This paper describes a strategy to lift up a deformable 2D object resting on a horizontal plane. Inspired by human hand lifting behavior, the strategy plans grasping trajectories of two fingertips using modified Rapidly-exploring Random Trees (RRT). Compared to a straight squeeze, a planned finger movement not only enlarges the graspable region, but also minimizes the work. Improvements on control complexity and robustness are made through modifications to RRT. The introduced strategy is applicable to both hollow and solid 2D objects, and is extendable to 3D ones.

This paper describes a simple strategy for a robot hand to grasp and lift a deformable 3D object resting on a table. Inspired by the human hand grasping, the strategy employs two rigid hemispherical fingers to first squeeze the object until a secure grip is achieved under contact friction, and then translate vertically upward. During the squeeze, a lift test is repeatedly conducted to determine if the maximum hypothetical liftable weight of the object reaches its real weight. Actual lifting follows when the test is passed. The object's deformation and configuration of contact with the fingers and the plane are tracked using the finite element method (FEM) in an event-driven manner, based on varying contact displacements induced by the finger movements. The gravitational force acting on the object is accounted for. Slips inside the contact regions are determined from solving quadratic systems. Experiment has been conducted to demonstrate the efficiency and accuracy for this sensorless grasping approach.

Robotic grasping of a deformable object is difficult not simply due to the high computational cost of deformable modeling. More fundamentally, the difficulty lies in a wrench space that changes under deformation, with growing contact areas, and subject to varying slip/stick modes in these areas. This paper presents a grasping strategy by squeezing the object with two fingers. An analysis based on the finite element method (FEM) proves equilibrium and uniqueness of deformation during the action, and leads to a (improved) quadratic time deformation update from the displacements of as few as two contact nodes. An event-driven algorithm is then presented to track the contact regions during a squeeze, and determine the stick/slip mode of every node in contact. The contacts supply the constraints needed for deformation update using FEM. Several experiments with a Barrett Hand have been conducted for validation.

This paper gives an in-depth analysis of two-finger squeeze grasping of deformable objects introduced in our previous work [6] with a focus on two special classes: stable squeezes, which minimize the potential energy of the system among squeezes of the same magnitude, and pure squeezes, which eliminate all possible Euclidean motions from the resulting deformations. Next, the paper characterizes the best resistance by a grasp to an adversary finger under known translation, as the one that minimizes the work done by the grasping fingers. An optimization scheme is offered to deal with the general case of frictional segment contact. Simulation and experimental results are presented.

Grasping a deformable object instantaneously requires maintaining equilibrium of its pre- and post-deformed shapes using the same set of forces. This paper studies the type of grasps generated by squeezing a planar object with two fingers. It is shown that the success of such a grasp is independent of the applied forces in the case of small deformation. Numerical algorithms are introduced to compute sets of squeeze grasps with small and large deformations modeled using the finite element method (FEM) based on the linear and nonlinear elasticity theories, respectively.