Hybrid Image-Based Motion Tracking and Adaptive Polynomial Kalman Filter for a Bio-Inspired Dual-Sheath Needle System
Issued Date
2024-01-01
Resource Type
ISSN
29943566
eISSN
29943574
Scopus ID
2-s2.0-105001502377
Journal Title
IEEE International Conference on Robotics and Biomimetics, ROBIO
Issue
2024
Start Page
104
End Page
110
Rights Holder(s)
SCOPUS
Bibliographic Citation
IEEE International Conference on Robotics and Biomimetics, ROBIO No.2024 (2024) , 104-110
Suggested Citation
Sivaraman D., Wiratkapun C., Pillai B.M., Suthakorn J., Methachan B., Nakdhamabhorn S., Ongwattanakul S. Hybrid Image-Based Motion Tracking and Adaptive Polynomial Kalman Filter for a Bio-Inspired Dual-Sheath Needle System. IEEE International Conference on Robotics and Biomimetics, ROBIO No.2024 (2024) , 104-110. 110. doi:10.1109/ROBIO64047.2024.10907698 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/109364
Title
Hybrid Image-Based Motion Tracking and Adaptive Polynomial Kalman Filter for a Bio-Inspired Dual-Sheath Needle System
Corresponding Author(s)
Other Contributor(s)
Abstract
This preliminary study investigated sensor-fusion methods for accurate motion estimation in a bio-inspired dual-sheath needle system designed for biopsy applications. The needle system draws inspiration from the segmented dual-sheath mechanism of ovipositors found in Hymenoptera species, which allows controlled and precise movement. The aim is to develop a reliable tracking system for both the needle tip and base, which is essential for accurate needle placement during biopsy procedures. A hybrid tracking approach was used to achieve this, combining image-based tracking of the needle tip with an Inertial Measurement Unit (IMU) sensor for needle-base tracking. An Adaptive Polynomial Kalman Filter (APKF) was applied to improve the motion estimation accuracy. Performance tests on a linear-rail system demonstrated the ability of the developed system to provide accurate and consistent motion estimates. The results suggest that this bio-inspired needle system using sensor fusion and advanced filtering holds promise for use in medical robotics, potentially improving the precision of biopsy procedures.