Physically based sensor modeling for a sonar map in a specular environment

A method for solving the specular reflection problem of sonar systems has been developed and implemented. This method, the specular reflection probability method, permits the robot to construct a high-quality probability map of an environment composed of specular surfaces. The method uses two parameters, the range confidence factor (RCF) and orientation probability. The RCF is the measure of confidence in the returning range from a sensor under a reflective environment, and the factor will have low values for long range information and vice versa. Orientation probability represents the surface orientation of an object. Bayesian reasoning is used to update the orientation probability from the range readings of the sensor.<
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