CN109709983B - Logistics unmanned aerial vehicle safety return control method - Google Patents
Logistics unmanned aerial vehicle safety return control method Download PDFInfo
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- CN109709983B CN109709983B CN201910019829.9A CN201910019829A CN109709983B CN 109709983 B CN109709983 B CN 109709983B CN 201910019829 A CN201910019829 A CN 201910019829A CN 109709983 B CN109709983 B CN 109709983B
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Abstract
The invention provides a safe return control method of a logistics unmanned aerial vehicle, which can acquire the current residual electric quantity of the unmanned aerial vehicle, and determines the scheme of returning the unmanned aerial vehicle to a logistics center by comparing the current residual electric quantity with the electric quantity required by various return conditions and combining the calculated maximum load capacity of the unmanned aerial vehicle in the transportation process. The invention replans the unmanned aerial vehicle which has transported the goods, including increasing the load when the unmanned aerial vehicle returns and replans the route, can effectively avoid the electric quantity waste brought by no-load return, greatly improve the utilization efficiency of the battery electric quantity; meanwhile, the rescue work of the logistics unmanned aerial vehicle is considered, and even if the logistics unmanned aerial vehicle cannot finish autonomous return flight under the condition of low electric quantity, the logistics unmanned aerial vehicle still can safely return to a logistics center.
Description
Technical Field
The invention relates to the field of logistics unmanned aerial vehicles, in particular to a safety return control method of a logistics unmanned aerial vehicle.
Background
With the rapid development of the unmanned aerial vehicle technology, the unmanned aerial vehicle is rapidly developed in the civil field and is widely applied to various aspects such as aerial photography, plant protection, data acquisition and the like. Because of its take-off and landing perpendicularly, the flexible operation, traffic convenience, efficiency is higher, does not receive the advantage in the aspects such as natural phenomena influences such as environment, weather, unmanned aerial vehicle is in the commodity circulation field favour.
At present, the logistics unmanned aerial vehicle starts late, and a plurality of problems such as path planning of the unmanned aerial vehicle, endurance of the unmanned aerial vehicle, safety and the like need to be solved urgently in the technology. However, the working characteristics of the logistics unmanned aerial vehicle are long time and large voyage, and therefore, the key for solving the technical problem of the logistics unmanned aerial vehicle is to reduce the energy consumption and improve the utilization efficiency of the energy.
Under the general condition, unmanned aerial vehicle has sent the goods to the destination from logistics center, can directly return voyage, nevertheless after having sent the goods, if battery power is still sufficient, empty load returns voyage can waste a large amount of electric energy.
Disclosure of Invention
The invention provides a safe return control method of a logistics unmanned aerial vehicle, which replans the unmanned aerial vehicle which has transported goods, comprises the steps of increasing the load of the unmanned aerial vehicle when the unmanned aerial vehicle returns and replanning a route, can effectively avoid the electric quantity waste caused by no-load return, and greatly improves the utilization efficiency of the electric quantity of a battery; meanwhile, the rescue work of the logistics unmanned aerial vehicle is considered, and even if the logistics unmanned aerial vehicle cannot finish autonomous return flight under the condition of low electric quantity, the logistics unmanned aerial vehicle still can safely return to a logistics center.
A logistics unmanned aerial vehicle safety return control method comprises the following steps:
step S101, acquiring the current state of the unmanned aerial vehicle when the unmanned aerial vehicle is ready to return to the air after the unmanned aerial vehicle finishes transporting goods, wherein the current state includes information such as the current residual electric quantity P _ ini and the position of the unmanned aerial vehicle;
step S102, detecting whether the current electric quantity of the unmanned aerial vehicle can meet the condition of directly returning to a logistics center from the current position; if yes, executing S103; if not, executing S104;
step S103, according to a set route, directly returning, judging a specific direct returning condition met, and calculating the maximum load capacity of safe returning;
step S104, detecting whether the current residual electric quantity can reach the next destination and then returning to the logistics center under the condition that the unmanned aerial vehicle is not full of goods; if yes, executing S106; if not, executing S105;
step S105, the current residual capacity does not meet the no-load automatic return condition, and an unmanned aerial vehicle is dispatched to carry out rescue;
s106, the unmanned aerial vehicle changes the route and flies to the next destination to continuously load the goods;
step S107, the current position is used as a starting point, the next destination is used as a destination point, the process returns to step S102, and whether the return is direct or the next destination is flown is determined.
Further, in step 102, there are various conditions for the logistics unmanned aerial vehicle to directly return to the logistics center from the current location, including:
(1) when the current residual electric quantity of the unmanned aerial vehicle is larger than the electric quantity required when the unmanned aerial vehicle directly returns to the logistics center in an idle load mode from the current position and is not larger than the electric quantity required when the logistics unmanned aerial vehicle fully returns to the logistics center in the current position, calculating the quantity of cargos which can be loaded when the unmanned aerial vehicle directly returns to the logistics center from the current position through constraint conditions, loading cargos at the current initial position, and then performing return operation;
(2) when the current residual electric quantity of the unmanned aerial vehicle is larger than the electric quantity required when the logistics unmanned aerial vehicle returns to the logistics center in a full-load mode from the current position, and the quantity of goods is sufficient, the full-load requirement of the unmanned aerial vehicle can be met, the unmanned aerial vehicle is filled with goods and then returns to the home;
(3) when the current residual electric quantity of the unmanned aerial vehicle is larger than the electric quantity required by the logistics unmanned aerial vehicle when the logistics unmanned aerial vehicle is fully loaded from the current position and returns to the logistics center, the quantity of the goods is insufficient, the maximum loading quantity of the unmanned aerial vehicle cannot be reached, and the electric quantity required by all goods carrying the current starting position to fly to the next destination and then return to the logistics center is not exceeded, and the direct return operation is executed;
only one of the above-mentioned three kinds of circumstances is satisfied, just can control unmanned aerial vehicle and directly return to the journey.
