Robotic ironing with a humanoid robot using human tools

There is an increasing demand of robots able to assist people in everyday home tasks. Some of these tasks, specially garment-related tasks (e.g. laundry, ironing, etc), are currently a big challenge for robots due to deformations and the high number of possible configurations the garment can adopt. Ironing, additionally, requires manipulation and control of the iron, as if performed incorrectly it can create even more wrinkles. In this work we present a method for robotic ironing with an unmodified iron and ironing board and a full-body humanoid robot, inspired in the way people perform the ironing task. In this method, the robot performs an ironing action controlled in velocity with feedback from a force/torque sensor. This action is later analyzed by the robot using computer vision to determine if any wrinkle exists, either pre-existent or created by the ironing action. The 3D vision algorithm segments the garment surface to be ironed and computes a Wrinkleness Local Descriptor (WiLD) that determines the location of the wrinkles on the garment. Wrinkles are processed using computer vision techniques on an flattened image created from the WiLD descriptors computed in the prior stage, resulting, if present, in an optimal ironing path that reduces wrinkleness and avoids creating new wrinkles in garments when ironing. The experimental results show that using our method the humanoid robot is able to successfully iron several garments with results similar to the expected from a human performing the same task.