Trajectory Execution for Mobile Robots Using Neural Networks: DE
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Techniques based on the use of artificial neural networks are currently attracting growing interest in the fields of control and robotics. The speed of processing, learning and adaptation capabilities, as well as the robustness of these approaches, are largely motivating much of the work in this field-the control of mobile robots. The aim of this work is to use artificial neural networks in the control of wheeled mobile robots. This study will enable these robots, using artificial neural controllers, to follow a predefined reference trajectory.
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Bol
Techniques based on the use of artificial neural networks are currently attracting growing interest in the fields of control and robotics. The speed of processing, learning and adaptation capabilities, as well as the robustness of these approaches, are largely motivating much of the work in this field-the control of mobile robots. The aim of this work is to use artificial neural networks in the control of wheeled mobile robots. This study will enable these robots, using artificial neural controllers, to follow a predefined reference trajectory.
Bol
Techniques based on the use of artificial neural networks are currently attracting growing interest in the fields of control and robotics. The speed of processing, learning and adaptation capabilities, as well as the robustness of these approaches, are largely motivating much of the work in this field-the control of mobile robots. The aim of this work is to use artificial neural networks in the control of wheeled mobile robots. This study will enable these robots, using artificial neural controllers, to follow a predefined reference trajectory.
AmazonPages: 60, Paperback, Our Knowledge Publishing
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