Detecting and Picking of Folded Objects with a Multiple Sensor Integrated Robot Hand

Abstract

Robotic picking of folded objects such as books is required for picking various objects. As a folded object is easily unfolded, it is difficult to carry it stably and place it in a desired pose due to its dangling part. For overcoming this difficulty, we propose a trial-and-error picking system using our Suction Pinching Hand, which can push the dangling part up with pinch grasp until the object lifted with suction grasp is folded. That system utilizes proximity sensors on the hand to predict whether folding will succeed with a current hand pose and decide whether to retry with another pose. Also, proximity sensors, flex sensors and an air pressure sensor are used to deal with uncertainty of the image recognition, the hand hardware and suction grasp. We evaluate our proposed system with experiments of picking and placing folded objects. It is confirmed that our proposed system realizes picking with the ability of our Suction Pinching Hand to carry folded objects stably and place them in desired poses. It is also proved that our proposed system is robust against the uncertainty.