This paper presents a novel reac.ve naviga.on algo- rithm for wheeled mobile robots under non-holonomic constraints and in unknown environments. Two tech- niques are proposed: a geometrical based technique and a neural network based technique. The mobile robot trav- els to a pre-defined goal posi.on safely and e.ciently without any prior map of the environment by modulat- ing its steering angle and turning radius. The dimen- sions and shape of the robot are incorporated to deter- mine the set of all possible collision-free steering angles. The algorithm then selects the best steering angle can- didate. In the geometrical naviga.on technique, a safe turning radius is computed based on an equa.on derived from the geometry of the problem. On the other hand, the neural-based technique aims to generate an op.- mized trajectory by using a user-defined objec.ve func- .on which minimizes the traveled distance to the goal po- si.on while avoiding obstacles. The experimental results demonstrate that the algorithms are capable of driving the robot safely across a variety of indoor environments.
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