Further, in step 103, the method for calculating the maximum load capacity of the safe return flight of the unmanned aerial vehicle includes the following steps:
step S1031, setting the load capacity of the current position as a variable W _ cur which is not more than Wmax, and obtaining the corresponding maximum flight speed V _ cur of the unmanned aerial vehicle under the variable W _ cur due to the nonlinear relation between the load of the unmanned aerial vehicle and the maximum flight speed of the unmanned aerial vehicle;
step S1032, the current state of the unmanned aerial vehicle when the unmanned aerial vehicle is ready to return to the flight after the unmanned aerial vehicle finishes transporting the goods is obtained in the step S101, the current position and the logistics center coordinate are obtained, the distance between the current position and the logistics center coordinate is calculated, and then the flight time of the current flight scheme is calculated according to the maximum flying speed of the unmanned aerial vehicle;
the current position is a starting point position S, the coordinate information of the current position can be obtained by a GPS sensor of the unmanned aerial vehicle, and the position of the logistics center, namely an end point position O, can be stored in the unmanned aerial vehicle in advance and can also be obtained in real time; the coordinate position information includes the precision J and latitude W of the point, and is denoted as S (Js, Ws) and O (Jo, Wo);
knowing the radius of the earth as R, and the precision and latitude of the two points, S (Js, Ws), O (Jo, Wo), the calculation of the distance between the two points is as follows:
C＝sin(90-Wo)×sin(90-Ws)×cos(Jo-Js)+cos(90-Wo)×cos(90-Ws)
calculating the distance between the current position (starting point S) and the logistics center (end point O) as distance (SO) according to the calculation formula between the two points;
the time that unmanned aerial vehicle flies back to the terminal position at commodity circulation center at current initial position is required, can be obtained through calculating by the maximum speed V _ cur of unmanned aerial vehicle flight and the distance between the terminal position O at unmanned aerial vehicle current initial position S and commodity circulation center, and unmanned aerial vehicle' S flight time is the distance/flight rate between two coordinate positions, promptly
Step S1033, obtaining an electric quantity consumption rate P _ cur of the unmanned aerial vehicle according to a fitted curve among the load of the unmanned aerial vehicle, the flight speed of the unmanned aerial vehicle and the electric quantity consumption rate of the unmanned aerial vehicle;
step S1031 can obtain the nonlinear relation between the load of the unmanned aerial vehicle and the maximum flying speed of the unmanned aerial vehicle, and according to a fitting curve among the load of the unmanned aerial vehicle, the flying speed of the unmanned aerial vehicle and the power consumption rate of the unmanned aerial vehicle, one variable (for example, the load of the unmanned aerial vehicle) in the fitting curve is obtained, so that the values of the other two variables can be obtained; the fitting curve needs a large number of experiments for the unmanned aerial vehicles to generate, the types of the unmanned aerial vehicles are different, and the curves are also different;
step S1034, calculating the electric quantity required by the current flight scheme according to the electric quantity consumption rate P _ cur and the flight time T _ cur;
the power consumption of the battery and the flight time are in a corresponding relation, when the unmanned aerial vehicle carries goods and flies stably, the power consumption rate of the battery is stable, and the total power consumption P required by the unmanned aerial vehicle to fly back to the logistics center is calculated according to the flight time T _ cur; at this time, the total power consumption P is the unmanned aerial vehicle battery power consumption rate × flight time, that is, P _ cur × T _ cur;
step S1035, calculating the maximum cargo capacity of the unmanned aerial vehicle according to the constraint condition that the required electric quantity of the current flight scheme of the unmanned aerial vehicle does not exceed the current residual electric quantity of the unmanned aerial vehicle;
step S101, acquiring the current state of the unmanned aerial vehicle when the unmanned aerial vehicle is ready to return to the navigation after the unmanned aerial vehicle finishes transporting goods, wherein the current state includes the current residual electric quantity P _ ini of the unmanned aerial vehicle; the constraint condition is that the total power consumption P of the unmanned aerial vehicle cannot exceed the current remaining power P _ ini of the unmanned aerial vehicle, namely
P＝P_cur×T_cur≤P_ini
Substituting into the calculation formula of T _ cur in step S1032 can obtain:
according to the formula, the maximum consumption rate which can be reached by the battery power of the unmanned aerial vehicle can be calculated approximately, then the load information W _ cur of the unmanned aerial vehicle is obtained according to the fitted curve between the load of the unmanned aerial vehicle, the flight speed of the unmanned aerial vehicle and the power consumption rate of the unmanned aerial vehicle, and after the load information of the unmanned aerial vehicle is obtained, the load of the unmanned aerial vehicle loaded with goods can be controlled, and the safe return voyage can be ensured.
