An angle positioning-based unmanned aerial vehicle (UAV) pre-precision design and obstacle avoidance control method

Abstract

The application discloses a kind of unmanned aerial vehicle pre-design precision based on angle positioning and obstacle avoidance control method, comprising the following steps: constructing the unmanned aerial vehicle positioning model based on angle, and the target and obstacle are accurately positioned by two observation points auxiliary unmanned aerial vehicle;Combining the unmanned aerial vehicle angle positioning model, construct local obstacle avoidance method, and obtain the kinematics model and angle error of unmanned aerial vehicle;Design unmanned aerial vehicle controller satisfying pre-design precision, and utilize obstacle lyapunov function to convert pre-design precision problem into constraint problem.The application utilizes the positioning model based on angle, and the distance constraint between unmanned aerial vehicle and target and obstacle is converted into angle constraint, reduces the requirement to the perception ability of unmanned aerial vehicle, simultaneously, a kind of obstacle avoidance auxiliary system is designed in conjunction with model, so that unmanned aerial vehicle completes obstacle avoidance without affecting system convergence precision.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of unmanned aerial vehicle control design and application, and particularly relates to a design and obstacle avoidance control method for unmanned aerial vehicle with predetermined accuracy based on angle positioning. BACKGROUND

[0002] The rapid development and wide application of unmanned aerial vehicles (UAVs) are changing the way of work and efficiency in many industries. With the continuous maturity of technology and the improvement of policy and market demand, unmanned aerial vehicles also show great potential in many fields in the future and become an important driving force for innovation and development in various industries. However, there are significant challenges in this process: the choice between cost and performance. The performance of unmanned aerial vehicles largely depends on their ability to perceive the external environment, and the improvement of performance usually means the increase of cost. And the traditional global obstacle avoidance method requires very high external environment perception ability of unmanned aerial vehicles, and blindly reducing the cost may lead to the reduction of the obstacle avoidance ability of unmanned aerial vehicles. Therefore, how to find an ideal balance point between performance and control cost has become a key problem that needs to be further studied.

[0003] In the face of the contradiction between cost and performance, a new model and obstacle avoidance method are needed to enable unmanned aerial vehicles to maintain high performance even in the case of limited information acquisition. And the angle-based positioning model is an extremely efficient and innovative solution, and a local obstacle avoidance method can be designed combined with the angle positioning model, so that unmanned aerial vehicles can still efficiently avoid obstacles even if their perception ability is weak.

[0004] In summary, in view of the defects in the control method of unmanned aerial vehicles and the problems such as complex information processing amount, high cost, and weak obstacle avoidance ability in the traditional method, the application provides a design and obstacle avoidance control method for unmanned aerial vehicles with predetermined accuracy based on angle positioning to solve the above problems. SUMMARY

[0005] The purpose of the application is to provide a design and obstacle avoidance control method for unmanned aerial vehicles with predetermined accuracy based on angle positioning to solve the problems such as complex information processing amount, high cost, and weak obstacle avoidance ability in the prior art.

[0006] To achieve the above purpose, the application adopts the following technical solutions:

[0007] A design and obstacle avoidance control method for unmanned aerial vehicles with predetermined accuracy based on angle positioning, comprising the following steps:

[0008] Step 1, constructing an angle-based unmanned aerial vehicle positioning model, assisting the unmanned aerial vehicle to accurately position the target and obstacles through two observation points;

[0009] Step 2, combine the unmanned aerial vehicle angle positioning model constructed in step 1, construct a local obstacle avoidance system, and obtain the kinematics model and angle error of the unmanned aerial vehicle;

[0010] Step 3, design an unmanned aerial vehicle controller that meets the predetermined accuracy, and convert the predetermined accuracy problem into a constraint problem using an obstacle Lyapunov function.

