A helicopter route planning method based on monitoring and evaluation mechanism

Abstract

This application belongs to the field of route planning technology. It provides a helicopter route planning method based on a monitoring and evaluation mechanism. In view of the needs of helicopters to perform low-altitude / ultra-low-altitude flight missions in complex mission scenarios, it selects the most suitable flight path for different mission scenarios, solves the problem that the same route planning algorithm is difficult to apply to different mission scenarios, and greatly improves the flyability and planning efficiency of the planned route.

Description

Technical Field

[0001] This application belongs to the field of route planning technology, specifically involving a helicopter route planning method based on a monitoring and evaluation mechanism. Background Technology

[0002] As a vertical takeoff and landing (VTOL) aircraft, helicopters possess advantages such as vertical takeoff and landing, hovering, and high maneuverability. In the civilian sector, helicopters are widely used in tasks such as law enforcement, medical rescue, and firefighting. Helicopters often need to fly in complex environments, such as urban buildings, mountainous terrain, and jungles. The flight path constraints for helicopters vary significantly depending on the mission objectives and scenarios. To ensure flight safety in different mission environments, helicopters are required to possess highly versatile route planning capabilities, enabling them to plan safe, reliable, and flyable reference routes under varying constraints.

[0003] Currently, research on route planning technology in the helicopter field mainly focuses on specific algorithms for fixed mission scenarios. Each algorithm has its own advantages and disadvantages, but its versatility is poor, and the planned routes obtained in other mission scenarios are often not very flyable. Summary of the Invention

[0004] Purpose of the invention: This invention addresses the need for helicopters to perform low-altitude / ultra-low-altitude flight missions in complex mission scenarios by providing a helicopter route planning method based on a monitoring and evaluation mechanism, thus solving the problem that the same route planning algorithm is difficult to apply to different mission scenarios.

[0005] This application provides a helicopter route planning method based on a monitoring and evaluation mechanism, the method comprising: S1: The distance between the starting and ending points, dis, is calculated based on the coordinates of the planning start and ending points. S2: Calculate the uniform step length step_len for each route planning algorithm based on the distance dis between the starting and ending points; S3: Based on the unified step size step_len, call the available algorithm models in the route planning algorithm library ψ to carry out route planning; S4: A subset φ of algorithm models that complete the planning within the specified time; where the planning result of the i-th algorithm model is denoted as path_i, the planning time is t_i, and path_i is a list of three-dimensional coordinates of waypoints; S5: φ is not an empty set, go to S6; S6: If there are multiple models in φ, calculate the number of segments n1_i in the planned route path_i of the i-th algorithm model that do not meet the climb / descent rate. S7: Calculate the number of segments n21_i that do not meet the minimum ground clearance in the planned route path_i of the i-th algorithm model, and the number of waypoints n22_i that do not meet the minimum ground clearance for each segment; S8: Calculate the number of segments n31_i that do not meet the horizontal clearance requirement in the planned route path_i of the i-th algorithm model, and the number of path points n32_i that do not meet the horizontal clearance requirement for each segment; S9: Calculate the maximum turning radius Rd of the helicopter platform: S10: If Rd > step_len / 2, go to S11; otherwise, n4_i = 0, and the turning angle constraint during segment switching does not need to be considered, go to S12. S11: Calculate the number of segments n4_i in the planned route path_i of the i-th algorithm model that do not satisfy the maximum turning angle; S12: Calculate the standard deviation F(n22_i) of the parameter n22_i obtained from the above steps. S13: Calculate the standard deviation F(n32_i) of the parameter n32_i obtained from the above steps. S14: Based on the parameters n1_i, n21_i, n22_i, n31_i, n32_i, n4_i, F(n22_i), and F(n32_i) obtained from the above steps, calculate the evaluation value n_i of the planned route; S15: Select the route j with the smallest value among all routes n_i as the candidate route.

