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The project Smartcopter aims to achieve completely autonomous navigation in a GPS denied environment, by using completely vision-based systems such as normal cameras, depth cameras, tracking cameras, etc. and analyzing the depth information and other relevant data thus obtained.


We intend to work on obstacle avoidance, experiment on path planning algorithms to achieve completely autonomous navigation in a GPS denied environment.


  • Firstly, we shall try implementing basic obstacle avoidance to make sure that the drone is capable of safe flight.
  • We shall then try implementing traditional global path planning using Open Motion Planning Library (OMPL), Moveit and PX4 avoidance.
  • We then go a step ahead, for this is a "smart" copter, we plan on using Deep learning and reinforcement learning algorithms to implement path planning, which would have happened previously, the traditional way.
  • There are various applications to this project some of which are avoidance, surveying and swarm missions, delivery applications, etc.


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