AdaTempo: Learning Shared Relative Tempo from Demonstrations for Faster Robot Manipulation
cs.RO
Submitted: 2026-10-02
Updated: 2026-10-02
Sources
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- SpeedAug: Policy Acceleration via Tempo-Enriched Policy and RL Fine-Tuning
- RT-1: Robotics Transformer for Real-World Control at Scale
- ManiCM: Real-time 3D Diffusion Policy via Consistency Model for Robotic Manipulation
- FAST: Efficient Action Tokenization for Vision-Language-Action Models
- Proleptic Temporal Ensemble for Improving the Speed of Robot Tasks Generated by Imitation Learning
- Speedup Patch: Learning a Plug-and-Play Policy to Accelerate Embodied Manipulation
- TempoVLA: Learning Speed-Controllable Vision-Language-Action Policies
- B-spline Policy: Accelerating Manipulation Policies via B-spline Action Representations
- ESPADA: Execution Speedup via Semantics Aware Demonstration Data Downsampling for Imitation Learning
- VOLT: Vision and Language Trajectory Segmentation for Faster-than-Demonstration Policies
- SkiP: When to Skip and When to Refine for Efficient Robot Manipulation
- Arc-Length-Based Warping for Robot Skill Synthesis from Multiple Demonstrations
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