Self localization of an autonomous robot: Using an EKF to merge odometry and vision based landmarks

被引：0
作者：
Sousa, Armando Jorge [1 ]
Costa, Paulo Jose [1 ]
Moreira, Antonio Paulo [1 ]
Carvalho, Adriano Silva [1 ]
机构：
[1] FEUP, ISR, P-4200465 Oporto, Portugal
来源：
ETFA 2005: 10TH IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION, VOL 1, PTS 1 AND 2, PROCEEDINGS | 2005年
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D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Localization is essential to modern autonomous robots in order to enable effective completion of complex tasks over possibly large distances in low structured environments. In this paper, a Extended Kalman Filter is used in order to implement self-localization. This is done by merging odometry and localization information, when available. The used landmarks are colored poles that can be recognized while the robot moves around performing normal tasks. This paper models measurements with very different characteristics in distance and angle to markers and shows results of the self-localization method. Results of simulations and real robot tests are shown.
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页码：227 / 233
页数：7
相关论文
共 26 条
  • [21] TOYAMA K, 1995, SPIE PHOTONICS, V2589, P38
  • [22] TSAI CC, 1998, IEEE INSTR MEAS TECH
  • [23] VIJK O, 1998, P IEEE INT C ROB AUT, V4, P3419
  • [24] THE ACTIVE BADGE LOCATION SYSTEM
    WANT, R
    HOPPER, A
    FALCAO, V
    GIBBONS, J
    [J]. ACM TRANSACTIONS ON INFORMATION SYSTEMS, 1992, 10 (01) : 91 - 102
  • [25] Welch G., 2002, 95041 U N CAR CHAP H
  • [26] Localization and navigation of a mobile robot using natural point landmarks extracted from sonar data
    Wijk, O
    Christensen, HI
    [J]. ROBOTICS AND AUTONOMOUS SYSTEMS, 2000, 31 (1-2) : 31 - 42
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