Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning

  title={Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning},
  author={Linhai Xie and Sen Wang and Andrew Markham and Agathoniki Trigoni},
Obstacle avoidance is a fundamental requirement for autonomous robots which operate in, and interact with, the real world. When perception is limited to monocular vision avoiding collision becomes significantly more challenging due to the lack of 3D information. Conventional path planners for obstacle avoidance require tuning a number of parameters and do not have the ability to directly benefit from large datasets and continuous use. In this paper, a dueling architecture based deep double-Q… CONTINUE READING
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