Implementation of extended kalman filter for localization of ambulance robot

• Published in: International journal of intelligent robotics and applications Online 2024-12, Vol.8 (4), p.960-973
• Main Authors: Yang, Chan-Yun, Samani, Hooman, Tang, Zirong, Li, Chunxu
• Format: Article
• Language: English
• Subjects: Algorithms; Ambulances; Artificial Intelligence; Cardiac arrest; Computer Science; Control; Electronics and Microelectronics; Extended Kalman filter; Global positioning systems; GPS; Indoor environments; Inertial coordinates; Inertial platforms; Instrumentation; Localization; Machines; Manufacturing; Mechatronics; Patients; Position measurement; Processes; Regular Paper; Robotics; Robots; Sensors; User Interfaces and Human Computer Interaction
• ISSN: 2366-5971; 2366-598X
• DOI: 10.1007/s41315-024-00352-z

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.