AS-EKF: A Delay Aware State Estimation Technique for Telepresence Robot Navigation

State estimation in dynamical telepresence systems is 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 framework using 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.