Báo điện tử IEEE

[john_den]

Bác lấy cho em mấy bài về mobile robot này nhé. Cảm ơn bác nhiều:

The mobile robot “staff”: mechanical analysis anddesign
Agullo, J. de Haro, S. Roure, F.
Dept. of Mech. Eng., Univ. Politecnica de Catalunya, Barcelona;

This paper appears in: Emerging Technologies and Factory Automation, 1999. Proceedings. ETFA '99. 1999 7th IEEE International Conference on
Publication Date: 1999
Volume: 2, On page(s): 1477-1484 vol.2
Meeting Date: 10/18/1999 - 10/21/1999
Location: Barcelona, Spain
ISBN: 0-7803-5670-5
References Cited: 7
INSPEC Accession Number: 6530085
Digital Object Identifier: 10.1109/ETFA.1999.813163
Posted online: 2002-08-06 22:47:51.0
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The structure design and dynamics analysis of an autonomous over-obstacle mobile robot
Wang Furui Wang Dexin Dong Erbao Chen Haoyao Du Huasheng Yang Jie
China Univ. of Sci. & Technol., Hefei, China;


This paper appears in: Industrial Technology, 2005. ICIT 2005. IEEE International Conference on
Publication Date: 14-17 Dec. 2005
On page(s): 248- 253
ISBN: 0-7803-9484-4
INSPEC Accession Number: 8956934
Digital Object Identifier: 10.1109/ICIT.2005.1600644
Posted online: 2006-03-06 09:14:02.0

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A position control differential drive wheeled mobile robot
Yongoug Chung; Chongkug Park; Harashima, F.
Industrial Electronics, IEEE Transactions on
Volume 48, Issue 4, Aug 2001 Page(s):853 - 863
Digital Object Identifier 10.1109/41.937419
Summary:For more accurate path tracking of a four-wheeled two-degrees-of-freedom mobile robot (WMR), a position control algorithm is proposed with two separated feedback loops, a velocity feedback loop and a position feedback loop. In the most conventional position control system of a WMR, internal error is mainly considered, while external error has, as yet, hardly been treated, although it plays an important role in accurate position control. This external error is caused by unexpected environmental situations. The proposed control algorithm is designed to compensate for both internal error and external error. This algorithm makes it possible to accurately follow the designed trajectory
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Sensor integration for mobile robot position determination
Azizi, F.; Houshangi, N.
Systems, Man and Cybernetics, 2003. IEEE International Conference on
Volume 2, Issue , 5-8 Oct. 2003 Page(s): 1136 - 1140 vol.2
Digital Object Identifier
Summary: The objective of the work presented is to determine an accurate position and orientation for mobile robots based on information received from multiple sensors. The approach taken in this paper is to integrate the information from odometry with the inertial system using Unscented Kalman Filter (UKF). The UKF is the newest extension of widely used estimation method, Kalman Filter. The UKF is more accurate and simpler than the extended Kalman filter applied to nonlinear systems.

[radiotech]

here are the documents that you requested.

[scentoflove]

Mấy anh down giùm em cái này

ieeexplore.ieee.org/iel5/6997/18853/00870792.pdf?arnumber=870792

An extended virtual force field based behavioral fusion with neuralnetworks and evolutionary programming for mobile robot navigation
Kwang-Young Im; Se-Young Oh
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Volume 2, Issue , 2000 Page(s):1238 - 1244 vol.2
Digital Object Identifier 10.1109/CEC.2000.870792
Summary:A local navigation algorithm for mobile robots is proposed, based on the new extended virtual force field (EVFF) concept, neural network-based fusion for the three primitive behaviors generated by the EVFF, and the evolutionary programming-based optimization of the neural network weights. Furthermore, a multi-network version of the above neurally-combined EVFF has been proposed that lends itself not only to an efficient architecture but also to a greatly enhanced generalization capability. These techniques have been verified through both simulation and real experiments under a collection of complex environments

[Mecha]

Nguyên văn bởi scentoflove

Mấy anh down giùm em cái này

ieeexplore.ieee.org/iel5/6997/18853/00870792.pdf?arnumber=870792

An extended virtual force field based behavioral fusion with neuralnetworks and evolutionary programming for mobile robot navigation
Kwang-Young Im; Se-Young Oh
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Volume 2, Issue , 2000 Page(s):1238 - 1244 vol.2
Digital Object Identifier 10.1109/CEC.2000.870792
Summary:A local navigation algorithm for mobile robots is proposed, based on the new extended virtual force field (EVFF) concept, neural network-based fusion for the three primitive behaviors generated by the EVFF, and the evolutionary programming-based optimization of the neural network weights. Furthermore, a multi-network version of the above neurally-combined EVFF has been proposed that lends itself not only to an efficient architecture but also to a greatly enhanced generalization capability. These techniques have been verified through both simulation and real experiments under a collection of complex environments

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