74 citations · 279 across the 24 of their papers we have counts for
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cs.RO2021★ 2 cited
Marginal MAP Estimation for Inverse RL under Occlusion with Observer Noise
Prasanth Sengadu Suresh, Prashant Doshi
We consider the problem of learning the behavioral preferences of an expert engaged in a task from noisy and partially-observable demonstrations. This is motivated by real-world ap…
cs.RO2019★ 24 cited
SA-Net: Deep Neural Network for Robot Trajectory Recognition from RGB-D Streams
Nihal Soans, Ehsan Asali, Yi Hong +1
Learning from demonstration (LfD) and imitation learning offer new paradigms for transferring task behavior to robots. A class of methods that enable such online learning require t…
cs.RO2017
Inverse Reinforcement Learning Under Noisy Observations
Shervin Shahryari, Prashant Doshi
We consider the problem of performing inverse reinforcement learning when the trajectory of the expert is not perfectly observed by the learner. Instead, a noisy continuous-time ob…