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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 localization algorithms known as Monte Carlo Localization [MCL]. MCL algorithms represent a robot’s belief by a set of weighted hypotheses [samples], which approximate the posterior under a common Bayesian formulation of the localization problem. Building on the basic MCL algorithm, this article develops a more robust algorithm called Mixture- MCL, which integrates two complimentary ways of generating samples in the estimation. To apply this algorithm to mobile robots equipped with range finders, a kernel density tree is learned that permits fast sampling. Systematic empirical results illustrate the robustness and computational efficiency of the approach.  2001 Published by Elsevier Science B.V. Keywords: Mobile robots Localization Position estimation Particle filters Kernel density trees
Update : 2025-03-07 Size : 1.36mb Publisher : xuyuhua

aoc.m 是用matlab实现蚁群算法ants_information.m蚁群算法中信息素的构建 mcl是马尔科夫聚类算法 nmf是矩阵的非负分解 Generative Topographic Mapping工具包-aoc.m is matlab implementation of ant colony algorithm ants_information.m pheromone ant colony algorithm is a Markov clustering algorithm to build mcl is nmf non-negative matrix decomposition of Generative Topographic Mapping Toolkit
Update : 2025-03-07 Size : 40kb Publisher : 颜利平

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MCL 算法,Markov Clustring 算法-MCL algorithm
Update : 2025-03-07 Size : 650kb Publisher : luguiqiao

马尔科夫链算法,详细介绍马尔科夫链算法的设计与实现。-Detailed design and implementation of the Markov chain algorithm.
Update : 2025-03-07 Size : 789kb Publisher : 朱杰

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基于蒙特卡洛的的移动传感器节点定位算法仿真代码(Simulation of mobile sensor node localization algorithm based on Monte Carlo)
Update : 2025-03-07 Size : 6kb Publisher : baolulu
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