Vehicle tracking based on robust bounded-error nonlinear state estimation using interval analysis

Abstract

Designing efficient localization techniques is a key issue for autonomous vehicles. This localization is usually based on information provided by proprioceptive sensors such as odometers (encoders that measure the rotation of each wheel) and exteroceptive sensors such as ultrasonic or laser telemeters. This paper is devoted to the localization of a vehicle in a structured environment described by a set of segments, without an initial precise localization. The main contribution of this work is to show that real-time robust localization can be achieved using the bounded-error technique in a real environment.