Record STMT-WDA45A0Voluntary

Verification-Gated Agentic Mission-State Governance for Intelligent Industrial Multi-Robot Systems

White paper Institutional policyGlobaladopted

This research paper introduces a verification-gated agentic mission-state governance framework for intelligent industrial multi-robot systems. The framework maintains an evolving task forest and a governed blackboard as synchronized state objects to separate autonomous proposal generation from verified execution commitments. It uses a derived execution coupling topology to evaluate cross-branch dependencies and enforce bounded repairs during disturbances. Evaluation across factory scenarios and stress benchmarks shows improved safe completion and reduced invalid commitments or lock conflicts compared to unchecked baselines.

Summary and content fields are drawn from the document text and are pending editorial review.

Who issued it

Beijing University of Posts and TelecommunicationsAcademic · CN

Lead issuer

arXivAcademic

Publisher

Legal forceVoluntary

Under whose authorityInstitutional policy

Judged fromfull text

Who it governs

Researchers and academicsCompaniesAI developers and providersAI deployers and users

Researchers and developers of multi-robot industrial systems who need to govern agentic AI task allocation and execution safely.

Sectors

Manufacturing and industry · industrial multi-robot systemsResearch and science · intelligent industrial systems research

What the document contains

What's covered

The document addresses the architectural design and evaluation of a verification-gated mission-state governance framework for multi-robot industrial systems. It covers canonical state representations using a task forest and governed blackboard, the derivation of an execution coupling topology, deterministic verification predicates, and local bounded repair strategies.

What's missing

The framework does not model actuator faults, localization drift, perception false positives, continuous physical collision avoidance, or hardware-in-the-loop deployments.

Key takeaways

Autonomous proposal generation in multi-robot systems requires a deterministic mission-state governance layer rather than unchecked execution authority.
Separating persistent task hierarchy in an evolving task forest from online records in a governed blackboard prevents state inconsistency during long-horizon execution.
An execution coupling topology derived from state snapshots exposes cross-branch dependencies for proposal verification, parallel commits, and bounded repair.
Candidate assignments, repairs, and constraint updates are committed only after passing deterministic verification checks for dependencies, capabilities, energy, resources, and safety boundaries.
Industrial factory and remote-construction stress benchmarks demonstrate that verification-gated governance reduces invalid commitments, lock conflicts, and disruptive repairs.

Outline

· 1. Introduction
· 2. Related Work
  - 2.1. Task-Structured Long-Horizon Multi-Robot Execution
  - 2.2. LLM-Assisted Multi-Robot Planning and Verifiable Proposals
  - 2.3. Feedback, Contingency Handling, and Local Repair
  - 2.4. Runtime Governance and Reconfiguration of Large Autonomous Systems
· 3. Proposed Framework
  - 3.1. Problem Setup and Mission-State Governance
  - 3.2. Canonical Mission State: Task Forest and Governed Blackboard
  - 3.3. Derived Execution Coupling Topology
  - 3.4. Verification-Gated Commit and Bounded Repair
· 4. Experimental Evaluation
  - 4.1. Experimental Setup
  - 4.2. Primary Industrial Factory Validation
  - 4.3. Remote-Construction Stress Comparison
  - 4.4. Ablation, Repair, and Runtime Diagnostics
· 5. Discussion
· 6. Conclusion
· Appendix A. Formal State and Verifier Details

Issued30 June 2026

Length7,884 words · 14 pages

FormatNot recorded

Scopeglobal

How it scores

Pending review

Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.

Fairness

0/5

Non-discrimination and equitable treatment

screening score · 2026-10-23

Human Dignity

0/5

Respect for the inherent worth of persons

screening score · 2026-10-23

Human Oversight

4/5

Humans remain in control of consequential decisions

The study positions agentic AI as a proposal-generating layer governed by inspectable mission-state verification rather than as an unchecked execution authority.

Abstract

screening score · 2026-10-23

Privacy

0/5

Protection of personal data and private life

screening score · 2026-10-23

Transparency

3/5

Openness about how AI systems work and are used

From each forest–blackboard snapshot, a derived execution coupling topology exposes cross-branch dependencies for proposal verification, parallel-commit eligibility, and bounded repair.

Abstract

screening score · 2026-10-23

Topics

Physical AI Governancecontext

agentic_ai multi_robot_systems mission_state_governance industrial_automation verification_gated_repair