Jampacker: An Efficient and Reliable Robotic Bin Packing System for Cuboid Objects

Abstract

Bin packing using a robotic arm is an important problem in the context of Industry 4.0. In this work, we present a reliable and efficient bin packing system, called Jampacker. We propose a new offline 3D bin packing algorithm, called Jampack that achieves higher packing efficiency in comparison to the state-of-the-art algorithms. Jampack computes placement points, called internal corner points that tries to maximize the utilization of free spaces in-between objects, which are generally ignored by existing algorithms. Additionally, we introduce a fault recovery module (FRM) for the robotic manipulator that helps to achieve a more reliable and efficient packing in a physical container. The FRM module monitors the object placement by the robotic arm, calculates a fault score for the placement, adjusts the placement if required, and also learns & adjusts the offset for the placement procedure on-the-go. We show that this system achieves faster completion of the overall packing process.