represents the coordinate information of this grid in map, represents different environmental informations by the value of different arrays.For example, " 0 " represents that this grid is searched and there is no barrier, and " 100 " represent that this grid has been explored and has existed barrier, and " 1 " represents that this grid is not also explored.
In one embodiment of the invention, explore the border in region and region to be explored according to the information extraction of grating map, be called zone of ignorance border.Be specially, whether traversal grating map, have the grid of value for " 1 " in the neighbours territory of judgment value for the grid of " 0 ", if there is this grid point to be zone of ignorance frontier point and to store its two-dimensional coordinate, and then all zone of ignorance frontier points done to continuity judgement.When having another frontier point in a certain frontier point eight neighborhoods, these two frontier points are continuous.The continuum boundary point that two-dimensional coordinate is met to linear relation couples together, and forms many zone of ignorance borders.By presetting threshold value T
1and T
2(0 < T
1< T
2) choose and there is appropriate length L(T
1< L < T
2) border and calculate its centre of form coordinate as goal seeking point to be selected.In one embodiment of the invention, after obtaining the centre of form coordinate on many zone of ignorance borders, choose from the nearest centre of form coordinate of unmanned plane as exploring point.
In step 103, according to current location, grating map and region description result selected target point.Utilize A
*algorithm calculates the flight path of point from current location to selected target.
In one embodiment of the invention, because be subject to, the interference, UAV Attitude of complicated flight environment of vehicle change and the impact of sensor noise, possibly cannot correctly extract zone of ignorance border and then cannot selecting paths point.In this case, unmanned plane according to real-time environmental information adopt Wall ?following algorithm calculate next accessibility flight path point, with the continuity that keeps complicated zone of ignorance to explore.
In step 105 and step 107, unmanned plane from the flight path of planning while choosing multiple path point, is distinguished the bee-line of calculating path point and corresponding barrier, to judge whether this path point can reach (whether being less than safe distance).When the radius of unmanned plane is r
ac, safe distance is r
t, radius of safety r
safe=r
ac+ r
t.Judge that the rule whether path point can reach is: with the Dian Wei center of circle, this path, with radius of safety r
safefor radius does circle, if there is no barrier within the scope of this, this path point can reach, otherwise is unreachable.Put in path when unreachable, adjust this path point to fly with the path point after adjusting meeting can reach condition time.Fig. 2 is the schematic diagram that can reach row judgement according to the path point of the embodiment of the present invention.As shown in Figure 2, two path point A and B, whether unmanned plane can first according to there is barrier (being whether some A in path can reach) before arriving A point in real-time Environmental Map Information computationally secure radius (as shown in shade in Fig. 2), determine within the scope of this and do not have to fly to A point after barrier.Arrive after A point, judge the accessibility that B is ordered.In safe hunting zone due to path point B, occurred barrier therefore can not be using path point the path point in the flight path of unmanned plane, need to adjust path point to hide this barrier.For example path can be put to B` and elect the point that is greater than radius of safety from this obstacle distance as.
Fig. 3 is the path planning schematic diagram according to the embodiment of the present invention.As shown in Figure 3, under unmanned plane initial state, be in 1 point, now whole region explored.Can utilize sensor to explore whole cartographic information, use be range finder using laser, being demarcated in whole region.In Fig. 2, white background is known region, and dash area is zone of ignorance.Carry out region description and can obtain a, b, c, tetra-borders of d.Therefrom choose some D on a of border as airbound target point.Now, utilize A
*algorithm calculates a flight path that comprises four path points (1 ?4 is put in path), and its path point quantity can be determined according to the concrete conditions such as flight demand or demand.Unmanned plane flies according to 1 → 2 → 3 → 4 order under normal circumstances.Put to path 1 o'clock in flight, the bee-line between can while calculating path point 2,3,4 and corresponding barrier, and with safe distance comparison judging whether to reach (be bee-line be greater than safe distance corresponding path point as reaching).If path point 2 can reach, and that put in path is 3 unreachable, adjust flight path at path point 2, abandon path point 3 and path point 4, and put in path 2 o'clock (arrive in path point 3 before) adopt wall ?following algorithm along the current wall flight that can detect, to guarantee the continuity of exploration.It should be noted that, unmanned plane constantly carries out planning and the adjustment of region division and path point in flight course.
According to the method for the embodiment of the present invention, information is carried out region description to flight environment of vehicle according to the map, by A
*algorithm and wall ?following algorithm combine to plan flight path, improved efficiency and the security of unmanned plane autonomous flight, there is good extendability simultaneously.
Fig. 4 is according to the structural representation of the control system of the unmanned plane of the embodiment of the present invention.As shown in Figure 4, comprise according to the control system of the unmanned plane of the embodiment of the present invention: description module 100, planning module 300, computing module 500 and flight module 700.
Particularly, description module 100 is for generating the grating map of flight environment of vehicle, and according to grating map, flight environment of vehicle carried out to region description.Planning module 300, for according to grating map and region description result, utilizes A
*algorithmic rule flight path.Computing module 500 is for choosing multiple paths point from the flight path of planning, and calculates respectively the bee-line of multiple path points and peripheral obstacle.Flight module 700 is in the time that respective path point is greater than radius of safety with the bee-line of peripheral obstacle, and the path point using this path point in flight path flies.