Further, in the step 106, the step of calculating the maximum loading capacity that can be loaded when the unmanned aerial vehicle flies to the destination and then returns to the destination includes:
step S1061, acquiring a current position cargo quantity W _ cur1, and setting a destination cargo quantity as a variable W _ cur2, wherein W _ cur1+ W _ cur2 is not more than Wmax (maximum unmanned aerial vehicle load), and the maximum unmanned aerial vehicle flight speed can be represented by the load W due to a nonlinear relation between the unmanned aerial vehicle load and the maximum unmanned aerial vehicle flight speed, so that the corresponding maximum unmanned aerial vehicle flight speed constants V _ cur1 and V _ cur2 of the unmanned aerial vehicle under the constant W _ cur1 and the variable W _ cur1+ W _ cur2 are obtained;
the load capacity of the unmanned aerial vehicle is increased, the maximum flying speed of the unmanned aerial vehicle is correspondingly reduced, the maximum flying speed is similar to an inverse proportional relation, and corresponding curves between the load and the maximum flying speed are greatly different according to different types of the unmanned aerial vehicle, so that a large amount of data collection and experiments are required to be carried out on the load and the flying speed of the unmanned aerial vehicle, and finally utilized data curves are infinitely close to real data;
step S1062, obtaining the current state of the unmanned aerial vehicle when the unmanned aerial vehicle is ready to return to the flight after the goods are transported in the step S101, including obtaining the coordinates of the current position, the destination and the logistics center, calculating the distance between every two coordinates, and then calculating the flight time of the current flight scheme according to the maximum speed of the unmanned aerial vehicle in flight;
the current position is a starting point position S, the coordinate information of which can be known by a GPS sensor of the unmanned aerial vehicle, the position coordinate D of a destination, and the position of a logistics center, namely an end point position O; the coordinate position information comprises the precision J and the latitude W of the point, which are respectively marked as S (Js, Ws), D (Jd, Wd) and O (Jo, Wo), and the distance between the current position (the starting point S) and the destination D is calculated as distance (SD) according to a distance formula between the two points;
the flight times of the drone under this flight scenario include the flight time T _ cur1 for the drone to fly from the current location S to the destination D, and the flight time T _ cur2 for the drone to fly back from the destination to the logistics center;
t _ cur1 may be calculated from the maximum speed V _ cur1 of the drone flight and the distance (sd) between the drone current start position S and destination D:
t _ cur2 may be calculated from the maximum speed V _ cur2 of the drone flight and the distance (do) between the drone destination D and the end position O of the logistics center:
step S1063, obtaining the electric quantity consumption rate of each flight phase of the unmanned aerial vehicle according to a fitted curve among the load of the unmanned aerial vehicle, the flight speed of the unmanned aerial vehicle and the electric quantity consumption rate of the unmanned aerial vehicle, wherein the electric quantity consumption rate of the first flight phase is a constant P _ cur1, and the electric quantity consumption rate of the second flight phase is P _ cur 2;
in the step S1061, the nonlinear relation between the load of the unmanned aerial vehicle and the maximum flying speed of the unmanned aerial vehicle can be known, and one variable in the fitted curve can be known according to the fitted curve among the load of the unmanned aerial vehicle, the flying speed of the unmanned aerial vehicle and the electric quantity consumption rate of the unmanned aerial vehicle, so that the values of the other two variables can be obtained; the fitting curve needs a large number of experiments for the unmanned aerial vehicles to generate, the types of the unmanned aerial vehicles are different, and the curves are also different;
step S1064, calculating the electric quantity required by the current flight scheme according to the electric quantity consumption rate and the flight time;
the power consumption of the battery and the flight time are in a corresponding relation, when the unmanned aerial vehicle carries goods and flies stably, the power consumption rate of the battery is stable, and the total power consumption P required by the unmanned aerial vehicle to fly back to the logistics center is calculated according to the flight time; at this time, the total power consumption P is the unmanned aerial vehicle battery power consumption rate × flight time, that is, P _ cur1 × T _ cur1+ P _ cur2 × T _ cur 2;
step S1065, calculating the maximum cargo capacity of the unmanned aerial vehicle according to the constraint condition that the required electric quantity of the current flight scheme of the unmanned aerial vehicle does not exceed the current residual electric quantity of the unmanned aerial vehicle;
in step S101, the current state of the unmanned aerial vehicle when it is ready to return to the flight after the transportation of the cargo is completed is obtained, the current remaining power P _ ini of the unmanned aerial vehicle is included, the constraint condition is that the total power consumption P of the unmanned aerial vehicle cannot exceed the current remaining power P _ ini of the unmanned aerial vehicle, and the following calculation formula can be obtained:
P＝P_cur1×T_cur1+P_cur2×T_cur2≤P_ini
substituting into the calculation formulas of T _ cur1 and T _ cur2 in step S1062 can obtain
The maximum consumption rate which can be reached by the battery power of the unmanned aerial vehicle can be approximately calculated according to the formula, and then the load information W _ cur2 of the unmanned aerial vehicle is obtained according to a fitting curve among the load of the unmanned aerial vehicle, the flight speed of the unmanned aerial vehicle and the power consumption rate of the unmanned aerial vehicle; after the load information of the unmanned aerial vehicle is obtained, the load of the unmanned aerial vehicle can be controlled, and the safe return flight under the flight scheme is ensured.
