AS-EKF: a delay aware state estimation technique for telepresence robot navigation

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State estimation in dynamical telepresence systemsis very important in real-world applications as the true state of the robot is unspecified and sensors provide only a sequence of noisy measurements. In this research, we proposed a new technique of state estimation using delayed sensor measurements of a Telepresence robot for real-time navigation. An Augmented State Extended Kalman Filter (AS-EKF) is introduced to estimate the true position of the robot. The proposed algorithm was successfully tested in a real-environment experimental frameworkusing a state-of-the-art differential-drive telepresence robot. Our results show improvements of an average of more than 34% when compared to traditional EKF.
Original languageEnglish
Title of host publicationProceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019
Place of PublicationPiscataway, NJ
Number of pages6
ISBN (Electronic)9781538692455
ISBN (Print)9781538692455
Publication statusPublished - 26 Mar 2019
EventThe Third IEEE International Conference on Robotic Computing - Naples, Italy
Duration: 25 Feb 201927 Feb 2019


ConferenceThe Third IEEE International Conference on Robotic Computing
Abbreviated titleIRC 2019


  • state estimation
  • EKF
  • augmented state
  • telepresence
  • robot navigation
  • time delay

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