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About this paper
Diwen Liu, Yiyang Shao, Borui Wang, Chi Zhang, Jizhuo Chen, Jiaming Wang, Benyun Zhao, Zhongyu Li and 1 more
EchoNav turns recent RGB images into a local bird’s-eye map that carries earlier visual evidence forward, predicts occluded occupancy, and represents prediction reliability without depth, camera poses, or geometric warping. A planner uses the map while handling robot constraints. In sequential two-goal simulation, it succeeds in 86.3% of episodes, 32.2 points above the strongest evaluated baseline, with current route waypoints provided.
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