Evaluating robot bin-picking performance based on Box and Blocks Test

The rise of e-commerce, which demands solutions for small order sizes, large product assortment, short delivery times, and variable order quantity has created a need for more advanced warehousing and order-picking systems. The advancements in collaborative robotics have made it possible to automate intralogistics processes, especially the order-picking systems. If the items to be order-picked are stored in small containers, called bins, the process is known as bin-picking. The processes of bin-picking are still mainly manual due to the adaptability, dexterity, and pace of human hands. However, with the emerging technologies, the gap between human and robot dexterity is getting thinner. The integrators of robotic technologies are therefore faced with the challenge of choosing an appropriate robotic system for bin-picking. There is a lack of standardized procedures, which are designed to process such decisions easier. In our research paper, we propose an improved robotic version of the Box and Blocks Test (BBT), which provides a quick evaluation of a complete robotic bin-picking system. Using our improved robot-adapted BBT protocol, we evaluate a sample robotic bin-picking system, consisting of a collaborative robot, a 3D vision system and three types of robotic grippers, comparing the bin-picking performance of each configuration.