RoboLineage: Agent-Native Data Lifecycle Governance Across Robot Policy Iterations
Overview
This paper introduces RoboLineage, an open-source system designed to govern the data lifecycle for robot policy iterations. It addresses the fragmentation of evidence in modern robotics workflows by representing rollouts, reviews, dataset decisions, training runs, and evaluations as typed lineage artifacts. The system allows agents to interpret embodied rollout evidence, adapt accepted data to existing training stacks, maintain data health, and summarize cross-iteration state within explicit artifact boundaries. In real-robot manipulation contexts, RoboLineage aims to make routine policy iteration faster and more auditable while maintaining downstream policy performance. The project is released as a lightweight lifecycle layer compatible with various robot embodiments and training families.
Generated from attributed reports · Updated 1 hours ago
Event evidence and corrections
0 attributed source owners. Ownership does not establish independent confirmation. Quantities are reported separately and are never added together.
No current evidence-backed claims. Missing information remains not reported.
Report timeline
Follow attributed reports and material updates.
- arXiv Robotics — research abstractsSignalRoboLineage: Agent-Native Data Lifecycle Governance Across Robot Policy Iterations
This paper introduces RoboLineage, an open-source system designed to govern the data lifecycle for robot policy iterations. It addresses the fragmentation of evidence in modern robotics workflows by representing rollouts, reviews, dataset decisions, training runs, and evaluations as typed lineage artifacts. The system allows agents to interpret embodied rollout evidence, adapt accepted data to existing training stacks, maintain data health, and summarize cross-iteration state within explicit artifact boundaries. In real-robot manipulation contexts, RoboLineage aims to make routine policy iteration faster and more auditable while maintaining downstream policy performance. The project is released as a lightweight lifecycle layer compatible with various robot embodiments and training families.
Event coverage history
There is not enough continuous observation data to show a trend.
Timezone · UTC
Article dates follow your selected timezone. Briefing editions use Hong Kong time (UTC+8).