Obstacle avoidance in person following for vision-based autonomousland vehicle guidance using vehicle location estimation and quadraticpattern classifier

An obstacle avoidance method for use in person following for vision-based autonomous land vehicle (ALV) guidance is proposed. This method is based on the use of vehicle location estimation and a quadratic pattern classifier, and aims to guide the ALV to follow a walking person in front by navigating along a derived collision-free path. Before generating the collision-free path, the person's location is obtained from extracted objects in the image by a person detection method. The object closest to a predicted person location is regarded as the followed person and the remaining objects are regarded as obstacles. The collision-free navigation path is designed for ALV guidance in such a way that the ALV not only can keep following the person but also can avoid collision with nearby obstacles. The navigation path results from a quadratic classifier that uses the vehicle and all of the objects in the image as input patterns. A turn angle is then computed to drive the ALV to follow the navigation path. Successful navigation sessions confirm the feasibility of the approach     

基于激光雷达和SLAM的自主行驶小车设计

结合ROS平台、激光雷达和SLAM技术设计出拥有自主移动能力的行驶小车。首先搭建硬件开发平台,配置ROS下的一系列开源功能包,实现路径规划、自主行驶和避障功能。软件部分通过激光雷达的功能包获取周围的环境信息,进行SLAM地图创建,通过导航功能包进行全局路径规划和局部路径规划,小车行驶过程中结合AMCL功能包对移动过程中产生的误差进行修正,小车能够实现自主行驶。     

不确定环境下的侦察无人机自主航路规划仿真

自主式无人机是无人机发展的必然趋势,不确定环境下的航路规划是无人机航路规划研究的新领域.为了研究战时条件下侦察无人机的自主航路规划,根据无人机的控制系统工作方式,建立了仿真模型框架,并在此基础上开展仿真研究.首先,针对战时条件下侦察无人机执行任务的不确定环境,从战场使用的实际情况出发,建立了基于目标存在概率的环境信息模型;然后,根据无人机机载探测设备探测区域建立了探测模型,提出了航路控制决策模型,并采用动态规划进行航路规划.最后,设计了一个无人机侦察不确定环境的仿真试验,仿真结果验证了该方法的有效性.     

一种轮式机器人轨迹跟踪控制算法的研究

针对轮式机器人轨迹跟踪控制问题，提出了一种轨迹跟踪控制算法。通过对轮式机器人进行运动学分析，建立了运动学模型来描述其在水平面内的运动规律；提出了轨迹跟踪控制算法，并对迹跟踪控制算法进行仿真试验，直线轨迹跟踪的纵向偏差 0.09m，横向偏差 0.06m， 航向角偏差 3.7°；曲线轨迹跟踪的纵向偏差 0.13m，横向偏差 0.09m，航向角偏差 5.1°。仿真试验结果表明本研究所设计的轨迹跟踪控制算法具有良好的动态响应，可以支撑实际应用。     

基于EKF的脉冲星导航在转移轨道的应用

为提高深空探测器在转移轨道的自主导航能力,提出了一种基于EKF的X射线脉冲星自主导航定位系统.以X射线探测器获得的脉冲到达时间为量测量,以深空探测器轨道动力学模型为状态方程,利用扩展卡尔曼滤波算法进行状态估计.以美国火星探路者任务深空转移段为例进行了仿真实验,仿真结果表明了该方法的可行性与有效性,能够完成深空探测器转移段的自主导航任务.     

Steering control in autonomous vehicles using deep reinforcement learning

A novel deep reinforcement learning-based steering control method of autonomous vehicles is proposed. A distortionless compressing method of action space is presented. Convolutional neural networks (CNNs) are designed to serve as an action policy. Driver experience is investigated and modeled to optimize policy of new actions exploration. Experimental results show that the proposed algorithm has better robustness and smoothness. Moreover, it is applicable to different roads, velocities or wire-control systems.     

Development of Steering Control System for Autonomous Vehicle Using Geometry‐Based Path Tracking Algorithm

In this paper, a steering control system for the path tracking of autonomous vehicles is described. The steering control system consists of a path tracker and primitive driver. The path tracker generates the desired steering angle by using the look‐ahead distance, vehicle heading, and a lateral offset. A method for applying an autonomous vehicle to path tracking is an advanced pure pursuit method that can reduce cutting corners, which is a weakness of the pure pursuit method. The steering controller controls the steering actuator to follow the desired steering angle. A servo motor is installed to control the steering handle, and it can transmit the steering force using a belt and pulley. We designed a steering controller that is applied to a proportional integral differential controller. However, because of a dead band, the path tracking performance and stability of autonomous vehicles are reduced. To overcome the dead band, a dead band compensator was developed. As a result of the compensator, the path tracking performance and stability are improved.     

