TY - JOUR
T1 - Range-Only Bearing Estimator for Localization and Mapping
AU - Marcantoni, Matteo
AU - Jayawardhana, Bayu
AU - Bunte, Kerstin
PY - 2023/6/16
Y1 - 2023/6/16
N2 - Navigation and exploration within unknown environments are typical examples in which simultaneous localization and mapping (SLAM) algorithms are applied. When mobile agents deploy only range sensors without bearing information, the agents must estimate the bearing using the online distance measurement for the localization and mapping purposes. In this paper, we propose a scalable dynamic bearing estimator to obtain the relative bearing of the static landmarks in the local coordinate frame of a moving agent in real-time. Using contraction theory, we provide convergence analysis of the proposed range-only bearing estimator and present upper and lower-bound for the estimator gain. Numerical simulations demonstrate the effectiveness of the proposed method.
AB - Navigation and exploration within unknown environments are typical examples in which simultaneous localization and mapping (SLAM) algorithms are applied. When mobile agents deploy only range sensors without bearing information, the agents must estimate the bearing using the online distance measurement for the localization and mapping purposes. In this paper, we propose a scalable dynamic bearing estimator to obtain the relative bearing of the static landmarks in the local coordinate frame of a moving agent in real-time. Using contraction theory, we provide convergence analysis of the proposed range-only bearing estimator and present upper and lower-bound for the estimator gain. Numerical simulations demonstrate the effectiveness of the proposed method.
U2 - 10.1109/LCSYS.2023.3286956
DO - 10.1109/LCSYS.2023.3286956
M3 - Article
SN - 2475-1456
VL - 7
SP - 2503
EP - 2508
JO - IEEE Control Systems Letters
JF - IEEE Control Systems Letters
ER -