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Maintaining a map online is resource-consuming while a robust navigationsystem usually needs environment abstraction via a well-fused map. In thispaper, we propose a mapless planner which directly conducts such abstraction onthe unfused sensor data. A limited-memory data structure with a reliableproximity query algorithm is proposed for maintaining raw historicalinformation. A sampling-based scheme is designed to extract the free-spaceskeleton. A smart waypoint selection strategy enables to generate high-qualitytrajectories within the resultant flight corridors. Our planner differs fromother mapless ones in that it can abstract and exploit the environmentinformation efficiently. The online replan consistency and success rate areboth significantly improved against conventional mapless methods.

Mapless-Planner: A Robust and Fast Planning Framework for Aggressive Autonomous Flight without Map Fusion