PackIt: A Virtual Environment for Geometric Planning
Ankit Goyal, Jia Deng
Abstract
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 modelfree 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 .
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Install the CLIlune papers fulltext 2d92b1df-9cbe-45e4-a834-ecc875798297Cited by top-tier papers2
- Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3DAnkit Goyal, Kaiyu Yang, Dawei Yang, Jia DengNeurIPS 2020 · 50 citations
- IFOR: Iterative Flow Minimization for Robotic Object RearrangementAnkit Goyal, Arsalan Mousavian, Chris Paxton, Yu-Wei Chao et al.CVPR 2022 · 34 citations
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