Estimating contact and grasping uncertainties using Kalman filters in force controlled assembly

This paper presents a general approach for the identification of contact and grasping uncertainties, and the monitoring of contact situation changes in force controlled assembly operations. The identification problem is solved using virtual contact manipulators and Kalman filter techniques. Monitoring is solved by carrying out a statistical test on the sum of normalized and squared innovations of the Kalman filter, within a moving window, identification and monitoring are verified by experimental results. The paper explains how the error covariance matrix of the Kalman filter is interpreted to analyse the observability of the Kalman filter´s states. Preliminary simulation results are presented for an ad hoc active sensing strategy to achieve complete state observability