Transit-Aware Planning (TAP) enriches navigation policies with object transit data on Dynamic Object Maps, raising success rates by 21.1% in MP3D simulation and 18.3% in real-world tests for finding non-stationary targets.
Dd-ppo: Learning near-perfect pointgoal navigators from 2.5 billion frames, 2020
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Personalized Embodied Navigation for Portable Object Finding
Transit-Aware Planning (TAP) enriches navigation policies with object transit data on Dynamic Object Maps, raising success rates by 21.1% in MP3D simulation and 18.3% in real-world tests for finding non-stationary targets.