Ponencia
Neural Predictive Control for Mobile Robot Navigation in a Partially Structured Static Environment
Autor/es | Gómez Ortega, Juan
Camacho, Eduardo F. ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
Departamento | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática |
Fecha de publicación | 1996 |
Fecha de depósito | 2020-04-28 |
Publicado en |
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ISBN/ISSN | 1474-6670 |
Resumen | This paper presents a way of implementing a Model Based Predictive Controller (MBPC) for mobile robot navigation when unexpected static obstacles are present in the robot environment. The method uses a non-linear model of ... This paper presents a way of implementing a Model Based Predictive Controller (MBPC) for mobile robot navigation when unexpected static obstacles are present in the robot environment. The method uses a non-linear model of mobile robot kinematics and thus allows an accurate prediction of the future trajectories. An ultrasonic ranging system has been used for obstacle detection. A Multilayer Perceptron is used to implement the MBPC, allowing real-time and also eliminating the need for data sensor high level processing. The perceptron has been trained to reproduce the MBPC behaviour in a supervised manner. Experimented results obtained when applying the neural network controller to a mobile robot are given in the paper. |
Cita | Gómez Ortega, J. y Camacho, E.F. (1996). Neural Predictive Control for Mobile Robot Navigation in a Partially Structured Static Environment. En Triennial World Congress (8125-8130), San Francisco, USA: Elsevier. |
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