Thi Thanh Tam Le

Robust disturbance-aware actor–critic reinforcement learning for multi-DOF robotic manipulators

Building on recent insights that augmenting reinforcement‐learning policies with disturbance estimates improves robustness and sim-to-real transfer, this paper proposes a disturbance-aware actor–critic RL framework for high‐precision robotic manipulators. We derive the dynamics of manipulators ranging from two to six d...