Published January 1, 2025 | Version v1
Conference paper Open

An Adaptive Kalman Fusion Technique for Reference Tracking Under Shot Noise

  • 1. Hacettepe Univ, Dept Elect & Elect Engn, TR-06800 Ankara, Turkiye

Description

Sensor fusion enhances robotic perception by integrating data from multiple sensing modalities. This paper introduces a biologically inspired, closed-loop sensor fusion framework combining camera and LiDAR data to robustly estimate the position of a moving object. To mitigate non-Gaussian disturbances such as shot noise, the approach employs dynamic weighting strategies integrated with the Maximum Correntropy Criterion Kalman Filter (MCC-KF). The proposed method is validated experimentally using a custom-built platform, demonstrating enhanced robustness and accuracy under diverse and challenging noise conditions.

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