Corpus ID: 210064528

Learning to Move with Affordance Maps

@article{Qi2020LearningTM,
  title={Learning to Move with Affordance Maps},
  author={William Qi and R. T. Mullapudi and Saurabh Gupta and D. Ramanan},
  journal={ArXiv},
  year={2020},
  volume={abs/2001.02364}
}

• William Qi, R. T. Mullapudi, +1 author D. Ramanan
• Published 2020
• Computer Science
• ArXiv

The ability to autonomously explore and navigate a physical space is a fundamental requirement for virtually any mobile autonomous agent, from household robotic vacuums to autonomous vehicles. Traditional SLAM-based approaches for exploration and navigation largely focus on leveraging scene geometry, but fail to model dynamic objects (such as other agents) or semantic constraints (such as wet floors or doorways). Learning-based RL agents are an attractive alternative because they can… Expand

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