基于轨迹大数据的城市交通感知和路网关键节点识别

结合城市道路网络的拓扑结构特征和交通流特性,建立基于有向加权复杂网络的城市交通网络关键节点识别模型.以兰州市连续7天的出租车GPS数据为基础,分析并可视化呈现兰州市在工作日和非工作日的城市交通流状态,并采用基于DWNodeRank的有向加权复杂网络关键节点识别方法对兰州市路网关键节点进行识别研究.本文研究方法和结果可为交通管理部门的规划、设计和管理提供科学指导.     

利用CSP技术辅助汽车驾驶室内布置方案设计

本文半约束满足问题用于驾驶室内布置方案设计问题求解，提出了驾驶室内各对象之间的约束描述及分层，建立了约束网络及求解策略，并提出了目标方案修改决策。     

基于逆推方法的非线性船舶航迹跟踪控制

基于包括科氏向心矩阵和非线性阻尼项的、带恒值扰动的非线性船舶水面运动数学模型,采用带积分器的逆推(Backstepping)设计工具,设计船舶航迹跟踪控制律;并借助Lyapunov函数、应用相关引理证明了所设计的船舶航迹跟踪控制律使得最终的闭环航迹跟踪控制系统一致全局渐近稳定,达到航迹跟踪控制的目的.仿真研究表明,所设计的控制律使船舶能够克服恒值扰动跟踪期望航迹,且控制量合理,从而验证了所设计控制律的有效性.     

基于有限弹迹点的高炮射弹分析

介绍了一种利用有限弹迹点检查射击诸元的方法,介绍了最小二乘法拟合曲线的原理。该方法可对高炮射击准备误差进行修正,为炮手提供精确的射击修正量。     

平面二自由度冗余驱动并联机器人控制实验研究

对平面二自由度冗余驱动并联机器人进行了逆运动学分析,由末端执行器的位置计算得到主动关节角的位置.分别采用传统的PID控制方法和PID+速度前馈补偿+加速度前馈补偿的方法对并联机器人轨迹跟踪问题进行了实验研究.通过比较2种控制方法的轨迹跟踪效果和比较由连接在连杆上的加速度传感器测量的振动大小,证明了PID+速度前馈补偿+加速度前馈补偿的方法能更好地实现轨迹跟踪.     

A new plan and coordination strategy for robot system based on state space

This paper proposes a general plan and coordination strategy for robot system. The state space for robot system is constructed according to the task requirement and system characteristic. Reachable state of the system is figured out by the system’s internal and external constraints. Task plan and coordination are then transformed as trajectory solving problem in the state space, by which the realizable conditions for the given task are discussed. If the task is realizable, the optimal strategy for task execution could be investigated and obtained in state space. Otherwise, it could be transformed to be realizable via adjusting the system configuration and/or task constraint, and the transformation condition could also be determined. This contributes to design, plan, and coordination of the robotic tasks. Experiments of the manipulator path planning and multi-robot formation movement are conducted to show the validity and generalization of the proposed method. Foundation item: the National Natural Science Foundation of China (No. 60675041) and the Program for New Century Excellent Talents in University (No. NCET-06-0398)     

一种船用服务机器人的轨迹跟踪控制

基于旅游类舰船的消费需求不断增加和机器人产业的逐渐普及,设计一种应用于游轮上的船用服务机器人。面对船舶复杂的工作环境等特点,该机器人位置跟踪和姿态跟踪控制显得尤为关键。首先根据驱动原理建立运动学模型,其次借鉴Backstepping方法设计虚拟控制的虚拟反馈,并结合Lyapunov函数构造出具有全局渐近稳定的轨迹跟踪控制器。最后并通过仿真实验证明该法具有稳定性好、响应时间短和稳态误差较小的优点,对机器人技术应用于船舶方向的研究产生了一定的积极影响。     

Coordinated multi-aircraft 4D trajectories planning considering buffer safety distance and fuel consumption optimization via pure-strategy game

In this paper, we consider a coordinated multi-aircraft 4D (3D space plus time) trajectories planning problem which is illustrated by planning 4D trajectories for aircraft traversing an Air Traffic Control (ATC) sector. The planned 4D trajectories need to specify each aircraft’s position at any time, ensuring conflict-free and reducing fuel and delay costs, with possible aircraft maneuvers such as speed adjustment and flight level change. Different from most existing literature, the impact of buffer safety distance is also under consideration, and conflict-free is guaranteed at any given time (not only at discrete time instances). The problem is formulated as a pure-strategy game with aircraft as players and all possible 4D trajectories as strategies. An efficient maximum improvement distributed algorithm is developed to find equilibrium at which every aircraft cannot unilaterally improve further, without enumerating all possible 4D trajectories in advance. Proof of existence of the equilibrium and convergence of the algorithm are given. A case study based on real air traffic data shows that the algorithm is able to solve 4D trajectories for online application with estimated 16.7% reduction in monetary costs, and allocate abundant buffer safety distance at minimum separation point. Scalability of the algorithm is verified by computational experiments.     

基于hp自适应伪谱法的智能汽车紧急变道轨迹规划与优化

为了提高智能汽车紧急变道轨迹规划的实时性和适应性,将紧急变道过程分为初始阶段和跟踪阶段,初始阶段的轨迹由优秀驾驶人紧急变道模型产生,跟踪阶段的轨迹采用Sigmoid函数规划出紧急避让路径。首先通过聚类分析处理优秀驾驶人转向操作的实车试验数据,拟合得出紧急变道过程中的方向盘转角随时间的关系（即驾驶人紧急变道模型）,作为智能汽车在紧急变道初始阶段不同速度下车辆控制的输入量。然后通过建立与求解约束方程,满足避撞约束、侧向位移约束以及最大侧向加速度约束,得出Sigmoid函数表达式,作为智能汽车在紧急变道过程跟踪阶段的参考路径。最后利用hp自适应伪谱法加入切换点的物理量约束,逼近全局正交多项式的状态量和控制量,自动调整和处理2个阶段的切换点位置和衔接问题,以最小变道距离为目标对跟踪阶段的变道轨迹进行优化。运用PreScan与MATLAB对4种不同工况下的紧急变道轨迹规划进行联合仿真。结果表明：提出的轨迹规划与优化方法在满足各项约束的情况下成功避开障碍物,同时缩短了需要优化的轨迹,优化时间都小于0.9 s,并且与基于多项式函数轨迹规划方法相比,该方法能够以距障碍物较远的距离避开障碍物,在不同的车辆速度、道路曲率和障碍物宽度的复杂工况下具有更好的适应性。