Folding deformable objects using predictive simulation and trajectory optimization

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.

Authors

• Yinxiao Li
• Yonghao Yue
• Danfei Xu
• Eitan Grinspun
• Peter K. Allen

Keywords

• Clothing
• Robots
• Shape
• Deformable models
• Trajectory optimization
• Resistance
• Predictive Simulations
• Deformable Objects
• Material Properties
• Friction Force
• Robotic Arm
• Adaptive Algorithm
• Simulation Environment
• Line Segment
• Feature Points
• End-effector
• Adjacent Segments
• Physical Simulation
• Target Shape
• Shear Resistance
• Multiple Arms
• Chord Length
• Bezier Curve
• Folding Step