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A codebase for determining obstacle avoidance policy for UAVs within a contained grid using standard q-learning methods and a neural network.

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ShayonX/uav-obstacle-avoidance

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matlab

matlab

 
 

.gitignore

.gitignore

 
 

CreateEnvironment.py

CreateEnvironment.py

 
 

Environment-0.txt

Environment-0.txt

 
 

Environment.txt

Environment.txt

 
 

GridWorld.py

GridWorld.py

 
 

agent.py

agent.py

 
 

entity.py

entity.py

 
 

environment.py

environment.py

 
 

gen_grid.py

gen_grid.py

 
 

neural_network.py

neural_network.py

 
 

simulation.py

simulation.py

 
 

system.py

system.py

 
 

uav.py

uav.py

 
 

visualizer.py

visualizer.py

 
 

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A codebase for determining obstacle avoidance policy for UAVs within a contained grid using standard q-learning methods and a neural network.

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  • Python 75.2%
  • MATLAB 24.8%