Traceable World State: A Provenance-Aware State Representation and Deterministic Replay Framework for Robotic Systems

Key points

• Robotic systems operating over extended tasks must maintain a world state assembled from observations arriving at different times, with varying confidence and potential revisions.1
• Validated update operations transform snapshots immutably, ordered updates support deterministic replay, and a canonical SHA-256 hash chain ensures tamper-evident logs.1
• We evaluate TWS through schema conformance, complete state lifecycles, deterministic replay, and fault injection.1
• Passing 38 tests across Python 3.10-3.14, the framework detects record corruptions, broken hash links, sequence discontinuities, and world mismatches.1

Sources (1)

• [1]Traceable World State: A Provenance-Aware State Representation and Deterministic Replay Framework for Robotic Systems
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 8, 02:26 PM

  We present Traceable World State (TWS), a middleware-neutral semantic representation and reference runtime for provenance-aware robot world state.

  Robotic systems operating over extended tasks must maintain a world state assembled from observations arriving at different times, with varying confidence and potential revisions.

Extractive summary: sentences quoted from the sources.