A resilient solution to Range-Only SLAM based on a decoupled landmark range and bearing reconstruction

A Range Only Simultaneous Localization and Mapping (RO-SLAM) problem is considered in this paper. The robot is a unicycle like vehicle equipped with encoders on the actuated wheels, which measures the distance to a set of UWB landmarks located in unknown position in the surrounding. A Multi Hy-potheses Extended Kalman Filter (MHEKF), one for each landmark, is designed to dynamically estimate the range and the bearing of the observed landmark. These estimates, regarded as measurements with a proper covariance matrix, are used in an EKF SLAM algorithm, endowed with a resilient module to discern and possibly to temporarily discard landmarks with an unreliable range and bearing estimate. This allows to cope with the initial uncertainty characterizing the bearing reconstruction, but also to resist the effects of outliers and to detect possible abnormal situations. Simulation and experimental results illustrate the effectiveness of the proposed approach compared to other methods available in the literature, especially in case of significant perturbations, like the sudden and unmodeled shift of the landmarks.(c) 2022 Elsevier B.V. All rights reserved.