Improving Imitation Learning Efficiency for Manipulation through Geometric Prior Pretraining
Improving Imitation Learning Efficiency for Manipulation through Geometric Prior Pretraining
This research presents a geometric visual pretraining dataset designed to enhance the efficiency of imitation learning for robotic manipulation.
The study demonstrates that pretraining a policy on simplified geometric scenes containing only a plane, an object, and a hand improves early-stage success rates in imitation learning for manipulation across multiple simulated robots and real-world tasks with limited task-specific demonstrations.
Source: arXiv Robotics — research abstracts · Read original article ↗
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Source：arXiv Robotics — research abstracts · arxiv.org