CN117610887A - A GEO space junk removal mission planning method based on space gas stations - Google Patents

Abstract

The invention discloses a GEO space garbage removal mission planning method based on a space gas station. The method includes obtaining basic information about space robots, space gas stations and space junk; determining the orbital maneuvering strategy for space robots to actively remove space junk from multiple GEOs. The maneuvering strategy includes launching and deploying space robots and space gas stations to GEO, and the space robots pass through the orbit Maneuvering between GEO and the tomb orbit, the space gas station stores enough fuel to provide fuel supplies for space robots to achieve active removal of multiple space debris; finally, the space robot’s GEO space waste active removal mission is planned, And output the optimal solution for the GEO space junk active removal mission of the space robot. The present invention proposes to use a space robot and a space gas station to remove multiple GEO space debris. The space robot does not need to carry a large amount of fuel, which will effectively save precious fuel.

Description

A GEO space debris removal mission planning method based on space refueling station

Technical Field

The present invention belongs to the field of geosynchronous orbit space debris removal, and in particular relates to a GEO space debris removal mission planning method based on a space refueling station.

Background Art

In recent decades, the planning method of active GEO space debris removal mission based on space robots has been further developed and utilized by humans in the space environment. The amount of space debris is increasing, mainly concentrated in the sun-synchronous orbit and the geosynchronous orbit (GEO). If no measures are taken, space debris will exist for a long time. Space debris poses a major threat to the normal and safe operation of on-orbit space systems. Once a collision occurs, it will cause the satellite to be damaged or explode and disintegrate. Furthermore, there may even be a cascade collision effect, which will force human space activities to stop. For example, in February 2009, the collision between the United States' Istar 33 and Russia's Cosmos 2251 destroyed both satellites and added nearly 3,000 pieces of space debris larger than 10 cm.

GEO is an extremely precious orbital resource. Its biggest feature is that its orbital period is consistent with the Earth's rotation period, hence the name geosynchronous orbit. GEO is a must-have for all major space powers, and it has now reached the point of "taking advantage of every opportunity". In addition to satellites that are functioning normally, there is also a large amount of space debris, mainly including abandoned satellites, various types of debris, rocket upper stages, etc. Although the International Space Debris Coordination Committee requires GEO satellites to use their remaining fuel to transfer to a graveyard orbit 200 to 300 km above GEO when their lifespan is about to end, the actual situation is that the space debris in GEO is still increasing. Therefore, the active removal of GEO space debris has become an imminent global issue and is of great significance.

The active removal of GEO space debris and the corresponding mission planning issues are hot issues that need to be resolved urgently. The existing space debris removal methods mainly include "one-to-one" and "one-to-many" modes, that is, one space robot removes one space debris, and one space robot removes multiple space debris. The space robot generally refers to a satellite with capture capabilities. Obviously, the "one-to-one" mode is very inefficient. Although the "one-to-many" mode can improve the removal efficiency to a certain extent, it is still limited by the fuel carrying capacity of the space robot. In addition, the more fuel the space robot carries, the more fuel will be consumed for orbital maneuvers.

Summary of the invention

In order to solve the problems existing in the background technology, the purpose of the present invention is to provide a geosynchronous orbit (GEO) space debris removal mission planning method based on a space refueling station.

The technical solution adopted by the present invention is as follows, comprising the following steps:

Step S1, obtaining basic information of a space robot, a space refueling station, and a plurality of space debris to be removed;

The basic information includes orbital elements and masses;

Step S2: designing an orbital maneuvering method for the space robot to actively remove multiple GEO space debris;

The orbital maneuvering method of the space robot is specifically as follows: at the initial moment of the mission, the space robot and the space refueling station are launched and deployed to GEO, the space robot travels back and forth between the GEO space debris and the space refueling station through orbital maneuvers, the space robot obtains fuel supplies at the space refueling station, captures space debris in the GEO orbit, and transfers to the graveyard orbit to release the space debris; after the cleaning mission is completed, the space robot returns to the space refueling station.

Step S3: Plan the space robot's GEO space debris active removal mission and output the optimal solution for the space robot's GEO space debris active removal mission.

In step S2, the orbital maneuvering mode of the space robot is as follows:

Step S2.1: at the initial moment of the mission, launch and deploy the space robot and the space refueling station to the initial GEO;

Step S2.2, adjusting the orbital plane and coplanar phase of the space robot so that the orbital plane and phase of the space robot are consistent with those of the space debris to be removed; then using the space robot to capture the space debris on GEO, after capturing the space debris, the space robot transfers from GEO to the graveyard orbit through double-pulse Hohmann transfer, and releases the space debris on the graveyard orbit;

This completes the first active removal mission of space debris to be removed;

Step S2.3: After releasing the space junk, determine the fuel reserve of the space robot:

If the remaining fuel of the space robot is greater than the fuel threshold, repeat step S2.2 to release the next space junk on the graveyard orbit;

Otherwise, the orbital plane of the space robot is adjusted and the coplanar phase is adjusted so that the orbital plane and phase of the space robot are consistent with those of the space refueling station; then the space robot is refueled through the space refueling station; after the refueling is completed, step S2.2 is repeated to release the next space junk on the graveyard orbit;

Step S2.4 and step S2.3 constitute a complete active space debris removal mission, and the active space debris removal mission is repeated multiple times to achieve active removal of multiple space debris;

Step S2.5: After all space debris active removal tasks are completed, the space robot returns to the space refueling station.

The step S3 is specifically as follows:

Step 3.1, define the space debris removal order X and decision variables S:

X＝[x ₁ ,x ₂ ,..,x _j ,..,x _n ]

S＝[s ₁ ,s ₂ ,..,s _j ,..,s _n ]

s _j ∈{0,1}

Where _xj is the number of the jth space junk removed, j is the removal sequence of the space junk, and n is the total number of space junk removed; _sj is the decision of whether the space robot returns to the space refueling station for refueling after removing the jth space junk, _sj = 0 means continuing to remove the next space junk, _sj = 1 means returning to the space refueling station for refueling, and continuing to remove the next target after refueling;

Step 3.2, obtain the total mass expression of fuel consumed by the space robot for orbital maneuvers;

Step 3.3: Optimize the design of the clearing path of the space robot based on the ant colony algorithm:

Step 3.3.1. First, construct the set P of all GEO space debris to be removed:

P＝{1,2,...,N}

Where N is the total amount of space debris;

Step 3.3.2: Define the path R of ant k in the ant colony algorithm according to the clearing order X and the decision variable S, and use the path as the clearing path R of the space robot:

