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Found 2 papers, 2 papers with code
Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models, Benchmark and Efficient Evaluation
All the proposed navigation models have been trained with the Habitat simulator on a synthetic office environment and have been tested on the same real-world environment using a real robotic platform.
On Embodied Visual Navigation in Real Environments Through Habitat
Visual navigation models based on deep learning can learn effective policies when trained on large amounts of visual observations through reinforcement learning.
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