Identification of Contact Conditions from Contaminated Data of Contact Moment

When a grasped object is in contact with external environment, it is required to identify contact conditions prior to performing assembly tasks. This paper discusses a method for identification of contact conditions by using an active force sensing method. This paper treats the practical case where sensing data are contaminated with noise. Contact types are characterized by a standard deviation of contact moments. The contact position is estimated by a least-squares method. The contact type can be judged by comparing the eigenvalues of a covariance matrix of estimated contact moment. We establish an efficient and analytical algorithm for identification of contact conditions. The algorithm can identify not only contact position and contact force, but also contact type.