This paper presents a motion planning scheme we call Model Predictive Planning (MPP), designed to optimize trajectories through obstacle-laden environments. The approach involves path planning, trajectory refinement through the solution of a quadratic program, and real-time selection of optimal trajectories. The paper highlights three technical innovations: a raytracing-based path-to-trajectory refinement, the integration of this technique with a multi-path planner to overcome difficulties due to local minima, and a method to achieve timescale separation in trajectory optimization. The scheme is demonstrated through simulations on a 2D longitudinal aircraft model and shows strong obstacle avoidance performance.