# Sensor Fusion Pipeline

> Multi-sensor fusion. EKF/UKF state estimation, camera-LiDAR-IMU calibration, point cloud registration.

- Skill: `aselimc/sensor-fusion-pipeline` (Agent Skill)
- Install (CLI): `npx skillmds@latest add aselimc/sensor-fusion-pipeline`
- Raw SKILL.md: https://api.skillmd.com/api/skills/aselimc/sensor-fusion-pipeline/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- Author: aselimc (https://skillmd.com/u/aselimc)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/aselimc/sensor-fusion-pipeline

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# Sensor Fusion Pipeline

## EKF State Estimation (robot_localization)
```yaml
# ekf.yaml
frequency: 50.0
odom0: /wheel_odom
odom0_config: [true, true, false, false, false, true, ...]
imu0: /imu/data
imu0_config: [false, false, false, true, true, true, ...]
```

## Calibration
- **Camera-LiDAR**: extrinsic calibration with checkerboard or targetless methods
- **Camera-IMU**: use kalibr for spatiotemporal calibration
- **Hand-eye**: AX=XB solvers (OpenCV, easy_handeye)

## Point Cloud Registration
```python
import open3d as o3d
result = o3d.pipelines.registration.registration_icp(
    source, target, max_distance=0.05,
    estimation_method=o3d.pipelines.registration.TransformationEstimationPointToPlane())
```

## Key Libraries
robot_localization, Open3D, kalibr, kiss-icp