Sensor Fusion for Motion Estimation of Mobile Robots with Compensation for Out-of-Sequence Measurements

Research output: Contribution to conferencePaper, not in proceeding


The position and orientation estimation problem for mobile robots is approached by fusing measurements from inertial sensors, wheel encoders, and a camera. The sensor fusion approach is based on the standard extended Kalman filter, which is modified to handle measurements from the camera with unknown prior delay. A real-time implementation is done on a four-wheeled omni-directional mobile robot, using a dynamic model with 11 states. The algorithm is analyzed and validated with simulations and experiments.


Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Control Engineering


  • mobile robotics, estimation, localization, Extended Kalman filter, out-of-sequence, sensor fusion
Original languageEnglish
Publication statusPublished - 2011
Publication categoryResearch
Event2011 11th International Conference on Control, Automation and Systems - Seoul, Korea
Duration: 2011 Oct 26 → …


Conference2011 11th International Conference on Control, Automation and Systems
Period2011/10/26 → …

Bibliographic note

month=October key=bern_etal2011ccas

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