According to the system of the embodiment of the present invention, information is carried out region description to flight environment of vehicle according to the map, by A
*algorithm and wall ?following algorithm combine to plan flight path, improved efficiency and the security of unmanned plane autonomous flight, there is good extendability simultaneously.
In one embodiment of the invention, also comprise: adjusting module 900 is in the time that the bee-line of respective path point is less than radius of safety, by wall ?following algorithm adjust this path point and flight path afterwards thereof, and guarantee that the path point after adjustment is greater than safe distance with the bee-line of peripheral obstacle, the multiple path points after adjusting fly as flight path.
According to the system of the embodiment of the present invention, information is carried out region description to flight environment of vehicle according to the map, by A
*algorithm and wall ?the following algorithm planning flight path that combines, the efficiency and the security that have improved unmanned plane autonomous flight have good extendability simultaneously.
In one embodiment of the invention, dividing module 100 specifically comprises: generation unit 110, recognition unit 120 and description unit 130.
Particularly, generation unit 110 is for generating the grating map of flight environment of vehicle according to the depth information of flight environment of vehicle.Recognition unit 120 is for identifying each grid of grating map according to grating map.Description unit 130 is for will comprising being connected so that flight environment of vehicle is carried out to region description in abutting connection with grid of barrier according to recognition result.
In one embodiment of the invention, generation unit 110 passes through the airborne sensors such as two-dimensional laser range finder according to the depth information of a certain height levels in the flight environment of vehicle of certain frequency scanning unmanned plane, and generates the grating map of flight environment of vehicle according to this depth information.Wherein, the cartographic information of grating map adopts two-dimensional array storage, and in array, ranks number represents the coordinate information of this grid in map, represents different environmental informations by the value of different arrays.For example, " 0 " represents that this grid is searched and there is no barrier, and " 100 " represent that this grid has been explored and has existed barrier, and " 1 " represents that this grid is not also explored.
In one embodiment of the invention, description unit 130 extracts the border of having explored region and region to be explored according to the cartographic information of grating map, be called zone of ignorance border.Be specially, whether traversal grating map, have the grid of value for " 1 " in the neighbours territory of judgment value for the grid of " 0 ", if there is this grid point to be zone of ignorance frontier point and to store its two-dimensional coordinate, and then all zone of ignorance frontier points done to continuity judgement.When having another frontier point in a certain frontier point eight neighborhoods, these two frontier points are continuous.The continuum boundary point that two-dimensional coordinate is met to linear relation couples together, and forms many zone of ignorance borders.By presetting threshold value T
1and T
2(0 < T
1< T
2) choose and there is appropriate length L(T
1< L < T
2) border and calculate its centre of form coordinate as goal seeking point to be selected.In one embodiment of the invention, after obtaining the centre of form coordinate on many zone of ignorance borders, choose from the nearest centre of form coordinate of unmanned plane as exploring point.
In one embodiment of the invention, planning module 300 specifically comprises: determining unit 310 and planning unit 320.
Determining unit 310 is for according to current location, grating map and region description result selected target point.Planning unit 320 is for utilizing A
*algorithm calculates the flight path of point from current location to selected target.
Computing module 500 from the flight path of planning while choosing multiple path point, is distinguished the bee-line of calculating path point and corresponding barrier, to judge whether this path point can reach (whether being less than safe distance).When the radius of unmanned plane is r
ac, safe distance is r
t, radius of safety r
safe=r
ac+ r
t.Judge that the rule whether path point can reach is: with the Dian Wei center of circle, this path, with radius of safety r
safefor radius does circle, if there is no barrier within the scope of this, this path point can reach, otherwise is unreachable.Put in path when unreachable, adjust this path point to fly with the path point after adjusting meeting can reach condition time.Fig. 2 is the schematic diagram that can reach row judgement according to the path point of the embodiment of the present invention.As shown in Figure 2, two path point A and B, whether unmanned plane can first according to there is barrier (being whether some A in path can reach) before arriving A point in real-time Environmental Map Information computationally secure radius (as shown in shade in Fig. 2), determine within the scope of this and do not have to fly to A point after barrier.Arrive after A point, judge the accessibility that B is ordered.In safe hunting zone due to path point B, occurred barrier therefore can not be using path point the path point in the flight path of unmanned plane, need to adjust path point to hide this barrier by adjusting module 900.For example adjusting module 900 can be put path B and elect the point that is greater than radius of safety from this obstacle distance as.
