SIMULATION OF DRONE CONTROLLER USING REINFORCEMENT LEARNING AI WITH HYPERPARAMETER OPTIMIZATION

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SIMULATION OF DRONE CONTROLLER USING REINFORCEMENT LEARNING AI WITH HYPERPARAMETER OPTIMIZATION. 

Drone is one of the latest drone technologies that grows with multiple applications; one of the critical applications is for fire-fighting drones such as water hose carrying for firefighting. One of the main challenges of the drone technologies is the non-linear dynamic movement caused by a variety of fire conditions.DF

ADVANTAGE:

The resulting a tree-structure in which a trajectory for the drone can be again found by a search algorithm.1

Work  include tests of the underlined advantages for the rectangular cuboid decomposition.1

THEORY:

Q-Learning theory

The idea is to build a system that can control robot without the remote which it can control itself based on environment learning through trial and error process depend on reward and discount action already taken by robot. In creating the system, will be deploy of machine learning system based on the RL.1


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