The invention has the following beneficial effects: the invention can effectively improve the effective utilization rate of the battery power of the unmanned aerial vehicle, and avoids resource waste caused by no-load flight of the unmanned aerial vehicle; meanwhile, the invention increases the rescue work of the logistics unmanned aerial vehicle under the accident condition, and more comprehensively ensures the safe return of the logistics unmanned aerial vehicle.
Drawings
Fig. 1 is a schematic flow chart of the safe return control method of the logistics unmanned aerial vehicle.
Fig. 2 is a flow chart for calculating the weight that can be loaded by the unmanned aerial vehicle in the safe return control method of the logistics unmanned aerial vehicle.
Fig. 3 is a flowchart for calculating the weight that can be loaded when the unmanned aerial vehicle flies to the destination and then makes a return flight in the method for controlling the safe return flight of the logistics unmanned aerial vehicle.
Fig. 4 is a schematic diagram of a return path of the logistics unmanned aerial vehicle safety return control method.
Detailed Description
The technical scheme of the invention is further explained in detail by combining the drawings in the specification.
A logistics unmanned aerial vehicle safety return control method comprises the following steps:
step S101, acquiring the current state of the unmanned aerial vehicle when the unmanned aerial vehicle is ready to return to the air after the unmanned aerial vehicle finishes transporting goods, wherein the current state includes information such as the current remaining power P _ ini and the position of the unmanned aerial vehicle.
Step S102, detecting whether the current electric quantity of the unmanned aerial vehicle can meet the condition of directly returning to a logistics center from the current position; if yes, executing S103; if not, S104 is executed.
In step 102, there are various conditions for the logistics unmanned aerial vehicle to directly return to the logistics center from the current position, including:
(1) when the current residual capacity of the unmanned aerial vehicle is larger than the electric quantity required when the unmanned aerial vehicle returns to the logistics center from the current position in a direct no-load manner, and is not larger than the electric quantity required when the logistics unmanned aerial vehicle returns to the logistics center from the current position in a full-load manner, the quantity of goods which can be loaded by the unmanned aerial vehicle returning to the logistics center from the current position is calculated through the constraint condition, the goods are loaded at the current initial position, and then the return operation is performed.
(2) When unmanned aerial vehicle's current residual capacity is greater than commodity circulation unmanned aerial vehicle from the current position fully load required electric quantity when returning the commodity circulation center, and goods volume is sufficient, can reach unmanned aerial vehicle's full load demand, then unmanned aerial vehicle fills with the goods, then back sails.
(3) When the current residual capacity of the unmanned aerial vehicle is larger than the electric quantity required when the logistics unmanned aerial vehicle is fully loaded from the current position and returns to the logistics center, the quantity of the goods is insufficient, the maximum loading capacity of the unmanned aerial vehicle cannot be reached, and the electric quantity required when all goods carrying the current starting position fly to the next destination and then return to the logistics center is not exceeded, and the direct return operation is executed.
Only one of the above-mentioned three kinds of circumstances is satisfied, just can control unmanned aerial vehicle and directly return to the journey.
And step S103, directly returning according to a set route, judging the specific direct return condition met, and calculating the maximum load capacity of the safe return.
In step 103, the method for calculating the maximum carrying capacity of the safe return flight of the unmanned aerial vehicle comprises the following steps:
and step S1031, setting the load capacity of the current position as a variable W _ cur which is not more than Wmax, and obtaining the corresponding maximum flying speed V _ cur of the unmanned aerial vehicle under the variable W _ cur due to the nonlinear relation between the load of the unmanned aerial vehicle and the maximum flying speed of the unmanned aerial vehicle.
And S1032, acquiring the current state of the unmanned aerial vehicle ready to return after the unmanned aerial vehicle finishes transporting the goods, including acquiring the current position and the logistics center coordinate, calculating the distance between the current position and the logistics center coordinate, and calculating the flight time of the current flight scheme according to the maximum flying speed of the unmanned aerial vehicle.
The current position is a starting point position S, the coordinate information of the current position can be obtained by a GPS sensor of the unmanned aerial vehicle, and the position of the logistics center, namely an end point position O, can be stored in the unmanned aerial vehicle in advance and can also be obtained in real time; the coordinate position information includes the accuracy J and the latitude W of the point, and is denoted as S (Js, Ws) and O (Jo, Wo), respectively.
Knowing the radius of the earth as R, and the precision and latitude of the two points, S (Js, Ws), O (Jo, Wo), the calculation of the distance between the two points is as follows:
C＝sin(90-Wo)×sin(90-Ws)×cos(Jo-Js)+cos(90-Wo)×cos(90-Ws)
according to the calculation formula between the two points, the distance between the current position (starting point S) and the logistics center (end point O) is calculated to be distance (SO).
The time that unmanned aerial vehicle flies back to the terminal position at commodity circulation center at current initial position is required, can be obtained through calculating by the maximum speed V _ cur of unmanned aerial vehicle flight and the distance between the terminal position O at unmanned aerial vehicle current initial position S and commodity circulation center, and unmanned aerial vehicle' S flight time is the distance/flight rate between two coordinate positions, promptly
Step S1033, obtaining the electric quantity consumption rate P _ cur of the unmanned aerial vehicle according to a fitting curve among the load of the unmanned aerial vehicle, the flight speed of the unmanned aerial vehicle and the electric quantity consumption rate of the unmanned aerial vehicle.
