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Learning from Demonstration
A Non-linear Manifold Alignment Approach to Robot Learning from Demonstrations
The number and variety of robots active in real-world environments are growing, as well as the skills they are expected to acquire, and …
Ndivhuwo Makondo
,
Michihisa Hiratsuka
,
Benjamin Rosman
,
Osamu Hasegawa
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Trajectory Learning from Human Demonstrations via Manifold Mapping
This work proposes a framework that enables arbitrary robots with unknown kinematics models to imitate human demonstrations to acquire …
Michihisa Hiratsuka
,
Ndivhuwo Makondo
,
Benjamin Rosman
,
Osamu Hasegawa
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Nonparametric Bayesian Reward Segmentation for Skill Discovery Using Inverse Reinforcement Learning
We present a method for segmenting a set of unstructured demonstration trajectories to discover reusable skills using inverse …
Pravesh Ranchod
,
Benjamin Rosman
,
George Konidaris
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