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This paper develops a novel slip estimator using the invariant observerdesign theory and Disturbance Observer (DOB). The proposed state estimator formobile robots is fully proprioceptive and combines data from an inertialmeasurement unit and body velocity within a Right Invariant Extended KalmanFilter (RI-EKF). By embedding the slip velocity into $\mathrm{SE}_3(3)$ matrixLie group, the developed DOB-based RI-EKF provides real-time velocity and slipvelocity estimates on different terrains. Experimental results using a Huskywheeled robot confirm the mathematical derivations and effectiveness of theproposed method in estimating the observable state variables. Open-sourcesoftware is available for download and reproducing the presented results.

Fully Proprioceptive Slip-Velocity-Aware State Estimation for Mobile Robots via Invariant Kalman Filtering and Disturbance Observer