Step S1031 can obtain the nonlinear relation between the load of the unmanned aerial vehicle and the maximum flying speed of the unmanned aerial vehicle, and according to a fitting curve among the load of the unmanned aerial vehicle, the flying speed of the unmanned aerial vehicle and the power consumption rate of the unmanned aerial vehicle, one variable (for example, the load of the unmanned aerial vehicle) in the fitting curve is obtained, so that the values of the other two variables can be obtained; wherein the fitting curve needs unmanned aerial vehicle to carry out a large amount of experiments and generate, and unmanned aerial vehicle's model is different, and the curve also differs.
In step S1034, the electric quantity required by the current flight plan is calculated according to the electric quantity consumption rate P _ cur and the flight time T _ cur.
The power consumption of the battery and the flight time are in a corresponding relation, when the unmanned aerial vehicle carries goods and flies stably, the power consumption rate of the battery is stable, and the total power consumption P required by the unmanned aerial vehicle to fly back to the logistics center is calculated according to the flight time T _ cur; at this time, the total power consumption P is the rate of power consumption of the battery by the flight time, i.e., P _ cur × T _ cur.
Step S1035, calculating the maximum cargo capacity of the drone according to the constraint condition that the required electric quantity of the current flight plan of the drone does not exceed the current remaining electric quantity of the drone.
Step S101, acquiring the current state of the unmanned aerial vehicle when the unmanned aerial vehicle is ready to return to the navigation after the unmanned aerial vehicle finishes transporting goods, wherein the current state includes the current residual electric quantity P _ ini of the unmanned aerial vehicle; the constraint condition is that the total power consumption P of the unmanned aerial vehicle cannot exceed the current remaining power P _ ini of the unmanned aerial vehicle, namely
P＝P_cur×T_cur≤P_ini
Substituting into the calculation formula of T _ cur in step S1032 can obtain:
according to the formula, the maximum consumption rate which can be reached by the battery power of the unmanned aerial vehicle can be calculated approximately, then the load information W _ cur of the unmanned aerial vehicle is obtained according to the fitted curve between the load of the unmanned aerial vehicle, the flight speed of the unmanned aerial vehicle and the power consumption rate of the unmanned aerial vehicle, and after the load information of the unmanned aerial vehicle is obtained, the load of the unmanned aerial vehicle loaded with goods can be controlled, and the safe return voyage can be ensured.
Step S104, detecting whether the current residual electric quantity can reach the next destination and then returning to the logistics center under the condition that the unmanned aerial vehicle is not full of goods; if yes, executing S106; if not, go to S105.
And step S105, the current residual capacity does not meet the no-load automatic return condition, and the unmanned aerial vehicle is dispatched to carry out rescue.
And step S106, the unmanned aerial vehicle changes the route and flies to the next destination to continuously load the goods.
In step 106, the step of calculating the maximum load capacity that can be loaded when the unmanned aerial vehicle flies to the destination and then returns is as follows:
in step S1061, a current location cargo amount W _ cur1 is obtained, and a destination cargo amount is set as a variable W _ cur2, where W _ cur1+ W _ cur2 is not greater than Wmax (maximum unmanned aerial vehicle load), and due to a non-linear relationship between the unmanned aerial vehicle load and the maximum unmanned aerial vehicle flight speed, the maximum unmanned aerial vehicle flight speed may be represented by a load W, and the corresponding maximum unmanned aerial vehicle flight speed constants V _ cur1 and V _ cur2 of the unmanned aerial vehicle under the constant W _ cur1 and the variable W _ cur1+ W _ cur2 are obtained.
The load capacity of the unmanned aerial vehicle is increased, the maximum speed of the unmanned aerial vehicle can be correspondingly reduced, the relationship is similar to an inverse proportion relationship, corresponding curves between the load and the maximum flying speed are also greatly different according to the difference of all types of the unmanned aerial vehicle, a large amount of data collection and experiments are carried out on the load and the flying speed of the unmanned aerial vehicle, and the finally utilized data curve is infinitely close to real data.
And step S1062, acquiring the current state of the unmanned aerial vehicle ready for returning after the cargo is transported by the unmanned aerial vehicle in the step S101, including acquiring coordinates of the current position, the destination and the logistics center, calculating the distance between every two coordinates, and calculating the flight time of the current flight scheme according to the maximum speed of the unmanned aerial vehicle.
The current position is a starting point position S, the coordinate information of the current position can be known by a GPS sensor of the unmanned aerial vehicle, the position coordinate D of a destination and the position of a logistics center are end point positions O; the coordinate position information includes the precision J and the latitude W of the point, which are respectively denoted as S (Js, Ws), D (Jd, Wd), and O (Jo, Wo), and the distance between the current position (starting point S) and the destination D is calculated as distance (sd) according to the distance formula between the two points.
The flight times of the drone under this flight scenario include the flight time T _ cur1 for the drone to fly from the current location S to the destination D, and the flight time T _ cur2 for the drone to fly back from the destination to the logistics center.
