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- Title
Integration of nonlinear observer and unscented Kalman filter for pose estimation in autonomous truck–trailer and container truck.
- Authors
Kuncara, Ivan Adi; Widyotriatmo, Augie; Hasan, Agus; Kim, Chang-Sei
- Abstract
This paper introduces a new approach to state estimation called nonlinear observer-unscented Kalman filter (NLO-UKF). The proposed method is designed to improve the accuracy of state estimation in complex systems that are subject to nonlinearity and uncertainty. The key idea of the NLO-UKF is to use a nonlinear observer to correct the projected sigma points based on a measurement, and then update the mean and covariance using the UKF. The paper provides a detailed description of the NLO-UKF algorithm and demonstrates its boundedness. The use of NLO-UKF for pose estimation is presented to compare the effectiveness of the proposed method with other state estimation methods in the simulation of an autonomous truck–trailer system and experimentation with a container truck system. The NLO-UKF demonstrates improved accuracy during steady-state estimation.
- Subjects
KALMAN filtering; TRUCK trailers; TRUCKS; NONLINEAR estimation; CONTAINERS; NONLINEAR systems
- Publication
Nonlinear Dynamics, 2024, Vol 112, Issue 13, p11217
- ISSN
0924-090X
- Publication type
Article
- DOI
10.1007/s11071-024-09658-w