Accounting for Directional Rigidity and Constraints in Control for Manipulation of Deformable Objects without Physical Simulation

Abstract

Deformable objects like cloth and rope are challenging to manipulate because it is difficult to predict the state of the object given a motion of the gripper(s) holding it. In much previous work, physical models (such as Mass-Spring or Finite-Element) have been used to model such affects. However, these models often require significant parameter tuning for each scenario and can be expensive to simulate inside a control loop. Furthermore, it is difficult to create a practical controller for deformable object manipulation that preserves constraints, especially avoiding overstretching the object. In this paper, we developed a more effective controller than previous work by (1) constructing a more accurate geometric model of how the direction of gripper motion and obstacles affect deformable objects; and (2) specifying a novel stretching avoidance constraint to prevent the object from being overstretched by the robot. Experiments comparing our new method to the previous method in simulation and on a physical robot suggest that our new model captures the behavior of the object more accurately. We also find that our controller is able to prevent tearing that would occur when using the previous method.