{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/rmpflow-a-computational-graph-for-automatic","title":"RMPflow: A Computational Graph for Automatic Motion Policy Generation","arxiv_id":"1811.07049","date":"2018-11-16","proceeding":null,"authors":["Ching-An Cheng","Mustafa Mukadam","Jan Issac","Stan Birchfield","Dieter Fox","Byron Boots","Nathan Ratliff"],"abstract":"We develop a novel policy synthesis algorithm, RMPflow, based on geometrically consistent transformations of Riemannian Motion Policies (RMPs). RMPs are a class of reactive motion policies designed to parameterize non-Euclidean behaviors as dynamical systems in intrinsically nonlinear task spaces. Given a set of RMPs designed for individual tasks, RMPflow can consistently combine these local policies to generate an expressive global policy, while simultaneously exploiting sparse structure for computational efficiency. We study the geometric properties of RMPflow and provide sufficient conditions for stability. Finally, we experimentally demonstrate that accounting for the geometry of task policies can simplify classically difficult problems, such as planning through clutter on high-DOF manipulation systems.","url_abs":"http://arxiv.org/abs/1811.07049v2","url_pdf":"http://arxiv.org/pdf/1811.07049v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"rmpflow-a-computational-graph-for-automatic","repo_url":"https://github.com/gtrll/multi-robot-rmpflow","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1811.07049","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1811.07049"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/gtrll/multi-robot-rmpflow","reach":null}],"summary":{"ran_violates":1,"ran_draft_wrong":3},"by_repo_kind":{"listed":{"samples":4,"ran":4,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":4,"samples":[{"code_sha256_prefix":"7304429d6d4ef5d0","entry":"at_position","repo":"gtrll/multi-robot-rmpflow","repo_kind":"listed","path":"formation_preservation.py","file_url":"https://github.com/gtrll/multi-robot-rmpflow/blob/HEAD/formation_preservation.py","link_basis":"first_harvest_node","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"7304429d6d4ef5d0"}},{"code_sha256_prefix":"20465da3de2b3319","entry":"create_mappings","repo":"gtrll/multi-robot-rmpflow","repo_kind":"listed","path":"multi_agent_rmp.py","file_url":"https://github.com/gtrll/multi-robot-rmpflow/blob/HEAD/multi_agent_rmp.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"20465da3de2b3319"}},{"code_sha256_prefix":"caff6e4db6641e65","entry":"create_mappings","repo":"gtrll/multi-robot-rmpflow","repo_kind":"listed","path":"formation_preservation.py","file_url":"https://github.com/gtrll/multi-robot-rmpflow/blob/HEAD/formation_preservation.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"caff6e4db6641e65"}},{"code_sha256_prefix":"56798b35fe9f5132","entry":"create_mappings_pair","repo":"gtrll/multi-robot-rmpflow","repo_kind":"listed","path":"formation_preservation.py","file_url":"https://github.com/gtrll/multi-robot-rmpflow/blob/HEAD/formation_preservation.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"56798b35fe9f5132"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}