[0011] The step 1 comprises:

[0012] Step 1.1, establish an unmanned aerial vehicle positioning model with the real-time position of the unmanned aerial vehicle as the origin, set the geographic true north direction as 0°, and the angle range as 0-360°;

[0013] Step 1.2, take two observation points in the unmanned aerial vehicle positioning model to assist the unmanned aerial vehicle in accurate positioning, the positions of the observation points are known, the distances of the two observation points from the unmanned aerial vehicle in the horizontal direction are Ox1 and Ox2, and the distances in the vertical direction are Oy1 and Oy2, that is, the position difference values of the two observation points in the horizontal and vertical directions are known, and the angles formed by the two observation points and the target are θ 1TO and θ 2TO , the angles formed by the two observation points and the unmanned aerial vehicle are θ1 and θ2, and the accurate positions of the target are Tx and Ty, the geometric relationship between these angles and distances is:

[0014]

[0015] At this time, the unmanned aerial vehicle obtains the accurate position of the target by the six quantities:

[0016]

[0017] After knowing the horizontal distance Tx and the vertical distance Ty of the target relative to the unmanned aerial vehicle, the angle θ target of the target relative to the unmanned aerial vehicle is obtained, which is defined as follows:

[0018]

[0019] In the step 2, the steps of constructing a local obstacle avoidance method comprise:

[0020] Step 2.1, the unmanned aerial vehicle first needs to determine whether it needs to avoid obstacles, and uses λ avoid to represent whether the unmanned aerial vehicle needs to avoid obstacles:

[0021]

[0022] Wherein, α safe is used to determine whether the unmanned aerial vehicle has completed obstacle avoidance, α avoid is used to determine whether the unmanned aerial vehicle needs to avoid obstacles; and α safe = |θobstacle -θ safe |,α avoid =|θ obstacle -θ target |,θ obstacle represents the angle between the center of the obstacle and the UAV, θ safe represents the angle between the safe edge of the obstacle and the UAV;

[0023] Step 2.2, when the obstacle avoidance is needed, the direction of the obstacle avoidance also needs to be considered, using D avoid represents the UAV chooses to avoid the obstacle clockwise or counterclockwise:

[0024]

[0025] where D avoid = -1 means to avoid the obstacle counterclockwise, otherwise, to avoid the obstacle clockwise;

[0026] Step 2.3, finally, it is needed to judge whether the UAV has completed the obstacle avoidance, choosing the angle α finish judges whether the UAV has completed the obstacle avoidance, when α safe = α avoid = α finish , it means that the UAV has perfectly avoided the obstacle, then the next obstacle is replaced to continue the judgment;

[0027] Step 2.4, combined with the above steps, the auxiliary obstacle avoidance system ξ is:

[0028]

[0029] where α is a normal number, ξ is the obstacle avoidance auxiliary system, is the first derivative of ξ; and ξ satisfies ξ(0) = 0, e avoid is used to judge whether the obstacle avoidance is needed and the direction of the obstacle avoidance, which is defined as follows:

[0030] e avoid = λ avoid (θ obstacle - θ target - D avoid α finish ) (7)

[0031] λ β is used to adjust the effect of the obstacle avoidance, which is defined as follows:

[0032]

[0033] where β is a normal number.

[0034] In the step 2.3, α finish ≤ 45°.

[0035] In step 2, the dynamic model and angle error of the UAV are as follows:

[0036] The kinematic model of the UAV is as follows:

[0037]

[0038] where, denotes the first derivative of θ1and θ2; u θ1 and u θ2 are the angular velocities of the UAV relative to the two observation points, respectively;

[0039] During the process of the UAV approaching the target, the differences between θ1and θ2and θ 1TO and θ 2TO will be less than or equal to the pre-set accuracy, and considering the obstacle avoidance problem during the UAV's travel, the angle errors e θ1 and e θ2 of the UAV are defined as follows:

[0040]

[0041] In step 3, the UAV controller satisfying the predetermined accuracy is designed, including the following steps:

[0042] Step 3.1, after differentiating equation (10), we get:

[0043]

[0044] Step 3.2, define the time-varying asymmetric obstacle Lyapunov function:

[0045]

