Abstract
In this study, the performance of autonomous flight was analyzed by introducing the PPO method as reinforcement learning for autonomous flight of drones. A simulator based on the dynamics of a drone was produced, and the performance of autonomous flight was confirmed when reinforcement learning was applied to a drone using this simulator. After that, the possibility of autonomous flight was confirmed by applying the PPO algorithm to the actual drone. Also, a lightweight embedded PC was attached to the drone to perform independent calculations to simultaneously construct obstacle avoidance and path planning.
| Original language | English |
|---|---|
| Pages (from-to) | 955-963 |
| Number of pages | 9 |
| Journal | Journal of Institute of Control, Robotics and Systems |
| Volume | 26 |
| Issue number | 11 |
| DOIs | |
| State | Published - Nov 2020 |
Keywords
- Autonomous drone
- PPO(Proximal Policy Optimization)
- Reinforcement learning
- Simulator
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