Task-Specified Active Metrological Inspection with Measurement-Steered VLA Manipulation and Deterministic Evidence Gating

arXiv:2609.14219 · cs.RO, cs.AI, cs.CV · Submitted 2026-09-13 · Read on arXiv

cs.RO, cs.AI, cs.CV

Submitted: 2026-09-13

Updated: 2026-09-13

Comments: 19 pages, 13 figures

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

Terminology

• Admissibility — 30× in this paper · explained in 2 episodes
• Consistency — 12× in this paper · explained in 3 episodes
• Benchmark — 10× in this paper · explained in 2 episodes
• Grounding — 8× in this paper · explained in 3 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Verification — 7× in this paper · explained in 2 episodes
• Abstention — 6× in this paper · explained in 1 episode
• Foundation Model — 5× in this paper · explained in 3 episodes
• Steering — 5× in this paper · explained in 2 episodes
• Foundation Models — 4× in this paper · explained in 7 episodes
• Provenance — 4× in this paper · explained in 3 episodes
• Affordance — 3× in this paper · explained in 1 episode
• Calibration — 3× in this paper · explained in 7 episodes
• Conference on Computer Vision and Pattern Recognition — 3× in this paper
• Adaptation — 2× in this paper · explained in 1 episode
• From Requirements to Admissible Metrological Evidence — 2× in this paper
• Ablation — 1× in this paper · explained in 1 episode
• Active Perception — 1× in this paper · explained in 2 episodes
• Agentic Framework — 1× in this paper · explained in 6 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Generalization — 1× in this paper · explained in 13 episodes
• Ground Vehicle Systems Center — 1× in this paper
• Hallucination — 1× in this paper · explained in 3 episodes
• Hierarchical Framework — 1× in this paper · explained in 2 episodes
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 9 episodes
• Regret — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Vision-Language-Action (VLA) Models — 1× in this paper · explained in 2 episodes

Sources

• GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks
• RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
• $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
• World Action Models are Zero-shot Policies
• Fast-WAM: Do World Action Models Need Test-time Future Imagination?
• DiT4DiT: Jointly Modeling Video Dynamics and Actions for Generalizable Robot Control
• Long-VLA: Unleashing Long-Horizon Capability of Vision Language Action Model for Robot Manipulation
• PALM: Progress-Aware Policy Learning via Affordance Reasoning for Long-Horizon Robotic Manipulation
• When to Trust Imagination: Adaptive Action Execution for World Action Models
• AI Harness Engineering: A Runtime Substrate for Foundation-Model Software Agents
• Harness VLA: Steering Frozen VLAs into Reliable Manipulation Primitives via Memory-Guided Agents
• Harness Engineering for Physical AI: Robot Middleware Is the Harness Layer
• ScanBot: A Benchmark for Precision Robotic Surface Scanning with Industrial Laser Profilers
• RT-1: Robotics Transformer for Real-World Control at Scale
• RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation
• Octo: An Open-Source Generalist Robot Policy
• Inner Monologue: Embodied Reasoning through Planning with Language Models
• ReAct: Synergizing Reasoning and Acting in Language Models
• ReKep: Spatio-Temporal Reasoning of Relational Keypoint Constraints for Robotic Manipulation
• RoboClaw: An Agentic Framework for Scalable Long-Horizon Robotic Tasks

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