IMP-HRL augments the MAPLE hierarchical RL framework with impedance primitives and an adaptive stiffness controller, improving compliance and success rates on sequential contact tasks, especially wiping.
Variable impedance control in end-effector space: An action space for reinforcement learning in contact-rich tasks,
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Impedance Primitive-augmented Hierarchical Reinforcement Learning for Sequential Tasks
IMP-HRL augments the MAPLE hierarchical RL framework with impedance primitives and an adaptive stiffness controller, improving compliance and success rates on sequential contact tasks, especially wiping.