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In the computational analysis of the mobile robot trajectory, some specific and fast tools of MAPLE11 soft are used.
In this section the results of computational simulations of the mobile robot trajectory in some specific conditions are presented.
The mobile robot trajectory is simulated in an interval of 0 … 18 time units, divided into five parts, representing the stages of observation and simulation cases too.
Finally, the feasibility and effectiveness of the proposed computational analysis for the mobile robot trajectory is demonstrated by the experimental results.
In the present study, these evolutionary methods have been utilized to conduct the optimum design of a fuzzy controller for mobile robot trajectory tracking.
Encouraging results on several traveling salesman problem instances and its application to the design of fuzzy controllers, in particular the optimization of membership functions for a unicycle mobile robot trajectory control are presented with the proposed method.
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This paper presents a novel integrated approach for efficient optimization based online trajectory planning of topologically distinctive mobile robot trajectories.
Following the results of mobile robots trajectory tracking reported in (Scaglia et al., 2010), the problem of model errors is focused and the zero convergence of tracking errors under polynomial uncertainties is demonstrated.
We test the optimal FLC obtained by the Hybrid PSO GA method using benchmark control plants and an autonomous mobile robot for trajectory tracking control.
Indeed, if a mobile robot follows an unknown trajectory in an unknown environment, the estimation of the robot's pose and the explored map becomes more complicated.
This paper discusses the application of the pattern classification capability of trained neural network for implementing an intelligent control strategy for a mobile robot in executing desired trajectory tracking tasks.
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