3 research outputs found

    Quasi-static Soft Fixture Analysis of Rigid and Deformable Objects

    Full text link
    We present a sampling-based approach to reasoning about the caging-based manipulation of rigid and a simplified class of deformable 3D objects subject to energy constraints. Towards this end, we propose the notion of soft fixtures extending earlier work on energy-bounded caging to include a broader set of energy function constraints and settings, such as gravitational and elastic potential energy of 3D deformable objects. Previous methods focused on establishing provably correct algorithms to compute lower bounds or analytically exact estimates of escape energy for a very restricted class of known objects with low-dimensional C-spaces, such as planar polygons. We instead propose a practical sampling-based approach that is applicable in higher-dimensional C-spaces but only produces a sequence of upper-bound estimates that, however, appear to converge rapidly to actual escape energy. We present 8 simulation experiments demonstrating the applicability of our approach to various complex quasi-static manipulation scenarios. Quantitative results indicate the effectiveness of our approach in providing upper-bound estimates for escape energy in quasi-static manipulation scenarios. Two real-world experiments also show that the computed normalized escape energy estimates appear to correlate strongly with the probability of escape of an object under randomized pose perturbation.Comment: Paper submitted to ICRA 202

    Whole-Hand Robotic Manipulation with Rolling, Sliding, and Caging

    Get PDF
    Traditional manipulation planning and modeling relies on strong assumptions about contact. Specifically, it is common to assume that contacts are fixed and do not slide. This assumption ensures that objects are stably grasped during every step of the manipulation, to avoid ejection. However, this assumption limits achievable manipulation to the feasible motion of the closed-loop kinematic chains formed by the object and fingers. To improve manipulation capability, it has been shown that relaxing contact constraints and allowing sliding can enhance dexterity. But in order to safely manipulate with shifting contacts, other safeguards must be used to protect against ejection. “Caging manipulation,” in which the object is geometrically trapped by the fingers, can be employed to guarantee that an object never leaves the hand, regardless of constantly changing contact conditions. Mechanical compliance and underactuated joint coupling, or carefully chosen design parameters, can be used to passively create a caging grasp – protecting against accidental ejection – while simultaneously manipulating with all parts of the hand. And with passive ejection avoidance, hand control schemes can be made very simple, while still accomplishing manipulation. In place of complex control, better design can be used to improve manipulation capability—by making smart choices about parameters such as phalanx length, joint stiffness, joint coupling schemes, finger frictional properties, and actuator mode of operation. I will present an approach for modeling fully actuated and underactuated whole-hand-manipulation with shifting contacts, show results demonstrating the relationship between design parameters and manipulation metrics, and show how this can produce highly dexterous manipulators
    corecore