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.
REF In their work, the robotic gripper followed the trajectory that optimized from offline simulation to fold the garment in order to prevent it from sliding.
Folding deformable objects using predictive simulation and trajectory optimization
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Engineering Computer Science