R＝[Ν+1, x ₁ , y ₁ , x ₂ , y ₂ ,..,x _j ,y _j ,..,x _n ,y _n ]

Wherein, N+1 is the number of the space refueling station; _yj represents the decision number of whether the space robot returns to the space refueling station for resupply after clearing the jth space junk. When _sj =0, _yj is empty (i.e., the number of the space refueling station is not added to the last digit of _xj , and no operation is performed); when _sj =1, _yj takes N+1 (i.e., the number of the space refueling station is added to the last digit of _xj );

Step 3.3.3, define the tabu list _tabuk of the ant colony algorithm and the set of space junk/gas stations allowed to be selected _allowedk ; at the initial moment of the mission, the tabu list at the beginning of the ant colony algorithm is Every time a piece of space junk is cleared, the number of the space junk is recorded in the taboo list _tabuk ;

Step 3.3.4, initialize the initial parameters of the ant colony algorithm, including pheromones and heuristic information;

Step 3.3.5: Based on the pheromone and heuristic information, obtain the probability of ant k moving from the current path number p to the next path number q The path number q is selected from the allowed space junk/gas station set allowed _k ;

Step 3.3.5: Make all ants follow the selection probability of the ant colony algorithm Each path is searched separately, and the path with the least total fuel mass M _fuel is selected as the optimal path L _best of the current cycle;

Step 3.3.6, update the pheromone between two path numbers according to the optimal path L _best ;

Step 3.3.7, repeat steps 3.3.5 to 3.3.6 for iteration until the ant colony algorithm reaches the maximum number of iterations, and select the path with the least total fuel mass Mfuel among all paths as the final clearing path of the space robot, and obtain the corresponding total fuel mass at the same time.

Step 3.4: Output the optimal solution

The optimal solution includes the final clearing path R of the space robot, the decision variable S of whether to return to the space refueling station for resupply, the speed increment of the space robot's orbital maneuvers, and the mass of fuel carried each time it departs from the space refueling station.

The method for adjusting the orbital plane of the space robot in step 2 so that the orbital plane of the space robot and the space junk to be cleared/space gas station are consistent is specifically:

The expression for adjusting the orbital plane angle of the space robot is as follows:

cosδ＝sini _robot sini _junk cos(Ω _robot -Ω _junk )+cosi _robot cosi _junk

Wherein, δ is the angle between the space robot and the orbital plane of the space junk/space refueling station; i _robot is the orbital inclination of the space robot; i _junk is the orbital inclination of the space junk/space refueling station to be removed; Ω _robot is the right ascension of the ascending node of the space robot; Ω _junk is the right ascension of the ascending node of the space junk/space refueling station to be removed;

The pulse velocity increment required for the maneuver of the space robot is determined according to the orbital plane angle. The pulse velocity increment Δv required for the space robot flying in GEO to adjust the orbital plane angle δ is:

Among them, v _GEO is the flight speed of the space robot in GEO.

The total velocity increment Δv _h of the double-pulse Hohmann transfer in step S2.2 is expressed as:

Δv _h ＝|v _e1 -v _geo |+|v _grave -v _e2 |

a _t = (r _geo + r _grave )/2

r _grave = r _geo +300

Wherein, _ve1 is the flight speed of the space robot at the perigee of the elliptical transfer orbit; _ve2 is the flight speed of the space robot at the apogee of the elliptical transfer orbit; _vgeo is the flight speed of the space robot in GEO; _vgrave is the flight speed of the space robot in the grave orbit; _rgeo is the radius of GEO; _rgrave is the radius of the grave orbit; _at is the major semi-axis of the elliptical transfer orbit; μ is the earth's gravitational constant;

The step 3.2 is specifically as follows:

Step 3.2.1. First, obtain the amount of space debris Q _g that the space robot needs to remove after departing from the space refueling station for the gth time:

Q _g = Sa'(g+1)-Sa'(g)

Sa＝[sa ₁ ,sa ₂ ,..,sa _h ,..,sa _G ]

Sa'＝[0,sa ₁ ,sa ₂ ,..,sa _h ,..,sa _G ]

Among them, sa _h represents the position of the hth element "1" in the decision variable S; G represents the number of times the space robot is recharged at the space refueling station;

Step 3.2.2, then obtain the remaining mass after the space robot clears Q _g pieces of space debris

in, is the pulse velocity increment required for the space robot to adjust the orbital plane after clearing Q _g pieces of space debris and returning to the space refueling station after starting from the space refueling station for the gth time; m _dry is the structural mass of the space robot; I _sp is the engine specific impulse, and g ₀ is the earth's gravitational acceleration;

Step 3.2.3: Next, according to the remaining mass The total mass m _g,0 at the g-th departure from the space refueling station is iteratively calculated according to the following formula:

Among them, _mg,j is the remaining mass of the space robot after it departs from the space refueling station for the gth time and clears the jth space debris; M _g,j is the mass of the jth space debris; Δv _g,j is the pulse velocity increment required for adjusting the orbital plane angle for the jth time; _mg,0 is the total mass of the space robot when it departs from the space refueling station for the gth time; in this iterative calculation, the initial value of j is Q _g , and j is reduced by 1 after each iteration. When the value of j is 1, the iterative calculation ends and finally mg _,0 is obtained;

Step 3.2.4. Finally, according to the total mass _mg,0 of the space robot each time it departs from the space refueling station, the total mass of fuel consumed by the space robot for orbital maneuvers Mfuel is obtained according to the following formula:

mfuel _g = m _g,0 - m _dry

Among them, G is the number of times the space robot is refueled at the space refueling station, and G is the number of elements "1" in the decision variable S; mfuel _g is the mass of fuel carried by the space robot when it departs from the space refueling station for the gth time.

In step 3.3.3, the set of space junk/gas stations allowed _k is obtained by processing as follows:

If the number of elements in the current tabu list tabu _k is n, then allowed _k = {N+1};

If the number of elements in the current taboo list tabu _k is less than n, and the space robot starts from the space gas station, then allowed _k = {P-tabu _k }

If the number of elements in the current taboo list _tabuk is less than n, and the space robot has not departed from the space refueling station, then allowed _k = {N+1, P-tabu _k }.

The step 3.3.4 is specifically as follows:

At the beginning of the ant colony algorithm, the pheromone between any two path numbers is initialized to τ _max , and the interval range of the pheromone during the iteration is set to [τ _min ,τ _max ]:

Among them, τ _max is the upper limit of the pheromone between two path numbers; τ _min is the lower limit of the pheromone between two path numbers; ρ is the volatility coefficient of the pheromone; Mfuel _best is the total mass of fuel corresponding to the optimal path of the current cycle; γ is a given design parameter.