Fig. 3 is the path planning schematic diagram according to the embodiment of the present invention.As shown in Figure 3, under unmanned plane initial state, be in 1 point, now whole region explored.Generation unit 110 can utilize sensor to explore whole cartographic information, use be range finder using laser, being demarcated in whole region.In Fig. 2, white background is known region, and dash area is zone of ignorance.Carry out region description and can obtain a, b, c, tetra-borders of d.Therefrom choose some D on a of border as air objective (D for destination).Now, utilize A
*algorithm calculates a flight path that comprises four path points (1 ?4 is put in path), and its path point quantity can be determined according to the concrete conditions such as flight demand or demand.Unmanned plane flies according to 1 → 2 → 3 → 4 order under normal circumstances.Put to path 1 o'clock in flight, the bee-line between can while calculating path point 2,3,4 and corresponding barrier, and with safe distance comparison judging whether to reach (be bee-line be greater than safe distance corresponding path point as reaching).If path point 2 can reach, and path is put 3 adjusting modules 900 when unreachable and is adjusted flight paths at path point 2, abandons path point 3 and path point 4, and puts 2 o'clock (before arrival path point 3) employing A in path
*the adjustment flight paths such as algorithm with in the flight path after adjustment determine with the bee-line of corresponding barrier be greater than safe distance multiple paths point with wall ?following algorithm (arithmetic along the wall), along the current wall flight that can detect, with the continuity that guarantees to explore.It should be noted that, unmanned plane constantly carries out planning and the adjustment of region division and path point in flight course.
According to the method for the embodiment of the present invention, information is carried out region description to flight environment of vehicle according to the map, by A
*algorithm and wall ?following algorithm combine to plan flight path, improved efficiency and the security of unmanned plane autonomous flight, there is good extendability simultaneously.
Although illustrated and described embodiments of the invention above, be understandable that, above-described embodiment is exemplary, can not be interpreted as limitation of the present invention, those of ordinary skill in the art can change above-described embodiment within the scope of the invention in the situation that not departing from principle of the present invention and aim, modification, replacement and modification.
Claims (8)
1. a control method for unmanned plane, is characterized in that, comprises the following steps:
Region description step, scans and generates the grating map of flight environment of vehicle, and according to described grating map, described flight environment of vehicle is carried out to region description;
Path planning step, according to described grating map and region description result, utilizes A
*algorithmic rule flight path;
Minimum distance calculation step is chosen multiple paths point from the described flight path of planning, calculates respectively the bee-line of described multiple path point and peripheral obstacle; And
The first flight step, in the time that respective path point is greater than radius of safety with the bee-line of described peripheral obstacle, described unmanned plane is along this path point flight.
2. the control method of unmanned plane as claimed in claim 1, is characterized in that, also comprises:
Route adjust step, in the time that the bee-line of described respective path point is less than described radius of safety, by wall ?following algorithm adjust this path point and flight path afterwards thereof, and path point and the bee-line of peripheral obstacle after guaranteeing to adjust is greater than described safe distance; And
The second flight step, the multiple path points after adjusting fly as flight path.
3. the control method of unmanned plane as claimed in claim 1, is characterized in that, described region description step specifically comprises:
Generate the grating map of described flight environment of vehicle according to the depth information of described flight environment of vehicle;
According to described grating map, each grid of described grating map is identified; And
Being connected so that described flight environment of vehicle is carried out to region description in abutting connection with grid of barrier will be comprised according to recognition result.
4. the control method of unmanned plane as claimed in claim 1, is characterized in that, described path planning step specifically comprises:
According to current location, described grating map and described region description result selected target point;
Utilize A
*algorithm calculates the flight path from described current location to described selected target point.
5. a control system for unmanned plane, is characterized in that, comprising:
Description module, for generating the grating map of flight environment of vehicle, and carries out region description according to described grating map to described flight environment of vehicle;
Planning module, for according to described grating map and region description result, utilizes A
*algorithmic rule flight path;
Computing module, for choosing multiple paths point from the described flight path of planning, and calculates respectively the bee-line of described multiple path point and peripheral obstacle; And
Flight module, in the time that respective path point is greater than radius of safety with the bee-line of described peripheral obstacle, the path point using this path point in flight path flies.
6. the control system of unmanned plane as claimed in claim 5, is characterized in that, also comprises:
Adjusting module, in the time that the bee-line of described respective path point is less than described radius of safety, by wall ?following algorithm adjust this path point and flight path afterwards thereof, and guarantee that the path point after adjustment is greater than described safe distance with the bee-line of described peripheral obstacle, the multiple path points after adjusting fly as flight path.
7. the control system of unmanned plane as claimed in claim 5, is characterized in that, described description module specifically comprises:
Generation unit, for generating the grating map of described flight environment of vehicle according to the depth information of described flight environment of vehicle;
Recognition unit, for identifying each grid of described grating map according to described grating map; And
Description unit, for will comprising being connected so that described flight environment of vehicle is carried out to region description in abutting connection with grid of barrier according to recognition result.