T _ cur1 may be calculated from the maximum speed V _ cur1 of the drone flight and the distance (sd) between the drone current start position S and destination D:
t _ cur2 may be calculated from the maximum speed V _ cur2 of the drone flight and the distance (do) between the drone destination D and the end position O of the logistics center:
step S1063, obtaining the electric quantity consumption rate of each flight phase of the unmanned aerial vehicle according to a fitted curve among the load of the unmanned aerial vehicle, the flight speed of the unmanned aerial vehicle and the electric quantity consumption rate of the unmanned aerial vehicle, wherein the electric quantity consumption rate of the first flight phase is a constant P _ cur1, and the electric quantity consumption rate of the second flight phase is P _ cur 2.
In the step S1061, the nonlinear relation between the load of the unmanned aerial vehicle and the maximum flying speed of the unmanned aerial vehicle can be known, and one variable in the fitted curve can be known according to the fitted curve among the load of the unmanned aerial vehicle, the flying speed of the unmanned aerial vehicle and the electric quantity consumption rate of the unmanned aerial vehicle, so that the values of the other two variables can be obtained; wherein the fitting curve needs unmanned aerial vehicle to carry out a large amount of experiments and generate, and unmanned aerial vehicle's model is different, and the curve also differs.
And step S1064, calculating the electric quantity required by the current flight scheme according to the electric quantity consumption rate and the flight time.
The power consumption of the battery and the flight time are in a corresponding relation, when the unmanned aerial vehicle carries goods and flies stably, the power consumption rate of the battery is stable, and the total power consumption P required by the unmanned aerial vehicle to fly back to the logistics center is calculated according to the flight time; at this time, the total power consumption P is the rate of power consumption of the battery by flight time, that is, P _ cur1 × T _ cur1+ P _ cur2 × T _ cur 2.
And step S1065, calculating the maximum cargo capacity of the unmanned aerial vehicle according to the constraint condition that the required electric quantity of the current flight scheme of the unmanned aerial vehicle does not exceed the current residual electric quantity of the unmanned aerial vehicle.
In step S101, the current state of the unmanned aerial vehicle when it is ready to return to the flight after the transportation of the cargo is completed is obtained, the current remaining power P _ ini of the unmanned aerial vehicle is included, the constraint condition is that the total power consumption P of the unmanned aerial vehicle cannot exceed the current remaining power P _ ini of the unmanned aerial vehicle, and the following calculation formula can be obtained:
P＝P_cur1×T_cur1+P_cur2×T_cur2≤P_ini
substituting into the calculation formulas of T _ cur1 and T _ cur2 in step S1062 can obtain
The maximum consumption rate which can be reached by the battery power of the unmanned aerial vehicle can be approximately calculated according to the formula, and then the load information W _ cur2 of the unmanned aerial vehicle is obtained according to a fitting curve among the load of the unmanned aerial vehicle, the flight speed of the unmanned aerial vehicle and the power consumption rate of the unmanned aerial vehicle; after the load information of the unmanned aerial vehicle is obtained, the load of the unmanned aerial vehicle can be controlled, and the safe return flight under the flight scheme is ensured.
Step S107, the current position is used as a starting point, the next destination is used as a destination point, the process returns to step S102, and whether the return is direct or the next destination is flown is determined.
The above description is only a preferred embodiment of the present invention, and the scope of the present invention is not limited to the above embodiment, but equivalent modifications or changes made by those skilled in the art according to the present disclosure should be included in the scope of the present invention as set forth in the appended claims.
Claims (3)
1. A logistics unmanned aerial vehicle safety return control method is characterized by comprising the following steps: the method comprises the following steps:
step S101, acquiring the current state of the unmanned aerial vehicle when the unmanned aerial vehicle is ready to return to the air after the unmanned aerial vehicle finishes transporting goods, wherein the current state includes information such as the current residual electric quantity P _ ini and the position of the unmanned aerial vehicle;
step S102, detecting whether the current electric quantity of the unmanned aerial vehicle can meet the condition of directly returning to a logistics center from the current position; if yes, executing S103; if not, executing S104;
in step S102, there are various conditions for the logistics unmanned aerial vehicle to directly return to the logistics center from the current position, including:
(1) when the current residual electric quantity of the unmanned aerial vehicle is larger than the electric quantity required when the unmanned aerial vehicle directly returns to the logistics center in an idle load mode from the current position and is not larger than the electric quantity required when the logistics unmanned aerial vehicle fully returns to the logistics center in the current position, calculating the quantity of cargos which can be loaded when the unmanned aerial vehicle directly returns to the logistics center from the current position through constraint conditions, loading cargos at the current initial position, and then performing return operation;
(2) when the current residual electric quantity of the unmanned aerial vehicle is larger than the electric quantity required when the logistics unmanned aerial vehicle returns to the logistics center in a full-load mode from the current position, and the quantity of goods is sufficient, the full-load requirement of the unmanned aerial vehicle can be met, the unmanned aerial vehicle is filled with goods and then returns to the home;
(3) when the current residual electric quantity of the unmanned aerial vehicle is larger than the electric quantity required by the logistics unmanned aerial vehicle when the logistics unmanned aerial vehicle is fully loaded from the current position and returns to the logistics center, the quantity of the goods is insufficient, the maximum loading quantity of the unmanned aerial vehicle cannot be reached, and the electric quantity required by all goods carrying the current starting position to fly to the next destination and then return to the logistics center is not exceeded, and the direct return operation is executed;
only if one of the three conditions is met, the unmanned aerial vehicle can be controlled to carry out direct return voyage;
step S103, according to a set route, directly returning, judging a specific direct returning condition met, and calculating the maximum load capacity of safe returning;
step S104, detecting whether the current residual electric quantity can reach the next destination and then returning to the logistics center under the condition that the unmanned aerial vehicle is not full of goods; if yes, executing S106; if not, executing S105;
step S105, the current residual capacity does not meet the no-load automatic return condition, and an unmanned aerial vehicle is dispatched to carry out rescue;
s106, the unmanned aerial vehicle changes the route and flies to the next destination to continuously load the goods;
step S107, the current position is used as a starting point, the next destination is used as a destination point, the process returns to step S102, and whether the return is direct or the next destination is flown is determined.
