Randomly stored material in bins is the most cost-effective and flexible supply form, especially when using it in material transfer automation. In these cases, the process of gripping single parts out of a bin is usually carried out by utilizing bin-picking technology that combines vision sensors, grippers and software for image processing and process planning to enable a robot to execute the gripping process automatically. Bin-picking technology has become more reliable in the last few years and as a result is recently available as a variety of products. However, there are still ongoing challenges in bin-picking, as objects with challenging surfaces cannot be processed in a reliable manner due to inadequate optical sensor input. Furthermore, the position of the gripped object cannot be monitored and controlled appropriately.
The experiment pickit will enable a commercially available vision based bin-picking system to handle a variety of objects. A tactile gripper will be introduced as an add-on to a commercial off-the-shelf bin-picking solution to overcome limitations of current bin-picking systems. This favourable combination of completely different technologies can achieve a step change in the domain of manufacturing with bin-picking applications.