人工蜂群算法的无人机航路规划与平滑

航路规划是无人机(UAV)作战任务规划系统的关键组成部分,目标是在适当的时间内为UAV计算出最优或次最优的飞行航路.人工蜂群(ABC)算法是一种最新发展的模拟昆虫王国中蜜蜂群体寻找优良蜜源的群体智能优化算法.采用人工蜂群算法完成无人机的平滑航路规划,首先阐述了人工蜂群算法的基本原理,然后将无人机航路规划问题通过建模转换成为一个多维函数优化问题,利用人工蜂群算法的优势,找到多维函数的最优解,最后对优化后的航路进行了平滑,使UAV对规划后的航路可飞.仿真实验结果表明,此方法可有效规划出航路,且所规划的航路可飞.     

Asynchronous double-precision windows based unmanned aerial vehicle real-time path planning

A real-time path planning approach based on asynchronous double-precision windows is proposed for unmanned aerial vehicles (UAVs). In this proposed method, cursory paths and elaborate paths are planned respectively in the global and local windows. Specifically, global cursory path planner and local elaborate path planner are integrated by rolling two windows on different frequencies with different modes. Simulation results demonstrate that the proposed approach is effective for realizing a balance between t...     

Image processing acceleration for intelligent unmanned aerial vehicle on mobile GPU

In this paper, we present an algorithm for providing visually-guided unmanned aerial vehicle (UAV) control using visual information that is processed on a mobile graphic processing unit (GPU). Most real-time machine vision applications for UAVs exploit low-resolution images because the shortage of computational resources comes from size, weight and power issue. This leads to the limitation that the data are insufficient to provide the UAV with intelligent behavior. However, GPUs have emerged as inexpensive parallel processors that are capable of providing high computational power in mobile environments. We present an approach for detecting and tracking lines that use a mobile GPU. Hough transform and clustering techniques were used for robust and fast tracking. We achieved accurate line detection and faster tracking performance using the mobile GPU as compared with an x86 i5 CPU. Moreover, the average results showed that the GPU provided approximately five times speedup as compared to an ARM quad-core Cortex-A15. We conducted a detailed analysis of the performance of proposed tracking and detection algorithm and obtained meaningful results that could be utilized in real flight.     

无人水面艇双目立体视觉系统设计

针对雷达不能利用目标的颜色等属性和水面多路径反射的干扰等问题,建立无人水面艇双目立体视觉系统,为实现无人水面艇的自主避障和目标跟踪等任务提供基础。采用两个IEEE1394接口的数字摄像机在无人水面艇上构建双目立体视觉系统,进而编程拍摄左右两幅图像并标定摄像机。结果表明,所构建的双目立体视觉系统可以用于无人水面艇视觉技术的研究。所设计的双目立体视觉系统对无人水面艇具有重要的研究意义。     

Path planning for unmanned aerial vehicle under complicated conditions and hazards

The flight of an unmanned aerial vehicle under complicated conditions and hazards is considered. Hazards are given in terms of 2D relief. To find the optimal 2D path minimizing the risk given constraints on flight time and velocity, the problem with the non-given boundary condition is transformed to the problem with the fixed flight time and the boundary problem solved numerically. The found 2D path is used to construct the polynomial approximation of the 3D path taking into account the local relief.     

基于GPU的点模型实时绘制

近几年随着GPU的可编程能力的增强,很多基于点的绘制算法都可以移植到GPU上来实现,这样既可以让CPU有时间来处理其他事,又可以通过GPU提高算法的运行速度。由于目前的GPU不支持epsilon-z-buffering算法,大部分基于GPU的绘制算法都是通过Multi-pass绘制来达到较高的绘制质量。然而,这些算法需要在第一和第二个pass中光栅化大量的可能可见的面圆,并在第二个pass的像素shader中对这些可能可见的面圆进行大量的计算。本文提出了一种基于GPU的改进Multi-pass绘制算法,与前面的Multi-pass算法相比,我们的算法只需在第一个pass中对大量可能可见的面圆进行光栅化和深度测试后,便可求出所有可见面圆,即离视点最近的面圆。然后在第二个pass中只对这些可见面圆进行光栅化和逐像素计算,从而避免了大量不必要的计算。     

