吸气式高超声速飞行器助推-巡航轨迹优化

针对吸气式高超声速巡航飞行器建立了纵向平面内的二维轨迹优化模型(包括火箭助推段和吸气式飞行段),其中大气模型、气动力模型和发动机模型均建立了比较详细的模型,能够比较全面、准确地描述吸气式高超声速巡航飞行器的特征;基于配点法建立了适用于高超声速巡航飞行器助推-巡航轨迹优化的方法,在求解非线性规划时引入了规范化处理、稀疏分析和偏导数计算方法等,以提高优化效率;对吸气式高超声速飞行器助推-巡航轨迹进行了优化研究,分析了典型设计参数变化对最优轨迹的影响。仿真结果表明:所建立的方法能够快速、高精度求解吸气式高超声速巡航飞行器轨迹优化问题,并且能够方便地分析设计参数变化对最优轨迹的影响,可用于吸气式高超声速飞行器飞行剖面设计与优化。     

Behavior pattern mining based on spatiotemporal trajectory multidimensional information fusion

Trajectory data mining is widely used in military and civil applications, such as early warning and surveillance system, intelligent traffic system and so on. Through trajectory similarity measurement and clustering, target behavior patterns can be found from massive spatiotemporal trajectory data. In order to mine frequent behaviors of targets from complex historical trajectory data, a behavior pattern mining algorithm based on spatiotemporal trajectory multidimensional information fusion is proposed in this paper. Firstly, spatial–temporal Hausdorff distance is proposed to measure multidimensional information differences of spatiotemporal trajectories, which can distinguish the behaviors with similar location but different course and velocity. On this basis, by combining the idea of k-nearest neighbor and density peak clustering, a new trajectory clustering algorithm is proposed to mine behavior patterns from trajectory data with uneven density distribution. Finally, we implement the proposed algorithm in simulated and radar measured trajectory data respectively. The experimental results show that the proposed algorithm can mine target behavior patterns from different complex application scenarios more quickly and accurately compared to the existing methods, which has a good application prospect in intelligent monitoring tasks.     

考虑移动目标不确定行为方式的轨迹预测方法

针对现有方法难以预测出符合飞行移动目标不确定行为方式轨迹的问题,提出基于逆强化学习的飞行移动目标轨迹预测方法,通过学习目标行为偏好以及模拟目标行为决策过程的方式预测目标的移动轨迹。首先基于深度神经网络建立目标的行为决策模型与行为偏好模型,然后通过最大熵逆强化学习方法交替地学习模型参数。为了有效地学习目标的不确定行为特征,采用监督学习的方法学习出目标示例轨迹概率分布模型,用于指导目标行为偏好模型的训练以及初始化目标行为决策模型,同时通过对目标行为偏好模型进行预训练的方式提高其训练质量。仿真结果表明,提出的飞行移动目标轨迹预测方法可通过学习到的目标行为决策模型较为准确地模拟目标的行为方式,预测的目标轨迹分布与真实的目标轨迹分布在Kullback Leibler(KL)散度下的相似度可达0.24。     

Trajectory prediction in pipeline form for intercepting hypersonic gliding vehicles based on LSTM

The interception problem of Hypersonic Gliding Vehicles (HGVs) has been an important aspect of missile defense systems. In order to provide interceptors with accurate information of target trajectory, a model based on an improved Long Short-Time Memory (LSTM) network for trajectory prediction pipeline is proposed for the interception of a skip gliding hypersonic target. Firstly, for trajectory prediction required by intercepting guidance laws, the altitude, velocity and velocity direction of the target are formulated in the form of analytic functions, consisting of linear decay terms and amplitude decay sinusoidal terms. Then, the dynamic characteristics of the model parameters are analyzed, and the target trajectory prediction pipeline is proposed with the prediction error considered. Finally, an improved LSTM network is designed to estimate parameters in a dynamically-updated manner, and estimation results are used for the calculation of the final trajectory prediction pipeline. The proposed prediction algorithm provides information on the velocity vector for midcourse guidance with the effect of prediction errors on interception taken into account. Simulation is conducted and the results show the high accuracy of the algorithm in HGVs’ trajectory prediction which is conducive to increasing the interception success rate.     

