Design and prototyping of a low-cost vehicle localization system with guaranteed convergence properties

This work presents a low-cost vehicle localization system, using measurements from one gyroscope, two wheel speed sensors and a GPS, to estimate the heading, velocity and position of a vehicle. Taking advantage of the nonholonomic constraints, the design of the observer (or “filter”) takes into account imperfections of the embedded sensor measurements, such as a slowly time-varying gyroscope bias or some uncertainty in the wheel diameter value. Thanks to a well-chosen nonlinear structure, the estimator is easy to tune, easy to implement, and well-behaved even at very low speed. Moreover, the proposed filter has guaranteed convergence properties when GPS is available and keeps providing good estimations during GPS losses. Simulation and experiment results in urban area illustrate the good performance of the algorithm.

Research highlights
► We propose a low-cost vehicle localization system based on a nonlinear filter.
► Measurements from one biased gyroscope, one speedometer, and a GPS are used.
► The filter is easy to tune and to implement, and behaves well even at very low speed.
► The observer has guaranteed convergence properties when GPS is available.
► Simulations and experiments in urban area validate the good behavior of the system.