RT-HCP combines a physics-informed model, multi-step planning, and an actor-critic policy to learn a swing-up controller on a real Furuta pendulum under strict time and sample limits.
Real-time reinforcement learning,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
RT-HCP: Dealing with Inference Delays and Sample Efficiency to Learn Directly on Robotic Platforms
RT-HCP combines a physics-informed model, multi-step planning, and an actor-critic policy to learn a swing-up controller on a real Furuta pendulum under strict time and sample limits.