Abstract:In semantic navigation, a top-down map with accurate and complete semantic information is vital to subsequent decision-making. However, due to occlusions and limitations of the robot's field of view (FOV), there are often unobserved areas in the top-down maps. To address this problem, recent works have studied semantic map prediction to complete the top-down maps. In this work, we propose to improve map prediction by integrating relational information. We propose RSMPNet, a relationship-guided semantic map pre… Show more
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