Intelligent Autonomous Navigation System for the Wheeled Mobile Robot


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An intelligent behavior control system for an autonomous mobile robot operating in an unstructured environment with sensor uncertainties is proposed. This study focuses on implementing and improving the methodology from Motlagh et al. [7] on a two-wheeled P3DX mobile robot. Motlagh et al. verified their design with computer simulation. When applying it on a real robot platform, we noticed some problems and improved the design using sensor selection strategy, safe rule and target switching strategy. The proposed sensor fusion architecture introduces two additional sensors, a laser range finder on the robot and an omnidirectional CCD camera on the ceiling, to improve the reliability of the sensing capability of P3DX mobile robot. The target switching strategy is used to guide the robot out of a dead zone and reach the target by creating a virtual target. Results of the experiments with the U-shaped and subspace dead zones are presented. These results proved that the target switching strategy successfully dealt with the loop path problem in the dead zone.



Advanced Materials Research (Volumes 383-390)

Edited by:

Wu Fan






T. M. Dat et al., "Intelligent Autonomous Navigation System for the Wheeled Mobile Robot", Advanced Materials Research, Vols. 383-390, pp. 1611-1618, 2012

Online since:

November 2011




[1] M. Al-Khatib and J.J. Saade. An efficient data-driven fuzzy approach to the motion planning problem of a mobile robot, Fuzzy Set. Syst. 134 (1) (2003) 65–82.

DOI: 10.1016/s0165-0114(02)00230-0

[2] M. Drumheller. Mobile robot localization using sonar, IEEE Transactions on Pattern Analysis and Machine Intelligence 9 (2) (1987) 325–332.

DOI: 10.1109/tpami.1987.4767907

[3] K. Demirli and I. B. Turksen. Sonar based mobile robot localization by using fuzzy triangulation, Robotics and Autonomous Systems 33 (2000), 109-123.

DOI: 10.1016/s0921-8890(00)00082-8

[4] K. Goris. Autonomous mobile robot mechanical design, Verije University, Brussels, (2006).

[5] J. L. John and F. H. W. Hugh. Directed Sonar sensing for mobile robot navigation, Kluwer Academic Publishers, (1992).

[6] H. Maaref and C. Barret. Sensor-based navigation of a mobile robot in an indoor environment, Robot. Auton. Syst. 38 (1) (2002) 1-18.

[7] R. E. Motlagh, T. S. Hong, N. Ismail, Development of a new minimum avoidance system for a behavior-based mobile robot, Fuzzy Sets and Systems 160 (2009) 1929-(1946).

DOI: 10.1016/j.fss.2008.09.015

[8] Saffiotti and L.P. Wesley. Perception-based self-localization using fuzzy locations, in: M. van Lambalgen, L. Dorst, F. Voorbraak (Eds. ), Reasoning with Uncertainty in Robotics, Proceedings of the International Workshop, Lecture Notes in Artificial Intelligence, Vol. 1093, Springer, Berlin (1996).

DOI: 10.1007/bfb0013973

[9] 10. J. Velagic, B. Lacevic, and N. Osmic. Efficient Path Planning Algorithm for Mobile Robot Navigation with a Local Minima Problem Solving, IEEE (2006) 2325-2330.

DOI: 10.1109/icit.2006.372707

[10] Mobile Robot INC, Pioneer 3 Operations Manual, Version 5, (2007).

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