GeoAAC: Geometry-Based Adaptive Action Chunking from Denoising Trajectories in VLA Policies
cs.RO, cs.AI, cs.LG
Submitted: 2026-09-17
Updated: 2026-09-17
Comments: 9 pages, 6 figures. Submitted to the IEEE International Conference on Robotics and Automation (ICRA) 2027
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware
- VLA Knows Its Limits: Adaptive Execution Horizons for Robot Policies
- Adaptive Action Chunking at Inference-time for Vision-Language-Action Models
- PACE: Phase-Aware Chunk Execution for Robot Policies with Action Chunking
- LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization
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