Tethered Multicopter Guidance in GPS-Denied Environments Through Reinforcement Learning
AIAA SCITECH 2023 Forum(2023)
摘要
This paper presents a novel reinforcement learning (RL) approach for a tethered drone to follow a predefined three-dimensional trajectory in a GPS-denied environment. The adopted Q-learning strategy determines high-level actions using raw observations from the onoard accelerometers, gyros, and altimeter, which facilitates a low-level proportional-integral-derivative (PID) controller to drive the drone through the desired waypoints on a reference trajectory. The effectiveness of the proposed approach is demonstrated in a simulated environment.
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关键词
gps-denied
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