356 citations · 652 across the 18 of their papers we have counts for
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cs.RO2020★ 19 cited
Broadly-Exploring, Local-Policy Trees for Long-Horizon Task Planning
Brian Ichter, Pierre Sermanet, Corey Lynch
Long-horizon planning in realistic environments requires the ability to reason over sequential tasks in high-dimensional state spaces with complex dynamics. Classical motion planni…
cs.RO2020★ 2 cited
Learning to Play by Imitating Humans
Rostam Dinyari, Pierre Sermanet, Corey Lynch
Acquiring multiple skills has commonly involved collecting a large number of expert demonstrations per task or engineering custom reward functions. Recently it has been shown that…
cs.RO2020★ 3 cited
Language Conditioned Imitation Learning over Unstructured Data
Corey Lynch, Pierre Sermanet
Natural language is perhaps the most flexible and intuitive way for humans to communicate tasks to a robot. Prior work in imitation learning typically requires each task be specifi…