NDLI: Derivative-free distributed nonlinear Kalman filtering for cooperating agricultural robots

Content Provider	IEEE Xplore Digital Library
Author	Rigatos, Gerasimos G.
Copyright Year	2013
Description	Author affiliation: Unit of Industrial Automation, Industrial Systems Institute, 26504, Rion Patras, Greece (Rigatos, Gerasimos G.)
Abstract	The paper proposes state estimation-based control for cooperating agricultural robots. To estimate with accuracy the position of the robotic vehicles as well as their motion characteristics, fusion of estimates from multiple sensors is performed with the use of the Derivative-free distributed Kalman Filter. The proposed derivative-free nonlinear filtering method enables distributed state estimation, by substituting the Extended Information Filter with the standard Information Filter recursion. This filtering approach has significant advantages because, unlike the Extended Information Filter, it is not based on local linearization of the nonlinear dynamics and computation of Jacobian matrices. The proposed nonlinear control is in accordance with the principles of differential flatness theory. The performance of the considered distributed filtering-based control is tested through simulation experiments on the problem of autonomous navigation of agricultural robots under a master-slave scheme.
Starting Page	1
Ending Page	6
File Size	400610
Page Count	6
File Format	PDF
ISBN	9781467351942
ISSN	21635145
e-ISBN	9781467351935
DOI	10.1109/ISIE.2013.6563603
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-28
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vectors Kalman filters Robot kinematics Vehicles Covariance matrices Robot sensing systems
Content Type	Text
Resource Type	Article

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