2. The logistics unmanned aerial vehicle safety return control method of claim 1, wherein: in step S103, the method for calculating the maximum carrying capacity of the safe return flight of the unmanned aerial vehicle includes the following steps:
step S1031, setting the load capacity of the current position as a variable W _ cur which is not more than Wmax, and obtaining the corresponding maximum flight speed V _ cur of the unmanned aerial vehicle under the variable W _ cur due to the nonlinear relation between the load of the unmanned aerial vehicle and the maximum flight speed of the unmanned aerial vehicle;
step S1032, the current state of the unmanned aerial vehicle when the unmanned aerial vehicle is ready to return to the flight after the unmanned aerial vehicle finishes transporting the goods is obtained in the step S101, the current position and the logistics center coordinate are obtained, the distance between the current position and the logistics center coordinate is calculated, and then the flight time of the current flight scheme is calculated according to the maximum flying speed of the unmanned aerial vehicle;
the current position is a starting point position S, the coordinate information of the current position is obtained by a GPS sensor of the unmanned aerial vehicle, and the position of the logistics center is an end point position O; the coordinate position information includes the precision J and latitude W of the point, and is respectively denoted as S (Js, Ws) and O (Jo, Wo);
knowing the radius of the earth as R, and the precision and latitude of the two points, S (Js, Ws), O (Jo, Wo), the calculation of the distance between the two points is as follows:
C＝sin(90-Wo)×sin(90-Ws)×cos(Jo-Js)+cos(90-Wo)×cos(90-Ws)
calculating the distance between the current position, namely the starting point S, and the logistics center, namely the end point O, as distance (SO) according to the calculation formula between the two points;
the time required for the unmanned aerial vehicle to fly back to the end position of the logistics center at the current starting position is obtained by calculating the maximum speed V _ cur of the unmanned aerial vehicle and the distance between the current starting position S of the unmanned aerial vehicle and the end position O of the logistics center, and the flight time of the unmanned aerial vehicle is the distance/flight speed between two coordinate positions, namely the flight time of the unmanned aerial vehicle is the distance/flight speed between the two coordinate positions
Step S1033, obtaining an electric quantity consumption rate P _ cur of the unmanned aerial vehicle according to a fitted curve among the load of the unmanned aerial vehicle, the flight speed of the unmanned aerial vehicle and the electric quantity consumption rate of the unmanned aerial vehicle;
step S1031, knowing the nonlinear relation between the load of the unmanned aerial vehicle and the maximum flying speed of the unmanned aerial vehicle, and knowing one variable in a fitting curve according to the fitting curve among the load of the unmanned aerial vehicle, the flying speed of the unmanned aerial vehicle and the electric quantity consumption rate of the unmanned aerial vehicle, so as to obtain values of the other two variables; wherein the fitted curve requires the drone to perform an experiment to generate;
step S1034, calculating the electric quantity required by the current flight scheme according to the electric quantity consumption rate P _ cur and the flight time T _ cur;
the power consumption of the battery and the flight time are in a corresponding relation, when the unmanned aerial vehicle carries goods and flies stably, the power consumption rate of the battery is stable, and the total power consumption P required by the unmanned aerial vehicle to fly back to the logistics center is calculated according to the flight time T _ cur; at this time, the total power consumption P is the unmanned aerial vehicle battery power consumption rate × flight time, that is, P _ cur × T _ cur;
step S1035, calculating the maximum cargo capacity of the unmanned aerial vehicle according to the constraint condition that the required electric quantity of the current flight scheme of the unmanned aerial vehicle does not exceed the current residual electric quantity of the unmanned aerial vehicle;
step S101, acquiring the current state of the unmanned aerial vehicle when the unmanned aerial vehicle is ready to return to the navigation after the unmanned aerial vehicle finishes transporting goods, wherein the current state includes the current residual electric quantity P _ ini of the unmanned aerial vehicle; the constraint condition is that the total power consumption P of the unmanned aerial vehicle cannot exceed the current remaining power P _ ini of the unmanned aerial vehicle, namely
P＝P_cur×T_cur≤P_ini
Substituting into the calculation formula of T _ cur in step S1032 to obtain:
the maximum consumption rate that unmanned aerial vehicle's battery power can reach is calculated according to the above formula approximation, again according to the fitting curve between unmanned aerial vehicle's load, unmanned aerial vehicle's flying speed, unmanned aerial vehicle's power consumption rate, obtains unmanned aerial vehicle's load information W _ cur, after obtaining unmanned aerial vehicle's load information, the volume of unmanned loading goods to guarantee safe returning voyage.
