CN112180954A - Unmanned aerial vehicle obstacle avoidance method based on artificial potential field - Google Patents
Unmanned aerial vehicle obstacle avoidance method based on artificial potential field Download PDFInfo
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Abstract
The invention discloses an unmanned aerial vehicle obstacle avoidance method based on an artificial potential field, wherein a gravitational field is arranged at a simulated target position, a repulsive field is arranged at an obstacle position, an unmanned aerial vehicle avoids an obstacle to fly to a target under the action of the gravitational field and the repulsive field, the power required to be provided for the unmanned aerial vehicle can be obtained by resolving the resultant force of the gravitational force and the repulsive force received by the unmanned aerial vehicle, and as the condition that the gravitational force and the repulsive force are mutually offset possibly exists, a transverse obstacle avoidance control force is additionally arranged, so that the adverse effect of a local minimum value on the obstacle avoidance of the unmanned aerial vehicle is avoided, and the unmanned aerial vehicle can safely and timely avoid the obstacle to reach the target position.
Description
Technical Field
The invention relates to an unmanned aerial vehicle obstacle avoidance method, in particular to an unmanned aerial vehicle obstacle avoidance method based on an artificial potential field.
Background
The current obstacle avoidance algorithms are divided into two categories, namely an algorithm of global path planning represented by an a-x algorithm and a local obstacle avoidance algorithm exemplified by an artificial potential field method. The two algorithms have advantages and disadvantages respectively, the A-x algorithm can obtain a global optimal solution so as to avoid the unmanned aerial vehicle from falling into a local optimal solution, but the A-x algorithm needs to obtain information of the whole map in advance and the resolving time of the A-x algorithm is prolonged along with the increase of the map; the artificial potential field method can quickly respond to the position information of the obstacle, has high reliability, does not depend on the prior information of the environment and the shape of the obstacle, is not influenced by the appearance of the obstacle, but falls into local optimum; specifically, the basic principle of the artificial potential field method is to generate two virtual potential fields during flight: gravitational field (gravitational potential energy field), repulsive field (electric potential field). Then, under the combined action of the two potential force fields, different acting forces are generated according to different models of the potential force fields.
The traditional artificial potential field method is to generate a specific search direction according to stress, further plan a path according to a specific step length, and finally perform a track tracking design.
For the reasons, the inventor of the invention makes an in-depth research on the existing unmanned aerial vehicle obstacle avoidance method of the artificial potential field, so as to wait for designing a new obstacle avoidance method capable of solving the problems.
Disclosure of Invention
In order to overcome the problems, the inventor of the invention carries out intensive research and designs an unmanned aerial vehicle obstacle avoidance method based on an artificial potential field, wherein acting force is directly acted on the unmanned aerial vehicle in the method, and the stress condition of the unmanned aerial vehicle is calculated according to the acting force between the potential fields. Due to the direct acting force, a subsequent track tracking mode does not need to be considered, and the speed of the unmanned aerial vehicle at the current moment is considered in a repulsive force field generation mode in the obstacle avoidance stage, so that the requirement on the speed of the unmanned aerial vehicle is low. Only when the unmanned aerial vehicle is in the terminal deceleration range, the speed and the acceleration of the unmanned aerial vehicle can be limited, and the requirement for the unmanned aerial vehicle to arrive is met; the method is mainly used for obstacle avoidance of simple obstacles under the condition of high-speed flight. In addition, because the attractive force and the repulsive force are offset, a transverse obstacle avoidance control force is additionally arranged in the method, so that the adverse effect of the local minimum value on the obstacle avoidance of the unmanned aerial vehicle is avoided, the unmanned aerial vehicle can safely and timely avoid the obstacle and reach the target position, and the method is completed.
Specifically, the invention aims to provide an unmanned aerial vehicle obstacle avoidance method based on an artificial potential field, which comprises the following steps:
and 2, applying power to the unmanned aerial vehicle through the propeller to control the unmanned aerial vehicle to fly to a target position, wherein the power applied to the unmanned aerial vehicle through the propeller is equal to the resultant force of the attractive force, the repulsive force and the transverse obstacle avoidance control force.
Wherein, the power applied to the unmanned aerial vehicle through the screw is as follows (one):
F(X)＝Fatt(X)+Frep(X)+Foff(A)
Wherein F (X) represents power applied to the drone through a propeller,
Fatt(X) represents the gravitational force of the target point acting on the drone,
Frep(X) represents a repulsive force of the obstacle acting on the drone,
Foffindicating the lateral obstacle avoidance control force.
Wherein the attraction F of the target point acting on the unmanned aerial vehicleatt(X) is obtained by the following formula (II):
wherein v represents the current speed of the droneDegree, kvIn order to be a speed feedback factor,
k represents a gravity proportional position gain coefficient,
Xgthe position of the object is indicated and,
x denotes the location where the drone is located,
ρ(X,Xg) Representing the distance between the drone and the target.
