Today I read a paper titled “Invariant EKF Design for Scan Matching-aided Localization”
The abstract is:
Localization in indoor environments is a technique which estimates the robot’s pose by fusing data from onboard motion sensors with readings of the environment, in our case obtained by scan matching point clouds captured by a low-cost Kinect depth camera.
We develop both an Invariant Extended Kalman Filter (IEKF)-based and a Multiplicative Extended Kalman Filter (MEKF)-based solution to this problem.
The two designs are successfully validated in experiments and demonstrate the advantage of the IEKF design.