Residual dynamics learning for trajectory tracking for multi-rotor aerial vehicles.

ABSTRACT: This paper presents a technique to model the residual dynamics between a high-level planner and a low-level controller by considering reference trajectory tracking in a cluttered environment as an example scenario. We focus on minimising residual dynamics that arise due to only the kinematical modelling of high-level planning. The kinematical modelling is sufficient for such scenarios due to safety constraints and aggressive manoeuvres that are difficult to perform when the environment is cluttered and dynamic. We used a simplified motion model to represent the motion of the quadrotor when formulating the high-level planner. The Sparse Gaussian Process Regression-based technique is proposed to model the residual dynamics. Recently proposed Data-Driven MPC is targeting aggressive manoeuvres

SUBMITTER: Kulathunga G 

PROVIDER: S-EPMC10810356 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature