For embodied AI agents navigating from visual instructions, explicitly modeling temporal context (past-only memory), multi-step planning with single-step execution, and decoupled termination detection significantly improves navigation success and efficiency.
DreamFly improves aerial drone navigation by combining three key techniques: a causal memory system that uses only past observations to avoid information leakage, a receding-horizon planning approach that predicts multiple future actions but executes one at a time, and explicit stop detection from action predictions.