Year: 2025
Type: conference-paper
Abstract: Estimating a vehicle’s pose in uncertain environments is a key challenge in autonomous navigation due to noisy sensor data and the nonlinear nature of kinematic models. This study focuses on computing the evolving covariance matrix for a rear-wheel bicycle model under uncertainty in wheel displacement and steering angle. By linearizing trigonometric terms using Taylor series, we derive accurate closed-form expectations that closely match Monte Carlo simulations. To our knowledge, this is the first complete and precise closed-form derivation for this model, addressing limitations in prior work.
Authors: Shafayat Abrar, M. Zaeem Baig, Shahir Ul Islam Anzal, Abdul Basit Memon
Institution: Habib University
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4412404989