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CN-121697215-B - Unmanned aerial vehicle 3D printing system combining track curvature optimization and tail end compensation and method thereof

CN121697215BCN 121697215 BCN121697215 BCN 121697215BCN-121697215-B

Abstract

The invention discloses an unmanned aerial vehicle 3D printing system and method combining track curvature optimization and tail end compensation. The system comprises a track optimization module, a dynamic feasibility checking module, a terminal compensation distribution module and an execution and closed-loop control module. Firstly, optimizing an original printing track containing sharp features such as right angles, acute angles and the like, and generating a smooth track meeting dynamics constraint by adopting a sequence quadratic programming algorithm under the conditions of deviation constraint, curvature constraint and boundary constraint. And then, carrying out time parameterization on the smooth track, limiting the acceleration and jerk of the flight platform, and realizing synchronous control of extrusion flow and track speed. Further, the residual geometric error of the optimized trajectory relative to the original trajectory is calculated and distributed to the end compensation mechanism for correction over its effective range of travel. High-precision track following and stable printing are realized through cooperative control of the flight platform and the tail end compensation mechanism.

Inventors

  • YUAN FENG
  • XIE XINGJIE
  • DU XU
  • FU JIAYAN

Assignees

  • 同济大学

Dates

Publication Date
20260505
Application Date
20260212

Claims (8)

