A Generalized Reinforcement Learning Algorithm for Online 3D Bin-Packing

Understand

We propose a Deep Reinforcement Learning (Deep RL) algorithm for solving the online 3D bin packing problem for an arbitrary number of bins and any bin size.

• The focus is on producing decisions that can be physically implemented by a robotic loading arm, a laboratory prototype used for testing the concept.
• The problem considered in this paper is novel in two ways.
• First, unlike the traditional 3D bin packing problem, we assume that the entire set of objects to be packed is not known a priori.