Localization of legged robots combining a fuzzy-Markov method and a population of extended Kalman filters

被引：13

作者：

Martin, Francisco ^{[1
]}

Matellan, Vicente ^{[1
]}

Barrera, Pablo ^{[1
]}

Canas, Jose M. ^{[1
]}

机构：

[1] Rey Juan Carlos Univ, Robot Lab, Madrid 28933, Spain

来源：

ROBOTICS AND AUTONOMOUS SYSTEMS | 2007年 / 55卷 / 12期

关键词：

mobile robots; robotic soccer; localization; fuzzy logic; Kalman filter; legged robot;

D O I：

10.1016/j.robot.2007.09.006

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a new approach to robot vision-based self-localization in dynamic and noisy environments for legged robots when efficiency is a strong requirement. The major contribution of this paper is the improvement of a Markovian method based on a fuzzy occupancy grid (FMK). Our proposal combines FMK with a population of Extended Kalman Filters, making the complete algorithm both robust and accurate while keeping its computational cost bounded. Two different strategies have been designed to combine both the methods. They have been tested in the RoboCup environment and quantitatively compared with other approaches in several experiments with the real robot. (c) 2007 Elsevier B.V. All rights reserved.

引用

页码：870 / 880

页数：11

共 18 条

[11] Kalman RE., 1960, J BASIC ENG, V82D, P35, DOI DOI 10.1115/1.3662552
[12] LENSER S, 2000, P IEEE INT C ROB AUT
[13] MARTINEZ H, 2006, TEAMCHAOS
[14] Ruiz-del-Solar J, 2005, P 2 IEEE LAT AM ROB
[15] SIMMONS R, 1995, P INT JOINT C ART IN, P1080
[16] Sridharan M, 2005, IEEE INT CONF ROBOT, P3366
[17] Robust vision-based localization by combining an image-retrieval system with Monte Carlo localization
Wolf, J
Burgard, W
Burkhardt, H
[J]. IEEE TRANSACTIONS ON ROBOTICS, 2005, 21 (02) : 208 - 216
[18] [No title captured]

← 1 2 →