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Autonomous-Drone-Navigation-using-Deep-Reinforcement-Learning

The goal is to build an autonomous system capable of navigating areas(small scale) without the use of GPS technology. The inspiration of the project is taken from recent advances in Semantic Segmentation and Deep Reinforcement Learning which have proven to be very successful in the context of Autonomous Navigation in the case of cars. We aim to extend it to drones. Navigation of areas involves obstacle avoidance, decision based system to classify input camera feed for commands for navigation. We are currently using ROS for interfacing.


Timeline

  • Order of materials required for drone and initial research
  • Implementation of initial model (Nvidia TrailNet): https://arxiv.org/abs/1705.02550
  • Dec '18: Research on Semantic Segmentation and Deep Reinforcement Learning
  • Jan '19: Implementation of models
  • Feb '19: Quark presentation

Research Papers (Resources)

Semantic Segmentation:

Deep Reinforcement Learning


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Autonomous Drone Navigation Project using Deep Reinforcement Learning

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