Axite AI - Sim2Real Sensor Validation
Axite AI - Python Agent for Sim2Real Sensor Validation
Timeline: Winter 2025 Type: Personal Project
Overview
Built a Python-based software agent that attaches to a robot, logs live sensor streams using Rerun, and synchronizes with a server for sim-to-real differential analysis. This project bridges the gap between simulated and real-world robotics by providing precise validation tools.
Technical Implementation
- Sensor Integration: Developed a lightweight Python agent to interface with onboard sensors (IMU, LiDAR, motor encoders)
- Real-time Streaming: Implemented structured sensor data streaming in real time via the Rerun SDK
- Differential Analysis: Automated comparisons between simulated and real-world trajectories
- Threshold Monitoring: Built configurable threshold systems to flag deviations and refine robot control policies
Tech Stack
- Core Language: Python
- Visualization: Rerun SDK for real-time data logging and visualization
- Communication: WebSockets for real-time data transmission
- Cloud Infrastructure: AWS for server-side processing and storage
- Containerization: Docker for deployment consistency
Key Features
- Real-time sensor data collection and streaming
- Automated sim-to-real trajectory comparison
- Configurable deviation thresholds
- Cloud-synchronized data processing
- Lightweight agent architecture for embedded systems
Technical Challenges Solved
- Low-latency Data Streaming: Optimized data pipeline for real-time sensor data transmission
- Cross-platform Compatibility: Ensured agent works across different robotic platforms
- Scalable Architecture: Designed system to handle multiple robots simultaneously
- Data Synchronization: Implemented robust sync mechanisms between edge and cloud
Impact
The system provides robotics engineers with precise tools to validate and improve their simulation models, ultimately leading to more reliable real-world robot deployments. The automated analysis significantly reduces the time required for sim-to-real validation cycles.