[0006] Preferably, S6 specifically includes: S1: Initialization, segment number j=1, number of segments that do not meet the requirements n1_i=0 S2: If j≤len(path_i), go to S3; otherwise, go to S6; len(path_i) is the length of the route path_i, i.e., the number of waypoints. S3: Calculate the climb / descent rate (grad) for the current flight segment:

[0007] S4: If grad > climb_rate_max or grad < -fall_rate_max, n1_i = n1_i + 1, where climb_rate_max and fall_rate_max are the maximum climb rate and maximum descent rate of the helicopter platform, respectively, and are positive values; S5: j = j + 1, go to S2; S6: Obtain the value of n1_i and end the calculation.

[0008] Preferably, S7 specifically includes: S1: Initialization, segment number j=1, number of segments that do not meet the requirements n21_i=0, number of path points that do not meet the requirements for each segment n22_i[], n22_i[0] records the total number of path points that do not meet the requirements for the entire route, n22_i[0]=0; S2: If j < len(path_i), go to S73; otherwise, go to S10. len(path_i) is the length of the route path_i, i.e., the number of waypoints. S3: Interpolate flight segment j at intervals of map grid resolution map_step to obtain the path point list path_i_j. The coordinates and altitude of the kth interpolation point are calculated as follows:

[0009] S4: The waypoint number of the current segment is k=0, and the number of waypoints in the current segment that do not meet the minimum ground clearance is n_j=0; S5: Calculate the ground clearance Δh of path point path_i_j[k]. If Δh < min_GC, n_j = n_j + 1, where min_GC is the minimum ground clearance. S6: k = k + 1; S7: If k < len(path_i_j), go to S5; otherwise go to S8; S8: If n_j≠0, n21_i=n21_i+1; S9: n22_i[j]=n_j, n22_i[0]= n22_i[0]+n_j, j=j+1, go to S2; S10: Obtain the values ​​of n21_i and n22_i, and end the calculation.

[0010] Preferably, S8 specifically includes: S1: Initialization, segment number j=1, number of segments that do not meet the requirements n31_i=0, number of path points that do not meet the requirements for each segment n32_i[], n32_i[0] records the total number of path points that do not meet the requirements for the entire route, n32_i[0]=0; S2: d = round(min_HC / map_step), if d ≥ 2, go to S3; otherwise go to S9; S3: If j≤len(path_i), go to S4; otherwise, go to S9; len(path_i) is the length of the route path_i, i.e., the number of waypoints. S4: Based on the flight segment waypoint list calculated in S7, calculate the coordinates and altitudes of the 2d translation points within the horizontal clearance range of each waypoint. The coordinates and altitudes of the m-th translation points on both sides of the k-th waypoint are calculated as follows:

[0011] S5: Calculate the number of translation points with non-positive ground altitudes among the 2d translation points within the horizontal gap range of each path point in the j-th flight segment as n32_i_j; S6: n32_i[j]=n32_i_j, n32_i[0]=n32_i[0]+n32_i_j; S7: If n32_i_j≠0, then n31_i=n31_i+1; S8: j = j + 1, go to S3; S9: Obtain the values ​​of n31_i and n32_i, and end the calculation.

[0012] Preferably, S11 specifically includes: S1: Initialization, segment number j=1, number of segments that do not meet the requirements n4_i=0; S2: Calculate the helicopter's maximum turning angle θ:

[0013] Where dis_j is the planar projection length of the j-th flight segment, and Rd is the maximum turning radius of the helicopter; S3: Calculate the turning angle θ_j between the j-th segment and the next segment using the vector dot product formula or the cosine theorem; S4: If θ_j>θ, n4_i=n4_i+1; S5: j = j + 1; S6: If j < len(path_i), go to S112; otherwise go to S7. S7: Obtain the value of n4_i and end the calculation.

[0014] Preferably, S12 specifically includes:

[0015] Where len(path_i) is the number of waypoints in the planned route path_i of the i-th algorithm model, and n22_i is the number of waypoints in each segment of the planned route path_i of the i-th algorithm model that do not meet the minimum takeoff height constraint.

[0016] Preferably, S13 specifically includes:

[0017] Where len(path_i) is the number of waypoints in the planned route path_i of the i-th algorithm model, and n32_i is the number of pathpoints in each segment of the planned route path_i of the i-th algorithm model that do not satisfy the horizontal clearance constraint.

