Abstract:Dense crowds are challenging scenes for an autonomous mobile robot. Planning in such an interactive environment requires predicting uncertain human intention and reaction to future robot actions. Concerning these capabilities, we propose a probabilistic forecasting model which factorizes the human motion uncertainty as follows: 1) A (conditioned) normalizing flow (CNF) estimates the densities of human goals.2) We forecast the crowd's trajectory density towards the goals by autoregressively (AR) inferring the i… Show more
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