8. the control system of unmanned plane as claimed in claim 5, is characterized in that, described planning module specifically comprises:
Determining unit, for according to current location, described grating map and described region description result selected target point; And
Planning unit, for utilizing A
*algorithm calculates the flight path from described current location to described selected target point.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410076856.7A CN103901892B (en) | 2014-03-04 | 2014-03-04 | The control method of unmanned plane and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410076856.7A CN103901892B (en) | 2014-03-04 | 2014-03-04 | The control method of unmanned plane and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103901892A true CN103901892A (en) | 2014-07-02 |
| CN103901892B CN103901892B (en) | 2016-12-07 |
Family
ID=50993280
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410076856.7A Expired - Fee Related CN103901892B (en) | 2014-03-04 | 2014-03-04 | The control method of unmanned plane and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103901892B (en) |
Cited By (49)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104881023A (en) * | 2015-04-23 | 2015-09-02 | 杨珊珊 | Control method of multi-rotor type aircraft, and multi-rotor type aircraft |
| CN105242687A (en) * | 2015-10-29 | 2016-01-13 | 桂林创研科技有限公司 | Remote control method of unmanned plane |
| CN105278543A (en) * | 2015-09-28 | 2016-01-27 | 小米科技有限责任公司 | Method and device for increasing flight security, and electronic equipment |
| CN105373616A (en) * | 2015-11-26 | 2016-03-02 | 杨珊珊 | Manufacture method and manufacture device of electronic map |
| CN105492985A (en) * | 2014-09-05 | 2016-04-13 | 深圳市大疆创新科技有限公司 | Multi-sensor environment map building |
| CN105629989A (en) * | 2015-12-28 | 2016-06-01 | 电子科技大学 | Obstacle region division method based on minimum enclosing circle and maximum inscribed circle |
| CN105652876A (en) * | 2016-03-29 | 2016-06-08 | 北京工业大学 | Mobile robot indoor route planning method based on array map |
| CN105843253A (en) * | 2016-04-08 | 2016-08-10 | 北京博瑞空间科技发展有限公司 | Design method and system for unmanned aerial vehicle's travel path |
| CN105867421A (en) * | 2016-05-25 | 2016-08-17 | 华中科技大学 | Unmanned aerial vehicle path planning method based on PH curve |
| CN106227232A (en) * | 2016-07-26 | 2016-12-14 | 斑马信息科技有限公司 | The control method of unmanned plane, device and equipment |
| CN106647766A (en) * | 2017-01-13 | 2017-05-10 | 广东工业大学 | Robot cruise method and system based on complex environment UWB-vision interaction |
| CN107063755A (en) * | 2017-05-29 | 2017-08-18 | 四川沃洛佳科技有限公司 | A kind of unmanned plane water sampling method |
| CN107422736A (en) * | 2017-08-03 | 2017-12-01 | 大连海事大学 | A kind of unmanned boat independently makes a return voyage system and its method of work |
| CN107450576A (en) * | 2017-07-24 | 2017-12-08 | 哈尔滨工程大学 | A kind of method of bridge machinery unmanned plane path planning |
| CN107577241A (en) * | 2017-07-13 | 2018-01-12 | 西北工业大学 | A kind of fire-fighting unmanned aerial vehicle flight path planing method based on obstacle avoidance system |
| CN107656545A (en) * | 2017-09-12 | 2018-02-02 | 武汉大学 | A kind of automatic obstacle avoiding searched and rescued towards unmanned plane field and air navigation aid |
| WO2018023556A1 (en) * | 2016-08-04 | 2018-02-08 | SZ DJI Technology Co., Ltd. | Methods and systems for obstacle identification and avoidance |
| CN107783554A (en) * | 2016-08-26 | 2018-03-09 | 北京臻迪机器人有限公司 | UAV Flight Control method and device |
| CN108227738A (en) * | 2017-12-28 | 2018-06-29 | 湖北电鹰科技有限公司 | A kind of unmanned plane barrier-avoiding method and system |
| CN108764653A (en) * | 2018-04-28 | 2018-11-06 | 广州亿航智能技术有限公司 | Unmanned plane cluster information display methods based on geographic model and system |
| CN108803659A (en) * | 2018-06-21 | 2018-11-13 | 浙江大学 | The heuristic three-dimensional path planing method of multiwindow based on magic square model |
| CN109254593A (en) * | 2018-10-15 | 2019-01-22 | 苏州极目机器人科技有限公司 | Point of safes, point of safes acquisition methods, control device and the operational method using the point of safes |
| CN109341702A (en) * | 2018-12-13 | 2019-02-15 | 广州极飞科技有限公司 | Route planning method, device, equipment and storage medium in operating area |
| CN109417802A (en) * | 2018-08-08 | 2019-03-01 | 北京小米移动软件有限公司 | Transmit the method and device of flight information |