[0018] Preferably, S14 specifically includes:

[0019] Where k1, k2, k3, and k4 are the weight values ​​of the climb / descent rate constraint, minimum ground clearance constraint, horizontal clearance constraint, and turning radius constraint, respectively. The higher the weight, the more important the constraint. F(n22_i) represents the standard deviation of the effective values ​​in list n22_i, and F(n32_i) represents the standard deviation of the effective values ​​in list n32_i.

[0020] This application has the following technical effects: This invention addresses the need for helicopters to perform low-altitude / ultra-low-altitude flight missions in complex mission scenarios by providing a helicopter route planning method based on a monitoring and evaluation mechanism. This method selects the most suitable flight path for different mission scenarios, solving the problem that the same route planning algorithm is difficult to apply to different mission scenarios, and greatly improving the flyability and planning efficiency of the planned route. Attached Figure Description

[0021] Figure 1 This is a flowchart of a helicopter planning method based on a monitoring and evaluation mechanism provided in an embodiment of this application. Detailed Implementation Please see Figure 1 In this method, a monitoring and evaluation mechanism is used to monitor and evaluate the flyability and performance of different route planning algorithms. Then, based on the evaluation results, the most suitable algorithm model for the current task scenario is selected. The main process is as follows: Figure 1 As shown.

[0022] A helicopter route planning method based on a monitoring and evaluation mechanism includes the following steps: S1: The distance between the starting and ending points, dis, is calculated based on the coordinates of the planning start and ending points. S2: Calculate the uniform step size step_len for all planning algorithms:

[0023] In the formula, dis is the distance between the starting and ending points of the plan, map_step is the map grid resolution, k1 is the set step size parameter, and round is the rounding operation; S3: Use the available algorithm models in the route planning algorithm library ψ to perform route planning; S4: A subset φ of algorithm models that complete the planning within a specified time, where the planning result of the i-th algorithm model is denoted as path_i, and the planning time is t_i, where path_i is a list of three-dimensional coordinates of waypoints; S5: φ is not an empty set, go to S6; φ is an empty set, planning fails, go to S15; S6: If there is only one model in φ, then the unique route corresponding to this algorithm is taken as the route to be flown, and go to S15; otherwise, calculate the number n1 of segments that do not meet the climb / descent rate in each route, and go to S7. The n1_i of the planned route paht_i of the i-th algorithm model is calculated as follows: S61: Initialization, segment number j=1, number of segments that do not meet the requirements n1_i=0 S62: If j≤len(path_i), go to S63; otherwise, go to S66; len(path_i) is the length of the route path_i, i.e., the number of waypoints. S63: Calculate the climb / descent rate (grad) for the current segment:

[0024] S64: If grad > climb_rate_max or grad < -fall_rate_max, n1_i = n1_i + 1, where climb_rate_max and fall_rate_max are the maximum climb rate and maximum descent rate of the helicopter platform, respectively, and are positive values; S65: j = j + 1, go to S62; S66: Obtain the value of n1_i, end the calculation. S7: Calculate the number of segments n21 that do not meet the minimum ground clearance in each route and the number of waypoints n22 that do not meet the minimum ground clearance in each segment. The calculation of n21_i and n22_i for the planned route paht_i of the i-th algorithm model is as follows: S71: Initialization, segment number j=1, number of segments that do not meet the requirements n21_i=0, number of path points that do not meet the requirements for each segment n22_i[], n22_i[0] records the total number of path points that do not meet the requirements for the entire route, n22_i[0]=0; S72: If j < len(path_i), go to S73; otherwise, go to S7a; len(path_i) is the length of the route path_i, i.e., the number of waypoints. S73: Interpolate flight segment j at intervals of map grid resolution map_step to obtain a list of path points path_i_j. The coordinates and altitude of the kth interpolation point are calculated as follows:

