PackIt: A Virtual Environment for Geometric Planning
Not on the map. Why?
Abstract (arXiv)
The ability to jointly understand the geometry of objects and plan actions for manipulating them is crucial for intelligent agents. We refer to this ability as geometric planning. Recently, many interactive environments have been proposed to evaluate intelligent agents on various skills, however, none of them cater to the needs of geometric planning. We present PackIt, a virtual environment to evaluate and potentially learn the ability to do geometric planning, where an agent needs to take a sequence of actions to pack a set of objects into a box with limited space. We also construct a set of challenging packing tasks using an evolutionary algorithm. Further, we study various baselines for the task that include model-free learning-based and heuristic-based methods, as well as search-based optimization methods that assume access to the model of the environment. Code and data are available at https://github.com/princeton-vl/PackIt.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Jul 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 4; 2023: 3; 2024: 1; 2025: 2.
10 papers.
- 2023RVT: Robotic View Transformer for 3D Object Manipulationcited by 224
- 2024RVT-2: Learning Precise Manipulation from Few Demonstrationscited by 135
- 2022IFOR: Iterative Flow Minimization for Robotic Object Rearrangementcited by 42
- 2022Learning Physically Realizable Skills for Online Packing of General 3D Shapescited by 12
- 2022Planning Irregular Object Packing via Hierarchical Reinforcement Learningcited by 7
- 2023Learning based 2D Irregular Shape Packingcited by 5
- 2022Learning to Assemble Geometric Shapescited by 3
- 2023Machine Learning for the Multi-Dimensional Bin Packing Problem: Literature Review and Empirical Evaluationcited by 3
- 2025HERB: Human-augmented Efficient Reinforcement learning for Bin-packingcited by 0
- 2025One4Many-StablePacker: An Efficient Deep Reinforcement Learning Framework for the 3D Bin Packing Problemcited by 0
- 2025One4Many-StablePacker: An Efficient Deep Reinforcement Learning Framework for the 3D Bin Packing Problem11 Oct 2025
- 2025HERB: Human-augmented Efficient Reinforcement learning for Bin-packing23 Apr 2025
- 2024RVT-2: Learning Precise Manipulation from Few Demonstrations12 Jun 2024
- 2023Machine Learning for the Multi-Dimensional Bin Packing Problem: Literature Review and Empirical Evaluation13 Dec 2023
- 2023Learning based 2D Irregular Shape Packing19 Sep 2023
- 2023RVT: Robotic View Transformer for 3D Object Manipulation26 Jun 2023
- 2022Learning Physically Realizable Skills for Online Packing of General 3D Shapes5 Dec 2022
- 2022Planning Irregular Object Packing via Hierarchical Reinforcement Learning17 Nov 2022
- 2022Learning to Assemble Geometric Shapes24 May 2022
- 2022IFOR: Iterative Flow Minimization for Robotic Object Rearrangement1 Feb 2022