# Field-to-Planning (F2P) Learning Framework

A two-stage learning framework turns obstacle point clouds inside the onboard camera frustum into a temporal polar gradient field that no longer separates static from dynamic obstacles, raising success rate by 16 percentage points over the best baseline in dense dynamic scenes while keeping replanning under 4.8 ms.

A two-stage learning framework turns obstacle point clouds inside the onboard camera frustum into a temporal polar gradient field that no longer separates static from dynamic obstacles, raising success rate by 16 percentage points over the best baseline in dense dynamic scenes while keeping replanning under 4.8 ms.