[0025] S74: The waypoint number of the current segment is k=0, and the number of waypoints in the current segment that do not meet the minimum ground clearance is n_j=0; S75: Calculate the ground clearance Δh of path point path_i_j[k]. If Δh < min_GC, n_j = n_j + 1, where min_GC is the minimum ground clearance. S76: k = k + 1; S77: If k < len(path_i_j), go to S75; otherwise go to S78; S78: If n_j≠0, n21_i=n21_i+1; S79: n22_i[j]=n_j, n22_i[0]= n22_i[0]+n_j, j=j+1, go to S72; S7a: Obtain the values ​​of n21_i and n22_i, and end the calculation. S8: Calculate the number n3 of segments that do not meet the horizontal clearance requirement in each route. The calculation of n31_i and n32_i[] for the planned route path_i of the i-th algorithm model is as follows: S81: Initialization, segment number j=1, number of segments that do not meet the requirements n31_i=0, number of path points that do not meet the requirements for each segment n32_i[], n32_i[0] records the total number of path points that do not meet the requirements for the entire route, n32_i[0]=0; S82: d = round(min_HC / map_step), if d ≥ 2, go to S83; otherwise go to S89; S83: If j≤len(path_i), go to S84; otherwise, go to S89; len(path_i) is the length of the route path_i, i.e., the number of waypoints. S84: Based on the flight segment waypoint list calculated in S7, calculate the coordinates and altitudes of the 2d translation points within the horizontal clearance range of each waypoint. The coordinates and altitudes of the m-th translation points on both sides of the k-th waypoint are calculated as follows:

[0026] S85: Calculate the number of translation points with non-positive ground altitudes among the 2d translation points within the horizontal clearance range of each path point in the j-th flight segment as n32_i_j; S86: n32_i[j]=n32_i_j, n32_i[0]=n32_i[0]+n32_i_j; S87: If n32_i_j≠0, then n31_i=n31_i+1; S88: j = j + 1, go to S83; S89: Obtain the values ​​of n31_i and n32_i, and end the calculation.

[0027] S9: Calculate the maximum turning radius Rd of the helicopter platform:

[0028] Where α is the maximum roll angle of the helicopter, which is related to the performance of the helicopter platform; V GS The ground speed of the helicopter is determined by taking the appropriate value based on the application scenario of the route planning. For example, the cruise speed is taken when planning a global route, the current speed is taken when planning an obstacle avoidance route, and the standard ground-hugging flight speed is taken when planning a ground-hugging route.

[0029] S10: If Rd > step_len / 2, go to S11; otherwise, n4_i = 0, and the turning angle constraint during segment switching does not need to be considered, go to S14. S11: Calculate the number n4 of segments in each route that do not meet the maximum turning angle requirement. The n4_i of the planned route path_i in the i-th algorithm model is calculated as follows: S111: Initialization, segment number j=1, number of segments that do not meet the requirements n4_i=0; S112: Calculate the helicopter's maximum turning angle θ:

[0030] Where dis_j is the planar projection length of the j-th flight segment, and Rd is the maximum turning radius of the helicopter; S113: Calculate the turning angle θ_j between the j-th segment and the next segment using the vector dot product formula or the cosine theorem; S114: If θ_j > θ, then n4_i = n4_i + 1; S115: j = j + 1; S116: If j < len(path_i), go to S112; otherwise go to S117. S117: Obtain the value of n4_i and end the calculation.

[0031] S12: Calculate the standard deviation of the number of waypoints n22_i in each segment of the planned route paht_i of the i-th algorithm model that do not meet the minimum takeoff altitude constraint:

[0032] Where len(path_i) is the number of waypoints for the i-th algorithm model's planned path_i. S13: Calculate the standard deviation of the number of path points n32_i in each segment of the planned route paht_i of the i-th algorithm model that do not satisfy the horizontal clearance constraint:

[0033] Where len(path_i) is the number of waypoints for the i-th algorithm model's planned path_i. S14: Calculate the evaluation value of the planned route:

[0034] Where k1, k2, k3, and k4 are the weight values ​​of the climb / descent rate constraint, minimum ground clearance constraint, horizontal clearance constraint, and turning radius constraint, respectively. The higher the weight, the more important the constraint. F(n22_i) represents the standard deviation of the effective values ​​in list n22_i, and F(n32_i) represents the standard deviation of the effective values ​​in list n32_i. For different mission scenarios, the weights of k1, k2, k3, and k4 tend to be set differently. Taking typical flight missions such as cruise at constant altitude, terrain following, and terrain avoidance in mountainous scenarios as examples, the weight settings are explained and illustrated.

