학술논문

Accounting for Directional Rigidity and Constraints in Control for Manipulation of Deformable Objects without Physical Simulation
Document Type
Conference
Source
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Intelligent Robots and Systems (IROS), 2018 IEEE/RSJ International Conference on. :512-519 Oct, 2018
Subject
General Topics for Engineers
Robotics and Control Systems
Grippers
Deformable models
Computational modeling
Robots
Predictive models
Finite element analysis
Adaptation models
Language
ISSN
2153-0866
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.