This paper presents a novel visual navigation strategy applied to real-time guidance and control of autonomous rotorcraft in outdoor environments. The proposed approach acquires a sequence of snapshots during an initial exploratory journey and computes the rotorcraft's 3D position and velocity relative to the locations of these memorised snaphots during its long-range homing return. This mapless algorithm provides an efficient strategy that enables route learning and drift-free navigation in unknown and unstructured 3D environments, based on a simple and sparse visual route description. The performance of our approach is evaluated in closed-loop flight experiments onboard a small-size rotorcraft. Dynamic path optimisation is observed when navigating back and forth between two locations of interest.