earticle

논문검색

A Study of State Estimation Algorithms in an OktoKopter

초록

영어

The prospective applications of unmanned aerial vehicle (UAV) have marked its significance in various military and non-military applications. On-board sensor accuracy and state estimation algorithms are important issues related with the performance aspects. Our study is focused on OktoKopter, which is one of the successful universal aerial platforms. The multi-rotor aircraft is equipped with global positioning system (GPS), compass, altitude control and telemetry, etc., thus the features make it powerful and extremely versatile. In this paper, we first present a sensor fusion model, and then proceed with comparison of three state estimation algorithms, namely Kalman, extended Kalman filter (EKF) and unscented Kalman filter(UKF).The performance of UKF is found to be the best; the result being tallied with theoretical notion of the algorithm with practical experimented data.

목차

Abstract
 1. Introduction
 2. Materials and Methods
  2.1. OktoKopter
  2.2. Basic Terms and Technical Specifications
  2.3. Flight Control Mechanism
 3. Sensor Fusion Model
 4. State Estimation and Filter Algorithms
  4.1. Kalman Filter
  4.2. Extended Kalman Filter
  4.3. Unscented Kalman Filter
 5. Results and Discussions
 6. Conclusion
 References

저자정보

  • S. A. Quadri Collaborative Microelectronic Design Excellence Centre (CEDEC) Universiti Sains Malaysia, Engineering Campus, Nibong Tebal Malaysia, 14300
  • Othman Sidek Collaborative Microelectronic Design Excellence Centre (CEDEC) Universiti Sains Malaysia, Engineering Campus, Nibong Tebal Malaysia, 14300
  • Azizul bin Abdullah Collaborative Microelectronic Design Excellence Centre (CEDEC) Universiti Sains Malaysia, Engineering Campus, Nibong Tebal Malaysia, 14300

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.