Estimation of time-to-contact from Tau-margin and statistical analysis of behavior

Mobile robots need a measure for assessing the proximity of obstacles named Time-To-Contact. In this paper, we use the monocular vision in robot navigation in order to estimate the Time-To-Contact computing the Tau-margin by the ratio of change of apparent size of an obstacle. Our contribution is the proposal of a statistical method to predict the Time-To-Contact, where we collect data in different time slots. To give greater robustness in our estimations, it is proposed that the robot generates a linear approximation by removing the values that apparently do not share a linear behavior as the rest of the estimations. This is in order to external factors such as changes in lighting or problems when the robot is in motion, do not affect the estimation of the Time-To-Contact. Models and data obtained are compared and statistically analyzed visually and quantitatively. Experimental results from the application of the method on synthetic and real scenarios are reported.