In step 3.3.5, select the probability According to the following formula:

in, represents the selection probability of ant k moving from the current number p to the next number q; [τ _pq ] is the pheromone between path number p and path number q; [η _pq ] is the heuristic information between path number p and path number q; α is the pheromone importance factor, β is the heuristic information importance factor; l is an element in the allowed _k set; Δm _pq is the fuel consumption required for the space robot to change track from path number p to path number q.

The step 3.3.6 is specifically as follows:

When all ants complete a cycle, the pheromone update formula is as follows:

Among them, [τ _pq ]' is the pheromone between the path number p and the path number q after the update; [τ _pq ] is the pheromone between the path number p and the path number q before the update; τ ₁ is the pheromone replacement value; Mfuel _best is the fuel consumption corresponding to the current cycle optimal path L _best .

The present invention proposes a new active removal method for GEO space debris, that is, using a space robot and a space refueling station to complete the active removal of multiple GEO space debris, and on this basis, designs a task planning method for active removal of GEO space debris. The space robot has the ability of orbital maneuvering and capturing, and travels back and forth between GEO and the graveyard orbit, capturing space debris in GEO, and releasing space debris in the graveyard orbit. The space refueling station stores enough fuel to provide fuel replenishment for the space robot. The space robot has the ability to receive fuel replenishment, and the upper limit of the fuel mass that can be carried is C. Since the fuel consumption of the space robot's orbital maneuvering is related to its own mass, the smaller the mass, the less fuel consumption. Therefore, based on the active removal method of the space robot and the space refueling station, the space robot does not need to carry a large amount of fuel, which will effectively save precious fuel.

The mission scenario of the present invention is: launching and deploying a space robot and a space refueling station to GEO, with the goal of transferring multiple GEO space debris with different orbital inclinations, ascending node right ascensions and geographic longitudes to the grave orbit, and the optimization goal is to consume the least fuel for orbital maneuvers of the space robot. In the present invention, the grave orbit is a circular orbit coplanar with the GEO orbit where the space debris is located, and the orbital altitude is 300km higher than GEO. The steps for active removal of GEO space debris based on the space robot and the space refueling station include: 1. Deploy the space robot and the space refueling station to GEO, and their orbital roots are the same; 2. The space robot leaves the space refueling station and maneuvers to the vicinity of the space debris; 3. Capture the space debris, transfer the space debris to the grave orbit and release it; 4. Return to the space refueling station for fuel refueling or continue to remove the next target. After the mission is completed, the space robot returns to the space refueling station. The mission planning problem of active removal of GEO space debris based on space robots and space refueling stations mainly solves the following three sub-problems: first, optimize and determine which space debris the space robot removes, and select n (n≤N) from N space debris; second, optimize the order in which the space robot removes GEO space debris; third, determine whether the space robot returns to the space refueling station for resupply after removing a piece of space debris; fourth, determine the pulse speed of the space robot's orbital maneuvers and the mass of fuel carried each time it departs from the space refueling station.

Compared with the prior art, the present invention has the following beneficial effects:

1. The present invention proposes to use a space robot and a space refueling station to actively remove multiple GEO space debris, which has the advantages of high removal efficiency and low fuel consumption.

2. The present invention proposes to use the clearing order X and the decision variable S to represent the task planning problem. Instead of directly optimizing X and S, an ant colony algorithm is designed to construct a path, which can quickly obtain the global optimal solution.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1 is a flow chart of GEO space debris removal;

Figure 2 is a schematic diagram of a space robot adjusting the orbital plane;

FIG3 is a schematic diagram of a space robot Hohmann transfer;

Figure 4 is a diagram of the ant colony algorithm;

Figure 5 is a diagram of the ant colony algorithm ant construction solution;

Figure 6 is a curve diagram of the ant colony algorithm optimization process;

Figure 7 is an optimal path diagram for the space robot;

Figure 8 is a comparison chart of the results of the ant colony algorithm, the genetic algorithm, and the simulated annealing algorithm.

DETAILED DESCRIPTION

The present invention is described in detail below in conjunction with specific implementation cases. The following implementation cases will help those skilled in the art to further understand the present invention, but will not limit the present invention in any form.

The method of the present invention comprises the following steps:

Step S1, obtaining basic information of a space robot, a space refueling station and a plurality of space debris to be removed; the basic information includes the number of orbital elements and mass;

In a specific implementation, the basic information obtained in step S1 includes the initial orbital elements of the space robot and the space refueling station; the structural mass and fuel carrying capacity of the space robot; and the orbital elements and mass of multiple GEO space debris. The GEO orbital elements include the semi-major axis, eccentricity, orbital inclination, right ascension of the ascending node, and geographic longitude. It is known that the semi-major axis of the orbit of all objects running on GEO is 42164km and the eccentricity is 0, so only the mass, orbital inclination, right ascension of the ascending node, and geographic longitude of the space debris need to be provided. The definition of orbital elements is common knowledge in the field.

Step S2: Designing an orbital maneuvering method for the space robot to actively remove multiple GEO space debris, as shown in FIG1 ;

The specific orbital maneuvering method of the space robot is as follows: at the initial moment of the mission, the space robot and the space refueling station are launched and deployed to GEO. The space robot travels back and forth between the GEO space debris and the space refueling station through orbital maneuvers. The space robot obtains fuel supplies at the space refueling station, captures space debris in the GEO orbit, and transfers to the graveyard orbit to release the space debris. After the cleaning mission is completed, the space robot returns to the space refueling station.

In the specific implementation, at the beginning of the mission, the space robot and the space refueling station are launched and deployed to the initial GEO; the space robot is used to capture the first space junk in the GEO orbit, and then the space robot orbitally maneuvers to the graveyard orbit and releases the first space junk in the graveyard orbit, thus completing the active removal of the first space junk; then the space robot returns to the space refueling station for fuel replenishment or directly returns to GEO to capture the next space junk, and after completing the capture, it orbitally maneuvers again to the graveyard orbit to release the space junk, thus completing the active removal of the next space junk; and so on, thereby achieving the active removal of multiple space junk. The orbital maneuvers include adjusting the orbital plane, Hohmann transfer, and coplanar phase modulation.

Step S3: Plan the space robot's GEO space debris active removal mission and output the optimal solution for the space robot's GEO space debris active removal mission.

