SkillsLib.ai

IMU Sensor Fusion Validator

Validate IMU sensor fusion and debug navigation anomalies

0.0(0 reviews)
100+ downloads
Updated Nov 2026

What You Can Do

You can validate IMU sensor fusion algorithms, interpret calibration data, and diagnose navigation errors through structured diagnostic workflows. The skill guides you through systematic checks of sensor offsets, quaternion calculations, gimbal lock conditions, and axis alignment issues. It produces actionable calibration coefficients, tuning parameters, and root-cause analysis of drift and orientation errors.

Features

Sensor calibration validation

Analyzes offset, scale, and bias coefficients against sensor specifications and cross-axis coupling

Quaternion & Euler angle verification

Validates orientation calculations, detects discontinuities, and checks for numerical stability

Gimbal lock detection

Identifies singularities in rotation sequences and recommends sequence alternatives

Axis alignment diagnosis

Detects orthogonality errors, misalignment with body frame, and sensor mounting issues

Drift analysis workflow

Quantifies accumulated error over time, correlates with temperature and motion patterns

Data quality assessment

Validates sensor readings against manufacturer specs and identifies outliers or timing anomalies

Filter tuning guidance

Generates Kalman filter covariance matrices or complementary filter parameters based on sensor characteristics

Cross-axis correlation analysis

Detects sensor coupling, interference patterns, and magnetic field contamination

Example Output

Sensor Calibration Report

AxisOffset (raw counts)Scale FactorBias DriftStatus
X-12.40.998+0.8 mG/°C✓ OK
Y8.71.002-0.3 mG/°C✓ OK
Z31.20.995+1.2 mG/°C⚠ Monitor

Orientation Error Diagnosis

code
Detected gimbal lock condition at roll=90°
Recommendation: Switch to quaternion representation (no singularity)
Current quaternion norm: 0.9998 ✓ (should be ≈1.0)
Euler angle discontinuity: None detected

Drift Correction Parameters
Complementary filter: α=0.01 (gyro weight), rate=100Hz
Gyro drift: -0.12°/min (acceptable for navigation-grade IMU)

What's Included

  • SKILL.md: Complete IMU validation workflow with decision trees, calibration procedures, and error diagnostics
  • Sensor specification templates: Reference checklists for common IMU datasheets (MPU-6050, BMI160, ICM-20689)
  • Calibration verification checklist: Step-by-step validation of offset, scale, and cross-axis coupling
  • Orientation calculation tester: Tools to verify quaternion/Euler conversions and singularity handling
  • Filter tuning worksheet: Parameters for Kalman and complementary filters based on sensor grade
  • Diagnostic report template: Structured format for calibration coefficients, error budgets, and recommendations

Who It's For

  • Roboticists — Debug SLAM and IMU-fused navigation systems
  • Embedded systems engineers — Validate sensor drivers and fusion firmware
  • Drone developers — Tune flight controller fusion for stable attitude estimation
  • AR/VR engineers — Diagnose head tracking and orientation jitter
  • Automotive engineers — Validate motion estimation for ADAS algorithms

Best For

  • Calibrating and validating new IMU sensors before deployment
  • Troubleshooting navigation drift and orientation errors in production systems
  • Tuning sensor fusion filter parameters (Kalman, complementary filter)
  • Diagnosing gimbal lock, axis misalignment, and sensor coupling issues
  • Creating error budgets and specifications for motion estimation pipelines

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