[0035] 1. Cruise at similar altitudes The characteristics of cruise flight are that the helicopter maintains a constant altitude. The helicopter stays at a relatively high altitude and avoids flying around mountain peaks. It also flies over mountains without climbing or descending, and makes a few turns. Therefore, in this mission scenario, the climb / descent rate constraint weight is reset to 0, the horizontal clearance constraint and turning radius constraint weight values ​​are set to low (can be 0.2), and the minimum ground clearance constraint weight value is the highest (can be 0.6).

[0036] 2. Terrain-following flight Terrain-following flight is characterized by the helicopter maintaining a constant altitude, following the terrain's undulations, and experiencing significant altitude changes, but with fewer turns. Therefore, in this mission scenario, the minimum altitude constraint weight is set to 0, the turning radius constraint and horizontal clearance constraint weights are set relatively low (e.g., 0.2), and the climb / descent rate constraint weight is the highest (e.g., 0.6).

[0037] 3. Terrain avoidance flight Terrain avoidance flight is characterized by helicopters maintaining a low altitude while flying around mountain peaks with minimal climb / descent. Therefore, in this mission scenario, the weight values ​​for climb / descent constraints and minimum ground clearance constraints are set low (e.g., 0.2), while the weight values ​​for turning radius and horizontal clearance are set high (e.g., 0.3).

[0038] S15: Select the route j with the smallest value among all routes n_i as the candidate route; S16: If route j is unique, then route j is the route to be flown; otherwise, select the route with the smallest t_i among all routes j as the route to be flown. S17: End.

Claims

1. A helicopter route planning method based on a monitoring and evaluation mechanism, characterized in that, The method includes: S1: The distance between the starting and ending points, dis, is calculated based on the coordinates of the planning start and end points. S2: Calculate the uniform step length step_len for each route planning algorithm based on the distance dis between the starting and ending points; S3: Based on the unified step size step_len, call the available algorithm models in the route planning algorithm library ψ to carry out route planning; S4: A subset φ of algorithm models that complete the planning within the specified time; where the planning result of the i-th algorithm model is denoted as path_i, the planning time is t_i, and path_i is a list of three-dimensional coordinates of waypoints; S5: φ is not an empty set, go to S6; S6: If there are multiple models in φ, calculate the number of segments n1_i in the planned route path_i of the i-th algorithm model that do not meet the climb / descent rate. S7: Calculate the number of segments n21_i that do not meet the minimum ground clearance in the planned route path_i of the i-th algorithm model, and the number of waypoints n22_i that do not meet the minimum ground clearance for each segment; S8: Calculate the number of segments n31_i that do not meet the horizontal clearance requirement in the planned route path_i of the i-th algorithm model, and the number of path points n32_i that do not meet the horizontal clearance requirement for each segment; S9: Calculate the maximum turning radius R of the helicopter platform d : S10: If Rd > step_len / 2, go to S11; otherwise, n4_i = 0, and the turning angle constraint during segment switching does not need to be considered, go to S12. S11: Calculate the number of segments n4_i in the planned route path_i of the algorithm model that do not meet the maximum turning angle requirement; S12: Calculate the standard deviation F(n22_i) of the parameter n22_i obtained from the above steps. S13: Calculate the standard deviation F(n32_i) of the parameter n32_i obtained from the above steps. S14: Based on the parameters n1_i, n21_i, n22_i, n31_i, n32_i, n4_i, F(n22_i), and F(n32_i) obtained from the above steps, calculate the evaluation value n_i of the planned route; S15: Select the route with the smallest value among all routes n_i as the candidate route.

2. The method according to claim 1, characterized in that, S6 specifically includes: S61: Initialization, segment number j=1, number of segments that do not meet the requirements n1_i=0; S62: If j≤len(path_i), go to S63; otherwise, go to S66; len(path_i) is the length of the route path_i, i.e., the number of waypoints. S63: Calculate the climb / descent rate (grad) for the current flight segment: S64: If grad > climb_rate_max or grad < -fall_rate_max, n1_i = n1_i + 1, where climb_rate_max and fall_rate_max are the maximum climb rate and maximum descent rate of the helicopter platform, respectively, and are positive values; S65: j = j + 1, go to S62; S66: Obtain the value of n1_i and end the calculation.

