Hybrid Kalman filter for improvement of camera-based position sensor

Edouard Laroche, Shingo Kagami, Loïc Cuvillon

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

When using a camera as a position sensor, the measurement is limited in bandwidth, mainly due to the blur effects. The knowledge of an accurate model of the camera is then necessary to reconstruct the trajectory from the measurements given by the camera. This paper deals with the reconstruction of the continuous-time trajectory from the discrete-time measurements provided by the camera and shows the improvement obtained by using an accurate camera model. In the proposed methodology, a Kalman filter is used for the data fusion between the model and the measurement. The tuning and implementation of the filter are discussed in the specific context of the camera measurement. The system is evaluated in the context of a biomedical application: the reconstruction of the movement of a beating-heart.

本文言語English
ホスト出版物のタイトル2011 IEEE International Conference on Robotics and Automation, ICRA 2011
ページ4405-4410
ページ数6
DOI
出版ステータスPublished - 2011 12 1
イベント2011 IEEE International Conference on Robotics and Automation, ICRA 2011 - Shanghai, China
継続期間: 2011 5 92011 5 13

Other

Other2011 IEEE International Conference on Robotics and Automation, ICRA 2011
CountryChina
CityShanghai
Period11/5/911/5/13

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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