Deep Visual MPC-Policy Learning for Navigation

@article{Hirose2019DeepVM,
  title={Deep Visual MPC-Policy Learning for Navigation},
  author={Noriaki Hirose and Fei Xia and Roberto Mart{\'i}n-Mart{\'i}n and Amir Sadeghian and Silvio Savarese},
  journal={IEEE Robotics and Automation Letters},
  year={2019},
  volume={4},
  pages={3184-3191}
}
  • Noriaki Hirose, Fei Xia, +2 authors Silvio Savarese
  • Published 2019
  • Engineering, Computer Science
  • IEEE Robotics and Automation Letters
  • Humans can routinely follow a trajectory defined by a list of images/landmarks. However, traditional robot navigation methods require accurate mapping of the environment, localization, and planning. Moreover, these methods are sensitive to subtle changes in the environment. In this letter, we propose PoliNet, a deep visual model predictive control-policy learning method that can perform visual navigation while avoiding collisions with unseen objects on the navigation path. PoliNet takes in as… CONTINUE READING

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