Trajectory optimisation in electrical discharge machining of three-dimensional curved and twisted channels

Numerical control electrical discharge machining(NC EDM) is one of the most widely used machining technologies for manufacturing a closed blisk flow path, particularly for three-dimensional(3D) curved and twisted flow channels. In this process, tool electrode design and machining trajectory planning are the key factors affecting machining accessibility and efficiency. Herein, to reduce the difficulty in designing the electrode and its motion path in the closed curved and twisted channels, a heur...     

Path,feedrate and trajectory planning for free-form surface machining: A state-of-the-art review

Nowadays, free-form surfaces have been widely used in various industrial fields. They are usually machined by CNC machine tools, but recently have also begun to be manufactured by industrial robotic arm manipulators, thanks to low cost, large operation reaching space and high machining flexibility of robot. So far, various methodologies have been proposed to improve efficiency and quality of free-form surface machining, thus this paper aims at providing a state-of-the-art review on research advances in free-form surface machining. In this review, tool path generation, feedrate scheduling in Cartesian space and trajectory planning in joint space are focused for both CNC machining and robot machining, and their research statues, existing difficulties and key issues are discussed in detail. Finally, the feasible routes, breakthrough points and future development trend are also expounded.     

Smooth free-cycle dynamic soaring in unspecified shear wind via quadratic programming

Harvesting wind energy is promising for extending long-endurance flights, which can be greatly facilitated by a flight technique called dynamic soaring. The presented study is concerned with generating model-based trajectories with smooth control histories for dynamic soaring maneuvers exploiting wind gradients. The desired smoothness is achieved by introducing a trigonometric series parameterization for the controls, which are formulated with respect to the normalized time.Specifically, the per...     

无人机群体视角下的轨迹预测CSCD

利用无人机对观测目标的运动轨迹进行预测是当前无人系统领域的关键任务之一。目前的目标轨迹预测研究通常基于单一无人机所采集的轨迹数据,但由于场景中障碍物以及视角倾斜等因素的影响,单无人机不易稳定监测目标具体位置,容易导致目标丢失。而且,现有利用无人机的目标轨迹预测一般基于鸟瞰视角,没有发挥出无人机的灵活性。随着无人机集群协同技术的发展,无人机群体视角为目标全方位监测提供了新的思路,在解决目标丢失和目标遮挡问题中具有明显的优势。同时,基于多无人机的位姿估计可以估计出目标的准确三维坐标,为无人机的灵活视角观测提供基础。因此,从轨迹预测的相关工作出发,探讨无人机群体视角下轨迹预测中面临的挑战和解决思路,以期对未来的轨迹预测研究以及集群协同技术发展提供一定帮助。     

Optimal trajectory design accounting for the stabilization of linear time-varying error dynamics

This study is dedicated to the development of a direct optimal control-based algorithm for trajectory optimization problems that accounts for the closed-loop stability of the trajectory tracking error dynamics already during the optimization. Consequently, the trajectory is designed such that the Linear Time-Varying(LTV) dynamic system, describing the controller’s error dynamics, is stable, while additionally the desired optimality criterion is optimized and all enforced constraints on the traje...     

A novel visual servo method for space manipulators by planning jerk

A novel trajectory planning method for space manipulators is proposed in this article, which can generate trajectory in Cartesian space with continuous joint jerk. The key idea is that, given the desired position for an individual joint, the corresponding joint trajectory is generated in a way like a controller. The generated jerk acts as the controller’s output driving an ideal third-order system to arrive at the desired position, with no need for discrete points in advance. In real applications, the visual servo task is accomplished hierarchically. Since the desired pose in Cartesian space measured by cameras concerns multi degrees of freedom (DOF), desired positions for individual joints are obtained by inverse-kinematics model. Then, joint trajectories are generated as above. To improve the trajectory’s smoothness, a bridging matrix is implemented to ensure that the desired pose varies continuously. Simulation and experimental results show that the proposed method is effective to track targets with different kinds of motion, i.e. can track the input-bounded signal asymptotically.