| CN109447326A (en) * | 2018-09-30 | 2019-03-08 | 深圳眸瞳科技有限公司 | Unmanned plane traveling locus generation method, device, electronic equipment and storage medium |
| WO2019047233A1 (en) * | 2017-09-11 | 2019-03-14 | Sz Dji Technology Co. , Ltd. | System and method for supporting safe operation of operating object |
| CN109506654A (en) * | 2018-11-14 | 2019-03-22 | 飞牛智能科技（南京）有限公司 | Low latitude Route planner and device, aircraft |
| US10240930B2 (en) | 2013-12-10 | 2019-03-26 | SZ DJI Technology Co., Ltd. | Sensor fusion |
| CN109709554A (en) * | 2018-12-13 | 2019-05-03 | 广州极飞科技有限公司 | Operating equipment and its control method and device |
| CN110119140A (en) * | 2018-02-07 | 2019-08-13 | 百度（美国）有限责任公司 | System and method for acceleration curve projection |
| CN110262518A (en) * | 2019-07-22 | 2019-09-20 | 上海交通大学 | Automobile navigation method, system and medium based on track topological map and avoidance |
| US10421543B2 (en) | 2014-09-05 | 2019-09-24 | SZ DJI Technology Co., Ltd. | Context-based flight mode selection |
| CN110494815A (en) * | 2018-03-30 | 2019-11-22 | 深圳市大疆创新科技有限公司 | A kind of paths planning method and device |
| CN110568862A (en) * | 2019-09-29 | 2019-12-13 | 苏州浪潮智能科技有限公司 | Unmanned aerial vehicle flight path planning method and device and related equipment |
| CN111435256A (en) * | 2019-01-12 | 2020-07-21 | 上海航空电器有限公司 | Automatic terrain evasion method for aircraft based on grid map |
| US10845805B2 (en) | 2014-09-05 | 2020-11-24 | SZ DJI Technology Co., Ltd. | Velocity control for an unmanned aerial vehicle |
| CN112166394A (en) * | 2019-10-31 | 2021-01-01 | 深圳市大疆创新科技有限公司 | Air route planning method, equipment, system and storage medium |
| CN112729248A (en) * | 2020-12-18 | 2021-04-30 | 湖南文理学院 | Remote sensing detection system and method based on unmanned aerial vehicle platform |
| CN113253761A (en) * | 2021-06-08 | 2021-08-13 | 北京远度互联科技有限公司 | Real-time path planning method and device, movable carrier and storage medium |
| CN113310493A (en) * | 2021-05-28 | 2021-08-27 | 广东工业大学 | Unmanned aerial vehicle real-time navigation method based on event trigger mechanism |
| CN113741516A (en) * | 2021-08-30 | 2021-12-03 | 中国科学院地理科学与资源研究所 | Multi-unmanned aerial vehicle stacking operation method and system, storage medium and electronic equipment |
| CN113741507A (en) * | 2020-05-29 | 2021-12-03 | 广州极飞科技股份有限公司 | Global path trajectory planning method and device for unmanned aerial vehicle, unmanned aerial vehicle and equipment |
| CN114115341A (en) * | 2021-11-18 | 2022-03-01 | 中国人民解放军陆军工程大学 | Intelligent cluster cooperative motion method and system |
| CN114252070A (en) * | 2020-09-25 | 2022-03-29 | 海鹰航空通用装备有限责任公司 | Unmanned aerial vehicle path planning method suitable for given path length |
| CN114610076A (en) * | 2022-05-10 | 2022-06-10 | 四川大学 | Flight path planning method combining artificial potential field method and A-star algorithm angle constraint |
| CN115016546A (en) * | 2022-08-10 | 2022-09-06 | 中国科学院自动化研究所 | Unmanned aerial vehicle three-dimensional path planning method and device, electronic equipment and storage medium |
| CN116449865A (en) * | 2023-03-15 | 2023-07-18 | 中国人民解放军国防科技大学 | Cluster task decomposition method and system for clustered unmanned aerial vehicle based on state awareness |
| CN116736879A (en) * | 2023-08-16 | 2023-09-12 | 成都飞航智云科技有限公司 | Unmanned aerial vehicle automatic obstacle avoidance method and obstacle avoidance system based on cloud computing |
| CN117232512A (en) * | 2023-08-04 | 2023-12-15 | 广东工业大学 | Unmanned aerial vehicle path acquisition method for efficient search and nested cooperation optimization strategy |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102880186A (en) * | 2012-08-03 | 2013-01-16 | 北京理工大学 | Flight path planning method based on sparse A* algorithm and genetic algorithm |
| CN103528586A (en) * | 2013-10-31 | 2014-01-22 | 中国航天时代电子公司 | Sailing planning algorithm design based on grid failure |
-
2014
- 2014-03-04 CN CN201410076856.7A patent/CN103901892B/en not_active Expired - Fee Related
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102880186A (en) * | 2012-08-03 | 2013-01-16 | 北京理工大学 | Flight path planning method based on sparse A* algorithm and genetic algorithm |
| CN103528586A (en) * | 2013-10-31 | 2014-01-22 | 中国航天时代电子公司 | Sailing planning algorithm design based on grid failure |
Non-Patent Citations (5)
| Title |
|---|
| MENG BO-BO,ETC: "UAV Path Planning based on Bidirectional Sparse A* Search Algorithm", 《2010 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION》, 31 December 2010 (2010-12-31), pages 1106 - 1109 * |