基于改进A~*算法的灾后井下无人机航迹规划

针对传统A~*算法应用在煤矿灾后井下环境侦测的无人机航迹规划中存在搜索点冗余、遇到突发威胁时实时性较差等问题,提出了一种逆向变权重稀疏A~*算法。根据无人机自身性能约束及灾后井下威胁模型,从目标点到起始点进行全局静态航迹规划,避免大量无效搜索;根据无人机执行任务的需要设置不同权重系数,得到侧重航程或安全的航迹;通过引入次目标点策略,仅对被突发威胁覆盖的航迹进行修正,可在短时间内有效避开突发威胁。仿真结果表明,利用该算法进行航迹规划用时较短,无人机受到的威胁较小,可有效保障航迹规划的实时性和安全性。     

Test generation from state based use case models

We present a strategy for the automatic generation of test cases from parametrised use case templates that capture control flow, state, input and output. Our approach allows test scenario selection based on particular traces or states of the model. The templates are internally represented as CSP processes with explicit input and output alphabets, and test generation is expressed as counter-examples of refinement checking, mechanised using the FDR tool. Soundness is addressed through an input–output conformance relation formally defined in the CSP traces model. This purely process algebraic characterisation of testing has some potential advantages, mainly an easy automation of conformance verification and test case generation via model checking, without the need to develop any explicit algorithm.     

基于Dubins曲线的无人直升机轨迹规划

为提高无人直升机的控制性能,提出了一种基于Dubins曲线的轨迹规划算法,并对其各个部分的实现进行了研究和设计。该算法利用Dubins曲线原理对定点飞行任务的两点或者多点目标进行分析计算,寻找出一条最短的飞行路径,从而提高了飞行效率。根据无人直升机系统多变量、非线性和强耦合的特点,采用串级PID方法设计了飞行控制器,该控制器能够修正无人直升机的姿态和位置,从而提高了轨迹规划的稳定性和准确性。最后,以某小型无人直升机为实验平台表明了该轨迹规划算法和控制器的可行性。     

基于云台摄像机的自适应无人机跟踪系统

针对当前光电跟踪系统作用距离短、目标跟踪易丢失、视频图像抖动等问题,设计了一种适用于远近距离目标稳定跟踪的系统.首先利用云台摄像机连续采集图像;其次图像处理模块预测目标图像区域进行目标检测;然后利用目标大小进行镜头的变倍变焦自适应控制;最后将视场划分三个区域,根据连续时间目标偏移中心趋势及所在区域位置逐步控制云台的速度...     

基于信赖域算法的机械臂时间最优轨迹规划

为了提高机械臂的工作效率,提出了一种新的时间最优轨迹规划方法.通过逆运动学运算得到与任务空间轨迹对应的关节空间位置序列,采用7次B样条曲线构造关节空间插值轨迹,将运动学约束转换为对B样条轨迹曲线控制顶点的约束,并适当放大约束条件,然后采用信赖域方法求解时间优化问题,从而规划出速度、加速度和脉动均连续且满足运动学约束的时间最优轨迹.仿真结果验证了所提出时间最优轨迹规划方法的有效性.     

Target following with motion prediction for unmanned surface vehicle operating in cluttered environments

The capability of following a moving target in an environment with obstacles is required as a basic and necessary function for realizing an autonomous unmanned surface vehicle (USV). Many target following scenarios involve a follower and target vehicles that may have different maneuvering capabilities. Moreover, the follower vehicle may not have prior information about the intended motion of the target boat. This paper presents a trajectory planning and tracking approach for following a differentially constrained target vehicle operating in an obstacle field. The developed approach includes a novel algorithm for computing a desired pose and surge speed in the vicinity of the target boat, jointly defined as a motion goal, and tightly integrates it with trajectory planning and tracking components of the entire system. The trajectory planner generates a dynamically feasible, collision-free trajectory to allow the USV to safely reach the computed motion goal. Trajectory planning needs to be sufficiently fast and yet produce dynamically feasible and short trajectories due to the moving target. This required speeding up the planning by searching for trajectories through a hybrid, pose-position state space using a multi-resolution control action set. The search in the velocity space is decoupled from the search for a trajectory in the pose space. Therefore, the underlying trajectory tracking controller computes desired surge speed for each segment of the trajectory and ensures that the USV maintains it. We have carried out simulation as well as experimental studies to demonstrate the effectiveness of the developed approach.     

