Fuzzy constraint satisfaction approach for landmark recognition in mobile robotics

Abstract

This work deals with landmark recognition in mobile robotics, using a new model based on Constraint Satisfaction Problems (CSP): the Multivariable Fuzzy Temporal Profile model (MFTP). A representation supported by CSPs makes it possible to capture a morphological description of the patterns that landmarks give rise to on sensor readings. Its representation, based on Fuzzy Set Theory, allows the imprecision and uncertainty that are characteristic of the problem to be handled. The work places special emphasis on those aspects that are resolved by means of this approach: the ability to model semantically rich landmarks, the simplicity of its description, and the high computational efficiency of the proposed detection algorithms. Finally, a validation of the model in the detection of various landmarks over ultrasound (US) sensors is presented. In spite of these sensors being highly noisy and imprecise, the MFTP model successfully detects 95% of the landmarks on the reference wall.