Dynamic order selection analysis in adaptive polynomial Kalman filtering: implementation and integration of sensor data and hybrid image processing for bio-inspired needle systems

Dynamic order selection analysis in adaptive polynomial Kalman filtering: implementation and integration of sensor data and hybrid image processing for bio-inspired needle systems

This study investigates dynamic-order selection in Adaptive Polynomial Kalman Filtering (APKF) for tracking the bioinspired dual-sheath needle systems used in biopsy procedures. Emphasizing integration of sensor data and hybrid image processing, the goal is to achieve precise motion estimation, whic...

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Bibliographic Details
Main Authors: Dileep Sivaraman, Branesh M. Pillai, Cholatip Wiratkapun, Jackrit Suthakorn, Songpol Ongwattanakul
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Systems Science & Control Engineering
Subjects:
Adaptive polynomial Kalman filter
bioinspired needle
dual-sheath mechanism
robotic biopsy
Online Access:https://www.tandfonline.com/doi/10.1080/21642583.2025.2546839
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