CN109557936A - Anti-collision control method between the unmanned plane machine that hung down based on Artificial Potential Field Method - Google Patents
Anti-collision control method between the unmanned plane machine that hung down based on Artificial Potential Field Method Download PDFInfo
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Abstract
The present invention is based on anti-collision control methods between the unmanned plane machine that hung down of Artificial Potential Field Method, include the following steps: 1: establishing the basic Controlling model of unmanned plane.2: establishing the security control model of unmanned plane.3: the rate control instruction of unmanned plane under current state is obtained based on the controller of the point-to-point provided in step according to the current location of unmanned plane and speed and the position of the target point of unmanned plane.Multiple no-manned plane machine flight anticollision control section.4: the position and speed based on the current position and speed of unmanned plane and surrounding other unmanned planes, calculate the opposite filtering distance between them, according to Artificial Potential Field caused by every frame unmanned plane around, calculate the potential field repulsive force from other unmanned planes around suffered by current unmanned plane, that is rate control instruction, according to the controller of design, the total rate control instruction for calculating current state unmanned plane controls every frame unmanned plane and reaches target point in the case where not colliding with other unmanned planes.
Description
Technical field
Anti-collision control method between the present invention relates to a kind of unmanned plane machine that hung down based on Artificial Potential Field Method, the invention
Belong to flight control method.
Background technique
With the development of microminiature unmanned vehicle, a large amount of use of unmanned plane has also caused people for the load of safety
Sorrow, influencing aviation order, swarm into sensitizing range etc. " black to fly ", phenomenon happens occasionally, and the unmanned plane that can hang down is then micro- in recent years
One Typical Representative of small drone.After unmanned plane quantity increase in small area, when multiple UAVs are completed to appoint jointly
When business, in order to ensure unmanned plane is awing with the safety in work, the programmed decision-making in flight course is inevitable.Due to nothing
Man-machine all in hedgehopping, airflight environment is sufficiently complex, in addition to unmanned plane to be avoided and some static-obstacle thing ratios
The building of such as surrounding bumps against, it is necessary to prevent unmanned plane and unmanned plane from bumping against.Therefore, the anticollision between multimachine, which flies, controls
It makes necessary.
To solve the above problems, anticollision between the invention proposes a kind of unmanned plane machine that hung down based on Artificial Potential Field Method
Control method realizes anticollision flight control between multiple no-manned plane.
Summary of the invention
The invention proposes anti-collision control methods between a kind of unmanned plane machine that hung down based on Artificial Potential Field Method used.
This method is based on traditional Artificial Potential Field Method.Firstly, establishing can the hang down basic Controlling model of unmanned plane and Ke Chui unmanned planes
Then security control model establishes the Artificial Potential Field of other unmanned planes that can hang down around the unmanned plane that can hang down, finally, according to
The current position and speed of unmanned plane, control unmanned plane are flown in the case where not colliding with the unmanned plane of surrounding to target
Point.
The present invention gives anti-collision control methods between the unmanned plane machine that hung down based on Artificial Potential Field Method.Here it defines such as
Lower variable:
It is the Filtering position of the i-th frame unmanned plane and l frame unmanned plane respectively,It is respectively
I-th frame unmanned plane and l frame unmanned plane current location,It is the present speed of the i-th frame unmanned plane,It is control
The rate control instruction of i-th frame unmanned plane of device output processed,It is p respectivelyi、vi、ξiFirst derivation.
It is the maximum value of the flying speed of unmanned plane;
It is safe distance,It is the safe distance based on filtering,It is avoidance maneuvering distance, rvBe away from
Noise error from measurement;
It is the aiming spot of the i-th frame unmanned plane;
It is the alternate position spike of the i-th frame unmanned plane and target point,It is the i-th frame unmanned plane and target point
Filtering position it is poor;
It is the alternate position spike of the i-th frame unmanned plane and l frame unmanned plane,It is the i-th frame unmanned plane and
The Filtering position of l frame unmanned plane is poor.
