一种三维航迹快速搜索方法

本文提出了基于SAS的自动三维航迹规划方法。该方法通过把约束条件结合到搜索算法中去，有效地减小了搜索空间，缩短了搜索时间，从而使三维规划能够用于实时航迹规划。在搜索过程中地形信息得到了充分利用，使算法生成的航迹能够自动回避地形和威胁。实验证明，该方法能够快速有效地完成规划任务，获得满意的三维航迹。

飞行器多任务在线实时航迹规划

针对不确定环境中的飞行器多任务航迹规划问题展开研究,提出了一种基于飞行路线图的两阶段航迹规划框架,航迹规划分成学习和查询两个阶段,环境信息和飞行器约束条件分阶段体现.在该框架下,通过采用一种混合多任务动态航迹规划方法,分别在稀疏路线图上实时搜索初始航迹和在精细路线图上启发式搜索后备航迹,能够在具有预先未知威胁、可变飞行任务的战场环境中实时生成三维航迹.

多飞行器协调航迹规划方法

针对多飞行器的协调航迹规划展开研究，提出了一种基于协同进化的多飞行器协调航迹规划算法。在该算法中，不同飞行器的潜在航迹形成它们自己的子种群，并在于种群内部进化。不同飞行器间的协调关系由航迹的评价函数来实现。同时，通过使用特定的染色体表示方法和进化算子，该算法可以有效利用各种环境信息，处理各种航迹约束，并实时地生成三维航迹。

一种针对运动目标的飞行器航迹搜索算法

鉴于目前大部份的航迹规划方法研究都局限于静止目标，提出了一种针对运动目标的飞行器航迹规划方法。该算法借鉴自学习实时A～*搜索的思想，将飞行器的运动与航迹搜索结合在一起，可以对目标的每一步移动实时作出反映。通过在限定的时间内扩大寻优范围，该算法不但可以满足实时在线应用的要求，而且可以有效地避免不可行区域，并使生成的航迹更加优化。实验结果表明，本文算法能有效地处理各种航迹约束，实时地生成满意的三维航迹。

动态环境中的飞行器实时三维航迹规划方法研究

本文提出了一种新的飞行器三维航迹规划方法—SDS。该方法能够在具有预先未知威胁的飞行环境中在线实时航迹规划。当飞行器上装备的探测器探测到飞行环境中有预先未知的威胁出现时，根据探测到的信息及时更新威胁数据。SDS根据新环境信息局部修正受到影响的航迹段来获得新的全局最优航迹。在每一时刻考虑当前已知的信息下，SDS生成的航迹是满足要求的最优航迹。

A simple route of morphology control and structural and optical properties of ZnO grown by metal-organic chemical vapour deposition

Employing the metal-organic chemical vapour deposition (MOCVD) technique, we prepare ZnO samples with different morphologies from the film to nanorods through conveniently changing the bubbled diethylzinc flux (BDF) and the carrier gas flux of oxygen (OCGF). The scanning electron microscope images indicate that small BDF and OCGF induce two-dimensional growth while the large ones avail quasi-one-dimensional growth. X-ray diffraction (XRD) and Raman scattering analyses show that all of the morphology-dependent ZnO samples are of high crystal quality with a c-axis orientation. From the precise shifts of the 2 theta. locations of ZnO (002) face in the XRD patterns and the E-2(high) locations in the Raman spectra, we deduce that the compressive stress forms in the ZnO samples and is strengthened with the increasing BDF and OCGF. Photoluminescence spectroscopy results show all the samples have a sharp ultraviolet luminescent band without any defects-related emission. Upon the experiments a possible growth mechanism is proposed.

Design and path planning for a remote-brained service robot

This paper presents a novel robot named "TUT03-A" with expert systems, speech interaction, vision systems etc. based on remote-brained approach. The robot is designed to have the brain and body separated. There is a cerebellum in the body. The brain with the expert systems is in charge of decision and the cerebellum control motion of the body. The brain-body. interface has many kinds of structure. It enables a brain to control one or more cerebellums. The brain controls all modules in the system and coordinates their work. The framework of the robot allows us to carry out different kinds of robotics research in an environment that can be shared and inherited over generations. Then we discuss the path planning method for the robot based on ant colony algorithm. The mathematical model is established and the algorithm is achieved with the Starlogo simulating environment. The simulation result shows that it has strong robustness and eligible pathfinding efficiency.

Design and path planning for a remote-brained service robot

This article introduced an effective design method of robot called remote-brain, which is made the brain and body separated. It leaves the brain in the mother environment, by which we mean the environment in which the brain's software is developed, and talks with its body by wireless links. It also presents a real robot TUT06-B based on this method which has human-machine interaction, vision systems, manipulator etc. Then it discussed the path planning method for the robot based on ant colony algorithm in details, especially the Ant-cycle model. And it also analyzed the parameter of the algorithm which can affect the convergence. Finally, it gives the program flow chat of this algorithm.

a real-time path planning approach without the computation of cspace obstacles

An important concept proposed in the early stage of robot path planning field is the shrinking of the robot to a point and meanwhile expanding of the obstacles in the workspace as a set of new obstacles. The resulting grown obstacles are called the Configuration Space (Cspace) obstacles. The find-path problem is then transformed into that of finding a collision free path for a point robot among the Cspace obstacles. However, the research experiences obtained so far have shown that the calculation of the Cspace obstacles is very hard work when the following situations occur: 1. both the robot and obstacles are not polygons and 2. the robot is allowed to rotate. This situation is even worse when the robot and obstacles are three dimensional (3D) objects with various shapes. Obviously a direct path planning approach without the calculation of the Cspace obstacles is strongly needed. This paper presents such a new real-time robot path planning approach which, to the best of our knowledge, is the first one in the robotic community. The fundamental ideas are the utilization of inequality and optimization technique. Simulation results have been presented to show its merits.