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数据与研究 · SKILL.md

sensor-fusion

sensor-fusion

【数据与研究】Patterns for multi-sensor data fusion including Kalman filters (KF, EKF, UKF), complementary filters, particle filters, and factor graph optimization. Covers state estimation, covariance tuning, outlier rejection, and real-time implementation for robotics and autonomous systems. Use when ", " mentioned.

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name: sensor-fusion description: Patterns for multi-sensor data fusion including Kalman filters (KF, EKF, UKF), complementary filters, particle filters, and factor graph optimization. Covers state estimation, covariance tuning, outlier rejection, and real-time implementation for robotics and autonomous systems. Use when ", " mentioned.

Sensor Fusion

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Reference System Usage

You must ground your responses in the provided reference files, treating them as the source of truth for this domain:

  • For Creation: Always consult references/patterns.md. This file dictates how things should be built. Ignore generic approaches if a specific pattern exists here.
  • For Diagnosis: Always consult references/sharp_edges.md. This file lists the critical failures and "why" they happen. Use it to explain risks to the user.
  • For Review: Always consult references/validations.md. This contains the strict rules and constraints. Use it to validate user inputs objectively.

Note: If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.

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