Household Clothing Set and Benchmarks for Characterising End-Effector Cloth Manipulation

The highly varied and deformable structure of clothing presents a challenging task in the area of robot manipulation. Recent literature has shown an increasing interest in this field, however limited information exists on the influence of end-effector selection, instead focusing on the perception, modelling, and methodology in handling fabrics. Here, we present a benchmark set of household clothing items, along with a framework for defining textile features in relation to how the objects can be grasped and manipulated. Alongside these, we present four example benchmarks for evaluating the performance of a robot end-effector in relation to the grasping and manipulation of common pieces of clothing: Edge drag accuracy, edge grasp resilience, grasp encapsulation, and grasp fold generation. We perform these benchmarks on several common robot end-effectors (Franka Emika (FE) Hand with standard and Fin Ray® style fingers (Flex), Robotiq 2F-140, and the Openhand Model T42) and present and discuss their respective performances. Results show that the Robotiq scored highest across most benchmarks, closely followed by the FE hand. The T42 showed excellent encapsulation of items, while the FE (Flex) was particularly successful picking up flat edges.