The control method is as follows: please referring to shown in attached drawing 6;
Step 1: establishing the basic Controlling model for the unmanned plane that can hang down
Firstly the need of the basic Controlling model for defining unmanned plane.It here is a Mass Model by unmanned aerial vehicle vision, then i-th
Frame unmanned plane meets following relationship model:
Here lcIt is the parameter of the control performance of unmanned plane, is determined by unmanned plane itself.Due to the mobility of unmanned plane
Can be limited, therefore the speed command that controller resolves can not be infinitely great.Here following saturation function is devised:
Therefore, the rate control instruction of the i-th frame unmanned plane of final controller output are as follows:
vc,i=sat (vc,i,vm) (3)
Here a concept, referred to as Filtering position are defined.Filtering position is in order to by the current location of unmanned plane and speed
It states out with a scale.Such benefit is that we can indicate the second order Controlling model of unmanned plane with single order form.
It is defined as shown in formula (4):
Next it can be obtained by:
Here it defines:
For convenience, it is defined as follows alternate position spike:
The alternate position spike of corresponding filtering distance are as follows:
According to filtering distance definition, Wo Menyou:
Here i, l=1,2,3..., i ≠ l.In order to guarantee safety, certain distance must be all kept between any unmanned plane.
If this distance is r, for the i-th frame unmanned plane and l frame unmanned plane, then having:
||pi-pl||≥r,i≠l (7)
Step 2: being built according to the current position and speed of unmanned plane that can hang down according to the safe distance for the unmanned plane that can hang down
The security control model of vertical unmanned plane;
In the region of multimachine flight, itself can be reported mutually by modes such as wireless networks between unmanned plane
Position and posture.Since communication has delay, there is also noises for the navigation data of acquisition, therefore the location information of unmanned plane exists
It is uncertain.In order to avoid the object of unmanned plane and surrounding collides, we define safe distance rm, safe distance is necessary
Greater than the physical radius of unmanned plane, as shown in Figure 1.For any two framves unmanned plane, their filtering distance should meet:
||ξi-ξl||≥2rM (8)
Formula (7) can be met by formula (8).Here rM=rm+rv, rMBe based on filtering distance definition safety away from
From.In order to there is sufficient time and space to carry out motor-driven avoidance, such as Fig. 1 when guaranteeing unmanned plane of the unmanned plane around discovery
It is shown.raIt is only related with the power performance of unmanned plane itself and response time.It is required that avoidance maneuvering distance raIt is tallying with the actual situation
Under conditions of must it is as big as possible, here require:
ra> 2rM (9)
Step 3: the flight control for the unmanned plane point-to-point that can hang down
The filtering distance of the current position of unmanned plane and target point isUnmanned plane reaches target point
Condition is:
In order to guarantee that the i-th frame unmanned plane can reach target point, controller output quantity v can be designedc,i, i.e. controller is defeated
The rate control instruction of the i-th frame unmanned plane out are as follows:
Wherein, k1For the gain coefficient of controller output.
Step 4: relative position and speed, calculating based on unmanned plane Yu surrounding other unmanned planes that can hang down of can having hung down can hang down
Play the control instruction of anticollision suffered by unmanned plane
If the current location of the i-th frame and l frame unmanned plane is respectivelyWithPresent speed is respectivelyWithThe airbound target point of this two framves unmanned plane is respectivelyWithThe speed received
Degree control instruction, which inputs, is respectivelyWithAccording to the security control model of unmanned plane, their current filters
Wave position isWithThe filtering distance of the current position of unmanned plane and target point isWithOpposite filtering distance between this two framves unmanned plane isAccording to the security control model of unmanned plane,
The distance between all target points of unmanned plane have to be larger than safe distance.
So unmanned plane is in the condition that cannot be collided into the way of respective target point of flying are as follows:
Wherein, t is the time.
