Simulator-based Study on Path Planning and Path Following Algorithms for Self-propelled Artillery Unit

As autonomous technologies continue to advance, their integration into ground weapon systems has accelerated. Among these systems, self-propelled artillery has recently become the subject of research in autonomous operation. Given that self-propelled artillery is a specialized type of tracked vehicle, both path planning and path following algorithms must be carefully tailored to suit its unique mobility characteristics. In this paper, we propose a complete framework for autonomous driving of a self-propelled artillery platform. For path planning, we employ a simplified bicycle kinematic model combined with a cost function that accounts for the platform’s specific physical constraints and dimensions. For path following, we design an LQR-based controller using a dynamic bicycle model to ensure accurate trajectory tracking. Additionally, we implement a low-level Model Predictive Control (MPC) module that outputs driving torques for smooth and responsive control. To validate the feasibility of the proposed approach, we conduct experiments in a high-fidelity simulation environment that models both the nonlinear dynamics of tracked vehicles and the effects of uneven terrain. The results demonstrate that our algorithm enables autonomous navigation of a self-propelled artillery system in complex terrain environments.