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localization of mobile robot by using Ekf
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详细介绍MCL算法，是由Sebastian Thrun a, Dieter Fox, Wolfram Burgard, Frank Dellaert所著的论文，发表于Artificial Intelligence上。-Mobile robot localization is the problem of determining a robot’s pose from sensor data. This
article presents a family of probabilistic lo
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基于互相关函数，采用求和广义互相关函数(summed-GCC)法用于机器人系统平台。由于采用不同的映射函数(mapping functions)，GCC法在该平台下，只需三个麦克风即可进行三维定位，突破了基于TDOA法进行三维声源定位最少需4个麦克风的限制-Based on cross-correlation function, using generalized cross-correlation function sum (summed-GCC) method for the robot s
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结合马尔可夫过程，提出一种概率论的声源定位算法，并给出了基于DSP的机器人实现。其中声源定位部分采用三个麦克风呈三角形放置，为减小由于噪声等引起的TDOA估计误差，采用马尔可夫过程计算时延，这样计算的时延会更可靠。该方案中的声源定位也属于一维定位，即只需知道声源的方向角-Combination of Markov process, a probability theory of sound source location algorithm, and give the robot based o
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澳大利亚的硕士论文：户外环境下的机器人定位和测图-Australia' s master' s thesis: outdoor environment, the robot localization and mapping
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一个详细讲述卡尔曼滤波的ppt，通过它可以学习有关卡尔曼滤博，和机器人自主定位的知识- Kalman filter detailed ppt, through which you can learn more about Bo Kalman filter, and knowledge of robot autonomous localization
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机器人人工智能的路径规划的发展和方向概述，让学生理解以及matlab仿真。-Artificial intelligence robot path planning overview of the development and direction, so that students understand and matlab simulation.
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Robot localization is the problem of estimating robot coordinates with respect to an external
reference frame. In the common formulation of the localization problem, the robot is given a
map of its environment, and to localize itself relative to
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Neural Network (MLP) Robot Localization with matlab code.
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旋翼飞行机器人视觉定位方法及系统_李力旋翼飞行机器人视觉定位方法及系统_李力-Rotor flying robot vision localization method and system _ Li Li-rotor flying robot vision localization method and system _ Li Li
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