  1. 1. A method of a unmanned 3D printing system combining trajectory curvature optimization and end compensation, comprising the steps of: step S1, acquiring an original track: acquiring an original design printing path of a flight platform, wherein the original design printing path comprises sharp geometric features including right angles, acute angles and turning back; Step S2, track pre-optimization: Performing track optimization on the original design printing path, converting the path containing sharp features into a smooth track through an algorithm, eliminating instantaneous steering actions which cannot be executed by a flight platform, and improving the track executable performance; the track optimization adopts a multi-target weighted optimization form, and the comprehensive objective function is as follows: ; wherein alpha is path length smoothness weight, beta is curvature smoothness weight, gamma is track fidelity weight; the ith discrete point in the original design track; Is the curvature of the trajectory at the corresponding discrete point; The track optimization is solved by adopting a sequence quadratic programming algorithm, and the original nonlinear constraint optimization problem is reconstructed into the following quadratic programming sub-problem: ; s.t. ; Wherein, the In order to search for the direction of the search, To be an approximation of the Hessian matrix, Is a track curvature constraint and a dynamic constraint condition; the sequence quadratic programming algorithm comprises the following steps: Taking the discrete points of the original track as an initial solution ; Constructing a Lagrange function: ; At the current iteration point Computing a Hessian matrix approximation Linearizing the constraint condition; solving quadratic programming sub-problems to obtain search direction ; Determining step size by line search And updating the trajectory solution: ; When meeting the convergence condition Terminating the iteration when the iteration is completed; Step S3, checking the time parameterized pre-dynamic feasibility: performing time parameterization and dynamic feasibility check on the smooth flight track to generate corresponding speed and acceleration planning information, so as to ensure that the flight platform is smoothly executed according to the track in actual operation; step S4, end compensation error distribution: Calculating residual geometric errors after track optimization and distributing the residual geometric errors to an end compensating mechanism, wherein an error distributing strategy ensures that the compensating mechanism can correct the residual errors within the range of the maximum effective travel of the compensating mechanism; And S5, controlling the flying platform to execute the flying track according to the track optimized in the steps S2 to S4, and simultaneously carrying out error adjustment through real-time closed-loop control feedback.
  2. 2. The method of a unmanned aerial vehicle 3D printing system that combines trajectory curvature optimization with end compensation according to claim 1, wherein in step S2, the trajectory optimization comprises bias constraints, curvature constraints, and boundary constraints; The deviation constraint is used for ensuring that the maximum deviation between the optimized track and the original track does not exceed a preset value, so that the fidelity of the track is ensured; the curvature constraint is that the curvature of the track is ensured not to exceed a preset maximum curvature value so as to avoid the situation of too sharp turning in the flight process; and the boundary constraint ensures that the positions of the start point and the end point of the track are fixed so as to maintain the global consistency of the flight path.
  3. 3. A method of unmanned aerial vehicle 3D printing system that combines trajectory curvature optimization with end compensation according to claim 2, wherein the bias constraints are as follows: , Wherein, the The space coordinates of the position corresponding to the printing track are designed for the original design; space coordinates of corresponding discrete points after track optimization; the maximum allowable track deviation is preset; The curvature constraint includes converting an original trajectory γ0(s) of the original design print path into a smoothed trajectory γ(s) that satisfies a dynamics constraint, wherein the curvature κ(s) satisfies: , Wherein alat,max is the maximum lateral acceleration, determined by the thrust-to-weight ratio and attitude margin of the flying platform V(s) is the track velocity along arc length s, Is the maximum curvature; the boundary constraints are as follows: ; , Wherein: the starting point coordinates of the optimized track are obtained; Is the starting point of the original track; the end point coordinates of the optimized track are obtained; Is the end point of the original trajectory.
  4. 4. A method of unmanned aerial vehicle 3D printing system that combines trajectory curvature optimization with end compensation according to claim 3, wherein the trajectory optimization achieves a balance of flying feasibility and smoothness by optimizing the variation of adjacent points of the smoothed trajectory and the difference between the trajectory and the original design trajectory while satisfying curvature constraints.
  5. 5. The method of combining trajectory curvature optimization with end-compensation for a 3D printing system of a drone according to claim 4, wherein the optimized smoothed trajectory γ(s) is obtained by minimizing the maximum deviation between the smoothed trajectory and the original trajectory: ; Wherein, the Objective function values optimized for trajectory smoothing; Summing all pairs of adjacent points in the trajectory; Optimized smooth track Coordinates of the discrete points; Track No From point to point A displacement vector of +1 points; Squared as euclidean norm.
  6. 6. The method of claim 1, wherein in step S3, the smooth flight trajectory is checked for time parameterization and dynamic feasibility to generate corresponding speed and acceleration planning information; Limiting acceleration a and jerk j (jerk) of the flying platform ensures that the flying platform can perform smoothly according to the trajectory: , the extrusion flow Q(s) and the track speed v(s) are synchronously controlled, and the relation is satisfied: , Wherein, the Is the nozzle cross-sectional area, k is the material flow coefficient.
  7. 7. The method of claim 1, wherein in step S4, the remaining geometric error after the trajectory optimization is calculated for measuring the spatial deviation of the optimized smooth trajectory from the original design trajectory: , Wherein, the Is the first Residual geometric error vectors of the individual track points; First for original design track Coordinates of the individual points; to optimize the post-smoothing track Coordinates of the individual points; Is the total number of discrete points of the track.
  8. 8. A system in a method of a unmanned 3D printing system based on a combination of trajectory curvature optimization and end compensation as claimed in any one of claims 1 to 7, comprising a trajectory optimization module, a kinetic feasibility check module, an end compensation distribution module, an execution and closed loop control module and a sensing system; The system comprises a track optimizing module, a dynamic feasibility checking module, an end compensation distribution module, an execution and closed-loop control module, a real-time closed-loop feedback adjustment module and a sensing system, wherein the track optimizing module is used for carrying out smooth processing on an original track to generate a smooth track meeting dynamic constraint, the dynamic feasibility checking module is used for carrying out time parameterization on the smooth track and limiting acceleration and jerk of a flight platform, the end compensation distribution module distributes errors to an end compensation mechanism according to residual geometric errors after the smooth track to ensure error correction within the maximum travel range of the end compensation mechanism, the execution and closed-loop control module is used for controlling the flight platform and the end compensation mechanism to execute optimized track and carry out real-time closed-loop feedback adjustment, and the sensing system comprises a positioning module, an attitude sensor, a mechanical state sensor and a displacement sensor and is used for monitoring the position, the attitude and the mechanical state of the flight platform and providing feedback for closed-loop control.