3. The logistics unmanned aerial vehicle safety return control method of claim 1, wherein: in step S106, the maximum load capacity that can be loaded when the unmanned aerial vehicle flies to the destination and then returns is calculated, and the steps are as follows:
step S1061, acquiring a current position cargo quantity W _ cur1, and setting a destination cargo quantity as a variable W _ cur2, wherein W _ cur1+ W _ cur2 is not more than Wmax, Wmax is the maximum load of the unmanned aerial vehicle, and because of the nonlinear relation between the load of the unmanned aerial vehicle and the maximum speed of the unmanned aerial vehicle, the maximum speed of the unmanned aerial vehicle is represented by the load W, and corresponding maximum flight speed constants V _ cur1 and V _ cur2 of the unmanned aerial vehicle under a constant W _ cur1 and a variable W _ cur1+ W _ cur2 are acquired;
the load capacity of the unmanned aerial vehicle is increased, the maximum flying speed of the unmanned aerial vehicle is correspondingly reduced, and data collection and experiments are carried out on the load capacity and the flying speed of the unmanned aerial vehicle, so that the finally utilized data curve is infinitely close to real data;
step S1062, obtaining the current state of the unmanned aerial vehicle when the unmanned aerial vehicle is ready to return to the flight after the goods are transported in the step S101, including obtaining the coordinates of the current position, the destination and the logistics center, calculating the distance between every two coordinates, and then calculating the flight time of the current flight scheme according to the maximum speed of the unmanned aerial vehicle in flight;
the current position is a starting point position S, the coordinate information of the current position is known by a GPS sensor of the unmanned aerial vehicle, the position coordinate D of a destination is obtained, and the position of a logistics center is an end point position O; the coordinate position information comprises the precision J and the latitude W of the point, which are respectively marked as S (Js, Ws), D (Jd, Wd) and O (Jo, Wo), and the distance between the current position, namely the starting point S and the destination D is calculated as distance (SD) according to a distance formula between the two points;
the flight times of the drone under this flight scenario include the flight time T _ cur1 for the drone to fly from the current location S to the destination D, and the flight time T _ cur2 for the drone to fly back from the destination to the logistics center;
t _ cur1 is calculated from the maximum speed V _ cur1 of the drone flight and the distance (sd) between the drone current start position S and the destination D:
t _ cur2 is calculated from the maximum speed V _ cur2 of the drone flight and the distance (do) between the drone destination D and the end position O of the logistics center:
step S1063, obtaining the electric quantity consumption rate of each flight phase of the unmanned aerial vehicle according to a fitted curve among the load of the unmanned aerial vehicle, the flight speed of the unmanned aerial vehicle and the electric quantity consumption rate of the unmanned aerial vehicle, wherein the electric quantity consumption rate of the first flight phase is a constant P _ cur1, and the electric quantity consumption rate of the second flight phase is P _ cur 2;
step S1061 is used for obtaining the nonlinear relation between the load of the unmanned aerial vehicle and the maximum flying speed of the unmanned aerial vehicle, and obtaining the values of the other two variables by obtaining one variable in a fitting curve according to the fitting curve among the load of the unmanned aerial vehicle, the flying speed of the unmanned aerial vehicle and the electric quantity consumption rate of the unmanned aerial vehicle; wherein the fitted curve requires the drone to perform an experiment to generate;
step S1064, calculating the electric quantity required by the current flight scheme according to the electric quantity consumption rate and the flight time;
the power consumption of the battery and the flight time are in a corresponding relation, when the unmanned aerial vehicle carries goods and flies stably, the power consumption rate of the battery is stable, and the total power consumption P required by the unmanned aerial vehicle to fly back to the logistics center is calculated according to the flight time; at this time, the total power consumption P is the unmanned aerial vehicle battery power consumption rate × flight time, that is, P _ cur1 × T _ cur1+ P _ cur2 × T _ cur 2;
step S1065, calculating the maximum cargo capacity of the unmanned aerial vehicle according to the constraint condition that the required electric quantity of the current flight scheme of the unmanned aerial vehicle does not exceed the current residual electric quantity of the unmanned aerial vehicle;
in step S101, the current state of the unmanned aerial vehicle when it is ready to return to the flight after the transportation of the cargo is completed is obtained, the current state includes the current remaining power P _ ini of the unmanned aerial vehicle, and the constraint condition is that the total power consumption P of the unmanned aerial vehicle cannot exceed the current remaining power P _ ini of the unmanned aerial vehicle, so as to obtain the following calculation formula:
P＝P_cur1×T_cur1+P_cur2×T_cur2≤P_ini
substituting into the calculation formulas of T _ cur1 and T _ cur2 in step S1062 can obtain
Approximately calculating the maximum consumption rate which can be reached by the battery power of the unmanned aerial vehicle according to the formula, and obtaining the load information W _ cur2 of the unmanned aerial vehicle according to a fitting curve among the load of the unmanned aerial vehicle, the flight speed of the unmanned aerial vehicle and the power consumption rate of the unmanned aerial vehicle; after the load information of the unmanned aerial vehicle is obtained, the amount of the unmanned aerial vehicle loaded with cargos is controlled, and the safe return flight under the flight scheme is ensured.
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