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NaP-Control: Diffusion Prior for Fast Character Control

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NaP-Control from ETH Zurich combines reinforcement learning with a task-agnostic diffusion motion prior, using latent noise optimization for precise and fast whole-body character control across goal reaching, velocity control and object interaction.

NaP-ControlCharacter ControlDiffusion PriorReinforcement LearningETH ZurichIsaacGymHumanoidWhole-Body ControlPhysics simulation
Category: humanoid
Author: @rsasaki0109
Date: 2026-08-23T00:00:00
Duration: 16.2s
Source: https://x.com/rsasaki0109/status/2091421974488924321
Reference: https://github.com/chiawenchen/NaP

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