56 citations · 266 across the 35 of their papers we have counts for
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cs.RO2019★ 4 cited
Learning Generalizable Locomotion Skills with Hierarchical Reinforcement Learning
Tianyu Li, Nathan Lambert, Roberto Calandra +2
Learning to locomote to arbitrary goals on hardware remains a challenging problem for reinforcement learning. In this paper, we present a hierarchical learning framework that impro…
cs.RO2019★ 1 cited
Low Level Control of a Quadrotor with Deep Model-Based Reinforcement Learning
Nathan O. Lambert, Daniel S. Drew, Joseph Yaconelli +3
Designing effective low-level robot controllers often entail platform-specific implementations that require manual heuristic parameter tuning, significant system knowledge, or long…