DocumentCode :
1722006
Title :
Theoretical and experimental study of uncertain set based moving target localization using multiple robots
Author :
Gu, Feng ; Wang, Zheng ; He, Yuqing ; Han, Jianda ; Wang, Yuechao
Author_Institution :
State Key Lab. of Robot., Grad. Sch. of Chinese Acad. of Sci., Shenyang, China
fYear :
2011
Firstpage :
1646
Lastpage :
1651
Abstract :
In this paper, multiple robots cooperation based moving target localization problem is researched. Different from traditional statistics based architecture, the concept of uncertain set is utilized in this paper to formulate the so called Cooperative Enhanced Set Membership Filter based cooperative localization algorithm. One of the most attracting advantages of this method is that it assumes the measurement errors are modeling as unknown-but-bounded set, instead of requiring the errors´ covariance to be obtainable beforehand, which is general in statistics based algorithm, such as Kalman Filter and Particle Filter. Furthermore, some strategies, which is originated from the update process of the ESMF algorithm itself, are proposed to improve the computational efficiency and localization accuracy. Finally, an original experimental scenario is designed with respect to an indoor multiple-rotorcraft-platform and the results are listed out and analyzed in detail to verify the feasibility and validity of the proposed algorithm.
Keywords :
Kalman filters; aircraft control; helicopters; mobile robots; multi-robot systems; particle filtering (numerical methods); path planning; robot vision; set theory; statistical analysis; ESMF algorithm; Kalman filter; computational efficiency improvement; cooperative enhanced set membership filter; cooperative localization algorithm; enhanced set-membership filter; indoor multiple-rotorcraft-platform; localization accuracy improvement; measurement errors; moving target localization problem; multiple robots cooperation; particle filter; statistics based architecture; uncertain set; unknown-but-bounded set; Ellipsoids; Estimation; Mathematical model; Measurement errors; Measurement uncertainty; Prediction algorithms; Robots;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2011 IEEE International Conference on
Conference_Location :
Karon Beach, Phuket
Print_ISBN :
978-1-4577-2136-6
Type :
conf
DOI :
10.1109/ROBIO.2011.6181525
Filename :
6181525
Link To Document :
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