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Unlabeled robot deployment failures don't need expensive corrective demonstrations to be useful: steering linearly separable latent states away from failure modes fixes policy execution with just 0.5% added parameters.
Real-world robot failures can be autonomously converted into interactive digital twins for targeted RL, boosting out-of-distribution manipulation by 18.75% while completely bypassing manual teleoperated recovery.
H-RePlan achieves a remarkable increase in task completion rates by intelligently distinguishing between local and global recovery strategies in multi-device environments.
Qwen-RobotNav redefines navigation by allowing real-time reconfiguration of strategies, achieving unprecedented flexibility and performance across diverse tasks.