Coactive design of explainable agent-based task planning and deep reinforcement learning for human-UAVs teamwork

Unmanned Aerial Vehicles (UAVs) are useful in dangerous and dynamic tasks such as search-and-rescue, forest surveillance, and anti-terrorist operations. These tasks can be solved better through the collaboration of multiple UAVs under human supervision. However, it is still difficult for human to monitor, understand, predict and control the behaviors of the UAVs due to the task complexity as well as the black-box machine learning and planning algorithms being used. In this paper, the coactive design method is adopted to analyze the cognitive capabilities required for the tasks and design the interdependencies among the heterogeneous teammates of UAVs or human for coherent collaboration. Then, an agent-based task planner is proposed to automatically decompose a complex task into a sequence of explainable subtasks under constrains of resources, execution time, social rules and costs. Besides, a deep reinforcement learning approach is designed for the UAVs to learn optimal policies of a flocking behavior and a path planner that are easy for the human operator to understand and control. Finally, a mixed-initiative action selection mechanism is used to evaluate the learned policies as well as the human’s decisions. Experimental results demonstrate the effectiveness of the proposed methods.     

俄反恐突袭的巡航导弹技术状态初步分析

2015年10月7日，俄罗斯采用远距离、高精度、大威力的“口径”对陆攻击巡航导弹远程空袭ISIS目标，该事件得到了高度关注。简要介绍了“口径”巡航导弹，并对俄巡航导弹技术状态进行了初步分析。     

终端区点融合进近程序设计方法研究

流量的增长导致终端区拥挤和航班延误,增大了管制压力和公司成本.以长沙黄花国际机场36号跑道为例,空城受限,4条航线汇聚一点,梯度曲折多变,航班排序难,指挥复杂度高.结合我国飞行程序设计和管制间隔要求,根据点融合的基本概念,设计跑道点融合进近程序,确定相关参数.对程序进行容量和下降梯度评估表明,静态容量可达到63架次/h,是当前运行最大流量的3.7倍;下降梯度得到明显改善,为连续下降实施奠定了基础.     

凸轮弹性连杆复合机构的动力学修改

本文以胶印机递纸机构为研究对象，该机构为一两自由度凸轮连杆复合机构。在建立该机构运动弹性动力学（ＫＥＤ）有限元分析模型和现场袂测固有频率的基础上，提出了一种利用实 固有频率数据修正复合机构有限元动力模型的方法。其基本思想是利用机构各个运动位置上的固有频率实测值与有限元模型的计算值之间的加权误差建立目标函数，然后利用优化方法使目标函数极小化，从而求出有限元模型参数的修正值。计算结果表明该方法是简便有     

在制品管理中条码技术的应用

针对面向订单的单件、小批量生产制造企业,设计了一套条码数据采集系统,分析了主要运作流程和功能模块.在在制品的管理中提出了基于不同级别的工件生产状态定义,并给出了相应的加工、检验判定准则.经实际使用证明条码技术运用于工业现场是可行的.     

规则回转体自动铺丝轨迹规划与丝束增减

为满足自动铺丝轨迹的满铺覆性要求，针对现阶段自动铺丝轨迹规划存在的不足，提出了不同的丝束增减算法。首先讨论纤维铺放方向的确定和中心轨迹数量的计算，设计不同铺放方向轨迹的生成算法。然后以丝束重叠系数为重要参数，对于纤维局部堆积和空缺问题提出单侧纤维裁剪算法和双侧纤维裁剪算法，并对裁剪后的重叠区域和间隙区域进行面积求解，使得纤维丝束均匀覆于芯模表面。最后基于CATIA CAA二次开发平台，将上述算法集成到纤维铺放CAD系统中，通过运动仿真系统验证算法的正确性。利用提出的丝束增减算法，实现了间隙/重叠区的均匀分布，尽量降低了富树脂区等相关缺陷的聚集对性能的不良影响。     

Optimization of beamforming and path planning for UAV-assisted wireless relay networks

Recently, unmanned aerial vehicles （UAVs） acting as relay platforms have attracted considerable attention due to the advantages of extending coverage and improving connectivity for long-range communications. Specifically, in the scenario where the access point （AP） is mobile, a UAV needs to find an efficient path to guarantee the connectivity of the relay link. Motivated by this fact, this paper proposes an optimal design for beamforming （BF） and UAV path planning. First of all, we study a dual-hop amplify-and-forward （AF） wireless relay network, in which a UAV is used as relay between a mobile AP and a fixed base station （BS）. In the network, both of the AP and the BS are equipped with multiple antennas, whereas the UAV has a single antenna. Then, we obtain the output signal~to-noise ratio （SNR） of the dual-hop relay network. Based on the criterion of maximizing the output SNR, we develop an optimal design to obtain the solution of the optimal BF weight vector and the UAV heading angle. Next, we derive the closed-form outage probability （OP） expression to investigate the performance of the dual-hop relay network conveniently. Finally, computer simulations show that the proposed approach can obtain nearly optimal flying path and OP performance, indicating the effectiveness of the proposed algorithm. Furthermore, we find that increasing the antenna number at the BS or the maximal heading angle can significantly improve the performance of the considered relay network.     

基于遗传模拟退火算法的无人机航迹规划

航迹规划技术是无人机任务规划系统中重要的核心技术之一,无人机飞行空间广阔,需要一种快速搜索最佳路径的方法.首先在飞行区域中建立数字地图模型和防空威胁区模型,在满足无人机飞行约束条件的情况下,为无人机航迹规划提供一种遗传模拟退火算法,充分利用模拟退化算法的概率突跳特性和遗传算法强大的快速搜索能力.仿真结果表明,使用该算法无人机能够自动避开模拟数字地图的威胁区,搜索出一条安全有效航迹,并保证航线的完整性和最优性.     

基于三维空域网格的低空飞行航迹战略规划方法

针对复杂低空环境下航空应急救援飞行安全问题,提出了一种基于三维空域网格的飞行航迹战略规划方法。将空域网格化分成多个飞行航迹节点,同时考虑地形、气象、飞行规则以及航空器性能等多种约束,使用改进的A*算法搜索单个航空器的最优飞行航迹。在单个航空器初始飞行航迹基础上,结合时间窗原理,提出两种方法解决了多机无冲突航迹战略规划问题。最后,通过案例仿真验证了方法的有效性。     

民用飞机试飞规划与管理软件适用性研究

飞行试验是民机研制的重要手段,也是飞机取得适航证的必经过程。随着现代大型民用飞机的设计越来越复杂,试飞制约因素越来越多样,任务量越来越庞大。试飞成为制约型号进度和研制成本的重要因素。对于试飞工作者而言,必须采用科学的方法对试飞任务进行合理规划和管理。为此,国内某飞机设计研究院历时三年,开发了一款用于试飞任务管理的软件——民用飞机试飞规划与管理软件(Flight Test Control System,简称FTCS)。以国内某型号飞机试飞为例,对FTCS的适用性进行了分析和评估,为FTCS的应用和发展提供建议。