Acting in Meters: Learning Metric Interactions for Precise Robotic Manipulation

arXiv:2609.18243 · cs.RO, cs.LG · Submitted 2026-09-16 · Read on arXiv

cs.RO, cs.LG

Submitted: 2026-09-16

Updated: 2026-09-20

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Alignment — 9× in this paper · explained in 1 episode
• Generalization — 9× in this paper · explained in 13 episodes
• Embeddings — 8× in this paper · explained in 2 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Fine-Tuning — 7× in this paper · explained in 5 episodes
• World Model — 7× in this paper · explained in 7 episodes
• Foundation Model — 6× in this paper · explained in 3 episodes
• Metric Action Interaction Field — 5× in this paper
• Accuracy — 4× in this paper · explained in 1 episode
• Adaptation — 4× in this paper · explained in 1 episode
• Point Clouds — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Semantic Understanding — 3× in this paper · explained in 2 episodes
• Action Space — 2× in this paper · explained in 1 episode
• Aggregation — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Two-stage training — 2× in this paper · explained in 2 episodes
• Vision-Language-Action (VLA) Models — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Average Displacement Error — 1× in this paper
• Benchmarking — 1× in this paper · explained in 3 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Causal Reasoning — 1× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 7 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• LoRA Fine-Tuning — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes
• Task Planning — 1× in this paper · explained in 2 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Two-Stage Framework — 1× in this paper · explained in 2 episodes
• VLA Models — 1× in this paper · explained in 3 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes

Sources

• GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
• GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulation
• RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
• StarVLA: A Lego-like Codebase for Vision-Language-Action Model Developing
• Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising
• Geometric Action Model for Robot Policy Learning
• MiMo-Embodied: X-Embodied Foundation Model Technical Report
• $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
• ${\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities
• Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning
• $\mu_0$: A Scalable 3D Interaction-Trace World Model
• Causal World Modeling for Robot Control
• WAM4D: Fast 4D World Action Model via Spatial Register Tokens
• Planning Takes More Than Token Prediction: Causal Plan for Benchmarking and Building Physically Grounded Embodied Reasoners
• LayerRoute: Action-Conditioned Mixture-of-Layers Routing for Vision-Language-Action Policies
• GeoSem-WAM: Geometry- and Semantic-Aware World Action Models
• SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Model
• SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
• GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch
• PointAction: 3D Points as Universal Action Representations for Robot Control

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