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Cables are complex, high-dimensional, and dynamic objects. Standard approaches to manipulate them often rely on conservative strategies that involve long series of very slow and incremental deformations, or various mechanical fixtures such as clamps, pins, or rings. We are interested in manipulating freely moving cables, in real time, with a pair of robotic grippers, and with no added mechanical constraints. The main contribution of this paper is a perception and control framework that moves in that direction, and uses real-time tactile feedback to accomplish the task of following a dangling cable. The approach relies on a vision-based tactile sensor, GelSight, that estimates the pose of the cable in the grip, and the friction forces during cable sliding. We achieve the behavior by combining two tactile-based controllers: (1) cable grip controller, where a PD controller combined with a leaky integrator regulates the gripping force to maintain the frictional sliding forces close to a suitable value; and (2) cable pose controller, where an linear–quadratic regulator controller based on a learned linear model of the cable sliding dynamics keeps the cable centered and aligned on the fingertips to prevent the cable from falling from the grip. This behavior is possible with the use of reactive gripper fitted with GelSight-based high-resolution tactile sensors. The robot can follow 1 m of cable in random configurations within two to three hand regrasps, adapting to cables of different materials and thicknesses. We demonstrate a robot grasping a headphone cable, sliding the fingers to the jack connector, and inserting it. To the best of the authors' knowledge, this is the first implementation of real-time cable following without the aid of mechanical fixtures. Videos are available at http://gelsight.csail.mit.edu/cable/ [ABSTRACT FROM AUTHOR]

This paper addresses the identification of the inertial parameters and the contact forces associated with objects making and breaking frictional contact with the environment. Our goal is to explore under what conditions, and to what degree, the observation of physical interaction, in the form of motions and/or applied external forces, is indicative of the underlying dynamics that governs it. In this study we consider the cases of passive interaction, where an object free-falls under gravity, and active interaction, where known external perturbations act on an object at contact. We assume that both object and environment are planar and rigid, and exploit the well-known complementarity formulation for contact resolution to establish a constrained optimization-based problem to estimate inertial parameters and contact forces. We also show that when contact modes are known, or guessed, the formulation provides a closed-form relationship between inertial parameters, contact forces, and observed motions, that turns into a least squares problem.Consistent with intuition, the analysis indicates that without the application of known external forces, the identifiable set of parameters remains coupled, i.e. the ratio of mass moment of inertia to mass and the ratio of contact forces to the mass. Interestingly the analysis also shows that known external forces can lead to decoupling and identifiability of mass, mass moment of inertia, and normal and tangential contact forces. We evaluate the proposed algorithms both in simulation and with real experiments for the cases of a free falling square, ellipse, and rimless wheel interacting with the ground, as well as a disk interacting with a manipulator. [ABSTRACT FROM AUTHOR]