{"id":74,"date":"2026-05-08T03:11:37","date_gmt":"2026-05-08T03:11:37","guid":{"rendered":"https:\/\/mscvprojects.ri.cmu.edu\/2026teamf18\/?page_id=74"},"modified":"2026-08-26T19:10:29","modified_gmt":"2026-08-26T19:10:29","slug":"introduction","status":"publish","type":"page","link":"https:\/\/mscvprojects.ri.cmu.edu\/2026teamf18\/","title":{"rendered":"Introduction"},"content":{"rendered":"\n

Dexterous manipulation is one of the most challenging problems in robotics.<\/strong> Compared with parallel-jaw grippers, multi-fingered dexterous hands introduce higher degrees of freedom, richer contact patterns, and more complex hand-object interaction geometry. A successful policy must reason about how the hand approaches the object, forms stable contact, and manipulates the object toward the desired goal.<\/p>\n\n\n\n

This project explores 3D goal conditioning for dexterous manipulation. <\/strong>We use a hierarchical framework in which a high-level policy predicts a future dexterous hand configuration, and a low-level policy executes actions conditioned on the predicted goal. Our main focus is designing compact but expressive 3D goal representations that capture finger placement, palm position, and hand-object contact geometry.<\/p>\n\n\n\n

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<\/p>\n","protected":false},"excerpt":{"rendered":"

Dexterous manipulation is one of the most challenging problems in robotics. Compared with parallel-jaw grippers, multi-fingered dexterous hands introduce higher degrees of freedom, richer contact patterns, and more complex hand-object interaction geometry. A successful policy must reason about how the hand approaches the object, forms stable contact, and manipulates the object toward the desired goal. … <\/p>\n

Continue reading “Introduction”<\/span><\/a><\/p>\n","protected":false},"author":306,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-74","page","type-page","status-publish","hentry"],"yoast_head":"\nIntroduction - Goal Conditioning for 3D Dexterous Manipulation Tasks<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/mscvprojects.ri.cmu.edu\/2026teamf18\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Introduction - Goal Conditioning for 3D Dexterous Manipulation Tasks\" \/>\n<meta property=\"og:description\" content=\"Dexterous manipulation is one of the most challenging problems in robotics. 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