[0046] where k a (t), k b (t) represent the predetermined accuracy, respectively; q(e θi ), i = {1, 2} are used to determine whether to select the upper or lower constraint boundary, which are defined as follows:

[0047]

[0048] Step 3.3, after differentiating equation (12), we get:

[0049]

[0050] Step 3.4, the controllers u θ1 and u θ2 of the UAV relative to the two observation points are designed as:

[0051]

[0052] Wherein k is a normal number set. Advantage: the present application realizes accurate positioning of low-cost unmanned aerial vehicle by using angle-based positioning model, and obtains information with less cost. Meanwhile, a local obstacle avoidance auxiliary system is designed, which ensures that the unmanned aerial vehicle completes obstacle avoidance without affecting the convergence accuracy of the system. Finally, an innovative control algorithm enables the unmanned aerial vehicle to reach the target with predetermined accuracy and avoid obstacles.

[0053] The present application is particularly applied to unmanned aerial vehicle control, and by using angle-based positioning mode, the cost and load of the perception device of the unmanned aerial vehicle are reduced, and the control target that the unmanned aerial vehicle can reach the target point with predetermined accuracy and avoid obstacles is mainly realized. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 is a flowchart of a predetermined accuracy design and obstacle avoidance control method of an unmanned aerial vehicle based on angle positioning of the present application;

[0055] Figure 2 is a trajectory diagram of an unmanned aerial vehicle;

[0056] Figure 3 is an angle error diagram;

[0057] Figure 4 is an obstacle avoidance auxiliary system diagram. DETAILED DESCRIPTION

[0058] The present application will be further described below in combination with the drawings.

[0059] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme of the embodiments of the present application will be described clearly and completely below in combination with the drawings of the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0060] The present application will be further described below in combination with the drawings.

[0061] As shown in the drawings, a predetermined accuracy design and obstacle avoidance control method of an unmanned aerial vehicle based on angle positioning, comprising the following steps: Figure 1

[0062] Step 1, constructing an angle-based unmanned aerial vehicle positioning model, assisting the unmanned aerial vehicle to accurately position the target and obstacles through two observation points;

[0063] Specifically comprising the following steps: ​

[0064] Step 1.1, because the model is based on angle positioning, a UAV positioning model is established with the real-time position of the UAV as the origin, and the geographic north direction is set to 0°, and the angle range is 0-360°;

[0065] Step 1.2, two observation points are taken in the UAV positioning model to assist the UAV in accurate positioning. The positions of the observation points are known, and the distances of the two observation points from the UAV in the horizontal direction are Ox1 and Ox2, and the distances in the vertical direction are Oy1 and Oy2, that is, the position difference values of the two observation points in the horizontal and vertical directions are known, and the angles formed by the two observation points and the target are θ 1TO and θ 2TO , the angles formed by the two observation points and the UAV are θ1 and θ2, and the accurate positions of the target are Tx and Ty. The geometric relationship between these angles and distances is:

[0066]

[0067] At this time, the UAV obtains the accurate position of the target by the six quantities:

[0068]

[0069] After learning the horizontal distance Tx and the vertical distance Ty of the target relative to the UAV, the angle θ target of the target relative to the UAV is obtained, which is defined as follows:

[0070]

[0071] Step 2, combined with the UAV angle positioning model constructed in step 1, a local obstacle avoidance method is constructed, and the kinematics model and angle error of the UAV are obtained;

[0072] The steps of constructing the local obstacle avoidance method include:

[0073] Step 2.1, the UAV first needs to determine whether it needs to avoid obstacles, and λ avoid is used to represent whether the UAV needs to avoid obstacles:

[0074]

[0075] Wherein, α safe is used to determine whether the UAV has completed obstacle avoidance, α avoid is used to determine whether the UAV needs to avoid obstacles; α safe = |θ obstacle - θ safe |, α avoid = |θ obstacle - θ target |, θobstacle denotes the angle of the center of the obstacle with the UAV, θ safe denotes the angle of the safety edge of the obstacle with the UAV;