Consider scene as shown in Figure 3, this is the schematic top plan view of three frame unmanned planes and its target point in region.Including
Three frame unmanned plane UAV1, UAV2 and UAV3 and corresponding three target points of eachFor
Unmanned plane in this region in-flight needs to guarantee to collide between unmanned plane, and reaches respective target point.
That is:
Remember Νm,iFor removed in a unmanned plane group of planes middle in region the i-th frame unmanned plane other unmanned planes set.In Fig. 3
Flying scene for, share three frame unmanned planes.Νm,1={ 2,3 }, Νm,2={ 1,3 }, Νm,3={ 1,2 }.Based on the above property
Matter can provide the rate control instruction of the i-th frame unmanned plane of controller output, representation here are as follows:
Wherein,For the potential-energy function of Artificial Potential Field, it is defined as follows:
For the convenience of description, we rememberd1=2rM,d2=ra, note
rsIt is a minimum.It is a smooth truncation letter
Number,It is a smooth saturation function.The smooth basic function of the two second orders, such as Fig. 2
(a), shown in Fig. 2 (b).The function of introducing is that the parameter for the operation relation between more simplified formula, therefore in following formula is equal
For intermediate variable, itself is without meaning, description merely for convenience.
Wherein, A=-2/ (d1-d2)3, B=3 (d1+d2)/(d1-d2)3, C=-6d1d2/(d1-d2)3, D=d2 2(3d1-d2)/
(d1-d2)3.Function σ (x, d1,d2) partial derivative relative to x are as follows:
Saturation function s (y, rs) are as follows:
Wherein,
y1=y2-sin45°rs
For any rs∈ [0, tan67.5 °/(tan67.5 ° sin45 ° -1)], have,
Wherein, min (y, 1) indicates the smaller value therein of variable y and 1.Function s (y, rs) relative to y partial derivative be public affairs
Formula (19), it is clear that
k2For the gain coefficient of controller output.There are indivisible ε, so that,
Other than anticollision, we also need to control unmanned plane reach target point, therefore controller output the i-th frame without
Man-machine rate control instruction:
Unmanned plane stablizes the constraint condition for reaching target point for there are an indivisible ε, so that formula (22) is set up.
Therefore, the method for anticollision includes: between unmanned plane
Input: the real time position velocity information of all unmanned planes and corresponding target point in region.
Output: the rate control instruction v of each unmanned planec,i。
4.1: obtaining the real time position velocity information and aiming spot of all unmanned planes in region;
4.2: the anticollision between unmanned plane and surrounding unmanned plane being calculated according to formula (14) and formula (15) and is instructed;
4.3: the control instruction that target point generates is calculated according to formula (11) according to unmanned plane target point position;
4.4: the instruction generated in step 4.2 and step 4.3 being superimposed according to formula (21), protect at the saturation in direction
Reason;
4.5: if meeting constraint condition formula (22), illustrating that unmanned plane arrived target point;Otherwise step is continued to execute
4.2。
Advantage and effect: the present invention provides anticollision controlling party between a kind of unmanned plane machine that hung down based on Artificial Potential Field Method
Method.The advantages of this method is: the collision problem that may occur between them when solving unmanned plane multimachine flight, advantage are as follows:
(1) the multi-rotor unmanned aerial vehicle model used is the Double Integral Models that there is speed command to input, and is suitble to most of nothings
It is man-machine.The model is simple and easy, it is often more important that, which is the tie for connecting bottom control and top layer application algorithm.We
It can be designed and developed accordingly based on commercial semi-autonomous autopilot for the completion of various tasks.
(2) rate control instruction has saturation capacity protection.Maximum speed instruction in the controller of design is conditional.
When unmanned plane and barrier are close, the speed command that anticollision generates can reach the speed control of target point much larger than unmanned plane
Instruction can be improved the priority of unmanned plane anticollision control, guarantee the peace of unmanned plane after using the saturation control in direction is protected
Entirely.
