Gedson Faria

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Potential field is a reactive method that has been used for trajectory control of mobile robots. In this method the robot behaves like a particle moving under the influence of an artificial potential produced by the target and the obstacles. This method has lower computational cost than others that utilize maps as a world model. However, one problem or this(More)
In this paper, we introduce a modification in the potential field method based on boundary value problems to control multiple robots. In this new method, that we call locally oriented potential field (LOPF), the robots share a single map, but the field is adjusted locally for each robot using a bias vector. We show that the LOPF method is very appropriated(More)
Artificial Neural Networks are computational devices inspired by the human brain for solving problems. Currently, they are being widely applied for solving problems in several areas such as: robotics, image processing, pattern recognition, etc.... The neural network model, Multilayer Perceptrons, is one of the most used due to its simple learning algorithm.(More)
There are many potential field techniques to control multiple robots. Among them are Arkin's Potential Field, Harmonic Potential Field and other ones based on the solution of the Boundary Value Problem (BVP). Most of them have been applied to control just one robot. In this paper, a modification in a technique of Potential Field based on the solution of BVP(More)
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