[0076] Step 2.2, when the obstacle avoidance is needed, the direction of the obstacle avoidance is also needed to be considered, using D avoid denotes the UAV chooses to avoid the obstacle clockwise or anticlockwise:

[0077]

[0078] where D avoid = -1 means anticlockwise avoidance, otherwise clockwise avoidance;

[0079] Step 2.3, finally, it is needed to judge whether the UAV has finished the obstacle avoidance, choosing the angle α finish judges whether the UAV has finished the obstacle avoidance, choosing α finish ≤ 45°; when α safe = α avoid = α finish , it means the UAV has perfectly avoided the obstacle, then the next obstacle is chosen to continue the judgment;

[0080] Step 2.4, combining the above steps, the auxiliary obstacle avoidance system ξ is:

[0081]

[0082] where α is a normal number, ξ is the obstacle avoidance auxiliary system, is the first derivative of ξ; and ξ satisfies ξ(0) = 0, e avoid is used to judge whether the obstacle avoidance is needed and the direction of the obstacle avoidance, which is defined as follows:

[0083] e avoid = λ avoid (θ obstacle - θ target - D avoid α finish ) (7)

[0084] λ β is used to adjust the effect of the obstacle avoidance, which is defined as follows:

[0085]

[0086] where β is a normal number.

[0087] The dynamics model of the UAV and the angle error are as follows:

[0088] The kinematics model of the UAV is as follows:

[0089]

[0090] where, denotes the first derivative of θ1 and θ2; u θ1 and u θ2 are the angular velocities of the UAV relative to the two observation points, respectively;

[0091] During the process of the UAV approaching the target, the difference between θ1 and θ2 and θ 1TO and θ 2TO will be less than or equal to the pre-set accuracy, while considering the obstacle avoidance problem during the UAV's travel, the angle errors e θ1 and e θ2 of the UAV are defined as follows:

[0092]

[0093] Step 3, design the UAV controller that meets the pre-set accuracy, and convert the pre-set accuracy problem into a constraint problem by using the barrier Lyapunov function;

[0094] Designing the UAV controller that meets the pre-set accuracy includes the following steps:

[0095] Step 3.1, after derivation of formula (10), we get:

[0096]

[0097] Step 3.2, define the time-varying asymmetric barrier Lyapunov function:

[0098]

[0099] where k a (t), k b (t) represent the pre-set accuracy, respectively; q(e θi ), i={1, 2} are used to determine whether to select the upper constraint boundary or the lower constraint boundary, which are defined as follows:

[0100]

[0101] Step 3.3, after derivation of (12), we get:

[0102]

[0103] Step 3.4, the controllers u θ1 and u θ2 of the UAV relative to the two observation points are designed as:

[0104]

[0105] where k is a pre-set normal number.

[0106] In one embodiment, the positions of the observation point and the target remain fixed, such as Figure 2 As shown, the angles between the two observation points and the initial position of the UAV are θ1 = 0.951 and θ2 = 1.418, respectively, and the initial angles between the observation points and the angles are θ1 = 0.951 and θ2 = 1.418, respectively. 1TO =2.540, θ 2TO =2.554. Its upper and lower angle constraints are k respectively. a (t)=-2e -t +0.02,k b (t)=e -t +0.02.

[0107] Under these initialization conditions, a simulation experiment was conducted, with the UAV's predetermined accuracy range being 0.02 (rad). The remaining parameters were configured as follows: α = 0.5, β = 0.5, k = 0.5. The simulation results are as follows: Figures 2-4 As shown, Figure 2 The drone's trajectory was shown to allow it to navigate through obstacles and reach the target point. Figure 3 The convergence process of the UAV angle error is shown, demonstrating that the error can converge to a predetermined accuracy range and not exceed the constraint limits. Figure 4 The process of the obstacle avoidance assist system was demonstrated, and the error quickly decreased to 0 after passing the obstacle, thus not affecting the convergence accuracy of the UAV.

