Robot Navigation Using a Neural Network Extracts From the Decision Tree

The paper will present an artificial neural network model extracts from the decision tree. This paper shows how representing decision trees into a multilayer neural network approach for mobile robot navigation. Two types of models were used in this paper, the first model will design a decision tree architecture that is able to configure itself automatically according to the structure of the mobile robot under consideration, and the second model converts the previous decision tree of robot navigation into an artificial neural network Also here, the kinematics of the differential drive of the wheeled mobile robot were discussed