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Implementation of extended kalman filter for localization of ambulance robot

Chan-Yun Yang, Hooman Samani, ZIRONG TANG, Chunxu Li Orcid Logo

International Journal of Intelligent Robotics and Applications

Swansea University Authors: ZIRONG TANG, Chunxu Li Orcid Logo

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DOI (Published version): 10.1007/s41315-024-00352-z

Abstract

This paper focuses on the implementation of the Extended Kalman Filter for indoor localization of a semi-autonomous Ambulance Robot system named Ambubot. The system is designed to reduce the response time for lay rescuers to locate an Automated External Defibrillator (AED) during sudden cardiac arre...

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Published in: International Journal of Intelligent Robotics and Applications
ISSN: 2366-5971 2366-598X
Published: Springer Science and Business Media LLC 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa67360
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Abstract: This paper focuses on the implementation of the Extended Kalman Filter for indoor localization of a semi-autonomous Ambulance Robot system named Ambubot. The system is designed to reduce the response time for lay rescuers to locate an Automated External Defibrillator (AED) during sudden cardiac arrest events. To achieve this objective, the robot is equipped with an AED, and the Extended Kalman Filter is utilized for optimal indoor localization. The filter is implemented using data from the robot’s Inertial Measurement Unit, which comprises 9 Degrees of Freedom. The paper provides an explicit description of the performance of the Extended Kalman Filter in estimating the position of Ambubot, and demonstrates that the proposed approach is effective in accurately determining and estimating the robot’s position in unknown indoor environments. The results suggest that the proposed method is a promising solution for improving survival rates in cardiac arrest cases, and may have potential applications in other fields where accurate indoor localization is required.
Keywords: Extended kalman filter; Localization; Intelligent system; Autonomous robot
College: Faculty of Science and Engineering
Funders: Swansea University

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