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

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.


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)