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With the recent advance of deep learning based object recognition andestimation, it is possible to consider object level SLAM where the pose of eachobject is estimated in the SLAM process. In this paper, based on a novel Liegroup structure, a right invariant extended Kalman filter (RI-EKF) for objectbased SLAM is proposed. The observability analysis shows that the proposedalgorithm automatically maintains the correct unobservable subspace, whilestandard EKF (Std-EKF) based SLAM algorithm does not. This results in a betterconsistency for the proposed algorithm comparing to Std-EKF. Finally,simulations and real world experiments validate not only the consistency andaccuracy of the proposed algorithm, but also the practicability of the proposedRI-EKF for object based SLAM problem. The MATLAB code of the algorithm is madepublicly available.

A Right Invariant Extended Kalman Filter for Object based SLAM