9 citations · 11 across the 2 of their papers we have counts for
2 papers
cs.RO2023★ 2 cited
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators
Alexander Herzog, Kanishka Rao, Karol Hausman +37
We describe a system for deep reinforcement learning of robotic manipulation skills applied to a large-scale real-world task: sorting recyclables and trash in office buildings. Rea…
cs.AI2011★ 9 cited
A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control
Todd Hester, Michael Quinlan, Peter Stone
Reinforcement Learning (RL) is a method for learning decision-making tasks that could enable robots to learn and adapt to their situation on-line. For an RL algorithm to be practic…