(3) according to the controller, unmanned plane is all finally to converge to target point regardless of whether encounter barrier.Namely
It says, which can not only make unmanned plane complete aerial mission, moreover it is possible to the safety during guaranteeing to fulfil a task.
(4) when two frame unmanned plane distances are less than safe distance, entire control algolithm still can quickly make its separation.
Detailed description of the invention
Fig. 1: safe distance two-dimensional projection model.
Fig. 2 (a): being smooth truncation funcation.
Fig. 2 (b): being smooth saturation function.
Fig. 3: flight schematic diagram in multiple UAVs region.
The experimental setup schematic diagram of Fig. 4: three frame unmanned plane anticollisions.
Fig. 5 (a): being the three-dimensional track of three frame quadrotors.
Fig. 5 (b): being the track floor projection of three frame quadrotors.
Fig. 6: being flow chart of the invention.
Symbol description in figure
Fig. 1: safe distance rm, avoidance maneuvering distance ra。
Fig. 2 (b): rs∈ [0, tan67.5 °/(tan67.5 ° sin45 ° -1)], it is a minimum.
Fig. 3: three frame unmanned plane UAV1, UAV2 and UAV3 and corresponding three target points of each
Fig. 4: three frame unmanned planes, are denoted as U respectively1,U2,U3, the p of their target point respectivelyd,1,pd,2,pd,3
Specific embodiment
Anti-collision control method between the present invention provides a kind of unmanned plane machine that hung down based on Artificial Potential Field Method, with multiple
For unmanned plane flies in region, a specific embodiment of the invention is further described.It is described below according to this hair
The method mentioned in bright is between anticollision flight control the multimachine machine of unmanned plane.It please refers to shown in attached drawing 1-6.
(1) method specific implementation step:
Step 1: the basic Controlling model of unmanned plane that can hang down is established
The foundation of basic Controlling model needs two parameters: l=10, vm=2.0m/s.Our Filtering position are as follows:
The rate control instruction of i-th frame unmanned plane of the controller output with saturation are as follows:
Step 2: the security control model for the unmanned plane that can hang down is established
The core parameter of Safety distance model are as follows: rm=0.6m, ra=1.8m, rM=0.8m.
Step 3: the flight control for the unmanned plane point-to-point that can hang down
It is k that this step, which needs parameter to be given,1=0.5, the speed of the i-th frame unmanned plane of the controller output with saturation
Control instruction are as follows:
Step 4: relative position and speed, calculating based on unmanned plane Yu surrounding other unmanned planes that can hang down of can having hung down can
It has hung down the control instruction of anticollision suffered by unmanned plane.
In the experiment, three frame unmanned planes have been used altogether, have been denoted as U respectively1,U2,U3, see Fig. 4.Their own initial position
It is respectively as follows:
pu1=[- 2.0-0.5 1.2]T
pu2=[0.0 0.0 1.2]T (26)
pu3=[2.0 1.0 1.2]T
Their target point is corresponding pd,1,pd,2,pd,3, such as Fig. 4, their coordinate is respectively:
pd,1=[2.2 0.5 1.2]T
pd,2=[- 0.1 0.6 1.2]T (27)
pd,3=[- 1.8-0.6 1.2]T
The starting point of unmanned plane and the straight line line of its respective target point are as shown in phantom in Figure 4, it is seen that this
A little straight lines are intersections.
The parameter of unmanned plane multimachine flight anticollision experiment are as follows:
1) anticollision speed command gain coefficient: k2=0.5
2) it restrains indivisible: ε=0.01
3) it is saturated basic function parameter: rs=0.01
The rate control instruction of i-th frame unmanned plane of the controller output of the anticollision flight of unmanned plane are as follows:
Wherein,
If not having the safeguard measure of anticollision between unmanned plane, unmanned plane will be sent out during toward target point flight
Raw collision.But preventing collision protection algorithm, which is added, to be bumped against in the sky to avoid unmanned plane.
