Open access
Sep 2026
AutoRL: A Tightly Synchronized ROS2–Gazebo Pipeline for Offline-Trained Reinforcement Learning-Based Multirotor Attitude Control
AutoRL enforces a strict one-to-one correspondence between agent actions and physics updates via blocking ROS2 service calls, preserving the Markov property required for stable policy learning and enabling verifiable reproducibility independent of the learning algorithm.
Khaled Jarrah, O. Rawashdeh
· Aerospace · 0 citations