Wherein the repulsion force F of the obstacle acting on the unmanned aerial vehiclerep(X) is obtained by the following formulae (three) and (four):
wherein, Frepi(X) denotes a repulsive force of the ith obstacle acting on the drone,
η represents a repulsive force positive proportional displacement gain coefficient,
ρi(X,X0) Indicating the distance between the drone and the ith obstacle
ρ0The maximum distance at which the repulsive force acts,
n represents the total number of obstacles.
Wherein the repulsive force positive proportional displacement gain coefficient η is obtained by the following formula (five):
l represents the minimum distance allowed in the radial direction of the connecting line between the unmanned aerial vehicle and the obstacle;
wherein, the transverse obstacle avoidance control force FoffObtained by the following formula (VI):
d represents the minimum distance allowed by the normal direction of the connecting line of the unmanned aerial vehicle and the obstacle;
Wherein, the transverse obstacle avoidance control force FoffThe unit vector of (a) is obtained by the following formula (seven):
wherein the content of the first and second substances,
representing a vector pointing from the drone to the obstacle,
indicating the speed direction of the drone.
The invention has the advantages that:
(1) according to the unmanned aerial vehicle obstacle avoidance method based on the artificial potential field, the occurrence of the local minimum value can be effectively avoided, and the obstacle avoidance effect under the condition that the speed direction and the obstacle direction are overlapped is improved;
(2) according to the unmanned aerial vehicle obstacle avoidance method based on the artificial potential field, the minimum distance between the unmanned aerial vehicle and the obstacle is ensured by calculating the repulsive force field potential field model of the unmanned aerial vehicle through the energy conversion relation in the repulsive force action field range, and the minimum safe offset force is increased, so that the obstacle avoidance efficiency is further improved, and the safety of the unmanned aerial vehicle is ensured;
drawings
Fig. 1 shows a flow chart of obstacle avoidance control of an unmanned aerial vehicle according to the invention;
fig. 2 shows a schematic diagram of a motion trajectory of an unmanned aerial vehicle obtained in an experimental example of the present invention.
Detailed Description
The invention is explained in more detail below with reference to the figures and examples. The features and advantages of the present invention will become more apparent from the description.
The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
The assumption is that under ideal environment, there is a repulsion field around the obstacle, can repel unmanned aerial vehicle, there is a gravitational field around the target, can attract unmanned aerial vehicle, unmanned aerial vehicle is under the combined action of gravitational field and repulsion field, and assume that unmanned aerial vehicle only receives gravitation and repulsion, then unmanned aerial vehicle chance flight target, and avoid the obstacle position at this in-process, realize perfect obstacle avoidance flight, so in real environment, if can provide the effort that equals with the resultant force of above-mentioned gravitation repulsion for unmanned aerial vehicle in real time, unmanned aerial vehicle also can realize perfect obstacle avoidance flight naturally, based on such theoretical research, carry out unmanned aerial vehicle and keep away barrier method setting.
According to the unmanned aerial vehicle obstacle avoidance method based on the artificial potential field, a gravitational field of a target point is simulated, a repulsive field of an obstacle is simulated, and the control force of the unmanned aerial vehicle is set according to the gravitational force generated by the target point, the repulsive force generated by the obstacle and the additionally provided transverse obstacle avoidance control force, so that the unmanned aerial vehicle can avoid the obstacle while flying to the target position, and the unmanned aerial vehicle is prevented from falling into the predicament of the local minimum value.
Preferably, the method comprises the steps of:
And 2, applying power to the unmanned aerial vehicle through the propeller to control the unmanned aerial vehicle to fly to a target position, wherein the power applied to the unmanned aerial vehicle through the propeller is equal to the resultant force of the gravitational force, the repulsive force and the transverse obstacle avoidance control force.
Specifically, in step 2, the power applied to the drone by the propeller is as described by the following equation (one):
F(X)＝Fatt(X)+Frep(X)+Foff(A)
Wherein F (X) represents power applied to the drone through a propeller,
Fatt(X) represents the gravitational force of the target point acting on the drone,
Frep(X) represents a repulsive force of the obstacle acting on the drone,
Foffindicating the lateral obstacle avoidance control force.
In a preferred embodiment, the attraction force F of the target point on the droneatt(X) is obtained by the following formula (II):
v denotes the current speed of the drone, kvIs a velocity feedback coefficient with a value of kv1.05. Through kvAnd v, the feedback quantity realizes that the unmanned aerial vehicle adjusts the speed of the unmanned aerial vehicle finally reaching the target point to be 0 in the terminal deceleration range.