In step S2, the orbital maneuvering mode of the space robot is as follows:

Step S2.1: at the initial moment of the mission, launch and deploy the space robot and the space refueling station to the initial GEO;

Step S2.2, adjusting the orbital plane and coplanar phase of the space robot so that the orbital plane and phase of the space robot are consistent with those of the space debris to be removed; then using the space robot to capture the space debris on GEO, after capturing the space debris, the space robot transfers from GEO to the graveyard orbit through double-pulse Hohmann transfer, and releases the space debris on the graveyard orbit;

This completes the first active removal mission of space debris to be removed;

Step S2.3: After releasing the space junk, determine the fuel reserve of the space robot:

If the remaining fuel of the space robot is greater than the fuel threshold, repeat step S2.2 to release the next space junk on the graveyard orbit;

Otherwise, the orbital plane of the space robot is adjusted and the coplanar phase is adjusted so that the orbital plane and phase of the space robot are consistent with those of the space refueling station; then the space robot is refueled through the space refueling station; after the refueling is completed, step S2.2 is repeated to release the next space junk on the graveyard orbit;

Step S2.4 and step S2.3 constitute a complete active space debris removal mission, and the active space debris removal mission is repeated multiple times to achieve active removal of multiple space debris;

Step S2.5: After all space debris active removal tasks are completed, the space robot returns to the space refueling station.

In the specific implementation, step S3 is specifically as follows:

Step 3.1, define the space debris removal order X and decision variables S:

X＝[x ₁ ,x ₂ ,..,x _j ,..,x _n ]

S＝[s ₁ ,s ₂ ,..,s _j ,..,s _n ]

s _j ∈{0,1}

Where _xj is the number of the jth space junk removed, j is the removal sequence of the space junk, and n is the total number of space junk removed; _sj is the decision of whether the space robot returns to the space refueling station for refueling after removing the jth space junk, _sj = 0 means continuing to remove the next space junk, _sj = 1 means returning to the space refueling station for refueling, and continuing to remove the next target after refueling;

In the specific implementation, the optimization variables are first designed, and the optimization variables are the order of clearing space junk; among them, x _j ∈ {1,2,…,N}, s _j ∈ {0,1}, x _i ≠x _j (i,j∈{1,2,…,n},i≠j), that is, the same space junk number will not appear repeatedly in the clearing order X; for example, N＝8, n＝5, X＝[4,7,1,5,8], S＝[0,1,0,0,1] means that there are 8 space junk targets in total, and 5 of them are selected for clearing, and the space junk numbered #4, #7, #1, #5, and #8 are cleared in turn. After clearing the #7 space junk, the space robot returns to the space refueling station for resupply, and then clears the #1 space junk. After clearing the #8 space junk, it returns to the space refueling station, and the entire mission is completed. Let R represent the clearing path of the space robot, and N+1 represent the initial GEO orbit where the space refueling station is located. Since the space robot starts from the space refueling station and returns to the space refueling station after completing the clearing mission, the clearing order in the above example corresponds to R=[9,4,7,9,1,5,8,9].

Step 3.2, obtain the total mass expression of fuel consumed by the space robot for orbital maneuvers;

Step 3.3: Optimize the design of the clearing path of the space robot based on the ant colony algorithm:

Step 3.3.1. First, construct the set P of all GEO space debris to be removed:

P＝{1,2,…,N}

Where N is the total amount of space debris;

Step 3.3.2: Define the path R of ant k in the ant colony algorithm according to the clearing order X and the decision variable S, and use the path as the clearing path R of the space robot:

R＝[Ν+1, x ₁ , y ₁ , x ₂ , y ₂ ,..,x _j ,y _j ,..,x _n ,y _n ]

Wherein, N+1 is the number of the space refueling station; _yj represents the decision number of whether the space robot returns to the space refueling station for resupply after clearing the jth space junk. When _sj =0, _yj is empty (i.e., the number of the space refueling station is not added to the last digit of _xj , and no operation is performed); when _sj =1, _yj takes N+1 (i.e., the number of the space refueling station is added to the last digit of _xj );

Step 3.3.3, define the tabu list _tabuk of the ant colony algorithm and the set of space junk/gas stations allowed to be selected _allowedk ; at the initial moment of the mission, the tabu list at the beginning of the ant colony algorithm is Every time a piece of space junk is cleared, the number of the space junk is recorded in the taboo list _tabuk ;

Step 3.3.4, initialize the initial parameters of the ant colony algorithm, including pheromones and heuristic information;

Step 3.3.5: Based on the pheromone and heuristic information, obtain the probability of ant k moving from the current path number p to the next path number q The path number q is selected from the allowed set of space junk/gas stations allowed _k ;

Step 3.3.5: Make all ants follow the selection probability of the ant colony algorithm Each path is searched separately, and the path with the least total fuel mass M _fuel is selected as the optimal path L _best of the current cycle;

Step 3.3.6, update the pheromone between two path numbers according to the optimal path L _best ;

Step 3.3.7, repeat steps 3.3.5 to 3.3.6 for iteration until the ant colony algorithm reaches the maximum number of iterations, and select the path with the least total fuel mass Mfuel among all paths as the final clearing path of the space robot, and obtain the corresponding total fuel mass at the same time.

Step 3.4: Output the optimal solution

The optimal solution includes the final clearing path R of the space robot, the decision variable S of whether to return to the space refueling station for resupply, the velocity increment of the space robot's orbital maneuvers, and the mass of fuel carried each time it departs from the space refueling station.

In step 2, the method for adjusting the orbital plane of the space robot so that the orbital plane of the space robot and the space junk/space gas station to be removed is specifically as follows:

The expression for adjusting the orbital plane angle of the space robot is as follows:

cosδ＝sini _robot sini _junk cos(Ω _robot -Ω _junk )+cosi _robot cosi _junk

Wherein, δ is the angle between the space robot and the orbital plane of the space junk/space refueling station; i _robot is the orbital inclination of the space robot; i _junk is the orbital inclination of the space junk/space refueling station to be removed; Ω _robot is the right ascension of the ascending node of the space robot; Ω _junk is the right ascension of the ascending node of the space junk/space refueling station to be removed;

The pulse velocity increment required for the maneuver of the space robot is determined according to the orbital plane angle. The pulse velocity increment Δv required for the space robot flying in GEO to adjust the orbital plane angle δ is:

Among them, v _GEO is the flight speed of the space robot in GEO.

When the space robot passes through the intersection of the two orbits, a velocity pulse is applied to adjust the orbital inclination and the right ascension of the ascending node at the same time, as shown in Figure 2, where point A is the intersection of the two orbits. It is known that the orbital inclination and right ascension of the ascending node of the space junk/space gas station are i _junk and Ω _junk , respectively, and the orbital inclination and right ascension of the ascending node of the space robot are i _robot and Ω _robot , respectively, and the angle between the two orbital planes is δ, from which the pulse velocity increment required for the space robot to adjust the orbital plane can be determined.

