21 lines
1.4 KiB
Markdown
21 lines
1.4 KiB
Markdown
# FleetOpt Verifiable Privacy (Python)
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FleetOpt is a modular, open-source platform for privacy-preserving cross-fleet coordination of robotic workloads. This repository implements a production-ready MVP scaffold in Python, focusing on core data models, a contract-driven registry for aggregated signals, an asynchronous ADMM-like solver, offline delta synchronization, and secure governance/audit trails.
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What you get in this MVP:
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- Core data models: LocalRobotPlan, SharedSignals, PlanDelta, and PrivacyBudget.
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- In-memory registry (GraphOfContracts) to exchange aggregated signals with simple policy blocks.
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- A lightweight asynchronous ADMM-like solver coordinating two fleets with privacy budgets and dual variables.
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- Privacy budget accounting and audit logging.
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- Tiny ROS 2 adapter placeholder and TLS-configured transport scaffolding (ready to integrate with real ROS2 adapters).
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- Tests validating cross-fleet optimization flow and privacy budgeting.
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- Lightweight DSL seeds for LocalRobotPlan/SharedSignals/PlanDelta (core/dsl.py)
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- Toy adapters for interoperability (adapters/ros2_adapter.py and adapters/gazebo_adapter.py)
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How to run tests
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- Install dependencies (if any): this MVP uses only the standard library for tests, but you can install pytest if you wish to run externally.
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- Run tests: `pytest -q`.
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- Run packaging check: `python3 -m build`.
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Architecture overview and how to contribute are described in AGENTS.md.
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