Wherein k represents a gravity proportional position gain coefficient, and the value of k is 5; ρ (X, X)g)＝||Xg-X||，XgThe position of target is shown, X shows the position at unmanned aerial vehicle place, learns the position at this unmanned aerial vehicle place in real time through the satellite receiver on the unmanned aerial vehicle. RhogThe terminal deceleration distance is expressed, the value of the terminal deceleration distance is related to the speed of the unmanned aerial vehicle according to the target distance, the terminal deceleration distance is set before the unmanned aerial vehicle takes off, and the value is generally 5-100 meters, rho (X, X)g) Representing a distance between the drone and the target;
in a preferred embodiment, the repelling force F of said obstacle acting on the dronerep(X) is obtained by the following formulae (three) and (four):
wherein, Frepi(X) represents the repulsive force of the ith obstacle acting on the unmanned aerial vehicle, eta represents the repulsive force positive proportional displacement gain coefficient, rhoi(X,X0) The distance between the unmanned aerial vehicle and the ith obstacle is represented, and the value of the distance is obtained by real-time detection of a detection device on the unmanned aerial vehicle, wherein the detection device comprises one or more of a radar detector, an infrared induction detector, an ultrasonic detector, a laser distance sensor and a binocular vision detector; rho0The maximum distance representing the effect of the repulsion force, namely the maximum distance of the obstacle influencing the unmanned aerial vehicle, is set according to the size of the no-fly area in the scene, the value is generally 5m, namely, when the aircraft flies to the position within 5m away from the obstacle, the obstacle provides the repulsion force, and when the aircraft flies to the position 5m away from the obstacle, the obstacle does not provide the repulsion force any more. The distance between the unmanned aerial vehicle and the obstacle is the minimum distance between the unmanned aerial vehicle and the obstacle, namely the minimum distance between the outer contour of the unmanned aerial vehicle and the outer contour of the obstacle.
When there are a plurality of obstacles, the total repulsive force acting on the unmanned aerial vehicle is F corresponding to all the obstaclesrepiThe sum of (X). Specifically, as shown in formula (iv):
where N represents the total number of obstacles.
Preferably, the repulsive force positive proportional displacement gain coefficient η is obtained by the following formula (five):
where ρ is0Is the maximum distance for the repulsion force to act, L is a constant and represents the minimum allowable in the radial direction of the connecting line between the unmanned aerial vehicle and the barrierThe preferred value for the distance in this application is 3 in meters.
Preferably, when the position of the obstacle is detected by the detector, the size of the outline of the obstacle is also obtained at the same time, so that the rho corresponding to the obstacle can be calculated0And if the action ranges of the repulsive forces of two adjacent obstacles are overlapped, determining the two obstacles as one obstacle to carry out obstacle avoidance control. The setting can shorten the calculation time, improve the efficiency and avoid the alternation of a plurality of obstacles
In a preferred embodiment, the lateral obstacle avoidance control force FoffObtained by the following formula (VI):
wherein d represents the minimum distance allowed in the normal direction of the connecting line between the unmanned aerial vehicle and the obstacle, and the value is related to the size of the obstacle, preferably 1 in the application and the unit is meter; when F is presentrepWhen (X) is zero, FoffTaking the value to zero, the calculation in equation (six) need not be performed, when FrepWhen the value of (X) is not zero, F is solved by the formula (VI)off；
wherein the content of the first and second substances,
representing a vector pointing from the drone to the obstacle,
indicating the speed direction of the drone. Obtaining a vector perpendicular to the connecting line direction of the unmanned aerial vehicle and the obstacle through cross multiplication between the vectors, so that the unmanned aerial vehicle can effectively avoid the obstacle, and further F is calculated through a normalization methodoffUnit vector
Through setting up above-mentioned horizontal obstacle control power of keeping away can provide horizontal power when unmanned aerial vehicle carries out the obstacle operation of keeping away to avoid local minimum's the condition to appear, through the settlement of application of force time and application of force size, just can satisfy the minimum horizontal obstacle control power of keeping away that keeps away the obstacle requirement for unmanned aerial vehicle provides simultaneously.
In this application, when unmanned aerial vehicle is in the within range that is close to target 5m, through the negative feedback of increase speed, reduce unmanned aerial vehicle's speed to unmanned aerial vehicle can stop at the target location steadily.
Experimental example:
considering that obstacle avoidance of the unmanned aerial vehicle is carried out at a constant height, the obstacle avoidance can be simplified into a 2D model, the unmanned aerial vehicle takes off from a starting point position (0,0), flies to a target position with coordinates of (0,30), and a circular obstacle with the circle center of (0,15) and the radius of 0.3m is arranged in a flight path;
the unmanned aerial vehicle is controlled through the method in the application, and the specific control process is as follows:
by F (X) ═ Fatt(X)+Frep(X)+FoffSolving the power applied to the unmanned aerial vehicle through the propeller in real time, and controlling the unmanned aerial vehicle to fly through the power.
