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- W4380343397 abstract "This work focuses on the trajectory tracking control of Wheeled Mobile Robots (WMRs) through neural networks and feedback control techniques. We employ different neural network architectures to analyze the environment, divide the road into segments, and generate reference trajectories for the WMR. For control purposes, we consider the nonlinear kinematic model of the WMR considering the nonholonomic constraints. Then, this kinematic model is fully linearized through a dynamic controller, which accomplishes the trajectory tracking objective. The reference trajectory procedure and control scheme combination are used to attain the desired trajectory tracking objective. To this end, we utilize a numerical simulator for a scale vehicle, namely the Autominy car. Numerical simulations using Matlab and the Robotic Operative System (ROS) demonstrate the performance of the proposed control methodology." @default.
- W4380343397 created "2023-06-13" @default.
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- W4380343397 date "2023-01-01" @default.
- W4380343397 modified "2023-09-23" @default.
- W4380343397 title "Trajectory Tracking Control of Wheeled Mobile Robots Using Neural Networks and Feedback Control Techniques" @default.
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- W4380343397 doi "https://doi.org/10.1007/978-3-031-28999-6_24" @default.
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