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Mathematical Problems in Engineering
Volume 2010, Article ID 979205, 22 pages
Research Article

Trajectory Planning for Nonholonomic Mobile Robot Using Extended Kalman Filter

Department of Electrical Engineering, State University of Londrina, Londrina, PR, Brazil

Received 26 August 2010; Revised 10 November 2010; Accepted 28 December 2010

Academic Editor: Miguel A. F. Sanjuán

Copyright © 2010 Leonimer Flavio de Melo and Jose Fernando Mangili Junior. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In the mobile robotic systems, a precise estimate of the robot pose with the intention of the optimization in the path planning is essential for the correct performance, on the part of the robots, for tasks that are destined to it. This paper describes the use of RF digital signal interacting with beacons for computational triangulation in the way to provide a pose estimative at bidimensional indoor environment, where GPS system is out of range. This methodology takes advantage of high-performance multicore DSP processors to calculate ToF of the order about ns. Sensors data like odometry, compass, and the result of triangulation Cartesian estimative, are fused for better position estimative. It uses a mathematical and computational tool for nonlinear systems with time-discrete sampling for pose estimative calculation of mobile robots, with the utilization of extended Kalman filter (EKF). A mobile robot platform with differential drive and nonholonomic constraints is used as a base for state space, plants and measurements models that are used in the simulations and validation of the experiments.