Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Benchmarking Augmentation Methods for Learning Robust Navigation Agents:
  the Winning Entry of the 2021 iGibson Challenge   Recent advances in deep reinforcement learning and scalable photorealistic
simulation have led to increasingly mature embodied AI for various visual
tasks, including navigation. However, while impressive progress has been made
for teaching embodied agents to navigate static environments, much less
progress has been made on more dynamic environments that may include moving
pedestrians or movable obstacles. In this study, we aim to benchmark different
augmentation techniques for improving the agent's performance in these
challenging environments. We show that adding several dynamic obstacles into
the scene during training confers significant improvements in test-time
generalization, achieving much higher success rates than baseline agents. We
find that this approach can also be combined with image augmentation methods to
achieve even higher success rates. Additionally, we show that this approach is
also more robust to sim-to-sim transfer than image augmentation methods.
Finally, we demonstrate the effectiveness of this dynamic obstacle augmentation
approach by using it to train an agent for the 2021 iGibson Challenge at CVPR,
where it achieved 1st place for Interactive Navigation. Video link:
https://www.youtube.com/watch?v=HxUX2HeOSE4

3
The categories of this paper are: physics
4
The categories of this paper are: cond-mat
12
The categories of this paper are: nucl-th
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The categories of this paper are: mtrl-th
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The categories of this paper are: hep-lat
13
The categories of this paper are: quant-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: chao-dyn
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The categories of this paper are: stat
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The categories of this paper are: gr-qc
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The categories of this paper are: plasm-ph
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The categories of this paper are: hep-ph
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The categories of this paper are: q-alg
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The categories of this paper are: ao-sci
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The categories of this paper are: alg-geom
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The categories of this paper are: nlin