Localization and map building for a mobile robot

Experimental Robotics VI - Lecture Notes in Control and Information Sciences ◽

10.1007/bfb0119401 ◽

2008 ◽

pp. 225-234 ◽

Cited By ~ 1

Author(s):

Patrick Rives ◽

José -Luís Sequeira ◽

Pedro Lourtie

Keyword(s):

Mobile Robot ◽

Map Building

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Fusing a hyper-ellipsoid clustering Kohonen network with the Julier-Uhlmann-Kalman filter for autonomous mobile robot map building and tracking

Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146) ◽

10.1109/robot.1998.677301 ◽

2002 ◽

Cited By ~ 1

Author(s):

J.A. Janet ◽

M.W. White ◽

M.G. Kay ◽

J.C. Sutton ◽

J.J. Brickley

Keyword(s):

Kalman Filter ◽

Mobile Robot ◽

Map Building ◽

Autonomous Mobile Robot ◽

Kohonen Network

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1A1-H06 A Odometry Error Proofing System with Road Surface Environment Map for Mobile Robot : Measurement Method of Odometry Error and Road Surface Environment Map Building on Tile-Carpet(Wheeled Robot/Tracked Vehicle(1))

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) ◽

10.1299/jsmermd.2012._1a1-h06_1 ◽

2012 ◽

Vol 2012 (0) ◽

pp. _1A1-H06_1-_1A1-H06_4

Author(s):

Taichi YAMADA ◽

Akihisa OHYA

Keyword(s):

Mobile Robot ◽

Measurement Method ◽

Road Surface ◽

Map Building ◽

Tracked Vehicle ◽

Environment Map ◽

Wheeled Robot ◽

Surface Environment ◽

Error Proofing

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Map-Building and Map-based Self-Localization of a Mobile Robot using Scan-Correlation Technique - A New Approach

IASTED Technology Conferences / 705: ARP / 706: RA / 707: NANA / 728: CompBIO ◽

10.2316/p.2010.706-044 ◽

2010 ◽

Author(s):

R. Ray ◽

V. Kumar ◽

D. Banerjee ◽

D. Bhattacharya

Keyword(s):

Mobile Robot ◽

Correlation Technique ◽

Map Building ◽

New Approach

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3D map building for a moving based on mobile robot

2014 Proceedings of the SICE Annual Conference (SICE) ◽

10.1109/sice.2014.6935206 ◽

2014 ◽

Cited By ~ 2

Author(s):

YoSeop Hwang ◽

DongJu Lee ◽

Jangmyung Lee

Keyword(s):

Mobile Robot ◽

Map Building

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A low cost map building sensor system for mobile robot

2008 6th IEEE International Conference on Industrial Informatics ◽

10.1109/indin.2008.4618141 ◽

2008 ◽

Cited By ~ 1

Author(s):

Hyun seung Choi ◽

Woong keun Hyun

Keyword(s):

Mobile Robot ◽

Low Cost ◽

Sensor System ◽

Map Building

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Laser-Based Mobile Robot Map Building

Frontiers in Computer Education - Advances in Intelligent and Soft Computing ◽

10.1007/978-3-642-27552-4_141 ◽

2012 ◽

pp. 1085-1091 ◽

Cited By ~ 1

Author(s):

Liu Yan ◽

Tian Qi ◽

Tang Wenjun

Keyword(s):

Mobile Robot ◽

Map Building

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Indoor localization and map building for autonomous mobile robot

2016 International Conference on Integrated Circuits and Microsystems (ICICM) ◽

10.1109/icam.2016.7813623 ◽

2016 ◽

Author(s):

Mingming Lou ◽

Pengwei Yu ◽

Yao Yao ◽

Lei Zhang

Keyword(s):

Mobile Robot ◽

Indoor Localization ◽

Map Building ◽

Autonomous Mobile Robot

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Mobile robot localization and map building based on laser ranging and PTAM

2011 IEEE International Conference on Mechatronics and Automation ◽

10.1109/icma.2011.5985799 ◽

2011 ◽

Cited By ~ 8

Author(s):

Jinbo Sheng ◽

Shunichi Tano ◽

Songmin Jia

Keyword(s):

Mobile Robot ◽

Laser Ranging ◽

Robot Localization ◽

Map Building ◽

Mobile Robot Localization

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LRF-based data processing algorithm for map building of mobile robot

The 2010 IEEE International Conference on Information and Automation ◽

10.1109/icinfa.2010.5512015 ◽

2010 ◽

Cited By ~ 6

Author(s):

Songmin Jia ◽

Hao Yang ◽

Xiuzhi Li ◽

Wei Fu

Keyword(s):

Data Processing ◽

Mobile Robot ◽

Processing Algorithm ◽

Map Building ◽

Data Processing Algorithm

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BUILDING MAP AND POSITIONING SYSTEM FOR INDOOR ROBOT BASED ON PLAYER

International Journal of Information Acquisition ◽

10.1142/s0219878911002483 ◽

2011 ◽

Vol 08 (04) ◽

pp. 281-290

Author(s):

BIN WANG ◽

WEI LU ◽

BIN KONG

Keyword(s):

Mobile Robot ◽

Positioning System ◽

Map Building ◽

Adaptive Monte Carlo ◽

Indoor Mobile Robot ◽

Robot Positioning ◽

Positioning Method ◽

Dynamic Map ◽

Slam Algorithm ◽

Number Of Particles

In this paper, we have proposed a map-building and positioning method for an indoor mobile robot based on the open source platform Player. First, the DP-SLAM algorithm is transplanted to the Player and used to build the dynamic offline map. This would reduce the errors and constraints caused by manual map building. Second, the KLD-Sampling Adaptive Monte Carlo Locating (KLD-AMCL) algorithm is introduced to reduce the number of particles required in locating. Meanwhile, higher accuracy of localization is achieved through calculating the MLE and the real posterior KL distance. Finally, an indoor mobile robot positioning system is built by combining the Player platform, dynamic map building and KLD-AMCL algorithm. Experimental results show that the proposed system has better environmental adaptability and higher positioning accuracy.

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