Updated: Sep 19, 2015


Folding Deformable Objects using Predictive Simulation and Trajectory Optimization  

Yinxiao Li, Yonghao Yue, Danfei Xu, Eitan Grinspun, Peter K. Allen
Columbia University
Abstract:

Robotic manipulation of deformable objects remains a challenging task. One such task is folding a garment autonomously. Given start and end folding positions, what is an optimal trajectory to move the robotic arm to fold a garment? Certain trajectories will cause the garment to move, creating wrinkles, and gaps, other trajectories will fail altogether. We present a novel solution to find an optimal trajectory that avoids such problematic scenarios. The trajectory is optimized by minimizing a quadratic objective function in an off-line simulator, which includes material properties of the garment and frictional force on the table. The function measures the dissimilarity between a user folded shape and the folded garment in simulation, which is then used as an error measurement to create an optimal trajectory. We demonstrate that our two-arm robot can follow the optimized trajectories, achieving accurate and efficient manipulations of deformable objects.

Keywords:

Robotics, garment, folding trajectory, optimization, predictive simulation


To appear in the Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Hamburg, Germany. Sep 2015.

Paper: PDF(4.2MB)
Video: VIDEO(YouTube)