Estimating an Articulated Tool's Kinematics Via Visuo-Tactile Based Robotic Interactive Manipulation

The usage of articulated tools for autonomous robots is still a challenging task. One of the difficulties is to automatically estimate the tool's kinematics model. This model cannot be obtained from a single passive observation, because some information, such as a rotation axis (hinge), can only be detected when the tool is being used. Inspired by a baby using its hands while playing with an articulated toy, we employ a dual arm robotic setup and propose an interactive manipulation strategy based on visual-tactile servoing to estimate the tool's kinematics model. In our proposed method, one hand is holding the tool's handle stably, and the other arm equipped with tactile finger flips the movable part of the articulated tool. An innovative visuo-tactile servoing controller is introduced to implement the flipping task by integrating the vision and tactile feedback in a compact control loop. In order to deal with the temporary invisibility of the movable part in camera, a data fusion method which integrates the visual measurement of the movable part and the fingertip's motion trajectory is used to optimally estimate the orientation of the tool's movable part. The important tool's kinematic parameters are estimated by geometric calculations while the movable part is flipped by the finger. We evaluate our method by flipping a pivoting cleaning head (flap) of a wiper and estimating the wiper's kinematic parameters. We demonstrate that the flap of the wiper is flipped robustly, even the flap is shortly invisible. The orientation of the flap is tracked well compared to the ground truth data. The kinematic parameters of the wiper are estimated correctly.