| 张得舒，等: "基于A*算法的无人机攻击轨迹解算", 《电光与控制》, vol. 18, no. 3, 31 March 2011 (2011-03-31), pages 18 - 20 * |
| 李季，等: "基于改进A-Star算法的无人机航迹规划算法研究", 《兵工学报》, vol. 29, no. 7, 31 July 2008 (2008-07-31) * |
| 王振华，等: "基于栅格空间V图的无人机路径规划", 《计算机测量与控制》, vol. 17, no. 6, 31 December 2009 (2009-12-31), pages 1212 - 1214 * |
| 穆中林，等: "基于改进A*算法的无人机航路规划方法研究", 《弹箭与制导学报》, vol. 27, no. 1, 31 December 2007 (2007-12-31), pages 297 - 300 * |
Cited By (75)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10240930B2 (en) | 2013-12-10 | 2019-03-26 | SZ DJI Technology Co., Ltd. | Sensor fusion |
| US10421543B2 (en) | 2014-09-05 | 2019-09-24 | SZ DJI Technology Co., Ltd. | Context-based flight mode selection |
| US10845805B2 (en) | 2014-09-05 | 2020-11-24 | SZ DJI Technology Co., Ltd. | Velocity control for an unmanned aerial vehicle |
| CN105492985A (en) * | 2014-09-05 | 2016-04-13 | 深圳市大疆创新科技有限公司 | Multi-sensor environment map building |
| US11914369B2 (en) | 2014-09-05 | 2024-02-27 | SZ DJI Technology Co., Ltd. | Multi-sensor environmental mapping |
| US11370540B2 (en) | 2014-09-05 | 2022-06-28 | SZ DJI Technology Co., Ltd. | Context-based flight mode selection |
| US10429839B2 (en) | 2014-09-05 | 2019-10-01 | SZ DJI Technology Co., Ltd. | Multi-sensor environmental mapping |
| US10901419B2 (en) | 2014-09-05 | 2021-01-26 | SZ DJI Technology Co., Ltd. | Multi-sensor environmental mapping |
| CN104881023A (en) * | 2015-04-23 | 2015-09-02 | 杨珊珊 | Control method of multi-rotor type aircraft, and multi-rotor type aircraft |
| CN105278543A (en) * | 2015-09-28 | 2016-01-27 | 小米科技有限责任公司 | Method and device for increasing flight security, and electronic equipment |
| CN105242687A (en) * | 2015-10-29 | 2016-01-13 | 桂林创研科技有限公司 | Remote control method of unmanned plane |
| CN105373616A (en) * | 2015-11-26 | 2016-03-02 | 杨珊珊 | Manufacture method and manufacture device of electronic map |
| CN105373616B (en) * | 2015-11-26 | 2019-03-22 | 杨珊珊 | The production method and producing device of electronic map |
| CN105629989B (en) * | 2015-12-28 | 2018-04-17 | 电子科技大学 | Based on the barrier zone division methods to take all of outside minimum with maximum inscribed circle |
| CN105629989A (en) * | 2015-12-28 | 2016-06-01 | 电子科技大学 | Obstacle region division method based on minimum enclosing circle and maximum inscribed circle |
| CN105652876A (en) * | 2016-03-29 | 2016-06-08 | 北京工业大学 | Mobile robot indoor route planning method based on array map |
| CN105843253A (en) * | 2016-04-08 | 2016-08-10 | 北京博瑞空间科技发展有限公司 | Design method and system for unmanned aerial vehicle's travel path |
| CN105867421A (en) * | 2016-05-25 | 2016-08-17 | 华中科技大学 | Unmanned aerial vehicle path planning method based on PH curve |
| CN106227232A (en) * | 2016-07-26 | 2016-12-14 | 斑马信息科技有限公司 | The control method of unmanned plane, device and equipment |
| CN109478070A (en) * | 2016-08-04 | 2019-03-15 | 深圳市大疆创新科技有限公司 | Obstacle recognition and preventing collision method and system |
| WO2018023556A1 (en) * | 2016-08-04 | 2018-02-08 | SZ DJI Technology Co., Ltd. | Methods and systems for obstacle identification and avoidance |
| CN107783554A (en) * | 2016-08-26 | 2018-03-09 | 北京臻迪机器人有限公司 | UAV Flight Control method and device |
| CN106647766A (en) * | 2017-01-13 | 2017-05-10 | 广东工业大学 | Robot cruise method and system based on complex environment UWB-vision interaction |
| CN107063755B (en) * | 2017-05-29 | 2023-05-05 | 四川沃洛佳科技有限公司 | Unmanned aerial vehicle water sample collection method |
| CN107063755A (en) * | 2017-05-29 | 2017-08-18 | 四川沃洛佳科技有限公司 | A kind of unmanned plane water sampling method |
| CN107577241B (en) * | 2017-07-13 | 2020-05-12 | 西北工业大学 | Fire-fighting unmanned aerial vehicle track planning method based on obstacle avoidance system |
| CN107577241A (en) * | 2017-07-13 | 2018-01-12 | 西北工业大学 | A kind of fire-fighting unmanned aerial vehicle flight path planing method based on obstacle avoidance system |
| CN107450576A (en) * | 2017-07-24 | 2017-12-08 | 哈尔滨工程大学 | A kind of method of bridge machinery unmanned plane path planning |
| CN107422736A (en) * | 2017-08-03 | 2017-12-01 | 大连海事大学 | A kind of unmanned boat independently makes a return voyage system and its method of work |
| WO2019047233A1 (en) * | 2017-09-11 | 2019-03-14 | Sz Dji Technology Co. , Ltd. | System and method for supporting safe operation of operating object |
| CN107656545A (en) * | 2017-09-12 | 2018-02-02 | 武汉大学 | A kind of automatic obstacle avoiding searched and rescued towards unmanned plane field and air navigation aid |
