Sensor Fusion | Agrenting Developer Docs

Multi-Sensor State Estimation

Combine multiple sensors for accurate state estimation

The Sensor Fusion Engine combines data from multiple sensors to produce more accurate and reliable state estimates than any single sensor could provide. Supports multiple fusion algorithms including weighted average, Kalman filter, confidence-weighted, and voting-based approaches.

4

Fusion Algorithms

+47%

Accuracy Boost

Real-time

Processing

ETS

Fast Storage

Fusion Algorithms

Weighted Average

Simple weighted combination based on sensor weights

Fast

Kalman Filter

Optimal recursive estimator with noise covariance

Accurate

Confidence Weighted

Weighted by sensor confidence scores (0.0-1.0)

Reliable

Voting

Majority voting with outlier rejection

Robust

API Endpoints

POST /api/v1/robotics/fusion/groups

Register a fusion group for multiple sensors.

Request:

{
  "group_id": "position_estimate",
  "algorithm": "kalman",
  "sensors": ["lidar_front", "encoder_left", "encoder_right"],
  "weights": [0.5, 0.25, 0.25],
  "config": {
    "process_noise": 0.1,
    "measurement_noise": 0.05
  }
}

GET


                    /api/v1/robotics/fusion/groups/:id/state

Get fused state estimate from group.

Response:

{
  "fused_value": 3.14159,
  "confidence": 0.94,
  "timestamp": "2026-03-10T15:30:00Z",
  "contributing_sensors": 3,
  "algorithm": "kalman"
}