目前这项艰苦的研究只是对于如纳米定位激光器和全功能型纳米粒子等新型的治疗设备有一定的帮助，可以跟踪、标记和杀死癌细胞。
This painstaking research can only help futuristic treatment efforts, such as nanoparticle-targeted lasers and do-it-all nanoparticles that can track, tag and kill cancer cells.
然后，介绍了基于粒子滤波器的移动机器人定位研究进展。
Secondly, the progress of mobile robot localization based on particle filters is described.
目前，实现定位跟踪的算法有很多，如卡尔曼滤波算法、扩展卡尔曼滤波算法、粒子滤波算法等。
At present, there are many algorithms to achieve position tracking, such as the Kalman filter algorithm, extended Kalman filter algorithm, particle filter algorithm and so on.
试验表明，改进后的粒子滤波跟踪算法目标跟踪更加稳定，目标定位更加准确。
Experimental results show that particle filter tracking algorithm is more stable and more accurate than traditional particle filter tracking algorithm.
该文研究了杂波干扰下适用于平面机动目标实时定位的粒子滤波器的设计和实现。
This paper studies the design and implementation method of particle filters suitable for the plane maneuvering targets real time tracking.
通过研究最简单的两粒子体系之间的量子纠缠特性，使得量子远程定位、时钟同步和光纤通信成为可能。
Quantum spatial positioning, clock synchronization and fiber optic communications become possible through researching the quantum entanglement characteristic between the simple two particles system.
针对动态自标定的问题，提出了一种改进的基于粒子群优化(PSO)的自标定位置视觉定位算法。
In allusion to the problem of dynamic self-calibration, a novel self-calibrating algorithm for visual position based on particle swarm optimization (PSO) is suggested in this paper.
纳米粒子的超微小体积可使药物输送智能化，例如靶向定位地将药物投递到病灶局部或专一性地作用于靶细胞。
Due to its ultra-small size, NP can achieve intelligent delivery of drugs, such as deliver drug site-specifically to disease focus or targeted tissue, even into target cells.
我们将会在下面场景中创建有各种不同尺寸的15个粒子和三个障碍物。在场景中的定位器是目标，粒子跟随这一个目标。
We will create the scene shown in the following image, there are 15 particles and three obstacles of various dimension.
其主要内容包括移动机器人的位姿跟踪方法、马尔可夫定位方法、粒子滤波方法及各种粒子滤波改进方法。
The research topics include approaches of robot's pose tracking, Markov localization, Particle Filter and other improved PF method.
提出了基于粒子群优化的齿轮箱传感器优化配置方法，解决多测点传感器的布置和定位问题。
It presents a method of optimum placement of sensors in gearbox based PSO algorithm to solve the problem of sensors layout and localization.
提出了基于粒子群优化的齿轮箱传感器优化配置方法，解决多测点传感器的布置和定位问题。
It presents a method of optimum placement of sensors in gearbox based PSO algorithm to solve the problem of sensors layout and localization.
应用推荐