Simulation-to-reality bridge for AI agents with environment adapters
Project description
agent-sim-bridge
Simulation-to-reality bridge for AI agents with environment adapters
Part of the AumOS open-source agent infrastructure portfolio.
Features
TransferBridgeapplies aCalibrationProfile(per-dimension linear scale + offset + noise model) to translate observations and actions between simulator coordinates and real-world distributionsCalibratorfits calibration profiles by regression on paired sim/real observation datasets, with support for iterative recalibration as new data arrivesDomainRandomizationperturbs simulation parameters (friction, mass, sensor noise, lighting) across configurable ranges to produce policies that transfer without fine-tuning- Simulation scenario recorder and replay engine lets you capture real-world trajectories, replay them in simulation, and measure the fidelity gap
SafetyMonitorenforces physical and policy constraints during both simulated and real execution, with configurable boundary definitions and emergency stop hooks- Sensor fusion module combines readings from multiple simulated or real sensors with configurable noise injection and covariance-weighted fusion
- Backend adapters for Gazebo and PyBullet expose a uniform
SimulationEnvironmentinterface so agents can be tested against either simulator without code changes
Quick Start
Install from PyPI:
pip install agent-sim-bridge
Verify the installation:
agent-sim-bridge version
Basic usage:
import agent_sim_bridge
# See examples/01_quickstart.py for a working example
Documentation
Enterprise Upgrade
For production deployments requiring SLA-backed support and advanced integrations, contact the maintainers or see the commercial extensions documentation.
Contributing
Contributions are welcome. Please read CONTRIBUTING.md before opening a pull request.
License
Apache 2.0 — see LICENSE for full terms.
Part of AumOS — open-source agent infrastructure.
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