95 citations · 228 across the 27 of their papers we have counts for
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cs.RO2026
Real-World Reinforcement Learning with MPC Scaffolding for Dexterous Manipulation
Emek Barış Küçüktabak, Karankumar Patel, Zhaodong Yang +3
Real-world reinforcement learning (RL) offers a promising route to dexterous manipulation policies that can adapt directly from physical interaction, but learning is hindered by in…
cs.RO2026
Primitive-Informed Sampling-Based MPC for Multi-Fingered Dexterous Manipulation
Emek Barış Küçüktabak, Karankumar Patel, Jinda Cui +3
We present a primitive-informed sampling-based model predictive control (MPC) framework for multi-fingered dexterous manipulation. Sampling-based MPC evaluates candidate control tr…