3. The method according to claim 1, characterized in that, S7 specifically includes: S71: Initialization, segment number j=1, number of segments that do not meet the requirements n21_i=0, number of path points that do not meet the requirements for each segment n22_i[], n22_i[0] records the total number of path points that do not meet the requirements for the entire route, n22_i[0]=0; S72: If j < len(path_i), go to S73; otherwise, go to S710; len(path_i) is the length of the route path_i, i.e., the number of waypoints. S73: Interpolate flight segment j at intervals of map grid resolution map_step to obtain a list of path points path_i_j. The coordinates and altitude of the kth interpolation point are calculated as follows: S74: The waypoint number of the current segment is k=0, and the number of waypoints in the current segment that do not meet the minimum ground clearance is n_j=0; S75: Calculate the ground clearance Δh of path point path_i_j[k]. If Δh < min_GC, n_j = n_j + 1, where min_GC is the minimum ground clearance. S76: k = k + 1; S77: If k < len(path_i_j), go to S75; otherwise go to S78; S78: If n_j≠0, n21_i=n21_i+1; S79: n22_i[j]=n_j, n22_i[0]= n22_i[0]+n_j, j=j+1, go to S72; S710: Obtain the values ​​of n21_i and n22_i, and end the calculation.

4. The method according to claim 1, characterized in that, S8 specifically includes: S81: Initialization, segment number j=1, number of segments that do not meet the requirements n31_i=0, number of path points that do not meet the requirements for each segment n32_i[], n32_i[0] records the total number of path points that do not meet the requirements for the entire route, n32_i[0]=0; S82: d = round(min_HC / map_step), if d ≥ 2, go to S83; otherwise go to S89; S83: If j≤len(path_i), go to S84; otherwise, go to S89; len(path_i) is the length of the route path_i, i.e., the number of waypoints. S84: Based on the flight segment waypoint list calculated in S87, calculate the coordinates and altitudes of the 2d translation points within the horizontal clearance range of each waypoint. The coordinates and altitudes of the m-th translation points on both sides of the k-th waypoint are calculated as follows: S85: Calculate the number of translation points with non-positive ground altitudes among the 2d translation points within the horizontal clearance range of each path point in the j-th flight segment as n32_i_j; S86: n32_i[j]=n32_i_j, n32_i[0]=n32_i[0]+n32_i_j; S87: If n32_i_j≠0, then n31_i=n31_i+1; S88: j = j + 1, go to S83; S89: Obtain the values ​​of n31_i and n32_i, and end the calculation.

5. The method according to claim 1, characterized in that, S11 specifically includes: S111: Initialization, segment number j=1, number of segments that do not meet the requirements n4_i=0; S112: Calculate the helicopter's maximum turning angle θ: Where, dis_j is the planar projection length of the j-th flight segment, R d This is the maximum turning radius of the helicopter; S113: Calculate the turning angle θ_j between the j-th segment and the next segment using the vector dot product formula or the cosine theorem; S114: If θ_j > θ, then n4_i = n4_i + 1; S115: j = j + 1; S116: If j < len(path_i), go to S112; otherwise go to S117. S117: Obtain the value of n4_i and end the calculation.

6. The method according to claim 1, characterized in that, S12 specifically includes: Where len(path_i) is the number of waypoints in the planned route path_i of the i-th algorithm model, and n22_i is the number of waypoints in each segment of the planned route path_i of the i-th algorithm model that do not meet the minimum takeoff height constraint.

7. The method according to claim 1, characterized in that, S13 specifically includes: Where len(path_i) is the number of waypoints in the planned route path_i of the i-th algorithm model, and n32_i is the number of pathpoints in each segment of the planned route path_i of the i-th algorithm model that do not satisfy the horizontal clearance constraint.

8. The method according to claim 1, characterized in that, S14 specifically includes: Where k1, k2, k3, and k4 are the weight values ​​of the climb / descent rate constraint, minimum ground clearance constraint, horizontal clearance constraint, and turning radius constraint, respectively. The higher the weight, the more important the constraint. F(n22_i) represents the standard deviation of the effective values ​​in list n22_i, and F(n32_i) represents the standard deviation of the effective values ​​in list n32_i.

Images