The repulsion that can be all generated by repulsive force caused by other two framves unmanned plane, zone boundary as every frame unmanned plane
Power and target point are to the attraction of unmanned plane, so unmanned plane can not be and every towards target point fully according to straight ahead
When it is every carve unmanned plane position and speed be all in variation, as shown in the track of three unmanned planes in Fig. 5 (a), Fig. 5 (b).
Claims (3)
1. anti-collision control method between a kind of unmanned plane machine that hung down based on Artificial Potential Field Method, it is characterised in that: including as follows
Step: where parameter definition is as follows:
ξi,It is the Filtering position of the i-th frame unmanned plane and l frame unmanned plane, p respectivelyi,It is the i-th frame respectively
Unmanned plane and l frame unmanned plane current location,It is the present speed of the i-th frame unmanned plane,It is controller
The rate control instruction of i-th frame unmanned plane of output,It is p respectivelyi、vi、ξiFirst derivation;It is nobody
The maximum value of the flying speed of machine;It is safe distance,It is the safe distance based on filtering,It is avoidance machine
Dynamic distance, rvIt is the noise error of range measurement;It is the aiming spot of the i-th frame unmanned plane;It is
The alternate position spike of i frame unmanned plane and target point,Be the i-th frame unmanned plane and target point Filtering position it is poor;
It is the alternate position spike of the i-th frame unmanned plane and l frame unmanned plane,It is the filtering of the i-th frame unmanned plane and l frame unmanned plane
Alternate position spike;
Step 1: establishing the basic Controlling model for the unmanned plane that can hang down
Firstly, it is necessary to define the basic Controlling model of unmanned plane;By unmanned aerial vehicle vision be a Mass Model, then the i-th frame nobody
Machine meets following relationship model:
Here lcIt is the parameter of the control performance of unmanned plane, is determined by unmanned plane itself;Since the mobility of unmanned plane has
Limit, therefore the speed command that controller resolves can not be infinitely great;Here following saturation function is devised:
Therefore, the rate control instruction of the i-th frame unmanned plane of final controller output are as follows:
vc,i=sat (vc,i,vm) (3)
Here a concept, referred to as Filtering position are defined;Filtering position be in order to by the current location of unmanned plane and speed with one
A scale is stated out;The second order Controlling model of unmanned plane is indicated with single order form;It is defined as shown in formula (4):
Next it just obtains:
Here it defines:
For convenience, it is defined as follows alternate position spike:
The alternate position spike of corresponding filtering distance are as follows:
Had according to the definition of filtering distance:
Here i, l=1,2,3..., i ≠ l;In order to guarantee safety, certain distance must be all kept between any unmanned plane;If this
A distance is r, for the i-th frame unmanned plane and l frame unmanned plane, then having:
||pi-pl||≥r,i≠l (7)
Step 2: nothing is established according to the safe distance for the unmanned plane that can hang down according to the current position and speed of unmanned plane that can hang down
Man-machine security control model;
In order to avoid the object of unmanned plane and surrounding collides, safe distance r is definedm, safe distance has to be larger than unmanned plane
Physical radius, for any two framves unmanned plane, their filtering distance should meet:
||ξi-ξl||≥2rM (8)
Formula (7) are just met by formula (8);Here rM=rm+rv, rMIt is the safe distance based on filtering distance definition;In order to protect
There are sufficient time and space to carry out motor-driven avoidance, r when demonstrate,proving unmanned plane of the unmanned plane around discoveryaOnly with unmanned plane itself
Power performance is related with the response time;It is required that avoidance maneuvering distance raMust be as big as possible under conditions of tallying with the actual situation,
Here it requires:
ra> 2rM (9)
Step 3: the flight control for the unmanned plane point-to-point that can hang down
The filtering distance of the current position of unmanned plane and target point isThe condition of unmanned plane arrival target point
It is:
In order to guarantee that the i-th frame unmanned plane reaches target point, controller output quantity v is designedc,i, i.e., controller output the i-th frame nobody
The rate control instruction of machine are as follows:
Wherein, k1For the gain coefficient of controller output;
Step 4: relative position and speed based on unmanned plane Yu surrounding other unmanned planes that can hang down of can having hung down, calculating can hang down nothing
The control instruction of man-machine suffered anticollision
If the current location of the i-th frame and l frame unmanned plane is respectivelyWithPresent speed is respectivelyWithThe airbound target point of this two framves unmanned plane is respectivelyWithThe speed received
Degree control instruction, which inputs, is respectivelyWithAccording to the security control model of unmanned plane, their current filters
Wave position isWithThe filtering distance of the current position of unmanned plane and target point isWithOpposite filtering distance between this two framves unmanned plane isAccording to the security control model of unmanned plane,
The distance between all target points of unmanned plane have to be larger than safe distance;
So unmanned plane is in the condition that cannot be collided into the way of respective target point of flying are as follows:
Wherein, t is the time.