| CN108227738B (en) * | 2017-12-28 | 2019-07-19 | 湖北电鹰科技有限公司 | A kind of unmanned plane barrier-avoiding method and system |
| CN108227738A (en) * | 2017-12-28 | 2018-06-29 | 湖北电鹰科技有限公司 | A kind of unmanned plane barrier-avoiding method and system |
| CN110119140A (en) * | 2018-02-07 | 2019-08-13 | 百度（美国）有限责任公司 | System and method for acceleration curve projection |
| CN110119140B (en) * | 2018-02-07 | 2022-05-17 | 百度（美国）有限责任公司 | System and method for accelerating curvilinear projection |
| CN110494815A (en) * | 2018-03-30 | 2019-11-22 | 深圳市大疆创新科技有限公司 | A kind of paths planning method and device |
| CN108764653A (en) * | 2018-04-28 | 2018-11-06 | 广州亿航智能技术有限公司 | Unmanned plane cluster information display methods based on geographic model and system |
| CN108803659B (en) * | 2018-06-21 | 2020-05-08 | 浙江大学 | Multi-window heuristic three-dimensional space path planning method based on magic cube model |
| CN108803659A (en) * | 2018-06-21 | 2018-11-13 | 浙江大学 | The heuristic three-dimensional path planing method of multiwindow based on magic square model |
| CN109417802B (en) * | 2018-08-08 | 2023-10-17 | 北京小米移动软件有限公司 | Method and device for transmitting flight information |
| CN109417802A (en) * | 2018-08-08 | 2019-03-01 | 北京小米移动软件有限公司 | Transmit the method and device of flight information |
| US11443639B2 (en) | 2018-09-30 | 2022-09-13 | Moutong Science And Technology Co., Ltd | Methods of generating a unmanned aerial vehicle migration trajectory, electronic devices and storage mediums |
| CN109447326A (en) * | 2018-09-30 | 2019-03-08 | 深圳眸瞳科技有限公司 | Unmanned plane traveling locus generation method, device, electronic equipment and storage medium |
| CN109447326B (en) * | 2018-09-30 | 2021-11-30 | 深圳眸瞳科技有限公司 | Unmanned aerial vehicle migration track generation method and device, electronic equipment and storage medium |
| CN109254593A (en) * | 2018-10-15 | 2019-01-22 | 苏州极目机器人科技有限公司 | Point of safes, point of safes acquisition methods, control device and the operational method using the point of safes |
| CN109254593B (en) * | 2018-10-15 | 2020-06-16 | 苏州极目机器人科技有限公司 | Security point, security point acquisition method, control device, and operation method using security point |
| CN109506654B (en) * | 2018-11-14 | 2020-10-20 | 飞牛智能科技（南京）有限公司 | Low-altitude route planning method and device and aircraft |
| CN109506654A (en) * | 2018-11-14 | 2019-03-22 | 飞牛智能科技（南京）有限公司 | Low latitude Route planner and device, aircraft |
| CN109341702B (en) * | 2018-12-13 | 2021-07-20 | 广州极飞科技股份有限公司 | Route planning method, device and equipment in operation area and storage medium |
| CN109341702A (en) * | 2018-12-13 | 2019-02-15 | 广州极飞科技有限公司 | Route planning method, device, equipment and storage medium in operating area |
| CN109709554A (en) * | 2018-12-13 | 2019-05-03 | 广州极飞科技有限公司 | Operating equipment and its control method and device |
| CN109709554B (en) * | 2018-12-13 | 2021-01-19 | 广州极飞科技有限公司 | Work device, and control method and device thereof |
| CN111435256A (en) * | 2019-01-12 | 2020-07-21 | 上海航空电器有限公司 | Automatic terrain evasion method for aircraft based on grid map |
| CN110262518A (en) * | 2019-07-22 | 2019-09-20 | 上海交通大学 | Automobile navigation method, system and medium based on track topological map and avoidance |
| CN110568862A (en) * | 2019-09-29 | 2019-12-13 | 苏州浪潮智能科技有限公司 | Unmanned aerial vehicle flight path planning method and device and related equipment |
| CN112166394A (en) * | 2019-10-31 | 2021-01-01 | 深圳市大疆创新科技有限公司 | Air route planning method, equipment, system and storage medium |
| CN113741507A (en) * | 2020-05-29 | 2021-12-03 | 广州极飞科技股份有限公司 | Global path trajectory planning method and device for unmanned aerial vehicle, unmanned aerial vehicle and equipment |
| CN114252070A (en) * | 2020-09-25 | 2022-03-29 | 海鹰航空通用装备有限责任公司 | Unmanned aerial vehicle path planning method suitable for given path length |
| CN112729248A (en) * | 2020-12-18 | 2021-04-30 | 湖南文理学院 | Remote sensing detection system and method based on unmanned aerial vehicle platform |
| CN113310493A (en) * | 2021-05-28 | 2021-08-27 | 广东工业大学 | Unmanned aerial vehicle real-time navigation method based on event trigger mechanism |
| CN113310493B (en) * | 2021-05-28 | 2022-08-05 | 广东工业大学 | Unmanned aerial vehicle real-time navigation method based on event trigger mechanism |
| CN113253761A (en) * | 2021-06-08 | 2021-08-13 | 北京远度互联科技有限公司 | Real-time path planning method and device, movable carrier and storage medium |
