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The paper introduces aUToPath, a unified online planning and control framework for autonomous vehicles that combines lattice-based and free-space search to generate optimal driveable corridors in complex urban environments. This framework uses sequential convex programming (SCP)-based model predictive control (MPC) to refine these corridors into smooth, dynamically feasible trajectories by solving a single optimization problem for both trajectory generation and control. Experimental results in simulation and on a Chevrolet Bolt EUV demonstrate the system's ability to navigate dense obstacle fields with a 100% success rate and no constraint violations.
aUToPath achieves 100% success in real-world autonomous driving trials by unifying global planning and control into a single optimization problem, outperforming decoupled approaches.
This paper presents aUToPath, a unified online framework for global path-planning and control to address the challenge of autonomous navigation in cluttered urban environments. A key component of our framework is a novel hybrid planner that combines pre-computed lattice maps with dynamic free-space sampling to efficiently generate optimal driveable corridors in cluttered scenarios. Our system also features sequential convex programming (SCP)-based model predictive control (MPC) to refine the corridors into smooth, dynamically consistent trajectories. A single optimization problem is used to both generate a trajectory and its corresponding control commands; this addresses limitations of decoupled approaches by guaranteeing a safe and feasible path. Simulation results of the novel planner on randomly generated obstacle-rich scenarios demonstrate the success rate of a free-space Adaptively Informed Trees* (AIT*)-based planner, and runtimes comparable to a lattice-based planner. Real-world experiments of the full system on a Chevrolet Bolt EUV further validate performance in dense obstacle fields, demonstrating no violations of traffic, kinematic, or vehicle constraints, and a 100% success rate across eight trials.