In step 2, the method of coplanar phasing the space robot so that the phase of the space robot is consistent with that of the space junk/space gas station to be removed is as follows: if the space robot is located in GEO, the space robot uses double pulse phasing to make the phase of the space robot the same as that of the space junk/space gas station. Since their orbital parameters are exactly the same, the space robot can approach the space junk/space gas station. Compared with adjusting the orbital plane, the fuel consumption of coplanar phasing can be ignored. If the space robot is located in a tomb orbit, the different characteristics of the tomb orbit and the GEO period can be used for phasing, and a certain period of time can be waited in the tomb orbit so that when the Hohmann transfer is to GEO, the geographical longitude of the space robot and the space junk is exactly the same.

The total velocity increment Δv _h of the double-pulse Hohmann transfer in step S2.2 is expressed as:

Δv _h ＝|v _e1 -v _geo |+|v _grave -v _e2 |

a _t = (r _geo + r _grave )/2

r _grave = r _geo +300

Wherein, _ve1 is the flight speed of the space robot at the perigee of the elliptical transfer orbit; _ve2 is the flight speed of the space robot at the apogee of the elliptical transfer orbit; _vgeo is the flight speed of the space robot in GEO; _vgrave is the flight speed of the space robot in the grave orbit; _rgeo is the radius of GEO; _rgrave is the radius of the grave orbit; _at is the major semi-axis of the elliptical transfer orbit; μ is the earth's gravitational constant;

As shown in Figure 3, the tomb orbit is a circular orbit located 300km above GEO. The transfer orbit is an elliptical orbit. The elliptical transfer orbit is a mobile orbit used to travel between the tomb orbit and GEO. The perigee and apogee of the elliptical transfer orbit are tangent to GEO and the tomb orbit respectively. The first pulse velocity increment Δv _h1 of the Hohmann transfer is the difference between the flight velocity on GEO and the velocity at the perigee on the elliptical transfer orbit. The second pulse velocity increment Δv _h2 is the difference between the velocity on the tomb orbit and the velocity at the apogee on the elliptical transfer orbit. Therefore, the total velocity increment Δv _h of the Hohmann transfer is:

Δv _h ＝Δv _h1 +Δv _h2 ＝|v _e1 -v _geo |+|v _grave -v _e2 |

In the specific implementation, step 3.2 is specifically as follows:

Step 3.2.1. First, obtain the amount of space debris Q _g that the space robot needs to remove after departing from the space refueling station for the gth time:

Q _g = Sa'(g+1)-Sa'(g)

Sa＝[sa ₁ ,sa ₂ ,..,sa _h ,..,sa _G ]

Sa'＝[0,sa ₁ ,sa ₂ ,..,sa _h ,..,sa _G ]

Among them, sa _h represents the position of the hth element "1" in the decision variable S; G represents the number of times the space robot is recharged at the space refueling station;

In the specific implementation, first obtain the position index Sa of the element value 1 in the decision variable S, insert the element 0 at the head of Sa to obtain Sa', and then obtain Q _g according to Sa'; for example: S = [0,0,0,1,0,0,1], then Sa = [4,7], Sa' = [0,4,7], Q ₁ = 4, Q ₂ = 3;

Step 3.2.2, then obtain the remaining mass after the space robot clears Q _g pieces of space debris

in, is the pulse velocity increment required for the space robot to return to the space refueling station to adjust the orbital plane after clearing Q _g pieces of space debris after departing from the space refueling station for the gth time; m _dry is the structural mass of the space robot; I _sp is the engine specific impulse, g ₀ is the earth's gravitational acceleration, and e is a natural number;

Step 3.2.3: Next, according to the remaining mass The total mass m _g,0 at the g-th departure from the space refueling station is iteratively calculated according to the following formula:

Among them, _mg,j is the remaining mass of the space robot after it departs from the space refueling station for the gth time and clears the jth space debris; M _g,j is the mass of the jth space debris; Δv _g,j is the pulse velocity increment required for adjusting the orbital plane angle for the jth time; _mg,0 is the total mass of the space robot when it departs from the space refueling station for the gth time; in this iterative calculation, the initial value of j is Q _g , and j is reduced by 1 after each iteration. When the value of j is 1, the iterative calculation ends and finally mg _,0 is obtained;

Step 3.2.4. Finally, according to the total mass _mg,0 of the space robot each time it departs from the space refueling station, the total mass of fuel consumed by the space robot for orbital maneuvers Mfuel is obtained according to the following formula:

mfuel _g = m _g,0 - m _dry

Among them, G is the number of times the space robot is refueled at the space refueling station, and G is the number of "1" elements in the decision variable S; mfuel _g is the mass of fuel carried by the space robot when it departs from the space refueling station for the gth time, and mfuel _g must satisfy the constraint: mfuel _g ≤ C, C is the upper limit of the mass of fuel that the space robot can carry each time; without loss of generality, it is assumed that the fuel of the space robot is just consumed every time it returns to the space refueling station. Obviously, Mfuel is the total mass of fuel consumed by orbital maneuvers; if mfuel _g is greater than the fuel carrying capacity C of the space robot during the calculation process, it means that the space debris removal mission planning plan is not feasible, and Mfuel is directly set to an infinite value, for example: Mfuel = 10 ⁸ ;

In the above formula, the number of times the space robot refuels at the space gas station G is obtained by the following processing: Calculate the number of elements in the decision variable S whose element value is 1. For example: S = [0,0,0,1,0,0,1], then G = 2

In the specific implementation, let m _dry be the structural mass of the space robot, m _g,0 be the total mass of the space robot when it departs from the space refueling station for the gth time,

m _g,0 = m _dry + m fuel _g

After the space robot departs from the space refueling station for the gth time, the pulse velocity increments Δv _g,j (1≤j≤Q _g +1) and Δv _h required to adjust the orbital plane and Hohmann transfer can be calculated according to the formula in step 2; Make the space robot return to the space refueling station, m _g,j is the remaining mass of the space robot after clearing the jth space junk, satisfying the following formula:

Wherein, M _g,j is the mass of the jth piece of space junk removed by the space robot after the space robot departs from the space refueling station for the gth time, I _sp is the engine specific impulse, and g ₀ is the earth's gravitational acceleration. m _f is the mass of the space robot returning to the space refueling station. Without loss of generality, it is assumed that the fuel of the space robot is just consumed every time it returns to the space refueling station, that is, m _f = m _dry . This gives the calculation method of the optimization index Mfuel.

