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 the assembly tasks. This paper discusses a method for identification of contact conditions from the information of force sensor equipped with the robot hand. This paper treats the practical case where sensing data are contaminated with noise. We propose an efficient and analytical algorithm for identifying contact conditions by using an active force sensing method. The algorithm can identify not only contact position and contact force, but also contact type such as soft finger contact type, line contact type, and plane contact type. These contact types are characterized by a standard deviation of contact moments. The contact position is estimated by a least-squares method. The contact moment is then estimated from noisy observations and its eigenvalues are analyzed. The contact type can be judged by the eigenvalues of estimated contact moment. The effectiveness of the algorithm is demonstrated by simulations