Wherein, Fatt(X) is obtained by the following formula (II):
Frep(X) is obtained by the following formulae (three) and (four):
Foffobtained by the following formula (VI):
the gravitational field proportional position coefficient k is 5, the velocity feedback gain coefficient is 1.05, rho0Is the maximum distance ρ at which the repulsive force acts0The distance between the unmanned aerial vehicle and the obstacle is 5 meters, the minimum distance L in the radial direction of a connecting line between the unmanned aerial vehicle and the obstacle is 3, and the minimum distance d in the normal phase direction of the connecting line between the unmanned aerial vehicle and the obstacle is 1; rhogValue of 5m
Eta and F of repulsive force field coefficient at the position calculated according to real-time feedback speed of the unmanned aerial vehicle in actual unmanned aerial vehicle flight conditionoffFinally, resolving the power F (X) applied to the unmanned aerial vehicle by the propeller in real time;
the calculated control quantity is the acceleration control quantity of the unmanned aerial vehicle, the control quantity converted into the attitude angle of the unmanned aerial vehicle is calculated through the attitude, the control of the unmanned aerial vehicle by the design quantity is finally realized through the attitude control loop of the unmanned aerial vehicle, and the finally obtained flight trajectory of the unmanned aerial vehicle is shown in fig. 2.
According to the experimental example, the method provided by the application can directly transmit the control quantity to the unmanned aerial vehicle, the process of path planning is reduced, the control algorithm is directly solved, and the resolving frequency of the control algorithm is greatly improved. The generation of the algorithm control quantity takes the speed of the unmanned aerial vehicle into consideration, and the obstacle avoidance speed of the unmanned aerial vehicle in the simple obstacle scene is improved.
The present invention has been described above in connection with preferred embodiments, but these embodiments are merely exemplary and merely illustrative. On the basis of the above, the invention can be subjected to various substitutions and modifications, and the substitutions and the modifications are all within the protection scope of the invention.
Claims (7)
1. An unmanned aerial vehicle obstacle avoidance method based on an artificial potential field is characterized by comprising the following steps:
step 1, detecting the position of an obstacle in real time through a detector arranged on an unmanned aerial vehicle;
and 2, applying power to the unmanned aerial vehicle through the propeller to control the unmanned aerial vehicle to fly to a target position, wherein the power applied to the unmanned aerial vehicle through the propeller is equal to the resultant force of the attractive force, the repulsive force and the transverse obstacle avoidance control force.
2. The unmanned aerial vehicle obstacle avoidance method based on the artificial potential field according to claim 1,
the power applied to the drone by the propeller is described by the following equation (one):
F(X)＝Fatt(X)+Frep(X)+Foff(A)
Wherein F (X) represents power applied to the drone through a propeller,
Fatt(X) represents the gravitational force of the target point acting on the drone,
Frep(X) represents a repulsive force of the obstacle acting on the drone,
Foffindicating the lateral obstacle avoidance control force.
3. The unmanned aerial vehicle obstacle avoidance method based on the artificial potential field according to claim 2,
gravity F of target point acting on unmanned aerial vehicleatt(X) is obtained by the following formula (II):
where v represents the current speed of the drone, kvIn order to be a speed feedback factor,
k represents a gravity proportional position gain coefficient,
Xgthe position of the object is indicated and,
x denotes the location where the drone is located,
ρ(X,Xg) Representing the distance between the drone and the target.
4. The unmanned aerial vehicle obstacle avoidance method based on the artificial potential field according to claim 2,
repulsion force F of barrier acting on unmanned aerial vehiclerep(X) is obtained by the following formulae (three) and (four):
wherein, Frepi(X) denotes a repulsive force of the ith obstacle acting on the drone,
η represents a repulsive force positive proportional displacement gain coefficient,
ρi(X,X0) Indicating the distance between the drone and the ith obstacle
ρ0The maximum distance at which the repulsive force acts,
n represents the total number of obstacles.
5. The unmanned aerial vehicle obstacle avoidance method based on the artificial potential field according to claim 4,
the repulsive force positive proportional displacement gain coefficient η is obtained by the following formula (five):
l represents the minimum distance allowed in the radial direction of the connection line between the drone and the obstacle.
6. The unmanned aerial vehicle obstacle avoidance method based on the artificial potential field according to claim 2,
transverse obstacle avoidance control force FoffObtained by the following formula (VI):
d represents the minimum distance allowed by the normal direction of the connecting line of the unmanned aerial vehicle and the obstacle;
7. The unmanned aerial vehicle obstacle avoidance method based on the artificial potential field according to claim 6,
transverse obstacle avoidance control force FoffThe unit vector of (a) is obtained by the following formula (seven):
wherein the content of the first and second substances,
representing a vector pointing from the drone to the obstacle,
indicating the speed direction of the drone.
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