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Found 2 papers, 1 papers with code
Grasp Transfer based on Self-Aligning Implicit Representations of Local Surfaces
This work addresses the problem of transferring a grasp experience or a demonstration to a novel object that shares shape similarities with objects the robot has previously encountered.
Reward Conditioned Neural Movement Primitives for Population Based Variational Policy Optimization
For this, the experience of the robot, which can be bootstrapped from demonstrated trajectories, is used to train a novel Neural Processes-based deep network that samples from its latent space and generates the required trajectories given desired rewards.
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