{"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/vl-grasp-a-6-dof-interactive-grasp-policy-for","title":"VL-Grasp: a 6-Dof Interactive Grasp Policy for Language-Oriented Objects in Cluttered Indoor Scenes","arxiv_id":"2308.00640","date":"2023-08-01","proceeding":null,"authors":["Yuhao Lu","Yixuan Fan","Beixing Deng","Fangfu Liu","Yali Li","Shengjin Wang"],"abstract":"Robotic grasping faces new challenges in human-robot-interaction scenarios. We consider the task that the robot grasps a target object designated by human's language directives. The robot not only needs to locate a target based on vision-and-language information, but also needs to predict the reasonable grasp pose candidate at various views and postures. In this work, we propose a novel interactive grasp policy, named Visual-Lingual-Grasp (VL-Grasp), to grasp the target specified by human language. First, we build a new challenging visual grounding dataset to provide functional training data for robotic interactive perception in indoor environments. Second, we propose a 6-Dof interactive grasp policy combined with visual grounding and 6-Dof grasp pose detection to extend the universality of interactive grasping. Third, we design a grasp pose filter module to enhance the performance of the policy. Experiments demonstrate the effectiveness and extendibility of the VL-Grasp in real world. The VL-Grasp achieves a success rate of 72.5\\% in different indoor scenes. The code and dataset is available at https://github.com/luyh20/VL-Grasp.","url_abs":"https://arxiv.org/abs/2308.00640v1","url_pdf":"https://arxiv.org/pdf/2308.00640v1.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":"vl-grasp-a-6-dof-interactive-grasp-policy-for","repo_url":"https://github.com/luyh20/vl-grasp","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[{"slug":"roborefit","name":"RoboRefIt","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2308.00640","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.00640"}},"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/luyh20/vl-grasp","reach":{"status":"ok"}}],"summary":{"ran":5,"unverified":1},"by_repo_kind":{"official":{"samples":6,"ran":5,"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":6,"samples":[{"code_sha256_prefix":"01b942adf716c13a","entry":"PCA","repo":"luyh20/vl-grasp","repo_kind":"official","path":"GraspNet/FGC_generate/vector.py","file_url":"https://github.com/luyh20/vl-grasp/blob/HEAD/GraspNet/FGC_generate/vector.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"01b942adf716c13a"}},{"code_sha256_prefix":"5ed1d1afac90e705","entry":"cal_dist_nb","repo":"luyh20/vl-grasp","repo_kind":"official","path":"GraspNet/FGC_generate/score_gen_mp.py","file_url":"https://github.com/luyh20/vl-grasp/blob/HEAD/GraspNet/FGC_generate/score_gen_mp.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"5ed1d1afac90e705"}},{"code_sha256_prefix":"4d2a7e3195314349","entry":"load_grasp_label","repo":"luyh20/vl-grasp","repo_kind":"official","path":"GraspNet/FGC_generate/score_gen_mp.py","file_url":"https://github.com/luyh20/vl-grasp/blob/HEAD/GraspNet/FGC_generate/score_gen_mp.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"4d2a7e3195314349"}},{"code_sha256_prefix":"c7ec7f86d76dee0d","entry":"load_grasp_labels","repo":"luyh20/vl-grasp","repo_kind":"official","path":"GraspNet/FGC_generate/rnn_neighbor.py","file_url":"https://github.com/luyh20/vl-grasp/blob/HEAD/GraspNet/FGC_generate/rnn_neighbor.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"c7ec7f86d76dee0d"}},{"code_sha256_prefix":"706a7b7002bdfbc4","entry":"orient_normals","repo":"luyh20/vl-grasp","repo_kind":"official","path":"GraspNet/FGC_generate/vector.py","file_url":"https://github.com/luyh20/vl-grasp/blob/HEAD/GraspNet/FGC_generate/vector.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"706a7b7002bdfbc4"}},{"code_sha256_prefix":"cbe418c55b3063eb","entry":"load_grasp_labels","repo":"luyh20/vl-grasp","repo_kind":"official","path":"GraspNet/dataset/graspnet_dataset.py","file_url":"https://github.com/luyh20/vl-grasp/blob/HEAD/GraspNet/dataset/graspnet_dataset.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"cbe418c55b3063eb"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}