[0108] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. An angle-based positioning unmanned aerial vehicle (UAV) pre-accuracy design and obstacle avoidance control method, characterized in that: The method comprises the following steps: Step 1, constructing an angle-based unmanned aerial vehicle positioning model, assisting the unmanned aerial vehicle in accurately positioning the target and obstacles through two observation points; Step 2, constructing a local obstacle avoidance method in combination with the unmanned aerial vehicle angle positioning model constructed in step 1, and obtaining a kinematics model and an angle error of the unmanned aerial vehicle; the step of constructing the local obstacle avoidance method comprises: Step 2.1, the drone first needs to determine whether it needs to avoid obstacles, using indicates whether the drone needs to avoid obstacles: （4） wherein, to determine whether the UAV needs to avoid the obstacle, to determine whether the UAV needs to avoid the obstacle; , , denotes an angle between the center of the obstacle and the UAV, denotes an angle between the safe edge of the obstacle and the UAV. Step 2.2, when it is necessary to avoid obstacles, also need to consider the direction of obstacle avoidance, using indicates that the UAV selects clockwise or counterclockwise to avoid obstacles: （5） wherein clockwise to avoid the obstacle, otherwise, counterclockwise is chosen to avoid the obstacle; Step 2.3, the last need to determine whether the UAV obstacle avoidance, select angle Determine whether the UAV obstacle avoidance, when The UAV has completed the perfect avoidance of obstacles, and then replace the next obstacle to continue the determination. Step 2.4, in conjunction with the above steps, the obstacle avoidance system is: （6） wherein, is a constant, is an obstacle avoidance assistance system, is a first derivative; and satisfies , for determining whether obstacle avoidance is needed and the direction of obstacle avoidance, which is defined as follows: （7） Adjustment for obstacle avoidance effect, defined as follows: （8） wherein is a constant; The dynamics model and the angle error of the unmanned aerial vehicle are as follows: The kinematics model of the unmanned aerial vehicle is as follows: （9） wherein, , denotes and a first derivative; and are angular velocities of the drone with respect to the two observation points, respectively. In the process of the UAV approaching the target, and respectively with and The difference will be less than or equal to the pre-set accuracy, while considering the obstacle avoidance problem in the process of the UAV traveling, the angle error of the UAV and defined as follows: （10） Step 3, designing an unmanned aerial vehicle controller satisfying a predetermined accuracy, and converting the predetermined accuracy problem into a constraint problem by using a Lyapunov barrier function; The step of designing the unmanned aerial vehicle controller satisfying the predetermined accuracy comprises the following steps: Step 3.1, for formula After derivation, we get: （11） Step 3.2, defining a time-varying asymmetric barrier-type Lyapunov function: （12） wherein , are expressed as predetermined precisions, respectively; , to determine whether to select the upper or lower constraint bound, which is defined as follows: （13） Step 3.3, for formula Taking the derivative gives: （14） Step 3.

4. Control of the drone relative to the two observation points and is designed to: （15） wherein is a set positive constant.

2. The unmanned aerial vehicle (UAV) precision design and obstacle avoidance control method based on angle positioning according to claim 1, wherein: The step 1 comprises: Step 1.1, establish the UAV positioning model with the real-time position of the UAV as the origin, set the geographic north direction as , and the angle range as ; Step 1.2, two observation points are taken in the UAV positioning model to assist the UAV in accurate positioning, the positions of the observation points are known, the distances of the two observation points from the UAV in the horizontal direction are and , the distances of the two observation points from the UAV in the vertical direction are and , that is, the position difference of the two observation points in the horizontal and vertical directions is and , the angles formed by the two observation points and the target are and , the angles formed by the two observation points and the UAV are and , and the accurate position of the target is and , and the geometric relationship between these angles and distances is: （1） At this time, the unmanned aerial vehicle obtains the accurate position of the target by the six quantities: （2） Upon learning the horizontal distance of the target relative to the UAV and the vertical distance of the target relative to the UAV, the angle of the target relative to the UAV is learned which is defined as follows: （3）。 3. The unmanned aerial vehicle precision design and obstacle avoidance control method based on angle positioning according to claim 1, characterized in that: Said step 2.3 in, .

Images