| CN113253761B (en) * | 2021-06-08 | 2021-11-09 | 北京远度互联科技有限公司 | Real-time path planning method and device, movable carrier and storage medium |
| CN113741516A (en) * | 2021-08-30 | 2021-12-03 | 中国科学院地理科学与资源研究所 | Multi-unmanned aerial vehicle stacking operation method and system, storage medium and electronic equipment |
| CN114115341A (en) * | 2021-11-18 | 2022-03-01 | 中国人民解放军陆军工程大学 | Intelligent cluster cooperative motion method and system |
| CN114115341B (en) * | 2021-11-18 | 2022-11-01 | 中国人民解放军陆军工程大学 | Intelligent agent cluster cooperative motion method and system |
| CN114610076A (en) * | 2022-05-10 | 2022-06-10 | 四川大学 | Flight path planning method combining artificial potential field method and A-star algorithm angle constraint |
| CN114610076B (en) * | 2022-05-10 | 2022-07-29 | 四川大学 | Flight path planning method combining artificial potential field method and A-star algorithm angle constraint |
| CN115016546B (en) * | 2022-08-10 | 2022-10-28 | 中国科学院自动化研究所 | Unmanned aerial vehicle three-dimensional path planning method and device, electronic equipment and storage medium |
| CN115016546A (en) * | 2022-08-10 | 2022-09-06 | 中国科学院自动化研究所 | Unmanned aerial vehicle three-dimensional path planning method and device, electronic equipment and storage medium |
| CN116449865A (en) * | 2023-03-15 | 2023-07-18 | 中国人民解放军国防科技大学 | Cluster task decomposition method and system for clustered unmanned aerial vehicle based on state awareness |
| CN116449865B (en) * | 2023-03-15 | 2024-03-12 | 中国人民解放军国防科技大学 | Cluster task decomposition method and system for clustered unmanned aerial vehicle based on state awareness |
| CN117232512A (en) * | 2023-08-04 | 2023-12-15 | 广东工业大学 | Unmanned aerial vehicle path acquisition method for efficient search and nested cooperation optimization strategy |
| CN117232512B (en) * | 2023-08-04 | 2024-05-24 | 广东工业大学 | Unmanned aerial vehicle path acquisition method for efficient search and nested cooperation optimization strategy |
| CN116736879A (en) * | 2023-08-16 | 2023-09-12 | 成都飞航智云科技有限公司 | Unmanned aerial vehicle automatic obstacle avoidance method and obstacle avoidance system based on cloud computing |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103901892B (en) | 2016-12-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103901892A (en) | Control method and system of unmanned aerial vehicle | |
| KR102226350B1 (en) | Autonomous visual navigation | |
| US10809361B2 (en) | Hybrid-view LIDAR-based object detection | |
| Gwon et al. | Generation of a precise and efficient lane-level road map for intelligent vehicle systems | |
| Droeschel et al. | Multilayered mapping and navigation for autonomous micro aerial vehicles | |
| CN108897312B (en) | Method for planning continuous monitoring path of multiple unmanned aerial vehicles to large-scale environment | |
| US9524647B2 (en) | Autonomous Nap-Of-the-Earth (ANOE) flight path planning for manned and unmanned rotorcraft | |
| KR101778028B1 (en) | Robot and method for planning path of the same | |
| US20160203374A1 (en) | Target grouping techniques for object fusion | |
| US10676213B2 (en) | Optimal safe landing area determination | |
| JP2015006874A (en) | Systems and methods for autonomous landing using three dimensional evidence grid | |
| KR101409323B1 (en) | Method and Apparatus for Path Planning of Unmanned Ground Vehicle in Dynamic Environment | |
| CN103809597A (en) | Flight path planning method for unmanned plane and unmanned plane | |
| Jain et al. | Autonomous river exploration | |
| ES2935618T3 (en) | Navigation method of a vehicle and system thereof | |
| CN113050685B (en) | Autonomous inspection method for underground unmanned aerial vehicle of coal mine | |
| Mueller et al. | GIS-based topological robot localization through LIDAR crossroad detection | |
| Chen et al. | Tracking with UAV using tangent-plus-Lyapunov vector field guidance | |
| Zhao et al. | Autonomous Exploration Method for Fast Unknown Environment Mapping by Using UAV Equipped with Limited FOV Sensor | |
| Raaijmakers et al. | In-vehicle roundabout perception supported by a priori map data | |
| Chen et al. | A dynamic path planning algorithm for UAV tracking | |
| Liu et al. | Binocular vision-based autonomous path planning for UAVs in unknown outdoor scenes | |
| Miller et al. | To drive is human | |
| Jung et al. | Robust Collision-free Lightweight Aerial Autonomy for Unknown Area Exploration | |
| Priyasad et al. | Point cloud based autonomous area exploration algorithm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20161207 |