Application of multicriteria decision-making techniques to manoeuvre planning in nonholonomic robots

In the scientific literature, one can find different techniques for tackling the problem involved in generating manoeuvres in robots with nonholonomic restrictions. Among these, probabilistic generation methods have been widely used. This paper presents a new technique that enables the best paths to be selected from among a set provided by a probabilistic planning method (RRT). This selection involved the application of multicriteria decision-making techniques (MCDMT). The particularity of these MCDMT lies in the fact that they provide the same result as would arise if the decision had been taken by a human being. The application of these techniques (generation and ranking) has enabled the development of an automatic tool for finding the best manoeuvres for nonholonomic robots. Lastly, we present the application of these techniques to a real situation, obtaining excellent results.