PROJECT TITLE :

Invariant EKF Design for Scan Matching-Aided Localization

ABSTRACT:

Localization in indoor environments could be a technique that estimates the robot's cause by fusing information from onboard motion sensors with readings of the environment, in our case obtained by scan matching point clouds captured by an occasional-value Kinect depth camera. We develop each an invariant extended Kalman filter (IEKF)-based and a multiplicative extended Kalman filter-primarily based resolution to the current problem. The 2 styles are successfully validated in experiments and demonstrate the advantage of the IEKF style.


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