Obstacle detection in single images with deep neural networks

Obstacle detection in single images is a challenging problem in autonomous navigation on low-cost condition. In this paper, we introduce an approach for obstacle detection in single images with deep neural networks. We propose the followings: (1) a deep model combined with other deep neural network for obstacle detection; (2) a method to segment obstacles and infer their depths. Among others, both local and global information are generated in our method for better classification and portability. Experiments are performed on the open datasets and images captured by our autonomous vehicle. The results show that our method is effective in both obstacle detection and depth inference.     

Fast Test Pattern Generation for Sequential Circuits Using Decision Diagram Representations

The paper presents a novel hierarchical approach to test pattern generation for sequential circuits based on an input model of mixed-level decision diagrams. A method that handles, both, data and control parts of the design in a uniform manner is proposed. The method combines deterministic and simulation-based techniques. On the register-transfer level, deterministic path activation is combined with simulation based-techniques used for constraints solving. The gate-level local test patterns for components are randomly generated driven by high-level constraints and partial path activation solutions. Experiments show that high fault coverages for circuits with complex sequential structures can be achieved in a very short time by using this approach.     

火星探测环绕段自主光学导航算法研究（特约）

针对火星探测环绕段自主导航需求,结合初始轨道参数及光学导航相机拍摄的火星图像,提出了一种基于火星本体的高精度自主导航方法。该方法首先利用初始轨道参数得到火星在导航相机像平面下的投影图,然后将该投影图与导航相机拍摄的火星图进行匹配融合得到火星的边缘图,后利用该边缘图进行精确椭圆拟合,继而可实现器-火视线距和视线矢量的测量,在算法仿真过程中充分考虑到了工程实现中可能会遇到的图像旋转、平移及尺寸变换问题,仿真结果表明:提出的利用先验信息的图像融合测量算法较单独利用火星图像进行导航测量的方法,精度和可靠度均有较大提升,可满足火星探测环绕段的任务需求。     

基于迭代优化的拦射空战瞄准引导方法

为解决无人战斗机使用空空导弹自主攻击目标的问题,提出了一种基于迭代优化的拦射瞄准引导法。首先描述了自主拦射攻击需要解决的问题;然后给出了基本解决思路并推演出瞄准偏差方程;接着创建了迭代优化瞄准控制模型并设计了瞄准控制过程;最后通过仿真实验进行了与比例导引控制方法的对比测试和抗误差干扰测试,结果表明,迭代优化拦射瞄准引导法对于解决自主拦射攻击问题非常有效。     

A Tabu search based routing algorithm for wireless sensor networks

In this paper, a Tabu search based routing algorithm is proposed to efficiently determine an optimal path from a source to a destination in wireless sensor networks (WSNs). There have been several methods proposed for routing algorithms in wireless sensor networks. In this paper, the Tabu search method is exploited for routing in WSNs from a new point of view. In this algorithm (TSRA), a new move and neighborhood search method is designed to integrate energy consumption and hop counts into routing choice. The proposed algorithm is compared with some of the ant colony optimization based routing algorithms, such as traditional ant colony algorithm, ant colony optimization-based location-aware routing for wireless sensor networks, and energy and path aware ant colony algorithm for routing of wireless sensor networks, in term of routing cost, energy consumption and network lifetime. Simulation results, for various random generated networks, demonstrate that the TSRA, obtains more balanced transmission among the node, reduces the energy consumption and cost of the routing, and extends the network lifetime.     

一种管线布局智能优化方法

为了实现复杂机电装备管线布局优化设计,提出了一种基于新的编码方式的管线布局智能优化方法.首先,设计了一种具有更好通用性的新的粒子编码方法,给出了管路路径映射规则.其次,给出了基于该编码方式的目标函数计算方法.再次,结合管路布局领域的相关技术,采用粒子群算法对管路避障路径进行寻优.最后应用MATLAB软件进行管路布局优化仿真计算,验证了该方法的有效性.     