2. anti-collision control method between the unmanned plane machine that hung down according to claim 1 based on Artificial Potential Field Method, special
Sign is: three frame unmanned planes and its target point in region, including three frame unmanned plane UAV1, UAV2 and UAV3 and each
Corresponding three target pointsFor the unmanned plane in this region in-flight, need to guarantee nothing
It will not collide between man-machine, and reach respective target point;That is:
Remember Νm,iFor removed in a unmanned plane group of planes middle in region the i-th frame unmanned plane other unmanned planes set;Share three framves without
It is man-machine;Νm,1={ 2,3 }, Νm,2={ 1,3 }, Νm,3={ 1,2 };Provide the speed control of the i-th frame unmanned plane of controller output
System instruction, representation are as follows:
Wherein,For the potential-energy function of Artificial Potential Field, it is defined as follows:
For the convenience of description, noteNotersIt is a minimum;It is a smooth truncation funcation,
It is a smooth saturation function;The smooth basic function of the two second orders introduces
Function be parameter for the operation relation between more simplified formula, therefore in following formula be intermediate variable, itself is without containing
Justice, description merely for convenience;
Wherein, A=-2/ (d1-d2)3, B=3 (d1+d2)/(d1-d2)3, C=-6d1d2/(d1-d2)3, D=d2 2(3d1-d2)/(d1-
d2)3;Function σ (x, d1,d2) partial derivative relative to x are as follows:
Saturation function s (y, rs) are as follows:
Wherein,
y1=y2-sin45°rs
For any rs∈ [0, tan67.5 °/(tan67.5 ° sin45 ° -1)], have,
Wherein, min (y, 1) indicates the smaller value therein of variable y and 1;Function s (y, rs) relative to y partial derivative be formula
(19), it is clear that
k2For the gain coefficient of controller output;There are indivisible ε, so that,
Other than anticollision, it is also necessary to it controls unmanned plane and reaches target point, therefore, the i-th frame unmanned plane of controller output
Rate control instruction:
Unmanned plane stablizes the constraint condition for reaching target point for there are an indivisible ε, so that formula (22) is set up;
3. anti-collision control method between the unmanned plane machine that hung down according to claim 2 based on Artificial Potential Field Method, special
Sign is: further include following steps:
Input: the real time position velocity information of all unmanned planes and corresponding target point in region;
Output: the rate control instruction v of each unmanned planec,i;
4.1: obtaining the real time position velocity information and aiming spot of all unmanned planes in region;
4.2: the anticollision between unmanned plane and surrounding unmanned plane being calculated according to formula (14) and formula (15) and is instructed;
4.3: the control instruction that target point generates is calculated according to formula (11) according to unmanned plane target point position;
4.4: the instruction generated in step 4.2 and step 4.3 being superimposed according to formula (21), carries out the saturated process for protecting direction;
4.5: if meeting constraint condition formula (22), illustrating that unmanned plane arrived target point;Otherwise step 4.2 is continued to execute.
