  Maintaining a map online is resource-consuming while a robust navigation
system usually needs environment abstraction via a well-fused map. In this
paper, we propose a mapless planner which directly conducts such abstraction on
the unfused sensor data. A limited-memory data structure with a reliable
proximity query algorithm is proposed for maintaining raw historical
information. A sampling-based scheme is designed to extract the free-space
skeleton. A smart waypoint selection strategy enables to generate high-quality
trajectories within the resultant flight corridors. Our planner differs from
other mapless ones in that it can abstract and exploit the environment
information efficiently. The online replan consistency and success rate are
both significantly improved against conventional mapless methods.
