Trajectory Planning for an Articulated Tracked Vehicle and Tracking the Trajectory via an Adaptive Model Predictive Control

This paper focuses on the trajectory planning and tracking control of articulated tracked vehicles (ATVs). It utilizes path method based Hybrid A-star minimum snap smoothing to obtain feasible kinematic trajectory. To overcome highly non-linearity ATVs, we proposed a linear-parameter-varying (LPV) tracking-error model. Then, controller was formulated as adaptive model predictive (AMPC). The simulation algorithm showed that strategy could provide for ATVs passing through obstacles. Moreover, compared AMPC with developed in four scenarios. comparison achieved satisfactory errors regarding lateral position orientation angle errors. maximum distance error by has been reduced 72.4% standard-MPC controller. 55.53%. results confirmed system effectively perform automated driving behaviors ATVs.