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CN111077910A (en) * | 2020-01-07 | 2020-04-28 | 西安理工大学 | Unmanned aerial vehicle swarm anti-collision system, device and method based on ultraviolet light guidance |
CN110162043B (en) * | 2019-05-17 | 2020-10-09 | 北京航空航天大学 | Cluster task allocation and control method under constraint of simultaneous arrival of multiple target points |
CN112534377A (en) * | 2019-11-29 | 2021-03-19 | 深圳市大疆创新科技有限公司 | Data processing method, unmanned aerial vehicle and computer readable storage medium |
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102591358A (en) * | 2012-03-12 | 2012-07-18 | 北京航空航天大学 | Multi-UAV (unmanned aerial vehicle) dynamic formation control method |
CN107807671A (en) * | 2017-11-27 | 2018-03-16 | 中国人民解放军陆军工程大学 | Unmanned aerial vehicle cluster danger avoiding method |
CN108196583A (en) * | 2017-08-21 | 2018-06-22 | 中国人民解放军陆军工程大学 | Unmanned aerial vehicle cluster control method |
CN108319291A (en) * | 2017-12-13 | 2018-07-24 | 中国人民解放军空军工程大学 | A kind of unmanned plane cognition anti-collision control method based on safety-boundary analysis |
CN108387232A (en) * | 2018-01-30 | 2018-08-10 | 河北科技大学 | The flying object path planning method of evolution algorithm based on Artificial Potential Field |
-
2018
- 2018-12-03 CN CN201811465370.7A patent/CN109557936B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102591358A (en) * | 2012-03-12 | 2012-07-18 | 北京航空航天大学 | Multi-UAV (unmanned aerial vehicle) dynamic formation control method |
CN108196583A (en) * | 2017-08-21 | 2018-06-22 | 中国人民解放军陆军工程大学 | Unmanned aerial vehicle cluster control method |
CN107807671A (en) * | 2017-11-27 | 2018-03-16 | 中国人民解放军陆军工程大学 | Unmanned aerial vehicle cluster danger avoiding method |
CN108319291A (en) * | 2017-12-13 | 2018-07-24 | 中国人民解放军空军工程大学 | A kind of unmanned plane cognition anti-collision control method based on safety-boundary analysis |
CN108387232A (en) * | 2018-01-30 | 2018-08-10 | 河北科技大学 | The flying object path planning method of evolution algorithm based on Artificial Potential Field |
Non-Patent Citations (2)
Title |
---|
JIAN YING LIU: "The Simulation of the UAV Collision Avoidance Based on the Artifical Potential Field Method", 《ADVANCED MATERIAL RESEARCH》 * |
朱旭等: "基于改进人工势场的无人机编队防碰撞控制方法", 《哈尔滨工程大学学报》 * |
Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110162043B (en) * | 2019-05-17 | 2020-10-09 | 北京航空航天大学 | Cluster task allocation and control method under constraint of simultaneous arrival of multiple target points |
CN110515391A (en) * | 2019-08-20 | 2019-11-29 | 西南石油大学 | A kind of three-dimensional barrier-avoiding method of unmanned plane formation based on gradient function |
CN110515391B (en) * | 2019-08-20 | 2022-04-15 | 西南石油大学 | Unmanned aerial vehicle formation three-dimensional obstacle avoidance method based on gradient function |
CN112534377A (en) * | 2019-11-29 | 2021-03-19 | 深圳市大疆创新科技有限公司 | Data processing method, unmanned aerial vehicle and computer readable storage medium |
WO2021102951A1 (en) * | 2019-11-29 | 2021-06-03 | 深圳市大疆创新科技有限公司 | Data processing method, unmanned aerial vehicle, and computer-readable storage medium |
CN111077910A (en) * | 2020-01-07 | 2020-04-28 | 西安理工大学 | Unmanned aerial vehicle swarm anti-collision system, device and method based on ultraviolet light guidance |
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CN113703486A (en) * | 2021-09-06 | 2021-11-26 | 北京航空航天大学 | Unmanned aerial vehicle distributed control method and system |
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