基于栅格模型机器人路径规划的量子蚁群算法

针对复杂环境中移动机器人路径规划问题,提出了一种基于量子-蚁群算法(QACA)融合的路径规划算法。该算法的核心是在蚁群系统(ACS)中引入量子算法中的量子态矢量和量子旋转门来分别表示和更新信息素,增加位置的多样性,加快算法的收敛速度。通过仿真实验表明,该算法可增加算法的随机性,较传统的蚁群算法具有更好的种群多样性,更快的收敛速度和全局寻优能力,即使在障碍物较复杂的环境下,也能迅速规划出一条最优路径。     

A novel mixed E–M coupled filter with adjustable transmission zeros

In this article, a novel idea to introduce two coupling paths including one electric coupling and one mixed electric and magnetic coupling between adjacent resonators is proposed. Theoretical exploration based on equivalent circuit model reveals that two adjustable finite transmission zeros can be generated to improve filter performances as the result of the interaction of the two paths for either electric domain or magnetic domain coupling. As an example, a microstrip filter is designed, fabricated and measured using the proposed configuration. The measure results validate and confirm the feasibility of the proposed design methodology.     

A Novel Integrated Path Planning Algorithm for Warehouse AGVs

We propose an integrated path planning method for multiple automated guided vehicles performing logistics delivery within a real-world warehouse environ-ment considering obstacles. By applying it on each vehicle, this proposed method enables the vehicle the vehicles have the capabilities for autonomous path planning. The path planning consists of three parts, K-means algorithm based task points clustering, genetic algorithm based task points ordering, and the probabilistic road map based best path search. Vehicle conflict resolution is depending on implementing the probabilistic road map construction considering the realistic map with obstacles. The simulations result validate that the clustering and ordering are necessary for the path planning, both the path planning time and the Automated guided vehicles (AGVs) running time can be dramatically reduced.     

基于改进RRT算法的无人机航迹规划

针对快速扩展随机树（RRT）算法用于无人机自主在线航迹规划时,只能快速获得可行的航迹,无法获得接近于最短航迹的较优航迹的缺点,提出了一种改进的RRT算法.该算法将无人机动力学约束融入到节点扩展过程中,通过改进离随机采样点最近的根节点的选取策略和引入航迹距离约束,搜索树将沿着航迹距离较短的方向朝着目标点进行扩展,使得规划出来的航迹接近最优,并采用基于B样条曲线的航迹平滑方法生成平滑可跟踪的航迹.仿真结果表明该算法能够快速地搜索安全并且满足无人机动力学约束的较优航迹.     

将盘旋动作引入自主航路规划的方法

为了使侦察无人机在不确定环境下航路选择更加灵活,提出了一种将盘旋动作引入到自主航路规划中的方法。首先,分析了盘旋动作对机载侦察设备的不利影响,以及盘旋动作对扩大航路选择范围上的优势。然后,通过设置修正系数的方法,对航路选择的目标函数进行改进,将盘旋动作引入到无人机航路规划的决策集中。最后,通过仿真试验验证了该方法的有效性。     

利用概率天气预报的通航飞行路径规划

为解决实际天气与天气预报不一致时根据确定性天气预报所规划飞行路径效益低的问题,提出一种利用以概率方式给出的天气预报,对通用航空飞行路径进行规划的方法。该方法利用由集合数值天气预报得到的概率天气预报信息,构建空域概率天气模型,使用分阶段飞行路径规划方法保障预期规划目标的实现,将飞行路径规划分解为多个阶段,除第一阶段外,从每个阶段的每个起始点出发都分别规划绕飞和穿越可能的危险天气区域两条不同的路径,各阶段的不同路径采用A*算法进行搜索,得到包含多条飞行路径的规划飞行路径集合。实验结果表明,在保证安全性的前提下,该方法规划的飞行路径与其他典型算法规划的飞行路径相比,在统计意义上的期望飞行距离显著减小。      

基于改进蚁群算法的大型建筑物疏散路径设计

针对在建筑物发生火灾等险情时,传统疏散路径方案中人员疏散路径固定、疏散时间较长、疏散效果较差等问题,文中结合大型建筑物的疏散背景与条件,同时考虑了人员在疏散过程中心里因素的影响,提出了一种用于描述大型建筑物中疏散路径的数学模型。在该数学模型的基础上,引入了新的收敛条件,并使用新的启发式函数设计了一种改进蚁群算法。通过数学推导,证明了该算法具有良好的收敛性,并在实际中应用良好。对所提出的算法进行了计算机仿真,仿真结果表明,使用该改进蚁群算法生成的疏散路径,在时间和效果上均优于现有的疏散路径设计方案。