{"url":"/dataset/threedworld-transport-challenge","name":"ThreeDWorld Transport Challenge","full_name":null,"description_markdown":"ThreeDWorld Transport Challenge is a visually-guided and physics-driven task-and-motion planning benchmark. In this challenge, an embodied agent equipped with two 9-DOF articulated arms is spawned randomly in a simulated physical home environment. The agent is required to find a small set of objects scattered around the house, pick them up, and transport them to a desired final location. Several containers are positioned around the house that can be used as tools to assist with transporting objects efficiently. To complete the task, an embodied agent must plan a sequence of actions to change the state of a large number of objects in the face of realistic physical constraints. \r\n\r\nThis benchmark challenge has been built using the ThreeDWorld simulation: a virtual 3D environment where all objects respond to physics, and where can be controlled using fully physics-driven navigation and interaction API.","description_withheld":null,"homepage":"http://tdw-transport.csail.mit.edu/","introduced_date":"2021-03-25","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-threedworld-transport-challenge-a","title":"The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark for Physically Realistic Embodied AI","first_author":"Chuang Gan","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Environment","url":"/datasets/modality/environment"}],"tasks":[{"name":"Motion Planning","url":"/task/motion-planning","datasets_with_task":"/datasets/task/motion-planning"}],"languages":[],"variants":["ThreeDWorld Transport Challenge"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}