A Global Localization and SelfDocking Method for Mobile Robot Based on Feature Map

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A Global Localization and SelfDocking Method for Mobile Robot Based on Feature Map

更新时间：2025-07-16

- A Global Localization and SelfDocking Method for Mobile Robot Based on Feature Map
- Acta Electronica Sinica Vol. 38, Issue 6, Pages: 1256-1261(2010)
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- Published：2010
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FONT face, Verdana, CHEN Feng, et al. A Global Localization and SelfDocking Method for Mobile Robot Based on Feature Map[J]. Acta Electronica Sinica, 2010, 38(6): 1256-1261.
DOI：

FONT face, Verdana, CHEN Feng, et al. A Global Localization and SelfDocking Method for Mobile Robot Based on Feature Map[J]. Acta Electronica Sinica, 2010, 38(6): 1256-1261. DOI：

摘要

<FONT face=Verdana>提出一种新的移动机器人全局定位与自主泊位方法.该方法分为两阶段：离线阶段，采用SIFT(Scale Invariant Feature Transform)算法并提出一种基于DDBBF(Double Direction Best Bin First)的特征匹配方法实现视觉特征三维重建；将进化策略应用于RaoBlackwellized粒子滤波器

并结合自适应重采样，实现了移动机器人同时定位和特征地图创建.在线阶段，采用基于HMM(Hidden Markov Model)的方法实现全局泊位位置识别；采用RANSAC算法实现全局度量定位；提出极点伺服控制方法，实现机器人精确自主泊位.在室内环境下的实验结果证实了该方法的优良性能.

Abstract

<FONT face=Verdana>A global localization and selfdocking method for mobile robot is presented.The method is composed of two stages:during the offline stage

SIFT (scale invariant feature transform) algorithm is used and a DDBBF (double direction best bin first) matching method is presented to implement the 3D reconstruction of vision features;an ES (evolution strategy) and adaptive re-sampling scheme were applied in RBPF (RaoBlackwellized particle filter) to implement the mobile robot SLAM (simultaneous localization and mapping).In the online stage

the global docking station is recognized through HMM (Hidden Markov Model) based methotd

he global metric pose and location of the robot are estimated by a RANSAC algorithm;and then an epipole servoing method is presented to dock the robot precisely.Experiment results carried out with a real robot in an indoor environment show the superior performance of the proposed method.

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