{"work":{"id":"1286fc26-002b-4688-a98f-c2e2e6163f9f","openalex_id":null,"doi":null,"arxiv_id":"2402.10329","raw_key":null,"title":"Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots","authors":null,"authors_text":"Cheng Chi, Zhenjia Xu, Chuer Pan, Eric Cousineau, Benjamin Burchfiel, Siyuan Feng","year":2024,"venue":"cs.RO","abstract":"We present Universal Manipulation Interface (UMI) -- a data collection and policy learning framework that allows direct skill transfer from in-the-wild human demonstrations to deployable robot policies. UMI employs hand-held grippers coupled with careful interface design to enable portable, low-cost, and information-rich data collection for challenging bimanual and dynamic manipulation demonstrations. To facilitate deployable policy learning, UMI incorporates a carefully designed policy interface with inference-time latency matching and a relative-trajectory action representation. The resulting learned policies are hardware-agnostic and deployable across multiple robot platforms. Equipped with these features, UMI framework unlocks new robot manipulation capabilities, allowing zero-shot generalizable dynamic, bimanual, precise, and long-horizon behaviors, by only changing the training data for each task. We demonstrate UMI's versatility and efficacy with comprehensive real-world experiments, where policies learned via UMI zero-shot generalize to novel environments and objects when trained on diverse human demonstrations. UMI's hardware and software system is open-sourced at https://umi-gripper.github.io.","external_url":"https://arxiv.org/abs/2402.10329","cited_by_count":null,"metadata_source":"pith","metadata_fetched_at":"2026-07-04T20:50:12.328550+00:00","pith_arxiv_id":"2402.10329","created_at":"2026-05-11T06:11:00.509795+00:00","updated_at":"2026-07-04T20:50:12.328550+00:00","title_quality_ok":true,"display_title":"Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots","render_title":"Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots"},"hub":{"state":{"work_id":"1286fc26-002b-4688-a98f-c2e2e6163f9f","tier":"hub","tier_reason":"10+ Pith inbound or 1,000+ external citations","pith_inbound_count":65,"external_cited_by_count":null,"distinct_field_count":3,"first_pith_cited_at":"2024-10-17T20:49:45+00:00","last_pith_cited_at":"2026-06-30T17:44:16+00:00","author_build_status":"not_needed","summary_status":"needed","contexts_status":"needed","graph_status":"needed","ask_index_status":"not_needed","reader_status":"not_needed","recognition_status":"not_needed","updated_at":"2026-08-22T19:49:28.329181+00:00","tier_text":"hub"},"tier":"hub","role_counts":[{"context_role":"background","n":15}],"polarity_counts":[{"context_polarity":"background","n":15}],"runs":{},"summary":{},"graph":{},"authors":[]}}