Description

Unmanned aerial vehicle 3D printing system combining track curvature optimization and tail end compensation and method thereof Technical Field The invention relates to the technical field of unmanned aerial vehicle 3D printing method and system combining track curvature optimization and tail end compensation. Background At present, trajectory planning of unmanned aerial vehicles in 3D printing (especially building or large-scale structure printing) is mostly directly performed along a design path, including sharp geometric features such as right angles. In the prior art, a secondary positioning system is adopted to correct the position and posture deviation (CN 115520406A) of the unmanned aerial vehicle caused by air flow drift in real time. There is also a scheme that a positioning identification unit is arranged on a flight path of an unmanned aerial vehicle, and real-time correction is performed on the path based on collected position information, so that printing accuracy (CN 109113343B) is improved. However, due to inertial, attitude adjustment lag, and kinetic constraints of the flying platform, such trajectories are prone to the following problems at sharp corners: And when the aircraft turns at right angles, the attitude adjustment of the aircraft is difficult to complete within a short distance, and the deviation between the actual printing path and the theoretical track is obvious. Poor molding quality, and the problems of material accumulation, broken wire, wire drawing and the like often occur at sharp corners, which affect molding precision and surface quality. The compensation is insufficient, namely, even if an end compensation mechanism (such as a Delta parallel arm) is integrated on the flying platform, the working space and the dynamic response capability of the compensation mechanism are insufficient due to the overlarge instantaneous curvature of the original track, so that the error cannot be completely eliminated. The existing scheme is often used for optimizing the flight track or the tail end compensation independently and lacks of a cooperative design of a track-dynamics-compensation mechanism. Therefore, a synergistic optimization method capable of fundamentally eliminating the dynamically infeasible trajectories in the trajectory planning stage and performing residual correction in combination with the end compensating mechanism is needed. Disclosure of Invention The invention aims to provide an unmanned aerial vehicle 3D printing system and a method thereof, wherein controllable geometric deviation is actively introduced in a track planning stage, a design track originally comprising sharp features is converted into a smooth track meeting unmanned aerial vehicle dynamics constraint, and residual error correction is carried out by combining a tail end compensation mechanism, so that the problems of large path deviation, poor forming quality, insufficient compensation and the like of the unmanned aerial vehicle at a sharp corner are systematically solved, and printing precision and reliability are improved. In order to achieve the above purpose, the present invention adopts the following technical scheme: An unmanned aerial vehicle 3D printing system combining track curvature optimization and end compensation comprises a track optimization module, a dynamic feasibility checking module, an end compensation distribution module, an execution and closed-loop control module and a sensing system; The system comprises a track optimizing module, a dynamic feasibility checking module, an end compensation distribution module, an execution and closed-loop control module, a real-time closed-loop feedback adjustment module and a sensing system, wherein the track optimizing module is used for carrying out smooth processing on an original track to generate a smooth track meeting dynamic constraint, the dynamic feasibility checking module is used for carrying out time parameterization on the smooth track and limiting acceleration and jerk of a flight platform, the end compensation distribution module distributes errors to an end compensation mechanism according to residual geometric errors after the smooth track to ensure error correction within the maximum travel range of the end compensation mechanism, the execution and closed-loop control module is used for controlling the flight platform and the end compensation mechanism to execute optimized track and carry out real-time closed-loop feedback adjustment, and the sensing system comprises a positioning module, an attitude sensor, a mechanical state sensor and a displacement sensor and is used for monitoring the position, the attitude and the mechanical state of the flight platform and providing feedback for closed-loop control. In addition, the invention also provides a method for combining trajectory curvature optimization and end compensation based on the unmanned aerial vehicle 3D printing system, which comprises the following steps: step S1,