In step 3.3.3, the set of space junk/gas stations allowed _k is obtained by processing as follows:

If the number of elements in the current tabu list tabu _k is n, then allowed _k = {N+1};

If the number of elements in the current taboo list tabu _k is less than n, and the space robot starts from the space gas station, then allowed _k = {P-tabu _k }

If the number of elements in the current taboo list _tabuk is less than n, and the space robot has not departed from the space refueling station, then allowed _k = {N+1, P-tabu _k }.

Step 3.3.4 is as follows:

At the beginning of the ant colony algorithm, the pheromone between any two path numbers is initialized to τ _max , and the interval range of the pheromone during the iteration is set to [τ _min ,τ _max ]:

Among them, τ _max is the upper limit of the pheromone between two path numbers; τ _min is the lower limit of the pheromone between two path numbers; ρ is the pheromone volatility coefficient; Mfuel _best is the total mass of fuel corresponding to the current optimal cycle path; γ is a given design parameter, and the path number is specifically the element in the clearing path R, and the path number includes the numbers of space debris and space gas stations.

In step 3.3.5, select the probability According to the following formula:

in, represents the selection probability of ant k moving from the current number p to the next number q, p,q∈{P,N+1}; [τ _pq ] is the pheromone between path number p and path number q; [η _pq ] is the heuristic information between path number p and path number q; α is the pheromone importance factor, β is the heuristic information importance factor; l is an element in the allowed _k set; Δm _pq is the fuel consumption required for the space robot to change track from path number p to path number q.

In this embodiment, step 3.3.6 is specifically as follows:

When all ants complete a cycle, the pheromone update formula is as follows:

Among them, [τ _pq ]' is the pheromone between the path number p and the path number q after the update; [τ _pq ] is the pheromone between the path number p and the path number q before the update; τ ₁ is the pheromone replacement value; Mfuel _best is the fuel consumption corresponding to the current cycle optimal path L _best .

The present invention uses an ant colony algorithm to solve the problem of active space debris removal mission planning based on a space robot and a space gas station, and the optimization process of the ant colony algorithm is shown in Figure 4. The ant colony algorithm is a commonly used intelligent optimization method, and each step is common knowledge in the technical field.

The biggest difference between the ant colony algorithm and other heuristic optimization algorithms is that it constructs solutions, and the construction of solutions is completed based on the probabilistic selection mechanism of pheromones and heuristic information. It should be pointed out that the ant colony algorithm designed in the present invention does not directly optimize variables X and S, but constructs a path R. The flowchart of ants constructing a feasible path is shown in Figure 5, where P = {1, 2, ..., N} represents a set of N space junk, N + 1 is a space gas station, _tabuk is a set of space junk that is not allowed to join the path, and _allowedk is a set of space junk and space gas stations that are allowed to join the path.

This embodiment takes the task planning of selecting 15 pieces of space debris from 20 GEO space debris for active removal based on a space robot and a space refueling station as an example for further explanation, and the specific steps are as follows:

Step 1: Input information of space robots, space gas stations and GEO space junk

The mass, orbital inclination, right ascension of ascending node and geographic longitude of 20 GEO space debris are shown in Table 1. At the initial moment of the mission, the space robot and the space refueling station are deployed on the same GEO, with an inclination of 0° and an initial geographic longitude of 0°. The fuel carrying capacity of the space robot is C = 1000 kg, the structural mass m _dry = 500 kg, and the engine parameter I _sp g ₀ = 3200 m/s.

Table 1 Mass and orbital elements of twenty GEO space debris

Step 2: Determine the orbital maneuvering strategy for the space robot to actively remove multiple GEO space debris:

At the beginning of the mission, the space robot and the space refueling station are launched and deployed to GEO. The space robot travels back and forth between the space junk and the refueling station through orbital maneuvers. The space robot obtains fuel supplies at the refueling station, captures space junk in GEO, and transfers to the graveyard orbit to release the space junk. After the removal mission is completed, the space robot must return to the space refueling station. Orbital maneuvers include adjusting the orbital plane, Hohmann transfer, and coplanar phasing. Adjusting the orbital plane refers to adjusting the orbital plane of the space robot to be consistent with the orbital plane of the space junk (or space refueling station). The space robot uses Hohmann transfer to maneuver between GEO and the graveyard orbit. Coplanar phasing refers to adjusting the phase of the space robot to be consistent with the phase of the space junk (or space refueling station).

Step 3: Active space debris removal mission planning based on space robots and space refueling stations:

1. Design optimization variables: including clearing order and decision variables

X＝[x ₁ ,x ₂ ,…,x _n ],S＝[s ₁ ,s ₂ ,…,s _n ]

Among them, n=15.

2. Calculation optimization index: the total fuel mass Mfuel obtained by the space robot from the space gas station

3. Design an optimization model for the removal order and decision variables as follows:

An optimization model for the planning of multiple GEO space debris active removal missions is established. The optimization variables of the optimization model are the removal order X and the decision variable S, and the optimization index is the total fuel mass Mfuel. The optimal removal order and decision variable with the least total fuel mass Mfuel and satisfying all constraints are found. The constraints are shown in the following formula:

x _j∈ {1,2,...,N},j∈{1,2,…,n}

x _i ≠x _j ,i,j∈{1,2,…,n},i≠j

s _j = 0/1, j ∈ {1, 2, …, n-1}

s _n = 1

mfuel _g ＜C

Among them, _xi is the number of the i-th space junk; i is the ordinal number of the space junk; N is the total number of space junk;

4. Ant colony algorithm design: The ant colony algorithm is used to solve the GEO space debris active removal mission planning problem based on space robots and space refueling stations. The optimization process of the ant colony algorithm is shown in Figure 4. The flowchart of ants constructing feasible paths is shown in Figure 5.

When the ant clears n GEO space debris and returns to the space gas station, the complete path construction is completed. The steps for the ant to construct a feasible path are as follows:

First, place ant k at the space gas station, and initialize the ant's path R to R = [N + 1]. The set of space junk tabu _k that is not allowed to join the path is initialized to an empty set.

Next, if the complete path is not constructed, repeat the following steps:

Step 1: Determine allowed _k (the set of space junk and space gas stations allowed to be added to the path); allowed _k has the following three possibilities:

1) If the number of elements in the set tabu _k is n (n pieces of space junk have been cleared), allowed _k = {N+1} (the space robot needs to return to the space refueling station)

2) If the number of elements in _tabuk is less than n, and the vehicle starts from the space gas station, allowed _k = {P-tabu _k }

3) If the number of elements in _tabuk is less than n, and the robot does not start from a space refueling station, that is, the robot starts from space junk, allowed _k = {N+1, P-tabu _k }; at the same time, the number of the currently cleared space junk is added to _tabuk ;

Step 2: Select the probability from allowed _k Select the next target target and expand the ant's path to R = [R, target];

Finally, the full path is output.

