This research paper proposes an efficient model predictive control (MPC) strategy for autonomous miniature racing. It uses a feasible sequential quadratic programming (SQP) algorithm to generate intermediate iterations, which allows the solver to stop after any number of iterations without jeopardizing recursive feasibility. This strategy provides suboptimal and yet feasible solutions with a lower computational footprint than other methods. The authors demonstrate the effectiveness of this strategy through simulations and physical experiments with autonomous miniature race cars. The results show that the proposed method is significantly faster than the state-of-the-art solver Ipopt.
Publication date: 5 Jan 2024
Project Page: Not provided
Paper: https://arxiv.org/pdf/2401.02194
