Random execution of a set of contacts to solve the grasping and contact uncertainties in robotic tasks

This paper addresses the problem of identifying the uncertainties present i n a robotic contact situation. These uncertainties are errors and misalignm ents of an object with respect to its ideal position. The paper describes h ow to solve for the errors caused during grasping and errors present when c oming into contact with the environment. A force sensor is used together wi th Kalman Filters to solve for all the uncertainties. The straightforward u se of a force sensor and the Kalman Filters is found to be effective in fin ding only some of the uncertainties in robotic contact. The other uncertain ties form dependencies that cannot be estimated in this manner. This depend ency brings about the problem of observability. To make the unobservable un certainties observable a sequence of contacts are used. The error covarianc e matrix of the Kalman Filter (KF) is used to obtain new contacts that are required to solve for all the uncertainties completely. There is complete f reedom in choosing which unobservable quantity to be excited in forming the next contact. The paper describes how these new contacts can be randomly e xecuted. A two dimensional contact situation will be used to demonstrate th e effectiveness of the method. Experimental data are also presented to prov e the validity of the procedure. Due to the non-linear relationship between the uncertainties and the forces, an Extended Kalman Filter (EKF) has been used.