mlsanityData to 14 Oct 2026

Diffusion Reinforcement Learning Based Online 3D Bin Packing Spatial Strategy Optimization

arXiv 2604.10953 ↗First posted 13 Apr 2026cs.ROcited by 0

On the map: Deep reinforcement learning methods → RL for robot navigation and UAV control

Abstract (arXiv)

The online 3D bin packing problem is important in logistics, warehousing and intelligent manufacturing, with solutions shifting to deep reinforcement learning (DRL) which faces challenges like low sample efficiency. This paper proposes a diffusion reinforcement learning-based algorithm, using a Markov decision chain for packing modeling, height map-based state representation and a diffusion model-based actor network. Experiments show it significantly improves the average number of packed items compared to state-of-the-art DRL methods, with excellent application potential in complex online scenarios.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in RL for robot navigation and UAV control, one of 15 directions in Deep reinforcement learning methods. Builds on 8 of its 30 references that are in the map. First posted on arXiv 13 Apr 2026.

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8 of 30 references.

References · 8

  1. 2017Attention Is All You Needcited by 60,361
  2. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  3. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
  4. 2018Reinforcement Learning for Solving the Vehicle Routing Problemcited by 333
  5. 2020Online 3D Bin Packing with Constrained Deep Reinforcement Learningcited by 41
  6. 2018Ranked Reward: Enabling Self-Play Reinforcement Learning for Combinatorial Optimizationcited by 27
  7. 2018Stable bin packing of non-convex 3D objects with a robot manipulatorcited by 21
  8. 2023Adjustable Robust Reinforcement Learning for Online 3D Bin Packingcited by 10

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  1. 2024An Efficient Deep Reinforcement Learning Model for Online 3D Bin Packing Combining Object Rearrangement and Stable Placement
  2. 2024Bin Packing Optimization via Deep Reinforcement Learning
  3. 2025Deliberate Planning of 3D Bin Packing on Packing Configuration Trees
  4. 2025One4Many-StablePacker: An Efficient Deep Reinforcement Learning Framework for the 3D Bin Packing Problem
  5. 2024GOPT: Generalizable Online 3D Bin Packing via Transformer-based Deep Reinforcement Learning
  6. 2026Effective Online 3D Bin Packing with Lookahead Parcels Using Monte Carlo Tree Search
  7. 2026Deep Reinforcement Learning on Item-Compatibility Graphs for One-Dimensional Bin Packing
  8. 2025A Hierarchical Bin Packing Framework with Dual Manipulators via Heuristic Search and Deep Reinforcement Learning