Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning

16 Sep 2016Yuke ZhuRoozbeh MottaghiEric KolveJoseph J. LimAbhinav GuptaLi Fei-FeiAli Farhadi

Two less addressed issues of deep reinforcement learning are (1) lack of generalization capability to new target goals, and (2) data inefficiency i.e., the model requires several (and often costly) episodes of trial and error to converge, which makes it impractical to be applied to real-world scenarios. In this paper, we address these two issues and apply our model to the task of target-driven visual navigation... (read more)

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