5. Output the optimal solution

The optimal solution includes the order X of the space robot to clear GEO space debris and the decision variable S of whether to return to the space refueling station for resupply, the speed increment of the space robot's orbital maneuvers and the mass of fuel carried each time it departs from the space refueling station.

The ant colony algorithm is used to optimize and solve the task planning problem of selecting 15 out of 20 GEO space debris for active removal based on space robots and space gas stations. Figure 6 shows the optimization process curve of the ant colony algorithm, the number of ants is 45, and the algorithm stops after 100 cycles. The optimal path of the space robot is R = [21,12,18,13,6,16,20,7,11,19,21,14,17,5,8,9,2,21], where 21 represents the space refueling station. The corresponding clearing order and decision variables are X = [12,18,13,6,16,20,7,11,19,14,17,5,8,9,2], S = [0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1]. The space refueling station provides fuel replenishment for the space robot twice, with a total fuel mass Mfuel = 597.47 kg. #1, #3, #4, #10, and #15 space debris are not selected for clearing. Figure 7 shows the optimal path of the space robot. After the space robot departs from the space refueling station for the first time, #12, #18, #13, #6, #16, #20, #7, #11, and #19 space debris are cleared in sequence, and then it returns to the space refueling station for refueling. After the space robot departs from the space refueling station for the second time, #14, #17, #5, #8, #9, and #2 space debris are cleared in sequence, and finally it returns to the space refueling station.

In order to verify the optimization performance of the ant colony algorithm (ACO), it is compared with the genetic algorithm (GA) and the simulated annealing algorithm (SA). Unlike ACO, GA and SA directly optimize the removal order X and the decision variable S. Figure 8 shows the results of 30 optimizations of the three algorithms. It can be seen that for the space debris removal mission planning problem in the present invention, ACO is significantly better than GA and SA.

Claims (10)

