Optimizing the lay-up of composite tapes based on improved geodesic strategy for automated tape placement

Author(s):  
Peng Zhang ◽  
Zhenhua Zhou ◽  
Gengbiao Chen ◽  
Shuhan Chen

The use of composite materials in aerospace, automotive and ship industry allows manufacturing lighter and more efficient mechanical structures. The major limiting factors are the high-manufacturing costs and low-production rates. Automated tape placement is one alternative process to overcome the limiting factors. Due to the complex contour of the mandrel, the lay-up paths of the contiguous tapes are not parallel along their lengths, which eventually introduce gaps or overlaps between the edges of tapes. Overlaps and excessive gaps are undesirable as they will decrease the strength of the resulting composite member. In this paper, a novel trajectory planning method for automated tape placement, entitled improved geodesic strategy, is proposed. The strategy aims to optimize the relationship between adjacent tapes. At the same time, the distortion of composite tape is also specified in order to prevent wrinkling. The principle and characteristic of the algorithm are presented. The method is investigated on the airfoil of an unmanned aerial vehicle and some of the results are presented in this paper.

Author(s):  
Jun Tang ◽  
Jiayi Sun ◽  
Cong Lu ◽  
Songyang Lao

Multi-unmanned aerial vehicle trajectory planning is one of the most complex global optimum problems in multi-unmanned aerial vehicle coordinated control. Results of recent research works on trajectory planning reveal persisting theoretical and practical problems. To mitigate them, this paper proposes a novel optimized artificial potential field algorithm for multi-unmanned aerial vehicle operations in a three-dimensional dynamic space. For all purposes, this study considers the unmanned aerial vehicles and obstacles as spheres and cylinders with negative electricity, respectively, while the targets are considered spheres with positive electricity. However, the conventional artificial potential field algorithm is restricted to a single unmanned aerial vehicle trajectory planning in two-dimensional space and usually fails to ensure collision avoidance. To deal with this challenge, we propose a method with a distance factor and jump strategy to resolve common problems such as unreachable targets and ensure that the unmanned aerial vehicle does not collide into the obstacles. The method takes companion unmanned aerial vehicles as the dynamic obstacles to realize collaborative trajectory planning. Besides, the method solves jitter problems using the dynamic step adjustment method and climb strategy. It is validated in quantitative test simulation models and reasonable results are generated for a three-dimensional simulated urban environment.


2012 ◽  
Vol 62 (6) ◽  
pp. 375-381 ◽  
Author(s):  
Hongfu Liu ◽  
Shaofei Chen ◽  
Lincheng Shen ◽  
Jing Chen

Author(s):  
Jiayu Tang ◽  
Xiangmin Li ◽  
Jinjin Dai

The paper studies how to plan the trajectories of an unmanned combat aerial vehicle (UCAV) that releases its airborne weapons and presents an online trajectory planning method based on threat modeling. Firstly, it analyzes the aerodynamic characteristics, engine thrust and fuel characteristics of the UCAV and builds its dynamic and kinematic models. Secondly, the trajectory planning model of the UCAV is formulated with flight performance constraints and battlefield threat constraints considered. To improve the accuracy of ground attacks, the envelope of a guided bomb's acceptable region of weapon release is studied, and the release center and posture of the guided bomb work as terminal planning conditions. Thirdly, an online trajectory planning method is proposed. With the help of threat modeling, the complicated trajectory planning problem is transformed into a simplified situation classification. Finally, the simulation results demonstrate that the online planning method proposed in the paper can provide feasible trajectories for a UCAV to succeed in releasing its airborne weapons.


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