基于ARM的无人机真空速测量系统设计

设计了以ARM微处理器为核心的中央控制处理单元,用于无人机真空速测量系统中.通过公式分解,并采用线性低次插值算法,有效解决了真空速解算公式复杂的缺点;同时利用ARM的UART串口总线,实现了传感器输出特性曲线、真空速的上位机实时显示,使系统相对误差控制在2.5％以内.测试结果证明了该系统具有良好的实效性和稳定性、精度高,优于传统的测量装置.     

Resolution-adaptive risk-aware trajectory planning for surface vehicles operating in congested civilian traffic

The growing variety and complexity of marine research and application oriented tasks requires unmanned surface vehicles (USVs) to operate fully autonomously over long time horizons even in environments with significant civilian traffic. In order to address this challenge, we have developed a lattice-based 5D trajectory planner for USVs. The planner estimates collision risk and reasons about the availability of contingency maneuvers to counteract unpredictable behaviors of civilian vessels. The planner also incorporates avoidance behaviors of the vessels into the search for a dynamically feasible trajectory to minimize collision risk. In order to be computationally efficient, it dynamically scales the control action primitives of a trajectory based on the distribution and concentration of civilian vessels while preserving the dynamical feasibility of the primitives. We present a novel congestion metric to compare the complexity of different scenarios when evaluating the performance of the planner. Our results demonstrate that the basic version of the risk and contingency-aware planner (RCAP) significantly decreases the number of collisions compared to a baseline, velocity obstacles based planner, especially in complex scenarios with a high number of civilian vessels. The adaptive version of the planner (A-RCAP) improves the computational performance of RCAP by 500 %. This leads to a high replanning rate, which allows shorter traversal distances and smaller arrival times, while ensuring comparable incidence of collisions.     

基于IMOSFLA的有人/无人战斗机协同空战火力分配方法

针对有人/无人战斗机协同空战中的火力分配问题,建立了以目标总存活概率最小和武器消耗数量最少的火力分配多目标优化模型,并提出一种改进的多目标蛙跳算法用于求解问题的Pareto最优解集.该改进算法充分利用混洗蛙跳算法收敛速度快、收敛精度高的算法优势进行全局寻优,利用自适应网格法对非劣解进行维护和更新,并在青蛙种群的全局进化过程中引入Tent混沌变异以避免算法早熟收敛.为便于从求解得到的Pareto最优解集中选择出最优火力分配方案,提出了一种最优火力分配方案的自主选择规则.最后通过仿真实验验证了所提方法的可行性和有效性.实验结果表明,所提方法能有效求解有人/无人战斗机协同空战中的火力分配问题.     

基于改进RRT-connect的四旋翼无人机避障轨迹规划算法

针对四旋翼无人机在低空复杂环境自主巡航所需的航迹规划问题,提出了一种基于快速搜索随机树(RRT-connect)的改进型算法。根据四旋翼无人机的微分平坦特性,合理设计了规划空间;引入转角约束和路径修剪方法,在保证规划实时性的基础上使所规划路径的平均长度缩短了19%;通过B样条函数对路径进行平滑处理,使生成的轨迹具有二阶几何连续性,同时能避免与障碍物区域发生碰撞。经多次重复对比试验,证实了提出算法的有效性、优越性和稳定性。     

基于混合遗传算法的工业机器人最优轨迹规划

为兼顾工业机器人工作效率与轨迹的平稳性,提出一种基于混合遗传算法的二次轨迹规划方案.通过最优时间轨迹规划得到最小执行时间,在最小执行时间内进行最优冲击轨迹规划,进而规划出一条既高效又平滑的运动轨迹.采用五次均匀B样条在关节空间进行快速插值,不仅保证了各关节速度和加速度连续性还保证了各关节冲击的连续性.连续平滑的冲击可以减少机械振动,延长机器人的工作寿命.选用PUMA560为对象进行仿真与实验,结果表明,该方案可以获得比较理想的机器人运动轨迹,所提出的混合遗传算法能有效提高全局寻优的性能和算法运行的稳定性.