1. A GEO space junk removal mission planning method based on a space gas station, which is characterized by including the following steps: Step S1: Obtain basic information about space robots, space gas stations and multiple space junks to be removed; The basic information described includes orbital root number and mass; Step S2: Design an orbital maneuvering method for the space robot to actively remove multiple GEO space debris; The specific orbital maneuvering method of the space robot is as follows: at the initial moment of the mission, the space robot and space refueling station are launched and deployed to GEO. The space robot travels to and from the GEO space junk and space refueling station through orbital maneuvering. The space robot obtains the space at the space refueling station. Fuel replenishment: capture space junk in GEO orbit and transfer it to the tomb orbit to release space junk; after the removal mission is completed, the space robot returns to the space refueling station; Step S3: Plan the space robot's GEO space junk active removal mission, and output the optimal solution for the space robot's GEO space junk active removal mission. 2. A GEO space garbage removal mission planning method based on a space gas station according to claim 1, characterized in that: in the step S2, the orbital maneuvering mode of the space robot is as follows: Step S2.1. At the initial moment of the mission, launch and deploy the space robot and space gas station to the initial GEO; Step S2.2: Adjust the orbital plane and coplanar phase of the space robot so that the orbital plane and phase of the space robot are consistent with the space junk to be removed; then use the space robot to capture the space junk on GEO. After capturing the space junk, , the space robot transfers from GEO to the tomb orbit through double-pulse Hohmann transfer, and releases space junk in the tomb orbit; Step S2.3. After releasing the space junk, judge the fuel reserve of the space robot: If the remaining fuel of the space robot is greater than the fuel threshold, repeat step S2.2 to release the next space junk in the grave orbit; Otherwise, adjust the orbital plane and coplanar phase adjustment of the space robot so that the orbital plane and phase of the space robot and the space gas station are consistent; then replenish the space robot with fuel through the space gas station; repeat step S2.2 after the fuel replenishment is completed. , to release the next piece of space junk in a graveyard orbit; Step S2.4 and step S2.3 constitute a complete active space debris removal mission, and the active space debris removal mission is repeated multiple times to achieve active removal of multiple space debris; Step S2.5. After the active removal of all space debris is completed, the space robot returns to the space gas station. 3. A space robot-based GEO space junk active removal mission planning method according to claim 1, characterized in that: the step S3 is specifically: Step 3.1. Define the space debris removal sequence X and decision variable S: X＝[x ₁ ,x ₂ ,..,x _j ,..,x _n ] S＝[s ₁ ,s ₂ ,..,s _j ,..,s _n ] _sj∈ {0,1} Among them, x _j is the number of the jth piece of space junk that has been cleared, j is the clearance number of the space junk, n is the total number of space junk that has been cleared; s _j is whether the space robot will return after clearing the jth piece of space junk. The decision to go to the space gas station for replenishment, s _j = 0 means continuing to clear the next space junk, s _j = 1 means returning to the space gas station to replenish fuel, and after the replenishment is completed, continue to clear the next target; Step 3.2. Obtain the total mass of fuel consumed by the space robot during orbital maneuvers; Step 3.3. Optimize the design of the space robot’s clearance path based on the ant colony algorithm: Step 3.3.1. First, construct a set P of all GEO space junk to be removed: P＝{1,2,…,N} Among them, N is the total amount of space junk; Step 3.3.2. Define the path R of ant k in the ant colony algorithm according to the clearance order X and the decision variable S, and use this path as the clearance path R of the space robot: R＝[Ν+1, x ₁ , y ₁ , x ₂ , y ₂ ,..,x _j ,y _j ,..,x _n ,y _n ] Among them, N+1 is the number of the space gas station; y _j represents the decision number of whether the space robot will return to the space gas station for replenishment after clearing the jth space junk. When s _j = 0, y _j is empty, s When _j = 1, y _j takes N+1; Step 3.3.3. Define the tabu list tabu _k of the ant colony algorithm, and the set of space junk/gas stations allowed _k that are allowed to be selected; at the initial moment of the task, the tabu list at the beginning of the ant colony algorithm Whenever a piece of space junk is cleared, the number of the space junk is recorded in tabu _k , the taboo list; Step 3.3.4. Initialize the initial parameters of the ant colony algorithm; Step 3.3.5. Based on the pheromone and heuristic information, obtain the selection probability of ant k moving from the current path number p to the next path number q. The path number q is selected from the space junk/gas station set allowed _k that is allowed to be selected; Step 3.3.5: Make all ants use the selection probability of the ant colony algorithm Find their own paths, and select the path with the smallest required total fuel mass M _fuel among all paths as the optimal path L _best for the current cycle; Step 3.3.6. Update the pheromone according to the optimal path L _best ; Step 3.3.7. Repeat steps 3.3.5 to 3.3.6 for iteration until the ant colony algorithm reaches the maximum number of iterations, and then select the path with the smallest required total fuel mass Mfuel among all paths as the final clearing path of the space robot; Step 3.4. Output the optimal solution The optimal solution includes the final clearing path R of the space robot, the decision variable S of whether to return to the space gas station for replenishment, the speed increment of the space robot's orbital maneuver and the mass of fuel carried each time it departs from the space gas station. 4. A GEO space garbage removal mission planning method based on a space gas station according to claim 2, characterized in that: in step 2, the orbital surface of the space robot is adjusted so that the space robot is in contact with the space garbage to be removed. The specific method of making the orbital surface of the space gas station consistent is as follows: The expression for adjusting the orbital surface angle of a space robot is as follows: cosδ＝sini _robot sini _junk cos(Ω _robot -Ω _junk )+cosi _robot cosi _junk Among them, δ is the angle between the orbital surface of the space robot and the space junk/space gas station; i _robot is the orbital inclination of the space robot; _ijun is the orbital inclination of the space junk/space gas station to be removed; Ω _robot is the space The right ascension of the ascending node of the robot; Ω _junk is the right ascension of the ascending node of the space junk/space gas station to be removed; The pulse speed increment required for the space robot to maneuver is determined based on the orbital surface angle. The pulse speed increment Δv required for the space robot flying in GEO to adjust the orbital surface angle δ is: Among them, v _GEO is the flight speed of the space robot on GEO. 5. A GEO space junk removal mission planning method based on a space gas station according to claim 2, characterized in that: the expression of the total speed increment Δv _h of the double-pulse Hohmann transfer in step S2.2 for: a _t = (r _geo + r _grave )/2 r _grave = r _geo +300 Among them, v _e1 is the flight speed of the space robot at the perigee of the elliptical transfer orbit; v _e2 is the flight speed of the space robot at the apogee of the elliptical transfer orbit; v _geo is the flight speed of the space robot in GEO; v _grave is the flight speed of the space robot on the grave orbit. flight speed; r _geo is the radius of GEO; r _grave is the radius of the grave orbit; a _t is the semi-major axis of the elliptical transfer orbit; μ is the Earth's gravitational constant. 6. A GEO space junk removal mission planning method based on a space gas station according to claim 3, characterized in that: the step 3.2 is specifically: Step 3.2.1. First, obtain the amount of space debris Q _g that needs to be removed after the space robot sets off from the space gas station for the g-th time: Q _g =Sa'(g+1)-Sa'(g) Sa＝[sa ₁ ,sa ₂ ,..,sa _h ,..,sa _G ] Sa'＝[0,sa ₁ ,sa ₂ ,..,sa _h ,..,sa _G ] Among them, sa _h represents the position of the h-th element "1" in the decision variable S; G represents the number of times the space robot has been replenished at a space gas station; Step 3.2.2. Then, obtain the remaining mass after the space robot has cleared Q _g pieces of space junk. in, is the pulse speed increment required for the space robot to return to the space gas station after clearing Q _g pieces of space junk for the g-th time from the space gas station; m _dry is the structural mass of the space robot; I _sp is the engine specific impulse, g ₀ is the earth’s gravitational acceleration; Step 3.2.3, then, according to the remaining mass The total mass m _g,0 when setting off from the space gas station for the gth time is iteratively calculated according to the following formula: Among them, m _g,j is the remaining mass after the space robot sets off from the space gas station for the gth time and clears the jth space junk; M _g,j is the mass of the jth space junk; Δv g,j is the mass of the jth space junk; Δv _g,j is the mass of the jth space junk. The pulse velocity increment required to adjust the orbital plane angle j times; m _g,0 is the total mass of the space robot when it sets off from the space gas station for the gth time; in this iterative calculation, the initial value of j is Q _g , each time After the iteration, j is reduced by 1. When the value of j is 1, the iterative calculation ends, and finally m _g,0 is obtained; Step 3.2.4. Finally, according to the total mass m _g,0 of the space robot each time it sets off from the space gas station, the total mass of fuel Mfuel consumed by the space robot for orbital maneuvers is obtained according to the following formula: mfuel _g =m _g,0 -m _dry Among them, G is the number of times the space robot has been replenished at the space gas station, and G is the number of elements "1" in the decision variable S; mfuel _g is the mass of fuel carried by the space robot when it sets off from the space gas station for the gth time. 7. A GEO space garbage removal mission planning method based on space gas stations according to claim 3, characterized in that: in step 3.3.3, the selected space garbage/gas station set allowed _k is allowed in the following manner Processed to get: If the number of elements in the current tabu list tabu _k is n, then allowed _k = {N+1}; If the number of elements in the current tabu list tabu _k is less than n, and the space robot sets off from a space gas station, then allowed _k = {P-tabu _k } If the number of elements in the current tabu list tabu _k is less than n, and the space robot does not set off from the space gas station, then allowed _k = {N+1,P-tabu _k }. 8. A GEO space junk removal mission planning method based on a space gas station according to claim 3, characterized in that: the step 3.3.4 is specifically: At the beginning of the ant colony algorithm, the pheromone between any two path numbers is initialized to τ _max , and the interval range of the pheromone during the iteration process is set [τ _min ,τ _max ]: Among them, τ _max is the upper limit of the pheromone between the two path numbers; τ _min is the lower limit of the pheromone between the two path numbers; ρ is the pheromone volatilization coefficient; Mfuel _best is the current cycle optimal The total mass of fuel corresponding to the path; γ is the given design parameter. 9. A GEO space junk removal mission planning method based on a space gas station according to claim 3, characterized by: In step 3.3.5, select the probability It is processed according to the following formula: in, Indicates the selection probability of ant k moving from the current number p to the next number q; [τ _pq ] is the pheromone between path number p and path number q; [η _pq ] is the pheromone between path number p and path number q Heuristic information; α is the pheromone importance factor, β is the heuristic information importance factor; l is the element in the allowed _k set; Δm _pq is the fuel consumption required for the space robot to change orbit from path number p to path number q. . 10. A GEO space junk removal mission planning method based on a space gas station according to claim 3, characterized in that: step 3.3.6 is specifically: When all ants complete a cycle, the pheromone update formula is as follows: Among them, [τ _pq ]' is the pheromone between the path number p and the path number q after the update; [τ _pq ] is the pheromone between the path number p and the path number q before the update; τ ₁ is the pheromone replacement value ;Mfuel _best is the fuel consumption corresponding to the current cycle optimal path L _best .