Vision-Sensorless Bin-Picking System Using Compliant Fingers with Proximity Sensors

In this study, we propose an exploratory bin- picking system with less installation space than a human worker. The robot adjusts the arm tip position based on quasi- static deformations of the compliant fingers. It also estimates the number of grasped objects by frequency analysis of the dynamic deformations. The proposed system has two advantages because it performs bin-picking using only deformations. The first is that all control can be performed on small on-board computer board (Raspberry Pi 4B). Second, there is no need to place and mount a 3D vision sensor. The control system can also be reconfigured without any learning time when shape of the picked objects changes. In bin-picking experiments, we confirmed that our system achieved a picking success rate of over 85 % and a bin picking tact time within 30 s for two types of metal bolts.