Highly reliable relative navigation for multi-UAV formation flight in urban environments

Formation flight of multiple Unmanned Aerial Vehicles (UAVs) is expected to bring significant benefits to a wide range of applications. Accurate and reliable relative position information is a prerequisite to safely maintain a fairly close distance between UAVs and to achieve inner-system collision avoidance. However, Global Navigation Satellite System (GNSS) measurements are vulnerable to erroneous signals in urban canyons, which could potentially lead to catastrophic consequences. Accordingly, on the basis of performing relative positioning with double differenced pseudoranges, this paper develops an integrity monitoring framework to improve navigation integrity (a measure of reliability) in urban environments. On the one hand, this framework includes a fault detection and exclusion scheme to protect against measurement faults. To accommodate urban scenarios, spatial dependence in the faults are taken into consideration by this scheme. On the other hand, relative protection level is rigorously derived to describe the probabilistic error bound of the navigation output. This indicator can be used to evaluate collision risk and to warn collision danger in real time. The proposed algorithms are validated by both simulations and flight experiments. Simulation results quantitatively reveal the sensitivity of navigation performance to receiver configurations and environmental conditions. And experimental results suggest high efficiency and effectiveness of the new integrity monitoring framework.     

Homotopy based optimal configuration space reduction for anytime robotic motion planning

Anytime sampling-based motion planning algorithms are widely used in practical applications due to limited real-time computing resources. The algorithm quickly finds feasible paths and incrementally improves them to the optimal ones. However, anytime sampling-based algorithms bring a paradox in convergence speed since finding a better path helps prune useless candidates but also introduces unrecognized useless candidates by sampling. Based on the words of homotopy classes, we propose a Homotopy class Informed Preprocessor (HIP) to break the paradox by providing extra information. By comparing the words of path candidates, HIP can reveal wasteful edges of the sampling-based graph before finding a better path. The experimental results obtained in many test scenarios show that HIP improves the convergence speed of anytime sampling-based algorithms.     

基于诱导航线的多无人机编队飞行控制方法

针对无人机编队飞行控制问题,提出了一种基于诱导航线的协同控制方法,僚机根据当前相对于期望位置的误差和长机的飞行状态生成诱导航线并进行跟踪;针对飞行过程中的突发障碍采用改变编队队形的方法进行规避;针对无人机之间可能出现的碰撞情况,根据无人机到达碰撞点的时间以及位置分别从高度以及航向两方面进行躲避,仿真结果表明:采用此方法无人机能够保持稳定的编队,并同时能够躲避飞行过程中的障碍以及避免飞机之间的碰撞。      

无人直升机三维避障方法及仿真

自主避障是无人直升机（UH）在复杂未知环境中执行飞行任务所必须的能力。针对未知环境下UH避障飞行问题,提出了一种新的三维实时避障方法,通过将三维激光雷达探测视野划分成若干不同半径的扇形柱区和等角度分布的直方柱区,结合雷达探测数据判断障碍物分布情况,UH根据避障方法执行相应的规避动作来实现避障飞行。同时提出一种基于CATIA三维建模软件二次开发的三维仿真方法,该方法可以对未知的飞行环境进行三维建模,结合避障方法实现UH在其中的真实避障飞行模拟,并利用该仿真方法验证了三维避障方法的可行性。      

Constant thrust collision avoidance maneuver under thruster failure

In this paper, the collision avoidance maneuver under the chaser’s thruster failure in radial direction is investigated. First, based on the vision measurement, the relative position parameters of the target spacecraft are obtained and the target maneuvre positions are calculated through the isochronous interpolation method. Then, by using coupling effects, the thrusters working time intervals can be computed by the time series analysis method. The perturbations and fuel consumptions are addressed during the computation of the thrusters working time intervals. Next, the switching control law under constant thrust is designed for active collision avoidance maneuvres along a specified trajectory.     

复杂禁飞区高超声速飞行器路径-轨迹双层规划

针对高超声速飞行器在复杂禁飞区的规避场景,为解决现有轨迹规划方法对任务初值依赖性强的问题,提出一种基于双层规划建模的路径-轨迹规划方法。其中,上层为路径规划,为轨迹提供路径点引导信息,避免轨迹陷入局部解;下层为轨迹规划,利用上层输出的路径点信息,将轨迹分割成多个横向机动小的子段,解析求解横纵向飞行剖面,减小运动模型简化误差。数值仿真表明,与现有轨迹优化方法相比,本方法能够选择指标更优的路径,提高了轨迹规划的全局性能;解析飞行剖面制导误差不超过0.03%,解决了大范围横向机动的剖面解析难题。     

一种基于有限视场的移动机器人避障路径规划算法

 提出一种基于传感器的移动机器人避障路径规划算法。考虑到传感器存在视场范围限制的问题,算法仅利用当前单一视场内的有限环境信息,采用两种搜索模式,以机器人当前的运动方向、障碍物边界端点数据及目标点所在方向为依据,在当前视场中搜索合适的路径。这两种搜索模式保证了路径最终收敛到目标点。最后,通过仿真实例验证了算法的有效性。     

基于碰撞检测的自适应阻抗控制机械臂系统(英文)

针对柔性关节机械臂,本文阐述了机械臂能够像人手一样安全操作的方法。3种方法相结合,以便机械臂能够柔顺的接触操作对象并控制接触力在预设定范围内。首先,提出采用虚拟分解法的笛卡尔阻抗控制用来实现机械臂在笛卡尔空间的柔顺控制。其次,引入自适应关节动态补偿器使得机械臂能够实施更为精确的控制。最后,设计了基于笛卡尔力反馈的实时路径规划,从而使机械臂能够检测碰撞并控制接触力。基于碰撞检测的自适应阻抗控制器能够简化其在机械臂上的实施,保持机械臂对环境的友好操作,并且严格满足系统的全局稳定性。实验在4自由度的卫星在轨自维护机械臂平台得以验证。碰撞检测实验和轨迹跟踪实验结果证明了所提出方法的有效性和可行性。     

未知环境中微型飞行器障碍回避与导航技术研究进展

微型飞行器在未知环境中自主飞行,须具备障碍回避和导航的能力,关键技术包括：环境探测、动态航迹规划以及航路跟踪。本文综述了近年来国内外在该领域的主要研究进展,围绕微型飞行器障碍回避与导航技术的概念内涵和问题描述障碍回避与导航技术中的飞行环境探测方法与传感器、飞行环境要素的模型表征及航迹规划算法等方面,系统地给予了阐述与分析,最后指出了微型飞行器动态障碍回避与导航技术中需要进一步研究的问题,旨在为微型飞行器的自主导航技术的发展提供参考。     

移动Ad hoc网络中的多信道预约MAC协议

移动Ad hoc网络中为有效利用无线信道资源,提出一种多信道预约媒质接入(MRMA, Multichannel Reservation Multiple Access)协议.该协议在公共信道上发送Request-to-Send/Clear-to-Send(RTS/CTS)分组预约信道,采用基于ID的信道选择方案选择无冲突的业务信道传输数据分组,目的节点成功接收完数据分组后在另一个公共信道上回复Acknowledgment(ACK)分组,有效避免了暴露终端问题,使得相邻通信节点对可以同时使用相同的业务信道传输数据分组,空分复用大大提高了无线资源的利用率.采用多信道分别进行不同通信对的业务分组传输解决了在单信道上传输所带来的隐藏终端问题.仿真结果表明,在总信道利用率和平均分组延迟性能上,MRMA协议明显优于IEEE 802.11 RTS/CTS协议.